{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T19:57:32Z","timestamp":1789070252297,"version":"build-2803163510"},"reference-count":94,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:00:00Z","timestamp":1763510400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:00:00Z","timestamp":1763510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100004359","name":"Vetenskapsr\u00e5det","doi-asserted-by":"publisher","award":["2021-02615_VR"],"award-info":[{"award-number":["2021-02615_VR"]}],"id":[{"id":"10.13039\/501100004359","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004359","name":"Vetenskapsr\u00e5det","doi-asserted-by":"publisher","award":["2021-02732"],"award-info":[{"award-number":["2021-02732"]}],"id":[{"id":"10.13039\/501100004359","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010661","name":"EC | Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["964874"],"award-info":[{"award-number":["964874"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005416","name":"Norges Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["296030"],"award-info":[{"award-number":["296030"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005416","name":"Norges Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["223273"],"award-info":[{"award-number":["223273"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mol Psychiatry"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1038\/s41380-025-03357-7","type":"journal-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T13:43:15Z","timestamp":1763559795000},"page":"2005-2013","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Genome-wide meta-analyses of non-response to antidepressants provide insights into underlying molecular genetics and suggest potential pharmacotherapies"],"prefix":"10.1038","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3727-4470","authenticated-orcid":false,"given":"Elise","family":"Koch","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tuuli","family":"Puusepp","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1326-2339","authenticated-orcid":false,"given":"Gu\u00f0mundur","family":"Einarsson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9050-1516","authenticated-orcid":false,"given":"Brittany L.","family":"Mitchell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arvid","family":"Harder","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhao","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luis M.","family":"Garc\u00eda-Mar\u00edn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0494-2751","authenticated-orcid":false,"given":"Kristi","family":"Krebs","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexey A.","family":"Shadrin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7644-014X","authenticated-orcid":false,"given":"Ying","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"Estonian Biobank Research Team","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andres","family":"Metspalu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"T\u00f5nu","family":"Esko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reedik","family":"M\u00e4gi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mari","family":"Nelis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georgi","family":"Hudjashov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6427-2625","authenticated-orcid":false,"given":"Oleksandr","family":"Frei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9933-3654","authenticated-orcid":false,"given":"Yi","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2452-1500","authenticated-orcid":false,"given":"Sara","family":"H\u00e4gg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4626-7248","authenticated-orcid":false,"given":"Miguel E.","family":"Renter\u00eda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1382-380X","authenticated-orcid":false,"given":"Sarah E.","family":"Medland","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7421-3357","authenticated-orcid":false,"given":"Naomi R.","family":"Wray","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4069-8020","authenticated-orcid":false,"given":"Nicholas G.","family":"Martin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"H\u00fcbel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2053-1792","authenticated-orcid":false,"given":"Gerome","family":"Breen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5149-7040","authenticated-orcid":false,"given":"Thorgeir","family":"Thorgeirsson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9331-6666","authenticated-orcid":false,"given":"Hreinn","family":"Stef\u00e1nsson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1676-864X","authenticated-orcid":false,"given":"K\u00e1ri","family":"Stef\u00e1nsson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kelli","family":"Lehto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5323-3102","authenticated-orcid":false,"given":"Lili","family":"Milani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4461-3568","authenticated-orcid":false,"given":"Ole A.","family":"Andreassen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin S.","family":"O\u2019Connell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,19]]},"reference":[{"key":"3357_CR1","doi-asserted-by":"publisher","first-page":"1508","DOI":"10.1136\/bmj.l1508","volume":"364","author":"G Iacobucci","year":"2019","unstructured":"Iacobucci G. NHS prescribed record number of antidepressants last year. BMJ. 2019;364:1508.","journal-title":"BMJ"},{"key":"3357_CR2","first-page":"1","volume":"283","author":"LA Pratt","year":"2017","unstructured":"Pratt LA, Brody DJ, Gu Q. Antidepressant use among persons aged 12 and over: United States, 2011\u20132014. NCHS Data Brief. 2017;283:1\u20138.","journal-title":"NCHS Data Brief"},{"key":"3357_CR3","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1002\/pds.1541","volume":"17","author":"AJ Smith","year":"2008","unstructured":"Smith AJ, Sketris I, Cooke C, Gardner D, Kisely S, Tett SE. A comparison of antidepressant use in Nova Scotia, Canada and Australia. Pharmacoepidemiol Drug Saf. 2008;17:697\u2013706.","journal-title":"Pharmacoepidemiol Drug Saf"},{"key":"3357_CR4","doi-asserted-by":"publisher","first-page":"693","DOI":"10.2174\/1570159X19666210517150418","volume":"20","author":"TB Jannini","year":"2022","unstructured":"Jannini TB, Lorenzo GD, Bianciardi E, Niolu C, Toscano M, Ciocca G, et al. Off-label uses of selective serotonin reuptake inhibitors (SSRIs). Curr Neuropharmacol. 2022;20:693\u2013712.","journal-title":"Curr Neuropharmacol"},{"key":"3357_CR5","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.clinthera.2011.11.024","volume":"34","author":"HD Anderson","year":"2012","unstructured":"Anderson HD, Pace WD, Libby AM, West DR, Valuck RJ. Rates of 5 common antidepressant side effects among new adult and adolescent cases of depression: a retrospective US claims study. Clin Ther. 2012;34:113\u201323.","journal-title":"Clin Ther"},{"key":"3357_CR6","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1176\/appi.ajp.163.1.28","volume":"163","author":"M Trivedi","year":"2006","unstructured":"Trivedi M, Rush A, Wisniewski S, Nierenberg AA, Warden D, Ritz L, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163:28\u201340.","journal-title":"Am J Psychiatry"},{"key":"3357_CR7","doi-asserted-by":"publisher","first-page":"1905","DOI":"10.1176\/ajp.2006.163.11.1905","volume":"163","author":"A Rush","year":"2006","unstructured":"Rush A, Trivedi B, Wisniewski S, Nierenberg AA, Stewart J, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163:1905\u201317.","journal-title":"Am J Psychiatry"},{"key":"3357_CR8","first-page":"420","volume":"16","author":"A Cipriani","year":"2018","unstructured":"Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Focus (Am Psychiatr Publ). 2018;16:420\u20139.","journal-title":"Focus (Am Psychiatr Publ)"},{"key":"3357_CR9","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.jad.2008.01.006","volume":"110","author":"D Amital","year":"2008","unstructured":"Amital D, Fostick L, Silberman A, Beckman M, Spivak B. Serious life events among resistant and non-resistant MDD patients. J Affect Disord. 2008;110:260\u20134.","journal-title":"J Affect Disord"},{"key":"3357_CR10","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1016\/j.psychres.2016.04.034","volume":"240","author":"V De Carlo","year":"2016","unstructured":"De Carlo V, Calati R, Serretti A. Socio-demographic and clinical predictors of non-response\/non-remission in treatment resistant depressed patients: A systematic review. Psychiatry Res. 2016;240:421\u201330.","journal-title":"Psychiatry Res"},{"key":"3357_CR11","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1093\/ijnp\/pyy024","volume":"22","author":"C Fabbri","year":"2019","unstructured":"Fabbri C, Corponi F, Souery D, Kasper S, Montgomery S, Zohar J, et al. The genetics of treatment-resistant depression: a critical review and future perspectives. Int J Neuropsychopharmacol. 2019;22:93\u2013104.","journal-title":"Int J Neuropsychopharmacol"},{"key":"3357_CR12","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1016\/j.biopsych.2012.10.030","volume":"73","author":"KE Tansey","year":"2013","unstructured":"Tansey KE, Guipponi M, Hu X, Domenici E, Lewis G, Malafosse A, et al. Contribution of common genetic variants to antidepressant response. Biol Psychiatry. 2013;73:679\u201382.","journal-title":"Biol Psychiatry"},{"key":"3357_CR13","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.bpsgos.2021.07.008","volume":"2","author":"O Pain","year":"2022","unstructured":"Pain O, Hodgson K, Trubetskoy V, Ripke S, Marshe VS, Adams MJ, et al. Identifying the common genetic basis of antidepressant response. Biol Psychiatry Glob Open Sci. 2022;2:115\u201326.","journal-title":"Biol Psychiatry Glob Open Sci"},{"key":"3357_CR14","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1176\/appi.ajp.2012.12020237","volume":"170","author":"GENDEP, MARS, STAR*D","year":"2013","unstructured":"GENDEP, MARS, STAR*D. Common genetic variation and antidepressant efficacy in major depressive disorder: a meta-analysis of three genome-wide pharmacogenetic studies. Am J Psychiatry. 2013;170:207\u201317.","journal-title":"Am J Psychiatry"},{"key":"3357_CR15","doi-asserted-by":"publisher","DOI":"10.1038\/tp.2015.47","volume":"5","author":"JM Biernacka","year":"2015","unstructured":"Biernacka JM, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, et al. The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Transl Psychiatry. 2015;5:e553.","journal-title":"Transl Psychiatry"},{"key":"3357_CR16","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1192\/bjp.2018.256","volume":"214","author":"C Fabbri","year":"2019","unstructured":"Fabbri C, Kasper S, Kautzky A, Bartova L, Dold M, Zohar J, et al. Genome-wide association study of treatment-resistance in depression and meta-analysis of three independent samples. Br J Psychiatry. 2019;214:36\u201341.","journal-title":"Br J Psychiatry"},{"key":"3357_CR17","doi-asserted-by":"publisher","first-page":"e1001326","DOI":"10.1371\/journal.pmed.1001326","volume":"9","author":"KE Tansey","year":"2012","unstructured":"Tansey KE, Guipponi M, Perroud N, Bondolfi G, Domenici E, Evans D, et al. Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis. PLoS Med. 2012;9:e1001326.","journal-title":"PLoS Med"},{"key":"3357_CR18","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1038\/tpj.2017.44","volume":"18","author":"C Fabbri","year":"2018","unstructured":"Fabbri C, Tansey KE, Perlis RH, Hauser J, Henigsberg N, Maier W, et al. New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation. Pharmacogenomics J. 2018;18:413\u201321.","journal-title":"Pharmacogenomics J"},{"key":"3357_CR19","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1038\/s41397-019-0067-3","volume":"20","author":"EM Wigmore","year":"2020","unstructured":"Wigmore EM, Hafferty JD, Hall LS, Howard DM, Clarke TK, Fabbri C, et al. Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP. Pharmacogenomics J. 2020;20:329\u201341.","journal-title":"Pharmacogenomics J"},{"key":"3357_CR20","doi-asserted-by":"publisher","DOI":"10.1038\/s41398-020-01035-6","volume":"10","author":"QS Li","year":"2020","unstructured":"Li QS, Tian C, Hinds D, andMe Research T. Genome-wide association studies of antidepressant class response and treatment-resistant depression. Transl Psychiatry. 2020;10:360.","journal-title":"Transl Psychiatry"},{"key":"3357_CR21","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.biopsych.2024.01.001","volume":"96","author":"E Koch","year":"2024","unstructured":"Koch E, Pardinas AF, O\u2019Connell KS, Selvaggi P, Camacho Collados J, Babic A, et al. How real-world data can facilitate the development of precision medicine treatment in psychiatry. Biol Psychiatry. 2024;96:543\u201351.","journal-title":"Biol Psychiatry"},{"key":"3357_CR22","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1093\/ije\/dyt268","volume":"44","author":"L Leitsalu","year":"2015","unstructured":"Leitsalu L, Haller T, Esko T, Tammesoo ML, Alavere H, Snieder H, et al. Cohort profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int J Epidemiol. 2015;44:1137\u201347.","journal-title":"Int J Epidemiol"},{"key":"3357_CR23","doi-asserted-by":"publisher","first-page":"dyae017","DOI":"10.1093\/ije\/dyae017","volume":"53","author":"T Ojalo","year":"2024","unstructured":"Ojalo T, Haan E, Koiv K, Kariis HM, Krebs K, Uusberg H, et al. Cohort profile update: mental health online survey in the Estonian Biobank (EstBB MHoS). Int J Epidemiol. 2024;53:dyae017.","journal-title":"Int J Epidemiol"},{"key":"3357_CR24","doi-asserted-by":"publisher","first-page":"e032580","DOI":"10.1136\/bmjopen-2019-032580","volume":"10","author":"EM Byrne","year":"2020","unstructured":"Byrne EM, Kirk KM, Medland SE, McGrath JJ, Colodro-Conde L, Parker R, et al. Cohort profile: the Australian genetics of depression study. BMJ Open. 2020;10:e032580.","journal-title":"BMJ Open"},{"key":"3357_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.brat.2019.103503","volume":"123","author":"MR Davies","year":"2019","unstructured":"Davies MR, Kalsi G, Armour C, Jones IR, McIntosh AM, Smith DJ, et al. The Genetic Links to Anxiety and Depression (GLAD) Study: online recruitment into the largest recontactable study of depression and anxiety. Behav Res Ther. 2019;123:103503.","journal-title":"Behav Res Ther"},{"key":"3357_CR26","doi-asserted-by":"publisher","first-page":"e1001779","DOI":"10.1371\/journal.pmed.1001779","volume":"12","author":"C Sudlow","year":"2015","unstructured":"Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12:e1001779.","journal-title":"PLoS Med"},{"key":"3357_CR27","doi-asserted-by":"publisher","DOI":"10.1038\/tp.2016.171","volume":"6","author":"QS Li","year":"2016","unstructured":"Li QS, Tian C, Seabrook GR, Drevets WC, Narayan VA. Analysis of 23andMe antidepressant efficacy survey data: implication of circadian rhythm and neuroplasticity in bupropion response. Transl Psychiatry. 2016;6:e889.","journal-title":"Transl Psychiatry"},{"key":"3357_CR28","doi-asserted-by":"publisher","first-page":"2190","DOI":"10.1093\/bioinformatics\/btq340","volume":"26","author":"CJ Willer","year":"2010","unstructured":"Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26:2190\u20131.","journal-title":"Bioinformatics"},{"key":"3357_CR29","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1016\/j.ajhg.2009.11.001","volume":"85","author":"DY Lin","year":"2009","unstructured":"Lin DY, Sullivan PF. Meta-analysis of genome-wide association studies with overlapping subjects. Am J Hum Genet. 2009;85:862\u201372.","journal-title":"Am J Hum Genet"},{"key":"3357_CR30","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-017-01261-5","volume":"8","author":"K Watanabe","year":"2017","unstructured":"Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8:1826.","journal-title":"Nat Commun"},{"key":"3357_CR31","doi-asserted-by":"publisher","first-page":"D1005","DOI":"10.1093\/nar\/gky1120","volume":"47","author":"A Buniello","year":"2019","unstructured":"Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47:D1005\u2013D1012.","journal-title":"Nucleic Acids Res"},{"key":"3357_CR32","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1126\/science.1262110","volume":"348","author":"Consortium G.","year":"2015","unstructured":"Consortium G. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348:648\u201360.","journal-title":"Science"},{"key":"3357_CR33","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.nbd.2012.03.020","volume":"47","author":"DG Hernandez","year":"2012","unstructured":"Hernandez DG, Nalls MA, Moore M, Chong S, Dillman A, Trabzuni D, et al. Integration of GWAS SNPs and tissue specific expression profiling reveal discrete eQTLs for human traits in blood and brain. Neurobiol Dis. 2012;47:20\u20138.","journal-title":"Neurobiol Dis"},{"key":"3357_CR34","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1038\/ng.2892","volume":"46","author":"M Kircher","year":"2014","unstructured":"Kircher M, Witten DM, Jain P, O\u2019Roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46:310\u20135.","journal-title":"Nat Genet"},{"key":"3357_CR35","doi-asserted-by":"publisher","first-page":"1790","DOI":"10.1101\/gr.137323.112","volume":"22","author":"AP Boyle","year":"2012","unstructured":"Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22:1790\u20137.","journal-title":"Genome Res"},{"key":"3357_CR36","doi-asserted-by":"publisher","first-page":"D1311","DOI":"10.1093\/nar\/gkaa840","volume":"49","author":"M Ghoussaini","year":"2021","unstructured":"Ghoussaini M, Mountjoy E, Carmona M, Peat G, Schmidt EM, Hercules A, et al. Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics. Nucleic Acids Res. 2021;49:D1311\u2013D1320.","journal-title":"Nucleic Acids Res"},{"key":"3357_CR37","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-017-02317-2","volume":"9","author":"Z Zhu","year":"2018","unstructured":"Zhu Z, Zheng Z, Zhang F, Wu Y, Trzaskowski M, Maier R, et al. Causal associations between risk factors and common diseases inferred from GWAS summary data. Nat Commun. 2018;9:224.","journal-title":"Nat Commun"},{"key":"3357_CR38","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-03819-3","volume":"9","author":"DM Howard","year":"2018","unstructured":"Howard DM, Adams MJ, Shirali M, Clarke TK, Marioni RE, Davies G, et al. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nat Commun. 2018;9:1470.","journal-title":"Nat Commun"},{"key":"3357_CR39","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1038\/ng.3211","volume":"47","author":"BK Bulik-Sullivan","year":"2015","unstructured":"Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S, Yang J, Schizophrenia Working Group of the Psychiatric Genomics C. 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":"3357_CR40","doi-asserted-by":"publisher","first-page":"3363","DOI":"10.1038\/s41380-021-01062-9","volume":"26","author":"C Fabbri","year":"2021","unstructured":"Fabbri C, Hagenaars SP, John C, Williams AT, Shrine N, Moles L, et al. Genetic and clinical characteristics of treatment-resistant depression using primary care records in two UK cohorts. Mol Psychiatry. 2021;26:3363\u201373.","journal-title":"Mol Psychiatry"},{"key":"3357_CR41","doi-asserted-by":"publisher","first-page":"1276","DOI":"10.1038\/s41588-021-00921-z","volume":"53","author":"DP Wightman","year":"2021","unstructured":"Wightman DP, Jansen IE, Savage JE, Shadrin AA, Bahrami S, Holland D, et al. A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer\u2019s disease. Nat Genet. 2021;53:1276\u201382.","journal-title":"Nat Genet"},{"key":"3357_CR42","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1038\/s41588-022-01285-8","volume":"55","author":"D Demontis","year":"2023","unstructured":"Demontis D, Walters GB, Athanasiadis G, Walters R, Therrien K, Nielsen TT, et al. Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains. Nat Genet. 2023;55:198\u2013208.","journal-title":"Nat Genet"},{"key":"3357_CR43","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1038\/s41588-019-0344-8","volume":"51","author":"J Grove","year":"2019","unstructured":"Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al. Identification of common genetic risk variants for autism spectrum disorder. Nat Genet. 2019;51:431\u201344.","journal-title":"Nat Genet"},{"key":"3357_CR44","doi-asserted-by":"publisher","first-page":"3292","DOI":"10.1038\/s41380-019-0559-1","volume":"25","author":"KL Purves","year":"2020","unstructured":"Purves KL, Coleman JRI, Meier SM, Rayner C, Davis KAS, Cheesman R, et al. A major role for common genetic variation in anxiety disorders. Mol Psychiatry. 2020;25:3292\u2013303.","journal-title":"Mol Psychiatry"},{"key":"3357_CR45","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 more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet. 2021;53:817\u201329.","journal-title":"Nat Genet"},{"key":"3357_CR46","doi-asserted-by":"publisher","first-page":"1112","DOI":"10.1038\/s41588-018-0147-3","volume":"50","author":"JJ Lee","year":"2018","unstructured":"Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50:1112\u201321.","journal-title":"Nat Genet"},{"key":"3357_CR47","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":"3357_CR48","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1038\/s41588-018-0152-6","volume":"50","author":"JE Savage","year":"2018","unstructured":"Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat Genet. 2018;50:912\u20139.","journal-title":"Nat Genet"},{"key":"3357_CR49","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1038\/s41588-018-0333-3","volume":"51","author":"PR Jansen","year":"2019","unstructured":"Jansen PR, Watanabe K, Stringer S, Skene N, Bryois J, Hammerschlag AR, et al. Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways. Nat Genet. 2019;51:394\u2013403.","journal-title":"Nat Genet"},{"key":"3357_CR50","doi-asserted-by":"publisher","first-page":"3091","DOI":"10.1038\/s41380-019-0439-8","volume":"25","author":"J Ward","year":"2020","unstructured":"Ward J, Tunbridge EM, Sandor C, Lyall LM, Ferguson A, Strawbridge RJ, et al. The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function. Mol Psychiatry. 2020;25:3091\u20139.","journal-title":"Mol Psychiatry"},{"key":"3357_CR51","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"},{"key":"3357_CR52","doi-asserted-by":"publisher","first-page":"1394","DOI":"10.1038\/s41593-019-0447-7","volume":"22","author":"J Gelernter","year":"2019","unstructured":"Gelernter J, Sun N, Polimanti R, Pietrzak R, Levey DF, Bryois J, et al. Genome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans. Nat Neurosci. 2019;22:1394\u2013401.","journal-title":"Nat Neurosci"},{"key":"3357_CR53","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1038\/s41586-022-04434-5","volume":"604","author":"V Trubetskoy","year":"2022","unstructured":"Trubetskoy V, Pardinas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature. 2022;604:502\u20138.","journal-title":"Nature"},{"key":"3357_CR54","doi-asserted-by":"publisher","first-page":"624","DOI":"10.1038\/ng.3552","volume":"48","author":"A Okbay","year":"2016","unstructured":"Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet. 2016;48:624\u201333.","journal-title":"Nat Genet"},{"key":"3357_CR55","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-12653-0","volume":"10","author":"LR Lloyd-Jones","year":"2019","unstructured":"Lloyd-Jones LR, Zeng J, Sidorenko J, Yengo L, Moser G, Kemper KE, et al. Improved polygenic prediction by Bayesian multiple regression on summary statistics. Nat Commun. 2019;10:5086.","journal-title":"Nat Commun"},{"key":"3357_CR56","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1038\/nature15393","volume":"526","author":"A Auton","year":"2015","unstructured":"Genomes Project C, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al. A global reference for human genetic variation. Nature. 2015;526:68\u201374.","journal-title":"Nature"},{"key":"3357_CR57","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v036.i03","volume":"36","author":"W Viechtbauer","year":"2010","unstructured":"Viechtbauer W. Conducting Meta-Analyses in R with the metafor Package. J Stat Softw. 2010;36:1\u201348.","journal-title":"J Stat Softw"},{"key":"3357_CR58","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.1038\/s41588-024-01771-1","volume":"56","author":"O Frei","year":"2024","unstructured":"Frei O, Hindley G, Shadrin AA, van der Meer D, Akdeniz BC, Hagen E, et al. Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets. Nat Genet. 2024;56:1310\u20138.","journal-title":"Nat Genet"},{"key":"3357_CR59","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2301342120","volume":"120","author":"D Morselli Gysi","year":"2023","unstructured":"Morselli Gysi D, Barabasi AL. Noncoding RNAs improve the predictive power of network medicine. Proc Natl Acad Sci USA. 2023;120:e2301342120.","journal-title":"Proc Natl Acad Sci USA"},{"key":"3357_CR60","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1038\/nbt1338","volume":"25","author":"MA Yildirim","year":"2007","unstructured":"Yildirim MA, Goh KI, Cusick ME, Barabasi AL, Vidal M. Drug-target network. Nat Biotechnol. 2007;25:1119\u201326.","journal-title":"Nat Biotechnol"},{"key":"3357_CR61","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1016\/j.ajhg.2008.02.013","volume":"82","author":"S K\u00f6hler","year":"2008","unstructured":"K\u00f6hler S, Bauer S, Horn D, Robinson PN. Walking the interactome for prioritization of candidate disease genes. Am J Hum Genet. 2008;82:949\u201358.","journal-title":"Am J Hum Genet"},{"key":"3357_CR62","doi-asserted-by":"publisher","first-page":"e1000641","DOI":"10.1371\/journal.pcbi.1000641","volume":"6","author":"O Vanunu","year":"2010","unstructured":"Vanunu O, Magger O, Ruppin E, Shlomi T, Sharan R. Associating genes and protein complexes with disease via network propagation. PLoS Comput Biol. 2010;6:e1000641.","journal-title":"PLoS Comput Biol"},{"key":"3357_CR63","doi-asserted-by":"publisher","first-page":"e1005598","DOI":"10.1371\/journal.pcbi.1005598","volume":"13","author":"DE Carlin","year":"2017","unstructured":"Carlin DE, Demchak B, Pratt D, Sage E, Ideker T. Network propagation in the cytoscape cyberinfrastructure. PLoS Comput Biol. 2017;13:e1005598.","journal-title":"PLoS Comput Biol"},{"key":"3357_CR64","doi-asserted-by":"publisher","first-page":"2498","DOI":"10.1101\/gr.1239303","volume":"13","author":"P Shannon","year":"2003","unstructured":"Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498\u2013504.","journal-title":"Genome Res"},{"key":"3357_CR65","doi-asserted-by":"publisher","first-page":"D1227","DOI":"10.1093\/nar\/gkad1040","volume":"52","author":"M Cannon","year":"2024","unstructured":"Cannon M, Stevenson J, Stahl K, Basu R, Coffman A, Kiwala S, et al. DGIdb 5.0: rebuilding the drug-gene interaction database for precision medicine and drug discovery platforms. Nucleic Acids Res. 2024;52:D1227\u2013D1235.","journal-title":"Nucleic Acids Res"},{"key":"3357_CR66","doi-asserted-by":"publisher","first-page":"1929","DOI":"10.1126\/science.1132939","volume":"313","author":"J Lamb","year":"2006","unstructured":"Lamb J, Crawford ED, Peck D, Modell JW, Blat IC, Wrobel MJ, et al. The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006;313:1929\u201335.","journal-title":"Science"},{"key":"3357_CR67","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1016\/j.cell.2017.10.049","volume":"171","author":"A Subramanian","year":"2017","unstructured":"Subramanian A, Narayan R, Corsello SM, Peck DD, Natoli TE, Lu X, et al. A next generation connectivity map: L1000 platform and the first 1,000,000 profiles. Cell. 2017;171:1437\u201352.e1417.","journal-title":"Cell"},{"key":"3357_CR68","doi-asserted-by":"publisher","first-page":"1427","DOI":"10.1093\/bioinformatics\/bty784","volume":"35","author":"OM Enache","year":"2019","unstructured":"Enache OM, Lahr DL, Natoli TE, Litichevskiy L, Wadden D, Flynn C, et al. The GCTx format and cmapPy, R, M, J packages: resources for optimized storage and integrated traversal of annotated dense matrices. Bioinformatics. 2019;35:1427\u20139.","journal-title":"Bioinformatics"},{"key":"3357_CR69","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-03621-1","volume":"9","author":"AN Barbeira","year":"2018","unstructured":"Barbeira AN, Dickinson SP, Bonazzola R, Zheng J, Wheeler HE, Torres JM, et al. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun. 2018;9:1825.","journal-title":"Nat Commun"},{"key":"3357_CR70","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-020-02252-4","volume":"22","author":"AN Barbeira","year":"2021","unstructured":"Barbeira AN, Bonazzola R, Gamazon ER, Liang Y, Park Y, Kim-Hellmuth S, et al. Exploiting the GTEx resources to decipher the mechanisms at GWAS loci. Genome Biol. 2021;22:49.","journal-title":"Genome Biol"},{"key":"3357_CR71","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1038\/ng.2653","volume":"45","author":"Consortium GT","year":"2013","unstructured":"Consortium GT. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45:580\u20135.","journal-title":"Nat Genet"},{"key":"3357_CR72","doi-asserted-by":"publisher","first-page":"e1007889","DOI":"10.1371\/journal.pgen.1007889","volume":"15","author":"AN Barbeira","year":"2019","unstructured":"Barbeira AN, Pividori M, Zheng J, Wheeler HE, Nicolae DL, Im HK. Integrating predicted transcriptome from multiple tissues improves association detection. PLoS Genet. 2019;15:e1007889.","journal-title":"PLoS Genet"},{"key":"3357_CR73","doi-asserted-by":"publisher","first-page":"37171","DOI":"10.1074\/jbc.M112.389916","volume":"287","author":"N Nakaya","year":"2012","unstructured":"Nakaya N, Sultana A, Lee HS, Tomarev SI. Olfactomedin 1 interacts with the Nogo A receptor complex to regulate axon growth. J Biol Chem. 2012;287:37171\u201384.","journal-title":"J Biol Chem"},{"key":"3357_CR74","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1111\/jnc.14231","volume":"143","author":"N Nakaya","year":"2017","unstructured":"Nakaya N, Sultana A, Tomarev SI. Impaired AMPA receptor trafficking by a double knockout of zebrafish olfactomedin1a\/b. J Neurochem. 2017;143:635\u201344.","journal-title":"J Neurochem"},{"key":"3357_CR75","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1016\/j.psychres.2014.12.028","volume":"225","author":"B Bertelsen","year":"2015","unstructured":"Bertelsen B, Melchior L, Jensen LR, Groth C, Nazaryan L, Debes NM, et al. A t(3;9)(q25.1;q34.3) translocation leading to OLFM1 fusion transcripts in Gilles de la Tourette syndrome, OCD and ADHD. Psychiatry Res. 2015;225:268\u201375.","journal-title":"Psychiatry Res"},{"key":"3357_CR76","doi-asserted-by":"publisher","first-page":"2776","DOI":"10.1038\/s41380-021-01061-w","volume":"26","author":"H Le-Niculescu","year":"2021","unstructured":"Le-Niculescu H, Roseberry K, Gill SS, Levey DF, Phalen PL, Mullen J, et al. Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs. Mol Psychiatry. 2021;26:2776\u2013804.","journal-title":"Mol Psychiatry"},{"key":"3357_CR77","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1017\/S0033291711002923","volume":"43","author":"M Wegerer","year":"2013","unstructured":"Wegerer M, Adena S, Pfennig A, Czamara D, Sailer U, Bettecken T, et al. Variants within the GABA transaminase (ABAT) gene region are associated with somatosensory evoked EEG potentials in families at high risk for affective disorders. Psychol Med. 2013;43:1207\u201317.","journal-title":"Psychol Med"},{"key":"3357_CR78","doi-asserted-by":"publisher","first-page":"2007","DOI":"10.2217\/pgs-2016-0093","volume":"17","author":"X Li","year":"2016","unstructured":"Li X, Zhang J, Wu X, Yan H, Zhang Y, He RH, et al. Polymorphisms of ABAT, SCN2A and ALDH5A1 may affect valproic acid responses in the treatment of epilepsy in Chinese. Pharmacogenomics. 2016;17:2007\u201314.","journal-title":"Pharmacogenomics"},{"key":"3357_CR79","doi-asserted-by":"publisher","first-page":"886","DOI":"10.1016\/j.biopsych.2016.05.005","volume":"81","author":"MS Lener","year":"2017","unstructured":"Lener MS, Niciu MJ, Ballard ED, Park M, Park LT, Nugent AC, et al. Glutamate and gamma-aminobutyric acid systems in the pathophysiology of major depression and antidepressant response to ketamine. Biol Psychiatry. 2017;81:886\u201397.","journal-title":"Biol Psychiatry"},{"key":"3357_CR80","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.neuron.2019.03.013","volume":"102","author":"RS Duman","year":"2019","unstructured":"Duman RS, Sanacora G, Krystal JH. Altered connectivity in depression: GABA and glutamate neurotransmitter deficits and reversal by novel treatments. Neuron. 2019;102:75\u201390.","journal-title":"Neuron"},{"key":"3357_CR81","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1038\/mp.2010.120","volume":"16","author":"B Luscher","year":"2011","unstructured":"Luscher B, Shen Q, Sahir N. The GABAergic deficit hypothesis of major depressive disorder. Mol Psychiatry. 2011;16:383\u2013406.","journal-title":"Mol Psychiatry"},{"key":"3357_CR82","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/S0140-6736(22)02080-3","volume":"401","author":"S Marwaha","year":"2023","unstructured":"Marwaha S, Palmer E, Suppes T, Cons E, Young AH, Upthegrove R. Novel and emerging treatments for major depression. Lancet. 2023;401:141\u201353.","journal-title":"Lancet"},{"key":"3357_CR83","doi-asserted-by":"publisher","first-page":"5526","DOI":"10.3390\/ijms23105526","volume":"23","author":"U Bright","year":"2022","unstructured":"Bright U, Akirav I. Modulation of endocannabinoid system components in depression: pre-clinical and clinical evidence. Int J Mol Sci. 2022;23:5526.","journal-title":"Int J Mol Sci"},{"key":"3357_CR84","doi-asserted-by":"publisher","first-page":"325","DOI":"10.3390\/brainsci13020325","volume":"13","author":"A Hasbi","year":"2023","unstructured":"Hasbi A, Madras BK, George SR. Endocannabinoid system and exogenous cannabinoids in depression and anxiety: a review. Brain Sci. 2023;13:325.","journal-title":"Brain Sci"},{"key":"3357_CR85","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1002\/cpt.2903","volume":"114","author":"CA Bousman","year":"2023","unstructured":"Bousman CA, Stevenson JM, Ramsey LB, Sangkuhl K, Hicks JK, Strawn JR, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes and serotonin reuptake inhibitor antidepressants. Clin Pharmacol Ther. 2023;114:51\u201368.","journal-title":"Clin Pharmacol Ther"},{"key":"3357_CR86","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1016\/j.jad.2018.09.067","volume":"243","author":"K Perlman","year":"2019","unstructured":"Perlman K, Benrimoh D, Israel S, Rollins C, Brown E, Tunteng JF, et al. A systematic meta-review of predictors of antidepressant treatment outcome in major depressive disorder. J Affect Disord. 2019;243:503\u201315.","journal-title":"J Affect Disord"},{"key":"3357_CR87","doi-asserted-by":"publisher","first-page":"2379","DOI":"10.2147\/NDT.S170645","volume":"14","author":"T Sternat","year":"2018","unstructured":"Sternat T, Fotinos K, Fine A, Epstein I, Katzman MA. Low hedonic tone and attention-deficit hyperactivity disorder: risk factors for treatment resistance in depressed adults. Neuropsychiatr Dis Treat. 2018;14:2379\u201387.","journal-title":"Neuropsychiatr Dis Treat"},{"key":"3357_CR88","first-page":"PCC.13r01600","volume":"16","author":"Y Ginsberg","year":"2014","unstructured":"Ginsberg Y, Quintero J, Anand E, Casillas M, Upadhyaya HP. Underdiagnosis of attention-deficit\/hyperactivity disorder in adult patients: a review of the literature. Prim Care Companion CNS Disord. 2014;16:PCC.13r01600.","journal-title":"Prim Care Companion CNS Disord"},{"key":"3357_CR89","doi-asserted-by":"publisher","first-page":"1307","DOI":"10.1016\/j.euroneuro.2013.01.004","volume":"23","author":"T Hajek","year":"2013","unstructured":"Hajek T, Kopecek M, Alda M, Uher R, Hoschl C. Why negative meta-analyses may be false? Eur Neuropsychopharmacol. 2013;23:1307\u20139.","journal-title":"Eur Neuropsychopharmacol"},{"key":"3357_CR90","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1016\/S2215-0366(25)00061-6","volume":"12","author":"E Koch","year":"2025","unstructured":"Koch E, Smart S, Einarsson G, Kampe A, Jonsson L, Alver M, et al. Recommendations for defining treatment outcomes in major psychiatric disorders using real-world data. Lancet Psychiatry. 2025;12:457\u201368.","journal-title":"Lancet Psychiatry"},{"key":"3357_CR91","first-page":"CD010753","volume":"5","author":"H Everitt","year":"2018","unstructured":"Everitt H, Baldwin DS, Stuart B, Lipinska G, Mayers A, Malizia AL, et al. Antidepressants for insomnia in adults. Cochrane Database Syst Rev. 2018;5:CD010753.","journal-title":"Cochrane Database Syst Rev"},{"key":"3357_CR92","doi-asserted-by":"publisher","first-page":"1376","DOI":"10.1038\/s41431-025-01894-x","volume":"33","author":"HM Kariis","year":"2025","unstructured":"Kariis HM, Sarg D, Krebs K, Joeloo M, Koiv K, Sirts K, et al. Genetic influences on antidepressant side effects: a CYP2C19 gene variation and polygenic risk study in the Estonian Biobank. Eur J Hum Genet. 2025;33:1376\u201385.","journal-title":"Eur J Hum Genet"},{"key":"3357_CR93","doi-asserted-by":"publisher","first-page":"100502","DOI":"10.1016\/j.bpsgos.2025.100502","volume":"5","author":"CWH Lo","year":"2025","unstructured":"Lo CWH, Gillett AC, Iveson MH, Kamp M, Fabbri C, Wong WLE, et al. Antidepressant switching as a proxy phenotype for drug nonresponse: investigating clinical, demographic, and genetic characteristics. Biol Psychiatry Glob Open Sci. 2025;5:100502.","journal-title":"Biol Psychiatry Glob Open Sci"},{"key":"3357_CR94","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1038\/s41397-022-00267-7","volume":"22","author":"AI Campos","year":"2022","unstructured":"Campos AI, Byrne EM, Mitchell BL, Wray NR, Lind PA, Licinio J, et al. Impact of CYP2C19 metaboliser status on SSRI response: a retrospective study of 9500 participants of the Australian Genetics of Depression Study. Pharmacogenomics J. 2022;22:130\u20135.","journal-title":"Pharmacogenomics J"}],"container-title":["Molecular Psychiatry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41380-025-03357-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41380-025-03357-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41380-025-03357-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T09:03:54Z","timestamp":1773824634000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41380-025-03357-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,19]]},"references-count":94,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["3357"],"URL":"https:\/\/doi.org\/10.1038\/s41380-025-03357-7","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-5418279\/v1","asserted-by":"object"}]},"ISSN":["1359-4184","1476-5578"],"issn-type":[{"value":"1359-4184","type":"print"},{"value":"1476-5578","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,19]]},"assertion":[{"value":"8 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Dr. Andreassen reported grants from Stiftelsen Kristian Gerhard Jebsen, South-East Regional Health Authority, Research Council of Norway, and European Union\u2019s Horizon 2020 during the conduct of the study; personal fees from cortechs.ai (stock options), Lundbeck (speaker\u2019s honorarium), and Sunovion (speaker\u2019s honorarium) and Janssen (speaker\u2019s honorarium) outside the submitted work.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}