Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood
| dc.contributor.author | Qi T | |
| dc.contributor.author | Wu Y | |
| dc.contributor.author | Zeng J | |
| dc.contributor.author | Zhang FT | |
| dc.contributor.author | Xue AL | |
| dc.contributor.author | Jiang LD | |
| dc.contributor.author | Zhu ZH | |
| dc.contributor.author | Kemper K | |
| dc.contributor.author | Yengo L | |
| dc.contributor.author | Zheng ZL | |
| dc.contributor.author | eQTLGen Consortium | |
| dc.contributor.author | Marioni RE | |
| dc.contributor.author | Montgomery GW | |
| dc.contributor.author | Deary IJ | |
| dc.contributor.author | Wray NR | |
| dc.contributor.author | Visscher PM | |
| dc.contributor.author | McRae AF | |
| dc.contributor.author | Yang J | |
| dc.contributor.organization | fi=sydäntutkimuskeskus|en=Cardiovascular Medicine (CAPC)| | |
| dc.contributor.organization | fi=tyks, vsshp|en=tyks, varha| | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.35734063924 | |
| dc.converis.publication-id | 32113458 | |
| dc.converis.url | https://research.utu.fi/converis/portal/Publication/32113458 | |
| dc.date.accessioned | 2022-10-27T11:45:46Z | |
| dc.date.available | 2022-10-27T11:45:46Z | |
| dc.description.abstract | Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r(b)). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples ((r) over cap (b) = 0.70 for ciseQTLs and (r) over cap (b) = 0.78 for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes. | |
| dc.identifier.eissn | 2041-1723 | |
| dc.identifier.jour-issn | 2041-1723 | |
| dc.identifier.olddbid | 171952 | |
| dc.identifier.oldhandle | 10024/155046 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/29576 | |
| dc.identifier.urn | URN:NBN:fi-fe2021042719380 | |
| dc.language.iso | en | |
| dc.okm.affiliatedauthor | Raitakari, Olli | |
| dc.okm.affiliatedauthor | Dataimport, tyks, vsshp | |
| dc.okm.discipline | 3111 Biomedicine | en_GB |
| dc.okm.discipline | 3111 Biolääketieteet | fi_FI |
| dc.okm.internationalcopublication | international co-publication | |
| dc.okm.internationality | International publication | |
| dc.okm.type | A1 ScientificArticle | |
| dc.publisher | NATURE PUBLISHING GROUP | |
| dc.publisher.country | United Kingdom | en_GB |
| dc.publisher.country | Britannia | fi_FI |
| dc.publisher.country-code | GB | |
| dc.relation.articlenumber | ARTN 2282 | |
| dc.relation.doi | 10.1038/s41467-018-04558-1 | |
| dc.relation.ispartofjournal | Nature Communications | |
| dc.relation.volume | 9 | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/155046 | |
| dc.title | Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood | |
| dc.year.issued | 2018 |
Tiedostot
1 - 1 / 1
Ladataan...
- Name:
- s41467-018-04558-1.pdf
- Size:
- 1.11 MB
- Format:
- Adobe Portable Document Format
- Description:
- Publisher's PDF