Abstract
Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
206,07 € per year
only 17,17 € per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others
References
Kannel, W.B., Dawber, T.R., Kagan, A., Revotskie, N. & Stokes, J. III. Factors of risk in the development of coronary heart disease—six year follow-up experience. The Framingham Study. Ann. Intern. Med. 55, 33–50 (1961).
Castelli, W.P. Cholesterol and lipids in the risk of coronary artery disease—the Framingham Heart Study. Can. J. Cardiol. 4 (suppl. A), 5A–10A (1988).
Lloyd-Jones, D. et al. Heart disease and stroke statistics—2010 update: a report from the American Heart Association. Circulation 121, e46–e215 (2010).
Teslovich, T.M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010).
Barter, P.J. & Rye, K.A. Cholesteryl ester transfer protein (CETP) inhibition as a strategy to reduce cardiovascular risk. J. Lipid Res. 53, 1755–1766 (2012).
Rahalkar, A.R. & Hegele, R.A. Monogenic pediatric dyslipidemias: classification, genetics and clinical spectrum. Mol. Genet. Metab. 93, 282–294 (2008).
Musunuru, K. et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature 466, 714–719 (2010).
Voight, B.F. et al. The Metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet. 8, e1002793 (2012).
1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).
Sanna, S. et al. Fine mapping of five loci associated with low-density lipoprotein cholesterol detects variants that double the explained heritability. PLoS Genet. 7, e1002198 (2011).
Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).
Asselbergs, F.W. et al. Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci. Am. J. Hum. Genet. 91, 823–838 (2012).
Welch, C.L. et al. Genetic regulation of cholesterol homeostasis: chromosomal organization of candidate genes. J. Lipid Res. 37, 1406–1421 (1996).
Sarria, A.J., Panini, S.R. & Evans, R.M. A functional role for vimentin intermediate filaments in the metabolism of lipoprotein-derived cholesterol in human SW-13 cells. J. Biol. Chem. 267, 19455–19463 (1992).
Hagberg, C.E. et al. Vascular endothelial growth factor B controls endothelial fatty acid uptake. Nature 464, 917–921 (2010).
Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000).
Segrè, A.V., Groop, L., Mootha, V.K., Daly, M.J. & Altshuler, D. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 6, e1001058 (2010).
Fitzgerald, M.L., Moore, K.J. & Freeman, M.W. Nuclear hormone receptors and cholesterol trafficking: the orphans find a new home. J. Mol. Med. (Berl.) 80, 271–281 (2002).
Rossin, E.J. et al. Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLoS Genet. 7, e1001273 (2011).
Plyte, S.E., Hughes, K., Nikolakaki, E., Pulverer, B.J. & Woodgett, J.R. Glycogen synthase kinase-3: functions in oncogenesis and development. Biochim. Biophys. Acta 1114, 147–162 (1992).
Toker, A. & Cantley, L.C. Signalling through the lipid products of phosphoinositide-3-OH kinase. Nature 387, 673–676 (1997).
Kaprio, J., Ferrell, R.E., Kottke, B.A., Kamboh, M.I. & Sing, C.F. Effects of polymorphisms in apolipoproteins E, A-IV, and H on quantitative traits related to risk for cardiovascular disease. Arterioscler. Thromb. 11, 1330–1348 (1991).
Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011).
The ENCODE Project Consortium. A user's guide to the encyclopedia of DNA elements (ENCODE). PLoS Biol. 9, e1001046 (2011).
Buyske, S. et al. Evaluation of the metabochip genotyping array in African Americans and implications for fine mapping of GWAS-identified loci: the PAGE study. PLoS ONE 7, e35651 (2012).
Palmen, J. et al. The functional interaction on in vitro gene expression of APOA5 SNPs, defining haplotype APOA52, and their paradoxical association with plasma triglyceride but not plasma apoAV levels. Biochim. Biophys. Acta 1782, 447–452 (2008).
Schunkert, H. et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat. Genet. 43, 333–338 (2011).
Coronary Artery Disease (C4D) Consortium. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease. Nat. Genet. 43, 339–344 (2011).
Voight, B.F. et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 42, 579–589 (2010).
Speliotes, E.K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010).
Heid, I.M. et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat. Genet. 42, 949–960 (2010).
Ehret, G.B. et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 478, 103–109 (2011).
Dupuis, J. et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat. Genet. 42, 105–116 (2010).
Freathy, R.M. et al. Common variation in the FTO gene alters diabetes-related metabolic traits to the extent expected given its effect on BMI. Diabetes 57, 1419–1426 (2008).
Clarke, R. et al. Cholesterol fractions and apolipoproteins as risk factors for heart disease mortality in older men. Arch. Intern. Med. 167, 1373–1378 (2007).
Willer, C.J. et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat. Genet. 40, 161–169 (2008).
Voight, B.F. et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet 380, 572–580 (2012).
Frikke-Schmidt, R. et al. Association of loss-of-function mutations in the ABCA1 gene with high-density lipoprotein cholesterol levels and risk of ischemic heart disease. J. Am. Med. Assoc. 299, 2524–2532 (2008).
Do, R. et al. Common variants associated with plasma triglycerides and risk for coronary artery disease. Nat. Genet. doi:10.1038/ng.2795 (6 October 2013).10.1038/ng.2795
Demirkan, A. et al. Genome-wide association study identifies novel loci associated with circulating phospho- and sphingolipid concentrations. PLoS Genet. 8, e1002490 (2012).
Friedewald, W.T., Levy, R.I. & Fredrickson, D.S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin. Chem. 18, 499–502 (1972).
Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).
Kang, H.M. et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 42, 348–354 (2010).
Stouffer, S.A., Suchman, E.A., DeVinney, L.C., Star, S.A. & Williams, R.M.J. Adjustment During Army Life (Princeton University Press, Princeton, NJ., 1949).
Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Keating, B.J. et al. Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies. PLoS ONE 3, e3583 (2008).
Schadt, E.E. et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol. 6, e107 (2008).
Chasman, D.I. et al. Forty-three loci associated with plasma lipoprotein size, concentration, and cholesterol content in genome-wide analysis. PLoS Genet. 5, e1000730 (2009).
Acknowledgements
We especially thank the more than 196,000 volunteers who participated in our study. Detailed acknowledgment of funding sources is provided in the Supplementary Note.
Author information
Authors and Affiliations
Consortia
Contributions
Writing and analysis group: G.R.A., M. Boehnke, L.A.C., P.D., P.W.F., S. Kathiresan, K.L.M., E.I., G.M.P., S.S.R., S.R., M.S.S., E.M.S., S. Sengupta and C.J.W. (Lead). E.M.S. and S. Sengupta performed meta-analysis, and E.M.S., S. Sengupta, G.M.P., M.L.B., J.C., S.G., A.G. and S. Kanoni performed bioinformatics analyses. E.M.S. and S. Sengupta prepared the tables, figures and supplementary material. C.J.W. led the analysis and bioinformatics efforts. E.I. and K.L.M. led the biological interpretation of results. C.J.W. and G.R.A. wrote the manuscript. All analysis and writing group authors extensively discussed the analysis, results, interpretation and presentation of results.
All authors contributed to the research and reviewed the manuscript.
Design, management and coordination of contributing cohorts: (ADVANCE) T.L.A.; (AGES Reykjavik study) T.B.H. and V.G.; (AIDHS/SDS) D.K.S.; (AMC-PAS) P.D. and G.K.H.; (Amish GLGC) A.R.S.; (ARIC) E.B.; (B58C-WTCCC and B58C-T1DGC) D.P.S.; (B58C-Metabochip) C.M.L., C. Power and M.I.M.; (BLSA) L.F.; (BRIGHT) P.B.M.; (CARDIOGRAM) N.S.; (CHS) B.M.P. and J.I.R.; (CLHNS) A.B.F., K.L.M. and L.S.A.; (CoLaus) P.V.; (CROATIA-Vis) C.H. and I.R.; (deCODE) K. Stefansson and U.T.; (DIAGEN) P.E.H.S. and S.R.B.; (DILGOM) S.R.; (DPS) M.U.; (DR's EXTRA) R.R.; (EAS) J.F.P.; (EGCUT (Estonian Genome Center of the University of Tartu)) A.M.; (ELY) N.J.W.; (ENGAGE) N.B.F.; (EPIC) N.J.W. and K.-T.K.; (EPIC_N_OBSET GWAS) E.H.Y.; (ERF) C.M.v.D.; (ESS (Erasmus Stroke Study)) P.J.K.; (Family Heart Study (FHS)) I.B.B.; (FBPP) A.C., R.S.C. and S.C.H.; (FENLAND) R.J.F.L. and N.J.W.; (FIN-D2D 27) A.K. and L.M.; (FINCAVAS) M. Kähönen; (Framingham) L.A.C., S. Kathiresan and J.M.O.; (FRISCII) A. Siegbahn and L.W.; (FUSION GWAS) K.L.M. and M. Boehnke; (FUSION stage 2) F.S.C., J.T. and J. Saramies; (GenomEUTwin) J.B.W., N.G.M., K.O.K., V.S., J. Kaprio, A.J., D.I.B., N.L.P. and T.D.S.; (GLACIER) P.W.F., G.H.; (Go-DARTS) A.D.M. and C.N.A.P.; (GxE/Spanish Town) B.O.T., C.A.M., F.B., J.N.H. and R.S.C.; (HUNT2) K. Hveem; (IMPROVE) U.d.F., A. Hamsten, E.T. and S.E.H.; (InCHIANTI) S.B.; (KORAF4) C.G.; (LifeLines) B.H.R.W.; (LOLIPOP) J.S.K. and J.C.C.; (LURIC) B.O.B. and W.M.; (MDC) L.C.G. and S. Kathiresan; (MEDSTAR) M.S.B., S.E.E.; (METSIM) J. Kuusisto and M.L.; (MICROS) P.P.P.; (MORGAM) D. Arveiler and J.F.; (MRC/UVRI GPC GWAS) P. Kaleebu, G.A., J. Seeley and E.H.Y.; (MRC National Survey of Health and Development) D.K.; (NFBC1986) M.-R.J.; (NSPHS) U.G.; (ORCADES) H.C.; (PARC) Y.-D.I.C., R.M.K. and J.I.R.; (PennCath) D.J.R. and M.P.R.; (PIVUS) E.I. and L.L.; (PROMIS) J.D., P.D. and D. Saleheen; (Rotterdam Study) A. Hofman and A.G.U.; (SardiNIA) G.R.A.; (SCARFSHEEP) A. Hamsten and U.d.F.; (SEYCHELLES) M. Burnier, M. Bochud and P. Bovet; (SUVIMAX) P.M.; (Swedish Twin Registry) E.I. and N.L.P.; (TAICHI) T.L.A., Y.-D.I.C., C.A.H., T.Q., J.I.R. and W.H.-H.S.; (THISEAS) G.D. and P.D.; (Tromsø) I.N.; (TWINGENE) U.d.F. and E.I.; (ULSAM) E.I.; and (Whitehall II) A. Hingorani and M. Kivimaki.
Genotyping of contributing cohorts: (ADVANCE) D. Absher; (AIDHS/SDS) L.F.B. and M.L.G.; (AMC-PAS) P.D. and G.K.H.; (B58C-WTCCC and B58C-T1DGC) W.L.M.; (B58C-Metabochip) M.I.M.; (BLSA) D.H.; (BRIGHT) P.B.M.; (CHS) J.I.R.; (DIAGEN) N.N. and G.M.; (DILGOM) A. Palotie; (DR's EXTRA) T.A.L.; (EAS) J.F.W.; (EGCUT (Estonian Genome Center of the University of Tartu)) T.E.; (EPIC) P.D.; (EPIC_N_SUBCOH GWAS) I.B.; (ERF) C.M.v.D.; (ESS (Erasmus Stroke Study)) C.M.v.D.; (FBPP) A.C. and G.B.E.; (FENLAND) M.S.S.; (FIN-D2D 27) A.J.S.; (FINCAVAS) T.L.; (Framingham) J.M.O.; (FUSION stage 2) L.L.B.; (GLACIER) I.B.; (Go-DARTS) C.J.G., C.N.A.P. and M.I.M.; (IMPROVE) A. Hamsten; (KORAF3) H.G. and T.I.; (KORAF4) N.K.; (LifeLines) C.W.; (LOLIPOP) J.S.K. and J.C.C.; (LURIC) M.E.K.; (MDC) B.F.V. and R.D.; (MICROS) A.A.H.; (MORGAM) L.T. and P. Brambilla; (MRC/UVRI GPC GWAS) M.S.S.; (MRC National Survey of Health and Development) A.W., D.K. and K.K.O.; (NFBC1986) A.-L.H., M.-R.J., M.M., P.E. and S.V.; (NSPHS and FRISCII) Å.J.; (ORCADES) H.C.; (PARC) M.O.G., M.R.J. and J.I.R.; (PIVUS) E.I. and L.L.; (PROMIS) P.D. and K. Stirrups; (Rotterdam Study) A.G.U. and F.R.; (SardiNIA) R.N.; (SCARFSHEEP) B.G. and R.J.S.; (SEYCHELLES) F.M. and G.B.E.; (Swedish Twin Registry) E.I. and N.L.P.; (TAICHI) D. Absher, T.L.A., E.K., T.Q. and L.L.W.; (THISEAS) P.D.; (TWINGENE) A. Hamsten and E.I.; (ULSAM) E.I.; (WGHS) D.I.C., S.M. and P.M.R.; and (Whitehall II) A. Hingorani, C.L., M. Kumari and M. Kivimaki.
Phenotype definition of contributing cohorts: (ADVANCE) C.I.; (AGES Reykjavik study) T.B.H. and V.G.; (AIDHS/SDS) L.F.B.; (AMC-PAS) J.J.P.K.; (Amish GLGC) A.R.S. and B.D.M.; (B58C-WTCCC and B58C-T1DGC) D.P.S.; (B58C-Metabochip) C. Power and E.H.; (BRIGHT) P.B.M.; (CHS) B.M.P.; (CoLaus) P.V.; (deCODE) G.I.E., H.H. and I.O.; (DIAGEN) G.M.; (DILGOM) K. Silander; (DPS) J. Lindström; (DR's EXTRA) P. Komulainen; (EAS) J.L.B.; (EGCUT (Estonian Genome Center of the University of Tartu)) A.M.; (EGCUT (Estonian Genome Center of the University of Tartu)) K.F.; (ERF and Rotterdam Study) A. Hofman; (ERF) C.M.v.D.; (ESS (Erasmus Stroke Study)) E.G.V.d.H., H.M.D.H. and P.J.K.; (FBPP) A.C., R.S.C. and S.C.H.; (FINCAVAS) T.V.M.N.; (Framingham) S. Kathiresan and J.M.O.; (GenomEUTwin: MZGWA) J.B.W.; (GenomEUTwin-FINRISK) V.S.; (GenomEUTwin-FINTWIN) J. Kaprio and K. Heikkilä; (GenomEUTwin-GENMETS) A.J.; (GenomEUTwin-NLDTWIN) G.W.; (Go-DARTS) A.S.F.D., A.D.M., C.N.A.P. and L.A.D.; (GxE/Spanish Town) C.A.M. and F.B.; (IMPROVE) U.d.F., A. Hamsten and E.T.; (KORAF3) C.M.; (KORAF4) A. Döring; (LifeLines) L.J.v.P.; (LOLIPOP) J.S.K. and J.C.C.; (LURIC) H.S.; (MDC) L.C.G.; (METSIM) A. Stančáková; (MORGAM) G.C.; (MRC/UVRI GPC GWAS) R.N.N.; (MRC National Survey of Health and Development) D.K.; (NFBC1986) A.R., A.-L.H., A. Pouta and M.-R.J.; (NSPHS and FRISCII) Å.J.; (NSPHS) U.G.; (ORCADES) S.H.W.; (PARC) Y.-D.I.C. and R.M.K.; (PIVUS) E.I. and L.L.; (PROMIS) D.F.F.; (Rotterdam Study) A. Hofman; (SCARFSHEEP) U.d.F. and B.G.; (SEYCHELLES) M. Burnier, M. Bochud and P. Bovet; (Swedish Twin Registry) E.I. and N.L.P.; (TAICHI) H.-Y.C., C.A.H., Y.-J.H., E.K., S.-Y.L. and W.H.-H.S.; (THISEAS) G.D. and M.D.; (Tromsø) T.W.; (TWINGENE) U.d.F. and E.I.; (ULSAM) E.I.; (WGHS) P.M.R.; and (Whitehall II) M. Kumari.
Primary analysis from contributing cohorts: (ADVANCE) L.L.W.; (AIDHS/SDS) R.S.; (AMC-PAS) S. Kanoni; (Amish GLGC) J.R.O. and M.E.M.; (ARIC) K.A.V.; (B58C-Metabochip) C.M.L., E.H. and T.F.; (B58C-WTCCC and B58C-T1DGC) D.P.S.; (BLSA) T.T.; (BRIGHT) T.J.; (CLHNS) Y.W.; (CoLaus) J.S.B.; (deCODE) G.T.; (DIAGEN) A.U.J.; (DILGOM) M.P.; (EAS) R.M.F.; (DPS) A.U.J.; (DR's EXTRA) A.U.J.; (EGCUT (Estonian Genome Center of the University of Tartu)) E.M., K.F. and T.E.; (ELY) D.G.; (EPIC) K. Stirrups and D.G.; (EPIC_N_OBSET GWAS) E.H.Y. and C.L.; (EPIC_N_SUBCOH GWAS) N.W.; (ERF) A.I.; (ESS (Erasmus Stroke Study)) C.M.v.D. and E.G.V.d.H.; (EUROSPAN) A. Demirkan; (Family Heart Study (FHS)) I.B.B. and M.F.F.; (FBPP) A.C. and G.B.E.; (FENLAND) T.P. and C. Pomilla; (FENLAND GWAS) J.H.Z. and J. Luan; (FIN-D2D 27) A.U.J.; (FINCAVAS) L.-P.L.; (Framingham) L.A.C. and G.M.P.; (FRISCII and NSPHS) Å.J.; (FUSION stage 2) T.M.T.; (GenomEUTwin-FINRISK) J. Kettunen; (GenomEUTwin-FINTWIN) K. Heikkilä; (GenomEUTwin-GENMETS) I.S.; (GenomEUTwin-SWETWIN) P.K.E.M.; (GenomEUTwin-UK-TWINS) M.M.; (GLACIER) D. Shungin; (GLACIER) P.W.F.; (Go-DARTS) C.N.A.P. and L.A.D.; (GxE/Spanish Town) C.D.P.; (HUNT) A.U.J.; (IMPROVE) R.J.S.; (InCHIANTI) T.T.; (KORAF3) M.M.-N.; (KORAF4) A.-K.P.; (LifeLines) I.M.N.; (LOLIPOP) W.Z.; (LURIC) M.E.K.; (MDC) B.F.V.; (MDC) P.F. and R.D.; (METSIM) A.U.J.; (MRC/UVRI GPC GWAS) R.N.N.; (MRC National Survey of Health and Development) A.W. and J. Luan; (NFBC1986) M. Kaakinen, I.S. and S.K.S.; (NSPHS and FRISCII) Å.J.; (PARC) X.L.; (PIVUS) C. Song and E.I.; (PROMIS) J.D., D.F.F. and K. Stirrups; (Rotterdam Study) A.I.; (SardiNIA) C. Sidore, J.L.B.-G. and S. Sanna; (SCARFSHEEP) R.J.S.; (SEYCHELLES) G.B.E. and M. Bochud; (SUVIMAX) T.J.; (Swedish Twin Registry) C. Song and E.I.; (TAICHI) D. Absher, T.L.A., H.-Y.C., M.O.G., C.A.H., T.Q. and L.L.W.; (THISEAS) S. Kanoni; (Tromsø) A.U.J.; (TWINGENE) A.G. and E.I.; (ULSAM) C. Song, E.I. and S.G.; (WGHS) D.I.C.; and (Whitehall II) S. Shah.
Corresponding authors
Ethics declarations
Competing interests
B.P. serves on the Data and Safety Monitoring Board of a clinical trial funded by the manufacturer (Zoll), and he serves on the Steering Committee of the Yale Open-Data Project funded by the Medtronic. P.V. received an unrestricted grant from GlaxoSmithKline to build the CoLaus study. G.T., H.H., A.K., K. Stefansson and U.T. are employees of deCODE Genetics/Amgen, a biotechnology company. I.B. and spouse own stock in GlaxoSmithKline and Incyte, Ltd.
Supplementary information
Supplementary Text and Figures
Supplementary Tables 1–14, Supplementary Figures 1–7 and Supplementary Note (PDF 3819 kb)
Rights and permissions
About this article
Cite this article
Global Lipids Genetics Consortium. Discovery and refinement of loci associated with lipid levels. Nat Genet 45, 1274–1283 (2013). https://doi.org/10.1038/ng.2797
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/ng.2797
This article is cited by
-
Effects of genetically proxied lipid-lowering drugs on acute myocardial infarction: a drug-target mendelian randomization study
Lipids in Health and Disease (2024)
-
Lipid-lowering drugs and inflammatory bowel disease’s risk: a drug-target Mendelian randomization study
Diabetology & Metabolic Syndrome (2024)
-
Causal relationship between lipid-lowering drugs and ovarian cancer, cervical cancer: a drug target mendelian randomization study
BMC Cancer (2024)
-
A Mendelian randomization study between metabolic syndrome and its components with prostate cancer
Scientific Reports (2024)
-
Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification
Nature Genetics (2024)