{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T09:30:24Z","timestamp":1788255024132,"version":"build-2803163510"},"reference-count":103,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T00:00:00Z","timestamp":1731974400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T00:00:00Z","timestamp":1731974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Sanofi US Services Inc."},{"DOI":"10.13039\/501100007601","name":"Horizon 2020","doi-asserted-by":"publisher","award":["810645"],"award-info":[{"award-number":["810645"]}],"id":[{"id":"10.13039\/501100007601","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007601","name":"Horizon 2020","doi-asserted-by":"publisher","award":["810645"],"award-info":[{"award-number":["810645"]}],"id":[{"id":"10.13039\/501100007601","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007601","name":"Horizon 2020","doi-asserted-by":"publisher","award":["810645"],"award-info":[{"award-number":["810645"]}],"id":[{"id":"10.13039\/501100007601","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["MOBEC008"],"award-info":[{"award-number":["MOBEC008"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["MOBEC008"],"award-info":[{"award-number":["MOBEC008"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["MOBEC008"],"award-info":[{"award-number":["MOBEC008"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002301","name":"Estonian Research Council","doi-asserted-by":"crossref","award":["PRG1291"],"award-info":[{"award-number":["PRG1291"]}],"id":[{"id":"10.13039\/501100002301","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002301","name":"Estonian Research Council","doi-asserted-by":"crossref","award":["PRG1291"],"award-info":[{"award-number":["PRG1291"]}],"id":[{"id":"10.13039\/501100002301","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002301","name":"Estonian Research Council","doi-asserted-by":"crossref","award":["PRG1291"],"award-info":[{"award-number":["PRG1291"]}],"id":[{"id":"10.13039\/501100002301","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005189","name":"Estonian Research Competency Council","doi-asserted-by":"publisher","award":["PRG184"],"award-info":[{"award-number":["PRG184"]}],"id":[{"id":"10.13039\/501100005189","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005189","name":"Estonian Research Competency Council","doi-asserted-by":"publisher","award":["PRG184"],"award-info":[{"award-number":["PRG184"]}],"id":[{"id":"10.13039\/501100005189","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005189","name":"Estonian Research Competency Council","doi-asserted-by":"publisher","award":["PRG184"],"award-info":[{"award-number":["PRG184"]}],"id":[{"id":"10.13039\/501100005189","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014438","name":"Business Finland","doi-asserted-by":"publisher","award":["HUS 4685\/31\/2016"],"award-info":[{"award-number":["HUS 4685\/31\/2016"]}],"id":[{"id":"10.13039\/501100014438","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006483","name":"AbbVie","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006483","id-type":"DOI","asserted-by":"publisher"}]},{"name":"AtraZeneca UK Ltd"},{"name":"Biogen MA Inc."},{"DOI":"10.13039\/100006436","name":"Celgene Corporation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100006436","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Celgene International II S\u00e0rl"},{"DOI":"10.13039\/100004328","name":"Genentech Inc.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100004328","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Merck Sharp & Dohme Corp"},{"DOI":"10.13039\/100004319","name":"Pfizer Inc.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100004319","id-type":"DOI","asserted-by":"crossref"}]},{"name":"GlaxoSmithKline Intellectual Property Development Ltd."},{"name":"Maze Therapeutics Inc."},{"DOI":"10.13039\/100005565","name":"Janssen Biotech Inc","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100005565","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100004336","name":"Novartis AG.","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100004336","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100031283","name":"Sanofi, France","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100031283","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Genomics"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Therapeutic targets supported by genetic evidence from genome-wide association studies (GWAS) show higher probability of success in clinical trials. GWAS is a powerful approach to identify links between genetic variants and phenotypic variation; however, identifying the genes driving associations identified in GWAS remains challenging. Integration of molecular quantitative trait loci (molQTL) such as expression QTL (eQTL) using mendelian randomization (MR) and colocalization analyses can help with the identification of causal genes. Careful interpretation remains warranted because eQTL can affect the expression of multiple genes within the same locus.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used a combination of genomic features that include variant annotation, activity-by-contact maps, MR, and colocalization with molQTL to prioritize causal genes across 4,611 disease GWAS and meta-analyses from biobank studies, namely FinnGen, Estonian Biobank and UK Biobank.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Genes identified using this approach are enriched for gold standard causal genes and capture known biological links between disease genetics and biology. In addition, we find that eQTL colocalizing with GWAS are statistically enriched for corresponding disease-relevant tissues. We show that predicted directionality from MR is generally consistent with matched drug mechanism of actions (&gt;\u200985% for approved drugs). Compared to the nearest gene mapping method, genes supported by multi-omics evidences displayed higher enrichment in approved therapeutic targets (risk ratio 1.75 vs. 2.58 for genes with the highest level of support). Finally, using this approach, we detected anassociation between the IL6 receptor signal transduction gene\n                      <jats:italic>IL6ST<\/jats:italic>\n                      and polymyalgia rheumatica, an indication for which sarilumab, a monoclonal antibody against IL-6, has been recently approved.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Combining variant annotation, activity-by-contact maps, and molQTL increases performance to identify causal genes, while informing on directionality which can be translated to successful target identification and drug development.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12864-024-10971-2","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T09:03:09Z","timestamp":1732006989000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Leveraging large-scale multi-omics evidences to identify therapeutic targets from genome-wide association studies"],"prefix":"10.1186","volume":"25","author":[{"given":"Samuel","family":"Lessard","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Chao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kadri","family":"Reis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"FinnGen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"Estonian Biobank Research Team","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mathieu","family":"Beauvais","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepak K.","family":"Rajpal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Sloane","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priit","family":"Palta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katherine","family":"Klinger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emanuele","family":"de Rinaldis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khader","family":"Shameer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cl\u00e9ment","family":"Chatelain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,19]]},"reference":[{"key":"10971_CR1","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/j.ajhg.2017.06.005","volume":"101","author":"PM Visscher","year":"2017","unstructured":"Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, Yang J. 10 years of GWAS Discovery: Biology, function, and translation. Am J Hum Genet. 2017;101:5\u201322.","journal-title":"Am J Hum Genet"},{"key":"10971_CR2","doi-asserted-by":"publisher","first-page":"5900","DOI":"10.1038\/s41467-020-19653-5","volume":"11","author":"RJF Loos","year":"2020","unstructured":"Loos RJF. 15 years of genome-wide association studies and no signs of slowing down. Nat Commun. 2020;11:5900.","journal-title":"Nat Commun"},{"key":"10971_CR3","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, McMahon A, Morales J, Mountjoy E, Sollis E, 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\u20131012.","journal-title":"Nucleic Acids Res"},{"key":"10971_CR4","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, Motyer A, Vukcevic D, Delaneau O, O\u2019Connell J, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203\u20139.","journal-title":"Nature"},{"key":"10971_CR5","doi-asserted-by":"publisher","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, Downey P, Elliott P, Green J, Landray M, 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":"10971_CR6","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, Perola M, Ng PC, Magi R, Milani L, 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":"10971_CR7","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1038\/s41586-022-05473-8","volume":"613","author":"MI Kurki","year":"2023","unstructured":"Kurki MI, Karjalainen J, Palta P, Sipila TP, Kristiansson K, Donner KM, Reeve MP, Laivuori H, Aavikko M, Kaunisto MA, et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature. 2023;613:508\u201318.","journal-title":"Nature"},{"key":"10971_CR8","doi-asserted-by":"publisher","first-page":"3761","DOI":"10.1038\/s41467-021-24051-6","volume":"12","author":"T Laisk","year":"2021","unstructured":"Laisk T, Lepamets M, Koel M, Abner E, Estonian Biobank Research T, Magi R. Genome-wide association study identifies five risk loci for pernicious anemia. Nat Commun. 2021;12:3761.","journal-title":"Nat Commun"},{"key":"10971_CR9","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1093\/humrep\/deab250","volume":"37","author":"JS Tyrmi","year":"2022","unstructured":"Tyrmi JS, Arffman RK, Pujol-Gualdo N, Kurra V, Morin-Papunen L, Sliz E, FinnGen Consortium EBRT, Piltonen TT, Laisk T, Kettunen J, Laivuori H. Leveraging northern European population history: novel low-frequency variants for polycystic ovary syndrome. Hum Reprod. 2022;37:352\u201365.","journal-title":"Hum Reprod"},{"key":"10971_CR10","doi-asserted-by":"publisher","first-page":"1173","DOI":"10.1038\/s41436-018-0311-2","volume":"21","author":"M Alver","year":"2019","unstructured":"Alver M, Palover M, Saar A, Lall K, Zekavat SM, Tonisson N, Leitsalu L, Reigo A, Nikopensius T, Ainla T, et al. Recall by genotype and cascade screening for familial hypercholesterolemia in a population-based biobank from Estonia. Genet Med. 2019;21:1173\u201380.","journal-title":"Genet Med"},{"key":"10971_CR11","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1008489","volume":"15","author":"EA King","year":"2019","unstructured":"King EA, Davis JW, Degner JF. Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval. PLoS Genet. 2019;15:e1008489.","journal-title":"PLoS Genet"},{"key":"10971_CR12","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1038\/ng.3314","volume":"47","author":"MR Nelson","year":"2015","unstructured":"Nelson MR, Tipney H, Painter JL, Shen J, Nicoletti P, Shen Y, Floratos A, Sham PC, Li MJ, Wang J, et al. The support of human genetic evidence for approved drug indications. Nat Genet. 2015;47:856\u201360.","journal-title":"Nat Genet"},{"key":"10971_CR13","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1038\/s41576-021-00387-z","volume":"22","author":"WR Reay","year":"2021","unstructured":"Reay WR, Cairns MJ. Advancing the use of genome-wide association studies for drug repurposing. Nat Rev Genet. 2021;22:658\u201371.","journal-title":"Nat Rev Genet"},{"key":"10971_CR14","doi-asserted-by":"publisher","first-page":"979","DOI":"10.1038\/ng.3359","volume":"47","author":"JZ Liu","year":"2015","unstructured":"Liu JZ, van Sommeren S, Huang H, Ng SC, Alberts R, Takahashi A, Ripke S, Lee JC, Jostins L, Shah T, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015;47:979\u201386.","journal-title":"Nat Genet"},{"key":"10971_CR15","doi-asserted-by":"publisher","first-page":"1461","DOI":"10.1126\/science.1135245","volume":"314","author":"RH Duerr","year":"2006","unstructured":"Duerr RH, Taylor KD, Brant SR, Rioux JD, Silverberg MS, Daly MJ, Steinhart AH, Abraham C, Regueiro M, Griffiths A, et al. A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science. 2006;314:1461\u20133.","journal-title":"Science"},{"key":"10971_CR16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0025038","volume":"6","author":"S Pidasheva","year":"2011","unstructured":"Pidasheva S, Trifari S, Phillips A, Hackney JA, Ma Y, Smith A, Sohn SJ, Spits H, Little RD, Behrens TW, et al. Functional studies on the IBD susceptibility gene IL23R implicate reduced receptor function in the protective genetic variant R381Q. PLoS ONE. 2011;6: e25038.","journal-title":"PLoS ONE"},{"key":"10971_CR17","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1111\/apt.17242","volume":"57","author":"L Peyrin-Biroulet","year":"2023","unstructured":"Peyrin-Biroulet L, Ghosh S, Lee SD, Lee WJ, Griffith J, Wallace K, Berg S, Liao X, Panes J, Loftus EV Jr, Louis E. Effect of risankizumab on health-related quality of life in patients with Crohn\u2019s disease: results from phase 3 MOTIVATE, ADVANCE and FORTIFY clinical trials. Aliment Pharmacol Ther. 2023;57:496\u2013508.","journal-title":"Aliment Pharmacol Ther"},{"key":"10971_CR18","doi-asserted-by":"publisher","first-page":"2031","DOI":"10.1016\/S0140-6736(22)00466-4","volume":"399","author":"M Ferrante","year":"2022","unstructured":"Ferrante M, Panaccione R, Baert F, Bossuyt P, Colombel JF, Danese S, Dubinsky M, Feagan BG, Hisamatsu T, Lim A, et al. Risankizumab as maintenance therapy for moderately to severely active Crohn\u2019s disease: results from the multicentre, randomised, double-blind, placebo-controlled, withdrawal phase 3 FORTIFY maintenance trial. Lancet. 2022;399:2031\u201346.","journal-title":"Lancet"},{"key":"10971_CR19","doi-asserted-by":"publisher","first-page":"1946","DOI":"10.1056\/NEJMoa1602773","volume":"375","author":"BG Feagan","year":"2016","unstructured":"Feagan BG, Sandborn WJ, Gasink C, Jacobstein D, Lang Y, Friedman JR, Blank MA, Johanns J, Gao LL, Miao Y, et al. Ustekinumab as induction and maintenance therapy for Crohn\u2019s Disease. N Engl J Med. 2016;375:1946\u201360.","journal-title":"N Engl J Med"},{"key":"10971_CR20","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.1038\/ng.2462","volume":"44","author":"S Eyre","year":"2012","unstructured":"Eyre S, Bowes J, Diogo D, Lee A, Barton A, Martin P, Zhernakova A, Stahl E, Viatte S, McAllister K, et al. High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis. Nat Genet. 2012;44:1336\u201340.","journal-title":"Nat Genet"},{"key":"10971_CR21","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1038\/nature09270","volume":"466","author":"TM Teslovich","year":"2010","unstructured":"Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707\u201313.","journal-title":"Nature"},{"key":"10971_CR22","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1111\/j.1600-065X.2011.01029.x","volume":"242","author":"C Ober","year":"2011","unstructured":"Ober C, Yao TC. The genetics of asthma and allergic disease: a 21st century perspective. Immunol Rev. 2011;242:10\u201330.","journal-title":"Immunol Rev"},{"key":"10971_CR23","doi-asserted-by":"publisher","first-page":"700","DOI":"10.1038\/s42003-021-02227-6","volume":"4","author":"K Valette","year":"2021","unstructured":"Valette K, Li Z, Bon-Baret V, Chignon A, Berube JC, Eslami A, Lamothe J, Gaudreault N, Joubert P, Obeidat M, et al. Prioritization of candidate causal genes for asthma in susceptibility loci derived from UK Biobank. Commun Biol. 2021;4:700.","journal-title":"Commun Biol"},{"key":"10971_CR24","doi-asserted-by":"publisher","first-page":"1190","DOI":"10.1126\/science.1222794","volume":"337","author":"MT Maurano","year":"2012","unstructured":"Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, Reynolds AP, Sandstrom R, Qu H, Brody J, et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337:1190\u20135.","journal-title":"Science"},{"key":"10971_CR25","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1056\/NEJMoa1502214","volume":"373","author":"M Claussnitzer","year":"2015","unstructured":"Claussnitzer M, Dankel SN, Kim KH, Quon G, Meuleman W, Haugen C, Glunk V, Sousa IS, Beaudry JL, Puviindran V, et al. FTO Obesity Variant Circuitry and Adipocyte Browning in humans. N Engl J Med. 2015;373:895\u2013907.","journal-title":"N Engl J Med"},{"key":"10971_CR26","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1038\/s41588-021-00945-5","volume":"53","author":"E Mountjoy","year":"2021","unstructured":"Mountjoy E, Schmidt EM, Carmona M, Schwartzentruber J, Peat G, Miranda A, Fumis L, Hayhurst J, Buniello A, Karim MA, et al. An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci. Nat Genet. 2021;53:1527\u201333.","journal-title":"Nat Genet"},{"key":"10971_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/ije\/dyg070","volume":"32","author":"GD Smith","year":"2003","unstructured":"Smith GD, Ebrahim S. Mendelian randomization\u2019: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32:1\u201322.","journal-title":"Int J Epidemiol"},{"key":"10971_CR28","doi-asserted-by":"publisher","first-page":"R89","DOI":"10.1093\/hmg\/ddu328","volume":"23","author":"G Davey Smith","year":"2014","unstructured":"Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23:R89\u201398.","journal-title":"Hum Mol Genet"},{"key":"10971_CR29","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1038\/s41467-019-13921-9","volume":"11","author":"TG Richardson","year":"2020","unstructured":"Richardson TG, Hemani G, Gaunt TR, Relton CL, Davey Smith G. A transcriptome-wide mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome. Nat Commun. 2020;11:185.","journal-title":"Nat Commun"},{"key":"10971_CR30","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1016\/j.ajhg.2016.10.003","volume":"99","author":"F Hormozdiari","year":"2016","unstructured":"Hormozdiari F, van de Bunt M, Segre AV, Li X, Joo JWJ, Bilow M, Sul JH, Sankararaman S, Pasaniuc B, Eskin E. Colocalization of GWAS and eQTL signals detects Target genes. Am J Hum Genet. 2016;99:1245\u201360.","journal-title":"Am J Hum Genet"},{"key":"10971_CR31","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1004383","volume":"10","author":"C Giambartolomei","year":"2014","unstructured":"Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, Plagnol V. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 2014;10: e1004383.","journal-title":"PLoS Genet"},{"key":"10971_CR32","doi-asserted-by":"crossref","unstructured":"Aguet F, Brown AA, Castel SE, Davis JR, He Y, Jo B, Mohammadi P, Park Y, Parsana P, Segr\u00e8 AV, et al. Genetic effects on gene expression across human tissues. Nature. 2017;550:204\u201313.","DOI":"10.1038\/nature24277"},{"key":"10971_CR33","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.ajhg.2020.01.003","volume":"106","author":"A Ndungu","year":"2020","unstructured":"Ndungu A, Payne A, Torres JM, van de Bunt M, McCarthy MI. A multi-tissue transcriptome analysis of human metabolites guides interpretability of associations based on Multi-SNP models for gene expression. Am J Hum Genet. 2020;106:188\u2013201.","journal-title":"Am J Hum Genet"},{"key":"10971_CR34","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1016\/j.ajhg.2017.03.002","volume":"100","author":"X Liu","year":"2017","unstructured":"Liu X, Finucane HK, Gusev A, Bhatia G, Gazal S, O\u2019Connor L, Bulik-Sullivan B, Wright FA, Sullivan PF, Neale BM, Price AL. Functional architectures of local and distal regulation of Gene expression in multiple human tissues. Am J Hum Genet. 2017;100:605\u201316.","journal-title":"Am J Hum Genet"},{"key":"10971_CR35","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1126\/science.1262110","volume":"348","author":"GT Consortium","year":"2015","unstructured":"Consortium GT. Human genomics. The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348:648\u201360.","journal-title":"Science"},{"key":"10971_CR36","doi-asserted-by":"crossref","unstructured":"Connally NJ, Nazeen S, Lee D, Shi H, Stamatoyannopoulos J, Chun S, Cotsapas C, Cassa CA, Sunyaev SR. The missing link between genetic association and regulatory function. Elife. 2022;11:e74970.","DOI":"10.7554\/eLife.74970"},{"key":"10971_CR37","doi-asserted-by":"crossref","unstructured":"Mostafavi H, Spence JP, Naqvi S, Pritchard JK: Limited overlap of eQTLs and GWAS hits due to systematic differences in discovery. bioRxiv 2022.","DOI":"10.1101\/2022.05.07.491045"},{"key":"10971_CR38","doi-asserted-by":"publisher","first-page":"3065","DOI":"10.1172\/JCI94378","volume":"127","author":"S Lessard","year":"2017","unstructured":"Lessard S, Gatof ES, Beaudoin M, Schupp PG, Sher F, Ali A, Prehar S, Kurita R, Nakamura Y, Baena E, et al. An erythroid-specific ATP2B4 enhancer mediates red blood cell hydration and malaria susceptibility. J Clin Invest. 2017;127:3065\u201374.","journal-title":"J Clin Invest"},{"key":"10971_CR39","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1038\/nature13138","volume":"507","author":"S Smemo","year":"2014","unstructured":"Smemo S, Tena JJ, Kim KH, Gamazon ER, Sakabe NJ, Gomez-Marin C, Aneas I, Credidio FL, Sobreira DR, Wasserman NF, et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature. 2014;507:371\u20135.","journal-title":"Nature"},{"key":"10971_CR40","doi-asserted-by":"publisher","first-page":"7","DOI":"10.7554\/eLife.34408","volume":"7","author":"G Hemani","year":"2018","unstructured":"Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018;7:7.","journal-title":"Elife"},{"key":"10971_CR41","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1038\/s41586-021-03446-x","volume":"593","author":"J Nasser","year":"2021","unstructured":"Nasser J, Bergman DT, Fulco CP, Guckelberger P, Doughty BR, Patwardhan TA, Jones TR, Nguyen TH, Ulirsch JC, Lekschas F, et al. Genome-wide enhancer maps link risk variants to disease genes. Nature. 2021;593:238\u201343.","journal-title":"Nature"},{"key":"10971_CR42","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1186\/s13059-016-0974-4","volume":"17","author":"W McLaren","year":"2016","unstructured":"McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F. The Ensembl variant effect predictor. Genome Biol. 2016;17:122.","journal-title":"Genome Biol"},{"key":"10971_CR43","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1038\/ng.3679","volume":"48","author":"PR Loh","year":"2016","unstructured":"Loh PR, Danecek P, Palamara PF, Fuchsberger C, Y AR HKF, Schoenherr S, Forer L, McCarthy S, Abecasis GR, et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat Genet. 2016;48:1443\u20138.","journal-title":"Nat Genet"},{"key":"10971_CR44","doi-asserted-by":"publisher","first-page":"1084","DOI":"10.1086\/521987","volume":"81","author":"SR Browning","year":"2007","unstructured":"Browning SR, Browning BL. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet. 2007;81:1084\u201397.","journal-title":"Am J Hum Genet"},{"key":"10971_CR45","doi-asserted-by":"crossref","unstructured":"Karczewski KJ, Gupta R, Kanai M, Lu W, Tsuo K, Wang Y, Walters RK, Turley P, Callier S, Baya N, et al. Pan-UK Biobank GWAS improves discovery, analysis of genetic architecture, and resolution into ancestry-enriched effects. medRxiv. 2024;03.13.2430386.","DOI":"10.1101\/2024.03.13.24303864"},{"key":"10971_CR46","unstructured":"Maintainer BP. liftOver: Changing genomic coordinate systems with rtracklayer::liftOver. R package version 1180 2021."},{"key":"10971_CR47","doi-asserted-by":"publisher","first-page":"W140","DOI":"10.1093\/nar\/gkae413","volume":"52","author":"JD Stephenson","year":"2024","unstructured":"Stephenson JD, Totoo P, Burke DF, Janes J, Beltrao P, Martin MJ. ProtVar: mapping and contextualizing human missense variation. Nucleic Acids Res. 2024;52:W140\u20137.","journal-title":"Nucleic Acids Res"},{"key":"10971_CR48","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1038\/s41586-021-04043-8","volume":"599","author":"J Frazer","year":"2021","unstructured":"Frazer J, Notin P, Dias M, Gomez A, Min JK, Brock K, Gal Y, Marks DS. Disease variant prediction with deep generative models of evolutionary data. Nature. 2021;599:91\u20135.","journal-title":"Nature"},{"key":"10971_CR49","doi-asserted-by":"publisher","first-page":"1512","DOI":"10.1038\/s41588-023-01465-0","volume":"55","author":"N Brandes","year":"2023","unstructured":"Brandes N, Goldman G, Wang CH, Ye CJ, Ntranos V. Genome-wide prediction of disease variant effects with a deep protein language model. Nat Genet. 2023;55:1512\u201322.","journal-title":"Nat Genet"},{"key":"10971_CR50","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1002\/humu.10212","volume":"21","author":"PD Stenson","year":"2003","unstructured":"Stenson PD, Ball EV, Mort M, Phillips AD, Shiel JA, Thomas NS, Abeysinghe S, Krawczak M, Cooper DN. Human gene mutation database (HGMD): 2003 update. Hum Mutat. 2003;21:577\u201381.","journal-title":"Hum Mutat"},{"key":"10971_CR51","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1038\/s41586-018-0175-2","volume":"558","author":"BB Sun","year":"2018","unstructured":"Sun BB, Maranville JC, Peters JE, Stacey D, Staley JR, Blackshaw J, Burgess S, Jiang T, Paige E, Surendran P, et al. Genomic atlas of the human plasma proteome. Nature. 2018;558:73\u20139.","journal-title":"Nature"},{"key":"10971_CR52","doi-asserted-by":"publisher","first-page":"1398","DOI":"10.1016\/j.cell.2016.10.026","volume":"167","author":"L Chen","year":"2016","unstructured":"Chen L, Ge B, Casale FP, Vasquez L, Kwan T, Garrido-Martin D, Watt S, Yan Y, Kundu K, Ecker S, et al. Genetic drivers of epigenetic and transcriptional variation in Human Immune cells. Cell. 2016;167:1398\u2013e14141324.","journal-title":"Cell"},{"key":"10971_CR53","doi-asserted-by":"publisher","first-page":"1300","DOI":"10.1038\/s41588-021-00913-z","volume":"53","author":"U Vosa","year":"2021","unstructured":"Vosa U, Claringbould A, Westra HJ, Bonder MJ, Deelen P, Zeng B, Kirsten H, Saha A, Kreuzhuber R, Yazar S, et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat Genet. 2021;53:1300\u201310.","journal-title":"Nat Genet"},{"key":"10971_CR54","doi-asserted-by":"publisher","first-page":"1290","DOI":"10.1038\/s41588-021-00924-w","volume":"53","author":"N Kerimov","year":"2021","unstructured":"Kerimov N, Hayhurst JD, Peikova K, Manning JR, Walter P, Kolberg L, Samovica M, Sakthivel MP, Kuzmin I, Trevanion SJ, et al. A compendium of uniformly processed human gene expression and splicing quantitative trait loci. Nat Genet. 2021;53:1290\u20139.","journal-title":"Nat Genet"},{"key":"10971_CR55","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1038\/ng.3162","volume":"47","author":"A Buil","year":"2015","unstructured":"Buil A, Brown AA, Lappalainen T, Vinuela A, Davies MN, Zheng HF, Richards JB, Glass D, Small KS, Durbin R, et al. Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins. Nat Genet. 2015;47:88\u201391.","journal-title":"Nat Genet"},{"key":"10971_CR56","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.1038\/s41593-018-0197-y","volume":"21","author":"AE Jaffe","year":"2018","unstructured":"Jaffe AE, Straub RE, Shin JH, Tao R, Gao Y, Collado-Torres L, Kam-Thong T, Xi HS, Quan J, Chen Q, et al. Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis. Nat Neurosci. 2018;21:1117\u201325.","journal-title":"Nat Neurosci"},{"key":"10971_CR57","doi-asserted-by":"publisher","first-page":"1701","DOI":"10.1016\/j.cell.2018.10.022","volume":"175","author":"BJ Schmiedel","year":"2018","unstructured":"Schmiedel BJ, Singh D, Madrigal A, Valdovino-Gonzalez AG, White BM, Zapardiel-Gonzalo J, Ha B, Altay G, Greenbaum JA, McVicker G, et al. Impact of genetic polymorphisms on human immune cell gene expression. Cell. 2018;175:1701\u2013e17151716.","journal-title":"Cell"},{"key":"10971_CR58","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1038\/nn.4632","volume":"20","author":"B Ng","year":"2017","unstructured":"Ng B, White CC, Klein HU, Sieberts SK, McCabe C, Patrick E, Xu J, Yu L, Gaiteri C, Bennett DA, et al. An xQTL map integrates the genetic architecture of the human brain\u2019s transcriptome and epigenome. Nat Neurosci. 2017;20:1418\u201326.","journal-title":"Nat Neurosci"},{"key":"10971_CR59","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.00523","volume":"2","author":"M Gutierrez-Arcelus","year":"2013","unstructured":"Gutierrez-Arcelus M, Lappalainen T, Montgomery SB, Buil A, Ongen H, Yurovsky A, Bryois J, Giger T, Romano L, Planchon A, et al. Passive and active DNA methylation and the interplay with genetic variation in gene regulation. Elife. 2013;2: e00523.","journal-title":"Elife"},{"key":"10971_CR60","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1005694","volume":"11","author":"M van de Bunt","year":"2015","unstructured":"van de Bunt M, Manning Fox JE, Dai X, Barrett A, Grey C, Li L, Bennett AJ, Johnson PR, Rajotte RV, Gaulton KJ, et al. Transcript expression data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for type 2 diabetes and glycemic traits to their downstream effectors. PLoS Genet. 2015;11: e1005694.","journal-title":"PLoS Genet"},{"key":"10971_CR61","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1038\/s41588-018-0046-7","volume":"50","author":"K Alasoo","year":"2018","unstructured":"Alasoo K, Rodrigues J, Mukhopadhyay S, Knights AJ, Mann AL, Kundu K, Consortium H, Hale C, Dougan G, Gaffney DJ. Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response. Nat Genet. 2018;50:424\u201331.","journal-title":"Nat Genet"},{"key":"10971_CR62","doi-asserted-by":"publisher","first-page":"10883","DOI":"10.1073\/pnas.1814263116","volume":"116","author":"DL Taylor","year":"2019","unstructured":"Taylor DL, Jackson AU, Narisu N, Hemani G, Erdos MR, Chines PS, Swift A, Idol J, Didion JP, Welch RP, et al. Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle. Proc Natl Acad Sci U S A. 2019;116:10883\u20138.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"10971_CR63","doi-asserted-by":"publisher","first-page":"e1005766","DOI":"10.1371\/journal.pcbi.1005766","volume":"13","author":"K Lepik","year":"2017","unstructured":"Lepik K, Annilo T, Kukuskina V, e QC, Kisand K, Kutalik Z, Peterson P, Peterson H. C-reactive protein upregulates the whole blood expression of CD59 - an integrative analysis. PLoS Comput Biol. 2017;13:e1005766.","journal-title":"PLoS Comput Biol"},{"key":"10971_CR64","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/j.cell.2016.09.024","volume":"167","author":"H Quach","year":"2016","unstructured":"Quach H, Rotival M, Pothlichet J, Loh YE, Dannemann M, Zidane N, Laval G, Patin E, Harmant C, Lopez M, et al. Genetic adaptation and neandertal admixture shaped the immune system of human populations. Cell. 2016;167:643\u2013e656617.","journal-title":"Cell"},{"key":"10971_CR65","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1016\/j.cell.2016.09.025","volume":"167","author":"Y Nedelec","year":"2016","unstructured":"Nedelec Y, Sanz J, Baharian G, Szpiech ZA, Pacis A, Dumaine A, Grenier JC, Freiman A, Sams AJ, Hebert S, et al. Genetic ancestry and Natural Selection Drive Population differences in Immune responses to pathogens. Cell. 2016;167:657\u2013e669621.","journal-title":"Cell"},{"key":"10971_CR66","doi-asserted-by":"publisher","first-page":"1086","DOI":"10.1016\/j.stemcr.2017.03.012","volume":"8","author":"AD Panopoulos","year":"2017","unstructured":"Panopoulos AD, D\u2019Antonio M, Benaglio P, Williams R, Hashem SI, Schuldt BM, DeBoever C, Arias AD, Garcia M, Nelson BC, et al. iPSCORE: a resource of 222 iPSC lines enabling functional characterization of genetic variation across a Variety of Cell types. Stem Cell Rep. 2017;8:1086\u2013100.","journal-title":"Stem Cell Rep"},{"key":"10971_CR67","doi-asserted-by":"publisher","first-page":"558","DOI":"10.1016\/j.stem.2017.03.017","volume":"20","author":"EE Pashos","year":"2017","unstructured":"Pashos EE, Park Y, Wang X, Raghavan A, Yang W, Abbey D, Peters DT, Arbelaez J, Hernandez M, Kuperwasser N, et al. Large, diverse population cohorts of hiPSCs and derived hepatocyte-like cells reveal functional genetic variation at blood lipid-Associated loci. Cell Stem Cell. 2017;20:558\u2013e570510.","journal-title":"Cell Stem Cell"},{"key":"10971_CR68","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1038\/nature22403","volume":"546","author":"H Kilpinen","year":"2017","unstructured":"Kilpinen H, Goncalves A, Leha A, Afzal V, Alasoo K, Ashford S, Bala S, Bensaddek D, Casale FP, Culley OJ, et al. Common genetic variation drives molecular heterogeneity in human iPSCs. Nature. 2017;546:370\u20135.","journal-title":"Nature"},{"key":"10971_CR69","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1038\/nature12531","volume":"501","author":"T Lappalainen","year":"2013","unstructured":"Lappalainen T, Sammeth M, Friedlander MR, t Hoen PA, Monlong J, Rivas MA, Gonzalez-Porta M, Kurbatova N, Griebel T, Ferreira PG, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature. 2013;501:506\u201311.","journal-title":"Nature"},{"key":"10971_CR70","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1038\/s41597-019-0183-6","volume":"6","author":"GE Hoffman","year":"2019","unstructured":"Hoffman GE, Bendl J, Voloudakis G, Montgomery KS, Sloofman L, Wang YC, Shah HR, Hauberg ME, Johnson JS, Girdhar K, et al. CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder. Sci Data. 2019;6:180.","journal-title":"Sci Data"},{"key":"10971_CR71","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1038\/s41467-020-14483-x","volume":"11","author":"S Guelfi","year":"2020","unstructured":"Guelfi S, D\u2019Sa K, Botia JA, Vandrovcova J, Reynolds RH, Zhang D, Trabzuni D, Collado-Torres L, Thomason A, Quijada Leyton P, et al. Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information. Nat Commun. 2020;11:1041.","journal-title":"Nat Commun"},{"key":"10971_CR72","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1038\/s41588-021-00875-2","volume":"53","author":"AMH Young","year":"2021","unstructured":"Young AMH, Kumasaka N, Calvert F, Hammond TR, Knights A, Panousis N, Park JS, Schwartzentruber J, Liu J, Kundu K, et al. A map of transcriptional heterogeneity and regulatory variation in human microglia. Nat Genet. 2021;53:861\u20138.","journal-title":"Nat Genet"},{"key":"10971_CR73","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1126\/science.aaz1776","volume":"369","author":"GT Consortium","year":"2020","unstructured":"Consortium GT. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science. 2020;369:1318\u201330.","journal-title":"Science"},{"key":"10971_CR74","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1186\/s12864-020-06966-4","volume":"21","author":"E Theusch","year":"2020","unstructured":"Theusch E, Chen YI, Rotter JI, Krauss RM, Medina MW. Genetic variants modulate gene expression statin response in human lymphoblastoid cell lines. BMC Genomics. 2020;21:555.","journal-title":"BMC Genomics"},{"key":"10971_CR75","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1007799","volume":"14","author":"S Peng","year":"2018","unstructured":"Peng S, Deyssenroth MA, Di Narzo AF, Cheng H, Zhang Z, Lambertini L, Ruusalepp A, Kovacic JC, Bjorkegren JLM, Marsit CJ, et al. Genetic regulation of the placental transcriptome underlies birth weight and risk of childhood obesity. PLoS Genet. 2018;14: e1007799.","journal-title":"PLoS Genet"},{"key":"10971_CR76","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.1038\/s41467-021-21593-7","volume":"12","author":"J Steinberg","year":"2021","unstructured":"Steinberg J, Southam L, Roumeliotis TI, Clark MJ, Jayasuriya RL, Swift D, Shah KM, Butterfield NC, Brooks RA, McCaskie AW, et al. A molecular quantitative trait locus map for osteoarthritis. Nat Commun. 2021;12:1309.","journal-title":"Nat Commun"},{"key":"10971_CR77","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1038\/s41588-017-0005-8","volume":"50","author":"J Schwartzentruber","year":"2018","unstructured":"Schwartzentruber J, Foskolou S, Kilpinen H, Rodrigues J, Alasoo K, Knights AJ, Patel M, Goncalves A, Ferreira R, Benn CL, et al. Molecular and functional variation in iPSC-derived sensory neurons. Nat Genet. 2018;50:54\u201361.","journal-title":"Nat Genet"},{"key":"10971_CR78","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/s13742-015-0047-8","volume":"4","author":"CC Chang","year":"2015","unstructured":"Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.","journal-title":"Gigascience"},{"key":"10971_CR79","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1038\/nature15393","volume":"526","author":"C Genomes Project","year":"2015","unstructured":"Genomes Project C, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR. A global reference for human genetic variation. Nature. 2015;526:68\u201374.","journal-title":"Nature"},{"key":"10971_CR80","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, Fumis L, Miranda A, Carvalho-Silva D, Buniello 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\u201320.","journal-title":"Nucleic Acids Res"},{"key":"10971_CR81","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1186\/s12859-021-04170-z","volume":"22","author":"EA King","year":"2021","unstructured":"King EA, Dunbar F, Davis JW, Degner JF. Estimating colocalization probability from limited summary statistics. BMC Bioinformatics. 2021;22:254.","journal-title":"BMC Bioinformatics"},{"key":"10971_CR82","first-page":"296","volume":"98","author":"D Lin","year":"1998","unstructured":"Lin D. An Information-Theoretic Definition of Similarity. In Proceedings of the Fifteenth International Conference on Machine Learning. Morgan Kaufmann Publishers Inc. 1998;98:296\u2013304.","journal-title":"Morgan Kaufmann Publishers Inc"},{"key":"10971_CR83","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1613\/jair.514","volume":"11","author":"P Resnik","year":"1999","unstructured":"Resnik P. Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. J Artificial Intellig Res. 1999;11:95\u2013130.","journal-title":"J Artificial Intellig Res"},{"key":"10971_CR84","doi-asserted-by":"publisher","first-page":"1104","DOI":"10.1093\/bioinformatics\/btw763","volume":"33","author":"D Greene","year":"2017","unstructured":"Greene D, Richardson S, Turro E. ontologyX: a suite of R packages for working with ontological data. Bioinformatics. 2017;33:1104\u20136.","journal-title":"Bioinformatics"},{"key":"10971_CR85","doi-asserted-by":"publisher","first-page":"3017","DOI":"10.1093\/bioinformatics\/btab186","volume":"37","author":"AP Boughton","year":"2021","unstructured":"Boughton AP, Welch RP, Flickinger M, VandeHaar P, Taliun D, Abecasis GR, Boehnke M. LocusZoom.js: interactive and embeddable visualization of genetic association study results. Bioinformatics. 2021;37:3017\u20138.","journal-title":"Bioinformatics"},{"key":"10971_CR86","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1111\/rssb.12388","volume":"82","author":"G Wang","year":"2020","unstructured":"Wang G, Sarkar A, Carbonetto P, Stephens M. A simple new approach to variable selection in regression, with application to genetic fine mapping. J R Stat Soc Ser B Stat Methodol. 2020;82:1273\u2013300.","journal-title":"J R Stat Soc Ser B Stat Methodol"},{"key":"10971_CR87","doi-asserted-by":"publisher","first-page":"710","DOI":"10.1038\/ejhg.2015.173","volume":"24","author":"G Nicolas","year":"2016","unstructured":"Nicolas G, Wallon D, Charbonnier C, Quenez O, Rousseau S, Richard AC, Rovelet-Lecrux A, Coutant S, Le Guennec K, Bacq D, et al. Screening of dementia genes by whole-exome sequencing in early-onset Alzheimer disease: input and lessons. Eur J Hum Genet. 2016;24:710\u20136.","journal-title":"Eur J Hum Genet"},{"key":"10971_CR88","doi-asserted-by":"publisher","first-page":"1582","DOI":"10.1086\/340731","volume":"70","author":"N Laurin","year":"2002","unstructured":"Laurin N, Brown JP, Morissette J, Raymond V. Recurrent mutation of the gene encoding sequestosome 1 (SQSTM1\/p62) in Paget disease of bone. Am J Hum Genet. 2002;70:1582\u20138.","journal-title":"Am J Hum Genet"},{"key":"10971_CR89","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1038\/ng0896-399","volume":"13","author":"JN Feder","year":"1996","unstructured":"Feder JN, Gnirke A, Thomas W, Tsuchihashi Z, Ruddy DA, Basava A, Dormishian F, Domingo R Jr, Ellis MC, Fullan A, et al. A novel MHC class I-like gene is mutated in patients with hereditary haemochromatosis. Nat Genet. 1996;13:399\u2013408.","journal-title":"Nat Genet"},{"key":"10971_CR90","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1038\/nature11283","volume":"488","author":"T Jonsson","year":"2012","unstructured":"Jonsson T, Atwal JK, Steinberg S, Snaedal J, Jonsson PV, Bjornsson S, Stefansson H, Sulem P, Gudbjartsson D, Maloney J, et al. A mutation in APP protects against Alzheimer\u2019s disease and age-related cognitive decline. Nature. 2012;488:96\u20139.","journal-title":"Nature"},{"key":"10971_CR91","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1038\/s41588-018-0314-6","volume":"51","author":"RP Kristjansson","year":"2019","unstructured":"Kristjansson RP, Benonisdottir S, Davidsson OB, Oddsson A, Tragante V, Sigurdsson JK, Stefansdottir L, Jonsson S, Jensson BO, Arthur JG, et al. A loss-of-function variant in ALOX15 protects against nasal polyps and chronic rhinosinusitis. Nat Genet. 2019;51:267\u201376.","journal-title":"Nat Genet"},{"key":"10971_CR92","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1038\/s41467-018-07867-7","volume":"10","author":"AP Morris","year":"2019","unstructured":"Morris AP, Le TH, Wu H, Akbarov A, van der Most PJ, Hemani G, Smith GD, Mahajan A, Gaulton KJ, Nadkarni GN, et al. Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific disease aetiologies. Nat Commun. 2019;10:29.","journal-title":"Nat Commun"},{"key":"10971_CR93","doi-asserted-by":"publisher","first-page":"1472","DOI":"10.1161\/ATVBAHA.115.305534","volume":"35","author":"M Beaudoin","year":"2015","unstructured":"Beaudoin M, Gupta RM, Won HH, Lo KS, Do R, Henderson CA, Lavoie-St-Amour C, Langlois S, Rivas D, Lehoux S, et al. Myocardial infarction-Associated SNP at 6p24 interferes with MEF2 binding and associates with PHACTR1 expression levels in human coronary arteries. Arterioscler Thromb Vasc Biol. 2015;35:1472\u20139.","journal-title":"Arterioscler Thromb Vasc Biol"},{"key":"10971_CR94","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1136\/annrheumdis-2020-218481","volume":"80","author":"E Lopez-Isac","year":"2021","unstructured":"Lopez-Isac E, Smith SL, Marion MC, Wood A, Sudman M, Yarwood A, Shi C, Gaddi VP, Martin P, Prahalad S, et al. Combined genetic analysis of juvenile idiopathic arthritis clinical subtypes identifies novel risk loci, target genes and key regulatory mechanisms. Ann Rheum Dis. 2021;80:321\u20138.","journal-title":"Ann Rheum Dis"},{"key":"10971_CR95","doi-asserted-by":"publisher","first-page":"4402","DOI":"10.1038\/s41467-020-18180-7","volume":"11","author":"J Yang","year":"2020","unstructured":"Yang J, McGovern A, Martin P, Duffus K, Ge X, Zarrineh P, Morris AP, Adamson A, Fraser P, Rattray M, Eyre S. Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis. Nat Commun. 2020;11:4402.","journal-title":"Nat Commun"},{"key":"10971_CR96","doi-asserted-by":"crossref","unstructured":"Zhao SS, Mackie SL, Larsson SC, Burgess S, Yuan S. Modifiable risk factors and inflammation-related proteins in polymyalgia rheumatica: genome-wide meta-analysis and Mendelian randomisation. Rheumatology (Oxford) 2024.","DOI":"10.1101\/2024.04.21.24306135"},{"issue":"10","key":"10971_CR97","doi-asserted-by":"publisher","first-page":"1480","DOI":"10.1136\/annrheumdis-2022-222578","volume":"81","author":"SS Zhao","year":"2022","unstructured":"Zhao SS, Gill D. Genetically proxied IL-6 receptor inhibition and risk of polymyalgia rheumatica. Ann Rheum Dis. 2022;81(10):1480\u20132.","journal-title":"Ann Rheum Dis"},{"key":"10971_CR98","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1136\/annrheumdis-2022-eular.5004a","volume":"81","author":"B Dasgupta","year":"2022","unstructured":"Dasgupta B, Unizony S, Warrington KJ, Sloane Lazar J, Giannelou A, Nivens C, Akinlade B, Wong W, Lin Y, Buttgereit F, et al. LB0006\u2005sarilumab in patients with relapsing polymyalgia rheumatica: a phase 3, multicenter, randomized, double blind, placebo controlled trial (SAPHYR). Ann Rheum Dis. 2022;81:210\u20131.","journal-title":"Ann Rheum Dis"},{"key":"10971_CR99","doi-asserted-by":"publisher","first-page":"100210","DOI":"10.1016\/j.xgen.2022.100210","volume":"2","author":"M Kanai","year":"2022","unstructured":"Kanai M, Elzur R, Zhou W, Daly MJ, Finucane HK, Global Biobank Meta-analysis I. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution. Cell Genom. 2022;2:100210.","journal-title":"Cell Genom"},{"key":"10971_CR100","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1016\/j.ajhg.2017.04.005","volume":"100","author":"F Hormozdiari","year":"2017","unstructured":"Hormozdiari F, Zhu A, Kichaev G, Ju CJ, Segre AV, Joo JWJ, Won H, Sankararaman S, Pasaniuc B, Shifman S, Eskin E. Widespread allelic heterogeneity in Complex traits. Am J Hum Genet. 2017;100:789\u2013802.","journal-title":"Am J Hum Genet"},{"key":"10971_CR101","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1009455","volume":"17","author":"A Zhu","year":"2021","unstructured":"Zhu A, Matoba N, Wilson EP, Tapia AL, Li Y, Ibrahim JG, Stein JL, Love MI. MRLocus: identifying causal genes mediating a trait through bayesian estimation of allelic heterogeneity. PLoS Genet. 2021;17: e1009455.","journal-title":"PLoS Genet"},{"key":"10971_CR102","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1038\/ng.3538","volume":"48","author":"Z Zhu","year":"2016","unstructured":"Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, Montgomery GW, Goddard ME, Wray NR, Visscher PM, Yang J. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48:481\u20137.","journal-title":"Nat Genet"},{"key":"10971_CR103","doi-asserted-by":"crossref","unstructured":"Yin X, Bose D, Kwon A, Hanks SC, Jackson AU, Stringham HM, Welch R, Oravilahti A, Fernandes Silva L, FinnGen, et al: Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk. Am J Hum Genet 2022, 109:1727\u20131741.","DOI":"10.1016\/j.ajhg.2022.08.007"}],"container-title":["BMC Genomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12864-024-10971-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12864-024-10971-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12864-024-10971-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T03:18:20Z","timestamp":1732072700000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcgenomics.biomedcentral.com\/articles\/10.1186\/s12864-024-10971-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,19]]},"references-count":103,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["10971"],"URL":"https:\/\/doi.org\/10.1186\/s12864-024-10971-2","relation":{},"ISSN":["1471-2164"],"issn-type":[{"value":"1471-2164","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,19]]},"assertion":[{"value":"15 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 October 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Patients and control subjects in FinnGen provided informed consent for biobank research, based on the Finnish Biobank Act. Alternatively, separate research cohorts, collected prior the Finnish Biobank Act came into effect (in September 2013) and start of FinnGen (August 2017), were collected based on study-specific consents and later transferred to the Finnish biobanks after approval by Fimea, the National Supervisory Authority for Welfare and Health. Recruitment protocols followed the biobank protocols approved by Fimea. The Coordinating Ethics Committee of the Hospital District of Helsinki and Uusimaa (HUS) approved the FinnGen study protocol Nr HUS\/990\/2017.The FinnGen study is approved by Finnish Institute for Health and Welfare (permit numbers: THL\/2031\/6.02.00\/2017, THL\/1101\/5.05.00\/2017, THL\/341\/6.02.00\/2018, THL\/2222\/6.02.00\/2018, THL\/283\/6.02.00\/2019, THL\/1721\/5.05.00\/2019, THL\/1524\/5.05.00\/2020, and THL\/2364\/14.02\/2020), Digital and population data service agency (permit numbers: VRK43431\/2017-3, VRK\/6909\/2018-3, VRK\/4415\/2019-3), the Social Insurance Institution (permit numbers: KELA 58\/522\/2017, KELA 131\/522\/2018, KELA 70\/522\/2019, KELA 98\/522\/2019, KELA 138\/522\/2019, KELA 2\/522\/2020, KELA 16\/522\/2020 and Statistics Finland (permit numbers: TK-53-1041-17 and TK-53-90-20).The Biobank Access Decisions for FinnGen samples and data utilized in FinnGen Data Freeze 6 include: THL Biobank BB2017_55, BB2017_111, BB2018_19, BB_2018_34, BB_2018_67, BB2018_71, BB2019_7, BB2019_8, BB2019_26, BB2020_1, Finnish Red Cross Blood Service Biobank 7.12.2017, Helsinki Biobank HUS\/359\/2017, Auria Biobank AB17-5154, Biobank Borealis of Northern Finland_2017_1013, Biobank of Eastern Finland 1186\/2018, Finnish Clinical Biobank Tampere MH0004, Central Finland Biobank 1-2017, and Terveystalo Biobank STB 2018001.UK Biobank has received ethical approval from the NHS National Research Ethics Service North West (approval numbers 11\/NW\/0382 and 16\/NW\/0274). All participants provided written informed consent. Estonian Biobank GWAS and consecutive meta-analyses were carried out under ethical approval permit number 1.1-12\/1020 from the Estonian Committee on Bioethics and Human Research (Estonian Ministry of Social Affairs).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"SL, MC, MB, CC, EdR, KK, JS, SK are employees of Sanofi US Services and hold shares and\/or stock options in the company. DKR is currently an employee of Takeda and was an employee of Sanofi US Services at the time of study. All authors declare no other competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1111"}}