Effect of weight on depression using multiple genetic instruments

dc.contributor.authorViinikainen Jutta
dc.contributor.authorBöckerman Petri
dc.contributor.authorWillage Barton
dc.contributor.authorElovainio Marko
dc.contributor.authorKari Jaana T.
dc.contributor.authorLehtimäki Terho
dc.contributor.authorPehkonen Jaakko
dc.contributor.authorPitkänen Niina
dc.contributor.authorRaitakari Olli
dc.contributor.organizationfi=InFLAMES Lippulaiva|en=InFLAMES Flagship|
dc.contributor.organizationfi=biolääketieteen laitos|en=Institute of Biomedicine|
dc.contributor.organizationfi=sydäntutkimuskeskus|en=Cardiovascular Medicine (CAPC)|
dc.contributor.organizationfi=tyks, vsshp|en=tyks, varha|
dc.contributor.organizationfi=väestötutkimuskeskus|en=Centre for Population Health Research (POP Centre)|
dc.contributor.organization-code1.2.246.10.2458963.20.35734063924
dc.contributor.organization-code1.2.246.10.2458963.20.42471027641
dc.contributor.organization-code1.2.246.10.2458963.20.68445910604
dc.contributor.organization-code1.2.246.10.2458963.20.77952289591
dc.converis.publication-id387387602
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/387387602
dc.date.accessioned2025-08-27T21:31:38Z
dc.date.available2025-08-27T21:31:38Z
dc.description.abstractA striking global health development over the past few decades has been the increasing prevalence of overweight and obesity. At the same time, depression has become increasingly common in almost all high-income countries. We investigated whether body weight, measured by body mass index (BMI), has a causal effect on depression symptoms in Finland. Using data drawn from the Cardiovascular Risk in Young Finns Study (N = 1,523, mean age 41.9, SD 5), we used linear regression to establish the relationship between BMI and depression symptoms measured by 21-item Beck's Depression Inventory. To identify causal relationships, we used the Mendelian randomization (MR) method with weighted sums of genetic markers (single nucleotide polymorphisms, SNPs) as instruments for BMI. We employ instruments (polygenic risk scores, PGSs) with varying number of SNPs that are associated with BMI to evaluate the sensitivity of our results to instrument strength. Based on linear regressions, higher BMI was associated with a higher prevalence of depression symptoms among females (b = 0.238, p = 0.000) and males (b = 0.117, p = 0.019). However, the MR results imply that the positive link applies only to females (b = 0.302, p = 0.007) but not to males (b = -0.070, p = 0.520). Poor instrument strength may explain why many previous studies that have utilized genetic instruments have been unable to identify a statistically significant link between BMI and depression-related traits. Although the number of genetic markers in the instrument had only a minor effect on the point estimates, the standard errors were much smaller when more powerful instruments were employed.
dc.identifier.eissn1932-6203
dc.identifier.jour-issn1932-6203
dc.identifier.olddbid200555
dc.identifier.oldhandle10024/183582
dc.identifier.urihttps://www.utupub.fi/handle/11111/45640
dc.identifier.urlhttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0297594
dc.identifier.urnURN:NBN:fi-fe2025082789153
dc.language.isoen
dc.okm.affiliatedauthorKannisto, Niina
dc.okm.affiliatedauthorRaitakari, Olli
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline3142 Public health care science, environmental and occupational healthen_GB
dc.okm.discipline3142 Kansanterveystiede, ympäristö ja työterveysfi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherPublic Library of Science
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.articlenumbere0297594
dc.relation.doi10.1371/journal.pone.0297594
dc.relation.ispartofjournalPLoS ONE
dc.relation.issue2
dc.relation.volume19
dc.source.identifierhttps://www.utupub.fi/handle/10024/183582
dc.titleEffect of weight on depression using multiple genetic instruments
dc.year.issued2024

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