Expressive

rs117760119 - ANGPTL4

Magnitude 2.0 · 3 studies on file

Reported associations

  • A genetic map of human metabolism across the allele frequency spectrum - Nature genetics (2025) · Zoodsma M, Beuchel C, Yasmeen S, Kohleick L, Nepal A, Koprulu M, Kronenberg F, Mayr M, Williamson A, Pietzner M, Langenberg C · PubMed 41044249

    ABSTRACT: Genetic studies of human metabolism have been limited in scale and allelic breadth. Here we provide a data-driven map of the genetic regulation of circulating small molecules and lipoprotein characteristics (249 traits) measured using proton nuclear magnetic resonance spectroscopy across the allele frequency spectrum in ~450,000 individuals. Trans-ancestral meta-analyses identify 29,824 locus-metabolite associations mapping to 753 regions with effects largely consistent between men and women and large ancestral groups represented in UK Biobank. We observe and classify extreme genetic pleiotropy, identify regulators of lipid metabolism, and assign effector genes at >100 loci through rare-to-common allelic series. We propose roles for genes less established in metabolic control (

  • The genetics of a "femaleness/maleness" score in cardiometabolic traits in the UK biobank - Scientific reports (2023) · Vosberg DE, Pausova Z, Paus T · PubMed 37277458

    ABSTRACT: We recently devised continuous "sex-scores" that sum up multiple quantitative traits, weighted by their respective sex-difference effect sizes, as an approach to estimating polyphenotypic "maleness/femaleness" within each binary sex. To identify the genetic architecture underlying these sex-scores, we conducted sex-specific genome-wide association studies (GWASs) in the UK Biobank cohort (females: n = 161,906; males: n = 141,980). As a control, we also conducted GWASs of sex-specific "sum-scores", simply aggregating the same traits, without weighting by sex differences. Among GWAS-identified genes, while sum-score genes were enriched for genes differentially expressed in the liver in both sexes, sex-score genes were enriched for genes differentially expressed

  • Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity - Nature communications (2019) · Kilpeläinen TO, Bentley AR, Noordam R, Sung YJ, Schwander K, Winkler TW, Jakupović H, Chasman DI, Manning A, Ntalla I, Aschard H, Brown MR, de las Fuentes L, Franceschini N, Guo X, Vojinovic D, Aslibekyan S, Feitosa MF, Kho M, Musani SK, Richard M, Wang H, Wang Z, Bartz TM, Bielak LF, Campbell A, Dorajoo R, Fisher V, Hartwig FP, Horimoto ARVR, Li C, Lohman KK, Marten J, Sim X, Smith AV, Tajuddin SM, Alver M, Amini M, Boissel M, Chai JF, Chen X, Divers J, Evangelou E, Gao C, Graff M, Harris SE, He M, Hsu FC, Jackson AU, Zhao JH, Kraja AT, Kühnel B, Laguzzi F, Lyytikäinen LP, Nolte IM, Rauramaa R, Riaz M, Robino A, Rueedi R, Stringham HM, Takeuchi F, van der Most PJ, Varga TV, Verweij N, Ware EB, Wen W, Li X, Yanek LR, Amin N, Arnett DK, Boerwinkle E, Brumat M, Cade B, Canouil M, Chen YI, Concas MP, Connell J, de Mutsert R, de Silva HJ, de Vries PS, Demirkan A, Ding J, Eaton CB, Faul JD, Friedlander Y, Gabriel KP, Ghanbari M, Giulianini F, Gu CC, Gu D, Harris TB, He J, Heikkinen S, Heng CK, Hunt SC, Ikram MA, Jonas JB, Koh WP, Komulainen P, Krieger JE, Kritchevsky SB, Kutalik Z, Kuusisto J, Langefeld CD, Langenberg C, Launer LJ, Leander K, Lemaitre RN, Lewis CE, Liang J, Liu J, Mägi R, Manichaikul A, Meitinger T, Metspalu A, Milaneschi Y, Mohlke KL, Mosley TH, Murray AD, Nalls MA, Nang EK, Nelson CP, Nona S, Norris JM, Nwuba CV, O'Connell J, Palmer ND, Papanicolau GJ, Pazoki R, Pedersen NL, Peters A, Peyser PA, Polasek O, Porteous DJ, Poveda A, Raitakari OT, Rich SS, Risch N, Robinson JG, Rose LM, Rudan I, Schreiner PJ, Scott RA, Sidney SS, Sims M, Smith JA, Snieder H, Sofer T, Starr JM, Sternfeld B, Strauch K, Tang H, Taylor KD, Tsai MY, Tuomilehto J, Uitterlinden AG, van der Ende MY, van Heemst D, Voortman T, Waldenberger M, Wennberg P, Wilson G, Xiang YB, Yao J, Yu C, Yuan JM, Zhao W, Zonderman AB, Becker DM, Boehnke M, Bowden DW, de Faire U, Deary IJ, Elliott P, Esko T, Freedman BI, Froguel P, Gasparini P, Gieger C, Kato N, Laakso M, Lakka TA, Lehtimäki T, Magnusson PKE, Oldehinkel AJ, Penninx BWJH, Samani NJ, Shu XO, van der Harst P, Van Vliet-Ostaptchouk JV, Vollenweider P, Wagenknecht LE, Wang YX, Wareham NJ, Weir DR, Wu T, Zheng W, Zhu X, Evans MK, Franks PW, Gudnason V, Hayward C, Horta BL, Kelly TN, Liu Y, North KE, Pereira AC, Ridker PM, Tai ES, van Dam RM, Fox ER, Kardia SLR, Liu CT, Mook-Kanamori DO, Province MA, Redline S, van Duijn CM, Rotter JI, Kooperberg CB, Gauderman WJ, Psaty BM, Rice K, Munroe PB, Fornage M, Cupples LA, Rotimi CN, Morrison AC, Rao DC, Loos RJF · PubMed 30670697

    ABSTRACT: Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL

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