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The power of genetic diversity in genome-wide association studies of lipids
Open accessAbstract
Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use 1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels 2, heart disease remains the leading cause of death worldwide 3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS 4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns 24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine 25, we anticipate that increased diversity of participants will lead to more accurate and equitable 26 application of polygenic scores in clinical practice.
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“This result replicated previous studies showing that multi-ancestry PGS demonstrated an improved prediction performance relative to ancestry-matched PGSs41,42.”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [41]
Experimental — accuracy not yet measuredIn the citing paper
“We found genetic variants significantly associated with plasma high-density lipoprotein cholesterol (HDL-c; p < 5.0E-08; Fig. 6a).”
From Hepatic SREBP signaling requires SPRING to govern systemic lipid metabolism in mice and humans (2023) · cites this paper as [28]
In the citing paper
“The top-associated single nucleotide polymorphism (SNP), rs10507274, more specifically the “C” allele, found in ~6% of the general population, is significantly associated with increased plasma levels of HDL-c (p = 8.6E-11, Beta = +0.0183 ( ± 2.8E-03); Fig. 6a, b).”
From Hepatic SREBP signaling requires SPRING to govern systemic lipid metabolism in mice and humans (2023) · cites this paper as [28]
In the citing paper
“The Global Lipids Genetics Consortium aggregated GWAS results from 1,654,960 individuals from 201 primary studies representing five genetic ancestry groups28.”
From Hepatic SREBP signaling requires SPRING to govern systemic lipid metabolism in mice and humans (2023) · cites this paper as [28]
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Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,724 · cited 1×
“Variants were annotated using WGSA 51 , including the summary of each variant from SnpEff 52 and the closest genes for intergenic variants from ANNOVAR 53 .”
MethodSelf-citationKass, R. E., & Raftery, A. (1995) · doi:10.4135/9781412952644.n45 · Cited by 13,782 · cited 1×
“Bayes factors 56,57 (BFs) for each variant in the ancestry-specific meta-analysis were approximated as follows: where β and s.e. are the effect size and standard error of the effect size estimate from the Raremetal meta-analysis, and N AS is the ancestry-specific sample size.”
MethodCingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., Land, S. J., Lu, X., & Ruden, D. M. (2012) · Fly · doi:10.4161/fly.19695 · Cited by 11,816 · cited 2×
“Variants were annotated using WGSA 51 , including the summary of each variant from SnpEff 52 and the closest genes for intergenic variants from ANNOVAR 53 .”
MethodSelf-citationFast model-based estimation of ancestry in unrelated individuals
Alexander, D. H., Novembre, J., & Lange, K. (2009) · Genome Research · doi:10.1101/gr.094052.109 · Cited by 9,898
Roth, G. A., Abate, D., Abate, K. H., Abay, S. M., Abbafati, C., Abbasi, N., Abbastabar, H., Abd-Allah, F., Abdela, J., Abdelalim, A., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(18)32203-7 · Cited by 8,600
The Ensembl Variant Effect Predictor
McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099 · cited 1×
“Variants within the credible sets were annotated with SnpEff 52 using WGSA 51 and with VEP 59 .”
MethodSelf-citationdbSNP: the NCBI database of genetic variation
Sherry, S. T. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.308 · Cited by 7,502
Howard, W. J. (2007) · Yearbook of Endocrinology · doi:10.1016/s0084-3741(08)70063-5 · Cited by 6,672 · cited 1×
“Individuals on cholesterol-lowering medication had their pre-medication levels 44 approximated by dividing the LDL-C value by 0.7 and the TC value by 0.8.”
MethodInfluential
Research works printed but not linked: 1
- Lehmann, B. C. L., Mackintosh, M., McVean, G. & Holmes, C. C. High trait variability in optimal polygenic prediction strategy within multiple-ancestry cohorts. Preprint at bioRxiv https://doi.org/10.1101/2021.01.15.426781 (2021). · DOI
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Items 301–400 of 829
CPEB2-activated Prdm16 translation promotes brown adipocyte function and prevents obesity
Lu, W.-H., Chen, H., King, P.-C., Peng, C., & Huang, Y. (2024) · Molecular Metabolism · doi:10.1016/j.molmet.2024.102034 · Cited by 5
“32 in the CPEB2 gene with low density lipoprotein cholesterol levels ( P ¼ 5.25 (cid:5) 10 (cid:4) 9 ) [61], suggesting that CPEB2-mediated translational control may have a role in regulating human body weight and lipid metabolism.”
InfluentialGenetics of glucose homeostasis in pregnancy and postpartum
Lowe, W. L., Kuang, A., Hayes, M. G., Hivert, M., & Scholtens, D. M. (2024) · Diabetologia · doi:10.1007/s00125-024-06256-8 · Cited by 9
“Finally, higher expression levels of IQSEC1 in blood cells of obese boys with normal insulin sensitivity compared with non-obese boys [40] and association of variants in IQSEC1 with non-HDL-cholesterol outside of pregnancy have been reported [41].”
Self-citationLeite, J., Pereira, J. L., de Souza, C. A., Soler, J. M. P., Mingroni-Netto, R., Fisberg, R. M., Rogero, M., & Sarti, F. (2024) · Lipids in Health and Disease · doi:10.1186/s12944-024-02085-1 · Cited by 7
“The adjustment baseline covariates age, sex, age-sex interaction, age 2 , and presence of overweight were commonly used across phenotypes in previous association analyses to avoid confounding, as in other studies [8].”
BackgroundMethodCardiero, G., Ferrandino, M., Calcaterra, I. L., Iannuzzo, G., Minno, M. N. D. D., Buganza, R., Guardamagna, O., Auricchio, R., Taranto, M. D. D., & Fortunato, G. (2024) · Genes · doi:10.3390/genes15040462 · Cited by 7
Pang, X., Yang, H., Li, M., Suárez‐Fariñas, M., & Tian, S. (2024) · eGastroenterology · doi:10.1136/egastro-2023-100034 · Cited by 5
Osteoporosis and Primary Biliary Cholangitis: A Trans-ethnic Mendelian Randomization Analysis
Wu, Y., Qian, Q., Liu, Q., Wang, R., Pu, X., Li, Y. O., Zhang, H., You, Z., Miao, Q., Xiao, X., et al. (2024) · Clinical Reviews in Allergy & Immunology · doi:10.1007/s12016-024-08986-4 · Cited by 8
“…were included as follows: BMI from 806,834 individuals included in a GWAS meta-analysis [31]; serum 25 hydroxyvitamin D [25(OH)D] concentration from 496,946 individuals [32], calcium from 357,831 individuals [33], and total cholesterol and triglycerides (TG) from 1,320,016 individuals [34].”
Genetic insight into putative causes of xanthelasma palpebrarum: a Mendelian randomization study
Hu, W., Liu, Y., Cuihong, L., & Lu, H. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1347112 · Cited by 6
Jareebi, M. A., Gharawi, N. F., Shami, M. O., Kariri, A., Hakami, T. F., Alamer, N. M., Alhazmi, K., Kariri, A. M., Darbashi, A. H., Kuriri, A. M., et al. (2023) · Cureus · doi:10.7759/cureus.51220 · Cited by 7
“These include the UKB [10], GWAS and Sequencing Consortium of Alcohol and Nicotine Use (GSCAN) [11], Genetic Investigation of Anthropometric Traits (GIANT) [12], Global Lipids Genetics Consortium (GLGC) [13], and Klimentidis et al. (2018) [14].”
MethodPolygenic risk score prediction accuracy convergence
Henches, L., Kim, J., Yang, Z., Rubinacci, S., Pires, G., Albiñana, C., Boetto, C., Julienne, H., Frouin, A., Auvergne, A., et al. (2025) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2025.100457 · Cited by 8
Cross-ancestry genetic architecture and prediction for cholesterol traits
Momin, M. M., Zhou, X., Hyppönen, E., Benyamin, B., & Lee, S. (2024) · Human Genetics · doi:10.1007/s00439-024-02660-7 · Cited by 6
“We note that the significance level in our study is higher compared to Graham et al. (2021) although similar sample sizes were used.”
InfluentialSelf-citationQiao, J., Shao, Z., Wu, Y., Zeng, P., & Wang, T. (2022) · Journal of Translational Medicine · doi:10.1186/s12967-022-03637-8 · Cited by 8
“, blood lipids [1], prostate cancer [2], blood pressure [3, 4], type II diabetes [5, 6], glycemic traits [7], and schizophrenia [8]).”
BackgroundGenetically proxied impaired GIPR signaling and risk of 6 cancers
Rogers, M., Gill, D., Ahlqvist, E., Robinson, T., Mariosa, D., Johansson, M., Penha, R. C. C., Dossus, L., Gunter, M. J., Moreno, V. R., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106848 · Cited by 10
Granot‐Hershkovitz, E., Sun, Q., Argos, M., Zhou, H., Lin, X., Browning, S. R., & Sofer, T. (2022) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2022.100096 · Cited by 12
“Global Lipids Genetics Consortium (GLGC) has recently published aggregated GWAS results, including results for n 1⁄4 48,000 Hispanic individuals, including the HCHS/ SOL.(29) Table S8 presents these results for the lipid-associated variants that we identified in HCHS/SOL.”
BackgroundSelf-citationPolygenic risk scores enhance LDL cholesterol–based risk stratification for coronary artery disease
Harper, C., Misra, A., Patel, A. P., Cho, S. M. J., Koyama, S., Peloso, G. M., Hornsby, W., Nakao, T., & Natarajan, P. (2026) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2026.101487 · Cited by 4
“For the analysis including individuals taking lipid-lowering medications, LDL-C was divided by 0.7 in both cohorts to approximate average imputed effect of lipid-lowering medications [25].”
InfluentialSelf-citationKim, D., Highland, H. M., Smit, R. A. J., Hysong, M. R., Buchanan, V. L., Young, K. L., Zhao, C. G., Spracklen, C. N., Kilpeläinen, T. O., Guo, B., et al. (2025) · Genome Medicine · doi:10.1186/s13073-025-01522-9 · Cited by 9
“…for atrial fibrillation, dementia, hypercholesterolemia, hypertension, MI, obesity, stroke, and T2D; Global Lipids Genetics Consortium (GLGC) GWAS [59, 60] for HDL, LDL, and TG; Meta-Analyses of Glucose and insulin-related traits Consortium (MAGIC) GWAS [61–64] for fasting glucose, fasting…”
Self-citationDistinct patterns of genetic overlap among multimorbidities revealed with trivariate MiXeR
Shadrin, A. A., Hindley, G., Hagen, E., Parker, N., Tesfaye, M., Jaholkowski, P. P., Rahman, Z., Kutrolli, G., Fominykh, V., Djurovic, S., et al. (2025) · Genome Medicine · doi:10.1186/s13073-025-01528-3 · Cited by 11
“…ADHD (38,691 cases, 186,843 controls) [12], T2D (80,154 cases, 853,816 controls) [26], eGFR (567,460 individuals) [27], HDL (1,244,580 individuals) [28], UC (12,366 cases, 33,609 controls) [29], MS (14,802 cases, 26,703 controls) [30] and PS (965 cases, 437,420 controls) [31] (FinnGen, release 11,…”
Currin, K. W., Perrin, H. J., Pandey, G. K., Alkhawaja, A. A., Vadlamudi, S., Musser, A. E., Etheridge, A. S., Broadaway, K. A., Rosen, J. D., Varshney, A., et al. (2025) · Genome Research · doi:10.1101/gr.279741.124 · Cited by 8
Self-citationYu, Y., Yang, H.-J., Li, C., Ryu, M. S., Seo, J.-W., Jeong, D., & Park, S. (2025) · Nutrients · doi:10.3390/nu17101617 · Cited by 6
“These findings are consistent with previous studies, demonstrating that isoflavonoids and Bacillus -fermented soybean products improve cognitive function through mechanisms involving BDNF upregulation and oxidative stress attenuation in aged or cognitively impaired rodent models [12–14].”
A Beneficial Role for Gluteofemoral Adipose Tissue in Cerebrovascular Disease
Myserlis, E. P., Georgakis, M. K., Parodi, L., Mayerhofer, E., Omarov, M., Rosand, J. M., Banerjee, C., & Anderson, C. D. (2025) · Neurology · doi:10.1212/wnl.0000000000213573 · Cited by 11
Petty, L. E., Chen, H., Frankel, E. G., Zhu, W., Downie, C. G., Graff, M., Lin, P., Sharma, P., Zhang, X., Scartozzi, A., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58574-z · Cited by 9
“As with T2D, we used S-PrediXcan to identify GReX-trait associations for each of the lipid traits (Supplementary Data 8).”
InfluentialSelf-citationIncorporating multiple functional annotations to improve polygenic risk prediction accuracy
Shao, Z., Tang, W., Hong-ji, W., Kong, Y., & Hao, X. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100850 · Cited by 8
Liu, Z., Chen, X., Yuan, H., Li, J., Zhang, T., & Chen, X. (2024) · Human Molecular Genetics · doi:10.1093/hmg/ddae184 · Cited by 7
Phylogenomics and plastome evolution of Lithospermeae (Boraginaceae)
Noroozi, M., Ghahremaninejad, F., Riahi, M., & Cohen, J. (2024) · BMC Plant Biology · doi:10.1186/s12870-024-05665-6 · Cited by 6
“This bias reflects the underlying dynamics of nucleotide alterations within the plastid genome and its implications for genetic diversity and evolutionary processes [84].”
BackgroundLim, A., Pasini, M., Yun, S., Gill, J., & Koirala, B. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.08.027 · Cited by 8
Fast and scalable ensemble learning method for versatile polygenic risk prediction
Chen, T., Zhang, H., Mazumder, R., & Lin, X. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2403210121 · Cited by 7
Self-citationSGLT2 Inhibition, Blood Lipids, and Cardiovascular Disease: A Mendelian Randomization Study
Li, J., Li, C., Feng, X., & Wei, X. (2024) · ESC Heart Failure · doi:10.1002/ehf2.14987 · Cited by 8
Funmap: integrating high-dimensional functional annotations to improve fine-mapping
Li, Y., Xiao, J., Ming, J., Zeng, Y., & Cai, M. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btaf017 · Cited by 6
“Then, we evaluated the replication rates of these newly identified SNPs using independent multi-ancestry GWASs from the Global Lipids Genetics Consortium (GLGC) [29], which comprised up to 900K samples across the four traits.”
MethodGenetic Architecture and Clinical Outcomes of Combined Lipid Disturbances
Gilliland, T., Dron, J. S., Selvaraj, M. S., Trinder, M., Paruchuri, K., Urbut, S., Haidermota, S., Bernardo, R. C., Uddin, M. M., Honigberg, M. C., et al. (2024) · Circulation Research · doi:10.1161/circresaha.123.323973 · Cited by 9
Self-citationWang, S., Ojewunmi, O. O., Kamiza, A. B., Ramsay, M., Morris, A. P., Chikowore, T., Fatumo, S., & Asimit, J. L. (2024) · Communications Biology · doi:10.1038/s42003-024-07236-9 · Cited by 5
“…(rs11884143, rs3735018, rs3808607, rs28362286 and rs7412), and one SNP driven jointly by sex and BMI, as well as urban status (rs10846742); rs28362286 and rs7412 were genome-wide significant SNPs for LDL in twelve African cohorts overlapping with the GLGC meta-analysis 38 ( Supplementary Data 1 ).”
BackgroundSelf-citationManikpurage, H., Ricard, J., Houessou, U., Bourgault, J., Gagnon, É., Gobeil, É., Girard, A., Li, Z.-L., Eslami, A., Mathieu, P., et al. (2024) · medRxiv · doi:10.1101/2024.04.23.24306257 · Cited by 6
Annevelink, C. E., Westra, J., Sala‐Vila, A., Harris, W. S., Tintle, N., & Shearer, G. C. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2023.12.035 · Cited by 5
Phenome-wide association study on miRNA-related sequence variants: the UK Biobank
Mustafa, R., Ghanbari, M., Karhunen, V., Evangelou, M., & Dehghan, A. (2023) · Human Genomics · doi:10.1186/s40246-023-00553-w · Cited by 9
“This finding was replicated using the largest GWAS from GLGC as the outcome dataset [49], supporting the lowering effect of miR-6891-3p on TC, TG, LDL-C, and non-HDL-C (Table 3).”
MethodSelf-citationCausal associations between blood lipids and brain structures: a Mendelian randomization study
Zeng, Y., Guo, R., Cao, S., & Yang, H. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad334 · Cited by 6
Effect of obesity, lipids and adipokines on allergic rhinitis risk: a Mendelian randomization study
Lin, C., Li, J., Deng, Y., Li, X., & Li, S. M. (2023) · Brazilian Journal of Otorhinolaryngology · doi:10.1016/j.bjorl.2023.101306 · Cited by 11
Self-citationYuan, S., Li, Y., Wang, L., Xu, F., Chen, J., Levin, M. G., Xiong, Y., Voight, B. F., Damrauer, S. M., Gill, D., et al. (2023) · medRxiv · doi:10.1101/2023.07.20.23292938 · Cited by 7
Self-citationHassanin, E., Maj, C., Klinkhammer, H., Krawitz, P., May, P., & Bobbili, D. (2023) · BMC Medical Genomics · doi:10.1186/s12920-023-01598-5 · Cited by 6
“possible, PRS should be constructed based on GWAS based on the same ancestry group [31].”
BackgroundBocher, O., Gilly, A., Park, Y., Zeggini, E., & Morris, A. P. (2023) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2023.100214 · Cited by 7
Self-citationBoukhalfa, W., Jmel, H., Kheriji, N., Gouiza, I., Dallali, H., Hechmi, M., & Kéfi, R. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1114810 · Cited by 7
“It has previously been associated with metabolic syndrome (Brown and Walker, 2016) and elevated serum cholesterol, LDL, and ApoB levels in individuals of African, East Asian, European, Hispanic, and South Asian ancestry (Graham et al., 2021).”
BackgroundPleiotropic influence of DNA methylation QTLs on physiological and ageing traits
Mozhui, K., Kim, H., Villani, F., Haghani, A., Sen, Ś., & Horvath, S. (2023) · Epigenetics · doi:10.1080/15592294.2023.2252631 · Cited by 5
Self-citationIntegrated Drivers of Basal and Acute Immunity in Diverse Human Populations
Souquette, A., Allen, E., Oshansky, C., Tang, L., Wong, S., Jeevan, T., Shi, L., Pounds, S., Elias, G., Kuan, G., et al. (2023) · bioRxiv · doi:10.1101/2023.03.25.534227 · Cited by 6
Roychowdhury, T., Klarin, D. M., Levin, M. G., Spin, J. M., Rhee, Y. H., Deng, A. C., Headley, C. A., Surakka, I. L., Tsao, N. L., Gellatly, C., et al. (2022) · medRxiv · doi:10.1101/2022.05.27.22275607 · Cited by 9
“, 2020) using the largest available GWAS summary statistics of 4 lipids traits (Graham et al., 2021), 3 blood pressure traits (Evangelou et al.”
MethodInfluentialSelf-citationGratton, J., Finan, C., Hingorani, A. D., Humphries, S. E., & Futema, M. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.845498 · Cited by 8
“16 across the five PCA-verified ancestry groups studied (Graham et al., 2021).”
BackgroundInfluential(2023) · doi:10.1101/2023.08.04.551959 · Cited by 6
Self-citationJacobs, B. M., Schalk, L., Tregaskis-Daniels, E., Scalfari, A., Nandoskar, A., Dunne, A., Gran, B., Mein, C. A., Sellers, C., Spilker, C., et al. (2026) · Neurology · doi:10.1212/wnl.0000000000214708 · Cited by 5
YAP/TAZ-VGLL3 governs adipocyte fate via epigenetic reprogramming of PPARγ and its target enhancers
Seol, T., Kang, J.-G., Ryu, K., Kim, W., Hwang, D., Cho, S., Song, D., Ku, B., Tran, Y. T. H., Jeong, S., et al. (2026) · Science Advances · doi:10.1126/sciadv.aea7235 · Cited by 8
Global patterns of natural selection inferred using ancient DNAPreprint
Colbran, L. L., Terhorst, J., & Mathieson, I. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.07.697984 · Cited by 3
“…Coronary Artery Disease (CAD) [176], Irritable Bowel Disease, ulcerative colitis (UC), Crohn’s Disease [177], HDL levels, LDL levels, triglycerides [178], Rheumatoid Arthritis (RA) [179], Type II Diabetes [180], and Waist-hip ratio (all, male, and female) [181], estimated Glomerular Filtration…”
Lipid-Related Polygenic Risk Score and Its Association With Plaque Rupture Versus Erosion
Hamana, T., Gaynor, B. J., Grogan, A., Turoni-Glitz, A., Kawakami, R., Shiraki, T., Sekimoto, T., Tanaka, T., Fujiyoshi, K., Nakayama, T., et al. (2025) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.125.323942 · Cited by 5
Potential synthetic associations created by epistasis
Liu, H., Fu, J., Xu, S., & Nordborg, M. (2025) · Genome biology · doi:10.1186/s13059-025-03807-z · Cited by 7
“Figure 2a–b shows an example of an association with smoking and drinking behavior [18, 19].”
Repurposing statin treatment for the prevention of gallstone disease.
Rønborg, S. N., Qayyum, F., Lauridsen, B., Frikke-Schmidt, R., Nordestgaard, B., Christoffersen, M., & Tybjærg-Hansen, A. (2025) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2025.120507 · Cited by 5
Ponomarenko, M., Reshetnikov, E., Churnosova, M., Aristova, I., Abramova, M. Y., Борисович, Н. В., Churnosov, V., Polonikov, A., Churnosov, M. I., & Ponomarenko, I. (2025) · Life · doi:10.3390/life15091459 · Cited by 6
Lin, C., Wen, H., Yu, M., Huang, Q., Wang, Q., Lin, J., Yang, W., Wong, J. M. J., Xia, M., Tang, H., et al. (2025) · BMC Medicine · doi:10.1186/s12916-025-04329-y · Cited by 5
“Notably, to account for the effects of lipid-lowering medications, we corrected LDL-c and total cholesterol (TC) levels in statin users by dividing LDL-c by 0.70 and TC by 0.80, and subsequently recalculated RC levels [32].”
InfluentialLiver single-nucleus multiome profiling reveals cell-type mechanisms for cardiometabolic traits
Alkhawaja, A. A., Currin, K. W., Perrin, H. J., Vadlamudi, S., Etheridge, A., Broadaway, K. A., Cannon, G. H., Anderson, C. W., Moxley, A. H., Iuga, A. C., et al. (2025) · bioRxiv · doi:10.1101/2025.08.06.668997 · Cited by 5
“Genome-wide association studies (GWASs) have identified hundreds of signals for cardiometabolic traits, 1–6 but the molecular mechanisms and cell type(s) of action for most of these signals have not yet been defined.”
Self-citationYang, Y.-H., & Zhu, X.-F. (2025) · bioRxiv · doi:10.1101/2025.07.11.664423 · Cited by 5
Self-citationKasela, S., Luitva, L. B., Krebs, K., Möls, M., Milani, L. A., & Alver, M. (2025) · Journal of Translational Medicine · doi:10.1186/s12967-025-06782-y · Cited by 6
“…smoking (EVERSMK) [47], estimated glomerular filtration rate (eGFR) [48], alanine aminotransferase (ALT) [49], body mass index (BMI) [50], glycated haemoglobin (Hb1Ac) [51], LDL-cholesterol (LDL-C) [52], HDL-cholesterol (HDL) [52], triglycerides (TG) [52], and systolic blood pressure (SBP) [53].”
Sun, G., Xia, D., Xue, B., Jian, X., Peng, L., Wang, B., Wu, C., Gao, C., He, L., Xu, Y., et al. (2025) · General Psychiatry · doi:10.1136/gpsych-2024-101900 · Cited by 3
Buren, E. V., Zhang, Y., Li, X., Selvaraj, M. S., Li, Z., Zhou, H., Palmer, N. D., Arnett, D. K., Blangero, J., Boerwinkle, E., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02919-5 · Cited by 4
“…CETP locus for HDL-C. cellSTAAR also revealed significant element–gene–phenotype combinations after conditional analysis in lipid-associated loci 27,47,48 for rare variant associations in pELS elements linked to the APOE locus for both LDL-C and TG and dELS elements linked to the APOA1 locus for…”
Self-citationInferring past demography and genetic adaptation in Spain using the GCAT cohort
Garcia-Calleja, J., Biagini, S. A., de Cid, R., Calafell, F., & Bosch, E. (2025) · Scientific Reports · doi:10.1038/s41598-025-98272-w · Cited by 5
Xu, L., Zhou, G., Jiang, W., Zhang, H., Dong, Y., Guan, L., & Zhao, H. (2025) · Nature Communications · doi:10.1038/s41467-025-59243-x · Cited by 21
Dudek, M. F., Wenz, B. M., Brown, C. D., Voight, B. F., Almasy, L. A., & Grant, S. F. A. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.03.019 · Cited by 8
Self-citationHuang, Q., Zhang, H., Shen, Z., Chen, J., Cao, X., Xu, L., Zhu, C., Lv, S., Yu, X., Ding, X., et al. (2025) · Phenomics · doi:10.1007/s43657-024-00179-5 · Cited by 4
“Our results should be cautiously interpreted in patients from other regions (Graham et al. 2021; McGladdery et al. 2001).”
Shen, J., Pan, J., Yu, G., Cai, H., Xu, H., Yan, H., & Feng, Y. (2024) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.70045 · Cited by 5
Gautam, Y., Satish, L., Ramirez, S., Grashel, B., Biagini, J. M., Martin, L. J., Rothenberg, M. E., Hershey, G. K. K., & Baye, T. M. (2024) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2024.100350 · Cited by 6
“71,72 Hence, there is an urgent need to increase representation of diverse ancestry in genomic research and to conduct ancestry-specific assessment of pathogenic variants.”
Self-citationA translational framework of genoproteomic studies for cardiovascular drug discovery
Yang, Z., Zhao, J. V., Qi, Y., Deng, X., Ji, Z., & Liu, J. (2024) · npj Cardiovascular Health · doi:10.1038/s44325-024-00015-9 · Cited by 6
“…fi cally, we used publicly available GWAS summary-level statistics of LDL-C from the Global Lipids Genetics Consortium (GCLC, 1,654,960 individuals) 83 , of CAD from the CARDIoGRAMplusC4D Consortium (60,801 cases and 123,504 controls) 84 , and the 29-year longitudinal data (5735 individuals) from…”
Self-citationNiu, Q., Zhang, T., Mao, R., Zhao, N., & Deng, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-69180-2 · Cited by 5
“To counteract potential biases arising from sample overlaps, we incorporated GWAS data from GLGC participants, deliberately excluding those from FinnGen (n = 1,177,987) or UKB (n = 842,660) when scrutinizing results from the FinnGen or UKB GWAS correspondingly.”
MethodInfluentialPCSK9 Inhibitors and the Risk of Vitiligo: A Mendelian Randomization Study
Kang, T.-J., Lee, S. Y., Yoon, S., Kim, E. G., Kim, J. O., Kim, J. S., Park, J., & Nam, K. (2024) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2024.07.021 · Cited by 5
Self-citationPolygenic risk of high LDL cholesterol and ischemic heart disease in the general population.
Eyrich, T. M., Dalila, N., Christoffersen, M., Tybjærg-Hansen, A., & Stender, S. (2024) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2024.118574 · Cited by 5
Aherrahrou, N., Tairi, H., & Aherrahrou, Z. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae356 · Cited by 7
Zhou, J., Zhu, D., Xu, Y., Chen, C., & Wang, K. (2024) · BMC Gastroenterology · doi:10.1186/s12876-024-03246-3 · Cited by 5
“Genome-wide association studies (GWAS) have transformed our comprehension of the genetic variations influencing lipid levels [10, 11].”
BackgroundXu, Z., & Wei, P. (2024) · PLoS Genetics · doi:10.1371/journal.pgen.1011483 · Cited by 1
“…an acceptable coverage probability when the number of studies is relatively large, for example, larger than 10, which holds for most large-scale genomic consortia, such as the TOPMed program with over 85 studies and The Global Lipids Genetics Consortium with over 200 studies (Graham et al., 2021).”
Evaluation of Bayesian Linear Regression models for gene set prioritization in complex diseases
Gholipourshahraki, T., Bai, Z., Shrestha, M., Hjelholt, A. J., Hu, S., Kjølby, M., Rohde, P. D., & Sørensen, P. (2024) · PLoS Genetics · doi:10.1371/journal.pgen.1011463 · Cited by 8
Discovery and Exploration of Lipid-Modifying Drug Targets for ALS by Mendelian Randomization
Jiang, Z., Gu, X., Su, W., Duan, Q., Yin, K., Ren, Y., Wang, Y., Cao, B., & Chen, Y. (2024) · Molecular Neurobiology · doi:10.1007/s12035-024-04007-9 · Cited by 5
“Summary statistics for triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL) were from Europeans and East Asians [24], while apoprotein B (ApoB) and apoprotein A1 (ApoA1) were only available in Europeans [25].”
Self-citationNovel functions of Tribbles-homolog 1 in liver, adipocytes and atherosclerosis
Hernandez-Resendiz, I., & Burkhardt, R. (2024) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000917 · Cited by 5
Chung, R., Chuang, S., Zhuang, Y., Jhang, Y.-S., Huang, T.-H., Li, G.-H., Chang, I., Hsiung, C. A., & Chiou, H. (2023) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2023.100260 · Cited by 3
“12 More importantly, these studies have demonstrated that trans-ethnic analyses, which combine association signals across different ancestries, can improve the power for identifying novel loci.”
BackgroundMethodNguyen, J., Arthur, T. D., Fujita, K., Salgado, B. M., Donovan, M. K. R., Aguiar, L. R., Arias, A. D., Benaglio, P., Berggren, W. T., Belmonte, J. C. I., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42560-4 · Cited by 17
Self-citationWu, T., Ye, L., Wang, S.-L., Huang, J., & Zhang, J. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1258018 · Cited by 5
Self-citationNguyen, J., Arthur, T. D., Fujita, K., Salgado, B. M., Donovan, M. K. R., Matsui, H., Kim, J. H., D'Antonio-Chronowska, A., D'Antonio, M., & Frazer, K. (2023) · bioRxiv · doi:10.1101/2021.03.17.435846 · Cited by 5
Missense variants in SORT1 are associated with LDL-C in an Amish population
Mitok, K. A., Schueler, K. L., King, S. M., Orr, J., Ryan, K. A., Keller, M. P., Krauss, R. M., Mitchell, B. D., Shuldiner, A. R., & Attie, A. (2023) · Journal of Lipid Research · doi:10.1016/j.jlr.2023.100468 · Cited by 5
“We looked for any association between the rs141749679 (K302E) or rs149456022 (Q225H) variants and lipids in the most recent lipid GWAS, from the Global Lipids Genetics Consortium (30).”
BackgroundSelf-citationChen, Y., Liaw, Y.-C., Nfor, O. N., Hsiao, C.-H., Zhong, J.-H., Wu, S., & Liaw, Y. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1235840 · Cited by 9
“…studies highlight the importance and benefits of involving diverse and multi-ethnic populations in genetic studies (Popejoy and Fullerton, 2016; Graham et al., 2021) including a more accurate representation of the risks of genetically associated diseases in different populations (Sirugo et…”
Self-citationIdentification and analysis of individuals who deviate from their genetically-predicted phenotype
Hawkes, G., Yengo, L., Vedantam, S., Marouli, E., Beaumont, R., Tyrrell, J., Weedon, M., Hirschhorn, J., Frayling, T., & Wood, A. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010934 · Cited by 5
Self-citationGenes, environment, and African ancestry in cardiometabolic disorders
Doumatey, A. P., Bentley, A. R., Akinyemi, R., Olanrewaju, T. O., Adeyemo, A., & Rotimi, C. N. (2023) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2023.07.007 · Cited by 9
Self-citationHuang, X., & Zhao, J. V. (2023) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2023.08.011 · Cited by 6
Self-citationLillo, A. D., Wendt, F. R., Pathak, G. A., & Polimanti, R. A. (2023) · Human Genomics · doi:10.1186/s40246-023-00514-3 · Cited by 4
Gobeil, É., Bourgault, J., Mitchell, P. L., Houessou, U., Gagnon, É., Girard, A. S., Paulin, A., Manikpurage, H. D., Couture, C., Marceau, S., et al. (2023) · medRxiv · doi:10.1101/2023.05.29.23290580 · Cited by 3
Self-citationLiu, K., Wang, S., Zhou, Y., Huang, S., Liu, Y., Song, L., & He, Z. (2023) · European journal of medical research · doi:10.1186/s40001-023-01116-4 · Cited by 8
“For Europeans, the GWAS of blood lipid traits and glucose traits were retrieved from the Global Lipids Genetics Consortium (GLGC) [21] and the MAGIC (the Meta-Analyses of Glucose and Insulinrelated traits Consortium) [22, 23], respectively (Table 1).”
MethodKwak, J., Hong, G., Lee, K. J., Kim, C., & Shin, D. (2023) · Nutrients · doi:10.3390/nu15092066 · Cited by 6
“In a previous study, LPL rs17482753 and blood lipid levels were investigated in populations including East Asians [22], but differences in sex and age were not investigated.”
BackgroundInfluentialChen, L., Fan, Z., Zhao, Y., Yang, H., & Lv, G. (2023) · Journal of Hepatology · doi:10.1016/j.jhep.2022.12.024 · Cited by 6
From Soldier's Heart to Shared Genetic Risk: PTSD and Cardiovascular Disease.
Ursano, R., & Stein, M. (2022) · American Journal of Psychiatry · doi:10.1176/appi.ajp.20220778 · Cited by 5
Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification
Ryu, J., Barkal, S., Yu, T., Jankowiak, M., Zhou, Y., Francoeur, M., Phan, Q. V., Li, Z., Tognon, M., Brown, L., et al. (2023) · doi:10.1101/2023.09.08.23295253 · Cited by 32
Self-citationHwang, L., Lin, C., Evans, D. M., Martin, N. G., Reed, D. R., & Joseph, P. V. (2026) · BMC Medicine · doi:10.1186/s12916-026-04966-x · Cited by 4
“…including systolic blood pressure, diastolic blood pressure [50], high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total lipid cholesterol [51], fasting glucose, fasting insulin, hemoglobin A1C [52], BMI [22], coronary artery disease [23], and type 2 diabetes [53].”
Self-citationChu, X., Biao, Y., Li, H., Chen, J., Yin, J., Gao, X., Wang, S.-L., Ma, J., Yi, L., Zhang, Y., et al. (2025) · Lipids in Health and Disease · doi:10.1186/s12944-025-02782-5 · Cited by 4
“For exposures, eight serum lipid traits were analyzed using datasets from the IEU Open GWAS platform (ApoA1, ApoB, remnant cholesterol, Lp(a); n = 393,193–439,214) and the Global Lipids Genetics Consortium (TC, TG, LDL-C, HDL-C) [21].”
Self-citationWhole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals
Selvaraj, M. S., Li, X., Li, Z., Buren, E. V., Haidermota, S., Postupaka, D., Hornsby, W., Bis, J. C., Brody, J. A., Cade, B. E., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03698-0 · Cited by 2
“Prior analyses in diverse individuals have identified common variants and rare variant aggregates that are associated with lipids [6–8].”
InfluentialSelf-citationNicholas, J., Alkis, T., Bis, J., Boerwinkle, E., Brody, J., Clish, C., de Vries, P. D., Gao, Y., Gerzsten, R. E., Guo, X.-Q., et al. (2025) · medRxiv · doi:10.1101/2025.08.06.25333064 · Cited by 4
“…beta ( FGB ) rare variant, rs6054 (allele frequency 0.004), which was robustly associated with fibrinogen levels in prior genome-wide association studies (GWAS)(9), also associates with lipid levels in other GWAS(36), implicating that some lipid-fibrinogen relationships may have genetic origins.”
InfluentialSelf-citationThe Role of Polygenic Risk Score in the General Population: Current Status and Future Prospects
Takase, M., & Hozawa, A. (2025) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.rv22039 · Cited by 4
Xu, Q., Liang, X.-Y., Shi, W., & Zhang, H.-F. (2025) · International Urology and Nephrology · doi:10.1007/s11255-025-04594-z · Cited by 4
“The GWAS data for uric acid and outcomes are detailed in Supplementary Table 1 [13–18].”
Wei, A., Border, R., Fu, B., Cullina, S., Brandes, N., Jang, S.-K., Sankararaman, S., Kenny, E. E., Udler, M. S., Ntranos, V., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-60339-7 · Cited by 4
Legault, M., Hartford, J., Arsenault, B. J., Yang, A. Y., & Pineau, J. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.04.010 · Cited by 7
Genome-Wide Assessment of Pleiotropy Across >1000 Traits from Global BiobanksPreprint
Levin, M. G., Koyama, S., Woerner, J., Zhang, D. Y., Rodriguez, A., Nandi, T., Truong, B. M. T., Abramowitz, S. A., Gupta, H., Kamineni, H., et al. (2025) · medRxiv · doi:10.1101/2025.04.18.25326074 · Cited by 6
“6,28,29 The identification of previously undiscovered associations, particularly those specific to non-European populations, underscores the importance of diverse population representation in genomic research.”
Self-citationGagnon, É., Gill, D., Chabot, D., Cronjé, H. T., Yuan, S., Brennan, S., Thériault, S., Burgess, S., Arsenault, B. J., & Dib, M. (2025) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.124.004933 · Cited by 10
“In line with the transparency and openness promotion guidelines, Genome wide association studies (GWAS) summary statistics were all retrieved from the public domain in publications listed in Table S1.”
LRP5 promotes adipose progenitor cell fitness and adipocyte insulin sensitivity
Loh, N. Y., Vasan, S. K., Rosoff, D. B., Roberts, E., van Dam, A. D., Verma, M., Phillips, D., Wesolowska‐Andersen, A., Neville, M. J., Noordam, R., et al. (2025) · Communications Medicine · doi:10.1038/s43856-025-00774-1 · Cited by 8
“…hip circumference (WCadjBMI, HIPadjBMI) 26 ), MRI-derived visceral, abdominal subcutaneous, and gluteofemoral WAT volumes, adjusted for BMI and height (vatadjbmi3, asatadjbmi3, gfatadjbmi3) 27 , and glycemic (BMI-adjusted fasting glucose and insulin 28 ) and lipid 29 traits (Supplementary Table 2).”
Self-citationLeveraging large-scale biobanks for therapeutic target discovery
Ferolito, B. R., Dashti, H., Giambartolomei, C., Peloso, G. M., Golden, D. J., Gravel-Pucillo, K., Rasooly, D., Horimoto, A. R. V. R., Matty, R., Gaziano, L., et al. (2025) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2025.100556 · Cited by 8
“Previous GWAS hits were obtained from Graham et al. 51 (Tables S3, S5, and S18).”
Self-citation
Metadata
- Authors
- Graham, S. E., Clarke, S. L., Wu, K.-H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., Locke, A. E., Marouli, E., Hwang, M. Y., Han, S., Narita, A., Choudhury, A., Bentley, A. R., Ekoru, K., Verma, A., Trivedi, B., Martin, H. C., Hunt, K. A., Hui, Q., Klarin, D., Zhu, X., Thorleifsson, G., Helgadottir, A., Gudbjartsson, D. F., Holm, H., Olafsson, I., Akiyama, M., Sakaue, S., Terao, C., Kanai, M., Zhou, W., Brumpton, B. M., Rasheed, H., Ruotsalainen, S. E., Havulinna, A. S., Veturi, Y., Feng, Q., Rosenthal, E. A., Lingren, T., Pacheco, J. A., Pendergrass, S. A., Haessler, J., Giulianini, F., Bradford, Y., Miller, J. E., Campbell, A., Lin, K., Millwood, I. Y., Hindy, G., Rasheed, A., Faul, J. D., Zhao, W., Weir, D. R., Turman, C., Huang, H., Graff, M., Mahajan, A., Brown, M. R., Zhang, W., Yu, K., Schmidt, E. M., Pandit, A., Gustafsson, S., Yin, X., Luan, J., Zhao, J.-H., Matsuda, F., Jang, H.-M., Yoon, K., Medina-Gomez, C., Pitsillides, A., Hottenga, J. J., Willemsen, G., Wood, A. R., Ji, Y., Gao, Z., Haworth, S., Mitchell, R. E., Chai, J. F., Aadahl, M., Yao, J., Manichaikul, A., Warren, H. R., Ramirez, J., Bork-Jensen, J., Kårhus, L. L., Goel, A., Sabater-Lleal, M., Noordam, R., Sidore, C., Fiorillo, E., McDaid, A. F., Marques-Vidal, P., Wielscher, M., Trompet, S., Sattar, N., Møllehave, L. T., Thuesen, B. H., Munz, M., Zeng, L., Huang, J., Yang, B., Poveda, A., Kurbasic, A., Lamina, C., Forer, L., Scholz, M., Galesloot, T. E., Bradfield, J. P., Daw, E. W., Zmuda, J. M., Mitchell, J. S., Fuchsberger, C., Christensen, H., Brody, J. A., Feitosa, M. F., Wojczynski, M. K., Preuss, M., Mangino, M., Christofidou, P., Verweij, N., Benjamins, J. W., Engmann, J., Kember, R. L., Slieker, R. C., Lo, K. S., Zilhao, N. R., Le, P., Kleber, M. E., Delgado, G. E., Huo, S., Ikeda, D. D., Iha, H., Yang, J., Liu, J., Leonard, H. L., Marten, J., Schmidt, B., Arendt, M., Smyth, L. J., Cañadas-Garre, M., Wang, C., Nakatochi, M., Wong, A., Hutri-Kähönen, N., Sim, X., Xia, R., Huerta-Chagoya, A., Fernandez-Lopez, J. C., Lyssenko, V., Ahmed, M., Jackson, A. U., Yousri, N. A., Irvin, M. R., Oldmeadow, C., Kim, H.-N., Ryu, S., Timmers, P. R. H. J., Arbeeva, L., Dorajoo, R., Lange, L. A., Chai, X., Prasad, G., Lorés-Motta, L., Pauper, M., Long, J., Li, X., Theusch, E., Takeuchi, F., Spracklen, C. N., Loukola, A., Bollepalli, S., Warner, S. C., Wang, Y. X., Wei, W. B., Nutile, T., Ruggiero, D., Sung, Y. J., Hung, Y.-J., Chen, S., Liu, F., Yang, J., Kentistou, K. A., Gorski, M., Brumat, M., Meidtner, K., Bielak, L. F., Smith, J. A., Hebbar, P., Farmaki, A.-E., Hofer, E., Lin, M., Xue, C., Zhang, J., Concas, M. P., Vaccargiu, S., van der Most, P. J., Pitkänen, N., Cade, B. E., Lee, J., van der Laan, S. W., Chitrala, K. N., Weiss, S., Zimmermann, M. E., Lee, J. Y., Choi, H. S., Nethander, M., Freitag-Wolf, S., Southam, L., Rayner, N. W., Wang, C. A., Lin, S.-Y., Wang, J.-S., Couture, C., Lyytikäinen, L.-P., Nikus, K., Cuellar-Partida, G., Vestergaard, H., Hildalgo, B., Giannakopoulou, O., Cai, Q., Obura, M. O., van Setten, J., Li, X., Schwander, K., Terzikhan, N., Shin, J. H., Jackson, R. D., Reiner, A. P., Martin, L. W., Chen, Z., Li, L., Highland, H. M., Young, K. L., Kawaguchi, T., Thiery, J., Bis, J. C., Nadkarni, G. N., Launer, L. J., Li, H., Nalls, M. A., Raitakari, O. T., Ichihara, S., Wild, S. H., Nelson, C. P., Campbell, H., Jäger, S., Nabika, T., Al-Mulla, F., Niinikoski, H., Braund, P. S., Kolcic, I., Kovacs, P., Giardoglou, T., Katsuya, T., Bhatti, K. F., de Kleijn, D., de Borst, G. J., Kim, E. K., Adams, H. H. H., Ikram, M. A., Zhu, X., Asselbergs, F. W., Kraaijeveld, A. O., Beulens, J. W. J., Shu, X.-O., Rallidis, L. S., Pedersen, O., Hansen, T., Mitchell, P., Hewitt, A. W., Kähönen, M., Pérusse, L., Bouchard, C., Tönjes, A., Chen, Y.-D. I., Pennell, C. E., Mori, T. A., Lieb, W., Franke, A., Ohlsson, C., Mellström, D., Cho, Y. S., Lee, H., Yuan, J.-M., Koh, W.-P., Rhee, S. Y., Woo, J.-T., Heid, I. M., Stark, K. J., Völzke, H., Homuth, G., Evans, M. K., Zonderman, A. B., Polasek, O., Pasterkamp, G., Hoefer, I. E., Redline, S., Pahkala, K., Oldehinkel, A. J., Snieder, H., Biino, G., Schmidt, R., Schmidt, H., Chen, Y. E., Bandinelli, S., Dedoussis, G., Thanaraj, T. A., Kardia, S. L. R., Kato, N., Schulze, M. B., Girotto, G., Jung, B., Böger, C. A., Joshi, P. K., Bennett, D. A., De Jager, P. L., Lu, X., Mamakou, V., Brown, M., Caulfield, M. J., Munroe, P. B., Guo, X., Ciullo, M., Jonas, J. B., Samani, N. J., Kaprio, J., Pajukanta, P., Adair, L. S., Bechayda, S. A., de Silva, H. J., Wickremasinghe, A. R., Krauss, R. M., Wu, J.-Y., Zheng, W., den Hollander, A. I., Bharadwaj, D., Correa, A., Wilson, J. G., Lind, L., Heng, C.-K., Nelson, A. E., Golightly, Y. M., Wilson, J. F., Penninx, B., Kim, H.-L., Attia, J., Scott, R. J., Rao, D. C., Arnett, D. K., Hunt, S. C., Walker, M., Koistinen, H. A., Chandak, G. R., Yajnik, C. S., Mercader, J. M., Tusié-Luna, T., Aguilar-Salinas, C. A., Villalpando, C. G., Orozco, L., Fornage, M., Tai, E. S., van Dam, R. M., Lehtimäki, T., Chaturvedi, N., Yokota, M., Liu, J., Reilly, D. F., McKnight, A. J., Kee, F., Jöckel, K.-H., McCarthy, M. I., Palmer, C. N. A., Vitart, V., Hayward, C., Simonsick, E., van Duijn, C. M., Lu, F., Qu, J., Hishigaki, H., Lin, X., März, W., Parra, E. J., Cruz, M., Gudnason, V., Tardif, J.-C., Lettre, G., ’t Hart, L. M., Elders, P. J. M., Damrauer, S. M., Kumari, M., Kivimaki, M., van der Harst, P., Spector, T. D., Loos, R. J. F., Province, M. A., Psaty, B. M., Brandslund, I., Pramstaller, P. P., Christensen, K., Ripatti, S., Widén, E., Hakonarson, H., Grant, S. F. A., Kiemeney, L. A. L. M., de Graaf, J., Loeffler, M., Kronenberg, F., Gu, D., Erdmann, J., Schunkert, H., Franks, P. W., Linneberg, A., Jukema, J. W., Khera, A. V., Männikkö, M., Jarvelin, M.-R., Kutalik, Z., Cucca, F., Mook-Kanamori, D. O., van Dijk, K. W., Watkins, H., Strachan, D. P., Grarup, N., Sever, P., Poulter, N., Rotter, J. I., Dantoft, T. M., Karpe, F., Neville, M. J., Timpson, N. J., Cheng, C.-Y., Wong, T.-Y., Khor, C. C., Sabanayagam, C., Peters, A., Gieger, C., Hattersley, A. T., Pedersen, N. L., Magnusson, P. K. E., Boomsma, D. I., de Geus, E. J. C., Cupples, L. A., van Meurs, J. B. J., Ghanbari, M., Gordon-Larsen, P., Huang, W., Kim, Y. J., Tabara, Y., Wareham, N. J., Langenberg, C., Zeggini, E., Kuusisto, J., Laakso, M., Ingelsson, E., Abecasis, G., Chambers, J. C., Kooner, J. S., de Vries, P. S., Morrison, A. C., North, K. E., Daviglus, M., Kraft, P., Martin, N. G., Whitfield, J. B., Abbas, S., Saleheen, D., Walters, R. G., Holmes, M. V., Black, C., Smith, B. H., Justice, A. E., Baras, A., Buring, J. E., Ridker, P. M., Chasman, D. I., Kooperberg, C., Wei, W.-Q., Jarvik, G. P., Namjou, B., Hayes, M. G., Ritchie, M. D., Jousilahti, P., Salomaa, V., Hveem, K., Åsvold, B. O., Kubo, M., Kamatani, Y., Okada, Y., Murakami, Y., Thorsteinsdottir, U., Stefansson, K., Ho, Y.-L., Lynch, J. A., Rader, D. J., Tsao, P. S., Chang, K.-M., Cho, K., O’Donnell, C. J., Gaziano, J. M., Wilson, P., Rotimi, C. N., Hazelhurst, S., Ramsay, M., Trembath, R. C., van Heel, D. A., Tamiya, G., Yamamoto, M., Kim, B.-J., Mohlke, K. L., Frayling, T. M., Hirschhorn, J. N., Kathiresan, S., Program, V. M. V., Global Lipids Genetics Consortium*, Boehnke, M., Natarajan, P., Peloso, G. M., Brown, C. D., Morris, A. P., Assimes, T. L., Deloukas, P., Sun, Y. V., & Willer, C. J.
- Affiliations
- University of Michigan (US)
- VA Palo Alto Health Care System (US)
- Queen Mary University of London (GB)
- University of Pennsylvania (US)
- Broad Institute (US)
- University of Regensburg (DE)
- Washington University in St. Louis (US)
- Korea National Institute of Health (KR)
- Tohoku University (JP)
- University of the Witwatersrand (ZA)
- National Institutes of Health (US)
- Wellcome Sanger Institute (GB)
- Emory University (US)
- Pennsylvania State University (US)
- deCODE Genetics (Iceland) (IS)
- National University Hospital of Iceland (IS)
- Kyushu University (JP)
- RIKEN Center for Integrative Medical Sciences (JP)
- Norwegian University of Science and Technology (NO)
- University of Helsinki (FI)
- Vanderbilt University Medical Center (US)
- University of Washington (US)
- Cincinnati Children's Hospital Medical Center (US)
- Northwestern University (US)
- Genentech (US)
- Fred Hutch Cancer Center (US)
- Brigham and Women's Hospital (US)
- Western General Hospital (GB)
- University of Oxford (GB)
- Qatar University (QA)
- Center for Non-Communicable Diseases (PK)
- Harvard University (US)
- University of North Carolina at Chapel Hill (US)
- Centre for Human Genetics (GB)
- Imperial College Healthcare NHS Trust (GB)
- Uppsala University (SE)
- University of Cambridge (GB)
- Kyoto University (JP)
- Boston University (US)
- Amsterdam Public Health (NL)
- Vrije Universiteit Amsterdam (NL)
- University of Exeter (GB)
- Nanjing University of Chinese Medicine (CN)
- University of Bristol (GB)
- National University of Singapore (SG)
- Frederiksberg Hospital (DK)
- The Lundquist Institute (US)
- University of Virginia (US)
- Leiden University Medical Center (NL)
- Institute of Genetic and Biomedical Research (IT)
- SIB Swiss Institute of Bioinformatics (CH)
- Centre Hospitalier Universitaire Vaudois (CH)
- MRC Centre for Environment and Health (GB)
- University of Glasgow (GB)
- Humboldt-Universität zu Berlin (DE)
- German Centre for Cardiovascular Research (DE)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Lund University (SE)
- Innsbruck Medical University (AT)
- Leipzig University (DE)
- Radboud University Medical Center (NL)
- Quantinuum (United States) (US)
- University of Pittsburgh (US)
- Eurac Research (IT)
- Vejle Sygehus (DK)
- Icahn School of Medicine at Mount Sinai (US)
- King's College London (GB)
- University Medical Center Groningen (NL)
- University College London (GB)
- Montreal Heart Institute (CA)
- University of Toronto (CA)
- Heidelberg University (DE)
- Shanghai Institute of Nutrition and Health (CN)
- Rush University Medical Center (US)
- Agency for Science, Technology and Research (SG)
- University of Duisburg-Essen (DE)
- Dortmund University of Applied Sciences and Arts (DE)
- Queen's University Belfast (GB)
- Nagoya University (JP)
- MRC Unit for Lifelong Health and Ageing (GB)
- Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases (US)
- Centre for Cellular and Molecular Biology (IN)
- Weill Cornell Medical College in Qatar (QA)
- University of Alabama at Birmingham (US)
- Hunter Medical Research Institute (AU)
- Ewha Womans University (KR)
- Kangbuk Samsung Hospital (KR)
- University of Colorado Anschutz (US)
- Institute of Genomics and Integrative Biology (IN)
- Radboud University Nijmegen (NL)
- University of California, San Francisco (US)
- National Center for Global Health and Medicine (JP)
- University of Leicester (GB)
- Beijing Tongren Hospital (CN)
- Institute of Genetics and Biophysics (IT)
- Istituto Neurologico Mediterraneo (IT)
- Tri-Service General Hospital Songshan Branch (TW)
- University of Edinburgh (GB)
- University Hospital Regensburg (DE)
- University of Trieste (IT)
- German Center for Diabetes Research (DE)
- Dasman Diabetes Institute (KW)
- Harokopio University of Athens (GR)
- Medical University of Graz (AT)
- University of North Carolina at Charlotte (US)
- IRCCS Materno Infantile Burlo Garofolo (IT)
- University of Turku (FI)
- Utrecht University (NL)
- Universitätsmedizin Greifswald (DE)
- Hallym University (KR)
- University of Gothenburg (SE)
- Christian-Albrechts-Universität zu Kiel (DE)
- Taichung Veterans General Hospital (TW)
- Université Laval (CA)
- Tampere University (FI)
- University of Copenhagen (DK)
- Erasmus MC (NL)
- The Ohio State University (US)
- George Washington University (US)
- Peking University (CN)
- University Hospital Leipzig (DE)
- Jichi Medical University (JP)
- Shimane University (JP)
- The University of Osaka (JP)
- Yonsei University (KR)
- University Medical Center Utrecht (NL)
- National and Kapodistrian University of Athens (GR)
- The University of Sydney (AU)
- University of Tasmania (AU)
- Pennington Biomedical Research Center (US)
- University of Newcastle Australia (AU)
- The University of Western Australia (AU)
- Sahlgrenska University Hospital (SE)
- Kyung Hee University (KR)
- Istituto di Genetica Molecolare (IT)
- University of Potsdam (DE)
- University of California, Los Angeles (US)
- University of San Carlos (PH)
- University of Kelaniya (LK)
- Institute of Biomedical Sciences, Academia Sinica (TW)
- Jawaharlal Nehru University (IN)
- University of Mississippi Medical Center (US)
- Amsterdam University Medical Centers (NL)
- University of Kentucky (US)
- Newcastle University (GB)
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (MX)
- National Institute of Genomic Medicine (MX)
- Kurume University (JP)
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- University of Dundee (GB)
- National Institute on Aging (US)
- Wenzhou Medical University (CN)
- Mexican Social Security Institute (MX)
- University of Iceland (IS)
- Philadelphia VA Medical Center (US)
- Kaiser Permanente Washington Health Research Institute (US)
- University of Southern Denmark (DK)
- Children's Hospital of Philadelphia (US)
- University of Oulu (FI)
- University of Sassari (IT)
- St George's, University of London (GB)
- Imperial College London (GB)
- Churchill Hospital (GB)
- Singapore National Eye Center (SG)
- Helmholtz Munich (DE)
- Karolinska Institutet (SE)
- Mashhad University of Medical Sciences (IR)
- Chinese National Human Genome Center at Shanghai (CN)
- University of Eastern Finland (FI)
- The University of Texas Health Science Center at Houston (US)
- University of Illinois Chicago (US)
- QIMR Berghofer Medical Research Institute (AU)
- Columbia University Irving Medical Center (US)
- National Institute for Health and Care Research (GB)
- University of Aberdeen (GB)
- Geisinger Health System (US)
- Regeneron (United States) (US)
- University of Washington Medical Center (US)
- Finnish Institute for Health and Welfare (FI)
- Institute of Medical Science, The University of Tokyo (JP)
- VA Boston Healthcare System (US)
- University of Massachusetts Boston (US)
- National Health Laboratory Service (ZA)
- University of Manchester (GB)
- King Abdulaziz University (SA)
- Corresponding author
- Sun, Yan V.
- ORCID
- Graham, Sarah E.
- Clarke, Shoa L.
- Wu, Kuan-Han H.
- Kanoni, Stavroula
- Zajac, Greg J. M.
- Ramdas, Shweta
- Surakka, Ida
- Vedantam, Sailaja
- Winkler, Thomas W.
- Locke, Adam E.
- Marouli, Eirini
- Hwang, Mi Yeong
- Han, Sohee
- Narita, Akira
- Choudhury, Ananyo
- Bentley, Amy R.
- Ekoru, Kenneth
- Verma, Anurag
- Martin, Hilary C.
- Hunt, Karen A.
- Hui, Qin
- Klarin, Derek
- Zhu, Xiang
- Gudbjartsson, Daniel F.
- Holm, Hilma
- Akiyama, Masato
- Sakaue, Saori
- Terao, Chikashi
- Kanai, Masahiro
- Zhou, Wei
- Brumpton, Ben M.
- Rasheed, Humaira
- Ruotsalainen, Sanni E.
- Havulinna, Aki S.
- Veturi, Yogasudha
- Feng, QiPing
- Rosenthal, Elisabeth A.
- Lingren, Todd
- Pacheco, Jennifer Allen
- Pendergrass, Sarah A.
- Miller, Jason E.
- Campbell, Archie
- Millwood, Iona Y.
- Hindy, George
- Faul, Jessica D.
- Zhao, Wei
- Weir, David R.
- Turman, Constance
- Huang, Hongyan
- Graff, Mariaelisa
- Mahajan, Anubha
- Zhang, Weihua
- Yu, Ketian
- Schmidt, Ellen M.
- Pandit, Anita
- Gustafsson, Stefan
- Yin, Xianyong
- Luan, Jian’an
- Matsuda, Fumihiko
- Jang, Hye-Mi
- Yoon, Kyungheon
- Medina-Gomez, Carolina
- Pitsillides, Achilleas
- Hottenga, Jouke Jan
- Willemsen, Gonneke
- Wood, Andrew R.
- Gao, Zishan
- Haworth, Simon
- Mitchell, Ruth E.
- Chai, Jin Fang
- Aadahl, Mette
- Manichaikul, Ani
- Warren, Helen R.
- Ramirez, Julia
- Kårhus, Line L.
- Goel, Anuj
- Sabater-Lleal, Maria
- Noordam, Raymond
- Sidore, Carlo
- Fiorillo, Edoardo
- McDaid, Aaron F.
- Marques-Vidal, Pedro
- Wielscher, Matthias
- Trompet, Stella
- Sattar, Naveed
- Møllehave, Line T.
- Thuesen, Betina H.
- Munz, Matthias
- Zeng, Lingyao
- Huang, Jianfeng
- Yang, Bin
- Poveda, Alaitz
- Kurbasic, Azra
- Lamina, Claudia
- Forer, Lukas
- Scholz, Markus
- Galesloot, Tessel E.
- Zmuda, Joseph M.
- Fuchsberger, Christian
- Brody, Jennifer A.
- Feitosa, Mary F.
- Wojczynski, Mary K.
- Preuss, Michael
- Mangino, Massimo
- Christofidou, Paraskevi
- Verweij, Niek
- Benjamins, Jan W.
- Engmann, Jorgen
- Kember, Rachel L.
- Slieker, Roderick C.
- Lo, Ken Sin
- Zilhao, Nuno R.
- Le, Phuong
- Kleber, Marcus E.
- Delgado, Graciela E.
- Huo, Shaofeng
- Ikeda, Daisuke D.
- Iha, Hiroyuki
- Yang, Jian
- Liu, Jun
- Leonard, Hampton L.
- Marten, Jonathan
- Schmidt, Börge
- Smyth, Laura J.
- Wang, Chaolong
- Nakatochi, Masahiro
- Wong, Andrew
- Sim, Xueling
- Xia, Rui
- Fernandez-Lopez, Juan Carlos
- Lyssenko, Valeriya
- Jackson, Anne U.
- Yousri, Noha A.
- Irvin, Marguerite R.
- Oldmeadow, Christopher
- Ryu, Seungho
- Timmers, Paul R. H. J.
- Arbeeva, Liubov
- Dorajoo, Rajkumar
- Chai, Xiaoran
- Prasad, Gauri
- Pauper, Marc
- Long, Jirong
- Li, Xiaohui
- Theusch, Elizabeth
- Takeuchi, Fumihiko
- Spracklen, Cassandra N.
- Loukola, Anu
- Bollepalli, Sailalitha
- Warner, Sophie C.
- Wang, Ya Xing
- Wei, Wen B.
- Nutile, Teresa
- Ruggiero, Daniela
- Hung, Yi-Jen
- Chen, Shufeng
- Liu, Fangchao
- Yang, Jingyun
- Kentistou, Katherine A.
- Gorski, Mathias
- Brumat, Marco
- Meidtner, Karina
- Bielak, Lawrence F.
- Smith, Jennifer A.
- Hebbar, Prashantha
- Farmaki, Aliki-Eleni
- Hofer, Edith
- Lin, Maoxuan
- Xue, Chao
- Zhang, Jifeng
- Concas, Maria Pina
- Vaccargiu, Simona
- van der Most, Peter J.
- Pitkänen, Niina
- Cade, Brian E.
- Lee, Jiwon
- van der Laan, Sander W.
- Chitrala, Kumaraswamy Naidu
- Weiss, Stefan
- Zimmermann, Martina E.
- Lee, Jong Young
- Nethander, Maria
- Southam, Lorraine
- Rayner, Nigel W.
- Wang, Carol A.
- Wang, Jun-Sing
- Lyytikäinen, Leo-Pekka
- Nikus, Kjell
- Cuellar-Partida, Gabriel
- Vestergaard, Henrik
- Giannakopoulou, Olga
- Cai, Qiuyin
- van Setten, Jessica
- Schwander, Karen
- Jackson, Rebecca D.
- Reiner, Alexander P.
- Martin, Lisa Warsinger
- Chen, Zhengming
- Li, Liming
- Highland, Heather M.
- Young, Kristin L.
- Kawaguchi, Takahisa
- Thiery, Joachim
- Bis, Joshua C.
- Nadkarni, Girish N.
- Launer, Lenore J.
- Nalls, Mike A.
- Raitakari, Olli T.
- Ichihara, Sahoko
- Wild, Sarah H.
- Nelson, Christopher P.
- Jäger, Susanne
- Nabika, Toru
- Braund, Peter S.
- Kovacs, Peter
- de Kleijn, Dominique
- de Borst, Gert J.
- Kim, Eung Kweon
- Adams, Hieab H. H.
- Ikram, M. Arfan
- Zhu, Xiaofeng
- Asselbergs, Folkert W.
- Kraaijeveld, Adriaan O.
- Beulens, Joline W. J.
- Shu, Xiao-Ou
- Pedersen, Oluf
- Hansen, Torben
- Hewitt, Alex W.
- Kähönen, Mika
- Pérusse, Louis
- Bouchard, Claude
- Tönjes, Anke
- Chen, Yii-Der Ida
- Pennell, Craig E.
- Mori, Trevor A.
- Lieb, Wolfgang
- Ohlsson, Claes
- Mellström, Dan
- Cho, Yoon Shin
- Lee, Hyejin
- Koh, Woon-Puay
- Rhee, Sang Youl
- Woo, Jeong-Taek
- Heid, Iris M.
- Stark, Klaus J.
- Homuth, Georg
- Evans, Michele K.
- Zonderman, Alan B.
- Pasterkamp, Gerard
- Hoefer, Imo E.
- Redline, Susan
- Pahkala, Katja
- Oldehinkel, Albertine J.
- Snieder, Harold
- Biino, Ginevra
- Schmidt, Reinhold
- Schmidt, Helena
- Chen, Y. Eugene
- Bandinelli, Stefania
- Dedoussis, George
- Thanaraj, Thangavel Alphonse
- Kato, Norihiro
- Schulze, Matthias B.
- Girotto, Giorgia
- Joshi, Peter K.
- Bennett, David A.
- De Jager, Philip L.
- Lu, Xiangfeng
- Mamakou, Vasiliki
- Brown, Morris
- Caulfield, Mark J.
- Munroe, Patricia B.
- Guo, Xiuqing
- Ciullo, Marina
- Jonas, Jost B.
- Samani, Nilesh J.
- Kaprio, Jaakko
- Pajukanta, Päivi
- Adair, Linda S.
- de Silva, H. Janaka
- Krauss, Ronald M.
- Zheng, Wei
- den Hollander, Anneke I.
- Bharadwaj, Dwaipayan
- Correa, Adolfo
- Wilson, James G.
- Lind, Lars
- Heng, Chew-Kiat
- Nelson, Amanda E.
- Golightly, Yvonne M.
- Wilson, James F.
- Penninx, Brenda
- Kim, Hyung-Lae
- Attia, John
- Scott, Rodney J.
- Rao, D. C.
- Arnett, Donna K.
- Hunt, Steven C.
- Koistinen, Heikki A.
- Chandak, Giriraj R.
- Yajnik, Chittaranjan S.
- Mercader, Josep M.
- Aguilar-Salinas, Carlos A.
- Orozco, Lorena
- Fornage, Myriam
- Tai, E. Shyong
- van Dam, Rob M.
- Lehtimäki, Terho
- Chaturvedi, Nish
- Liu, Jianjun
- Reilly, Dermot F.
- McKnight, Amy Jayne
- Kee, Frank
- Jöckel, Karl-Heinz
- McCarthy, Mark I.
- Hayward, Caroline
- Simonsick, Eleanor
- van Duijn, Cornelia M.
- Qu, Jia
- März, Winfried
- Parra, Esteban J.
- Cruz, Miguel
- Gudnason, Vilmundur
- Tardif, Jean-Claude
- Lettre, Guillaume
- Elders, Petra J. M.
- Damrauer, Scott M.
- Kivimaki, Mika
- van der Harst, Pim
- Spector, Tim D.
- Loos, Ruth J. F.
- Province, Michael A.
- Psaty, Bruce M.
- Brandslund, Ivan
- Pramstaller, Peter P.
- Christensen, Kaare
- Ripatti, Samuli
- Widén, Elisabeth
- Hakonarson, Hakon
- Grant, Struan F. A.
- Kiemeney, Lambertus A. L. M.
- Loeffler, Markus
- Kronenberg, Florian
- Gu, Dongfeng
- Erdmann, Jeanette
- Schunkert, Heribert
- Franks, Paul W.
- Linneberg, Allan
- Jukema, J. Wouter
- Khera, Amit V.
- Männikkö, Minna
- Cucca, Francesco
- van Dijk, Ko Willems
- Watkins, Hugh
- Strachan, David P.
- Grarup, Niels
- Poulter, Neil
- Rotter, Jerome I.
- Dantoft, Thomas M.
- Karpe, Fredrik
- Neville, Matt J.
- Timpson, Nicholas J.
- Cheng, Ching-Yu
- Wong, Tien-Yin
- Khor, Chiea Chuen
- Sabanayagam, Charumathi
- Peters, Annette
- Gieger, Christian
- Hattersley, Andrew T.
- Pedersen, Nancy L.
- Magnusson, Patrik K. E.
- Boomsma, Dorret I.
- de Geus, Eco J. C.
- Cupples, L. Adrienne
- van Meurs, Joyce B. J.
- Ghanbari, Mohsen
- Gordon-Larsen, Penny
- Huang, Wei
- Kim, Young Jin
- Wareham, Nicholas J.
- Langenberg, Claudia
- Zeggini, Eleftheria
- Kuusisto, Johanna
- Laakso, Markku
- Ingelsson, Erik
- Chambers, John C.
- Kooner, Jaspal S.
- de Vries, Paul S.
- Morrison, Alanna C.
- North, Kari E.
- Daviglus, Martha
- Kraft, Peter
- Martin, Nicholas G.
- Whitfield, John B.
- Saleheen, Danish
- Walters, Robin G.
- Holmes, Michael V.
- Black, Corri
- Smith, Blair H.
- Justice, Anne E.
- Baras, Aris
- Buring, Julie E.
- Ridker, Paul M.
- Chasman, Daniel I.
- Kooperberg, Charles
- Wei, Wei-Qi
- Jarvik, Gail P.
- Namjou, Bahram
- Hayes, M. Geoffrey
- Ritchie, Marylyn D.
- Jousilahti, Pekka
- Salomaa, Veikko
- Hveem, Kristian
- Åsvold, Bjørn Olav
- Kubo, Michiaki
- Okada, Yukinori
- Murakami, Yoshinori
- Ho, Yuk-Lam
- Lynch, Julie A.
- Rader, Daniel J.
- Tsao, Philip S.
- Chang, Kyong-Mi
- Cho, Kelly
- O’Donnell, Christopher J.
- Gaziano, John M.
- Wilson, Peter
- Rotimi, Charles N.
- Hazelhurst, Scott
- Ramsay, Michèle
- Trembath, Richard C.
- van Heel, David A.
- Tamiya, Gen
- Yamamoto, Masayuki
- Kim, Bong-Jo
- Mohlke, Karen L.
- Frayling, Timothy M.
- Hirschhorn, Joel N.
- Kathiresan, Sekar
- Boehnke, Michael
- Natarajan, Pradeep
- Peloso, Gina M.
- Brown, Christopher D.
- Morris, Andrew P.
- Assimes, Themistocles L.
- Deloukas, Panos
- Sun, Yan V.
- Willer, Cristen J.
- Venue
- Nature
- Published
- 2021-12-09
- Volume
- 600
- Issue
- 7890
- Pages
- 675-679
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC8730582
- OpenAlex
- W3205644245
- Cited by
- 972
- References
- 77
- Citations by year
- 2026: 164 · 2025: 246 · 2024: 274 · 2023: 192 · 2022: 89 · 2021: 6
- FWCI
- 21.98
- Type
- journal article
- Language
- en
- Update notices
- correction (2023-05-26)
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- UWA Profiles and Research Repository (UWA) (publishedVersion, other-oa)
- University of Southern Denmark Research Portal (University of Southern Denmark) (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, other-oa)
- VU Research Portal (publishedVersion, other-oa)
- SERVAL (Université de Lausanne) (publishedVersion, cc-by-nc)
- PubMed Central (acceptedVersion)
- Discovery Research Portal (University of Dundee) (acceptedVersion, other-oa)
- St George's Online Research Archive (St George's University of London) (acceptedVersion)
- Open Research Exeter (University of Exeter) (acceptedVersion)
- Open Access at Essex (University of Essex) (acceptedVersion)
- ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) (submittedVersion, other-oa)
- Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by-nc-nd)
- IRIS (submittedVersion, cc-by-nc)
- Explore Bristol Research (submittedVersion, other-oa)
- UTAS Research Repository (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- DR-NTU (Nanyang Technological University) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- University of Regensburg Publication Server (University of Regensburg) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Figshare (submittedVersion)
- YUHSpace (Yonsei University Medical Library) (submittedVersion, cc-by-nc-nd)
- UnissResearch (Università degli Studi di Sassari) (submittedVersion)
- CNR ExploRA (submittedVersion)
- publish.UP (University of Potsdam) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Research Portal (Queen's University Belfast) (submittedVersion, other-oa)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- Qatar University QSpace (Qatar University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Open Research (University of Surrey) (submittedVersion, cc-by)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- U.S. Department of Veterans Affairs (IK2-CX001780, I01-BX004821, I01-BX003362)
- McKnight Foundation
- Office of Research and Development
- Wellcome Trust (212946/Z/18/Z, 212945/Z/18/Z, 210561/Z/18/Z, 217065/Z/19/Z, 202802/Z/16/Z, 221854/Z/20/Z)
- Barts Charity (MGU0284)
- Cancer Research UK (16896)
- National Institute for Health and Care Research (NF-SI-0611-10170, NF-SI-0512-10113, NIHR-INF-0987, 16/136/102, NF-SI-0617-10154)
- British Heart Foundation (FS/19/62/34901D, RG/14/5/30893)
- Public Health Agency (STL/5569/19)
- Lundbeckfonden (R155-2013-14070)
- Novo Nordisk Fonden (NNF14OC0010513, NNF19OC0055250, NNF18OC0033898, NNF13OC0005785)
- National Institutes of Health (5k01hl135405-04, 24460, 85,86)
- Medical Research Council (MR/S019669/1, MC_PC_14135, MC_UU_00017/1, MR/S011676/1, MR/R024227/1, MC_PC_15018, MC_PC_20026, MC_PC_19009, MC_UU_00007/10, MC_PC_13049)
- Economic and Social Research Council (ES/N00812X/1, ES/L008459/1)
- Japan Society for the Promotion of Science (21H03206, 21K10439, 19K19434, 21H04850)
- National Institute on Aging (R01AG017917, R01AG015819, P30AG010161)
- National Heart, Lung, and Blood Institute (R01HL133218, R01HL127564, R03HL154284, K01-HL135405, R35HL135818, R01HL149683, R35HL135824, R01HL105756, R01HL109946, R01HL153805)
- National Human Genome Research Institute (K08HG010155, R01HG010297, T32HG000040, U01HG011723)
- National Cancer Institute (R01CA144034, R01CA080205, UM1CA182876)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK072193, U01DK062370, P30DK020572, R01DK093757, P30DK020541, R01DK062370)
- National Center for Chronic Disease Prevention and Health Promotion (U01DP006266)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD030880)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- serum lipids, genetic diversity, non-European ancestry, polygenic risk score, fine mapping, cardiovascular risk, LDL cholesterol, triglycerides, HDL cholesterol, genetic ancestry, sample size and statistical power, linkage disequilibrium
- MeSH terms
- Cardiovascular Diseases, Humans, Linkage Disequilibrium, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Population Groups, Genome-Wide Association Study
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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