Using polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samples

Basit Öğe Kaydı
dc.authoridWetherill, Leah/0000-0003-2888-9051
dc.authoridJohnson, Emma/0000-0003-0394-777X
dc.authorid/0000-0003-2291-6880
dc.authoridKaprio, Jaakko/0000-0002-3716-2455
dc.authoridKuperman, Samuel/0000-0002-5995-1981
dc.authoridLatvala, Antti/0000-0001-5695-117X
dc.authoridAnokhin, Andrey/0000-0001-8158-6346
dc.contributor.authorBarr, Peter B.
dc.contributor.authorKsinan, Albert
dc.contributor.authorSu, Jinni
dc.contributor.authorJohnson, Emma C.
dc.contributor.authorMeyers, Jacquelyn L.
dc.contributor.authorWetherill, Leah
dc.contributor.authorLatvala, Antti
dc.date.accessioned2024-09-29T16:01:01Z
dc.date.available2024-09-29T16:01:01Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractGenome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability. There is growing evidence that PRS may prove useful for early identification of those at increased risk for certain diseases. The current potential of PRS for alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high-risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of (1) alcohol dependence/alcohol problems, (2) alcohol consumption, and (3) risky behaviors with AUD and other substance use disorder (SUD) criteria. These PRSs explain similar to 2.5-3.5% of the variance in AUD (across FT12 and COGA) when all PRSs are included in the same model. Calculations of area under the curve (AUC) show PRS provide only a slight improvement over a model with age, sex, and ancestral principal components as covariates. While individuals in the top 20, 10, and 5% of the PRS distribution had greater odds of having an AUD compared to the lower end of the continuum in both COGA and FT12, the point estimates at each threshold were statistically indistinguishable. Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis and opioid) SUD criteria. PRSs are associated with risk for SUD in independent samples. However, usefulness for identifying those at increased risk in their current form is modest, at best. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.en_US
dc.description.sponsorshipNational Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health [R01AA015416, K02AA018755, K02DA32573, K01DA037914, F32AA027435]; Academy of Finland [100499, 205585, 118555, 141054, 265240, 308248, 308698, 312073]; Scientific and Technological Research Council of Turkey (TUBITAK) [114C117]; NIDA [MH109532]; NIMH [MH109532]; NIAAA [U01AA008401]en_US
dc.description.sponsorshipResearch reported in this publication was supported by the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health under award numbers R01AA015416 (D.M.D.), K02AA018755 (D.M.D.), K02DA32573 (A.A.), K01DA037914 (J.L.M.), and F32AA027435 (E.C.J.); the Academy of Finland (grants 100499, 205585, 118555, 141054, 265240, 308248, 308698 and 312073); and the Scientific and Technological Research Council of Turkey (TUBITAK) under award number 114C117 (F.A.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, the Academy of Finland, or the Scientific and Technological Research Council of Turkey. This research also used summary data from the Psychiatric Genomics Consortium (PGC) Substance Use Disorders (SUD) working group. The PGC-SUD is supported by funds from NIDA and NIMH to MH109532 and, previously, had analyst support from NIAAA to U01AA008401 (COGA). PGC-SUD gratefully acknowledges its contributing studies and the participants in those studies, without whom this effort would not be possible.en_US
dc.identifier.doi10.1038/s41398-020-00865-8
dc.identifier.issn2158-3188
dc.identifier.issue1en_US
dc.identifier.pmid32555147en_US
dc.identifier.scopus2-s2.0-85086694350en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1038/s41398-020-00865-8
dc.identifier.urihttps://hdl.handle.net/20.500.14619/5491
dc.identifier.volume10en_US
dc.identifier.wosWOS:000544612300003en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherNature Publishing Groupen_US
dc.relation.ispartofTranslational Psychiatryen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGenetic Influencesen_US
dc.subjectAlcohol-Consumptionen_US
dc.subjectPredictionen_US
dc.subjectDependenceen_US
dc.subjectTwinen_US
dc.subjectTrajectoriesen_US
dc.subjectBehavioren_US
dc.subjectMenen_US
dc.titleUsing polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samplesen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
PubMed İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu