ARTICLE
Shared heritability and functional enrichment
across six solid cancers
Xia Jiang et al.#
Quantifying the genetic correlation between cancers can provide important insights into the
mechanisms driving cancer etiology. Using genome-wide association study summary sta-
tistics across six cancer types based on a total of 296,215 cases and 301,319 controls of
European ancestry, here we estimate the pair-wise genetic correlations between breast,
colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other
diseases. We observed statistically significant genetic correlations between lung and head/
neck cancer (rg= 0.57, p= 4.6 × 10−8), breast and ovarian cancer (rg= 0.24, p= 7 × 10−5),
breast and lung cancer (rg= 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg= 0.15,
p= 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-
cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional
enrichment analysis revealed a significant excess contribution of conserved and regulatory
regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability sug-
gests that solid tumors arising across tissues share in part a common germline genetic basis.
Corrected: Publisher correction
https://doi.org/10.1038/s41467-018-08054-4 OPEN
Correspondence and requests for materials should be addressed to X.J. (email: xiajiang@hsph.harvard.edu) or to P.K. (email: pkraft@hsph.harvard.edu)
or to S.Löm. (email: saralind@uw.edu). #A full list of authors and their affiliations appears at the end of the paper.
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 1
12
34
56
78
9
0
()
:,;
Inherited genetic variation plays an important role in canceretiology. Large twin studies have demonstrated an excessfamilial risk for cancer sites including, but not limited to,
breast, colorectal, head/neck, lung, ovary, and prostate with
heritability estimates ranging between 9% (head/neck) to 57%
(prostate)1–3. Data from nation-wide and multi-generation
registries further show that elevated cancer risks go beyond
nuclear families and isolated types, as family history of a specific
cancer can increase risk for other cancers4–6. Additional evidence
for a shared genetic component have been demonstrated by
cross-cancer genome-wide association study (GWAS) meta-ana-
lyses, which set out to identify genetic variants associated with
more than one cancer type. Fehringer et al. studied breast, col-
orectal, lung, ovarian, and prostate cancer, and identified a novel
locus at 1q22 associated with both breast and lung cancer7. Kar
et al. focused on three hormone-related cancers (breast, ovarian,
and prostate), and identified seven novel susceptibility loci shared
by at least two cancers8.
Previous attempts to estimate the genetic correlation across
cancers using GWAS data9–12 have mostly relied on restricted
maximum likelihood (REML) implemented in GCTA (genome-
wide complex trait analysis)13 and individual-level genotype data.
However, these studies have had limited sample sizes, yielding
inconclusive results. Sampson et al. quantified genetic correlations
across 13 cancers in European ancestry populations and identified
four cancer pairs with nominally significant genetic correlations
(bladder–lung, testis–kidney, lymphoma–osteosarcoma, and
lymphoma–leukemia)9. They did not observe any significant
genetic correlations across common solid tumors including can-
cers of the breast, lung and prostate9. REML becomes computa-
tionally challenging for large sample sizes and is sensitive to
technical artifacts. LD score regression (LDSC)14,15 overcomes
these issues by leveraging the relationship between association
statistics and LD patterns across the genome. We recently used
cross-trait LDSC to quantify genetic correlations across six cancers
based on a subset of the data included here and found moderate
correlations between colorectal and pancreatic cancer, as well as
between lung and colorectal cancer16. However, the average
sample size was only 11,210 cases and 13,961 controls per cancer,
resulting in imprecise estimates with wide confidence intervals.
In addition to the development of novel analytical methods
tailored to genomic data, several high-quality functional anno-
tations have recently been released into the public domain
through large-scale efforts. For example, the ENCODE con-
sortium has built a comprehensive and informative parts list of
functional elements in the human genome (http://www.nature.
com/encode/#/threads), which allows for the analysis of compo-
nents of SNP-heritability to unravel the functional architecture of
complex traits.
Here, we use summary statistics from the largest-to-date Eur-
opean ancestry GWAS of breast, colorectal, head/neck, lung,
ovary, and prostate cancer with an average sample size of 49,369
cases and 50,219 controls per cancer, to quantify genetic corre-
lations between cancers and their subtypes. We also use GWAS
summary statistics for 38 non-cancer traits (average N= 113,808
per trait), to quantify the genetic correlations between the six
cancers and other diseases. Furthermore, we assessed the pro-
portion of cancer heritability attributable to specific functional
categories, with the goal of identifying functional elements that
are enriched for SNP-heritability.
Our comprehensive analysis identifies statistically significant
genetic correlations between lung and head/neck cancer, breast
and ovarian cancer, breast and lung cancer, and breast and col-
orectal cancer. We also find multiple cancers to be genetically
correlated with non-cancer traits including smoking, psychiatric
diseases, and metabolic traits. Functional enrichment analysis
reveals a significant contribution of conserved and regulatory
regions to cancer heritability. Our results suggest that solid
tumors arising across tissues share in part a common germline
genetic basis.
Results
Heritability estimates across cancers. We first estimated cancer-
specific heritability causally explained by common SNPs (h2g)
using LDSC (note that this quantity is slightly different from the
h2g as defined in Yang et al.
17 which estimates the heritability due
to genotyped and imputed SNPs) (see Methods). Estimates of h2g
on the liability scale ranged from 0.03 (ovarian) to 0.25 (prostate)
(Supplementary Table 1). After removing genome-wide sig-
nificant (p < 5 × 10−8) loci, defined as all SNPs within 500 kb of
the most significant SNP in a given region (Supplementary
Data 1), we observed an ~50% decrease in SNP-heritability for
prostate and breast cancer, and ~20% decrease for lung, ovarian,
and colorectal cancer, despite the fact that we were only excluding
1% (colorectal cancer) to 5% (breast cancer) of the genome. In
contrast, the SNP-heritability for head/neck cancer was not
affected by removing genome-wide significant loci (Fig. 1a). For
most of the cancers, the GWAS significant loci for that particular
cancer explained most of the heritability. For some cancers,
however, significant GWAS loci of other cancers also explained a
non-trivial part of its heritability. For example, the significant
breast cancer GWAS loci explained 10%, 15%, and 22% herit-
ability of colorectal, ovarian and prostate cancer, respectively; the
significant colorectal cancer GWAS loci explained 11% herit-
ability of prostate cancer; the significant lung cancer GWAS loci
explained 10% heritability of head/neck cancer; and the sig-
nificant prostate cancer GWAS loci explained 11 and 15% her-
itability of breast and ovarian cancer, respectively (Supplementary
Table 2). Comparing the liability-scale SNP-heritability to cor-
responding estimates from twin studies suggests that common
SNPs can almost entirely explain the classical heritability of head/
neck cancer, whereas for other cancers, only 30–40% of herit-
ability can be explained (Fig. 1b).
Genetic correlations between cancers. We then estimated the
genetic correlation between cancers using cross-trait LDSC (see
Methods). After adjusting for the number of tests (p < 0.05/15=
0.003), we found multiple significant genetic correlations Fig. 1c
and Supplementary Table 1), with the strongest result observed
for lung and head/neck cancer (rg= 0.57, se= 0.10). In addition,
colorectal and lung cancer (rg= 0.28, se= 0.06), breast and
ovarian cancer (rg= 0.24, se=0.06), breast and lung cancer (rg=
0.18, se= 0.04), and breast and colorectal cancer (rg= 0.15, se=
0.04) showed statistically significant genetic correlations. We also
observed nominally significant genetic correlations (p < 0.05)
between lung and ovarian cancer (rg= 0.16, se= 0.08), prostate
cancer and head/neck (rg= 0.15, se= 0.08), colorectal (rg= 0.11,
se= 0.05), and breast cancer (rg= 0.07, se= 0.03) (Fig. 1c). Some
cancer pairs showed minimal correlations with estimates close to
0 (ovarian and prostate: rg= 0.02, se= 0.07; lung and prostate:
rg=−0.03, se= 0.04; breast and head/neck: rg= 0.03, se= 0.06).
We further calculated the cross-cancer genetic correlation based
on data after excluding the GWAS significant regions of each
cancer. The estimates were mostly consistent with the results
calculated based on all SNPs.
We conducted subtype-specific analysis for breast, lung,
ovarian, and prostate cancer (Supplementary Table 1). Estrogen
receptor positive (ER+) and negative (ER−) breast cancer
showed a genetic correlation of 0.60 (se= 0.03), indicating that
the genetic contributions to these two subtypes are in part
distinct. The genetic correlation between the two common lung
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
2 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
cancer subtypes adenocarcinoma and squamous cell carcinoma
was similarly 0.58 (se= 0.10). Further, we observed a significantly
larger genetic correlation of lung cancer with ER− (rg= 0.29,
se= 0.06) than with ER+ breast cancer (rg= 0.13, se= 0.04)
(pdifference= 0.002). This also held true for lung squamous cell
carcinoma, which showed statistically stronger genetic correlation
with ER− (rg= 0.33, se= 0.08) than with ER+ breast cancer
(rg= 0.11, se= 0.05) (pdifference= 0.0019). We observed no other
statistically significant differential genetic correlations across
subtypes (all pdifference > 0.1).
We then estimated local genetic correlations between cancers
using ρ-HESS, dividing the genome into 1703 regions (see
Methods) (Fig. 2 and Supplementary Fig. 1). We found that
although the genome-wide genetic correlation between breast
and prostate cancer was modest (rg= 0.07), chr10:123M
(10q26.13, p= 1.0 × 10−7) and chr9:20–22 M (9p21, p= 1.0 ×
10−6), two previously known pleiotropic regions18, showed
significant genetic correlations (rg=−0.00098 and rg=
0.00046). Similarly, although the genome-wide genetic correla-
tion between lung and prostate cancer was negligible (rg=
−0.03), two previously identified pleiotropic regions
(chr6:30–31 M or 6p21.33, p= 5.7 × 10−7 and chr20:62M or
20q13.33, p= 2.8 × 10−6) exhibited significant local genetic
correlations (rg=−0.00060 and rg= 0.00067). Overall, local
genetic correlation analysis reinforced shared effects for 44%
(31/71) of previously reported pleiotropic cancer regions
(Supplementary Data 2). It also identified novel pleiotropic
signals. For example, the breast and prostate cancer pleiotropic
region at 2q33.1 showed significant local genetic correlation
between breast and ovarian cancer (p= 2.3 × 10−6). Addition-
ally, 6p21.32, a region indicated for head/neck and prostate
cancer, showed highly significant local genetic correlation for
head/neck and lung cancer (p= 8.6 × 10−8).
Genetic correlations between cancer and other traits. Sig-
nificant genetic correlations (p < 0.05/228= 0.0002) between the
six cancers and 38 non-cancer traits reflected several known
associations (Fig. 3 and Supplementary Data 3). We observed a
strong genetic correlation between smoking and lung cancer
(rg= 0.56, se= 0.06), and similarly for head/neck cancer (rg=
0.47, se= 0.08), both cancers having smoking as its primary risk
factor19,20. Educational attainment was negatively genetically
correlated with colorectal (rg=−0.17, se= 0.04), head/neck
(rg=−0.42, se= 0.07), and lung cancer (rg=−0.39, se=0.04) (all
p < 5 × 10−6). Body mass index (BMI) showed a positive genetic
correlation with colorectal cancer (rg= 0.15, se= 0.03) and also
suggestive but weak negative correlations with prostate (rg=
−0.07, se= 0.03) and breast cancer (rg=−0.06, se= 0.03). Lung
cancer showed a negative genetic correlation with lung function
(rg=−0.15, se= 0.04) and age at natural menopause (rg=−0.25,
se= 0.05), and moderate positive genetic correlations with
depressive symptoms (rg= 0.25, se=0.06) and waist-to-hip ratio
(rg= 0.16, se= 0.04). Breast cancer showed a positive genetic
correlation with schizophrenia (rg= 0.14, se= 0.03).
We did not find evidence of genetic correlations between cancer
and several previously suggested risk factors21–23 including
cardiovascular traits (coronary artery disease, hypertension, and
blood pressure) or sleep characteristics (chronotype, duration, and
insomnia). Further, we did not observe genetic correlations
between cancer and circulating lipids (HDL, LDL, and triglycer-
ides) or type 2 diabetes-related traits except a significant
negative correlation between HDL and lung cancer
(rg=−0.14, se= 0.04). We observed no significant genetic
correlation between breast cancer and age at menarche
(rg=−0.03, se= 0.03) or age at natural menopause (rg=−0.01,
se= 0.03). We also did not observe notable genetic correlations
between cancer and autoimmune inflammatory diseases or height.
0.25
All SNPs vs. excluding top hits (± 500 kbp)
LDSC estimates vs. twin study estimates
Cross heritability among the six cancersh2: based on SNPs after excluding top hits ± 500 kbp
h2: top hits ± 500 kbp
a
b
c
0.20
45%
20% 0%
25.3%
24.2%
53.9% Prostate 1
0.0241
1
1
1
1 0.15 0.029
–0.067 –0.061
0.18 0.24
0.11
0.15
0.072
0.095
1.0
0.5
–1.0
–0.5
0.0
0.16 –0.026
0.28
0.57
**
**
**** **
*
*
*
*
Pro
sta
te
Ovarian
Ov
ar
ian
Lung
Lu
ng
0.15
0.10
0.05
0.00
1.0
0.8
0.6
0.4
0.2
0.0
LD
SC
 h
er
ita
bi
lity
LD
SC
 h
er
ita
bi
lity
Breast
Breast
Bre
as
t
Colorectal
Colorectal
Co
lor
ect
al
Headneck Headneck
He
ad
ne
ck
Lung Ovarian Prostate
Breast Colorectal Headneck Lung Ovarian Prostate
1.0
0.8
0.6
0.4
0.2
0.0 Tw
in
 s
tu
dy
 h
er
ita
bi
lity
Fig. 1 Estimates of SNP-heritability (h2g) and cross-cancer heritability (rg) for the six cancer types. SNP-heritability and cross-cancer heritability are
calculated based on HapMap3 SNPs using LD score regression (LDSC). a The solid bar represents overall SNP h2g on the liability scale, calculated based on
all HapMap3 SNPs. The dark green bar represents h2g calculated based on non-significant SNPs—the remaining SNPs after excluding genome-wide
significant hits (p < 5 × 10−8) ± 500 kb. The black bar with density texture indicates proportion of h2g (as reflected by the percentages displayed on top of
each bar) that could be explained by top hits ±500 kb surrounded areas. The orange error bars represent 95% confidence intervals. b The solid blue bar
represents overall SNP h2g in liability scale (no SNP exclusion), with black error bars indicating 95% confidence intervals. The red short lines correspond to
classical estimates of h2 measured in a twin study of Scandinavian countries (Mucci et al.2). c Genetic correlations between cancers. Estimates withstood
Bonferroni corrections (p < 0.05/15) are marked with double asterisk (**), and nominal significant results (p < 0.05) are marked with single asterisk (*)
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 3
Breast_prostate Lung_prostate
O
bs
er
ve
d 
–l
og
10
 (
p)
Expected –log10 (p ) Expected –log10 (p )
O
bs
er
ve
d 
–l
og
10
 (
p)
8
10:123231465–123900544 6:30798168–31571217
20:62190180–62965162
6:26791233–28017818
9:20463534–22206558
11:68005825–69516129
6:28017819–28917607
1:203334734–204681067
2:214014282–215573794
6:25684587–26791232
1:154770403–156336132
7:1353067–2062397
6:28917608–29737970
3:87409732–88298372
14:35859593–38667724
3:139954597–141339096
6:28017819–28917607
11:112459488–114257727
1:44969183–46899500
8
6
64
4
2
2
0
0
6
6
4
4
2
2
0
0
Local genetic covariance
0.0007
0.0003
0.0000
–0.0003
–0.0007
–0.0005
–0.0003
–0.0008
0.002
0.001
0
0.001
0.000
0.002
0.0000
0.0008
0.0005
0.0003
–0.0010
0.002
0.001
0.000
0.002
0.001
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
1 2 3 4 5 6 7
Local SNP-heritability
Local SNP-heritability
Local genetic covariance
8 9
chr9:20463534–22206558
chr10:123231465-123900544
chr6:26791233–28017818
chr20:62190180–62965162
chr6:30798168–31571217
10 11 12 13 14 15 16 17 18 19 20 21 22
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
B
re
as
t
B
re
as
t &
 p
ro
st
at
e
Lu
ng
 &
 p
ro
st
at
e
P
ro
st
at
e
P
ro
st
at
e
Lu
ng
a
c
b
d
Fig. 2 Local genetic correlation between breast, lung and prostate cancer. The region-specific p-values for the local genetic covariance for breast and
prostate cancer are shown in a, and for lung and prostate cancer in b. Each dot presents a specific genomic region. In the QQ plots, red color indicates
significance after multiple corrections (p < 0.05/1703 regions compared), and blue color indicates nominal significance (p < 0.05/15 pairs of cancers
compared). Manhattan-style plots showing the estimates of local genetic covariance for breast and prostate cancer (c), and for lung and prostate cancer
(d). Although breast and prostate cancer only show modest genome-wide genetic correlation, two loci exhibit significant local genetic covariance. Similarly,
albeit the negligible overall genetic correlation for lung and prostate cancer, three loci present significant local genetic covariance. In the Manhattan plots,
red color indicates even number chromosomes and blue color indicates odd number chromosomes
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
4 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
Subtype analysis revealed that smoking and educational
attainment showed genetic correlations with all lung cancer
subtypes (Supplementary Data 3). Educational attainment, forced
vital capacity and depressive symptoms showed genetic correla-
tions with ER− but not ER+ breast cancer, whilst the observed
genetic correlation between schizophrenia and breast cancer was
limited to ER+ disease, and the genetic correlation between
depressive symptoms and lung cancer was observed only for lung
squamous cell carcinoma.
We further assessed the support for mediated or pleiotropic
causal models for non-cancer traits and cancer using the
correlation between trait-specific effect sizes of genome-wide
significant SNPs for pairs of phenotypes. We detected four
putative directional genetic correlations (defined as p < 0.05 from
a likelihood ratio (LR) comparing the best non-causal model to
the best causal model) (Fig. 4), where SNPs associated with the
non-cancer trait showed correlated effect estimates with cancer
but the reverse was not true (circulating HDL concentrations and
breast cancer, LRnon-causal vs. causal= 0.04, schizophrenia and
breast cancer, LRnon-causal vs. causal= 0.003, age at natural
menopause and breast cancer, LRnon-causal vs. causal= 0.04, and
lupus and prostate cancer, LRnon-causal vs. causal= 0.0006).
Functional enrichment analysis of cancer heritability. Finally,
we partitioned SNP-heritability of each cancer by using 24
genomic functional annotations (the baseline-LD model descri-
bed in Gazal et al.24) and 220 cell-type-specific histone mark
annotations (the cell-type-specific model described in Finucane
et al.14). Meta-analysis across the six cancers revealed statistically
significant enrichments for multiple functional categories.
We observed the highest enrichment for conserved regions
(Table 1, Supplementary Table 3) which overlapped with
only 2.6% of SNPs but explained 25% of cancer SNP-heritability
Insomnia
–0.17
0.47
0.14
0.09
0.11
0.14
0.25
0.13
0.11
–0.17
–0.14
0.16
0.15
0.38 0.19
1.0
0.5
0.0
–0.5
–1.0
–0.07
*P < 0.01
**P < 0.05/228
Bonferroni correction
0.18
0.56
** **
**
****
**
** *
*
*
**
**
** *
* *
*
*
**
**
*
**
–0.42 –0.39
–0.25
–0.15
–0.19
Common phenotypes
Psychiatric traits
Metabolism/cardiovascular traits
Systolic blood pressure
Diastolic blood pressure
a
c d
b
Hypertension
Coronary artery disease
Type 2 diabetes
Fasting glucose
Waist hip ratio adjusted for BMI
Body mass index
Triglycerides
Low-density lipoprotein
High-density lipoprotein
Ulcerative colitis
Autoimmune/inflammatory traits
Rheumatoid arthritis
Primary biliary cirrhosis
Lupus
Inflammatory bowel disease
Eczema
Crohns disease
Celiac disease
Asthma
Sleep duration
Sleep chronotype
Years of education
Age at menopause
Age at menarche
Heel T score
Smoking status
Forced vital capacity
FEV1/FVC ratio
Height
Subjective well being
Schizophrenia
Neuroticism
Depressive symptoms
Bipolar disorder
Autism
Anorexia
Br
ea
st
Co
lor
ec
ta
l
He
ad
ne
ck
Lu
ng
Ov
ar
ian
Pr
os
ta
te
Br
ea
st
Co
lor
ec
ta
l
He
ad
ne
ck
Lu
ng
Ov
ar
ian
Pr
os
ta
te
Br
ea
st
Co
lor
ec
ta
l
He
ad
ne
ck
Lu
ng
Ov
ar
ian
Pr
os
ta
te
Br
ea
st
Co
lor
ec
ta
l
He
ad
ne
ck
Lu
ng
Ov
ar
ian
Pr
os
ta
te
Fig. 3 Cross-trait genetic correlation (rg) analysis between cancers and non-cancer traits. The traits were divided into four categories: a Common
phenotypes, b Metabolic or cardiovascular related traits, c Psychiatric traits, d Autoimmune inflammatory diseases. Pair-wise genetic correlations
withstood Bonferroni corrections (228 tests) are marked with double asterisk (**), with estimates of correlation shown in the cells. Pair-wise genetic
correlations with significance at p < 0.01 are marked with a single asterisk (*). The color of cells represents the magnitude of correlation
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 5
(9.8-fold enrichment, p= 2.3 × 10−5). Transcription factor bind-
ing sites showed the second highest enrichment (4.0-fold, 13% of
SNPs explaining 40% of SNP-heritability, p= 1.4 × 10−7). Fur-
ther, super-enhancers (groups of putative enhancers in close
genomic proximity with unusually high levels of mediator bind-
ing) showed a significant 2.6-fold enrichment (p= 2.0 × 10−20).
Additional enhancers, including regular enhancers (3.2-fold),
weak enhancers (3.1-fold) and FANTOM5 enhancers (3.1-fold),
presented similar enrichments but were not statistically sig-
nificant. In addition, multiple histone modifications of epigenetic
markers H3K9ac, H3K4me3, and H3K27ac, were all significantly
enriched for cancer heritability. Repressed regions exhibited
depletion (0.34-fold, p= 1.2 × 10−6). Enrichment analysis of
functional categories for each cancer and cancer subtype are
shown in Fig. 5 and Supplementary Table 4.
Overall, cell-type-specific analysis of histone marks identified
significant enrichments specific to individual cancers (Supple-
mentary Fig. 2). For breast cancer, 3 out of 8 statistically
significant tissues were adipose nuclei (H3K4me1, H3K9ac) and
breast myoepithelial (H3K4me1) cells. For colorectal cancer, 15
out of the 18 statistically significant enrichments were observed in
either colon or rectal tissues (colon/rectal mucosa, duodenum
mucosa, small/large intestine, and colon smooth muscle). We
observed no significant enrichments for head/neck, lung, and
ovarian cancer, but we noted that for both lung (9 out of 10) and
ovarian cancer (6 out of 10), the most enriched cell types were
immune cells; while in head/neck cancer, 6 out of 10 most highly
enriched cell types belonged to CNS (Supplementary Fig. 3,
Supplementary Data 4). Cell-type-specific analysis for cancer
subtypes are shown in Supplementary Data 5. Comparing
0.2
Directional correlation analysis
Positive
effect
Negative
effect
Breast
cancer
Breast
cancer
Breast
cancer
Prostate
cancer
Schizophrenia
Age at
menopause
Systemic
lupus
HDL
a
b
c
d
0.1
0.0
–0.1
0.2
0.2
0.2
0.3
0.3
0.2
–0.06
–0.02
0.06
HDL ascertainment
Schizophrenia ascertainment
Menopause age ascertainment
Systemic lupus ascertainment
Breast cancer ascertainment
Breast cancer ascertainment
Breast cancer ascertainment
Prostate cancer ascertainment
0.02
0.2
0.2
0.4
0.8
0.6
1.0
0.1
1.2
–0.2
–0.1
–0.2
–0.3
–0.4
0.1
0.1
0.1
0.1
0.0
0.0
0.0
0.5
1.0
–1.0
–0.5
–0.5
0.0
0.0
0.0
0.0
0.0
–0.1
–0.1
–0.1
–0.1
–0.2
–0.2
0.2
0.2
0.3
0.4
0.10.0
0.0
–0.1–0.2
–0.2
–0.2
–0.3
–0.08 –0.06 –0.04
–0.05 0.00 0.05
0.05
0.5
0.10
–0.05
–0.05
0.00
0.00
0.05
–0.02 0.00 0.02 0.04 0.06
Fig. 4 Putative directional relationships between cancers and traits. For each cancer–trait pair identified as candidates to be related in a causal manner, the
plots show trait-specific effect sizes (beta coefficients) of the included genetic variants. Gray lines represent the relevant standard errors. a HDL and breast
cancer. Trait-specific effect sizes for HDL and breast cancer are shown for SNPs associated with HDL levels (left) and breast cancer (right).
b Schizophrenia and breast cancer. Trait-specific effect sizes for schizophrenia and breast cancer are shown for SNPs associated with schizophrenia (left)
and breast cancer (right). c Age at natural menopause and breast cancer. Trait-specific effect sizes for age at natural menopause and breast cancer are
shown for SNPs associated with age at natural menopause (left) and breast cancer (right). d Lupus and prostate cancer. Trait-specific effect sizes for lupus
and prostate cancer are shown for SNPs associated with lupus (left) and prostate cancer (right)
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
6 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
cell-type-specific enrichment for cancers to the additional 38
non-cancer traits revealed notably differential clustering patterns
(Supplementary Fig. 4). Breast, colorectal, and prostate cancer
showed enrichment mostly for adipose and epithelial tissues, in
contrast to autoimmune diseases (enriched for immune/hemato-
poietic cells) or psychiatric disorders (enriched for brain tissues).
Discussion
We performed a comprehensive analysis quantifying the herit-
ability and genetic correlation of six cancers, leveraging summary
statistics from the largest cancer GWAS conducted to date. Our
study demonstrates shared genetic components across multiple
cancer types. These results contrast with a prior study conducted
by Sampson et al. which reported an overall negligible genetic
correlation among common solid tumors9. Our results are,
however, in line with a recent study,16 which analyzed a subset of
the data included here, and identified a significant genetic cor-
relation between lung and colorectal cancer.
Our data support, and for the first time quantify, the strong
genetic correlation (rg= 0.57) between lung and head/neck can-
cer, two cancers linked to tobacco use20,25. We also for the first
time observed a significant genetic correlation between breast and
ovarian cancer (rg= 0.24), two cancers that are known to share
rare genetic factors including BRCA1/2 mutations, and environ-
mental exposures associated with endogenous and exogenous
hormone exposures26. Prostate cancer is also considered as
hormone-dependent and associated with BRCA1/2mutations, but
interestingly, we only observed a nominally significant and
modest (rg= 0.07) genetic correlation between breast and pros-
tate cancer, while ovarian and prostate cancer showed no genetic
correlation (rg= 0.02, se= 0.07).
Our large sample sizes allowed us to conduct well-powered
analyses for cancer subtypes. While head/neck cancer showed
negligible genetic correlation with overall (rg= 0.03, se= 0.06)
and ER+ breast cancer (rg=−0.02, se= 0.07), it showed a
stronger genetic correlation with ER− breast cancer (rg= 0.21,
se= 0.09). Similarly, lung cancer showed a statistically more
pronounced genetic correlation with ER− (rg= 0.29, se= 0.06)
than ER+ breast cancer (rg= 0.13, se= 0.04). A recent pooled
analysis of smoking and breast cancer risk demonstrated a
smoking-related increased risk for ER+ but not for ER− breast
cancer27, and thus it is unlikely that the stronger genetic corre-
lation between ER− subtype and lung and head/neck cancer is
due to smoking behavior. Perhaps surprisingly, despite literature
suggesting substantial similarities between ER− breast cancer and
serous ovarian cancer in particular28, we did not observe statis-
tically significant different genetic correlations between ER− or
ER+ breast cancer and serous ovarian cancer (rg= 0.17, se=
0.08 vs. rg= 0.11, se= 0.06). This suggests that rare high pene-
trance variants may play a more important role in driving the
similarities behind ER− breast cancer and serous ovarian cancer
than common genetic variation.
Heritability analysis confirms that common cancers have a
polygenic component that involves a large number of variants.
Although susceptibility variants identified at genome-wide sig-
nificance explain an appreciable fraction of the heritability for
some cancers, we estimate that the majority of the polygenic effect
is attributable to other, yet undiscovered variants, presumably
with effects that are too weak to have been identified with current
sample sizes. We found the genetic component that could be
attributed to genome-wide significant loci varied greatly from
~0% for head/neck cancer to ~50% for breast and prostate cancer.
These results reflect in part the strong correlation between
number of GWAS-identified loci and sample size, as we had more
than twice as many breast and prostate cancer samples compared
to the other cancers. One corollary is that larger GWAS are likely
to identify new susceptibility loci that could help our under-
standing of disease development, improve prediction power of
genetic risk scores and hence contribute to screening and per-
sonalized risk prediction29.
Among the genetic correlations between cancer and non-
cancer traits, we observed positive correlations for psychiatric
disorders (depressive symptoms, schizophrenia) with lung and
breast cancer, where findings from epidemiological studies have
been suggestive but inconclusive. It has been proposed that the
linkage between psychiatric traits and cancers are more likely to
be mediated through cancer-associated risk phenotypes such as
smoking, excessive alcohol consumption in depressed popula-
tions30, and reduced fertility patterns (e.g., nulliparous) in psy-
chiatric populations31. Detailed analyses considering confounding
traits like reproductive history and smoking are needed to make
inference about the mechanisms involved. GWAS have identified
pleiotropic regions influencing both lung cancer and nicotine
dependence, such as 15q25.132,33. In line with those results, we
identified a strong genetic correlation between smoking and both
lung (rg= 0.56) and head/neck cancer (rg= 0.47). It remains
unclear whether this genetic correlation is completely explained
by the direct influence of smoking or if the shared genetic com-
ponent affects the traits through separate pathways. Interestingly,
a genetic correlation (rg= 0.35, se= 0.14) between lung and
bladder cancer, another smoking-associated cancer, has been
identified previously9. Due to the small numbers of GWAS-
identified smoking-associated SNPs, we were unable to assess a
directional correlation between smoking and cancer, but we
expect such analyses to become feasible as additional smoking-
related SNPs are identified. We found modest positive, yet sig-
nificant genetic correlations between adiposity-related measures
(as reflected by waist-to-hip ratio, circulating HDL levels and
BMI) and both colorectal and lung cancer, but negative genetic
correlations between BMI and prostate and breast cancer, con-
sistent with previous reported findings34 and reinforce the com-
plex dynamics between obesity and cancer where multiple factors
including age, smoking, endogenous hormones and reproductive
status play a role.
We did not observe genetic correlations between breast cancer
and age at menarche or age at natural menopause. These null
observations were largely driven by ER+ breast cancer (ER+ :
rg= 0.006, se= 0.03 vs. ER−: rg=−0.09, se= 0.04 for age
at menarche. ER+ : rg= 0.0005, se= 0.04 vs. ER−: rg=−0.10,
se= 0.05 for age at natural menopause), and were unexpected
given that both factors play pivotal roles in breast cancer etiol-
ogy35 and previous Mendelian randomization (MR) analyses have
identified a link36,37. An important difference between genetic
Table 1 Significant enrichment estimates of genomic
functional categories, meta-analyzed across six cancer sites
Category Enrichment (95% CI) P-value
Conserved region 9.78 (5.72–13.84) 2.28 × 10−5
TFBS 4.04 (2.91–5.17) 1.43 × 10−7
H3K9ac 3.41 (2.14–4.69) 2.04 × 10−4
H3K4me3 3.23 (2.47–4.00) 8.91 × 10−9
Super Enhancer 2.56 (2.23–2.89) 1.99 × 10−20
H3K27ac (PGC) 2.36 (1.91–2.80) 2.12 × 10−9
H3K27ac (Hnisz) 1.90 (1.65–2.15) 1.86 × 10−12
H3K4me1 1.84 (1.56–2.12) 2.57 × 10−9
Repressed region 0.34 (0.07–0.61) 1.15 × 10−6
The meta-analysis was performed based on the enrichment estimates and standard errors
calculated using LD score regression in each individual cancer type. P-values were significant
after Bonferroni correction (P < 0.05/24)
TFBS transcription factor binding sites
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 7
10.0
7.5
5.0
2.5
0.0
10.0
7.5
5.0
2.5
0.0
10.0
7.5
5.0
2.5
0.0
10.0
7.5
5.0
2.5
0.0
10.0
7.5
5.0
2.5
0.0
10.0
7.5
5.0
2.5
0.0
–l
og
10
 (
en
ric
hm
en
t_
p-
va
lu
es
)
Breast cancer
Colorectal cancer
Headneck cancer
Lung cancer
Ovarian cancer
Prostate cancer
3′
 U
T
R
5′
 U
T
R
C
od
in
g
C
T
C
F
C
on
se
rv
ed
D
G
F
D
H
S
E
nh
an
ce
r
FA
N
TO
M
5 
en
ha
nc
er
F
et
al
 D
H
S
H
3K
27
ac
 (
H
ni
sz
)
H
3K
27
ac
 (
P
G
C
2)
H
3K
4m
e1
H
3K
4m
e3
H
3K
9a
c
In
tr
on
P
ro
m
ot
er
P
ro
m
ot
er
 fl
an
ki
ng
R
ep
re
ss
ed
S
up
er
 e
nh
an
ce
r
W
ea
k 
en
ha
nc
er
T
F
B
S
T
S
S
Tr
an
sc
rib
ed
24_main_annotation
Fig. 5 Enrichment p-values of 24 non-cell-type-specific functional categories over six cancer types. The x-axis represents each of the 24 functional
categories, y-axis represents log-transformed p-values of enrichment. Annotations with statistical significance after Bonferroni corrections (p < 0.05/24)
were plotted in orange, otherwise blue. The horizontal gray dash line indicates p-threshold of 0.05; horizontal red dash line indicates p-threshold of 0.05/
24. From top to bottom are six panels representing six cancers: breast cancer, colorectal cancer, head/neck cancer, lung cancer, ovarian cancer, and
prostate cancer. TSS transcription start site, UTR untranslated region, TFBS transcription factor binding sites, DHS DNase I hypersensitive sites, DGF digital
genomic foot printing, CTCF CCCTC-binding factor
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
8 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
correlation and MR analyses is that the latter only considers
genome-wide significant SNPs while the former incorporates the
entire genome. It is possible that a relatively small overlap in
strongly associated SNPs can result in significant MR results
despite low evidence of an overall genetic correlation. Indeed, the
directional genetic correlations we observed for age at natural
menopause, schizophrenia, and HDL with breast cancer, and for
lupus with prostate cancer, highlight again that although an
overall genetic correlation may be negligible, there can still be
genetic links between traits. It is important to note that we cannot
rule out unmeasured confounding, including the possibility that
these genetic variants affect an intermediate phenotype that is
pleiotropic for both target traits. Given the observational nature
of our data, these putative causal directions should be interpreted
with caution.
Pan-cancer tumor-based studies have demonstrated that dif-
ferent cancers are sometimes driven by similar somatic functional
events such as specific copy number abnormalities and
mutations38,39. Our enrichment results of germline genetic across
functional annotation data shed new light on the biological
mechanisms leading to cancer development. The more pro-
nounced enrichment identified for conserved regions compared
with coding regions provides evidence for the biological impor-
tance of the former, which has been shown to be true for multiple
traits14,40. Even though the biochemical function of many con-
served regions remains uncharacterized, transcribed ultra-
conserved regions have been found to be frequently located at
fragile sites. Compared to normal cells, cancer cells have a unique
spectrum of transcribed ultra-conservative regions, suggesting
that variation in expression of these regions are involved in the
malignant process41,42. These results bridge the link between
germline and somatic genetics in cancer development, which was
also observed in a recent breast cancer GWAS that has demon-
strated a strong overlap between target genes for GWAS hits and
somatic driver genes in breast tumors43. We also found a four-
fold enrichment for transcription factor binding sites and a three-
fold enrichment for super-enhancers, consistent with prior
observations that breast cancer GWAS loci fall in enhancer
regions involved in distal regulation of target genes43. Cell-type-
specific analysis of histone marks demonstrated the importance of
tissue specificity, primarily for colorectal and breast cancer.
Further, our results suggest that immune cells are important for
ovarian and lung cancer whilst CNS is important to head/neck
cancer. Unfortunately, we did not have data on prostate-specific
tissues, but we note that tissue-specific enrichment of prostate
cancer heritability for epigenetic markers has been observed
previously10. We note that generation of rich functional anno-
tation is ongoing and we expect to include additional tissue-
specific functional elements in our future work.
Our study has several strengths. We were able to robustly
quantify pair-wise genetic correlations between multiple cancers
using the largest available cancer GWAS, comprising almost
600,000 samples across six major cancers and subtypes. We were
also able to systematically assess the genetic correlations between
cancer and 38 non-cancer traits. Notwithstanding the large
sample sizes, several limitations need to be acknowledged. We did
not have the sample sizes required to assess relevant cancer
subgroups including oropharyngeal cancer, clear cell, mucinous
and endometrioid ovarian cancer, or lung cancer among never
smokers (each with ~2000 cases). In addition, we did not have
access to GWAS summary statistics for pre- vs. post-menopausal
breast cancer. We were not able to consider all cancer risk factors
when selecting non-cancer traits, since some of the well-
established risk factors such as infection were either not avail-
able, showed no evidence of heritability or were not based on
adequate sample sizes for robust analyses. SNP-heritability varies
with minor allele frequency, linkage disequilibrium, and genotype
certainty; we note that approaches to estimate heritability lever-
aging GWAS data are constantly evolving. We also note that
estimate variability needs to be taken into account when com-
paring the SNP-heritability with the classical twin-heritability, in
particular for cancers with small sample sizes such as head/neck
cancer (SNP-heritability varied between 5–14% and twin-
heritability varied between 0–60%, although both point esti-
mates were 9%). Further, our data were based on GWAS meta-
analysis from multiple individual GWAS across European
ancestry populations from Europe, Australia and the US. Intra-
European ancestry differences are likely to be a source of bias.
However, since we limited our analysis to SNPs with MAF > 1%
and HapMap3 SNPs (which have proven to be well imputed
across European ancestry populations), we believe that any
population structure across cancers will have minimal effect on
our results. Finally, as more non-European and multi-ethnic
GWAS data become available, it is important to examine trans-
ethnic genetic correlation in cancer.
In conclusion, results from our comprehensive analysis of
heritability and genetic correlations across six cancer types indi-
cate that solid tumors arising from different tissues share com-
mon germline genetic influences. Our results also demonstrate
evidence for common genetic risk sharing between cancers and
smoking, psychiatric, and metabolic traits. In addition, functional
components of the genome, particularly conserved and regulatory
regions, are significant contributors to cancer heritability across
multiple cancer types. Our results provide a basis and direction
for future cross-cancer studies aiming to further explore the
biological mechanisms underlying cancer development.
Methods
Studies and quality control. We used summary statistics from six cancer GWASs
based on a total of 597,534 participants of European ancestry. Cancer-specific
sample sizes were: breast cancer: 122,977 cases/105,974 controls; colorectal cancer:
36,948/30,864; head/neck cancer (oral and oropharyngeal cancers): 5452/5984; lung
cancer: 29,266/56,450; ovarian cancer: 22,406/40,941; prostate cancer: 79,166/
61,106. These data were generated through the joint efforts of multiple consortia.
Details on study characteristics and subjects contributed to each cancer-specific
GWAS summary dataset have been described elsewhere43–49. SNPs were imputed
to the 1000 Genomes Project reference panel (1KGP) using a standardized protocol
for all cancer types18. We included autosomal SNPs with a minor allele frequency
(MAF) larger than 1% and present in HapMap3 (NSNPs= ~1 million) because
those SNPs are usually well imputed in most studies (note that excluding sex
chromosomes could reduce the overall heritability estimates). A brief overview of
the quality control in each cancer dataset are presented in Supplementary Table 5.
For some of the cancers, we further obtained summary statistics data on subtypes
(ER+ and ER− breast cancer; lung adenocarcinoma, and squamous cell carci-
noma; serous invasive ovarian cancer and advanced stage prostate cancer, defined
as metastatic disease or Gleason score ≥ 8 or PSA > 100 or prostate cancer death).
Sample sizes and more details shown in Supplementary Table 1.
We additionally assembled European ancestry GWAS summary statistics from
38 traits, which spanned a wide range of phenotypes including anthropometric
(e.g., height and body mass index (BMI)), psychiatric disorder (e.g., depressive
symptoms and schizophrenia), and autoimmune disease (e.g., rheumatoid arthritis
and celiac disease) (Supplementary Table 6). We calculated trait-specific SNP-
heritability and restricted our analysis to traits with a heritable component
(Supplementary Table 7)14. We removed the major histocompatibility complex
(MHC) region from all analysis because of its unusual LD and genetic architecture.
Estimation of SNP-heritability and genetic correlation. We estimated the SNP-
heritability due to genotyped and imputed SNPs (h2g , the proportion of phenotypic
variance causally explained by common SNPs) of each cancer using LDSC15.
Briefly, this method is based on the relationship between LD score and χ2-statistics:
E χ2j
h i

 Njh
2
g
M
lj þ 1 ð1Þ
where E χ2j
h i
denotes the expected χ2-statistics for the association between the
outcome and SNP j, Nj is the study sample size available for SNP j, M is the total
numbers of variants and lj denotes the LD score of SNP j defined as lj ¼
P
k
r2 j; kð Þ
(k denotes other variants within the LD region). Note that the quantity estimated
by LDSC is the causal heritability of common SNPs, which is different from the
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 9
SNP-heritability as defined in Yang et al.17. To estimate h2g attributable to undis-
covered loci, we identified SNPs that were associated with a given cancer at
genome-wide significance (p < 5 × 10−8) and removed all SNPs within (+/−)
500,000 base-pairs of those loci prior to calculation (number of regions (+/−
500 kb) for each cancer that reach the 5 × 10−8 threshold and measures of effect
size are shown in Supplementary Data 1). We also converted the SNP-heritability
from observed scale to liability scale by incorporating sample prevalence (P) and
population prevalence (F) of each cancer:
h2liability ¼ h2observed
F 1 Fð Þ
ϕ Φ1 Fð Þð Þ2
F 1 Fð Þ
P 1 Pð Þ ð2Þ
We subsequently calculated the genome-wide genetic correlations (rg) between
different cancers, and between cancers and non-cancer traits, using an algorithm14:
E βjγj
h i
¼
ffiffiffiffiffiffiffiffiffiffiffi
N1N2
p
rg
M
lj þ
Nsrffiffiffiffiffiffiffiffiffiffiffi
N1N2
p ð3Þ
where βj and γj are the effect sizes of SNP j on traits 1 and 2, rg is the genetic
covariance, M is number of SNPs, N1 and N2 are the sample sizes for trait 1 and 2,
Ns is the number of overlapping samples, r is the phenotypic correlation in
overlapping samples and lj is the LD score defined as above. For genetic correlation
between 6 cancers, the significance level is 0.05/15= 0.003; for genetic correlation
between 6 cancers and 38 traits, the significance level is 0.05/(6 × 38)= 0.0002.
Overall genetic correlations as estimated by LDSC are based on aggregated
information across all variants in the genome. It is possible that even though two
traits show negligible overall genetic correlation, there are specific regions in the
genome that contribute to both traits. We therefore examined local genetic
correlations between cancer pairs using ρ-HESS50, an algorithm which partitions
the whole genome into 1703 regions based on LD-pattern of European populations
and quantifies correlation between pairs of traits due to genetic variation restricted
to these genomic regions. Local genetic correlation was considered statistically
significant if p < 0.05/1,703= 2.9 × 10−5. In particular, we assessed the local genetic
correlations for previously reported pleiotropic regions18,51 known to harbor SNPs
affecting multiple cancers.
Directional genetic correlation analysis. In addition to the genetic correlation
analysis, which reflects overall genetic overlaps, we also attempted to identify
directions of potential genetic correlations using a subset of SNPs as proposed by
Pickrell et al.52. The method adopts the following assumption: if a trait X influences
trait Y, then SNPs influencing X should also influence Y, and the SNP-specific
effect sizes for the two traits should be correlated. Further, since Y does not
influence X, but could be influenced by mechanisms independent of X, genetic
variants that influence Y do not necessarily influence X. Based on this assumption,
the method proposes two causal models and two non-causal models; and calculates
the relative likelihood ratio (LR) of the best non-causal model compared to the best
causal model. We determined significant SNPs for each given cancer or trait in two
independent ways, (1) LD pruned SNPs: we selected genome-wide significant (p <
5 × 10−8) SNPs and pruned on LD-pattern in the European populations in Phase1
of 1KGP; (2) posterior probability of association (PPA) SNPs: we used a method
implemented in fgwas53, which splits the genome into independent blocks based on
LD patterns in 1KGP and estimates the prior probability that any block contains an
association. The model outputs posterior probability that the region contains a
variant that influences the trait. We selected the lead SNP from each of the
regions with a PPA of at least 0.9. We scanned through all pairs of cancers
and traits to identify directional correlations. Only pairs of traits with evidence
of directional correlations (LR comparing the best non-causal model over
the best causal model < 0.05) and without evidence of heteroscedasticity
(pleiotropic effects)54 were reported as relatively more likely to exhibit mediated
causation.
Functional partitioning of SNP-heritability. To assess the importance of specific
functional annotations in SNP-heritability across cancers, we partitioned the
cancer-specific heritability using stratified-LDSC14. This method partitions SNPs
into functional categories and calculates category-specific enrichments based on the
assumption that a category of SNPs is enriched for heritability if SNPs with high
LD to that category have higher χ2 statistics than SNPs with low LD to that
category. The analysis was performed using two models14,24.
1. A full baseline-LD model including 24 publicly available annotations that are
not specific to any cell type. When performing this model, we adjusted for
MAF via MAF-stratified quantile-normalized LD score, and other LD-related
annotations such as predicted allele age and recombination rate, as
implemented by Gazal et al.24. Briefly, the 24 annotations included coding,
3′UTR and 5′UTR, promoter and intronic regions, obtained from UCSC
Genome Browser and post-processed by Gusev et al.55; the histone marks
mono-methylation (H3K4me1) and tri-methylation of histone H3 at lysine 4
(H3K4me3), acetylation of histone H3 at lysine 9 (H3K9ac) processed by
Trynka et al.56–58 and two versions of acetylation of histone H3 at lysine 27
(H3K27ac, one version processed by Hnisz et al.59, another used by the
Psychiatric Genomics Consortium (PGC)60); open chromatin, as reflected by
DNase I hypersensitivity sites (DHSs and fetal DHSs)55, obtained as a
combination of ENCODE and Roadmap Epigenomics data, processed by
Trynka et al.58; combined chromHMM and Segway predictions obtained from
Hoffman et al.61, which make use of many annotations to produce a single
partition of the genome into seven underlying chromatin states (The CCCTC-
binding factor (CTCF), promoter-flanking, transcribed, transcription start site
(TSS), strong enhancer, weak enhancer categories, and the repressed
category); regions that are conserved in mammals, obtained from Lindblad-
Toh et al.40 and post-processed by Ward and Kellis62; super-enhancers, which
are large clusters of highly active enhancers, obtained from Hnisz et al.59;
FANTOM5 enhancers with balanced bi-directional capped transcripts
identified using cap analysis of gene expression in the FANTOM5 panel of
samples, obtained from Andersson et al.63; digital genomic footprint (DGF)
and transcription factor binding site (TFBS) annotations obtained from
ENCODE and post-processed by Gusev et al.55
2. In addition to the baseline-LD model, we also performed analyses using 220 cell-
type-specific annotations for the four histone marks H3K4me1, H3K4me3,
H3K9ac, and H3K27ac. Each cell-type-specific annotation corresponds to a
histone mark in a single cell type (for example, H3K27ac in CD19 immune
cells), and there were 220 such annotations in total. We further divided these 220
cell-type-specific annotations into 10 groups (adrenal and pancreas, central
nervous system (CNS), cardiovascular, connective and bone, gastrointestinal,
immune and hematopoietic, kidney, liver, skeletal muscle, and other) by taking a
union of the cell-type-specific annotations within each group (for example, SNPs
with any of the four histone modifications in any hematopoietic and immune
cells were considered as one big category). When generating the cell-type-
specific models, we added annotations individually to the baseline model,
creating 220 separate models.
We performed a random-effects meta-analysis of the proportion of heritability
over six cancers for each functional category. We set significance thresholds for
individual annotations at p < 0.05/24 for baseline model and at p < 0.05/220 for
cell-type-specific annotation.
Data availability
The datasets generated during and/or analyzed during the current study are
available from the authors on request. Breast cancer: summary results for all
variants are available at http://bcac.ccge.medschl.cam.ac.uk/. Requests for further
data should be made through the Data Access Coordination Committee (http://
bcac.ccge.medschl.cam.ac.uk/). Ovarian cancer: summary results are available from
the Ovarian Cancer Association Consortium (OCAC) (http://ocac.ccge.medschl.
cam.ac.uk/). Requests for further data can be made to the Data Access Coordi-
nation Committee (http://cimba.ccge.medschl.cam.ac.uk/). Prostate cancer: sum-
mary results are publicly available at the PRACTICAL website (http://practical.icr.
ac.uk/blog/). Lung cancer: genotype data for lung cancer are available at the
database of Genotypes and Phenotypes (dbGaP) under accession phs001273.v1.p1.
Readers interested in obtaining a copy of the original data can do so by completing
the proposal request form at http://oncoarray.dartmouth.edu/. Head/neck cancer:
genotype data for the oral and pharyngeal OncoArray study have been deposited at
the database of Genotypes and Phenotypes (dbGaP) under accession phs001202.v1.
p1. Colorectal cancer: genotype data have been deposited at the database of
Genotypes and Phenotypes (dbGaP) under accession number phs001415.v1.p1 and
phs001078.v1.p1.
Received: 30 July 2018 Accepted: 10 December 2018
Published online: 25 January 2019
References
1. Lichtenstein, P. et al. Environmental and heritable factors in the causation of
cancer–analyses of cohorts of twins from Sweden, Denmark, and Finland. N.
Engl. J. Med. 343, 78–85 (2000).
2. Mucci, L. A. et al. Familial risk and heritability of cancer among twins in
nordic countries. JAMA 315, 68 (2016).
3. Polderman, T. J. C. et al. Meta-analysis of the heritability of human traits
based on fifty years of twin studies. Nat. Genet. 47, 702–709 (2015).
4. Amundadottir, L. T. et al. Cancer as a complex phenotype: pattern of
cancer distribution within and beyond the nuclear family. PLoS Med. 1, e65
(2004).
5. Yu, H., Frank, C., Sundquist, J., Hemminki, A. & Hemminki, K. Common
cancers share familial susceptibility: implications for cancer genetics and
counselling. J. Med. Genet. 54, 248–253 (2017).
6. Frank, C., Sundquist, J., Yu, H., Hemminki, A. & Hemminki, K. Concordant
and discordant familial cancer: familial risks, proportions and population
impact. Int. J. Cancer 140, 1510–1516 (2017).
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
10 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
7. Fehringer, G. et al. Cross-cancer genome-wide analysis of lung, ovary, breast,
prostate, and colorectal cancer reveals novel pleiotropic associations. Cancer
Res. 76, 5103–5114 (2016).
8. Kar, S. P. et al. Genome-wide meta-analyses of breast, ovarian, and prostate
cancer association studies identify multiple new susceptibility loci shared by at
least two cancer types. Cancer Discov. 6, 1052–1067 (2016).
9. Sampson, J. N. et al. Analysis of heritability and shared heritability based on
genome-wide association studies for thirteen cancer types. J. Natl. Cancer Inst.
107, djv279 (2015).
10. Gusev, A. et al. Atlas of prostate cancer heritability in European and African-
American men pinpoints tissue-specific regulation. Nat. Commun. 7, 10979
(2016).
11. Jiao, S. et al. Estimating the heritability of colorectal cancer. Hum. Mol. Genet.
23, 3898–3905 (2014).
12. Lu, Y. et al. Most common ‘sporadic’ cancers have a significant germline
genetic component. Hum. Mol. Genet. 23, 6112–6118 (2014).
13. Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for
genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
14. Finucane, H. K. et al. Partitioning heritability by functional annotation using
genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
15. Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding
from polygenicity in genome-wide association studies. Nat. Genet. 47,
291–295 (2015).
16. Lindström, S. et al. Quantifying the genetic correlation between multiple
cancer types. Cancer Epidemiol. Biomark. Prev. 26, 1427–1435 (2017).
17. Yang, J. et al. Common SNPs explain a large proportion of the heritability for
human height. Nat. Genet. 42, 565–569 (2010).
18. Amos, C. I. et al. The OncoArray Consortium: a network for understanding
the genetic architecture of common cancers. Cancer Epidemiol. Biomark. Prev.
26, 126–135 (2017).
19. SMOKING and health. Joint report of the Study Group on Smoking and
Health. Science 125, 1129–1133 (1957).
20. Shaw, R. & Beasley, N. Aetiology and risk factors for head and neck cancer:
United Kingdom National Multidisciplinary Guidelines. J. Laryngol. Otol. 130,
S9–S12 (2016).
21. Koene, R. J., Prizment, A. E., Blaes, A. & Konety, S. H. Shared risk factors in
cardiovascular disease and cancer. Circulation 133, 1104–1114 (2016).
22. Thompson, C. L. et al. Short duration of sleep increases risk of colorectal
adenoma. Cancer 117, 841–847 (2011).
23. Sigurdardottir, L. G. et al. Sleep disruption among older men and risk of
prostate cancer. Cancer Epidemiol. Prev. Biomark. 22, 872–879 (2013).
24. Gazal, S. et al. Linkage disequilibrium-dependent architecture of human
complex traits shows action of negative selection. Nat. Genet. 49, 1421–1427
(2017).
25. Field, R. W. & Withers, B. L. Occupational and environmental causes of lung
cancer. Clin. Chest Med. 33, 681–703 (2012).
26. Hulka, B. S. Epidemiologic analysis of breast and gynecologic cancers. Prog.
Clin. Biol. Res. 396, 17–29 (1997).
27. Gaudet, M. M. et al. Pooled analysis of active cigarette smoking and invasive
breast cancer risk in 14 cohort studies. Int. J. Epidemiol. 46, 881–893 (2017).
28. Cancer Genome Atlas Network. Comprehensive molecular portraits of human
breast tumours. Nature 490, 61–70 (2012).
29. Maas, P. et al. Breast cancer risk from modifiable and nonmodifiable risk
factors among white women in the United States. JAMA Oncol 2, 1295–1302
(2016).
30. Nakaya, N. et al. Personality traits and cancer risk and survival based on
finnish and swedish registry data. Am. J. Epidemiol. 172, 377–385 (2010).
31. Oksbjerg Dalton, S., Munk Laursen, T., Mellemkjaer, L., Johansen, C. &
Mortensen, P. B. Schizophrenia and the risk for breast cancer. Schizophr. Res.
62, 89–92 (2003).
32. Hung, R. J. et al. A susceptibility locus for lung cancer maps to nicotinic
acetylcholine receptor subunit genes on 15q25. Nature 452, 633–637 (2008).
33. Amos, C. I. et al. Genome-wide association scan of tag SNPs identifies
a susceptibility locus for lung cancer at 15q25.1. Nat. Genet. 40, 616–622
(2008).
34. Gao, C. et al. Mendelian randomization study of adiposity-related traits and
risk of breast, ovarian, prostate, lung and colorectal cancer. Int. J. Epidemiol.
45, 896–908 (2016).
35. Collaborative Group on Hormonal Factors in Breast Cancer. Menarche,
menopause, and breast cancer risk: individual participant meta-analysis,
including 118 964 women with breast cancer from 117 epidemiological
studies. Lancet Oncol. 13, 1141–1151 (2012).
36. Day, F. R. et al. Large-scale genomic analyses link reproductive aging to
hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated
DNA repair. Nat. Genet. 47, 1294–1303 (2015).
37. Day, F. R. et al. Genomic analyses identify hundreds of variants associated
with age at menarche and support a role for puberty timing in cancer risk.
Nat. Genet. 49, 834–841 (2017).
38. Zack, T. I. et al. Pan-cancer patterns of somatic copy number alteration. Nat.
Genet. 45, 1134–1140 (2013).
39. Ciriello, G. et al. Emerging landscape of oncogenic signatures across human
cancers. Nat. Genet. 45, 1127–1133 (2013).
40. Lindblad-Toh, K. et al. A high-resolution map of human evolutionary
constraint using 29 mammals. Nature 478, 476–482 (2011).
41. Calin, G. A. et al. Ultraconserved regions encoding ncRNAs are altered in
human leukemias and carcinomas. Cancer Cell 12, 215–229 (2007).
42. Peng, J. C., Shen, J. & Ran, Z. H. Transcribed ultraconserved region in human
cancers. RNA Biol. 10, 1771–1777 (2013).
43. Michailidou, K. et al. Association analysis identifies 65 new breast cancer risk
loci. Nature 551, 92–94 (2017).
44. Milne, R. L. et al. Identification of ten variants associated with risk of estrogen-
receptor-negative breast cancer. Nat. Genet. 49, 1767–1778 (2017).
45. McKay, J. D. et al. Large-scale association analysis identifies new lung cancer
susceptibility loci and heterogeneity in genetic susceptibility across histological
subtypes. Nat. Genet. 49, 1126–1132 (2017).
46. Schmit, S. L. et al. Novel Common Genetic Susceptibility Loci for Colorectal
Cancer. J. Natl. Cancer Inst. 111, djy099 (2019).
47. Phelan, C. M. et al. Identification of 12 new susceptibility loci for different
histotypes of epithelial ovarian cancer. Nat. Genet. 49, 680–691 (2017).
48. Lesseur, C. et al. Genome-wide association analyses identify new susceptibility
loci for oral cavity and pharyngeal cancer. Nat. Genet. 48, 1544–1550 (2016).
49. Schumacher, F. R. et al. Association analyses of more than 140,000 men
identify 63 new prostate cancer susceptibility loci. Nat. Genet. 50, 928–936
(2018).
50. Shi, H., Mancuso, N., Spendlove, S. & Pasaniuc, B. Local genetic correlation
gives insights into the shared genetic architecture of complex traits. Am. J.
Hum. Genet. 101, 737–751 (2017).
51. Sakoda, L. C., Jorgenson, E. & Witte, J. S. Turning of COGS moves forward
findings for hormonally mediated cancers. Nat. Genet. 45, 345–348 (2013).
52. Pickrell, J. K. et al. Detection and interpretation of shared genetic influences
on 42 human traits. Nat. Genet. 48, 709–717 (2016).
53. Pickrell, J. K. Joint analysis of functional genomic data and genome-wide
association studies of 18 human traits. Am. J. Hum. Genet. 94, 559–573
(2014).
54. Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with
invalid instruments: effect estimation and bias detection through Egger
regression. Int. J. Epidemiol. 44, 512–525 (2015).
55. Gusev, A. et al. Partitioning heritability of regulatory and cell-type-specific
variants across 11 common diseases. Am. J. Hum. Genet. 95, 535–552 (2014).
56. Roadmap Epigenomics Consortium. et al. Integrative analysis of 111 reference
human epigenomes. Nature 518, 317–330 (2015).
57. ENCODE Project Consortium. An integrated encyclopedia of DNA elements
in the human genome. Nature 489, 57–74 (2012).
58. Trynka, G. et al. Chromatin marks identify critical cell types for fine mapping
complex trait variants. Nat. Genet. 45, 124–130 (2013).
59. Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell
155, 934–947 (2013).
60. Schizophrenia Working Group of the Psychiatric Genomics Consortium.
Biological insights from 108 schizophrenia-associated genetic loci. Nature 511,
421–427 (2014).
61. Hoffman, M. M. et al. Integrative annotation of chromatin elements from
ENCODE data. Nucleic Acids Res. 41, 827–841 (2013).
62. Ward, L. D. & Kellis, M. Evidence of abundant purifying selection in humans
for recently acquired regulatory functions. Science 337, 1675–1678 (2012).
63. Andersson, R. et al. An atlas of active enhancers across human cell types and
tissues. Nature 507, 455–461 (2014).
Acknowledgements
The authors in this manuscript were working on behalf of BCAC, CCFR, CIMBA,
CORECT, GECCO, OCAC, PRACTICAL, CRUK, BPC3, CAPS, PEGASUS, TRICL-
ILCCO, ABCTB, APCB, BCFR, CONSIT TEAM, EMBRACE, GC-HBOC, GEMO,
HEBON, kConFab/AOCS Mod SQuaD, and SWE-BRCA. The breast cancer genome-wide
association analyses: BCAC is funded by Cancer Research UK [C1287/A16563, C1287/
A10118], the European Union’s Horizon 2020 Research and Innovation Programme
(grant numbers 634935 and 633784 for BRIDGES and B-CAST, respectively), and by the
European Community’s Seventh Framework Programme under grant agreement number
223175 (grant number HEALTH-F2-2009-223175) (COGS). The EU Horizon 2020
Research and Innovation Programme funding source had no role in study design, data
collection, data analysis, data interpretation, or writing of the report. Genotyping of the
OncoArray was funded by the NIH Grant U19 CA148065, and Cancer UK Grant C1287/
A16563 and the PERSPECTIVE project supported by the Government of Canada through
Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344)
and, the Ministère de l’Économie, Science et Innovation du Québec through Genome
Québec and the PSR-SIIRI-701 grant, and the Quebec Breast Cancer Foundation. Funding
for the iCOGS infrastructure came from: the European Community’s Seventh Framework
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 11
Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS),
Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014,
C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of
Health (CA128978), and Post-Cancer GWAS initiative (1U19 CA148537, 1U19
CA148065, and 1U19 CA148112—the GAME-ON initiative), the Department of Defence
(W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR
Team in Familial Risks of Breast Cancer, and Komen Foundation for the Cure, the Breast
Cancer Research Foundation, and the Ovarian Cancer Research Fund. The DRIVE
Consortium was funded by U19 CA148065. The Australian Breast Cancer Family Study
(ABCFS) was supported by grant UM1 CA164920 from the National Cancer Institute
(USA). The content of this manuscript does not necessarily reflect the views or policies of
the National Cancer Institute or any of the collaborating centers in the Breast Cancer
Family Registry (BCFR), nor does mention of trade names, commercial products, or
organizations imply endorsement by the USA Government or the BCFR. The ABCFS was
also supported by the National Health and Medical Research Council of Australia, the
New South Wales Cancer Council, the Victorian Health Promotion Foundation (Aus-
tralia), and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health
and Medical Research Council (NHMRC) Senior Principal Research Fellow. M.C.S. is a
NHMRC Senior Research Fellow. The ABCS study was supported by the Dutch Cancer
Society [grants NKI 2007-3839; 2009 4363]. The Australian Breast Cancer Tissue Bank
(ABCTB) is generously supported by the National Health and Medical Research Council
of Australia, The Cancer Institute NSW and the National Breast Cancer Foundation. The
ACP study is funded by the Breast Cancer Research Trust, UK. The AHS study is
supported by the intramural research program of the National Institutes of Health, the
National Cancer Institute (grant number Z01-CP010119), and the National Institute of
Environmental Health Sciences (grant number Z01-ES049030). The work of the BBCC
was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is
funded by Cancer Research UK and Breast Cancer Now and acknowledges NHS funding
to the NIHR Biomedical Research Centre, and the National Cancer Research Network
(NCRN). The BCEES was funded by the National Health and Medical Research Council,
Australia and the Cancer Council Western Australia and acknowledges funding from the
National Breast Cancer Foundation (JS). For the BCFR-NY, BCFR-PA, and BCFR-UT this
work was supported by grant UM1 CA164920 from the National Cancer Institute. The
content of this manuscript does not necessarily reflect the views or policies of the National
Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry
(BCFR), nor does mention of trade names, commercial products, or organizations imply
endorsement by the US Government or the BCFR. For BIGGS, ES is supported by NIHR
Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ NHS Foundation Trust
in partnership with King’s College London, United Kingdom. IT is supported by the
Oxford Biomedical Research Centre. BOCS is supported by funds from Cancer Research
UK (C8620/A8372/A15106) and the Institute of Cancer Research (UK). BOCS
acknowledges NHS funding to the Royal Marsden/Institute of Cancer Research NIHR
Specialist Cancer Biomedical Research Centre. The BREast Oncology GAlician Network
(BREOGAN) is funded by Acción Estratégica de Salud del Instituto de Salud Carlos III
FIS PI12/02125/Cofinanciado FEDER; Acción Estratégica de Salud del Instituto de Salud
Carlos III FIS Intrasalud (PI13/01136); Programa Grupos Emergentes, Cancer Genetics
Unit, Instituto de Investigacion Biomedica Galicia Sur. Xerencia de Xestion Integrada de
Vigo-SERGAS, Instituto de Salud Carlos III, Spain; Grant 10CSA012E, Consellería de
Industria Programa Sectorial de Investigación Aplicada, PEME I+D e I+D Suma del
Plan Gallego de Investigación, Desarrollo e Innovación Tecnológica de la Consellería de
Industria de la Xunta de Galicia, Spain; Grant EC11-192. Fomento de la Investigación
Clínica Independiente, Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain; and
Grant FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Gali-
cia, Spain. The BSUCH study was supported by the Dietmar-Hopp Foundation, the
Helmholtz Society and the German Cancer Research Center (DKFZ). The CAMA study
was funded by Consejo Nacional de Ciencia y Tecnología (CONACyT) (SALUD-2002-
C01-7462). Sample collection and processing was funded in part by grants from the
National Cancer Institute (NCI R01CA120120 and K24CA169004). CBCS is funded by
the Canadian Cancer Society (grant # 313404) and the Canadian Institutes of Health
Research. CCGP is supported by funding from the University of Crete. The CECILE study
was supported by Fondation de France, Institut National du Cancer (INCa), Ligue
Nationale contre le Cancer, Agence Nationale de Sécurité Sanitaire, de l’Alimentation, de
l’Environnement et du Travail (ANSES), Agence Nationale de la Recherche (ANR). The
CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the
Danish Medical Research Council, and Herlev and Gentofte Hospital. The CNIO-BCS
was supported by the Instituto de Salud Carlos III, the Red Temática de Investigación
Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and
the Fondo de Investigación Sanitario (PI11/00923 and PI12/00070). COLBCCC is sup-
ported by the German Cancer Research Center (DKFZ), Heidelberg, Germany. D.T. was
in part supported by a postdoctoral fellowship from the Alexander von Humboldt
Foundation. The American Cancer Society funds the creation, maintenance, and updating
of the CPS-II cohort. The CTS was initially supported by the California Breast Cancer Act
of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is
currently funded through the National Institutes of Health (R01 CA77398, UM1
CA164917, and U01 CA199277). Collection of cancer incidence data was supported by
the California Department of Public Health as part of the statewide cancer reporting
program mandated by California Health and Safety Code Section 103885. H.A.C eceives
support from the Lon V Smith Foundation (LVS39420). The University of Westminster
curates the DietCompLyf database funded by Against Breast Cancer Registered Charity
No. 1121258 and the NCRN. The coordination of EPIC is financially supported by the
European Commission (DG-SANCO) and the International Agency for Research on
Cancer. The national cohorts are supported by: Ligue Contre le Cancer, Institut Gustave
Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la
Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research
Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the
Hellenic Health Foundation, the Stavros Niarchos Foundation (Greece); Associazione
Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy);
Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry
(NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek
Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Neth-
erlands); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-
Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and
Navarra, ISCIII RETIC (RD06/0020) (Spain); Cancer Research UK (14136 to EPIC-
Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council
(1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom). The
ESTHER study was supported by a grant from the Baden Württemberg Ministry of
Science, Research and Arts. Additional cases were recruited in the context of the VERDI
study, which was supported by a grant from the German Cancer Aid (Deutsche Kreb-
shilfe). FHRISK is funded from NIHR grant PGfAR 0707-10031. The GC-HBOC (Ger-
man Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German
Cancer Aid (grant no 110837, coordinator: Rita K. Schmutzler, Cologne). This work was
also funded by the European Regional Development Fund and Free State of Saxony,
Germany (LIFE - Leipzig Research Centre for Civilization Diseases, project numbers 713-
241202, 713-241202, 14505/2470, and 14575/2470). The GENICA was funded by the
Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5,
01KW9976/8, 01KW9977/0, and 01KW0114, the Robert Bosch Foundation, Stuttgart,
Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, the Institute for Prevention and
Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr
University Bochum (IPA), Bochum, as well as the Department of Internal Medicine,
Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The
GEPARSIXTO study was conducted by the German Breast Group GmbH. The GESBC
was supported by the Deutsche Krebshilfe e. V. [70492] and the German Cancer Research
Center (DKFZ). GLACIER was supported by Breast Cancer Now, CRUK and Biomedical
Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College
London. The HABCS study was supported by the Claudia von Schilling Foundation for
Breast Cancer Research, by the Lower Saxonian Cancer Society, and by the Rudolf-
Bartling Foundation. The HEBCS was financially supported by the Helsinki University
Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer
Society, and the Sigrid Juselius Foundation. The HERPACC was supported by MEXT
Kakenhi (No. 170150181 and 26253041) from the Ministry of Education, Science, Sports,
Culture and Technology of Japan, by a Grant-in-Aid for the Third Term Comprehensive
10-Year Strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan,
by Health and Labour Sciences Research Grants for Research on Applying Health
Technology from Ministry Health, Labour and Welfare of Japan, by National Cancer
Center Research and Development Fund, and “Practical Research for Innovative Cancer
Control (15ck0106177h0001)” from Japan Agency for Medical Research and develop-
ment, AMED, and Cancer Bio Bank Aichi. The HMBCS was supported by a grant from
the Friends of Hannover Medical School and by the Rudolf Bartling Foundation. The
HUBCS was supported by a grant from the German Federal Ministry of Research and
Education (RUS08/017), and by the Russian Foundation for Basic Research and the
Federal Agency for Scientific Organizations for support the Bioresource collections and
RFBR grants 14-04-97088, 17-29-06014, and 17-44-020498. ICICLE was supported by
Breast Cancer Now, CRUK, and Biomedical Research Centre at Guy’s and St Thomas’
NHS Foundation Trust and King’s College London. Financial support for KARBAC was
provided through the regional agreement on medical training and clinical research (A.L.
F.) between Stockholm County Council and Karolinska Institutet, the Swedish Cancer
Society, The Gustav V Jubilee foundation and Bert von Kantzows foundation. The
KARMA study was supported by Märit and Hans Rausings Initiative Against Breast
Cancer. The KBCP was financially supported by the special Government Funding (E.V.
O.) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer
Organizations, and by the strategic funding of the University of Eastern Finland. kConFab
is supported by a grant from the National Breast Cancer Foundation, and previously by
the National Health and Medical Research Council (NHMRC), the Queensland Cancer
Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia,
and the Cancer Foundation of Western Australia. Financial support for the AOCS was
provided by the United States Army Medical Research and Materiel Command
[DAMD17-01-1-0729], Cancer Council Victoria, Queensland Cancer Fund, Cancer
Council New South Wales, Cancer Council South Australia, The Cancer Foundation of
Western Australia, Cancer Council Tasmania and the National Health and Medical
Research Council of Australia (NHMRC; 400413, 400281, 199600). G.C.-T. and P.W. are
supported by the NHMRC. RB was a Cancer Institute NSW Clinical Research Fellow. The
KOHBRA study was partially supported by a grant from the Korea Health Technology
R&D Project through the Korea Health Industry Development Institute (KHIDI), and the
National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of
Korea (HI16C1127; 1020350; 1420190). LAABC is supported by grants (1RB-0287, 3PB-
0102, 5PB-0018, 10PB-0098) from the California Breast Cancer Research Program.
Incident breast cancer cases were collected by the USC Cancer Surveillance Program
(CSP) which is supported under subcontract by the California Department of Health. The
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
12 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
CSP is also part of the National Cancer Institute’s Division of Cancer Prevention and
Control Surveillance, Epidemiology, and End Results Program, under contract number
N01CN25403. L.M.B.C. is supported by the ‘Stichting tegen Kanker’. D.L. is supported by
the FWO. The MABCS study is funded by the Research Centre for Genetic Engineering
and Biotechnology “Georgi D. Efremov” and supported by the German Academic
Exchange Program, DAAD. The MARIE study was supported by the Deutsche Krebshilfe
e.V. [70-2892-BR I, 106332, 108253, 108419, 110826, 110828], the Hamburg Cancer
Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Edu-
cation and Research (BMBF) Germany [01KH0402]. MBCSG is supported by grants from
the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens
who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS
Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects
“5 × 1000”). The MCBCS was supported by the NIH grants CA192393, CA116167,
CA176785 an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer
[CA116201], and the Breast Cancer Research Foundation and a generous gift from the
David F. and Margaret T. Grohne Family Foundation. MCCS cohort recruitment was
funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by
Australian NHMRC grants 209057 and 396414, and by infrastructure provided by Cancer
Council Victoria. Cases and their vital status were ascertained through the Victorian
Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW),
including the National Death Index and the Australian Cancer Database. The MEC was
support by NIH grants CA63464, CA54281, CA098758, CA132839, and CA164973. The
MISS study is supported by funding from ERC-2011-294576 Advanced grant, Swedish
Cancer Society, Swedish Research Council, Local hospital funds, Berta Kamprad Foun-
dation, Gunnar Nilsson. The MMHS study was supported by NIH grants CA97396,
CA128931, CA116201, CA140286, and CA177150. MSKCC is supported by grants from
the Breast Cancer Research Foundation and Robert and Kate Niehaus Clinical Cancer
Genetics Initiative. The work of MTLGEBCS was supported by the Quebec Breast Cancer
Foundation, the Canadian Institutes of Health Research for the “CIHR Team in Familial
Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic
Development, Innovation and Export Trade – grant # PSR-SIIRI-701. MYBRCA is funded
by research grants from the Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/
06) and Cancer Research Malaysia. MYMAMMO is supported by research grants from
Yayasan Sime Darby LPGA Tournament and Malaysian Ministry of Higher Education
(RP046B-15HTM). The NBCS has been supported by the Research Council of Norway
grant 193387/V50 (to A.-L. Børresen-Dale and V.N. Kristensen) and grant 193387/H10
(to A.-L. Børresen-Dale and V.N. Kristensen), South Eastern Norway Health Authority
(grant 39346 to A.-L. Børresen-Dale and 27208 to V.N. Kristensen) and the Norwegian
Cancer Society (to A.-L. Børresen-Dale and 419616 - 71248 - PR-2006-0282 to V.N.
Kristensen). It has received funding from the K.G. Jebsen Centre for Breast Cancer
Research (2012-2015). The NBHS was supported by NIH grant R01CA100374. Biological
sample preparation was conducted the Survey and Biospecimen Shared Resource, which is
supported by P30 CA68485. The Northern California Breast Cancer Family Registry (NC-
BCFR) and Ontario Familial Breast Cancer Registry (OFBCR) were supported by grant
UM1 CA164920 from the National Cancer Institute (USA). The content of this manu-
script does not necessarily reflect the views or policies of the National Cancer Institute or
any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does
mention of trade names, commercial products, or organizations imply endorsement by
the USA Government or the BCFR. The Carolina Breast Cancer Study was funded by
Komen Foundation, the National Cancer Institute (P50 CA058223, U54 CA156733, and
U01 CA179715), and the North Carolina University Cancer Research Fund. The
NGOBCS was supported by Grants-in-Aid for the Third Term Comprehensive Ten-Year
Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan, and
for Scientific Research on Priority Areas, 17015049 and for Scientific Research on
Innovative Areas, 221S0001, from the Ministry of Education, Culture, Sports, Science, and
Technology of Japan. The NHS was supported by NIH grants P01 CA87969, UM1
CA186107, and U19 CA148065. The NHS2 was supported by NIH grants UM1
CA176726 and U19 CA148065. The OBCS was supported by research grants from the
Finnish Cancer Foundation, the Academy of Finland (grant number 250083, 122715 and
Center of Excellence grant number 251314), the Finnish Cancer Foundation, the Sigrid
Juselius Foundation, the University of Oulu, the University of Oulu Support Foundation,
and the special Governmental EVO funds for Oulu University Hospital-based research
activities. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-
1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-
NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer
Institute, Department of Health and Human Services, USA. Genotyping for PLCO was
supported by the Intramural Research Program of the National Institutes of Health, NCI,
Division of Cancer Epidemiology and Genetics. The PLCO is supported by the Intramural
Research Program of the Division of Cancer Epidemiology and Genetics and supported by
contracts from the Division of Cancer Prevention, National Cancer Institute, National
Institutes of Health. The POSH study is funded by Cancer Research UK (grants C1275/
A11699, C1275/C22524, C1275/A19187, C1275/A15956, and Breast Cancer Campaign
2010PR62, 2013PR044. PROCAS is funded from NIHR grant PGfAR 0707-10031. The
RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318).
The SASBAC study was supported by funding from the Agency for Science, Technology
and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the
Susan G. Komen Breast Cancer Foundation. The SBCGS was supported primarily by NIH
grants R01CA64277, R01CA148667, UMCA182910, and R37CA70867. Biological sample
preparation was conducted the Survey and Biospecimen Shared Resource, which is
supported by P30 CA68485. The scientific development and funding of this project were,
in part, supported by the Genetic Associations and Mechanisms in Oncology (GAME-
ON) Network U19 CA148065. The SBCS was supported by Sheffield Experimental Cancer
Medicine Centre and Breast Cancer Now Tissue Bank. The SCCS is supported by a grant
from the National Institutes of Health (R01 CA092447). Data on SCCS cancer cases used
in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky
Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer
Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North
Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana
Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry;
Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of
Health, Cancer Registry, 4815W. Markham, Little Rock, AR 72205. The Arkansas Central
Cancer Registry is fully funded by a grant from National Program of Cancer Registries,
Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from
Mississippi were collected by the Mississippi Cancer Registry which participates in the
National Program of Cancer Registries (NPCR) of the Centers for Disease Control and
Prevention (CDC). The contents of this publication are solely the responsibility of the
authors and do not necessarily represent the official views of the CDC or the Mississippi
Cancer Registry. SEARCH is funded by Cancer Research UK [C490/A10124, C490/
A16561] and supported by the UK National Institute for Health Research Biomedical
Research Centre at the University of Cambridge. The University of Cambridge has
received salary support for PDPP from the NHS in the East of England through the
Clinical Academic Reserve. SEBCS was supported by the BRL (Basic Research Laboratory)
program through the National Research Foundation of Korea funded by the Ministry of
Education, Science and Technology (2012-0000347). SGBCC is funded by the NUS start-
up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant and the
NMRC Clinician Scientist Award. Additional controls were recruited by the Singapore
Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC), which was funded by
the Biomedical Research Council, grant number: 05/1/21/19/425. The Sister Study (SIS-
TER) is supported by the Intramural Research Program of the NIH, National Institute of
Environmental Health Sciences (Z01-ES044005 and Z01-ES049033). The Two Sister
Study (2SISTER) was supported by the Intramural Research Program of the NIH,
National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES102245),
and, also by a grant from Susan G. Komen for the Cure, grant FAS0703856. SKKDKFZS is
supported by the DKFZ. The SMC is funded by the Swedish Cancer Foundation. The
SZBCS was supported by Grant PBZ_KBN_122/P05/2004. The TBCS was funded by The
National Cancer Institute, Thailand. The TNBCC was supported by a Specialized Program
of Research Excellence (SPORE) in Breast Cancer (CA116201), a grant from the Breast
Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne
Family Foundation. The TWBCS is supported by the Taiwan Biobank project of the
Institute of Biomedical Sciences, Academia Sinica, Taiwan. The UCIBCS component of
this research was supported by the NIH [CA58860, CA92044] and the Lon V Smith
Foundation [LVS39420]. The UKBGS is funded by Breast Cancer Now and the Institute
of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Bio-
medical Research Centre. The UKOPS study was funded by The Eve Appeal (The Oak
Foundation) and supported by the National Institute for Health Research University
College London Hospitals Biomedical Research Centre. The US3SS study was supported
by Massachusetts (K.M.E., R01CA47305), Wisconsin (P.A.N., R01 CA47147) and New
Hampshire (L.T.-E., R01CA69664) centers, and Intramural Research Funds of the
National Cancer Institute, Department of Health and Human Services, USA. The USRT
Study was funded by Intramural Research Funds of the National Cancer Institute,
Department of Health and Human Services, USA. The WAABCS study was supported by
grants from the National Cancer Institute of the National Institutes of Health (R01
CA89085 and P50 CA125183 and the D43 TW009112 grant), Susan G. Komen
(SAC110026), the Dr. Ralph and Marian Falk Medical Research Trust, and the Avon
Foundation for Women. The WHI program is funded by the National Heart, Lung, and
Blood Institute, the US National Institutes of Health and the US Department of Health
and Human Services (HHSN268201100046C, HHSN268201100001C,
HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and
HHSN271201100004C). This work was also funded by NCI U19 CA148065-01. D.G.E. is
supported by the all Manchester NIHR Biomedical research center Manchester (IS-BRC-
1215-20007). HUNBOCS, Hungarian Breast and Ovarian Cancer Study was supported by
Hungarian Research Grant KTIA-OTKA CK-80745, NKFI_OTKA K-112228. C.I.
received support from the Nontherapeutic Subject Registry Shared Resource at George-
town University (NIH/NCI P30-CA-51008) and the Jess and Mildred Fisher Center for
Hereditary Cancer and Clinical Genomics Research. K.M. is supported by CRUK C18281/
A19169. City of Hope Clinical Cancer Community Research Network and the Hereditary
Cancer Research Registry, supported in part by Award Number RC4CA153828 (PI: J
Weitzel) from the National Cancer Institute and the office of the Directory, National
Institutes of Health. The content is solely the responsibility of the authors and does not
necessarily represent the official views of the National Institutes of Health. The colorectal
cancer genome-wide association analyses: Colorectal Transdisciplinary Study (CORECT):
The content of this manuscript does not necessarily reflect the views or policies of the
National Cancer Institute or any of the collaborating centers in the CORECT Consortium,
nor does mention of trade names, commercial products or organizations imply endor-
sement by the US Government or the CORECT Consortium. We are incredibly grateful
for the contributions of Dr. Brian Henderson and Dr. Roger Green over the course of this
study and acknowledge them in memoriam. We are also grateful for support from Daniel
and Maryann Fong. ColoCare: we thank the many investigators and staff who made this
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 13
research possible in ColoCare Seattle and ColoCare Heidelberg. ColoCare was initiated
and developed at the Fred Hutchinson Cancer Research Center by Drs. Ulrich and Grady.
CCFR: the Colon CFR graciously thanks the generous contributions of their study par-
ticipants, dedication of study staff, and financial support from the U.S. National Cancer
Institute, without which this important registry would not exist. Galeon: GALEON wishes
to thank the Department of Surgery of University Hospital of Santiago (CHUS), Sara
Miranda Ponte, Carmen M Redondo, and the staff of the Department of Pathology and
Biobank of CHUS, Instituto de Investigación Sanitaria de Santiago (IDIS), Instituto de
Investigación Sanitaria Galicia Sur (IISGS), SERGAS, Vigo, Spain, and Programa Grupos
Emergentes, Cancer Genetics Unit, CHUVI Vigo Hospital, Instituto de Salud Carlos III,
Spain. MCCS: this study was made possible by the contribution of many people, including
the original investigators and the diligent team who recruited participants and continue to
work on follow-up. We would also like to express our gratitude to the many thousands of
Melbourne residents who took part in the study and provided blood samples. SEARCH:
We acknowledge the contributions of Mitul Shah, Val Rhenius, Sue Irvine, Craig Luc-
carini, Patricia Harrington, Don Conroy, Rebecca Mayes, and Caroline Baynes. The
Swedish low-risk colorectal cancer study: we thank Berith Wejderot and the Swedish low-
risk colorectal cancer study group. Genetics & Epidemiology of Colorectal Cancer Con-
sortium (GECCO): we thank all those at the GECCO Coordinating Center for helping
bring together the data and people that made this project possible. ASTERISK: we are very
grateful to Dr. Bruno Buecher without whom this project would not have existed. We also
thank all those who agreed to participate in this study, including the patients and the
healthy control persons, as well as all the physicians, technicians and students. DACHS:
we thank all participants and cooperating clinicians, and Ute Handte-Daub, Renate
Hettler-Jensen, Utz Benscheid, Muhabbet Celik, and Ursula Eilber for excellent technical
assistance. HPFS, NHS and PHS: we acknowledge Patrice Soule and Hardeep Ranu of the
Dana-Farber Harvard Cancer Center High-Throughput Polymorphism Core who assisted
in the genotyping for NHS, HPFS, and PHS under the supervision of Dr. Immaculata
Devivo and Dr. David Hunter, Qin (Carolyn) Guo, and Lixue Zhu who assisted in
programming for NHS and HPFS and Haiyan Zhang who assisted in programming for
the PHS. We thank the participants and staff of the Nurses’ Health Study and the Health
Professionals Follow-Up Study, for their valuable contributions as well as the following
state cancer registries for their help: A.L., A.Z., A.R., C.A., C.O., C.T., D.E., F.L., G.A., I.D.,
I.L., I.N., I.A., K.Y., L.A., M.E., M.D., M.A., M.I., N.E., N.H., N.J., N.Y., N.C., N.D., O.H.,
O.K., O.R., P.A., R.I., S.C., T.N., T.X., V.A., W.A., W.Y. In addition, this study was
approved by the Connecticut Department of Public Health (DPH) Human Investigations
Committee. Certain data used in this publication were obtained from the DPH. We
assume full responsibility for analyses and interpretation of these data. PLCO: we thank
Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention, National Cancer
Institute, the Screening Center investigators and staff or the Prostate, Lung, Colorectal and
Ovarian (PLCO) Cancer Screening Trial, Mr. Tom Riley and staff, Information Man-
agement Services Inc., Ms. Barbara O’Brien and staff, Westat Inc. and Drs. Bill Kopp, Wen
Shao and staff, SAIC-Frederick. Most importantly, we acknowledge the study participants
for their contributions for making this study possible. The statements contained herein are
solely those of the authors and do not represent or imply concurrence or endorsement by
NCI. PMH: we thank the study participants and staff of the Hormones and Colon Cancer
study. WHI: we thank the WHI investigators and staff for their dedication, and the study
participants for making the program possible. A full listing of WHI investigators can be
found at https://cleo.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI
%20Investigator%20Short20List.pdf. CORECT: The CORECT Study was supported by the
National Cancer Institute, National Institutes of Health (NCI/NIH), U.S. Department of
Health and Human Services (grant numbers U19 CA148107, R01 CA81488, P30
CA014089, R01 CA197350; P01 CA196569; and R01 CA201407) and National Institutes
of Environmental Health Sciences, National Institutes of Health (grant number T32
ES013678). The ATBC Study was supported by the US Public Health Service contracts
(N01-CN-45165, N01-RC-45035, N01-RC-37004, and HHSN261201000006C) from the
National Cancer Institute. The Cancer Prevention Study-II Nutrition Cohort is funded by
the American Cancer Society. ColoCare: This work was supported by the National
Institutes of Health (grant numbers R01 CA189184, U01 CA206110, 2P30CA015704-40
(Gilliland)), the Matthias Lackas-Foundation, the German Consortium for Translational
Cancer Research, and the EU TRANSCAN initiative. Genetics and Epidemiology of
Colorectal Cancer Consortium (GECCO): funding for GECCO was provided by the
National Cancer Institute, National Institutes of Health, U.S. Department of Health and
Human Services (grant numbers U01 CA137088, R01 CA059045, and U01 CA164930).
This research was funded in part through the NIH/NCI Cancer Center Support Grant P30
CA015704. The Colon Cancer Family Registry (CFR) Illumina GWAS was supported by
funding from the National Cancer Institute, National Institutes of Health (grant numbers
U01 CA122839, R01 CA143247). The Colon CFR/CORECT Affymetrix Axiom GWAS
and OncoArray GWAS were supported by funding from National Cancer Institute,
National Institutes of Health (grant number U19 CA148107 to S.G.). The Colon CFR
participant recruitment and collection of data and biospecimens used in this study were
supported by the National Cancer Institute, National Institutes of Health (grant number
UM1 CA167551) and through cooperative agreements with the following Colon CFR
centers: Australasian Colorectal Cancer Family Registry (NCI/NIH grant numbers U01
CA074778 and U01/U24 CA097735), USC Consortium Colorectal Cancer Family Reg-
istry (NCI/NIH grant numbers U01/U24 CA074799), Mayo Clinic Cooperative Family
Registry for Colon Cancer Studies (NCI/NIH grant number U01/U24 CA074800),
Ontario Familial Colorectal Cancer Registry (NCI/NIH grant number U01/U24
CA074783), Seattle Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24
CA074794), and University of Hawaii Colorectal Cancer Family Registry (NCI/NIH grant
number U01/U24 CA074806), Additional support for case ascertainment was provided
from the Surveillance, Epidemiology and End Results (SEER) Program of the National
Cancer Institute to Fred Hutchinson Cancer Research Center (Control Nos. N01-CN-
67009 and N01-PC-35142, and Contract No. HHSN2612013000121), the Hawai’i
Department of Health (Control Nos. N01-PC-67001 and N01-PC-35137, and Contract
No. HHSN26120100037C, and the California Department of Public Health (contracts
HHSN261201000035C awarded to the University of Southern California, and the fol-
lowing state cancer registries: A.Z., C.O., M.N., N.C., N.H., and by the Victoria Cancer
Registry and Ontario Cancer Registry. ESTHER/VERDI was supported by grants from the
Baden–Württemberg Ministry of Science, Research and Arts and the German Cancer Aid.
MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria.
GALEON: FIS Intrasalud (PI13/01136). The MCCS was further supported by Australian
NHMRC grants 509348, 209057, 251553, and 504711 and by infrastructure provided by
Cancer Council Victoria. Cases and their vital status were ascertained through the Vic-
torian Cancer Registry (VCR) and the Australian Institute of Health and Welfare
(AIHW), including the National Death Index and the Australian Cancer Database.
MSKCC: the work at Sloan Kettering in New York was supported by the Robert and Kate
Niehaus Center for Inherited Cancer Genomics and the Romeo Milio Foundation. Moffitt:
This work was supported by funding from the National Institutes of Health (grant
numbers R01 CA189184, P30 CA076292), Florida Department of Health Bankhead-Coley
Grant 09BN-13, and the University of South Florida Oehler Foundation. Moffitt con-
tributions were supported in part by the Total Cancer Care Initiative, Collaborative Data
Services Core, and Tissue Core at the H. Lee Moffitt Cancer Center & Research Institute, a
National Cancer Institute-designated Comprehensive Cancer Center (grant number P30
CA076292). SEARCH: Cancer Research UK (C490/A16561). The Spanish study was
supported by Instituto de Salud Carlos III, co-funded by FEDER funds –a way to build
Europe– (grants PI14-613 and PI09-1286), Catalan Government DURSI (grant
2014SGR647), and Junta de Castilla y León (grant LE22A10-2). The Swedish Low-risk
Colorectal Cancer Study: the study was supported by grants from the Swedish research
council; K2015-55 × -22674-01-4, K2008-55 × -20157-03-3, K2006-72 × -20157-01-2 and
the Stockholm County Council (ALF project). CIDR genotyping for the Oncoarray was
conducted under contract 268201200008I (to K.D.), through grant 101HG007491-01 (to
C.I.A.). The Norris Cotton Cancer Center - P30CA023108, The Quantitative Biology
Research Institute - P20GM103534, and the Coordinating Center for Screen Detected
Lesions - U01CA196386 also supported efforts of C.I.A. This work was also supported by
the National Cancer Institute (grant numbers U01 CA1817700, R01 CA144040).
ASTERISK: a Hospital Clinical Research Program (PHRC) and supported by the Regional
Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte
contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue
Régionale Contre le Cancer (LRCC). COLO2&3: National Institutes of Health (grant
number R01 CA060987). DACHS: This work was supported by the German Research
Council (BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, CH 117/1-1, HO 5117/2-1, HE 5998/2-
1, KL 2354/3-1, RO 2270/8-1, and BR 1704/17-1), the Interdisciplinary Research Program
of the National Center for Tumor Diseases (NCT), Germany, and the German Federal
Ministry of Education and Research (01KH0404, 01ER0814, 01ER0815, 01ER1505A, and
01ER1505B). DALS: National Institutes of Health (grant number R01 CA048998 to M.L.
S). HPFS is supported by National Institutes of Health (grant numbers P01 CA055075,
UM1 CA167552, R01 137178, and P50 CA127003), NHS by the National Institutes of
Health (grant numbers UM1 CA186107, R01 CA137178, P01 CA087969, and P50
CA127003), NHSII by the National Institutes of Health (grant numbers R01 050385CA
and UM1 CA176726), and PHS by the National Institutes of Health (grant number R01
CA042182). MEC: National Institutes of Health (grant numbers R37 CA054281, P01
CA033619, and R01 CA063464). OFCCR: National Institutes of Health, through funding
allocated to the Ontario Registry for Studies of Familial Colorectal Cancer (grant number
U01 CA074783); see Colon CFR section above. As subset of ARCTIC, OFCCR is sup-
ported by a GL2 grant from the Ontario Research Fund, the Canadian Institutes of Health
Research, and the Cancer Risk Evaluation (CaRE) Program grant from the Canadian
Cancer Society Research Institute. T.J.H. and B.W.Z. are recipients of Senior Investigator
Awards from the Ontario Institute for Cancer Research, through generous support from
the Ontario Ministry of Research and Innovation. PLCO: Intramural Research Program of
the Division of Cancer Epidemiology and Genetics and supported by contracts from the
Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. Additionally, a
subset of control samples was genotyped as part of the Cancer Genetic Markers of
Susceptibility (CGEMS) Prostate Cancer GWAS, Colon CGEMS pancreatic cancer scan
(PanScan), and the Lung Cancer and Smoking study. The prostate and PanScan study
datasets were accessed with appropriate approval through the dbGaP online resource
(http://cgems.cancer.gov/data/) accession numbers phs000207.v1.p1 and phs000206.v3.
p2, respectively, and the lung datasets were accessed from the dbGaP website (http://www.
ncbi.nlm.nih.gov/gap) through accession number phs000093.v2.p2. Funding for the Lung
Cancer and Smoking study was provided by National Institutes of Health (NIH), Genes,
Environment and Health Initiative (GEI) Z01 CP 010200, NIH U01 HG004446, and NIH
GEI U01 HG 004438. For the lung study, the GENEVA Coordinating Center provided
assistance with genotype cleaning and general study coordination, 23 and the Johns
Hopkins University Center for Inherited Disease Research conducted genotyping.
PMH: National Institutes of Health (grant number R01 CA076366). VITAL: National
Institutes of Health (grant number K05-CA154337). WHI: The WHI program is funded
by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S.
Department of Health and Human Services through contracts HHSN268201600018C,
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
14 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN26
8201600004C. The head and neck cancer genome-wide association analyses: The study
was supported by NIH/NCI: P50 CA097190, and P30 CA047904, Canadian Cancer
Society Research Institute (no. 020214) and Cancer Care Ontario Research Chair to R.H.
The Princess Margaret Hospital Head and Neck Cancer Translational Research Program
is funded by the Wharton family, Joe’s Team, Gordon Tozer, Bruce Galloway and the Elia
family. Geoffrey Liu was supported by the Posluns Family Fund and the Lusi Wong
Family Fund at the Princess Margaret Foundation, and the Alan B. Brown Chair in
Molecular Genomics. This publication presents data from Head and Neck 5000
(H&N5000). H&N5000 was a component of independent research funded by the UK
National Institute for Health Research (NIHR) under its Programme Grants for Applied
Research scheme (RP-PG-0707-10034). The views expressed in this publication are those
of the author(s) and not necessarily those of the NHS, the NIHR or the Department of
Health. Human papillomavirus (HPV) in H&N5000 serology was supported by a Cancer
Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (grant
number: C18281/A19169). National Cancer Institute (R01-CA90731); National Institute
of Environmental Health Sciences (P30ES10126). The authors thank all the members of
the GENCAPO team/The Head and Neck Genome Project (GENCAPO) was supported
by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant
numbers 04/12054-9 and 10/51168-0). CPS-II recruitment and maintenance is supported
with intramural research funding from the American Cancer Society. Genotyping per-
formed at the Center for Inherited Disease Research (CIDR) was funded through the U.S.
National Institute of Dental and Craniofacial Research (NIDCR) grant 1 × 01HG007780-
0. The University of Pittsburgh head and neck cancer case-control study is supported by
National Institutes of Health grants P50 CA097190 and P30 CA047904. The Carolina
Head and Neck Cancer Study (CHANCE) was supported by the National Cancer Institute
(R01-CA90731). The Head and Neck Genome Project (GENCAPO) was supported by the
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/
12054-9 and 10/51168-0). The authors thank all the members of the GENCAPO team.
The HN5000 study was funded by the National Institute for Health Research (NIHR)
under its Programme Grants for Applied Research scheme (RP-PG-0707-10034), the
views expressed in this publication are those of the author(s) and not necessarily those of
the NHS, the NIHR or the Department of Health. The Toronto study was funded by the
Canadian Cancer Society Research Institute (020214) and the National Cancer Institute
(U19-CA148127) and the Cancer Care Ontario Research Chair. The alcohol-related
cancers and genetic susceptibility study in Europe (ARCAGE) was funded by the Eur-
opean Commission’s 5th Framework Program (QLK1-2001-00182), the Italian Associa-
tion for Cancer Research, Compagnia di San Paolo/FIRMS, Region Piemonte, and Padova
University (CPDA057222). The Rome Study was supported by the Associazione Italiana
per la Ricerca sul Cancro (AIRC) IG 2011 10491 and IG2013 14220 to S.B., and Fon-
dazione Veronesi to S.B. The IARC Latin American study was funded by the European
Commission INCO-DC programme (IC18-CT97-0222), with additional funding from
Fondo para la Investigacion Cientifica y Tecnologica (Argentina) and the Fundação de
Amparo à Pesquisa do Estado de São Paulo (01/01768-2). We thank Leticia Fernandez,
Instituto Nacional de Oncologia y Radiobiologia, La Habana, Cuba and Sergio and
Rosalina Koifman, for their efforts with the IARC Latin America study São Paulo center.
The IARC Central Europe study was supported by European Commission’s INCO-
COPERNICUS Program (IC15- CT98-0332), NIH/National Cancer Institute grant
CA92039, and the World Cancer Research Foundation grant WCRF 99A28. The IARC
Oral Cancer Multicenter study was funded by grant S06 96 202489 05F02 from Europe
against Cancer; grants FIS 97/0024, FIS 97/0662, and BAE 01/5013 from Fondo de
Investigaciones Sanitarias, Spain; the UICC Yamagiwa-Yoshida Memorial International
Cancer Study; the National Cancer Institute of Canada; Associazione Italiana per la
Ricerca sul Cancro; and the Pan-American Health Organization. Coordination of the
EPIC study is financially supported by the European Commission (DG-SANCO) and the
International Agency for Research on Cancer. The lung cancer genome-wide association
analyses: Transdisciplinary Research for Cancer in Lung (TRICL) of the International
Lung Cancer Consortium (ILCCO) was supported by (U19-CA148127, CA148127S1,
U19CA203654, and Cancer Prevention Research Institute of Texas RR170048). The
ILCCO data harmonization is supported by Cancer Care Ontario Research Chair of
Population Studies to R. H. and Lunenfeld-Tanenbaum Research Institute, Sinai Health
System. The TRICL-ILCCO OncoArray was supported by in-kind genotyping by the
Centre for Inherited Disease Research (26820120008i-0-26800068-1). The CAPUA study
was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-
07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and
the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber
de Epidemiologia y Salud Pública. CIBERESP, SPAIN. The work performed in the
CARET study was supported by the National Institute of Health/National Cancer Insti-
tute: UM1 CA167462 (PI: Goodman), National Institute of Health UO1-CA6367307 (PIs
Omen, Goodman); National Institute of Health R01 CA111703 (PI Chen), National
Institute of Health 5R01 CA151989-01A1(PI Doherty). The Liverpool Lung project is
supported by the Roy Castle Lung Cancer Foundation. The Harvard Lung Cancer Study
was supported by the NIH (National Cancer Institute) grants CA092824, CA090578,
CA074386. The Multi-ethnic Cohort Study was partially supported by NIH Grants
CA164973, CA033619, CA63464, and CA148127. The work performed in MSH-PMH
study was supported by The Canadian Cancer Society Research Institute (020214),
Ontario Institute of Cancer and Cancer Care Ontario Chair Award to R.J.H. and G.L. and
the Alan Brown Chair and Lusi Wong Programs at the Princess Margaret Hospital
Foundation. NJLCS was funded by the State Key Program of National Natural Science of
China (81230067), the National Key Basic Research Program Grant (2011CB503805), the
Major Program of the National Natural Science Foundation of China (81390543). The
Norway study was supported by Norwegian Cancer Society, Norwegian Research Council.
The Shanghai Cohort Study (SCS) was supported by National Institutes of Health R01
CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The Singapore Chinese Health
Study (SCHS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan)
and UM1 CA182876 (PI: Yuan). The work in TLC study has been supported in part the
James & Esther King Biomedical Research Program (09KN-15), National Institutes of
Health Specialized Programs of Research Excellence (SPORE) Grant (P50 CA119997),
and by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and
Research Institute, an NCI designated Comprehensive Cancer Center (grant number P30-
CA76292). The Vanderbilt Lung Cancer Study—BioVU dataset used for the analyses
described was obtained from Vanderbilt University Medical Center’s BioVU, which is
supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by
the Vanderbilt CTSA grant UL1TR000445 from NCATS/NIH. Dr. Aldrich was supported
by NIH/National Cancer Institute K07CA172294 (PI: Aldrich) and Dr. Bush was sup-
ported by NHGRI/NIH U01HG004798 (PI: Crawford). The Copenhagen General
Population Study (CGPS) was supported by the Chief Physician Johan Boserup and Lise
Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The NELCS
study: Grant Number P20RR018787 from the National Center for Research Resources
(NCRR), a component of the National Institutes of Health (NIH). The Kentucky Lung
Cancer Research Initiative was supported by the Department of Defense [Congressionally
Directed Medical Research Program, U.S. Army Medical Research and Materiel Com-
mand Program] under award number: 10153006 (W81XWH-11-1-0781). Views and
opinions of, and endorsements by the author(s) do not reflect those of the US Army or the
Department of Defense. This research was also supported by unrestricted infrastructure
funds from the UK Center for Clinical and Translational Science, NIH grant
UL1TR000117 and Markey Cancer Center NCI Cancer Center Support Grant (P30
CA177558) Shared Resource Facilities: Cancer Research Informatics, Biospecimen and
Tissue Procurement, and Biostatistics and Bioinformatics. The M.D. Anderson Cancer
Center study was supported in part by grants from the NIH (P50 CA070907, R01
CA176568) (to X.W.), Cancer Prevention & Research Institute of Texas (RP130502) (to X.
W.), and The University of Texas MD Anderson Cancer Center institutional support for
the Center for Translational and Public Health Genomics. The deCODE study of smoking
and nicotine dependence was funded in part by a grant from NIDA (R01- DA017932).
The study in Lodz center was partially funded by Nofer Institute of Occupational Med-
icine, under task NIOM 10.13: Predictors of mortality from non-small cell lung cancer—
field study. Genetic sharing analysis was funded by NIH grant CA194393. The research
undertaken by M.D.T., L.V.W., and M.S.A. was partly funded by the National Institute for
Health Research (NIHR). The views expressed are those of the author(s) and not
necessarily those of the NHS, the NIHR or the Department of Health. M.D.T. holds a
Medical Research Council Senior Clinical Fellowship (G0902313). The work to assemble
the FTND GWAS meta-analysis was supported by the National Institutes of Health
(NIH), National Institute on Drug Abuse (NIDA) grant number R01 DA035825 (Prin-
cipal Investigator [PI]: DBH). The study populations included COGEND (dbGaP
phs000092.v1.p1 and phs000404.v1.p1), COPDGene (dbGaP phs000179.v3.p2), deCODE
Genetics, EAGLE (dbGaP phs000093.vs.p2), and SAGE. dbGaP phs000092.v1.p1). See
Hancock et al. Transl Psychiatry 2015 (PMCID: PMC4930126) for the full listing of
funding sources and other acknowledgments. The Resource for the Study of Lung Cancer
Epidemiology in North Trent (ReSoLuCENT)study was funded by the Sheffield Hospitals
Charity, Sheffield Experimental Cancer Medicine Centre and Weston Park Hospital
Cancer Charity. The ovarian cancer genome-wide association analysis: The Ovarian
Cancer Association Consortium (OCAC) is supported by a grant from the Ovarian
Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek
Smith (PPD/RPCI.07). The scientific development and funding for this project were in
part supported by the US National Cancer Institute GAME-ON Post-GWAS Initiative
(U19-CA148112). This study made use of data generated by the Wellcome Trust Case
Control consortium that was funded by the Wellcome Trust under award 076113. The
results published here are in part based upon data generated by The Cancer Genome Atlas
Pilot Project established by the National Cancer Institute and National Human Genome
Research Institute (dbGap accession number phs000178.v8.p7). The OCAC OncoArray
genotyping project was funded through grants from the U.S. National Institutes of Health
(CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.), and
R01-CA058598 (M.T.G.); Canadian Institutes of Health Research (MOP-86727 (L.E.K.)
and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a
European Commission’s Seventh Framework Programme grant (agreement number
223175 - HEALTH-F2-2009-223175) and through a grant from the U.S. National Insti-
tutes of Health (R01-CA122443 (E.L.G)). Funding for individual studies: AAS: National
Institutes of Health (RO1-CA142081); AOV: The Canadian Institutes for Health Research
(MOP-86727); AUS: The Australian Ovarian Cancer Study Group was supported by the
U.S. Army Medical Research and Materiel Command (DAMD17-01-1-0729), National
Health & Medical Research Council of Australia (199600, 400413 and 400281),
Cancer Councils of New South Wales, Victoria, Queensland, South Australia and Tas-
mania and Cancer Foundation of Western Australia (Multi-State Applications 191,
211, and 182). The Australian Ovarian Cancer Study gratefully acknowledges additional
support from Ovarian Cancer Australia and the Peter MacCallum Foundation; BAV:
ELAN Funds of the University of Erlangen-Nuremberg; BEL: National Kankerplan; BGS:
Breast Cancer Now, Institute of Cancer Research; BVU: Vanderbilt CTSA grant from the
National Institutes of Health (NIH)/National Center for Advancing Translational Sciences
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 15
(NCATS) (ULTR000445); CAM: National Institutes of Health Research Cambridge
Biomedical Research Centre and Cancer Research UK Cambridge Cancer Centre; CHA:
Innovative Research Team in University (PCSIRT) in China (IRT1076); CNI: Instituto de
Salud Carlos III (PI12/01319); Ministerio de Economía y Competitividad (SAF2012);
COE: Department of Defense (W81XWH-11-2-0131); CON: National Institutes of Health
(R01-CA063678, R01-CA074850; and R01-CA080742); DKE: Ovarian Cancer Research
Fund; DOV: National Institutes of Health R01-CA112523 and R01-CA87538; EMC:
Dutch Cancer Society (EMC 2014-6699); EPC: The coordination of EPIC is financially
supported by the European Commission (DG-SANCO) and the International Agency for
Research on Cancer. The national cohorts are supported by Danish Cancer Society
(Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de
l’Education Nationale, Institut National de la Santé et de la Recherche Médicale
(INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ),
Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health
Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and
National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports
(VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention
Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF),
Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic
Centre of Excellence programme on Food, Nutrition and Health (Norway); Health
Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional
Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC
(RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County
Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-
Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council
(1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom); GER:
German Federal Ministry of Education and Research, Programme of Clinical Biomedical
Research (01 GB 9401) and the German Cancer Research Center (DKFZ); GRC: This
research has been co-financed by the European Union (European Social Fund—ESF) and
Greek national funds through the Operational Program “Education and Lifelong Learn-
ing” of the National Strategic Reference Framework (NSRF)—Research Funding Program
of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in
knowledge society through the European Social Fund; GRR: Roswell Park Cancer Institute
Alliance Foundation, P30 CA016056; HAW: U.S. National Institutes of Health (R01-
CA58598, N01-CN-55424, and N01-PC-67001); HJO: Intramural funding; Rudolf-
Bartling Foundation; HMO: Intramural funding; Rudolf-Bartling Foundation; HOC:
Helsinki University Research Fund; HOP: Department of Defense (DAMD17-02-1-0669)
and NCI (K07-CA080668, R01-CA95023, P50-CA159981 MO1-RR000056 R01-
CA126841); HUO: Intramural funding; Rudolf-Bartling Foundation; JGO: JSPS
KAKENHI grant; JPN: Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy
for Cancer Control from the Ministry of Health, Labour and Welfare; KRA: This study
(Ko-EVE) was supported by a grant from the Korea Health Technology R&D Project
through the Korea Health Industry Development Institute (KHIDI), and the National
R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea
(HI16C1127; 0920010); LAX: American Cancer Society Early Detection Professorship
(SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences
(NCATS), Grant UL1TR000124; LUN: ERC-2011-AdG 294576-risk factors cancer,
Swedish Cancer Society, Swedish Research Council, Beta Kamprad Foundation; MAC:
National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo
Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen
Foundation; Fraternal Order of Eagles; MAL: Funding for this study was provided by
research grant R01- CA61107 from the National Cancer Institute, Bethesda, MD, research
grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mer-
maid I project; MAS: Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06)
and Cancer Research Initiatives Foundation; MAY: National Institutes of Health (R01-
CA122443, P30-CA15083, and P50-CA136393); Mayo Foundation; Minnesota Ovarian
Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; MCC: Cancer Council
Victoria, National Health and Medical Research Council of Australia (NHMRC) grants
number 209057, 251533, 396414, and 504715; MDA: DOD Ovarian Cancer Research
Program (W81XWH-07-0449); MEC: NIH (CA54281, CA164973, CA63464); MOF:
Moffitt Cancer Center, Merck Pharmaceuticals, the state of Florida, Hillsborough County,
and the city of Tampa; NCO: National Institutes of Health (R01-CA76016) and the
Department of Defense (DAMD17-02-1-0666); NEC: National Institutes of Health R01-
CA54419 and P50-CA105009 and Department of Defense W81XWH-10-1-02802; NHS:
UM1 CA186107, P01 CA87969, R01 CA49449, R01-CA67262, UM1 CA176726; NJO:
National Cancer Institute (NIH-K07 CA095666, R01-CA83918, NIH-K22-CA138563, and
P30-CA072720) and the Cancer Institute of New Jersey; If Sara Olson and/or Irene Orlow
is a co-author, please add NCI CCSG award (P30-CA008748) to the funding sources;
NOR: Helse Vest, The Norwegian Cancer Society, The Research Council of Norway;
NTH: Radboud University Medical Centre; OPL: National Health and Medical Research
Council (NHMRC) of Australia (APP1025142) and Brisbane Women’s Club; ORE:
OHSU Foundation; OVA: This work was supported by Canadian Institutes of Health
Research grant (MOP-86727) and by NIH/NCI 1 R01CA160669-01A1; PLC: Intramural
Research Program of the National Cancer Institute; POC: Pomeranian Medical Uni-
versity; POL: Intramural Research Program of the National Cancer Institute; PVD:
Canadian Cancer Society and Cancer Research Society GRePEC Program; RBH: National
Health and Medical Research Council of Australia; RMH: Cancer Research UK, Royal
Marsden Hospital; RPC: National Institute of Health (P50-CA159981, R01-CA126841);
SEA: Cancer Research UK (C490/A10119 C490/A10124); UK National Institute for
Health Research Biomedical Research Centres at the University of Cambridge; SIS: NIH,
National Institute of Environmental Health Sciences, Z01-ES044005 and Z01-ES049033;
SMC: The bbSwedish Research Council-SIMPLER infrastructure; the Swedish Cancer
Foundation; SON: National Health Research and Development Program, Health Canada,
grant 6613-1415-53; SRO: Cancer Research UK (C536/A13086, C536/A6689) and
Imperial Experimental Cancer Research Centre (C1312/A15589); STA: NIH grants U01
CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and
VårKampMotCancer foundation; SWH: NIH (NCI) grant R37-CA070867; TBO: National
Institutes of Health (R01-CA106414-A2), American Cancer Society (CRTG-00-196-01-
CCE), Department of Defense (DAMD17-98-1-8659), Celma Mastery Ovarian Cancer
Foundation; TOR: NIH grants R01-CA063678 and R01 CA063682; UCI: NIH R01-
CA058860 and the Lon V Smith Foundation grant LVS39420; UHN: Princess Margaret
Cancer Centre Foundation-Bridge for the Cure; UKO: The UKOPS study was funded by
The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health
Research University College London Hospitals Biomedical Research Centre; UKR: Cancer
Research UK (C490/A6187), UK National Institute for Health Research Biomedical
Research Centres at the University of Cambridge; USC: P01CA17054, P30CA14089,
R01CA61132, N01PC67010, R03CA113148, R03CA115195, N01CN025403, and Cali-
fornia Cancer Research Program (00-01389V-20170, 2II0200); VAN: BC Cancer Foun-
dation, VGH & UBC Hospital Foundation; VTL: NIH K05-CA154337; WMH: National
Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID
628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16; WOC: National
Science Centren (N N301 5645 40). The Maria Sklodowska-Curie Memorial Cancer
Center and Institute of Oncology, Warsaw, Poland. The University of Cambridge has
received salary support for PDPP from the NHS in the East of England through the
Clinical Academia Reserve. The prostate cancer genome-wide association analyses: we pay
tribute to Brian Henderson, who was a driving force behind the OncoArray project, for his
vision and leadership, and who sadly passed away before seeing its fruition. We also thank
the individuals who participated in these studies enabling this work. The ELLIPSE/
PRACTICAL (http//:practical.icr.ac.uk) prostate cancer consortium and his collaborating
partners were supported by multiple funding mechanisms enabling this current work.
ELLIPSE/PRACTICAL Genotyping of the OncoArray was funded by the US National
Institutes of Health (NIH) (U19 CA148537 for ELucidating Loci Involved in Prostate
Cancer SuscEptibility (ELLIPSE) project and X01HG007492 to the Center for Inherited
Disease Research (CIDR) under contract number HHSN268201200008I). Additional
analytical support was provided by NIH NCI U01 CA188392 (F.R.S.). Funding for the
iCOGS infrastructure came from the European Community’s Seventh Framework Pro-
gramme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer
Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/
A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the National Institutes of
Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19
CA148065, and 1U19 CA148112; the GAME-ON initiative), the Department of Defense
(W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR
Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast
Cancer Research Foundation, and the Ovarian Cancer Research Fund. This work was
supported by the Canadian Institutes of Health Research, European Commission’s
Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175),
Cancer Research UK Grants C5047/A7357, C1287/A10118, C1287/A16563, C5047/
A3354, C5047/A10692, C16913/A6135, C5047/A21332 and The National Institute of
Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA148537-01 (the
GAME-ON initiative). We also thank the following for funding support: The Institute of
Cancer Research and The Everyman Campaign, The Prostate Cancer Research Founda-
tion, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal,
The National Cancer Research Network UK, and The National Cancer Research Institute
(NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical
Research Centre at The Institute of Cancer Research and The Royal Marsden NHS
Foundation Trust. The Prostate Cancer Program of Cancer Council Victoria also
acknowledge grant support from The National Health and Medical Research Council,
Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204,
940394, and 614296), VicHealth, Cancer Council Victoria, The Prostate Cancer Foun-
dation of Australia, The Whitten Foundation, PricewaterhouseCoopers, and Tattersall’s.
E.A.O., D.M.K., and E.M.K. acknowledge the Intramural Program of the National Human
Genome Research Institute for their support. The BPC3 was supported by the U.S.
National Institutes of Health, National Cancer Institute (cooperative agreements U01-
CA98233 to D.J.H., U01-CA98710 to S.M.G., U01-CA98216 to E.R., and U01-CA98758 to
B.E.H., and Intramural Research Program of NIH/National Cancer Institute, Division of
Cancer Epidemiology and Genetics). CAPS GWAS study was supported by the Swedish
Cancer Foundation (grant no 09-0677, 11-484, 12-823), the Cancer Risk Prediction
Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed
by the Swedish Research Council, Swedish Research Council (grant no K2010-70 × -
20430-04-3, 2014-2269). The Hannover Prostate Cancer Study was supported by the
Lower Saxonian Cancer Society. PEGASUS was supported by the Intramural Research
Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute,
National Institutes of Health. RAPPER was supported by the NIHR Manchester Bio-
medical Research Center, Cancer Research UK (C147/A25254, C1094/A18504) and the
EU’s 7th Framework Programme Grant/Agreement no 60186. Overall: this research has
been conducted using the UK Biobank Resource (application number 16549). NHS is
supported by UM1 CA186107 (NHS cohort infrastructure grant), P01 CA87969, and R01
CA49449. NHSII is supported by UM1 CA176726 (NHSII cohort infrastructure grant),
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
16 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
and R01-CA67262. A.L.K. is supported by R01 MH107649. We would like to thank the
participants and staff of the NHS and NHSII for their valuable contributions as well as the
following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID,
IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI,
SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and
interpretation of these data.
Author Contribution
All authors reviewed and commented on the manuscript, as well as approved the sub-
mission. Writing group: X.J., H.K.F., F.R.S., S.L.S., J.P.T., Y. Han., K. Michailidou, C.L.,
K.B.K., J.D., D.V.C., G. Casey, M.M.G., J. Huyghe, D. Thomas, R.J. Hung, B.D., J.M.,
U.P., L.H., M. Garcia-Closas, R.A.E., G. Chenevix-Trench, P.J.B., C.A.H., J. Schleutker,
D.F.E., S.B.G., P.D.P., A.L.P., B.P., C.I.A., P.K., S. Lindström. Interpret results: A.A.,
I.L.A., A.C.A., N.N.A., S.A., B.K.A., R.B.B., J. Batra, A.B., S.I.B., S.A.B., C.B., S.E.B.,
M.K.B., J. Benitez, R.B., G. Cadoni, T.C., P.T.C., G. Cancel-Tassin, D.C., A.T.C.,
J. Chang-Claude, D.C.C., J.M. Collee, F.J.C., A.C., J.M. Cunningham, C. Chen, M.B.D.,
P.D., O.D., J.L.D., T.D., E.D., C.K.E., D.V.E., D.G.E., P.A.F., R.T.F., F.F., S.F., E.F.,
J. Garber, S.A.G., G.G.G., D.E.G., M.T.G., G.G., K.G., P.G., U.H., J. Huyghe, F.H.,
R. Herrero, P. Hall, M.H., D.G.H., G.I., E.N.I., C.I., P.J., M.A. Jakubowska, A. Joshi,
L.E.K., T.K., E.K., A.S.K., L.A.K., J. Kim, M.K., V.N.K., P.L., N.D.L., F. Loupakis, H.L.,
G. Liu, D. Lambrechts, D.A.L., C.I.L., A.L., N.M.L., G. Leslie, J. Lester, L. Maehle, C.M.,
L.L.M., S.M., L. McGuffog, A. Mannermaa, P.M., F.M., M.M., V.M., K.B.M., L. Mucci,
K. Muir, F.C.N., B.G.N., R.L.N., K.O., O.I.O., H.O., A.O., H.P., J.Y.P., M.T.P., T.P.,
C.M.P., A.I.P., D. Plaseska-Karanfilska, M.P., K. Stefansson, S.J.R., L.R., H.S.R.,
M.J. Riggan, M.A.R., K.D.R., E.S., E.J.S., M.B.S., M.K.S., V.W.S., E.M.S., M.L.S., K.D.S.,
M.C.S., A.B.S., V.L.S., S.S., J. Stone, K. Sundfeldt, A.T., J.A.T., M.R.T., M.B.T., K.L.T., L.B.,
A.E.T., P.A.T., R.C.T., N.T., C.V., A.V., Q.W., S.W., J.N.W., E.W., A.S.W., F.W., R.W.,
X.W., D.Y., W.Z., A.Z., J.M.L. Oversee consortium dataset: F.R.S., M.K.B., J.M.L.,
R. Saxena, R.J. Hung, U.P., R.A.E., G. Chenevix-Trench, D.F.E., S.B.G., C.I.A.,
P.K. Develop and review the analysis plan and statistical analysis: X.J., H.K.F., A.L.P.,
B.P., C.I.A., P.K., S. Lindström. Design and manage individual study: D.A., M.C.A.,
I.L.A., H.A.-C., N.N.A., K.J.A., E.V.B., D.D.B., J. Brenton, M.W.B., S. Benlloch,
H. Bickeboller, S. Boccia, N.V.B., H. Brauch, H. Brenner, J. Brunet, M.B., H. Brunnstrom,
D.R.B., B.B., M.A.C., I.C., L.C., N.C., A.L.C., J. Clements, S.J.C., C. Cybulski, K.B.C., F.C.,
J. Chang-Claude, M.C.C., K.C., A.d., M. Gago-Dominguez, J.L.D., A.M.D., M.D., D.M.E.,
C.E., R.L.F., T.L., J.C.F., O.F., S.J.G., P.A.G., J.A.G., G.G.G., A.K.G., M.S.G., E.L.G.,
M.T.G., K.G., M.H.G., H.G., J. Gronwald, N.H., P. Hillemanns, F.C.H., R.J. Hamilton,
J. Hampe, A.H., E.H., Y. Hong, J.L.H., R. Houlston, P.J.H., D.J.H., E.N.I., S.A.I., A.J., P.J.,
Mattias. Johansson, Mikael. Johansson, E.M.J., R.K., B.Y.K., K.K., S.K.K., J.A.K., Z.K.,
S.K., J. Kupryjanczyk, M.L., S. Lam, D. Lessel, M.T.L., E.L., J. Lubinski, L.L., F. Lejbko-
wicz, J. Lubinski, A. Meindl, T.M., P.M., A. Miller, R.L.M., R.J.M., M.M., A.M.M., K.L.N.,
D.E.N., A.R.N., S.L.N., H.N., P.A.N., L.F.N., L.N., K.O., E.O., A.A.A.O., O.I.O., A.F.O.,
H.P., J.Y.P., N.P., K.L.P., W.H.P., C.M.P., D. Prokofieva, P.R., G.R., E.J.v.R., H.A.R., A.R.,
M.J. Roobol, B.R., K.D.R., D.P.S., J. Simard, V.W.S., H.S., E.M.S., W.S., C.F.S., J.L.S.,
V.L.S., R. Sutphen, A.J.S., E.H.T., C.M.T., M.D.T., S.N.T., M. Thomassen, M.
Tischkowitz, D. Torres, S.S.T., C.M.U., N.U., E.V.N., M.E.A., P.M.W., C.R.W., S.W.,
M.C.W., C.W., H.W., F.W., A.W., P.W., M.W., A.H.W., X.W., S.Z., K.K.Z., R. Saxena.
Additional information
Supplementary Information accompanies this paper at https://doi.org/10.1038/s41467-
018-08054-4.
Competing interests: The authors declare no competing interests.
Reprints and permission information is available online at http://npg.nature.com/
reprintsandpermissions/
Journal peer review information: Nature Communications thanks the anonymous
reviewers for their contribution to the peer review of this work. Peer reviewer reports are
available.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative
Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the article’s Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
article’s Creative Commons license and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this license, visit http://creativecommons.org/
licenses/by/4.0/.
© The Author(s) 2019
Xia Jiang1,2, Hilary K. Finucane 3,4, Fredrick R. Schumacher 5,6, Stephanie L. Schmit 7,8, Jonathan P. Tyrer9,
Younghun Han10, Kyriaki Michailidou 11,12, Corina Lesseur13,14, Karoline B. Kuchenbaecker 15,16, Joe Dennis 11,
David V. Conti17, Graham Casey18,19, Mia M. Gaudet20, Jeroen R. Huyghe 21, Demetrius Albanes22,
Melinda C. Aldrich23, Angeline S. Andrew24, Irene L. Andrulis 25,26, Hoda Anton-Culver27,
Antonis C. Antoniou11, Natalia N. Antonenkova28, Susanne M. Arnold 29, Kristan J. Aronson30, Banu K. Arun31,
Elisa V. Bandera32, Rosa B. Barkardottir33,34, Daniel R. Barnes 11, Jyotsna Batra 35,36, Matthias W. Beckmann37,
Javier Benitez38,39, Sara Benlloch11,40, Andrew Berchuck41, Sonja I. Berndt22, Heike Bickeböller42,
Stephanie A. Bien21,43, Carl Blomqvist44,45, Stefania Boccia46,47, Natalia V. Bogdanova28,48,49,
Stig E. Bojesen 50,51,52, Manjeet K. Bolla11, Hiltrud Brauch 53,54,55, Hermann Brenner55,56,57,
James D. Brenton 58, Mark N. Brook 40, Joan Brunet 59, Hans Brunnström 60,61,
Daniel D. Buchanan 62,63,64, Barbara Burwinkel65,66, Ralf Butzow67, Gabriella Cadoni46,47, Trinidad Caldés68,
Maria A. Caligo69, Ian Campbell 70,71, Peter T. Campbell20, Géraldine Cancel-Tassin 72,73,
Lisa Cannon-Albright74,75, Daniele Campa76,77, Neil Caporaso22, André L. Carvalho78,79, Andrew T. Chan 80,81,
Jenny Chang-Claude76,82, Stephen J. Chanock 22, Chu Chen83, David C. Christiani3, Kathleen B.M. Claes 84,
Frank Claessens85, Judith Clements35,36, J. Margriet Collée86, Marcia Cruz Correa87, Fergus J. Couch88,
Angela Cox89, Julie M. Cunningham 88, Cezary Cybulski90, Kamila Czene91, Mary B. Daly92, Anna deFazio93,94,
Peter Devilee 95,96, Orland Diez97, Manuela Gago-Dominguez98,99, Jenny L. Donovan100, Thilo Dörk49,
Eric J. Duell101, Alison M. Dunning9, Miriam Dwek102, Diana M. Eccles103, Christopher K. Edlund104,
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 17
Digna R Velez Edwards105, Carolina Ellberg 106, D. Gareth Evans107, Peter A. Fasching 37,108,
Robert L. Ferris109, Triantafillos Liloglou 110, Jane C. Figueiredo111,112, Olivia Fletcher 113, Renée T. Fortner76,
Florentia Fostira114, Silvia Franceschi115, Eitan Friedman116,117, Steven J. Gallinger118,119,120, Patricia A. Ganz121,
Judy Garber122, José A. García-Sáenz 68, Simon A. Gayther123,124,125, Graham G. Giles126,127,128,
Andrew K. Godwin129, Mark S. Goldberg130,131, David E. Goldgar132, Ellen L. Goode133, Marc T. Goodman134,135,
Gary Goodman136, Kjell Grankvist 137, Mark H. Greene 138, Henrik Gronberg 91, Jacek Gronwald90,
Pascal Guénel 139, Niclas Håkansson140, Per Hall91,141, Ute Hamann142, Freddie C. Hamdy143,
Robert J. Hamilton144, Jochen Hampe 145, Aage Haugen146, Florian Heitz147,148, Rolando Herrero149,
Peter Hillemanns49, Michael Hoffmeister56, Estrid Høgdall150,151, Yun-Chul Hong152, John L. Hopper127,
Richard Houlston 153, Peter J. Hulick 154,155, David J. Hunter1, David G. Huntsman156,157,158, Gregory Idos17,
Evgeny N. Imyanitov159, Sue Ann Ingles17, Claudine Isaacs160, Anna Jakubowska90,161, Paul James 71,162,
Mark A. Jenkins 62,127, Mattias Johansson14, Mikael Johansson163, Esther M. John164, Amit D. Joshi 3,165,
Radka Kaneva166, Beth Y. Karlan167, Linda E. Kelemen168, Tabea Kühl169, Kay-Tee Khaw170,
Elza Khusnutdinova171,172, Adam S. Kibel173, Lambertus A. Kiemeney174, Jeri Kim175, Susanne K. Kjaer150,176,
Julia A. Knight177,178, Manolis Kogevinas39,179,180,181, Zsofia Kote-Jarai40, Stella Koutros182,
Vessela N. Kristensen183,184,185, Jolanta Kupryjanczyk186, Martin Lacko187, Stephan Lam188,
Diether Lambrechts 189,190, Maria Teresa Landi191, Philip Lazarus192, Nhu D. Le193, Eunjung Lee123,
Flavio Lejbkowicz194, Heinz-Josef Lenz104, Goska Leslie 11, Davor Lessel 195, Jenny Lester167,
Douglas A. Levine 196,197, Li Li198,199, Christopher I. Li200, Annika Lindblom201, Noralane M. Lindor202,
Geoffrey Liu203, Fotios Loupakis204, Jan Lubiński90, Lovise Maehle205, Christiane Maier206,
Arto Mannermaa207,208,209, Loic Le Marchand210, Sara Margolin211, Taymaa May212, Lesley McGuffog11,
Alfons Meindl213, Pooja Middha76,214, Austin Miller 215, Roger L. Milne 126,127, Robert J. MacInnis126,127,
Francesmary Modugno216,217, Marco Montagna218, Victor Moreno 219, Kirsten B. Moysich220, Lorelei Mucci3,
Kenneth Muir 221,222, Anna Marie Mulligan223,224, Katherine L. Nathanson 225, David E. Neal58,143,226,
Andrew R. Ness227, Susan L. Neuhausen228, Heli Nevanlinna 229, Polly A. Newcomb 21,43,
Lisa F. Newcomb21,230, Finn Cilius Nielsen231, Liene Nikitina-Zake 232, Børge G. Nordestgaard 50,51,52,
Robert L. Nussbaum233, Kenneth Offit234,235, Edith Olah236, Ali Amin Al Olama 11,237,
Olufunmilayo I. Olopade 238, Andrew F. Olshan239,240, Håkan Olsson106, Ana Osorio38,39, Hardev Pandha241,
Jong Y. Park242, Nora Pashayan 243,244, Michael T. Parsons 245, Tanja Pejovic246,247, Kathryn L. Penney81,
Wilbert H M. Peters248, Catherine M. Phelan242, Amanda I. Phipps21,249, Dijana Plaseska-Karanfilska 250,
Miranda Pring251, Darya Prokofyeva171, Paolo Radice252, Kari Stefansson253, Susan J. Ramus254,255,
Leon Raskin 256, Gad Rennert 257, Hedy S. Rennert257, Elizabeth J. van Rensburg258, Marjorie J. Riggan41,
Harvey A. Risch259, Angela Risch 260,261,262, Monique J. Roobol 263, Barry S. Rosenstein264,265,
Mary Anne Rossing83,266, Kim De Ruyck267, Emmanouil Saloustros 268, Dale P. Sandler269, Elinor J. Sawyer270,
Matthew B. Schabath 242, Johanna Schleutker 271,272,273, Marjanka K. Schmidt 274,275,
V. Wendy Setiawan276, Hongbing Shen277, Erin M. Siegel7, Weiva Sieh278, Christian F. Singer279,
Martha L. Slattery280, Karina Dalsgaard Sorensen 281,282, Melissa C. Southey283,284, Amanda B. Spurdle245,
Janet L. Stanford21,249, Victoria L. Stevens20, Sebastian Stintzing 285, Jennifer Stone 127,286, Karin Sundfeldt287,
Rebecca Sutphen288, Anthony J. Swerdlow40,289, Eloiza H. Tajara290,291, Catherine M. Tangen292,
Adonina Tardon 293, Jack A. Taylor269,294, M. Dawn Teare295, Manuel R. Teixeira 296,297, Mary Beth Terry298,
Kathryn L. Terry299,300, Stephen N. Thibodeau88, Mads Thomassen301, Line Bjørge302,303,
Marc Tischkowitz304,305, Amanda E. Toland 306, Diana Torres142,307, Paul A. Townsend308, Ruth C. Travis309,
Nadine Tung310, Shelley S. Tworoger3,242, Cornelia M. Ulrich21,311, Nawaid Usmani312,313, Celine M. Vachon133,
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
18 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
Els Van Nieuwenhuysen314, Ana Vega39,315, Miguel Elías Aguado-Barrera 315, Qin Wang11,
Penelope M. Webb 316, Clarice R. Weinberg317, Stephanie Weinstein22, Mark C. Weissler318,
Jeffrey N. Weitzel319, Catharine M.L. West320, Emily White321,322, Alice S. Whittemore323,324,
H-Erich Wichmann325,326,327, Fredrik Wiklund91, Robert Winqvist328,329, Alicja Wolk 140,330, Penella Woll331,
Michael Woods332, Anna H. Wu123, Xifeng Wu333, Drakoulis Yannoukakos 114, Wei Zheng 256,
Shanbeh Zienolddiny146, Argyrios Ziogas 27, Kristin K. Zorn334, Jacqueline M. Lane4,335, Richa Saxena4,335,
Duncan Thomas123, Rayjean J. Hung177,178, Brenda Diergaarde336,337, James McKay338, Ulrike Peters 249,
Li Hsu21, Montserrat García-Closas22, Rosalind A. Eeles 40,339, Georgia Chenevix-Trench245,
Paul J. Brennan 14, Christopher A. Haiman17, Jacques Simard340, Douglas F. Easton 9,11, Stephen B. Gruber123,
Paul D.P. Pharoah 9,11, Alkes L. Price 1,3,4, Bogdan Pasaniuc341, Christopher I. Amos342,
Peter Kraft1,3 & Sara Lindström21,249
1Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115,
USA. 2Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Nobels vagen 13, 17177 Stockholm, Sweden.
3Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA. 4Program in Medical and
Population Genetics, Broad Institute of MIT and Harvard, 75 Ames St, Cambridge, MA 02142, USA. 5Department of Population and Quantitative
Health Sciences, Case Western Reserve University, 10900 Eucid Avenue, Cleveland, OH 44106, USA. 6Seidman Cancer Center, University
Hospitals, Cleveland, OH 44106, USA. 7Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia
Dr. MRC-CANCONT, Tampa, FL 33612, USA. 8Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute,
12902 Magnolia Dr. MRC-CANCONT, Tampa, FL 33612, USA. 9Centre for Cancer Genetic Epidemiology, Department of Oncology, University of
Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK. 10Department of Biomedical Data Science, The Geisel School of Medicine at Dartmouth,
1 Medical Center Drive, Lebanon, NH 03756, USA. 11Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care,
University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK. 12Department of Electron Microscopy/Molecular Pathology, The Cyprus
Institute of Neurology and Genetics, 1683 Nicosia, Cyprus. 13Genetic Epidemiology Group, International Agency for Research on Cancer, 150 Cours
Albert Thomas, 69008 Lyon, France. 14Section of Genetics, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon,
France. 15Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Road, London W1T 7NF, UK. 16UCL Genetics
Institute, University College London, Gower Street, London WC1E 6BT, UK. 17Department of Preventive Medicine, Keck School of Medicine,
University of Southern California Norris Comprehensive Cancer Center, Los Angeles, CA 48109, USA. 18Public Health Sciences, University of
Virginia, P.O. Box 800717 Charlottesville, VI 22908, USA. 19Center for Public Health Genomics, University of Virginia, P.O. Box 800717
Charlottesville, VI 22908, USA. 20Epidemiology Research Program, American Cancer Society, 250 Williams Street NW, Atlanta, GA 30303, USA.
21Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109-1024, USA. 22Division of
Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD 20850, USA. 23Department of Thoracic
Surgery, Division of Epidemiology, Vanderbilt University Medical Center, 609 Oxford House, Nashville, TN 37232, USA. 24Department of
Neurology, Dartmouth-Hitchcock Medical Center, 7927 Rubin Building, Room 860, One Medical Center Drive, Lebanon, NH 3756, USA. 25Fred
ALitwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, 600 University Avenue, Toronto, ON
M5G1X5, Canada. 26Department of Molecular Genetics, University of Toronto, 1 King’s College Circle, Toronto, ON M5S1A8, Canada.
27Department of Epidemiology, Genetic Epidemiology Research Institute, University of California Irvine, 224 Irvine Hall, Irvine, CA 92617, USA.
28NNAlexandrov Research Institute of Oncology and Medical Radiology, Settlement of Lesnoy-2, 223040 Minsk, Belarus. 29Markey Cancer Center,
University of Kentucky, 800 Rose Street, cc445, Lexington, KY 40508, USA. 30Department of Public Health Sciences, and Cancer Research
Institute, Queen’s University, 10 Stuart Street, Kingston, ON K7L 3N6, Canada. 31Department of Breast Medical Oncology, University of Texas MD
Anderson Cancer Center, 1155 Pressler St, Houston, TX 77030, USA. 32Cancer Prevention and Control Program, Rutgers Cancer Institute of New
Jersey, 195 Little Albany Street, Room 5568, New Brunswick, NJ 08903, USA. 33Department of Pathology, Landspitali University Hospital,
Hringbraut, Reykjavik 101, Iceland. 34BMC (Biomedical Centre), Faculty of Medicine, University of Iceland, Vatnsmyrarvegi 16, Reykjavik 101, Iceland.
35Australian Prostate Cancer Research Centre-Qld, Translational Research Institute, 37 Kent St, Woolloongabba, QLD 4102, Australia. 36Institute of
Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059,
Australia. 37Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen Nuremberg, University Hospital Erlangen, Friedrich-
Alexander-University Erlangen-Nuremberg, Universitaetsstrasse 21-23, 91054 Erlangen, Germany. 38Human Cancer Genetics Programme, Spanish
National Cancer Research Centre (CNIO), Calle de Melchor Fernández Almagro, 3, 28029 Madrid, Spain. 39Biomedical Network on Rare Diseases
(CIBERER), AvMonforte de Lemos, 3-5Pabellón 11Planta 0, 28029 Madrid, Spain. 40Division of Genetics and Epidemiology, The Institute of Cancer
Research, 15 Cotswold Road, London SM2 5NG, UK. 41Department of Obstetrics and Gynecology, Duke University Medical Center, 25171 Morris
Bldg, Durham, NC 27710, USA. 42Department of Genetic Epidemiology, University Medical Center Goettingen, Humboldtallee 32, 37073
Goettingen, Germany. 43School of Public Health, University of Washington, 1959 NE Pacific Street, Health Science Buidling, F-350, Seattle, WA
98195, USA. 44Department of Oncology, Helsinki University Hospital, University of Helsinki, Haartmaninkatu 4, 00290 Helsinki, Finland.
45Department of Oncology, Örebro University Hospital, 70185 Örebro, Sweden. 46Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168
Roma, Italy. 47Università Cattolica del Sacro Cuore, 00168 Roma, Italy. 48Department of Radiation Oncology, Hannover Medical School, Carl-
Neuberg-Straße 1, 30625 Hannover, Germany. 49Gynaecology Research Unit, Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover,
Germany. 50Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, 2730 Herlev,
Denmark. 51Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, 2730 Herlev,
Denmark. 52Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark. 53DrMargarete
Fischer-Bosch-Institute of Clinical Pharmacology, Auerbachstr112, 70376 Stuttgart, Germany. 54University of Tübingen, Geschwister-Scholl-Platz,
72074 Tübingen, Germany. 55German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120
Heidelberg, Germany. 56Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280,
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 19
69120 Heidelberg, Germany. 57Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases
(NCT), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. 58Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing
Centre, Robinson Way, CB2 0RE Cambridge, UK. 59Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI (Institut d’Investigació Biomèdica
de Girona), Catalan Institute of Oncology, CIBERONC, AvFrança s/n, 17007 Girona, Spain. 60Clinical Sciences, Lund University, Box 117, 221 00
Lund, Sweden. 61Department of Genetics and Pathology, Division of Laboratory Medicine, 221 85 Lund, Sweden. 62University of Melbourne Centre
for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC 3010, Australia. 63Colorectal Oncogenomics Group, Department of
Clinical Pathology, The University of Melbourne, Parkville, VIC 3010, Australia. 64Genomic Medicine and Family Cancer Clinic, Royal Melbourne
Hospital, Parkville, VIC 3010, Australia. 65Department of Obstetrics and Gynecology, University of Heidelberg, Im Neuenheimer Feld 440, 69120
Heidelberg, Germany. 66Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120
Heidelberg, Germany. 67Department of Pathology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki 4th floor,
Haartmaninkatu 8, 00029 Helsinki, Finland. 68Medical Oncology Department, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San
Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Calle del Prof Martín Lagos, 28040 Madrid, Spain. 69Section of
Genetic Oncology, Department of Laboratory Medicine, University and University Hospital of Pisa, via Roma 67, 56126 Pisa, Italy. 70Peter
MacCallum Cancer Center, 305 Grattan Street, Melbourne, VIC 3000, Australia. 71Sir Peter MacCallum Department of Oncology, The University of
Melbourne, 305 Grattan Street, Melbourne, VIC 3000, Australia. 72Sorbonne Université, GRC N°5 ONCOTYPE-URO, Tenon Hospital, 75020 Paris,
France. 73CeRePP, Tenon Hospital, 75020 Paris, France. 74Division of Genetic Epidemiology, Department of Medicine, University of Utah School of
Medicine, Salt Lake City, UT 84112, USA. 75George EWahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT 84112, USA.
76Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
77Department of Biology, University of Pisa, 56126 Pisa, Italy. 78Molecular Oncology Research Center, Barretos Cancer Hospital, Rua Antenor
Duarte Villela, 1331, Barretos, SP 784-400, Brazil. 79Head and Neck Surgery Department, Barretos Cancer Hospital, Pio XII, 1331, Antenor Duarte
Villela St, Barretos, SP 14784-400, Brazil. 80Division of Gastroenterology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
81Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood
Avenue, Boston, MA 02115, USA. 82Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-
Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. 83Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer
Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA. 84Centre for Medical Genetics, Ghent University, De Pintelaan 185, 9000 Gent,
Belgium. 85Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, KU Leuven, Leuven 3000, Belgium. 86Department
of Clinical Genetics, Erasmus University Medical Center, Wytemaweg 80, 3015 Rotterdam, CN, The Netherlands. 87University of Puerto Rico
Medical Sciences Campus and Comprehensive Cancer Center, San Juan, PR 00936, USA. 88Department of Laboratory Medicine and Pathology,
Mayo Clinic, 200 First StSW, Rochester, MN 55905, USA. 89Sheffield Institute for Nucleic Acids (SInFoNiA), Department of Oncology and
Metabolism, University of Sheffield, Western Bank, Sheffield S10 2TN, UK. 90International Hereditary Cancer Center, Department of Genetics and
Pathology, Pomeranian Medical University, ulUnii Lubelskiej 1, 71-252 Szczecin, Poland. 91Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Karolinska Univ Hospital, 171 76 Stockholm, Sweden. 92Department of Clinical Genetics, Fox Chase Cancer Center, 333
Cottman Ave, Philadelphia, PA 19111, USA. 93Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney,
176 Hawkesbury Rd, Sydney, NSW 2145, Australia. 94Department of Gynaecological Oncology, Westmead Hospital, Hawkesbury Rd & Darcy Rd,
Sydney, NSW 2145, Australia. 95Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands.
96Department of Human Genetics, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands. 97Oncogenetics Group,
Clinical and Molecular Genetics Area, Vall d’Hebron Institute of Oncology (VHIO), University Hospital, Vall d’Hebron, Passeig de la Vall d’Hebron
119-129, 08035 Barcelona, Spain. 98Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de
Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Travesía da Choupana S/N, 15706 Santiago de
Compostela, Spain. 99Moores Cancer Center, University of California, San Diego, 3855 Health Sciences Drive, La Jolla, CA 92037, USA. 100School of
Social and Community Medicine, University of Bristol, Bristol BS8 1TH, UK. 101Unit of Nutrition and Cancer, Cancer Epidemiology Research Program,
Catalan Institute of Oncology (ICO-IDIBELL), AvGran Via 199-203, L’Hospitalet de Llobregat, 08908 Barcelona, Spain. 102Department of
Biomedical Sciences, Faculty of Science and Technology, University of Westminster, 309 Regent Street, London W1B 2HW, UK. 103Cancer Sciences
Academic Unit, Faculty of Medicine, University of Southampton, Tremona Road, Southampton SO16 6YD, UK. 104Department of Medicine, Keck
School of Medicine, University of Southern California, Los Angeles, CA 90033, USA. 105Vanderbilt Epidemiology Center, Vanderbilt Genetics
Institute, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 600, Nashville, TN
37203, USA. 106Department of Cancer Epidemiology, Clinical Sciences, Lund University, Barngatan 4, Skånes universitetssjukhus, 222 42 Lund,
Sweden. 107Manchester Centre for Genomic Medicine, Division of Evolution and Genomic Sciences, University of Manchester, St Mary’s Hospital,
Central Manchester University Hospitals NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK. 108David Geffen School of Medicine,
Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, 10833 Le Conte Ave, Los Angeles, CA
90095, USA. 109Department of Otolaryngology, UPMC Hillman Cancer Center, Cancer Pavilion, University of Pittsburgh, Suite 500, 5150 Centre
Avenue, Pittsburgh, PA 15232, USA. 110Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of
Liverpool Institute of Translational Medicine, The Wiliam Duncan Building, 6 West Derby Street, Liverpool L69 3BX, UK. 111Samuel Oschin
Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA. 112Keck School of Medicine,
University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, USA. 113The Breast Cancer Now Toby Robins Research Centre, The
Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK. 114Molecular Diagnostics Laboratory, INRASTES, National Centre for
Scientific Research ‘Demokritos’, Neapoleos 10, AgParaskevi, Athens 15310, Greece. 115Section of Infections, International Agency for Research on
Cancer, 150 cours Albert Thomas, 69008 Lyon, France. 116The Susanne Levy Gertner Oncogenetics Unit, Chaim Sheba Medical Center, Emek HaEla
St 1, 52621 Ramat Gan, Israel. 117Sackler Faculty of Medicine, Tel Aviv University, Haim Levanon 30, 69978 Ramat Aviv, Israel. 118Department of
Surgery, Mount Sinai Hospital, 600 University Avenue, Toronto, ON M5G 1X5, Canada. 119Samuel Lunenfeld Research Institute, 600 University
Avenue, Toronto, ON M5G 1X5, Canada. 120University Health Network Toronto General Hospital, 200 Elizabeth St, Toronto, ON M5G 2C4,
Canada. 121Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research, Jonsson Comprehensive Cancer Centre,
UCLA, 650 Charles Young Drive South, Los Angeles, CA 90095-6900, USA. 122Cancer Risk and Prevention Clinic, Dana-Farber Cancer Institute,
450 Brookline Avenue, Boston, MA 02215, USA. 123Department of Preventive Medicine, Keck School of Medicine, University of Southern California,
1975 Zonal Ave, Los Angeles, CA 90033, USA. 124Center for Cancer Prevention and Translational Genomics, Samuel Oschin Comprehensive
Cancer Institute, Cedars-Sinai Medical Center, Spielberg Building, 8725 Alden Dr, Los Angeles, CA 90048, USA. 125Department of Biomedical
Sciences, Cedars-Sinai Medical Center, Spielberg Building, 8725 Alden Dr, Los Angeles, CA 90048, USA. 126Cancer Epidemiology & Intelligence
Division, Cancer Council Victoria, 615 St Kilda Road, Melbourne, VIC 3004, Australia. 127Centre for Epidemiology and Biostatistics, Melbourne
School of Population and Global Health, The University of Melbourne, Level 1, 723 Swanston Street, Melbourne, VIC 3010, Australia. 128Department
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
20 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia. 129Department of Pathology and Laboratory Medicine,
University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS 66160, USA. 130Department of Medicine, McGill University, 1001 Decarie
Boulevard, Montréal, QC H4A3J1, Canada. 131Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, 1001 Decarie Boulevard,
Montréal, QC H4A3J1, Canada. 132Department of Dermatology, Huntsman Cancer Institute, University of Utah School of Medicine, 2000 Circle of
Hope, Salt Lake City, UT 84112, USA. 133Department of Health Sciences Research, Mayo Clinic, 200 First StSW, Rochester, MN 55905, USA.
134Cancer Prevention and Control, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Room 1S37,
Los Angeles, CA 90048, USA. 135Community and Population Health Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical
Center, 8700 Beverly Blvd, Room 1S37, Los Angeles, CA 90048, USA. 136Public Health Sciences Division, Swedish Cancer Institute, 1221 Madison
StSte 300, Seattle, WA 98109, USA. 137Unit of Clinical Chemistry, Department of Medical Biosciences, Umeå University, By 6M van 2,
Sjukhusomradet, Umea universitet, 901 85 Umea, Sweden. 138Clinical Genetics Branch, National Cancer Institute, DCEG, 9609 Medical Center Dr,
Bethesda, MD 20850-9772, USA. 139Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM,
University Paris-Sud, University Paris-Saclay, 94805 Villejuif, France. 140Department of Environmental Medicine, Division of Nutritional
Epidemiology, Karolinska Institutet, Nobels väg 13, SE-171 77, SE-171 Stockholm, Sweden. 141Department of Oncology, Södersjukhuset,
Sjukhusbacken 10, 118 83 Stockholm, Sweden. 142Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Im Neuenheimer
Feld 580, 69120 Heidelberg, Germany. 143Nuffield Department of Surgical Sciences, Faculty of Medical Science, John Radcliffe Hospital, University
of Oxford, Oxford OX1 2JD, UK. 144Department of Surgical Oncology, Princess Margaret Cancer Centre, 610 University Avenue, Toronto, Ontario
M5G2M9, Canada. 145Department of Internal Medicine 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), 01307
Dresden, Germany. 146National Institute of Occupational Health (STAMI), Gydas vei 8, 0033 Oslo, Norway. 147Department of Gynecology and
Gynecologic Oncology, DrHorst Schmidt Kliniken Wiesbaden, Ludwig-Erhard-Straße 100, 65199 Wiesbaden, Germany. 148Department of
Gynecology and Gynecologic Oncology, Kliniken Essen-Mitte/ EvangHuyssens-Stiftung/ Knappschaft GmbH, Henricistrasse 92, 45136 Essen,
Germany. 149Early Detection and Prevention Section, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France.
150Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Strandboulevarden 49, DK-2100 Copenhagen, Denmark.
151Molecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev, Denmark. 152Preventive
Medicine, Seoul National University College of Medicine, 1 Gwanak-ro, Gwanak-gu, Seoul 151 742, Korea. 153German Research Center for
Environmental Health, Institute for Cancer Research, Ingolstadter Landstr1, London SM2 5NG, UK. 154Center for Medical Genetics, NorthShore
University HealthSystem, 1000 Central St, Evanston, IL 60201, USA. 155The University of Chicago Pritzker School of Medicine, 924 E 57th St,
Chicago, IL 60637, USA. 156British Columbia’s Ovarian Cancer Research (OVCARE) Program, Vancouver General Hospital, BC Cancer Agency and
University of British Columbia, #3427-600 West 10th Avenue, Vancouver, BC V5Z 4E6, Canada. 157Department of Molecular Oncology, BC
Cancer Agency Research Centre, #3427-600 West 10th Avenue, Vancouver, BC V5Z 4E6, Canada. 158Department of Pathology and Laboratory
Medicine, University of British Columbia, #3427-600 West 10th Avenue, Vancouver, BC V5Z 4E6, Canada. 159NNPetrov Institute of Oncology,
Leningradskaya ul, 68, StPetersburg, Russia 197758. 160Lombardi Comprehensive Cancer Center, Georgetown University, 3800 Reservoir Road,
Washington, DC 20007, USA. 161Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Rybacka 1,
70-204 Szczecin, Poland. 162Parkville Familial Cancer Centre, Peter MacCallum Cancer Center, 305 Grattan Street, Melbourne, VIC 3000,
Australia. 163Department of Radiation Sciences, Umeå University, By 6M van 2, Sjukhusomradet, Umea universitet, 901 85 Umea, Sweden.
164Department of Medicine, Division of Oncology and Stanford Cancer Institute, Stanford University School of Medicine, 780 Welch Rd, Stanford,
CA 94304, USA. 165Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, 02114 Boston, MA, USA. 166Molecular Medicine
Center, Department of Medical Chemistry and Biochemistry, Medical Faculty, Medical University of Sofia, Sofia 1504, Bulgaria. 167Women’s Cancer
Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048,
USA. 168Hollings Cancer Center and Department of Public Health Sciences, Medical University of South Carolina, 68 President Street
Bioengineering Building, MSC955, Charleston, SC 29425, USA. 169Cancer Epidemiology, University Cancer Center Hamburg (UCCH), University
Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. 170Clinical Gerontology, Department of Public Health and
Primary Care, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK. 171Department of Genetics and Fundamental Medicine,
Bashkir State University, ulZaki Validi 32, Ufa, Russia 450076. 172Institute of Biochemistry and Genetics, Ufa Scientific Center of Russian Academy
of Sciences, 71 prosp Oktyabrya, Ufa, Russia 450054. 173Division of Urologic Surgery, Brigham and Womens Hospital, Boston, Massachusettes
02115, USA. 174Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein 21, 6525 EZ Nijmegen, The
Netherlands. 175Department of Genitourinary Medical Oncology, University of Texas MD Anderson Cancer Center, 1155 Pressler St, Houston, TX
77030, USA. 176Department of Gynaecology, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, DK-2100 Copenhagen, Denmark.
177Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, 60 Murray Street, Toronto,
Ontario M5T 3L9, Canada. 178Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON
M5T3M7, Canada. 179Centre for Research in Environmental Epidemiology (CREAL), ISGlobal, 08036 Barcelona, Spain. 180IMIM (Hospital del Mar
Research Institute), Barcelona 08003, Spain. 181Universitat Pompeu Fabra (UPF), Barcelona 08002, Spain. 182Division of Cancer Epidemiology and
Genetics, National Cancer Institute, Department of Health and Human Services, National Institutes of Health, 9609 Medical Center Dr, Bethesda,
MD 20892, USA. 183Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Ullernchausseen 70,
0379 Oslo, Norway. 184Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway. 185Department of
Clinical Molecular Biology, Oslo University Hospital, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway. 186Department of Pathology and
Laboratory Diagnostics, the Maria Sklodowska-Curie Institute - Oncology Center, Roentgena 5, 02-781 Warsaw, Poland. 187Head and Neck Surgery,
Department of Otorhinolaryngology, Maastricht University Medical Center, PDebyelaan 25, POBox 5800, 6202 AZ Maastricht, The Netherlands.
188Department of Integrative Oncology, British Columbia Cancer Agency, Room 10-111 675 West 10th Avenue, Vancouver, BC V5Z1L3, Canada.
189VIB Center for Cancer Biology, VIB, Herestraat 49, 3001 Leuven, Belgium. 190Laboratory for Translational Genetics, Department of Human
Genetics, University of Leuven, Oude Markt 13, 3000 Leuven, Belgium. 191Integrative Tumor Epidemiology Branch, DCEG, National Cancer Institute,
9609 Medical Center Drive, Room SG/7E106, Rockville, MD 20850, USA. 192College of Pharmacy, Washington State University, PBS 431 PO Box
1495, Spokane, WA 99210-1495, USA. 193Cancer Control Research, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada.
194Clalit Health Services, Clalit National Israeli Cancer Control Center, Carmel Medical Center, 2 Horev Street, 3436212 Haifa, Israel. 195Institute of
Human Genetics, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany. 196Gynecology Service,
Department of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 197Gynecologic Oncology, Laura
and Isaac Pearlmutter Cancer Center, NYU Langone Medical Center, 240 East 38th Street 19th Floor, New York, NY 10016, USA. 198Department of
Family Medicine and Community Health, Mary Ann Swetland Center for Environmental Health, Case Western Reserve University, Cleveland, OH
44106, USA. 199Servicio Galego de Saude (SERGAS), Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), 15706 Santiago De
Compostela, Spain. 200Translational Research Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. 201Department of
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 21
Molecular Medicine and Surgery, Karolinska Institutet, Karolinska Univ Hospital, 171 76 Stockholm, Sweden. 202Health Sciences Research, Mayo
Clinic Arizona, 13400 EShea Blvd, Scottsdale, AZ 85259, USA. 203Epidemiology Division, Princess Margaret Cancer Centre, 610 University Avenue,
Toronto, ON M5G2M9, Canada. 204Unit of Oncology 1, Department of Clinical and Experimental Oncology, Istituto Oncologico Veneto IRCCS,
35122 Padua, Italy. 205Department of Medical Genetics, Oslo University Hospital, Kirkeveien 166, 0450 Oslo, Norway. 206Institute of Human
Genetics, University Hospital Ulm, Prittwitzstrasse 43, 89075 Ulm, Germany. 207Translational Cancer Research Area, University of Eastern Finland,
Yliopistonranta 1, 70210 Kuopio, Finland. 208Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland,
KuopioYliopistonranta 1, 70210, Finland. 209Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Puijonlaaksontie 2,
70210 Kuopio, Finland. 210Epidemiology Program, University of Hawaii Cancer Center, 701 Ilalo St, Honolulu, HI 96813, USA. 211Department of
Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm 17177, Sweden. 212Division of Gynecologic Oncology, University
Health Network, Princess Margaret Hospital, 610 University Avenue, OPG Wing, 6-811, Toronto, ON M5G 2M9, Canada. 213Division of
Gynaecology and Obstetrics, , Technische Universität München, Arcisstraße 21, 80333 Munich, Germany. 214Faculty of Medicine, University of
Heidelberg, In Neuenheimer Feld 672, 69120 Heidelberg, Germany. 215NRG Oncology, Statistics and Data Management Center, Roswell Park
Cancer Institute, Elm & Carlton Streets, Buffalo, NY 14263, USA. 216Womens Cancer Research Center, Magee-Womens Research Institute and
Hillman Cancer Center, Pittsburgh, PA 15213, USA. 217Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive
Sciences, University of Pittsburgh School of Medicine, 300 Halket Street, Pittsburgh, PA 15213, USA. 218Immunology and Molecular Oncology Unit,
Veneto Institute of Oncology IOV - IRCCS, Via Gattamelata 64, Padua 35128, Italy. 219Catalan Institute of Oncology, Bellvitge Biomedical Research
Institute (IDIBELL), Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP) and University of Barcelona, Barcelona
08908, Spain. 220Division of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm & Carlton Streets, Buffalo, NY 14263, USA.
221Division of Population Health, Health Services Research and Primary Care, University of Manchester, Oxford Road, Manchester M13 9PL, UK.
222Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK. 223Department of Laboratory Medicine
and Pathobiology, University of Toronto, 1 King’s College Circle, Toronto, ON M5S1A8, Canada. 224Laboratory Medicine Program, University Health
Network, 200 Elizabeth Street, Toronto, ON M5G2C4, Canada. 225Department of Medicine, Abramson Cancer Center, Perelman School of
Medicine at the University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA 19104, USA. 226Department of Oncology, Addenbrooke’s
Hospital, University of Cambridge, Cambridge CB1 8RN, UK. 227NIHR Bristol Biomedical Research Centre Nutrition Theme, University of Bristol,
Upper Maudlin Street, Bristol BS2 8AE, UK. 228Department of Population Sciences, Beckman Research Institute of City of Hope, 1500 E Duarte,
Duarte, CA 91010, USA. 229Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Haartmaninkatu 8,
00290 Helsinki, Finland. 230Department of Urology, University of Washington, Seattle, Washington 98195, USA. 231Center for Genomic Medicine,
Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark. 232Latvian Biomedical Research and Study
Centre, Ratsupites str 1, Riga LV-1067, Latvia. 233Cancer Genetics and Prevention Program, University of California San Francisco, 1600 Divisadero
St, San Francisco, CA 94143-1714, USA. 234Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan-Kettering
Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 235Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering
Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 236Department of Molecular Genetics, National Institute of Oncology, Ráth György
u7-9, 1122 Budapest, Hungary. 237Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK. 238Center for Clinical
Cancer Genetics, The University of Chicago, 5841S Maryland Ave, Chicago, IL 60637, USA. 239Department of Epidemiology, Gillings School of
Global Public Health, University of North Carolina, 135 Dauer Dr, Chapel Hill, NC 27599-7435, USA. 240UNC Lineberger Comprehensive Cancer
Center, 450 West Dr, Chapell Hill, NC 27599, USA. 241The University of Surrey, Guildford, Surrey GU2 7XH, UK. 242Department of Cancer
Epidemiology, HLee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL 33612, USA. 243Department of Applied Health
Research, University College London, 1-19 Torrington Place, London WC1E 6BT, UK. 244Centre for Cancer Genetic Epidemiology, Department of
Oncology, Strangeways Laboratory, University of Cambridge, Cambridge CB1 8RN, UK. 245Department of Genetics and Computational Biology,
QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia. 246Department of Obstetrics and Gynecology,
Oregon Health & Science University, 3181 SW Sam Jackson Park Road, L-466, Portland, OR 97239, USA. 247Knight Cancer Institute, Oregon Health
& Science University, 3181 SW Sam Jackson Park Road, L-466, Portland, OR 97239, USA. 248Department of Gastroenterology, Radboud University
Nijmegen Medical Center, Geert Grooteplein Zuid 10, Internal BOBox 433, 6525 GA Nijmegen, The Netherlands. 249Department of Epidemiology,
University of Washington School of Public Health, 1959 NE Pacific St, Seattle, WA 98195, USA. 250Research Centre for Genetic Engineering and
Biotechnology ‘Georgi DEfremov’, Macedonian Academy of Sciences and Arts, Boulevard Krste Petkov Misirkov, 1000 Skopje, Republic of
Macedonia. 251Bristol Dental School, University of Bristol, Lower Maudlin Street, Bristol BS1 2LY, UK. 252Unit of Molecular Bases of Genetic Risk and
Genetic Testing, Department of Research, Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) Istituto Nazionale dei Tumori
(INT), Via Giacomo Venezian 1, 20133 Milan, Italy. 253Decode genetics, Sturlugata 8, IS-101 ReykjavikReykjavikIceland, Iceland. 254School of
Women’s and Children’s Health, Faculty of Medicine, University of NSW Sydney, 18 High St, Sydney, NSW 2052, Australia. 255The Kinghorn
Cancer Centre, Garvan Institute of Medical Research, 384 Victoria Street, Sydney, NSW 2010, Australia. 256Division of Epidemiology, Department
of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 1161 21st Ave S #
D3300, Nashville, TN 37232, USA. 257Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, 7 Michal
Street, 34362 Haifa, Israel. 258Department of Genetics, University of Pretoria, Private Bag X323, Arcadia 0007, South Africa. 259Department of
Chronic Disease Epidemiology, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA. 260Cancer Center Cluster Salzburg at
PLUS, Department of Molecular Biology, University of Salzburg, Billrothstr11, 5020 Salzburg, Austria. 261Division of Epigenomics and Cancer Risk
Factors, DKFZ – German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. 262Member of the German Center for
Lung Research (DZL), Translational Lung Research Center Heidelberg (TLRC-H), 69120 Heidelberg, Germany. 263Department of Urology, Erasmus
University Medical Center, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands. 264Department of Radiation Oncology, Icahn School of
Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA. 265Department of Genetics and Genomic Sciences, Icahn School of
Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA. 266Department of Epidemiology, University of Washington, M4 C308,
1100 Fairview Ave N, Seattle, WA 98109, USA. 267Faculty of Medicine and Health Sciences, Basic Medical Sciences, Ghent University, De Pintelaan
185, 9000 Gent, Belgium. 268Hereditary Cancer Clinic, University Hospital of Heraklion, Voutes, 711 10 Heraklion, Greece. 269Epidemiology Branch,
National Institute of Environmental Health Sciences, NIH, 111TWAlexander Drive, Research Triangle Park, NC 27709, USA. 270Research Oncology,
Guy’s Hospital, King’s College London, Guy’s Hospital Great Maze Pond, London SE1 9RT, UK. 271Institute of Biomedicine, University of Turku,
20014 Turku, Finland. 272Division of Laboratory, Department of Medical Genetics, Turku University Hospital, 20014 Turku, Finland. 273Prostate
Cancer Research Center, Faculty of Medicine and Life Sciences and BioMediTech Institute, University of Tampere, 33014 Tampere, Finland.
274Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam,
The Netherlands. 275Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital,
Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. 276Department of Preventive Medicine, Keck School of Medicine, University of Southern
ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4
22 NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications
California, 1450 Biggy Street, Los Angeles, CA 90033, USA. 277Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer
Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical
University, 101 Longmian Ave, Jiangning District, 211166 Nanjing, People’s Republic of China. 278Department of Genetics and Genomic Sciences,
Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, 2nd floor, New York, NY
10029, USA. 279Dept of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna,
Austria. 280Department of Internal Medicine, University of Utah Health Sciences Center, 295 Chipeta Way, Salt Lake City, UT 84132, USA.
281Department of Molecular Medicine, Aarhus University Hospital, DK-8200 Aarhus, Denmark. 282Department of Clinical Medicine, Aarhus
University, DK-8200 Aarhus, Denmark. 283Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, 246 Clayton
Road, Clayton, VIC 3168, Australia. 284Department of Clinical Pathology, The University of Melbourne, Cnr Grattan Street and Royal Parade,
Melbourne, VIC 3010, Australia. 285Department of Medicine III, University Hospital, LMU Munich, Marchioninistr15, 81377 Munich, Germany.
286The Curtin UWA Centre for Genetic Origins of Health and Disease, Curtin University and University of Western Australia, 35 Stirling Hwy, Perth,
WA 6000, Australia. 287Department of Obstetrics and Gynecology, Sahlgrenska Cancer Center, Inst Clinical Scienses, University of Gothenburg,
Blå stråket 6, 41345 Gothenburg, Sweden. 288Epidemiology Center, College of Medicine, University of South Florida, 3650 Spectrum Blvd, Suite
100, Tampa, FL 33612, USA. 289Division of Breast Cancer Research, The Institute of Cancer Research, London SW7 3RP, UK. 290Department of
Molecular Biology, School of Medicine of São José do Rio Preto, Av Brig Faria Lima 5416 Vila São Pedro, São José do Rio Preto, SP 15090-000,
Brazil. 291Department of Genetics and Evolutive Biology, Institute of Biosciences, University of São Paulo, Rua do Matão, 321, São Paulo, SP 05508-
090, Brazil. 292SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA. 293Faculty of Medicine,
University of Oviedo and CIBERESP, Campus del Cristo s/n, 33006 Oviedo, Spain. 294Epigenetic and Stem Cell Biology Laboratory, National
Institute of Environmental Health Sciences, NIH, 111TWAlexander Drive, Research Triangle Park, NC 27709, USA. 295Medical Statistics Group,
School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK. 296Department of
Genetics, Portuguese Oncology Institute, Rua DrAntónio Bernardino de Almeida 62, 4220-072 Porto, Portugal. 297Biomedical Sciences Institute
(ICBAS), University of Porto, RJorge de Viterbo Ferreira 228, 4050-013 Porto, Portugal. 298Department of Epidemiology, Mailman School of Public
Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA. 299Obstetrics and Gynecology Epidemiology Center, Brigham and
Women’s Hospital, 221 Longwood Avenue RFB 368, Boston, MA 02115, USA. 300Harvard THChan School of Public Health, 221 Longwood Avenue
RFB 368, Boston, MA 02115, USA. 301Department of Clinical Genetics, Odense University Hospital, Sonder Boulevard 29, 5000 Odence C,
Denmark. 302Department of Gynecology and Obstetrics, Haukeland University Hospital, 5021 Bergen, Norway. 303Centre for Cancer Biomarkers
CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway. 304Program in Cancer Genetics, Departments of Human
Genetics and Oncology, McGill University, 1001 Decarie Boulevard, Montréal, QC H4A3J1, Canada. 305Department of Medical Genetics, Cambridge
University, Hills Road, Cambridge CB2 0QQ, UK. 306Department of Cancer Biology and Genetics, The Ohio State University, 460W12th Avenue,
Columbus, OH 43210, USA. 307Institute of Human Genetics, Pontificia Universidad Javeriana, Carrera 7 No40-90, Bogota, Colombia. 308Division of
Cancer Sciences, Manchester Cancer Research Centre, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre,
NIHR Manchester Biomedical Research Centre, Health Innovation Manchester, University of Manchester, Manchester M20 4GJ, UK. 309Cancer
Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK. 310Department of Medical Oncology, Beth
Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, USA. 311Huntsman Cancer Institute and Department of Population
Health Sciences, University of Utah, 2000 Circle of Hope, Rm 4125, Salt Lake City, UT 84112, USA. 312Department of Oncology, Cross Cancer
Institute, University of Alberta, 116 St & 85 Ave, Edmonton AB T6G 2R3, Canada. 313Division of Radiation Oncology, Cross Cancer Institute,
University of Alberta, 116 St & 85 Ave, Edmonton AB T6G 2R3, Canada. 314Division of Gynecologic Oncology, Department of Obstetrics and
Gynaecology and Leuven Cancer Institute, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium. 315Fundación Pública Galega
Medicina Xenómica & Instituto de Investigación Sanitaria de Santiago de Compostela, calle Choupana s/n, 15706 Santiago De Compostela, Spain.
316Population Health Department, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia. 317Biostatistics
and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, 111TWAlexander Drive, Research Triangle Park, NC
27709, USA. 318Department of Otolaryngology/Head and Neck Surgery, University of North Carolina at Chapel Hill, Chapel Hill 27514 NC, USA.
319City of Hope Clinical Cancer Genomics Community Research Network, 1500 East Duarte Road, Duarte, CA 91010, USA. 320Division of Cancer
Sciences, University of Manchester, Manchester Cancer Research Centre, Manchester Academic Health Science Centre,, The Christie Hospital NHS
Foundation Trust, Manchester M13 9PL, UK. 321Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA.
322Department of Epidemiology, University of Washington, 1100 Fairview Ave N, Seattle, WA 98109, USA. 323Department of Health Research and
Policy - Epidemiology, Stanford University School of Medicine, 259 Campus Drive, Stanford, CA 94305, USA. 324Department of Biomedical Data
Science, Stanford University School of Medicine, 259 Campus Drive, Stanford, CA 94305, USA. 325Institute of Medical Informatics, Biometry and
Epidemiology, Chair of Epidemiology, Ludwig Maximilians University, Neuherberg D-85764, Munich 803539 Bavaria, Germany. 326Helmholtz
Zentrum Munchen, German Research Center for Environmental Health (GmbH), Institute of Epidemiology, Ingolstadter Landstr1, 85764
Neuherberg, Germany. 327Institute of Medical Statistics and Epidemiology, Technical University Munich, Munich 80333, Germany. 328Laboratory of
Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Aapistie 5A, 90220
Oulu, Finland. 329Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Aapistie 5A, 90220 Oulu, Finland.
330Department of Surgical Sciences, Uppsala University, 751 85 Uppsala, Sweden. 331Academic Unit of Clinical Oncology, University of Sheffield,
Weston Park Hospital, Whitham Road, Sheffield S10 2SJ, UK. 332Discipline of Genetics, Memorial University of Newfoundland, StJohn’s, NL A1C
5S7, Canada. 333Department of Epidemiology, Division of Cancer Prevention and Population Science, The University of Texas MD Anderson Cancer
Center, 1515 Holcombe Blvd, Houston, TX 77030, USA. 334Magee-Womens Hospital, University of Pittsburgh School of Medicine, 300 Halket St,
Pittsburgh, PA 15213, USA. 335Center for Genomic Medicine and Department of Anasthesia, Massachusetts General Hospital, Boston, MA 02114,
USA. 336Human Genetics, Graduate School of Public Health, University of Pittsburgh, UPMC Cancer Pavilion, Suite 4C, Office # 467, 5150 Centre
Avenue, Pittsburgh, PA 15232, USA. 337UPMC Hillman Cancer Center, Pittsburgh 15232 PA, USA. 338Genetic Cancer Susceptibility Group,
International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France. 339Oncogenetics Team, The Institute of Cancer
Research and Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5NG, UK. 340Genomics Center, Centre Hospitalier Universitaire de
Québec - Université Laval Research Center, 2705 Laurier Boulevard, Québec City, QC G1V4G2, Canada. 341UCLA Path and Lab Med, University of
California, 10833 Le Conte Ave, Los Angeles, CA 190095, USA. 342Department of Medicine, Epidemiology Section, Institute for Clinical and
Translational Research, Baylor Medical College, One Baylor Plaza, MS: BCM451, Suite 100D, Houston, TX 77030-3411, USA
NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-018-08054-4 ARTICLE
NATURE COMMUNICATIONS | (2019) 10:431 | https://doi.org/10.1038/s41467-018-08054-4 | www.nature.com/naturecommunications 23