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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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Carter, P., Gozdecka, M., Wen, S., Quirós, P. M., Lockhart, S. M., Dudek, M., Bond, L., Richenberg, G., Larsson, S. C., Bromage, D. I., et al. (2026) · medRxiv · doi:10.64898/2026.07.08.26357595
“Although the association between inherited genetic variation at HMGCR and LDL-C is also observed in other ancestries 28,57 , it remains to be seen whether our findings can be generalized to other ancestral groups globally.”
Self-citationPolygenic Prediction of Non-goal Response to Statin Therapy
Liou, L., García‐González, J., Wu, H. M., Namba, S., Vaura, F. C., Okada, Y., Kovacic, J. C., & O’Reilly, P. F. (2026) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.125.005666
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Shan, N., Qiu, Y., Hou, L., & Wang, Z. (2026) · Genes · doi:10.3390/genes17070840
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InfluentialBarad, A., Ritter, V., Nudy, M., Horn, L. V., Allison, M., Spracklen, C. N., Liu, L., Jung, S. Y., Manson, J. E., Assimes, T. L., et al. (2026) · medRxiv · doi:10.64898/2026.06.29.26356854
“26 The distribution of saturated fat intake and correlations between macronutrients (expressed as % of total daily calories), AHEI, and PGS LDL in the pooled cohort are shown in Supplementary Figure 2 .”
Self-citationMIXPRS enables multi-population and multi-method polygenic risk scores using summary statistics
Xu, L., Dong, Y., Zeng, X., Bian, Z., Zhou, G., Guan, L., & Zhao, H. (2026) · Nature Genetics · doi:10.1038/s41588-026-02637-4 · Cited by 2
“We compiled GWAS summary statistics for all available traits in each population, including 26 traits in EUR, 26 in EAS, 11 in AFR, four in SAS and four in AMR, from multiple consortia 5–9, 11, 13, 59– 68 .”
Murrin, O., Voller, B., Woodward, R. M., Carrasco-Ribelles, L. A., Türkmen, D., Gu, Q., Boddy, K., Farmer, L., Mancini, M., Khalid, S., et al. (2026) · Respiratory Research · doi:10.1186/s12931-026-03726-y
“…published GWAS from leading consortia for ten potential risk factors: BMI [18], waist-hip ratio [19], cholesterol (LDL, HDL, triglycerides) [20], educational attainment [21], smoking status (ever smoked, and separately smoking intensity in smokers) [22], alcohol consumption [22], and PA…”
Self-citationSmith, J. L., Norland, K., Hamed, M. E., Yu, Y., Na, J., Dikilitas, O., Schaid, D. J., & Kullo, I. J. (2026) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.125.005382
Self-citationZheng, L., Xie, S., Zhou, Z., Wu, J., Wang, H., Wang, K., Yu, H., Gong, H., Qin, X., Wu, T., et al. (2026) · Communications Biology · doi:10.1038/s42003-026-10425-3
Self-citationTranslating Lipoprotein Genetics Into New Therapies
Hegele, R. A. (2026) · Circulation Research · doi:10.1161/circresaha.126.328828 · Cited by 1
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Self-citationHan, X., Wang, F., & Wang, G. (2026) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2026.1780649
“The UK NIHR Biomedical Research Centre has built a inherited cardiac disease database combining sequence and phenotype data from over 8,000 patients and families to aid variant interpretation and family screening (96).”
Genetic perspectives on the comorbidity of anxiety and mood disorders with cardiovascular disease
de Geus, E. J. C., Treur, J. L., & Penninx, B. W. J. H. (2026) · Nature Cardiovascular Research · doi:10.1038/s44161-026-00822-6 · Cited by 1
Self-citationZhang, P., Wang, H., Lin, M.-H., Dai, P., Zhong, Q., Wang, R.-T., Sheng, L., He, Z., & Nan, Z. (2026) · Medicine · doi:10.1097/md.0000000000049077
“[9,10] To mitigate potential bias from sample overlap, analyses utilizing outcomes from FinnGen were conducted using data that excluded Finnish participants (n = 345,506; Table 1).”
Self-citationUncovering Novel Atrial Fibrillation Genetics Through Pleiotropic Overlap with Life’s Essential 8
Wu, J., Qin, X. Y., Shuting, X., Zheng, L. G., Yu, H., Wang, H., Chen, Y., Li, T., Wu, T., Chen, D., et al. (2026) · Biomedicines · doi:10.3390/biomedicines14061179
Self-citationGenetic array data from the Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA)
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“GWAS analysis of the NICOLA dataset has contributed to an international GWAS examining human height[9], an international multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels[10], [11], [12] and two GWAS examining age-related macular degeneration[13], [14].”
Self-citationZhu, Y., Ru, Y., Xie, J., Zuo, T., Hong, X.-J., & Wang, D.-M. (2026) · Health Information Science and Systems · doi:10.1007/s13755-026-00437-y
Sinkala, M., Elsheikh, S. S. M., Mbiyavanga, M., Cullinan, J., & Mulder, N. (2026) · Communications Biology · doi:10.1038/s42003-026-09977-1 · Cited by 2
“In conclusion, our fi ndings add to the growing body of literature describing the complexity and diversity of the genetic underpinnings of cardiovascular traits across different populations 85 – 87 .”
Advancing predictive preventive personalized medicine for African health equity
Bajinka, O., Jallow, L., Bah, A., Cheng, Z.-W., Yu, W.-B., Li, N., & Zhan, X.-Q. (2026) · Scientific African · doi:10.1016/j.sciaf.2026.e03383
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“…to calculate ADHD-and ASD-PRS were derived from populations of European ancestry because no large-scale GWAS summary statistics from East Asian populations (including Japanese) with ADHD and ASD have been available to date, which may limit generalizability and potentially decrease robustness (78).”
Zhang, Z., He, Y., Zhao, W., Wei, R., Han, H., Zhan, Q., Yu, P., Li, S., Hou, X., Wang, J., et al. (2026) · Genetics Selection Evolution · doi:10.1186/s12711-026-01048-7
“To address this, increasing GWAS population diversity has been suggested as a method to reduce the impact of LD on fine mapping [6].”
Self-citationLu, W., Zhao, Z., Molina, D., Fan, H., Shi, R., Tian, Y., Gopoju, R., Yang, T., Zhang, X., Zhang, Y., et al. (2026) · Journal of Clinical Investigation · doi:10.1172/jci204602 · Cited by 1
“GWAS has identified that 1 of the SNPs (rs6682862, chr1:177969302, alleles: G>A) located in the promoter region of SEC16B is significantly associated with plasma cholesterol levels (Figure 1A) (20, 21).”
Shen, C., Adams, M., Davyson, E., Iveson, M., Cox, S. R., Harris, S. E., McIntosh, A., & Shen, X.-Y. (2026) · Clinical Epigenetics · doi:10.1186/s13148-026-02125-w
“NOC3L and PLCE1 are associated with low-density lipoprotein (LDL) cholesterol levels in the blood [50].”
Lee, Y. A., Zhang, Y., Dice, A. L. E., Li, J. H., Tubbs, J. D., Feng, Y. A., Ge, T., Maihofer, A. X., Nievergelt, C. M., Smoller, J. W., et al. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03553-z · Cited by 1
“We used the largest publicly available GWAS summary statistics for PTSD (this time including the MGB samples), cholesterol in HDL [21], cholesterol in VLDL [22], glucose [23], triglyceride [24], urea nitrogen [25], vitamin D [26], potassium [27], erythrocyte distribution width [28], mean platelet…”
Hu, X., Araújo, D. S., Khunsriraksakul, C., Wang, L., Sun, Q., Wen, J., Zhou, L., Ekunwe, L., Lange, L. A., Lange, E. M., et al. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2026.03.008 · Cited by 1
“8,9,49 Although our transcriptome prediction models were built on diverse ancestry populations, the overall sample size (i.e., 1,287 multi-ancestry participants) is not large enough to produce powerful multi-ancestry eQTLs and thus affects the accuracy of fine-mapping.”
Self-citationJin, Y., Topaloudi, A., Petros Drineas, B., & Paschou, P. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71411 · Cited by 1
“BEAN1 encodes a protein interacting with NEDD4 and has been implicated in protein degradation and lipid-related traits, 60 as well as cerebellar ataxias.”
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Self-citationEditorial: Proteomics in atherosclerosis
Yuan, X.-M., & Singh, S. A. (2026) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2026.1792281
PCSK9 and Breast Cancer Survival: A Mendelian Randomization Study
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“…downloaded both the female-specific and sex-combined GWAS summary statistics from the Global Lipids Genetics Consortium (GLGC; Europeans only, maximum sample size females ¼ 558,500; sex-combined ¼ 1,231,284), as published in Kanoni and colleagues (25) and Graham and colleagues (24), respectively.”
Genetic susceptibility of cardiometabolic outcomes in schizophrenia spectrum disorders.
Zhao, C.-X., Lin, B., Naderi, E., Moazzen, S., Habtewold, T., Bruggeman, R., van Amelsvoort, T., Cahn, W., de Haan, L., van der Pluijm, M., et al. (2026) · Schizophrenia Research · doi:10.1016/j.schres.2026.03.009
PCSK9 Inhibitors and Bipolar Disorder: A Drug Target Mendelian Randomization Study
Li, J., & Yao, P. (2026) · Clinical Neuropharmacology · doi:10.1097/wnf.0000000000000677
On the potential of group-specific component (GC) inhibition for treating metabolic disease
Gill, R. D., & Kuo, T. (2026) · Metabolism and Target Organ Damage · doi:10.20517/mtod.2025.195
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“…[18], Vanderbilt University Medical Center’s BioVU biobank [52], the UK Biobank Pharma Proteomics Project (UKB-PPP) [19], the Global Lipids Genetics Consortium (GLGC) [51], a large CAD GWAS meta-analysis [26], and the Drug-Gene Interaction Database [50] (DGIdb; see Supplementary Methods §1 ).”
Self-citationSong, Z.-Q., Pei, Y.-Z., Wu, S.-K., Chen, X.-X., & Chen, Y.-H. (2026) · NMCD. Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2026.104701
Self-citationPathway-Based Genetic Risk Scores Are Associated with Blood Lipids Among Young Mexican Adults
Esteves, B. A. H., Teran-Garcia, M., Andrade, F. C. D., Vázquez-Vidal, I., Vargas-Morales, J. M., & Aradillas-García, C. (2026) · Nutrients · doi:10.3390/nu18060979
Genome-wide fine-mapping improves identification of causal variants
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“…of GWFM with SBayesRC onto the prediction for a simulated trait (under sparse architecture), height 30,37 , HDL 30,38 , schizophrenia (SCZ) 39,40 and Crohn’s disease (CD) 30,41 , which represented diverse genetic architectures, using two datasets with different…”
Self-citationBioVault: A privacy-first data visitation platform for equitable global collaboration in biomedicinePreprint
Edupalli, M., Torok, T., Jay, M., Jordan, K., Abdirahman, Z., Frederick, D., Weldon, C., Dajani, R. B., & Chen, X. D. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.12.705603
“Cross-institutional aggregation of genomic, clinical, and molecular data enables the discovery of novel disease variants 4,5 , improves prediction performance of machine learning models 6 , and reveals disease mechanisms across populations 7 .”
Du, J., Horimoto, A. R. V. R., Best, L. G., Zhang, Y., Cole, S. A., Umans, J. G., Franceschini, N., & Sun, Q. (2026) · medRxiv · doi:10.64898/2026.02.08.26345859
Hwang, L., Lin, C.-L., Evans, D., Martin, N. G., Reed, D. R., & Joseph, P. V. (2026) · medRxiv · doi:10.64898/2026.02.05.26345702
“…summary results statistics, including systolic blood pressure, diastolic blood pressure 48 , high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total lipid cholesterol 49 , fasting glucose, fasting insulin 50 , BMI 22 , coronary artery disease 23 , and type 2 diabetes 51 .”
Self-citationWright, H. W., Darrous, L., Ferrat, L. A., Chundru, V. K., Kamoun, A., Ar, W., Wright, C. F., Patel, K., Frayling, T. M., Weedon, M. N., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.03.702791
“Previous studies, whose focus has been on common genetic variation, have used reference panels to establish statistical independence in multi-ancestry meta-analyses 1,7 .”
Self-citationLiu, D., Baranova, A. V., Sun, W., Cao, H., Zhang, B., Zhang, F., & Initiative, A. D. N. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-07756-4
“…lipid levels on AD, total cholesterol (TC), triglycerides (TG), HDL-C, LDL-C, and very-low-density lipoprotein cholesterol (VLDL-C) datapoints were incorporated using summary-level GWAS genetic data for these lipoproteins from studies conducted by Graham et al. [22] and Richardson et al. [23].”
Multi-ancestry conditional and joint analysis (Manc-COJO) applied to GWAS summary statisticsPreprint
Wang, X.-T., Wang, Y., Visscher, P., Wray, N., & Yengo, L. (2026) · bioRxiv · doi:10.64898/2026.01.30.702783
“Global Lipids Genetics Consortium (GLGC) GWAS summary statistics (which excluded UK biobank) were available for high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TC), and log-transformed triglyceride levels (logTG) 38 .”
Self-citationGolebiewski, A. K., Stolze, L. K., Vazquez, V. D., Yazdi, A. M., Careaga, C. M., & Romanoski, C. E. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2026.01.010 · Cited by 1
Feng, Y., Li, Y., Zhang, H., Xia, H., Lü, Y., Zhou, H., & Huang, P. (2026) · BMC Psychiatry · doi:10.1186/s12888-026-07816-5
Xu, H., Zou, M., Cheng, Y., & Ge, S. (2026) · Lipids · doi:10.1002/lipd.70032
“…Phase 3 reference panels for genotype imputation and employed linear mixed models to analyze five key lipid traits: total cholesterol, low-density li-poprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and non- high-density lipoprotein cholesterol (Graham et al. 2021).”
Penna, L. S., Amemiya, R. B., Núñez, I. A., Grefenhagen, Á. I. D. S., Flores, V. S., Oliveira, M. V. L., Almodobar, L., Mauer, J., Neto, F. A. S., Filho, R. D. L., et al. (2026) · Human Genetics · doi:10.1007/s00439-025-02811-4
“Regarding genetics, genome-wide association studies (GWAS) have improved our understanding of many complex phenotypes, including dyslipidemia (Kathiresan et al. 2008, 2009; Willer et al. 2008; Chasman et al. 2008; Aulchenko et al. 2009; Ma et al. 2010; Spracklen et al. 2017; Graham et al. 2021 ).”
InfluentialEast Asian Mendelian-Randomization Evidence Linking PCOS to Gestational Diabetes Mellitus
Du, J.-H., Xing, L.-W., Chen, Y., He, Z., Zhong, L.-P., & Zhao, R. (2026) · International Journal of Women's Health · doi:10.2147/ijwh.s559022
Self-citationYu, S.-Y., Wen, J., Gao, Y., Yang, Z.-Q., Wang, X., Lu, Y., Chu, J.-Y., Maimaitiyiming, D., & Xu, S.-H. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag041
An Exploratory Analysis of Essential Tremor and Associated Phenotypes
Gharibian, D., Medeiros, M., Dion, P. A., & Rouleau, G. A. (2026) · Tremor and Other Hyperkinetic Movements · doi:10.5334/tohm.1168
Seagle, H., Kim, J., Akerele, A. T., Hung, A. M., Hellwege, J., & Edwards, T. L. (2025) · Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · doi:10.1142/9789819824755_0048
Hu, Y., He, M., & Yu, C. (2025) · Archives of Dermatological Research · doi:10.1007/s00403-025-04449-8
“The genetic data for the 15 CVDs and 15 metabolic traits were sourced from multiple large-scale bio-banks and consortia, including FinnGen, UK Biobank [ 17], AFGen Consortium [ 18 ], MEGASTROKE [ 19 ], MAGIC [ 20], and GLGC [21].”
Co-expression-wide association studies link genetically regulated interactions with complex traits
Malakhov, M. M., & Pan, W. (2025) · Nature Communications · doi:10.1038/s41467-025-66039-6 · Cited by 2
“For LDL cholesterol levels, we downloaded GWAS summary statistics data from the Global Lipids Genetics Consortium (GLGC) 42 .”
InfluentialMetabolomic Signatures of Prediabetes in Mexican Americans: The Role of Genetics and Macronutrients
Chung, S., Evans, C. R., Burant, C., Chen, H., Yu, B., Aguilar, D. A., Brown, E. L., Hanis, C. L., & Jun, G. (2025) · Advanced Genetics · doi:10.1002/ggn2.202500032
Wang, S., Ojewunmi, O. O., Pirie, F., Motala, A., Ramsay, M., Morris, A., Fatumo, S., Chikowore, T., & Asimit, J. (2025) · bioRxiv · doi:10.1101/2025.11.26.690727
“Stop-gain variant rs28362286 is also only polymorphic in AFR (MAF=0.00798) and was also prioritised by the Global Lipids Genetics Consortium (GLGC) African ancestry analysis 41 , but not by the GLGC multi-ancestry analysis.”
InfluentialSelf-citationWeighted Burden Analysis of Rare Genetic Variants Identifies Novel Genes with Effects on BMI
Curtis, D. (2025) · Human Heredity · doi:10.1159/000549644 · Cited by 1
“GALNT9 codes for a brain-expressed polypeptide N -acetylgalactosaminyltransferase, and common variants in it have been reported to be associated with total cholesterol in humans and with abdominal fat in chickens [27–29].”
Tian, X., Fabiha, T., Li, W. F., Dey, K. K., Kellis, M., & Tanigawa, Y. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.13.688144 · Cited by 3
“Fifth, this initial application focuses on individuals of African ancestry in the UKB; future studies should expand the application to additional populations, leveraging resources from All of Us, MVP, and other emerging resources [10–12] .”
Admixture Mapping of Lipid Traits in Hispanic Americans
Ding, K., Johar, A., Zaidi, A. A., Crane, P. K., Edwards, D. R. V., Jarvik, G. P., Karlson, E. W., Rosenthal, E. A., Stanaway, I. B., Weng, C., et al. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.124.036650
Self-citationLyu, Q., Wang, X.-Y., Chen, E., Sun, C., Qiu, Z., Xie, Y., & He, P. (2025) · iScience · doi:10.1016/j.isci.2025.114129
Polygenic risks and cardiovascular treatment effects in severe mental illness
Yao, K., Burton, A., Heinkel, S., Osborn, D., Bass, N. J., & McQuillin, A. (2025) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000401
“We used GWAS summary statistics on European samples from the Global Lipids Genetics Consortium for total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides (Graham et al. , 2021).”
Sanikini, H., Mina, T. H., Tsilidis, K. K., The HELIOS Study Team, Ngeow, J. Y. Y., Lee, E. S., Lee, J., Elliott, P., Chambers, J. C., & Ríboli, E. (2025) · medRxiv · doi:10.1101/2025.10.10.25337779
“Additionally, to assess the direct effects of lipid traits on arterial stiffness, multivariable MR (MVMR) analyses were conducted using summary statistics from the GLGC 19 , with HDL-C, LDL-C and triglycerides included in the model.”
Self-citationMohandes, S., Hirohama, D., Ha, E., Dumoulin, B., Pan, S., Bergeson, A., Abedini, A., Nguyen, T., McAllister, F. E., & Suszták, K. (2025) · medRxiv · doi:10.1101/2025.10.02.25337157
“…to extrarenal cardiac and metabolic traits, we utilized publicly available GWAS summary statistics for Coronary Artery Disease 67 ,Heart Failure 68 , Systolic and Diastolic blood pressure 69 , Lipids to include HDL, LDL and Triglycerides 70 , obesity 71 , Type 1 72 and Type 2 73 diabetes mellitus.”
Wu, X.-J., Zhang, X., Xu, W., She, C., Li, L., Mao, Y.-T., & Wang, S.-D. (2025) · European Journal of Medical Research · doi:10.1186/s40001-025-03206-x
“In addition, genome-wide association studies (GWAS) have significantly changed researchers’ understanding of the genetic variants that affect lipid levels [17, 18].”
Self-citationShinoda, G., Obara, T., Takahashi, I., Ohseto, H., Kawaguchi, C., Narita, A., Noda, A., Murakami, K., Orui, M., Ishikuro, M., et al. (2025) · Genes Brain & Behavior · doi:10.1111/gbb.70038 · Cited by 1
“It is significantly associated with total PHF-tau [48] levels and hypothyroidism [49], which are associated with the pathology of cognitive decline.”
Self-citationDaria, T., Iyer, K. R., Alkhairo, H., Kho, P. F., Ken, S., Hatzikotoulas, K., Southam, L., Taylor, H. J., Yin, X., Mandla, R., et al. (2025) · JACC Basic to Translational Science · doi:10.1016/j.jacbts.2025.101390 · Cited by 2
Self-citationPersonalized polygenic risk prediction and assessment with a Mixture-of-Experts frameworkPreprint
Zabad, S., Li, Y., & Gravel, S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.15.676165
“Recent analyses from the Global Lipids Genetics Consortium (GLGC) have shown that these phenotypes are moderately heritable, somewhat polygenic, and influenced by many large effect variants, some of which are [11].”
InfluentialFrüh, D., Imtiaz, M., Estrada, S., Shahid, M., Aziz, N. A., & Breteler, M. (2025) · medRxiv · doi:10.1101/2025.09.09.25335402
“…with vascular risk factors (i.e., waist-to-hip ratio 45 , BMI 45 , alcohol consumption, SBP 46 , DBP 46 , high-density lipoprotein (HDL) cholesterol 47 , low-density lipoprotein (LDL) cholesterol 48 , type 2 diabetes 49 and plasminogen activator inhibitor-1 (PAI-1) 50 ), as well as…”
Do PCSK9 Inhibitors Impair Memory? A Dual Approach Combining Real-World Data and Genetic Evidence
Shi, X., Wang, S., Yang, Y., Xia, X., Fan, J., Wang, J., Wang, N., & Jia, X. (2025) · Pharmacy · doi:10.3390/pharmacy13050125
“Given the clear clinical efficacy of PCSK9 inhibitors in reducing LDL-C levels, single nucleotide polymorphisms (SNPs) associated with LDL-C were utilized as instrumental variables (IVs) sourced from the Global Lipids Genetics Consortium (GLGC) [19].”
Self-citationLuo, M., Lin, J., Zhuo, Q., Lin, L., & Han, Y. (2025) · Health Science Reports · doi:10.1002/hsr2.71040
Yang, J., Zhang, X., Zhang, H., Guo, X., Ren, F., & Dong, C. (2025) · International Journal of Women s Health · doi:10.2147/ijwh.s552619 · Cited by 1
Self-citationLiang, Y., Mo, J., Huang, A., Zhang, X., Wang, K., Hu, Y., Pei, Q., Huang, X., Peng, J., He, J., et al. (2025) · Surgical Endoscopy · doi:10.1007/s00464-025-12118-0
Bolier, M., Pluimakers, V. G., Broer, L., Neggers, S. J. C. M. M., de Winter, D. T. C., Wang, F., Baedke, J. L., Uitterlinden, A. G., Petrykey, K., Kremer, L. C. M., et al. (2025) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-25-0338
“…large childhood cancer survivor cohorts, providing a relatively high number of participants for this specific research field, the sample size remains relatively low compared with the general population cohorts that have explored the ge-netic susceptibility of dyslipidemia (14–18, 45, 47).”
Petrenya, N., Hopstock, L., Hadler-Olsen, E., Asa'ad, F., Larsson, L., Zykova, S. N., Holde, G. E., Vieira, A. R., & Jönsson, B. (2025) · Acta Odontologica Scandinavica · doi:10.2340/aos.v84.44368
“ANRIL polymorphism in intron 3 rs1537373 has been previously linked to three comorbidities of periodontitis [19–21], that is lipid levels [22, 23], artery calcification [24], and pancreatic cancer [25].”
Xu, L.-Q., Zheng, W.-J., Hu, J.-Q., Lin, Y., Zhao, J., Wang, G.-F., Liu, T.-Y., & Zhao, H.-Y. (2025) · bioRxiv · doi:10.1101/2025.08.05.668705
“…selected to represent major disease domains, biomarkers, and behavioral factors with broad relevance to human health [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63] (Supplementary Table 1), using LDSC [64].”
Self-citationAberra, Y. T., Yang, Q., Cowan, A., Gediksiz, B. Y., Thomas, M., Gragirenes‐Delgado, D., Keita, F., & Civelek, M. (2025) · Physiological Reports · doi:10.14814/phy2.70513
“GWAS have identified hundreds of genetic loci associated with MetSyn traits (Aragam et al., 2022; Chen et al., 2021; Graham et al., 2021; Pulit et al., 2019; Suzuki et al., 2024; Tcheandjieu et al., 2022).”
Bentley, A. R., Brown, M. R., Musani, S. K., Schwander, K., Winkler, T. W., Sims, M., Kilpeläinen, T. O., Aschard, H., Bartz, T. M., Bielak, L. F., et al. (2025) · Translational Psychiatry · doi:10.1038/s41398-025-03418-z
“The novelty of associated loci was determined by comparison to the recent Global Lipids Genetic Consortium results for GWAS meta-analyses including approximately 1.65 million individuals with notable inclusion of those of diverse ancestral backgrounds [1].”
InfluentialSelf-citationLeveraging genetic correlations to prioritize drug groups for repurposing in type 2 diabetes
Hjelholt, A. J., Gholipourshahraki, T., Bai, Z., Shrestha, M., Kjølby, M., Sørensen, P., & Rohde, P. D. (2025) · The Pharmacogenomics Journal · doi:10.1038/s41397-025-00392-z · Cited by 1
“These include T2D [12], coronary artery disease (CAD) [26], chronic kidney disease (CKD) [27], hypertension (HTN) [28], body mass index (BMI) [29], waist-hip ratio (WHR) [29], glycated haemoglobin (Hb1Ac) [27], systolic blood pressure (SBP) [30], and triglycerides (TG) [31].”
Association of dietary preferences with cardiovascular disease: a Mendelian randomization study
Lee, D., & Voight, B. F. (2025) · Atherosclerosis Plus · doi:10.1016/j.athplu.2025.04.002 · Cited by 1
“…prior and literature-based observations and selected the following risk factors as potential mediators: body mass index (BMI) [40], low-density lipoprotein (LDL) [41], triglycerides (TG) [41], diastolic blood pressure (DBP) [42] and educational attainment (EA, Supplementary Table 2) [43].”
Garza, A. L., Blangero, J., Lee, M., Bauer, C., Czerwinski, S. A., & Choh, A. C. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26104812
“…with HDL-C levels in a Chinese twin-study, [12] and the Rab GTPase-binding effector protein-1 ( RABEP1 ) gene that has been found to be associated with lipid and adiposity biomarkers, specifically the following: non-HDL cholesterol, TG and total cholesterol levels, [13] BMI, [14], and BF% [15].”
Impact of lipid-lowering drug targets on genetic associations with diabetic retinopathy
Zhang, X., Fan, K.-L., & Li, J. (2025) · Archives of medical science : AMS · doi:10.5114/aoms/199622
“Genetic association data for lipid biomarkers were obtained from the Global Lipids Genetics Consortium, which represents the largest genome-wide association study (GWAS) meta-analysis to date, encompassing approximately 1.5 million people of European heritage [22].”
InfluentialInvestigating the genetic factors of medication dosing using biobank-linked drug purchase data
Kasela, S., Luitva, L. B., Krebs, K., Estonian biobank research team, MoÌls, M., Milani, L., & Alver, M. (2025) · medRxiv · doi:10.1101/2025.04.01.25325019
“, HDL-cholesterol (HDL-C) 52 , triglycerides (TG) 52 , and systolic blood pressure (SBP) 53 .”
Functional interrogation of candidate cis-regulatory elements at the LDLR locus
Leix, K., Serrano-Zayas, C., Vyas, H., Graham, S. E., & Emmer, B. T. (2026) · PLoS Genetics · doi:10.1371/journal.pgen.1012082 · Cited by 1
Self-citationGilchrist, L., Pain, O., Marriott, H., Pfaff, A. L., Watson, C. J., Iacoangeli, A., Kõks, S., Lewis, C. M., & Proitsi, P. (2025) · medRxiv · doi:10.1101/2025.03.20.25324166
“Although this is a multi-ancestry GWAS, PRS generated from multi-ancestry base datasets show equivalent or better performance in European target samples 53,54 .”
Xiao, J., Li, J., Wu, X., Yu, H., Zhao, X., Zhang, W., Xu, B., Ma, T., Zhang, L., Xiang, R., et al. (2025) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2025.03.027
Self-citationGenetically-Determined Low-density Lipoprotein in Ischemic Stroke SurvivorsPreprint
Wu, K., Huo, S., Rivier, C., Torres-Lopez, V. M., Sharma, R., de Havenon, A., Worrall, B., Sheth, K., & Falcone, G. (2025) · medRxiv · doi:10.1101/2025.02.26.25322908
Self-citationWang, R., Sun, J., & Yu, X. (2025) · Scientific Reports · doi:10.1038/s41598-024-85070-z
Insights Into Modifiable Risk Factors of Vertigo Using the Mendelian Randomization Approach
Guo, X.-Z., Hou, C., Tang, P., Zhang, X., Gou, N., Chong, L. T., Liu, P., & Li, R. (2025) · Acta Neurologica Scandinavica · doi:10.1155/ane/8775816
“…(LDL-C), high-density lipoprotein-cholesterol (HDL-C), and total cholesterol from the Global Lipids Genetics Consortium (GLGC) [22]; gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), and alanine transaminase (ALT) for liver function [23]; interleukin-6 (IL-6),…”
Self-citationGenomic Landscape of Thrombosis Recurrence Risk Across Venous Thromboembolism SubtypesPreprint
Munsch, G., Thibord, F., Bezerra, O. C. D. L., Brody, J. A., Vlieg, A. V. H., Gourhant, L., Chen, M., Germain, M., Caro, I., Suchon, P., et al. (2024) · medRxiv · doi:10.1101/2024.12.02.24317788
“MR analysis with LDL cholesterol levels 69 on VT recurrence did not support a causal association (HR=0.97, P=0.59).”
InfluentialSelf-citationLalagkas, P. N., & Melamed, R. (2024) · Human Genomics · doi:10.1186/s40246-024-00688-4 · Cited by 5
Ruan, Y., Bhukar, R., Patel, A. P., Koyama, S., Hull, L. E., Truong, B., So, M., Hornsby, W., Zhang, H.-Y., Chatterjee, N., et al. (2024) · medRxiv · doi:10.1101/2024.11.09.24316996
Self-citationSmith, J., Norland, K., Hamed, M., Yu, Y., Na, J., Dikilitas, O., Schaid, D., & Kullo, I. (2024) · medRxiv · doi:10.1101/2024.11.05.24316750
Self-citationMichorowska, S., Vogel, K. R., Jain, R., Clair, S. L. S., Simcox, J., & Parks, B. W. (2024) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2024.151059 · Cited by 2
“1B and C) [7].”
Hutten, C. G., Boehm, F. J., Smith, J. A., Spitzer, B., Wassertheil-Smoller, S. W., Isasi, C. R., Cai, J., Unkart, J., Sun, J., Persky, V., et al. (2024) · medRxiv · doi:10.1101/2024.09.25.24313663
“The portability of PRS between populations has come into question due to differences in LD, allele frequencies, and genetic architecture (9,43); however, we hypothesized a more diverse sample of Hispanics/Latinos, such as HCHS/SOL, would provide a higher likelihood that the SNPs are in LD with a…”
BackgroundSelf-citationNoordam, R., Wang, W., Nagarajan, P., Wang, H., Brown, M. R., Bentley, A. R., Hui, Q., Kraja, A. T., Morrison, J. L., O’Connel, J. R., et al. (2024) · medRxiv · doi:10.1101/2024.09.02.24312466 · Cited by 1
Self-citationZaranek, S. W., Zaranek, A. W., Amstutz, P., Bao, J., Chen, J., Clegg, T., Craft, H., Jo, T., Lee, B., Nho, K. T., et al. (2024) · medRxiv · doi:10.1101/2024.08.01.24311329
“…et al. 2022b; Yan et al. 2021; Sinnott-Armstrong et al. 2021; Kunkle et al. 2021; Wang et al. 2020; Guo et al. 2019; Liu et al. 2018; Wojcik et al. 2019; Lo et al. 2019; Harper et al. 2022; Graham et al. 2021; Richardson et al. 2022; Yan et al. 2021; Park et al. 2021; Schwartzentruber et al. 2021).”
Self-citationTheusch, E., Ting, F., Qin, Y., Stevens, K., Naidoo, D., King, S. M., Yang, N. V., Orr, J., Han, Y., Cyster, J. G., et al. (2024) · Genome Medicine · doi:10.1186/s13073-024-01366-9 · Cited by 2
“Variants associated with blood HDL cholesterol, triglyceride, non-HDL cholesterol, and LDL cholesterol levels in GWAS are located in and near the ZNF335 gene [40].”
BackgroundSelf-citationChen, Y., Chen, W., Qian, J., Jin, X.-C., Wang, C.-Y., & Zheng, Y.-H. (2024) · medRxiv · doi:10.1101/2024.07.22.24310765
“To avoid potential sample overlap issues with the PUFAs data, we used a meta dataset with the UK Biobank cohort removed for this part of the study (Table 1) [16].”
MethodSelf-citationZhabin, S., Lazarenko, V. A., Azarova, Y., Bashkatov, D., Klyosova, E., Gneeva, E., Churnosov, M., & Polonikov, A. (2024) · Kardiologiia · doi:10.18087/cardio.2024.6.n2365
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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