{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T00:44:29Z","timestamp":1791333869821,"version":"4.3.1"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T00:00:00Z","timestamp":1721088000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T00:00:00Z","timestamp":1721088000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mol Psychiatry"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Genome-Wide Association Studies (GWAS) over-represent European ancestries, neglecting all other ancestry groups and low-income nations. Consequently, polygenic risk scores (PRS) more accurately predict complex traits in Europeans than African Ancestries groups. Very few studies have looked at the transferability of European-derived PRS for behavioural and mental health phenotypes to Africans. We assessed the comparative accuracy of depression PRS trained on European and African Ancestries GWAS studies to predict major depressive disorder (MDD) and related traits in African ancestry participants from the UK Biobank. UK Biobank participants were selected based on Principal component analysis clustering with an African genetic similarity reference population, MDD was assessed with the Composite International Diagnostic Interview (CIDI). PRS were computed using PRSice2 software using either European or African Ancestries GWAS summary statistics. PRS trained on European ancestry samples (246,363 cases) predicted case control status in Africans of the UK Biobank with similar accuracies (R2\u2009=\u20092%, \u03b2\u2009=\u20090.32, empirical p-value\u2009=\u20090.002) to PRS trained on far much smaller samples of African Ancestries participants from 23andMe, Inc. (5045 cases, R\u00b2 = 1.8%, \u03b2\u2009=\u20090.28, empirical p-value\u2009=\u20090.008). This suggests that prediction of MDD status from Africans to Africans had greater efficiency relative to discovery sample size than prediction of MDD from Europeans to Africans. Prediction of MDD status in African UK Biobank participants using GWAS findings of likely causal risk factors from European ancestries was non-significant. GWAS of MDD in European ancestries are inefficient for improving polygenic prediction in African samples; urgent MDD studies in Africa are needed.<\/jats:p>","DOI":"10.1038\/s41380-024-02662-x","type":"journal-article","created":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T03:02:12Z","timestamp":1721098932000},"page":"151-157","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Polygenic prediction of major depressive disorder and related traits in African ancestries UK Biobank participants"],"prefix":"10.1038","volume":"30","author":[{"given":"S. C.","family":"Kanjira","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3599-6018","authenticated-orcid":false,"given":"M. J.","family":"Adams","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Y.","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C.","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"23andMe Research Team","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8249-8476","authenticated-orcid":false,"given":"C. M.","family":"Lewis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9726-603X","authenticated-orcid":false,"given":"K.","family":"Kuchenbaecker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0198-4588","authenticated-orcid":false,"given":"A. M.","family":"McIntosh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,7,16]]},"reference":[{"key":"2662_CR1","doi-asserted-by":"publisher","first-page":"1789","DOI":"10.1016\/S0140-6736(18)32279-7","volume":"392","author":"SL James","year":"2018","unstructured":"James SL, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990\u20132017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1789\u2013858.","journal-title":"Lancet."},{"key":"2662_CR2","unstructured":"World Health Organization. Depression and other common mental disorders: global health estimates. Geneva: World Health Organization; 2017. Report No. WHO\/MSD\/MER\/2017.2. https:\/\/apps.who.int\/iris\/handle\/10665\/254610"},{"key":"2662_CR3","doi-asserted-by":"publisher","DOI":"10.1186\/s13643-022-01893-9","volume":"11","author":"A Fekadu","year":"2022","unstructured":"Fekadu A, Demissie M, Berhane R, Medhin G, Bitew T, Hailemariam M, et al. Under detection of depression in primary care settings in low and middle-income countries: a systematic review and meta-analysis. Syst Rev. 2022;11:21.","journal-title":"Syst Rev"},{"key":"2662_CR4","doi-asserted-by":"publisher","first-page":"e023421","DOI":"10.1136\/bmjopen-2018-023421","volume":"8","author":"S Rathod","year":"2018","unstructured":"Rathod S, Roberts T, Medhin G. Detection and treatment initiation for depression and alcohol use disorders: facility-based cross-sectional studies in five low-income and middle-income country districts. BMJ Open. 2018;8:e023421.","journal-title":"BMJ Open"},{"key":"2662_CR5","doi-asserted-by":"publisher","first-page":"1552","DOI":"10.1176\/appi.ajp.157.10.1552","volume":"157","author":"PF Sullivan","year":"2000","unstructured":"Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552\u201362.","journal-title":"Am J Psychiatry"},{"key":"2662_CR6","doi-asserted-by":"publisher","first-page":"1832","DOI":"10.1038\/s41591-023-02352-1","volume":"29","author":"TD Als","year":"2023","unstructured":"Als TD, Kurki MI, Grove J, Voloudakis G, Therrien K, Tasanko E, et al. Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses. Nat Med. 2023;29:1832\u201344.","journal-title":"Nat Med"},{"key":"2662_CR7","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-11112-0","volume":"10","author":"L Duncan","year":"2019","unstructured":"Duncan L, Shen H, Gelaye B, Meijsen J, Ressler K, Feldman M, et al. Analysis of polygenic risk score usage and performance in diverse human populations. Nat Commun. 2019;10:3328.","journal-title":"Nat Commun"},{"key":"2662_CR8","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1038\/s41588-019-0379-x","volume":"51","author":"AR Martin","year":"2019","unstructured":"Martin AR, Kanai M, Kamatani Y, Okada Y, Neale BM, Daly MJ. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat Genet. 2019;51:584\u201391.","journal-title":"Nat Genet"},{"key":"2662_CR9","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.cell.2019.02.048","volume":"177","author":"G Sirugo","year":"2019","unstructured":"Sirugo G, Williams SM, Tishkoff SA. The missing diversity in human genetic studies. Cell. 2019;177:26\u201331.","journal-title":"Cell"},{"key":"2662_CR10","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/s12687-017-0316-6","volume":"8","author":"AR Bentley","year":"2017","unstructured":"Bentley AR, Callier S, Rotimi CN. Diversity and inclusion in genomic research: why the uneven progress? J Community Genet. 2017;8:255\u201366.","journal-title":"J Community Genet"},{"key":"2662_CR11","doi-asserted-by":"publisher","first-page":"e1009670","DOI":"10.1371\/journal.pgen.1009670","volume":"17","author":"LG Fritsche","year":"2021","unstructured":"Fritsche LG, Ma Y, Zhang D, Salvatore M, Lee S, Zhou X, et al. On cross-ancestry cancer polygenic risk scores. PLOS Genet. 2021;17:e1009670.","journal-title":"PLOS Genet"},{"key":"2662_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.xgen.2022.100118","volume":"2","author":"N Mars","year":"2022","unstructured":"Mars N, Kerminen S, Feng YCA, Kanai M, L\u00e4ll K, Thomas LF, et al. Genome-wide risk prediction of common diseases across ancestries in one million people. Cell Genomics. 2022;2:100118.","journal-title":"Cell Genomics"},{"key":"2662_CR13","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-016-1016-y","volume":"17","author":"S Petrovski","year":"2016","unstructured":"Petrovski S, Goldstein DB. Unequal representation of genetic variation across ancestry groups creates healthcare inequality in the application of precision medicine. Genome Biol. 2016;17:157.","journal-title":"Genome Biol"},{"key":"2662_CR14","first-page":"110","volume":"18","author":"N Timpson","year":"2017","unstructured":"Timpson N, Greenwood C, Soranzo N. Genetic architecture: the shape of the genetic contribution to human traits and disease. Nat Rev Genet. 2017;18:110\u201324.","journal-title":"Nat Rev Genet"},{"key":"2662_CR15","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1038\/s41586-019-1310-4","volume":"570","author":"GL Wojcik","year":"2019","unstructured":"Wojcik GL, Graff M, Nishimura KK, Tao R, Haessler J, Gignoux CR, et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature. 2019;570:514\u20138.","journal-title":"Nature."},{"key":"2662_CR16","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41586-018-0579-z","volume":"562","author":"C Bycroft","year":"2018","unstructured":"Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203\u20139.","journal-title":"Nature"},{"key":"2662_CR17","doi-asserted-by":"publisher","DOI":"10.1192\/bjo.2019.100","volume":"6","author":"KAS Davis","year":"2020","unstructured":"Davis KAS, Coleman JRI, Adams M, Allen N, Breen G, Cullen B, et al. Mental health in UK Biobank \u2013 development, implementation and results from an online questionnaire completed by 157 366 participants: a reanalysis. BJPsych Open. 2020;6:e18.","journal-title":"BJPsych Open"},{"key":"2662_CR18","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1002\/mpr.47","volume":"7","author":"RC Kessler","year":"1998","unstructured":"Kessler RC, Andrews G, Mroczek D, Ustun B, Wittchen HU. The World Health Organization Composite International Diagnostic Interview short-form (CIDI-SF). Int J Methods Psychiatr Res. 1998;7:171\u201385.","journal-title":"Int J Methods Psychiatr Res"},{"key":"2662_CR19","doi-asserted-by":"publisher","DOI":"10.1038\/s41398-020-0848-0","volume":"10","author":"DM Howard","year":"2020","unstructured":"Howard DM, Folkersen L, Coleman JRI, Adams MJ, Glanville K, Werge T, et al. Genetic stratification of depression in UK Biobank. Transl Psychiatry. 2020;10:163.","journal-title":"Transl Psychiatry"},{"key":"2662_CR20","doi-asserted-by":"publisher","DOI":"10.1093\/gigascience\/giz082","volume":"8","author":"SW Choi","year":"2019","unstructured":"Choi SW, O\u2019Reilly PF. PRSice-2: Polygenic Risk Score software for biobank-scale data. GigaScience. 2019;8:giz082.","journal-title":"GigaScience"},{"key":"2662_CR21","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1038\/ng.3211","volume":"47","author":"Bulik-Sullivan","year":"2015","unstructured":"Bulik-Sullivan, Loh BK, Finucane PR, Ripke HK, Yang S, Schizophrenia Working Group of the Psychiatric Genomics Consortium J, et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47:291\u20135.","journal-title":"Nat Genet"},{"key":"2662_CR22","doi-asserted-by":"publisher","first-page":"1228","DOI":"10.1038\/ng.3404","volume":"47","author":"HK Finucane","year":"2015","unstructured":"Finucane HK, Bulik-Sullivan B, Gusev A, Trynka G, Reshef Y, Loh PR, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat Genet. 2015;47:1228\u201335.","journal-title":"Nat Genet"},{"key":"2662_CR23","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1038\/s41586-023-06079-4","volume":"618","author":"Y Ding","year":"2023","unstructured":"Ding Y, Hou K, Xu Z, Pimplaskar A, Petter E, Boulier K, et al. Polygenic scoring accuracy varies across the genetic ancestry continuum. Nature. 2023;618:774\u201381.","journal-title":"Nature"},{"key":"2662_CR24","doi-asserted-by":"publisher","first-page":"777","DOI":"10.1017\/S0033291717002148","volume":"48","author":"AC Edwards","year":"2018","unstructured":"Edwards AC, Docherty AR, Moscati A, Bigdeli TB, Peterson RE, Webb BT, et al. Polygenic risk for severe psychopathology among Europeans is associated with major depressive disorder in Han Chinese women. Psychol Med. 2018;48:777\u201389.","journal-title":"Psychol Med"},{"key":"2662_CR25","doi-asserted-by":"publisher","first-page":"2526","DOI":"10.1017\/S0033291719002629","volume":"50","author":"MJ Adams","year":"2020","unstructured":"Adams MJ, Howard DM, Luciano M, Clarke TK, Davies G, Hill WD, et al. Genetic stratification of depression by neuroticism: revisiting a diagnostic tradition. Psychol Med. 2020;50:2526\u201335.","journal-title":"Psychol Med"},{"key":"2662_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1001\/jamapsychiatry.2019.4188","volume":"77","author":"S Bahrami","year":"2020","unstructured":"Bahrami S, Steen NE, Shadrin A, O\u2019Connell K, Frei O, Bettella F, et al. Shared genetic loci between body mass index and major psychiatric disorders. JAMA Psychiatry. 2020;77:1\u201311.","journal-title":"JAMA Psychiatry"},{"key":"2662_CR27","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1016\/j.biopsych.2016.05.010","volume":"81","author":"RA Power","year":"2017","unstructured":"Power RA, Tansey KE, Buttensch\u00f8n HN, Cohen-Woods S, Bigdeli T, Hall LS, et al. Genome-wide association for major depression through age at onset stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. Biol Psychiatry. 2017;81:325\u201335.","journal-title":"Biol Psychiatry"},{"key":"2662_CR28","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1038\/s41593-018-0326-7","volume":"22","author":"DM Howard","year":"2019","unstructured":"Howard DM, Adams MJ, Clarke TK, Hafferty JD, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343\u201352.","journal-title":"Nat Neurosci"},{"key":"2662_CR29","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1038\/nature14177","volume":"518","author":"AE Locke","year":"2015","unstructured":"Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197\u2013206.","journal-title":"Nature"},{"key":"2662_CR30","doi-asserted-by":"publisher","first-page":"704","DOI":"10.1038\/s41586-022-05275-y","volume":"610","author":"L Yengo","year":"2022","unstructured":"Yengo L, Vedantam S, Marouli E, Sidorenko J, Bartell E, Sakaue S, et al. A saturated map of common genetic variants associated with human height. Nature. 2022;610:704\u201312.","journal-title":"Nature"},{"key":"2662_CR31","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1038\/s41586-022-04434-5","volume":"604","author":"V Trubetskoy","year":"2022","unstructured":"Trubetskoy V, Panagiotaropoulou G, Awasthi S, Braun A, Kraft J, Skarabis N, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature. 2022;604:502\u20138.","journal-title":"Nature."},{"key":"2662_CR32","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1038\/s41588-022-01016-z","volume":"54","author":"A Okbay","year":"2022","unstructured":"Okbay A, Wu Y, Wang N, Jayashankar H, Bennett M, Nehzati SM, et al. Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nat Genet. 2022;54:437\u201349.","journal-title":"Nat Genet"},{"key":"2662_CR33","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1038\/s41588-021-00857-4","volume":"53","author":"N Mullins","year":"2021","unstructured":"Mullins N, Forstner AJ, O\u2019Connell KS, Coombes B, Coleman JRI, Qiao Z, et al. Genome-wide association study of over 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet. 2021;53:817\u201329.","journal-title":"Nat Genet"},{"key":"2662_CR34","doi-asserted-by":"publisher","first-page":"920","DOI":"10.1038\/s41588-018-0151-7","volume":"50","author":"M Nagel","year":"2018","unstructured":"Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, et al. Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. Nat Genet. 2018;50:920\u20137.","journal-title":"Nat Genet"}],"container-title":["Molecular Psychiatry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41380-024-02662-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41380-024-02662-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41380-024-02662-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T15:03:08Z","timestamp":1734361388000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41380-024-02662-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,16]]},"references-count":34,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["2662"],"URL":"https:\/\/doi.org\/10.1038\/s41380-024-02662-x","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2023.12.24.23300412","asserted-by":"object"}]},"ISSN":["1359-4184","1476-5578"],"issn-type":[{"value":"1359-4184","type":"print"},{"value":"1476-5578","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,16]]},"assertion":[{"value":"16 December 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 June 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 July 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"YJ, CT are employed by and hold stock or stock options in 23andMe, Inc. All other authors declare no conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The research involved human data in accordance with the Declaration of Helsinki. All participants provided written informed consent and the current study (application number 4844) was approved by the NHS National Research Ethics Service (approval letter dated 17th June 2011, Ref 11\/NW\/0382). All participants gave full informed written consent.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}]}}