rs1057208 - PLTP - PCIF1
Magnitude 2.0 · 6 studies on file
Reported associations
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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 (
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Genome-wide characterization of circulating metabolic biomarkers - Nature (2024) · Karjalainen MK, Karthikeyan S, Oliver-Williams C, Sliz E, Allara E, Fung WT, Surendran P, Zhang W, Jousilahti P, Kristiansson K, Salomaa V, Goodwin M, Hughes DA, Boehnke M, Fernandes Silva L, Yin X, Mahajan A, Neville MJ, van Zuydam NR, de Mutsert R, Li-Gao R, Mook-Kanamori DO, Demirkan A, Liu J, Noordam R, Trompet S, Chen Z, Kartsonaki C, Li L, Lin K, Hagenbeek FA, Hottenga JJ, Pool R, Ikram MA, van Meurs J, Haller T, Milaneschi Y, Kähönen M, Mishra PP, Joshi PK, Macdonald-Dunlop E, Mangino M, Zierer J, Acar IE, Hoyng CB, Lechanteur YTE, Franke L, Kurilshikov A, Zhernakova A, Beekman M, van den Akker EB, Kolcic I, Polasek O, Rudan I, Gieger C, Waldenberger M, Asselbergs FW, Hayward C, Fu J, den Hollander AI, Menni C, Spector TD, Wilson JF, Lehtimäki T, Raitakari OT, Penninx BWJH, Esko T, Walters RG, Jukema JW, Sattar N, Ghanbari M, Willems van Dijk K, Karpe F, McCarthy MI, Laakso M, Järvelin MR, Timpson NJ, Perola M, Kooner JS, Chambers JC, van Duijn C, Slagboom PE, Boomsma DI, Danesh J, Ala-Korpela M, Butterworth AS, Kettunen J · PubMed 38448586
ABSTRACT: Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associa
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Decreased Circulating Very Small Low-Density Lipoprotein is Likely Causal for Age-Related Macular Degeneration - Ophthalmology science (2024) · Farashi S, Bonelli R, Jackson VE, Ansell BRE, Guymer RH, Bahlo M · PubMed 39091897
ABSTRACT: Objective Abnormal changes in metabolite levels in serum or plasma have been highlighted in several studies in age-related macular degeneration (AMD), the leading cause of irreversible vision loss. Specific changes in lipid profiles are associated with an increased risk of AMD. Metabolites could thus be used to investigate AMD disease mechanisms or incorporated into AMD risk prediction models. However, whether particular metabolites causally affect the disease has yet to be established. Design A 3-tiered analysis of blood metabolites in the United Kingdom (UK) Biobank cohort to identify metabolites that differ in AMD patients with evidence for a putatively causal role in AMD. Participants A total of 72 376 donors from the UK Biobank cohort including participants with AMD (N =
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Metabolomic investigation of major depressive disorder identifies a potentially causal association with polyunsaturated fatty acids - Biological psychiatry (2023) · Davyson E, Shen X, Gadd DA, Bernabeu E, Hillary RF, McCartney DL, Adams M, Marioni R, McIntosh AM · PubMed 36764567
ABSTRACT: Background: Metabolic differences have been reported between individuals with and without Major Depressive Disorder (MDD), but their consistency and causal relevance has been unclear. Methods: We conducted a metabolome-wide association study of MDD with 249 metabolomic measures available in UK Biobank (N = 29, 757). We then applied 2-sample bidirectional Mendelian Randomisation (MR) and colocalization analysis to identify potentially causal relationships between each metabolite and MDD. Results: One hundred and ninety-one metabolites tested were significantly associated with MDD (PFDR < 0.05), which reduced to 129 after adjustment for likely confounders. Lower abundance of Omega-3 fatty acid measures and a higher Omega-6: Omega-3 ratio showed potentially causal effects on liabili
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Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation - PLoS biology (2022) · Richardson TG, Leyden GM, Wang Q, Bell JA, Elsworth B, Davey Smith G, Holmes MV · PubMed 35213538
ABSTRACT: Large-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on the human metabolome. We firstly constructed genetic risk scores for 8 drug targets on the basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9, and NPC1L1), high-density lipoprotein (HDL) cholesterol (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4, and LPL). Conducting mendelian randomisation (MR) provided strong evidence of an effect of drug-based genetic scores on coronary artery disease (CAD) risk with the exception of ANGPTL3. We then systematically estimated the effects of each score on 249 metabolic traits derived using blood samples from an unprecedented sample size of up to
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Trans-ethnic and ancestry-specific blood-cell genetics in 746,667 individuals from 5 global populations - Cell (2021) · Chen MH, Raffield LM, Mousas A, Sakaue S, Huffman JE, Moscati A, Trivedi B, Jiang T, Akbari P, Vuckovic D, Bao EL, Zhong X, Manansala R, Laplante V, Chen M, Lo KS, Qian H, Lareau CA, Beaudoin M, Hunt KA, Akiyama M, Bartz TM, Ben-Shlomo Y, Beswick A, Bork-Jensen J, Bottinger EP, Brody JA, van Rooij FJA, Chitrala K, Cho K, Choquet H, Correa A, Danesh J, Di Angelantonio E, Dimou N, Ding J, Elliott P, Esko T, Evans MK, Floyd JS, Broer L, Grarup N, Guo MH, Greinacher A, Haessler J, Hansen T, Howson JMM, Huang QQ, Huang W, Jorgenson E, Kacprowski T, Kähönen M, Kamatani Y, Kanai M, Karthikeyan S, Koskeridis F, Lange LA, Lehtimäki T, Lerch MM, Linneberg A, Liu Y, Lyytikäinen LP, Manichaikul A, Martin HC, Matsuda K, Mohlke KL, Mononen N, Murakami Y, Nadkarni GN, Nauck M, Nikus K, Ouwehand WH, Pankratz N, Pedersen O, Preuss M, Psaty BM, Raitakari OT, Roberts DJ, Rich SS, Rodriguez BAT, Rosen JD, Rotter JI, Schubert P, Spracklen CN, Surendran P, Tang H, Tardif JC, Trembath RC, Ghanbari M, Völker U, Völzke H, Watkins NA, Zonderman AB, Wilson PWF, Li Y, Butterworth AS, Gauchat JF, Chiang CWK, Li B, Loos RJF, Astle WJ, Evangelou E, van Heel DA, Sankaran VG, Okada Y, Soranzo N, Johnson AD, Reiner AP, Auer PL, Lettre G · PubMed 32888493
ABSTRACT: SUMMARY Most loci identified by GWAS have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at P<5×10−9, including 71 novel loci not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional, and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value
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