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Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes
Open accessAbstract
IMPORTANCE: Low-density lipoprotein cholesterol (LDL-C) is causally related to coronary artery disease (CAD), but the relevance of high-density lipoprotein cholesterol (HDL-C) and triglycerides (TGs) is uncertain. Lowering of LDL-C levels by statin therapy modestly increases the risk of type 2 diabetes, but it is unknown whether this effect is specific to statins. OBJECTIVE: To investigate the associations of 3 routinely measured lipid fractions with CAD and diabetes through mendelian randomization (MR) using conventional MR and making use of newer approaches, such as multivariate MR and MR-Egger, that address the pleiotropy of genetic instruments where relevant. DESIGN, SETTING, AND PARTICIPANTS: Published data from genome-wide association studies were used to construct genetic instruments and then applied to investigate associations between lipid fractions and the risk of CAD and diabetes using MR approaches that took into account pleiotropy of genetic instruments. The study was conducted from March 12 to December 31, 2015. MAIN OUTCOMES AND MEASURES: Coronary artery disease and diabetes. RESULTS: Genetic instruments composed of 130 single-nucleotide polymorphisms (SNPs) were used for LDL-C (explaining 7.9% of its variance), 140 SNPs for HDL-C (6.6% of variance), and 140 SNPs for TGs (5.9% of variance). A 1-SD genetically instrumented elevation in LDL-C levels (equivalent to 38 mg/dL) and TG levels (equivalent to 89 mg/dL) was associated with higher CAD risk; odds ratios (ORs) were 1.68 (95% CI, 1.51-1.87) for LDL-C and 1.28 (95% CI, 1.13-1.45) for TGs. The corresponding OR for HDL-C (equivalent to a 16-mg/dL increase) was 0.95 (95% CI, 0.85-1.06). All 3 lipid traits were associated with a lower risk of type 2 diabetes. The ORs were 0.79 (95% CI, 0.71-0.88) for LDL-C and 0.83 (95% CI, 0.76-0.90) for HDL-C per 1-SD elevation. For TG, the MR estimates for diabetes were inconsistent, with MR-Egger giving an OR of 0.83 (95%CI, 0.72-0.95) per 1-SD elevation. CONCLUSIONS AND RELEVANCE: Routinely measured lipid fractions exhibit contrasting associations with the risk of CAD and diabetes. Increased LDL-C, HDL-C, and possibly TG levels are associated with a lower risk of diabetes. This information will be relevant to the design of clinical trials of lipid-modifying agents, which should carefully monitor participants for dysglycemia and the incidence of diabetes.
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“as pharmacological modification of C-reactive protein is unlikely to be beneficial to CHD 51 , whereas randomized evidence demonstrates the value of targeting biomarkers further upstream, e.g. interleukin-6 receptor 21,54 or interleukin 1-beta 52”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [21]
In the citing paper
“With increasing availability of large-scale phenotyping (and genotyping), MR is being widely applied to quantitative traits (e.g. markers or adiposity, such as body mass index 13-16 ; blood lipids such as HDL-cholesterol 17-19 ; inflammation-related proteins such as interleukin-6 receptor 20,21 12 ) with the aim of discovering modifiable risk factors for disease that are causal and amenable to the”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [21]
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“In this latter example, genetic variants used to mimic pharmacological inhibition of IL6R (and thus the effects of inhibiting pathways downstream of IL6) lead to a paradoxical increase in IL6 concentrations in the blood 21 ,”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [21]
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“Exploring inflammation-related proteins more upstream, genetic variants around the gene encoding interleukin 6 receptor (IL6R) shows an association with risk of CHD 21,54 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [21]
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Citations
Cites
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816
Cholesterol Treatment Trialists' (CTT) Collaboration (2010) · The Lancet · doi:10.1016/s0140-6736(10)61350-5 · Cited by 6,550
Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology
Lawlor, D. A., Harbord, R. M., Sterne, J. A. C., Timpson, N., & Davey Smith, G. (2008) · Statistics in Medicine · doi:10.1002/sim.3034 · Cited by 4,618
Ezetimibe Added to Statin Therapy after Acute Coronary Syndromes
Cannon, C. P., Blazing, M. A., Giugliano, R. P., McCagg, A., White, J. A., Theroux, P., Darius, H., Lewis, B. S., Ophuis, T. O., Jukema, J. W., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1410489 · Cited by 4,487
Self-citationWiller (2013) · doi:10.1038/ng.2797 · Cited by 2,983
Collaborators, C. T. T. (. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60367-5 · Cited by 2,833
Effects of dalcetrapib in patients with a recent acute coronary syndrome
Schwartz, G. G., Olsson, A. G., Abt, M., Ballantyne, C. M., Barter, P. J., Brumm, J., Chaitman, B. R., Holme, I. M., Kallend, D., Leiter, L. A., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1206797 · Cited by 2,022
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912
Calculating statistical power in Mendelian randomization studies.
Brion, M.-J. A., Shakhbazov, K., & Visscher, P. M. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dyt179 · Cited by 1,751
Large-scale association analysis identifies new risk loci for coronary artery disease
The CARDIoGRAMplusC4D Consortium, Deloukas, P., DIAGRAM Consortium, CARDIOGENICS Consortium, MuTHER Consortium, Wellcome Trust Case Control Consortium, Kanoni, S., Willenborg, C., Farrall, M., Assimes, T. L., et al. (2013) · Nature Genetics · doi:10.1038/ng.2480 · Cited by 1,614
Cited by
Sorted by citations
Items 201–296 of 296
Xie, X., Liao, J., Huang, C., Li, X., Cao, Q., Kong, L., Okamura, T., Hashimoto, Y., Obora, A., Kojima, T., et al. (2023) · International Journal of Medical Sciences · doi:10.7150/ijms.83371 · Cited by 8
“Interestingly, some previous studies also indicated of the protective effect of raised TG levels on type 2 diabetes mellitus [21-23].”
InfluentialPinal‐Fernandez, I., Casal-Domínguez, M., & Mammen, A. L. (2018) · Medicina Clínica (English Edition) · doi:10.1016/j.medcle.2018.03.001 · Cited by 8
Type 2 Diabetes and HDL Dysfunction: A Key Contributor to Glycemic Control
Rotllán, N., Julve, J., & Escolá‐Gil, J. C. (2023) · Current Medicinal Chemistry · doi:10.2174/0929867330666230201124125 · Cited by 8
Bowden, J., Burgess, S., & Smith, G. D. (2017) · JAMA Cardiology · doi:10.1001/jamacardio.2017.1572 · Cited by 8
Hypolipidemic Drugs and Diabetes Mellitus—Mechanisms and Data From Genetic Trials
Filippatos, T. D., Panagiotopoulou, T., Tzavella, E., & Elisaf, M. (2018) · Journal of Cardiovascular Pharmacology and Therapeutics · doi:10.1177/1074248418757011 · Cited by 8
Chen, S., Zhou, Z., Zhou, Z., Liu, Y., Sun, S., Huang, K., Yang, Q., & Guo, Y. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1307944 · Cited by 8
“As a result, research on MR applied to GWAS data has grown in popularity over the past few decades (28, 29).”
BackgroundZusi, C., Trombetta, M., Bonetti, S., Dauriz, M., Boselli, M. L., Trabetti, E., Malerba, G., Penno, G., Zoppini, G., Bonora, E., et al. (2018) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2018.08.013 · Cited by 7
Boutari, C., Rizos, C. V., Doumas, M. N., Liamis, G. L., Skoumas, I., Rallidis, L. S., Garoufi, A., Kolovou, G. D., Τζιόμαλος, Κ., Skalidis, E. I., et al. (2022) · Pharmaceuticals · doi:10.3390/ph16010044 · Cited by 7
“Analogous were the results of a study that examined the association between lipid profile and T2DM risk through mendelian randomization [15].”
ResultDifferential impact of glycation on apolipoprotein A-I of high-density lipoprotein: a review
Maarfi, F., Ahmad, S., Alouffi, S., Akasha, R., Khan, M. S., Rafi, Z., Basnet, H., & Khan, M. Y. (2023) · Glycobiology · doi:10.1093/glycob/cwad010 · Cited by 7
Assessing Cardiovascular Disease Risk and Responses to Preventive Therapies in Clinical Practice
Maki, K. C., & Dicklin, M. R. (2018) · Current Atherosclerosis Reports · doi:10.1007/s11883-018-0725-y · Cited by 7
Differences in HDL-related coronary heart disease risk between individuals with and without diabetes
Chen, J., Lu, Q., Geng, T., Wang, Y., Wang, Y., Li, R., Xia, P., Guo, K., Yang, K., Tong, W.-W., et al. (2024) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2024.118553 · Cited by 6
Unsupervised Learning-Derived Complex Metabolic Signatures Refine Cardiometabolic Risk
Zhou, Y., Xiang, B., Yang, X., Ren, Y., Gu, X., & Zhou, X. (2025) · JACC Advances · doi:10.1016/j.jacadv.2025.101620 · Cited by 6
Hashem, C., Altin, S. E., Guyton, J. R., & Boden, W. E. (2024) · Journal of clinical lipidology · doi:10.1016/j.jacl.2024.12.009 · Cited by 7
Lee, K., & Kim, J. (2020) · Alcohol and Alcoholism · doi:10.1093/alcalc/agaa051 · Cited by 6
Ni, X., Bai, C., Nie, C., Qi, L., Liu, Y., Yuan, H., Zhu, X., Sun, L., Zhou, Q., Li, Y., et al. (2021) · Aging · doi:10.18632/aging.203700 · Cited by 6
“Several observational studies have found that increases in TG levels are associated with an increase in the risk of morbidity and mortality related to aging-associated diseases [35, 36].”
BackgroundFunaki, D., Kaneda, H., Miyakoshi, A., Saito, K., Sasaki, H., & Nakatani, E. (2023) · PLoS ONE · doi:10.1371/journal.pone.0295052 · Cited by 6
Gordillo‐Marañón, M., Zwierzyna, M., Charoen, P., Drenos, F., Chopade, S., Shah, T., Engmann, J., Casas, J. P., Chaturvedi, N., Papacosta, O., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.11.377747 · Cited by 6
Self-citationBeazer, J., Sillars, A., Beck, S., Christoffersen, C., Ferraz, M. J., Mulder, M. T., Graham, D., Karlsson, H., Ljunggren, S., Gill, J. M. R., et al. (2024) · Bioscience Reports · doi:10.1042/bsr20241165 · Cited by 5
Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches
Wittemans, L. B. L., Lotta, L. A., & Langenberg, C. (2018) · Current Diabetes Reports · doi:10.1007/s11892-018-1009-1 · Cited by 7
Li, H.-Y., Ji, H.-Y., Maimaitituersun, G., Ma, Y.-T., & Fu, Z.-Y. (2023) · Medicine · doi:10.1097/md.0000000000033256 · Cited by 5
“This conclusion is similar to previous reports.[14] We also found that compared with SUA levels below quartiles, higher SUA levels gradually increased the risk factors for CAD.”
ResultSerum Progranulin As a Risk Predictor in Patients with Acute Myocardial Infarction
Zhou, T., Chen, Y., Zhang, S., Li, M., & Wang, J. (2020) · Medical Science Monitor · doi:10.12659/msm.928864 · Cited by 5
“In our study, we demonstrated that conventional cardiometabolic risk factors, including triglyceride and LDL-cholesterol levels, were higher, while cholesterol and HDL-cholesterol concentrations were lower, in patients with AMI compared to control subjects, which is consistent with other previous reports [14].”
ResultYin, L., Feng, Y., Lau, A., Qiu, J., Sham, P. C., & So, H. (2022) · medRxiv · doi:10.1101/2022.12.25.22283943 · Cited by 5
Zheng, W., Zhang, J., Huang, Y., Wang, S., Gao, X., Yang, Z., Zong, Y., & Yang, Z. (2024) · High Blood Pressure & Cardiovascular Prevention · doi:10.1007/s40292-024-00694-6 · Cited by 4
CETP Inhibitors: Back With a New Target
Nicholls, S. J., Ray, K. K., Nelson, A. J., & Kastelein, J. J. P. (2026) · Circulation Research · doi:10.1161/circresaha.125.327271 · Cited by 4
Savla, J. J., & Neeland, I. J. (2018) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-018-0566-9 · Cited by 4
Martín-Campos, J. M. (2021) · Biomedicines · doi:10.3390/biomedicines9111728 · Cited by 4
Pappa, E. T., Kostara, C. E., Bairaktari, E. T., Arvaniti, E., & Tsimihodimos, V. (2022) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2022.108286 · Cited by 4
Lin, Y.-C., Tu, H., & Wang, T. (2023) · Journal of Endocrinological Investigation · doi:10.1007/s40618-023-02209-x · Cited by 4
Fu, L., Liu, Q., Cheng, H., Zhao, X., Xiong, J., & Mi, J. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.124.038857 · Cited by 4
“Additionally, a breadth of evidence from observational, 77 genetic, 19,78 interventional 79 studies supports the causality of LDL-C in the pathogenesis of CHD. Recent genetic research further implicates triglycerides 80,81 as a causal factor in cardiometabolic diseases.”
Statin-Associated muscle symptoms and vitamin D supplementation
Fadah, K., Mares, A. C., & Lange, R. A. (2025) · Current Opinion in Cardiology · doi:10.1097/hco.0000000000001222 · Cited by 4
Li, Y., Adi, D., Wang, Y.-H., Wang, Y.-T., Li, X., Fu, Z.-Y., Liu, F., Aizezi, A., Abuzhalihan, J., Gai, M., et al. (2023) · PeerJ · doi:10.7717/peerj.15536 · Cited by 3
“, 2022)while a genetically-induced elevation of circulated LDL-C levels was associated with a lower risk of T2DM in individuals with European or Asian ancestry (Hsu et al., 2022; White et al., 2016).”
BackgroundPCSK9 inhibitors and diabetes mellitus
Vohnout, B., Lisičanová, J., & Havranová, A. (2018) · Vnitřní lékařství · doi:10.36290/vnl.2018.170 · Cited by 4
Zhang, N., Song, C., Ji, C., Xie, B., Shu, Y., & Yuan, C. (2023) · Medicine · doi:10.1097/md.0000000000035127 · Cited by 3
Woerner, J., Sriram, V., Nam, Y., Verma, A., & Kim, D. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae126 · Cited by 4
Lu, J., Liu, Y., Wang, Z., Zhou, K., Pan, Y., Zhong, S., & Jiang, G. (2024) · JACC Asia · doi:10.1016/j.jacasi.2024.07.011 · Cited by 3
Glucose‐dependent leucocyte activation in familial hypercholesterolemia
Koks, N., de Vries, M. A., Birnie, E., Alipour, A., & Cabezas, M. C. (2017) · European Journal of Clinical Investigation · doi:10.1111/eci.12818 · Cited by 3
Commentary: Big data bring big controversies: HDL cholesterol and mortality
Ala‐Korpela, M., Kuusisto, S. M., & Holmes, M. V. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab016 · Cited by 3
“evidence points to a potential protective role in type 2 diabetes.(16) Nonetheless, whereas such reliable information on the potential causal role of HDL-C remains relatively scarce, the most likely explanation is pervasive confounding, including socioeconomic circumstances, lifestyle, obesity and diet as well as vari…”
BackgroundSelf-citationYu, C., Liu, Z., Zhong, J., Liu, X., Mo, J., & Kuang, J. (2025) · BMC Endocrine Disorders · doi:10.1186/s12902-025-02012-0 · Cited by 2
“Abbreviation: UHR , serum uric acid high-density lipoprotein cholesterol ratio; PIR , household income to poverty ratio; TC , total cholesterol; BMI , body mass index; PAL , physical activity levels; SMK , smoking in HDL-C have been linked to increased diabetes risk [33].”
The two faces of cholesteryl ester transfer protein inhibitors
Pirillo, A., & Catapano, A. L. (2025) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000001017 · Cited by 2
Relation of Hypocholesterolemia With Diabetes Mellitus in Patients With Coronary Artery Disease
Ndrepepa, G., Cassese, S., Xhepa, E., Fusaro, M., Laugwitz, K., Schunkert, H., & Kastrati, A. (2020) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2019.12.044 · Cited by 2
Ma, Y., Zhou, Z., Li, X., Ding, K., Xiao, H., Wu, Y., Wu, T., & Chen, D. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.1009095 · Cited by 2
Type-2 diabetes with low LDL-C: genetic insights into a unique phenotypePreprint
Klimentidis, Y. C., Arora, A., Newell, M., Zhou, J. J., Ordovás, J. M., Renquist, B. J., & Wood, A. C. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/837013 · Cited by 2
Local and systemic factors associated with quantitative stiffness of carotid plaque
Sakaeyama, Y., Kondo, K., Terazono, S., Fuchinoue, Y., Kubota, S., Mikai, M., Abe, M., Sugo, N., Nagao, T., & Nemoto, M. (2024) · Acta Neurochirurgica · doi:10.1007/s00701-024-05952-z · Cited by 1
“The stability of plaque is influenced by its composition, including the relative proportions of lipids, inflammatory cells, smooth muscle cells, connective tissue, and thrombi [38, 40].”
Wang, J., Chen, J., Liu, Y., & Xu, J. (2025) · JMIR Medical Informatics · doi:10.2196/64992 · Cited by 1
Wang, J., Liu, S., Zhang, M., Meng, X., Wang, X., Wang, W., Gao, J., Zheng, J., Yang, Z., Wen, J., et al. (2025) · Neuroprotection/Neuroprotection (Chichester, England. Print) · doi:10.1002/nep3.72 · Cited by 1
Zhu, H., Zhang, M., Zhu, L., Wang, C., Zhang, Y., Yu, L. L., & Gao, B. (2025) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.5c05873 · Cited by 1
Li, J., Yupeng, Z., Liu, H., Panpan, Y., Yang, S., & Geyu, L. (2025) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2025.119105 · Cited by 1
Cao, C., Zheng, Y., Zha, F., Han, Y. Y., Hu, H., & Huang, M. (2025) · European journal of medical research · doi:10.1186/s40001-025-03284-x · Cited by 2
Enhanced identification of medicinal caterpillar fungus with structural lipidomic analysis
Jiang, Y., Yao, C., Zhang, H., Ouyang, Z., Guo, D., & Zhang, W. (2026) · Talanta · doi:10.1016/j.talanta.2026.129775 · Cited by 1
Adiponectin, Diabetes, and the Cardiovascular System
Gasbarrino, K., Boutari, C., Filippaios, A., Gianopoulos, I., Daskalopoulou, S. S., & Mantzoros, C. S. (2023) · Contemporary cardiology · doi:10.1007/978-3-031-13177-6_8 · Cited by 1
Hsu, L., Teng, M., Duan, D., Yeh, K.-H., Wu, S., & Ko, Y. (2025) · Tzu Chi Medical Journal · doi:10.4103/tcmj.tcmj_247_24 · Cited by 1
“Mendelian randomization (MR) studies have further reinforced the causal links between LDL-C levels and adverse vascular events and mortality [8-12].”
Анатольевна, К. О., Sushkova, A., Zhuravleva, O. A., Владимировна, В. И., Brazovskaya, N. G., Kravchenko, E. S., Суслова, Т. Е., & Karpov, R. S. (2017) · Diabetes Mellitus · doi:10.14341/dm8633 · Cited by 1
Beyond HDL-Cholesterol: The Search for Functional Biomarkers of High Density Lipoproteins
von Eckardstein, A. (2022) · CardioMetabolic Syndrome Journal · doi:10.51789/cmsj.2022.2.e5 · Cited by 1
Yanda, S. T., Longo‐Mbenza, B., Aundu, A. M., Gombet, R., Makulo, J.-R., Lusunsi, C. K., Malengele, H. M., & Okwe, A. N. (2022) · Vascular Health and Risk Management · doi:10.2147/vhrm.s366339 · Cited by 1
“Atherogenicity indices included CT/HDL-c, TG/HDL-c, LDL-c/HDL-c ratio, Body Fat Index, Visceral Adiposity Index), Height-Obesity Index.(14,15) After 5 minutes of relaxation, seated blood pressure (BP) was measured at each subject’s left arm using an Omron MI digital electronic blood pressure monitor/pulse monitor (OMR…”
MethodParveen, F. S., Quamri, M. A., Ahmed, K., & Shahid, A. (2022) · International Journal of Advanced Biochemistry Research · doi:10.33545/26174693.2022.v6.i2c.151 · Cited by 1
The predictive value of significant fibrosis for metabolic disturbances in patients with NAFLD
Liu, M., Sun, L., & Mao, Y. (2020) · Journal of Hepatology · doi:10.1016/j.jhep.2020.10.028 · Cited by 1
Biomedical consequences of elevated cholesterol-containing lipoproteins and apolipoproteinsPreprint
Schmidt, A. F., Joshi, R., Gordillo‐Marañón, M., Drenos, F., Charoen, P., Giambartolomei, C., Bis, J. C., Gaunt, T. R., Hughes, A. D., Lawlor, D. A., et al. (2022) · medRxiv · doi:10.1101/2022.03.11.22272251 · Cited by 1
Self-citationGordillo‐Marañón, M., Zwierzyna, M., Charoen, P., Drenos, F., Chopade, S., Shah, T., Engmann, J., Casas, J. P., Chaturvedi, N., Papacosta, O., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-122651/v1 · Cited by 1
Self-citationBulyk, T. S., Rynzhuk, V. Y., Gresko, M. D., Rynzhuk, L. V., Sydorchuk, L., MAKSIMYUK, V. V., MALYSHEVSKYI, Y. O., Kryvchanska, M. I., Хоменко, В. Г., Vlasova, K. V., et al. (2018) · Archives of the Balkan Medical Union · doi:10.31688/abmu.2018.53.2.05
Treating hypercholesterolaemia with evolocumab
Češka, R., Šnejdrlová, M., Vrablı́k, M., Altschmiedová, T., & Štulc, T. (2018) · Intervenční a akutní kardiologie · doi:10.36290/kar.2018.057
Integration of Multi-Omics in Type 2 Diabetes and Related Disorders Research
Liu, J. (2020) · EUR Research Repository (Erasmus University Rotterdam)
Fatakia, S. N. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/213124
“involve lipid regulation [23-26], inflammation [27-29], as well as other epigenetic agents such as an altered lifestyle [30, 31].”
BackgroundGenetic and lifestyle risks of cardiovascular disease
Said, M. A. (2021) · University of Groningen research database (University of Groningen / Centre for Information Technology) · doi:10.33612/diss.157192207
Nam, M. J., Lee, C.-W., Kim, H., Yoo, J. W., Lee, K. N., Han, K., Jung, J.-H., Park, Y. G., Kim, D., & Park, J. (2021) · Research Square · doi:10.21203/rs.3.rs-1186742/v1
Levy, D. A. (2017) · Journal of the American Society of Hypertension · doi:10.1016/j.jash.2017.07.002
Güvenç, O., Engin, M., Demir, Ö. F., Ata, F., & Yavuz, Ş. (2022) · The European Research Journal · doi:10.18621/eurj.1205252
Nicholls, S. J., & Nelson, A. J. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-88286-6.00029-7
Paradoxical mortality differential of HDL cholesterol
Mukhopadhyay, J., Mallik, D., & Garg, S. (2023) · Asian Journal of Medical Sciences · doi:10.3126/ajms.v14i5.50292
Zhao, H., Jiang, W., Song, S., Lyu, L., Chang, C., Zhao, Y., Wu, B., Wang, L., & Girgenti, M. J. (2023) · Research Square · doi:10.21203/rs.3.rs-3229244/v1
Le, N. N., Tran, T., Gill, D., & Padmanabhan, S. (2023) · medRxiv · doi:10.1101/2023.10.18.23297196
How safe are proprotein convertase subtilisinekexin type 9 inhibitors in diabetes?
Chen, T., & Liu, N. (2024) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000934
Chandran, M., Abhirami, Shareef, B., Surendran, A., Jaleel, A., & Ayyappan, J. P. (2024) · Human Gene · doi:10.1016/j.humgen.2024.201330
Associations between carotid artery intima-media thickness, traditional risk factors and proteins
Lind, L., & Zheng, R. (2025) · npj Cardiovascular Health · doi:10.1038/s44325-025-00073-7
“However, while MR studies have con fi rmed that BMI, blood pressure, LDL-cholesterol, and diabetes likely are causally related to myocardial infarction and ischemic stroke 8 – 16 , the causal role of HDL-cholesterol as a protective factor has been questioned 11,12 .”
Hu, C., Zhou, Y., Wu, X., Jia, X., Zhu, Y., Zheng, R., Wang, S., Lin, L., Qi, H., Lin, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26595413
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059060
Hu, C., Zhou, Y., Wu, X., Jia, X., Zhu, Y., Zheng, R., Wang, S., Lin, L., Qi, H., Lin, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26595419
Yang, G., & Schooling, C. M. (2024) · Figshare · doi:10.6084/m9.figshare.26560082
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059045
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059057
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059039
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059042
Yang, G., & Schooling, C. M. (2024) · Figshare · doi:10.6084/m9.figshare.26560085
Jiang, H., Si, M., Tian, T., Shi, H., Huang, N., Chi, H., Yang, R., Long, X., & Qiao, J. (2023) · Figshare · doi:10.6084/m9.figshare.23621302
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059048
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059054
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059051
Zhao, J., Ke, Z., Huang, R., Wen, X., Liu, W., Wang, S., Zhang, X., Zhuang, X., Pan, L., & Liao, L. (2024) · Figshare · doi:10.6084/m9.figshare.27059036
The role of testosterone in cardiovascular health: benefits and risks of replacement therapy
Gawełczyk, W., Tokarz, E., Soczyńska, J., Żołyniak, M., Pluta, K., Muzyka, A., & Obrycka, P. (2025) · Medical Journal of Cell Biology · doi:10.2478/acb-2025-0004
Zhou, Y., Wang, X., Ding, Z., Wang, Y., & Song, W. (2026) · Journal of Ovarian Research · doi:10.1186/s13048-026-02026-9
喻, 慧. (2026) · Advances in Clinical Medicine · doi:10.12677/acm.2026.1651815
Sniderman, A. D., Pencina, K. M., Thanassoulis, G., Dufresne, L., & Pencina, M. J. (2026) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwag400 · Cited by 1
Yu, H., Zhang, X., Yang, S., Fan, Z., Zhang, D., & Dan, W. A. N. G. (2026) · Lipids · doi:10.1002/lipd.70085
Metadata
- Authors
- White, J., Swerdlow, D. I., Preiss, D., Fairhurst-Hunter, Z., Keating, B. J., Asselbergs, F. W., Sattar, N., Humphries, S. E., Hingorani, A. D., & Holmes, M. V.
- Affiliations
- University College London (GB)
- Farr Institute (GB)
- University of Oxford (GB)
- Centre for Human Genetics (GB)
- Children's Hospital of Philadelphia (US)
- University Medical Center Utrecht (NL)
- University of Glasgow (GB)
- British Heart Foundation (GB)
- Corresponding author
- Holmes, Michael V.
- ORCID
- Venue
- JAMA Cardiology
- Publisher
- American Medical Association (AMA)
- Published
- 2016-09-01
- Volume
- 1
- Issue
- 6
- Pages
- 692
- ISSN
- 2380-6583 (ISSN-L)
- PMC
- PMC5642865
- OpenAlex
- W2481252033
- Cited by
- 293
- References
- 40
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 38 · 2023: 36 · 2022: 24 · 2021: 34 · 2020: 34 · 2019: 20 · 2018: 42 · 2017: 37 · 2016: 5
- FWCI
- 38.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- JAMA Cardiology (publishedVersion, public-domain)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust
- National Institute for Health and Care Research (NF-SI-0515-10091, ACF-2015-21-003)
- British Heart Foundation (PG 08/008, RG/10/12/28456)
- Medical Research Council (MR/K006584/1)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- LDL cholesterol, HDL cholesterol, triglycerides, coronary artery disease, type 2 diabetes, lipid fractions, statin therapy, pleiotropy, genetic instruments, multivariate Mendelian randomization, MR-Egger, causal inference, single nucleotide polymorphisms, polygenic risk score, cardiovascular risk prediction
- MeSH terms
- Coronary Artery Disease, Diabetes Mellitus, Type 2, Humans, Lipids, Cholesterol, HDL, Cholesterol, LDL, Risk Factors, Polymorphism, Single Nucleotide, Genome-Wide Association Study
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