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Linking protein to phenotype with Mendelian Randomization detects 38 proteins with causal roles in human diseases and traits

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Bretherick, Andrew D., Canela-Xandri, Oriol, Joshi, Peter K., Clark, David W., Rawlik, Konrad, Boutin, Thibaud S., Zeng, Yanni, Amador, Carmen +11 more·2020·PLOS Genetics
DOI 10.1371/journal.pgen.1008785PMC PMC7337286

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Abstract

To efficiently transform genetic associations into drug targets requires evidence that a particular gene, and its encoded protein, contribute causally to a disease. To achieve this, we employ a three-step proteome-by-phenome Mendelian Randomization (MR) approach. In step one, 154 protein quantitative trait loci (pQTLs) were identified and independently replicated. From these pQTLs, 64 replicated locally-acting variants were used as instrumental variables for proteome-by-phenome MR across 846 traits (step two). When its assumptions are met, proteome-by-phenome MR, is equivalent to simultaneously running many randomized controlled trials. Step 2 yielded 38 proteins that significantly predicted variation in traits and diseases in 509 instances. Step 3 revealed that amongst the 271 instances from GeneAtlas (UK Biobank), 77 showed little evidence of pleiotropy (HEIDI), and 92 evidence of colocalization (eCAVIAR). Results were wide ranging: including, for example, new evidence for a causal role of tyrosine-protein phosphatase non-receptor type substrate 1 (SHPS1; SIRPA) in schizophrenia, and a new finding that intestinal fatty acid binding protein (FABP2) abundance contributes to the pathogenesis of cardiovascular disease. We also demonstrated confirmatory evidence for the causal role of four further proteins (FGF5, IL6R, LPL, LTA) in cardiovascular disease risk.

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  • IL6R was selected because it has been widely reported by previous pQTL studies as an example of the successful linking of molecular traits and diseases to discover drug targets.

    “IL6R was selected because it has been widely reported by previous pQTL studies as an example of the successful linking of molecular traits and diseases to discover drug targets50,59.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [59]

    The Results section, “One-to-Many: Linking IL6R levels to atopy, rheumatoid arthritis, and coronary artery disease” (page not provided), links plasma IL6R abundance to several diseases and notes that an IL6R-targeting drug is in clinical use. It cites prior MR and genetic evidence, but does not establish that IL6R was widely reported by previous pQTL studies as an example of drug-target discovery. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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  1. [1]Munos B. Lessons from 60 years of pharmaceutical innovation. Nat Rev Drug Discov. 2009; 8: 959– 968. 10.1038/nrd2961 19949401 · DOI
  2. [3]Baillie JK. Translational genomics. Targeting the host immune response to fight infection. Science. 2014; 344: 807– 808. 10.1126/science.1255074 24855243 · DOI
  3. [5]Finan C, Gaulton A, Kruger FA, Lumbers RT, Shah T, Engmann J, et al The druggable genome and support for target identification and validation in drug development. Sci Transl Med. 2017; 9: eaag1166 10.1126/scitranslmed.aag1166 28356508 PMC6321762 · DOI
  4. [6]Fang H, ULTRA-DD Consortium, De Wolf H, Knezevic B, Burnham KL, Osgood J, et al A genetics-led approach defines the drug target landscape of 30 immune-related traits. Nat Genet. 2019; 51: 1082– 1091. 10.1038/s41588-019-0456-1 31253980 PMC7124888 · DOI
  5. [8]MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, et al The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 2017; 45: D896– D901. 10.1093/nar/gkw1133 27899670 PMC5210590 · DOI · Paper page
  6. [9]Smith GD, Ebrahim S. “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003; 32: 1– 22. 10.1093/ije/dyg070 12689998 · DOI · Paper page
  7. [10]Burgess S, Scott RA, Timpson NJ, Smith GD, Thompson SG, EPIC-InterAct Consortium. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol. 2015; 30: 543– 552. 10.1007/s10654-015-0011-z 25773750 PMC4516908 · DOI · Paper page
  8. [11]Mirauta BA, Seaton DD, Bensaddek D, Brenes A, Bonder MJ, Kilpinen H, et al Population-scale proteome variation in human induced pluripotent stem cells. bioRxiv. 2018 [cited 13 Nov 2018]. 10.1101/439216 PMC7447446 32773033 · DOI · Paper page
  9. [12]Folkersen L, Fauman E, Sabater-Lleal M, Strawbridge RJ, Frånberg M, Sennblad B, et al Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease. PLoS Genet. 2017; 13: e1006706 10.1371/journal.pgen.1006706 28369058 PMC5393901 · DOI · Paper page
  10. [13]Suhre K, Arnold M, Bhagwat AM, Cotton RJ, Engelke R, Raffler J, et al Connecting genetic risk to disease end points through the human blood plasma proteome. Nat Commun. 2017; 8: 14357 10.1038/ncomms14357 28240269 PMC5333359 · DOI · Paper page
  11. [14]Sun BB, Maranville JC, Peters JE, Stacey D, Staley JR, Blackshaw J, et al Genomic atlas of the human plasma proteome. Nature. 2018; 558: 73– 79. 10.1038/s41586-018-0175-2 29875488 PMC6697541 · DOI · Paper page
  12. [15]Yao C, Chen G, Song C, Keefe J, Mendelson M, Huan T, et al Genome-wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease. Nat Commun. 2018; 9: 3268 10.1038/s41467-018-05512-x 30111768 PMC6093935 · DOI · Paper page
  13. [17]Chong M, Sjaarda J, Pigeyre M, Mohammadi-Shemirani P, Lali R, Shoamanesh A, et al Novel Drug Targets for Ischemic Stroke Identified Through Mendelian Randomization Analysis of the Blood Proteome. Circulation. 2019; 140: 819– 830. 10.1161/CIRCULATIONAHA.119.040180 31208196 · DOI
  14. [18]Mosley JD, Benson MD, Smith JG, Melander O, Ngo D, Shaffer CM, et al Probing the Virtual Proteome to Identify Novel Disease Biomarkers. Circulation. 2018; 138: 2469– 2481. 10.1161/CIRCULATIONAHA.118.036063 30571344 PMC8833190 · DOI
  15. [19]GTEx Consortium. Genetic effects on gene expression across human tissues. Nature. 2017; 550: 204– 213. 10.1038/nature24277 29022597 PMC5776756 · DOI · Paper page
  16. [20]Canela-Xandri O, Rawlik K, Tenesa A. An atlas of genetic associations in UK Biobank. bioRxiv. 2017 [cited 25 Aug 2017]. 10.1101/176834 PMC6707814 30349118 · DOI
  17. [21]Staley JR, Blackshaw J, Kamat MA, Ellis S, Surendran P, Sun BB, et al PhenoScanner: a database of human genotype–phenotype associations. Bioinformatics. 2016; 32: 3207– 3209. 10.1093/bioinformatics/btw373 27318201 PMC5048068 · DOI · Paper page
  18. [22]Kamat MA, Blackshaw JA, Young R, Surendran P, Burgess S, Danesh J, et al PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019; 35: 4851– 4853. 10.1093/bioinformatics/btz469 31233103 PMC6853652 · DOI
  19. [23]Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, et al Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016; 48: 481– 487. 10.1038/ng.3538 27019110 · DOI · Paper page
  20. [25]Scott RA, Scott LJ, Mägi R, Marullo L, Gaulton KJ, Kaakinen M, et al An expanded genome-wide association study of type 2 diabetes in Europeans. Diabetes. 2017; 66: 2888– 2902. 10.2337/db16-1253 28566273 PMC5652602 · DOI
  21. [26]Nelson CP, Goel A, Butterworth AS, Kanoni S, Webb TR, Marouli E, et al Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nat Genet. 2017; 49: 1385– 1391. 10.1038/ng.3913 28714975 · DOI
  22. [27]Liu JZ, van Sommeren S, Huang H, Ng SC, Alberts R, Takahashi A, et al Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015; 47: 979– 986. 10.1038/ng.3359 26192919 PMC4881818 · DOI · Paper page
  23. [28]Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014; 511: 421– 427. 10.1038/nature13595 25056061 PMC4112379 · DOI · Paper page
  24. [29]Bronson PG, Chang D, Bhangale T, Seldin MF, Ortmann W, Ferreira RC, et al Common variants at PVT1, ATG13-AMBRA1, AHI1 and CLEC16A are associated with selective IgA deficiency. Nat Genet. 2016; 48: 1425– 1429. 10.1038/ng.3675 27723758 PMC5086090 · DOI
  25. [30]Okada Y, Wu D, Trynka G, Raj T, Terao C, Ikari K, et al Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature. 2014; 506: 376– 381. 10.1038/nature12873 24390342 PMC3944098 · DOI · Paper page
  26. [31]van Rheenen W, Shatunov A, Dekker AM, McLaughlin RL, Diekstra FP, Pulit SL, et al Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis. Nat Genet. 2016; 48: 1043– 1048. 10.1038/ng.3622 27455348 PMC5556360 · DOI
  27. [33]Sniekers S, Stringer S, Watanabe K, Jansen PR, Coleman JRI, Krapohl E, et al Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat Genet. 2017; 49: 1107– 1112. 10.1038/ng.3869 28530673 PMC5665562 · DOI · Paper page
  28. [34]Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, et al Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016; 533: 539– 542. 10.1038/nature17671 27225129 PMC4883595 · DOI · Paper page
  29. [35]Hou L, Bergen SE, Akula N, Song J, Hultman CM, Landén M, et al Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder. Hum Mol Genet. 2016; 25: 3383– 3394. 10.1093/hmg/ddw181 27329760 PMC5179929 · DOI
  30. [36]Beaumont RN, Warrington NM, Cavadino A, Tyrrell J, Nodzenski M, Horikoshi M, et al Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics. Hum Mol Genet. 2018; 27: 742– 756. 10.1093/hmg/ddx429 29309628 PMC5886200 · DOI
  31. [37]Phelan CM, Kuchenbaecker KB, Tyrer JP, Kar SP, Lawrenson K, Winham SJ, et al Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer. Nat Genet. 2017; 49: 680– 691. 10.1038/ng.3826 28346442 PMC5612337 · DOI
  32. [38]van der Harst P, Verweij N. Identification of 64 Novel Genetic Loci Provides an Expanded View on the Genetic Architecture of Coronary Artery Disease. Circ Res. 2018; 122: 433– 443. 10.1161/CIRCRESAHA.117.312086 29212778 PMC5805277 · DOI · Paper page
  33. [39]van den Berg SM, de Moor MHM, Verweij KJH, Krueger RF, Luciano M, Vasquez AA, et al Meta-analysis of genome-wide association studies for extraversion: findings from the Genetics of Personality Consortium. Behav Genet. 2016; 46: 170– 182. 10.1007/s10519-015-9735-5 26362575 PMC4751159 · DOI
  34. [41]The EArly Genetics and Lifecourse Epidemiology (EAGLE) Eczema Consortium. Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis. Nat Genet. 2015; 47: 1449– 1456. 10.1038/ng.3424 26482879 PMC4753676 · DOI
  35. [43]Astle WJ, Elding H, Jiang T, Allen D, Ruklisa D, Mann AL, et al The allelic landscape of human blood cell trait variation and links to common complex disease. Cell. 2016; 167: 1415– 1429.e19. 10.1016/j.cell.2016.10.042 27863252 PMC5300907 · DOI · Paper page
  36. [45]Gordon ED, Palandra J, Wesolowska-Andersen A, Ringel L, Rios CL, Lachowicz-Scroggins ME, et al IL1RL1 asthma risk variants regulate airway type 2 inflammation. JCI Insight. 2016; 1: e87871 10.1172/jci.insight.87871 27699235 PMC5033813 · DOI
  37. [46]Gudbjartsson DF, Bjornsdottir US, Halapi E, Helgadottir A, Sulem P, Jonsdottir GM, et al Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction. Nat Genet. 2009; 41: 342– 347. 10.1038/ng.323 19198610 · DOI
  38. [47]Busse WW, Israel E, Nelson HS, Baker JW, Charous BL, Young DY, et al Daclizumab improves asthma control in patients with moderate to severe persistent asthma: a randomized, controlled trial. Am J Respir Crit Care Med. 2008; 178: 1002– 1008. 10.1164/rccm.200708-1200OC 18787222 · DOI
  39. [48]Massoud AH, Charbonnier L-M, Lopez D, Pellegrini M, Phipatanakul W, Chatila TA. An asthma-associated IL4R variant exacerbates airway inflammation by promoting conversion of regulatory T cells to TH17-like cells. Nat Med. 2016; 22: 1013– 1022. 10.1038/nm.4147 27479084 PMC5014738 · DOI
  40. [49]Navarini AA, French LE, Hofbauer GFL. Interrupting IL-6–receptor signaling improves atopic dermatitis but associates with bacterial superinfection. J Allergy Clin Immunol. 2011; 128: 1128– 1130. 10.1016/j.jaci.2011.09.009 21962991 · DOI
  41. [50]Ullah MA, Sukkar M, Ferreira M, Phipps S. 53: IL-6R blockade: A new personalised treatment for asthma? Cytokine. 2014; 70: 40 10.1016/j.cyto.2014.07.060 · DOI
  42. [51]Esparza-Gordillo J, Schaarschmidt H, Liang L, Cookson W, Bauerfeind A, Lee-Kirsch M-A, et al A functional IL-6 receptor (IL6R) variant is a risk factor for persistent atopic dermatitis. J Allergy Clin Immunol. 2013; 132: 371– 377. 10.1016/j.jaci.2013.01.057 23582566 · DOI · Paper page
  43. [52]Ferreira MAR, Matheson MC, Duffy DL, Marks GB, Hui J, Le Souëf P, et al Identification of IL6R and chromosome 11q13.5 as risk loci for asthma. Lancet. 2011; 378: 1006– 1014. 10.1016/S0140-6736(11)60874-X 21907864 PMC3517659 · DOI · Paper page
  44. [53]Scott LJ. Tocilizumab: a review in rheumatoid arthritis. Drugs. 2017; 77: 1865– 1879. 10.1007/s40265-017-0829-7 29094311 PMC5736769 · DOI · Paper page
  45. [56]Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010; 26: 2336– 2337. 10.1093/bioinformatics/btq419 20634204 PMC2935401 · DOI · Paper page
  46. [57]Thul PJ, Åkesson L, Wiking M, Mahdessian D, Geladaki A, Blal HA, et al A subcellular map of the human proteome. Science. 2017; 356: eaal3321 10.1126/science.aal3321 28495876 · DOI · Paper page
  47. [58]Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al Tissue-based map of the human proteome. Science. 2015; 347: 1260419 10.1126/science.1260419 25613900 · DOI · Paper page
  48. [60]Ohnishi H, Kaneko Y, Okazawa H, Miyashita M, Sato R, Hayashi A, et al Differential localization of Src homology 2 domain-dontaining protein tyrosine phosphatase substrate-1 and CD47 and Its molecular mechanisms in cultured hippocampal neurons. J Neurosci. 2005; 25: 2702– 2711. 10.1523/JNEUROSCI.5173-04.2005 15758180 PMC6725182 · DOI
  49. [61]Toth AB, Terauchi A, Zhang LY, Johnson-Venkatesh EM, Larsen DJ, Sutton MA, et al Synapse maturation by activity-dependent ectodomain shedding of SIRPα. Nat Neurosci. 2013; 16: 1417– 1425. 10.1038/nn.3516 24036914 PMC3820962 · DOI
  50. [62]Ma L, Kulesskaya N, Võikar V, Tian L. Differential expression of brain immune genes and schizophrenia-related behavior in C57BL/6N and DBA/2J female mice. Psychiatry Res. 2015; 226: 211– 216. 10.1016/j.psychres.2015.01.001 25661533 · DOI
  51. [63]Koshimizu H, Takao K, Matozaki T, Ohnishi H, Miyakawa T. Comprehensive behavioral analysis of cluster of differentiation 47 knockout mice. PLoS ONE. 2014; 9: e89584 10.1371/journal.pone.0089584 24586890 PMC3933641 · DOI
  52. [64]Ohnishi H, Murata T, Kusakari S, Hayashi Y, Takao K, Maruyama T, et al Stress-evoked tyrosine phosphorylation of signal regulatory protein α regulates behavioral immobility in the forced swim test. J Neurosci. 2010; 30: 10472– 10483. 10.1523/JNEUROSCI.0257-10.2010 20685990 PMC6634652 · DOI
  53. [65]Chang HP, Lindberg FP, Wang HL, Huang AM, Lee EHY. Impaired memory retention and decreased long-term potentiation in integrin-associated protein-deficient mice. Learn Mem. 1999; 6: 448– 457. 10.1101/lm.6.5.448 10541465 PMC311315 · DOI
  54. [66]Huang AM, Wang HL, Tang YP, Lee EHY. Expression of integrin-associated protein gene associated with memory formation in rats. J Neurosci. 1998; 18: 4305– 4313. 10.1523/JNEUROSCI.18-11-04305.1998 9592107 PMC6792811 · DOI
  55. [67]Brown GC, Neher JJ. Microglial phagocytosis of live neurons. Nat Rev Neurosci. 2014; 15: 209– 216. 10.1038/nrn3710 24646669 · DOI · Paper page
  56. [68]Martins-de-Souza D, Gattaz WF, Schmitt A, Rewerts C, Maccarrone G, Dias-Neto E, et al Prefrontal cortex shotgun proteome analysis reveals altered calcium homeostasis and immune system imbalance in schizophrenia. Eur Arch Psychiatry Clin Neurosci. 2009; 259: 151– 163. 10.1007/s00406-008-0847-2 19165527 · DOI
  57. [69]Klarin D, Zhu QM, Emdin CA, Chaffin M, Horner S, McMillan BJ, et al Genetic analysis in UK Biobank links insulin resistance and transendothelial migration pathways to coronary artery disease. Nat Genet. 2017; 49: 1392– 1397. 10.1038/ng.3914 28714974 PMC5577383 · DOI
  58. [70]Ozaki K, Ohnishi Y, Iida A, Sekine A, Yamada R, Tsunoda T, et al Functional SNPs in the lymphotoxin-alpha gene that are associated with susceptibility to myocardial infarction. Nat Genet. 2002; 32: 650– 654. 10.1038/ng1047 12426569 · DOI
  59. [71]Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A, Huddleston J, et al An integrated map of structural variation in 2,504 human genomes. Nature. 2015; 526: 75– 81. 10.1038/nature15394 26432246 PMC4617611 · DOI · Paper page
  60. [72]The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015; 526: 68– 74. 10.1038/nature15393 26432245 PMC4750478 · DOI · Paper page
  61. [74]Wenzel S, Castro M, Corren J, Maspero J, Wang L, Zhang B, et al Dupilumab efficacy and safety in adults with uncontrolled persistent asthma despite use of medium-to-high-dose inhaled corticosteroids plus a long-acting β2 agonist: a randomised double-blind placebo-controlled pivotal phase 2b dose-ranging trial. Lancet. 2016; 388: 31– 44. 10.1016/S0140-6736(16)30307-5 27130691 · DOI
  62. [75]Wenzel S, Ford L, Pearlman D, Spector S, Sher L, Skobieranda F, et al Dupilumab in persistent asthma with elevated eosinophil levels. N Engl J Med. 2013; 368: 2455– 2466. 10.1056/NEJMoa1304048 23688323 · DOI
  63. [76]McQuillan R, Leutenegger A-L, Abdel-Rahman R, Franklin CS, Pericic M, Barac-Lauc L, et al Runs of homozygosity in European populations. Am J Hum Genet. 2008; 83: 359– 372. 10.1016/j.ajhg.2008.08.007 18760389 PMC2556426 · DOI
  64. [77]Campbell H, Carothers AD, Rudan I, Hayward C, Biloglav Z, Barac L, et al Effects of genome-wide heterozygosity on a range of biomedically relevant human quantitative traits. Hum Mol Genet. 2007; 16: 233– 241. 10.1093/hmg/ddl473 17220173 · DOI
  65. [78]Rudan I, Marusić A, Janković S, Rotim K, Boban M, Lauc G, et al “10001 Dalmatians:” Croatia launches its national biobank. Croat Med J. 2009; 50: 4– 6. 10.3325/cmj.2009.50.4 19260138 PMC2657560 · DOI
  66. [80]Chang CC, Chow CC, Tellier LCAM, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience. 2015; 4: s13742-015-0047–8. 10.1186/s13742-015-0047-8 25722852 PMC4342193 · DOI · Paper page
  67. [82]O’Connell J, Gurdasani D, Delaneau O, Pirastu N, Ulivi S, Cocca M, et al A general approach for haplotype phasing across the full spectrum of relatedness. PLoS Genet. 2014; 10: e1004234 10.1371/journal.pgen.1004234 24743097 PMC3990520 · DOI · Paper page
  68. [83]The Haplotype Reference Consortium. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016; 48: 1279– 1283. 10.1038/ng.3643 27548312 PMC5388176 · DOI · Paper page
  69. [84]Assarsson E, Lundberg M, Holmquist G, Björkesten J, Thorsen SB, Ekman D, et al Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PloS ONE. 2014; 9: e95192 10.1371/journal.pone.0095192 24755770 PMC3995906 · DOI · Paper page
  70. [85]Haller T, Kals M, Esko T, Mägi R, Fischer K. RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations. Brief Bioinform. 2015; 16: 39– 44. 10.1093/bib/bbt066 24008273 PMC4293375 · DOI
  71. [86]Zerbino DR, Achuthan P, Akanni W, Amode MR, Barrell D, Bhai J, et al Ensembl 2018. Nucleic Acids Res. 2018; 46: D754– D761. 10.1093/nar/gkx1098 29155950 PMC5753206 · DOI · Paper page
  72. [87]Lynch M, Walsh B. Genetics and Analysis of Quantitative Traits. 1998 edition Sunderland, Mass: Sinauer; 1998.
  73. [88]Canela-Xandri O, Rawlik K, Tenesa A. An atlas of genetic associations in UK Biobank. Nat Genet. 2018; 50: 1593– 1599. 10.1038/s41588-018-0248-z 30349118 PMC6707814 · DOI
  74. [89]Davies M, Nowotka M, Papadatos G, Dedman N, Gaulton A, Atkinson F, et al ChEMBL web services: streamlining access to drug discovery data and utilities. Nucleic Acids Res. 2015; 43: W612– W620. 10.1093/nar/gkv352 25883136 PMC4489243 · DOI

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Authors
Bretherick, A. D., Canela-Xandri, O., Joshi, P. K., Clark, D. W., Rawlik, K., Boutin, T. S., Zeng, Y., Amador, C., Navarro, P., Rudan, I., Wright, A. F., Campbell, H., Vitart, V., Hayward, C., Wilson, J. F., Tenesa, A., Ponting, C. P., Baillie, J. K., & Haley, C.
Affiliations
  • Western General Hospital (GB)
  • University of Edinburgh (GB)
  • Roslin Institute (GB)
  • Sun Yat-sen University (CN)
Corresponding author
  • Bretherick, Andrew D.
  • Haley, Chris
ORCID
Venue
PLOS Genetics
Publisher
Public Library of Science (PLoS)
Published
2020-07-06
Volume
16
Issue
7
Pages
e1008785
ISSN
  • 1553-7390 (ISSN-L)
  • 1553-7404
DOI
10.1371/journal.pgen.1008785
PMC
PMC7337286
OpenAlex
W3038762676
Cited by
42
References
14
Citations by year
2026: 4 · 2025: 9 · 2024: 6 · 2023: 5 · 2022: 7 · 2021: 7 · 2020: 3 · 2019: 1
FWCI
3.18
Type
journal article
Language
en
Open access
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Locations
  • PLoS Genetics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
Funders
  • Intensive Care Foundation
  • Wellcome Trust (103258/Z/13/Z, 103258, 204979/Z/16/Z, 204979)
  • Scottish Government
  • European Commission (018947, CZB/4/276, LSHG-CT-2006-018947)
  • AXA Research Fund
  • Versus Arthritis
  • Medical Research Council (MR/R025851/1, LSHG-CT-2006-018947, MC_PC_U127592696, MR/P015514/1, 1811434, MC_UU_12008/1, MC_UU_00007/10, MC_UU_00007/15, MR/N003179/1)
  • Biotechnology and Biological Sciences Research Council (BBS/E/D/30002276, BBS/E/D/20002172, /30002275, BBS/E/D/10002071, BBS/E/D/30002275, BBS/E/D/20002174, 20002174)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords
protein quantitative trait loci, protein abundance, drug target identification, schizophrenia, cardiovascular disease, FABP2, FGF5, IL-6 receptor, lipoprotein lipase, LTA, pleiotropy, colocalization, UK Biobank
MeSH terms
Antigens, Differentiation, Cardiovascular Diseases, Female, Humans, Lipoprotein Lipase, Lymphotoxin-alpha, Male, Receptors, Immunologic, Schizophrenia, Receptors, Interleukin-6, Proteome, Quantitative Trait Loci, Fatty Acid-Binding Proteins, Fibroblast Growth Factor 5, Genetic Association Studies, Mendelian Randomization Analysis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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