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1. Causal inference in health and disease: a review of the principles and applications of Mendelian randomization.

Author: Lovegrove, Catherine E, Howles, Sarah A, Furniss, Dominic, and Holmes, Michael V
Abstract: Mendelian randomization (MR) is a genetic epidemiological technique that uses genetic variation to infer causal relationships between modifiable exposures and outcome variables. Conventional observational epidemiological studies are subject to bias from a range of sources; MR analyses can offer an advantage in that they are less prone to bias as they use genetic variants inherited at conception as "instrumental variables", which are proxies of an exposure. However, as with all research tools, MR studies must be carefully designed to yield valuable insights into causal relationships between exposures and outcomes, and to avoid biased or misleading results that undermine the validity of the causal inferences drawn from the study. In this review, we outline Mendel's laws of inheritance, the assumptions and principles that underlie MR, MR study designs and methods, and how MR analyses can be applied and reported. Using the example of serum phosphate concentrations on liability to kidney stone disease we illustrate how MR estimates may be visualized and, finally, we contextualize MR in bone and mineral research including exemplifying how this technique could be employed to inform clinical studies and future guidelines concerning BMD and fracture risk. This review provides a framework to enhance understanding of how MR may be used to triangulate evidence and progress research in bone and mineral metabolism as we strive to infer causal effects in health and disease. [ABSTRACT FROM AUTHOR]
Published: 2024
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2. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

Author: Swerdlow, Daniel I, Preiss, David, Kuchenbaecker, Karoline B, Holmes, Michael V, Engmann, Jorgen EL, Shah, Tina, Sofat, Reecha, Stender, Stefan, Johnson, Paul CD, Scott, Robert A, Leusink, Maarten, Verweij, Niek, Sharp, Stephen J, Guo, Yiran, Giambartolomei, Claudia, Chung, Christina, Peasey, Anne, Amuzu, Antoinette, Li, KaWah, Palmen, Jutta, Howard, Philip, Cooper, Jackie A, Drenos, Fotios, Li, Yun R, Lowe, Gordon, Gallacher, John, Stewart, Marlene CW, Tzoulaki, Ioanna, Buxbaum, Sarah G, van der A, Daphne L, Forouhi, Nita G, Onland-Moret, N Charlotte, van der Schouw, Yvonne T, Schnabel, Renate B, Hubacek, Jaroslav A, Kubinova, Ruzena, Baceviciene, Migle, Tamosiunas, Abdonas, Pajak, Andrzej, Topor-Madry, Romanvan, Stepaniak, Urszula, Malyutina, Sofia, Baldassarre, Damiano, Sennblad, Bengt, Tremoli, Elena, de Faire, Ulf, Veglia, Fabrizio, Ford, Ian, Jukema, J Wouter, Westendorp, Rudi GJ, de Borst, Gert Jan, de Jong, Pim A, Algra, Ale, Spiering, Wilko, der Zee, Anke H Maitland-van, Klungel, Olaf H, de Boer, Anthonius, Doevendans, Pieter A, Eaton, Charles B, Robinson, Jennifer G, Duggan, David, DIAGRAM Consortium, MAGIC Consortium, Kjekshus, John, Downs, John R, Gotto, Antonio M, Keech, Anthony C, Marchioli, Roberto, Tognoni, Gianni, Sever, Peter S, Poulter, Neil R, Waters, David D, Pedersen, Terje R, Amarenco, Pierre, Nakamura, Haruo, McMurray, John JV, Lewsey, James D, Chasman, Daniel I, Ridker, Paul M, Maggioni, Aldo P, Tavazzi, Luigi, Ray, Kausik K, Seshasai, Sreenivasa Rao Kondapally, Manson, JoAnn E, Price, Jackie F, Whincup, Peter H, Morris, Richard W, Lawlor, Debbie A, Smith, George Davey, Ben-Shlomo, Yoav, Schreiner, Pamela J, Fornage, Myriam, Siscovick, David S, Cushman, Mary, Kumari, Meena, Wareham, Nick J, Verschuren, WM Monique, Redline, Susan, Patel, Sanjay R, Whittaker, John C, and Hamsten, Anders
Subjects: Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Clinical Trials and Supportive Activities, Clinical Research, Genetics, Nutrition, Diabetes, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Metabolic and endocrine, Aged, Body Mass Index, Body Weight, Cholesterol, HDL, Cholesterol, LDL, Diabetes Mellitus, Type 2, Female, Genetic Testing, Humans, Hydroxymethylglutaryl CoA Reductases, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Male, Middle Aged, Polymorphism, Single Nucleotide, Randomized Controlled Trials as Topic, Risk Factors, DIAGRAM Consortium, MAGIC Consortium, InterAct Consortium, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundStatins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target.MethodsWe used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis.FindingsData were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials).InterpretationThe increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition.FundingThe funding sources are cited at the end of the paper.
Published: 2015

3. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data

Author: Holmes, Michael V, Dale, Caroline E, Zuccolo, Luisa, Silverwood, Richard J, Guo, Yiran, Ye, Zheng, Prieto-Merino, David, Dehghan, Abbas, Trompet, Stella, Wong, Andrew, Cavadino, Alana, Drogan, Dagmar, Padmanabhan, Sandosh, Li, Shanshan, Yesupriya, Ajay, Leusink, Maarten, Sundstrom, Johan, Hubacek, Jaroslav A, Pikhart, Hynek, Swerdlow, Daniel I, Panayiotou, Andrie G, Borinskaya, Svetlana A, Finan, Chris, Shah, Sonia, Kuchenbaecker, Karoline B, Shah, Tina, Engmann, Jorgen, Folkersen, Lasse, Eriksson, Per, Ricceri, Fulvio, Melander, Olle, Sacerdote, Carlotta, Gamble, Dale M, Rayaprolu, Sruti, Ross, Owen A, McLachlan, Stela, Vikhireva, Olga, Sluijs, Ivonne, Scott, Robert A, Adamkova, Vera, Flicker, Leon, Bockxmeer, Frank M van, Power, Christine, Marques-Vidal, Pedro, Meade, Tom, Marmot, Michael G, Ferro, Jose M, Paulos-Pinheiro, Sofia, Humphries, Steve E, Talmud, Philippa J, Mateo Leach, Irene, Verweij, Niek, Linneberg, Allan, Skaaby, Tea, Doevendans, Pieter A, Cramer, Maarten J, van der Harst, Pim, Klungel, Olaf H, Dowling, Nicole F, Dominiczak, Anna F, Kumari, Meena, Nicolaides, Andrew N, Weikert, Cornelia, Boeing, Heiner, Ebrahim, Shah, Gaunt, Tom R, Price, Jackie F, Lannfelt, Lars, Peasey, Anne, Kubinova, Ruzena, Pajak, Andrzej, Malyutina, Sofia, Voevoda, Mikhail I, Tamosiunas, Abdonas, Maitland-van der Zee, Anke H, Norman, Paul E, Hankey, Graeme J, Bergmann, Manuela M, Hofman, Albert, Franco, Oscar H, Cooper, Jackie, Palmen, Jutta, Spiering, Wilko, de Jong, Pim A, Kuh, Diana, Hardy, Rebecca, Uitterlinden, Andre G, Ikram, M Arfan, Ford, Ian, Hyppönen, Elina, Almeida, Osvaldo P, Wareham, Nicholas J, Khaw, Kay-Tee, Hamsten, Anders, Husemoen, Lise Lotte N, Tjønneland, Anne, Tolstrup, Janne S, Rimm, Eric, Beulens, Joline WJ, and Verschuren, WM Monique
Subjects: Epidemiology, Public Health, Health Sciences, Substance Misuse, Genetics, Brain Disorders, Cardiovascular, Alcoholism, Alcohol Use and Health, Heart Disease, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Oral and gastrointestinal, Stroke, Good Health and Well Being, Adult, Aged, Alcohol Dehydrogenase, Alcohol Drinking, Biomarkers, Coronary Disease, Female, Genetic Markers, Genotype, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Models, Statistical, Polymorphism, Single Nucleotide, InterAct Consortium, Clinical Sciences, Public Health and Health Services, General & Internal Medicine, Biomedical and clinical sciences, Health sciences, Psychology
Abstract: ObjectiveTo use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease.DesignMendelian randomisation meta-analysis of 56 epidemiological studies.Participants261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers.Main outcome measuresOdds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption.ResultsCarriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)).ConclusionsIndividuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health.
Published: 2014

4. Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci

Author: Asselbergs, Folkert W, Guo, Yiran, van Iperen, Erik PA, Sivapalaratnam, Suthesh, Tragante, Vinicius, Lanktree, Matthew B, Lange, Leslie A, Almoguera, Berta, Appelman, Yolande E, Barnard, John, Baumert, Jens, Beitelshees, Amber L, Bhangale, Tushar R, Chen, Yii-Der Ida, Gaunt, Tom R, Gong, Yan, Hopewell, Jemma C, Johnson, Toby, Kleber, Marcus E, Langaee, Taimour Y, Li, Mingyao, Li, Yun R, Liu, Kiang, McDonough, Caitrin W, Meijs, Matthijs FL, Middelberg, Rita PS, Musunuru, Kiran, Nelson, Christopher P, O’Connell, Jeffery R, Padmanabhan, Sandosh, Pankow, James S, Pankratz, Nathan, Rafelt, Suzanne, Rajagopalan, Ramakrishnan, Romaine, Simon PR, Schork, Nicholas J, Shaffer, Jonathan, Shen, Haiqing, Smith, Erin N, Tischfield, Sam E, van der Most, Peter J, van Vliet-Ostaptchouk, Jana V, Verweij, Niek, Volcik, Kelly A, Zhang, Li, Bailey, Kent R, Bailey, Kristian M, Bauer, Florianne, Boer, Jolanda MA, Braund, Peter S, Burt, Amber, Burton, Paul R, Buxbaum, Sarah G, Chen, Wei, Cooper-DeHoff, Rhonda M, Cupples, L Adrienne, deJong, Jonas S, Delles, Christian, Duggan, David, Fornage, Myriam, Furlong, Clement E, Glazer, Nicole, Gums, John G, Hastie, Claire, Holmes, Michael V, Illig, Thomas, Kirkland, Susan A, Kivimaki, Mika, Klein, Ronald, Klein, Barbara E, Kooperberg, Charles, Kottke-Marchant, Kandice, Kumari, Meena, LaCroix, Andrea Z, Mallela, Laya, Murugesan, Gurunathan, Ordovas, Jose, Ouwehand, Willem H, Post, Wendy S, Saxena, Richa, Scharnagl, Hubert, Schreiner, Pamela J, Shah, Tina, Shields, Denis C, Shimbo, Daichi, Srinivasan, Sathanur R, Stolk, Ronald P, Swerdlow, Daniel I, Taylor, Herman A, Topol, Eric J, Toskala, Elina, van Pelt, Joost L, van Setten, Jessica, Yusuf, Salim, Whittaker, John C, Zwinderman, AH, Study, LifeLines Cohort, Anand, Sonia S, Balmforth, Anthony J, and Berenson, Gerald S
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Human Genome, Cardiovascular, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Cholesterol, HDL, Cholesterol, LDL, Female, Genome-Wide Association Study, Genotype, Humans, Lipids, Male, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sex Factors, Triglycerides, White People, LifeLines Cohort Study, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract: Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
Published: 2012

5. Fibroblast Growth Factor-23 and Risk of Cardiovascular Diseases A Mendelian Randomization Study

Author: Donovan, Killian, Herrington, William G., Pare, Guillaume, Pigeyre, Marie, Haynes, Richard, Sardell, Rebecca, Butterworth, Adam S., Folkersen, Lasse, Gustafsson, Stefan, Wang, Qin, Baigent, Colin, Malarstig, Anders, Holmes, Michael V., and Staplin, Natalie
Subjects: Transplantation, Kardiologi, Nephrology, Epidemiology, Cardiac and Cardiovascular Systems, Critical Care and Intensive Care Medicine
Abstract: Background: Fibroblast growth factor 23 (FGF-23) is associated with a range of cardiovascular and non-cardiovascular diseases in conventional epidemiological studies, but substantial residual confounding may exist. Mendelian randomization approaches can help control for such confounding. Methods: SCALLOP consortium data on 19,195 participants were used to generate an FGF-23 genetic score. Data from 337,448 UK Biobank participants were used to estimate associations between higher genetically-predicted FGF-23 concentration and the odds of any atherosclerotic cardiovascular disease (n=26,266 events), of any non-atherosclerotic cardiovascular disease (n=12,652), and of non-cardiovascular diseases previously linked to FGF-23. Measurements of carotid intima-media thickness and left ventricular mass were available in a subset. Associations with cardiovascular outcomes were also tested in three large case-control consortia: CARDIOGRAMplusC4D (coronary artery disease, n=181,249 cases), MEGASTROKE (stroke, n=34,217), and HERMES (heart failure, n=47,309). Results: We identified 34 independent variants for circulating FGF-23 which formed a validated genetic score. There were no associations between genetically-predicted FGF-23 and any of the cardiovascular or non-cardiovascular outcomes. In UK Biobank, the odds ratio for any atherosclerotic cardiovascular disease per 1-SD higher genetically-predicted logFGF-23 was 1.03 (95% confidence interval [CI] 0.98-1.08), and for any non-atherosclerotic cardiovascular disease was 1.01 (0.94-1.09). The odds ratios in the case-control consortia were 1.00 (0.97-1.03) for coronary artery disease, 1.01 (0.95-1.07) for stroke, and 1.00 (0.95-1.05) for heart failure. In those with imaging, logFGF-23 was not associated with carotid or cardiac abnormalties. Conclusion: Genetically predicted FGF-23 levels are not associated atherosclerotic and non-atherosclerotic cardiovascular diseases, suggesting no important causal link.
Published: 2023

6. The physiological paradox: reframing the polypill as a vaccine for cardiovascular disease

Author: Holmes, Michael V and Bhala, Neeraj
Published: 2013

7. Circulating insulin-like growth factors and risks of overall, aggressive and early-onset prostate cancer:a collaborative analysis of 20 prospective studies and Mendelian randomization analysis

Author: Watts, Eleanor L., Perez-Cornago, Aurora, Fensom, Georgina K., Smith-Byrne, Karl, Noor, Urwah, Andrews, Colm D., Gunter, Marc J., Holmes, Michael V., Martin, Richard M., Tsilidis, Konstantinos K., Albanes, Demetrius, Barricarte, Aurelio, Bueno-De-Mesquita, H. Bas, Cohn, Barbara A., Deschasaux-Tanguy, Melanie, Dimou, Niki L., Ferrucci, Luigi, Flicker, Leon, Freedman, Neal D., Giles, Graham G., Giovannucci, Edward L., Haiman, Christopher A., Hankey, Graham J., Holly, Jeffrey M. P., Huang, Jiaqi, Huang, Wen-Yi, Hurwitz, Lauren M., Kaaks, Rudolf, Kubo, Tatsuhiko, Le Marchand, Loic, Macinnis, Robert J., Männistö, Satu, Metter, E. Jeffrey, Mikami, Kazuya, Mucci, Lorelei A., Olsen, Anja W., Ozasa, Kotaro, Palli, Domenico, Penney, Kathryn L., Platz, Elizabeth A., Pollak, Michael N., Roobol, Monique J., Schaefer, Catherine A., Schenk, Jeannette M., Stattin, Pär, Tamakoshi, Akiko, Thysell, Elin, Tsai, Chiaojung Jillian, Touvier, Mathilde, Van Den Eeden, Stephen K., Weiderpass, Elisabete, Weinstein, Stephanie J., Wilkens, Lynne R., Yeap, Bu B., Allen, Naomi E., Key, Timothy J., Travis, Ruth C., The PRACTICAL Consortium, CRUK, BPC3, CAPS, PEGASUS, and consortium, The PRACTICAL
Subjects: Cancer och onkologi, prospective analysis, Epidemiology, General Medicine, prostate cancer, aggressive prostate cancer, Cancer and Oncology, Mendelian randomization, international consortia, Insulin-like growth factor-I, ICEP, Bristol Population Health Science Institute
Abstract: Background Previous studies had limited power to assess the associations of circulating insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs) with clinically relevant prostate cancer as a primary endpoint, and the association of genetically predicted IGF-I with aggressive prostate cancer is not known. We aimed to investigate the associations of IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 concentrations with overall, aggressive and early-onset prostate cancer. Methods Prospective analysis of biomarkers using the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset (up to 20 studies, 17 009 prostate cancer cases, including 2332 aggressive cases). Odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression. For IGF-I, two-sample Mendelian randomization (MR) analysis was undertaken using instruments identified using UK Biobank (158 444 men) and outcome data from PRACTICAL (up to 85 554 cases, including 15 167 aggressive cases). Additionally, we used colocalization to rule out confounding by linkage disequilibrium. Results In observational analyses, IGF-I was positively associated with risks of overall (OR per 1 SD = 1.09: 95% CI 1.07, 1.11), aggressive (1.09: 1.03, 1.16) and possibly early-onset disease (1.11: 1.00, 1.24); associations were similar in MR analyses (OR per 1 SD = 1.07: 1.00, 1.15; 1.10: 1.01, 1.20; and 1.13; 0.98, 1.30, respectively). Colocalization also indicated a shared signal for IGF-I and prostate cancer (PP4: 99%). Men with higher IGF-II (1.06: 1.02, 1.11) and IGFBP-3 (1.08: 1.04, 1.11) had higher risks of overall prostate cancer, whereas higher IGFBP-1 was associated with a lower risk (0.95: 0.91, 0.99); these associations were attenuated following adjustment for IGF-I. Conclusions These findings support the role of IGF-I in the development of prostate cancer, including for aggressive disease.
Published: 2022
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8. Putting genomics into practice: A new analysis casts doubt on the clinical utility of CYP2C19 genotype testing to help guide antiplatelet prescribing

Author: Holmes, Michael V, Casas, Juan P, and Hingorani, Aroon D
Published: 2011

9. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Author: Shah, Sonia, Henry, Albert, Roselli, Carolina, Lin, Honghuang, Sveinbjornsson, Gardar, Fatemifar, Ghazaleh, Hedman, Asa K, Wilk, Jemma B, Morley, Michael P, Chaffin, Mark D, Helgadottir, Anna, Verweij, Niek, Dehghan, Abbas, Almgren, Peter, Andersson, Charlotte, Aragam, Krishna G, Arnlov, Johan, Backman, Joshua D, Biggs, Mary L, Bloom, Heather L, Brandimarto, Jeffrey, Brown, Michael R, Buckbinder, Leonard, Carey, David J, Chasman, Daniel I, Chen, Xing, Chen, Xu, Chung, Jonathan, Chutkow, William, Cook, James P, Delgado, Graciela E, Denaxas, Spiros, Doney, Alexander S, Doerr, Marcus, Dudley, Samuel C, Dunn, Michael E, Engstrom, Gunnar, Esko, Tonu, Felix, Stephan B, Finan, Chris, Ford, Ian, Ghanbari, Mohsen, Ghasemi, Sahar, Giedraitis, Vilmantas, Giulianini, Franco, Gottdiener, John S, Gross, Stefan, Gudbjartsson, Daniel F, Gutmann, Rebecca, Haggerty, Christopher M, van der Harst, Pim, Hyde, Craig L, Ingelsson, Erik, Jukema, J Wouter, Kavousi, Maryam, Khaw, Kay-Tee, Kleber, Marcus E, Kober, Lars, Koekemoer, Andrea, Langenberg, Claudia, Lind, Lars, Lindgren, Cecilia M, London, Barry, Lotta, Luca A, Lovering, Ruth C, Luan, Jian'an, Magnusson, Patrik, Mahajan, Anubha, Margulies, Kenneth B, Maerz, Winfried, Melander, Olle, Mordi, Ify R, Morgan, Thomas, Morris, Andrew D, Morris, Andrew P, Morrison, Alanna C, Nagle, Michael W, Nelson, Christopher P, Niessner, Alexander, Niiranen, Teemu, O'Donoghue, Michelle L, Owens, Anjali T, Palmer, Colin NA, Parry, Helen M, Perola, Markus, Portilla-Fernandez, Eliana, Psaty, Bruce M, Rice, Kenneth M, Ridker, Paul M, Romaine, Simon PR, Rotter, Jerome I, Salo, Perttu, Salomaa, Veikko, van Setten, Jessica, Shalaby, Alaa A, Smelser, Diane T, Smith, Nicholas L, Stender, Steen, Stott, David J, Svensson, Per, Tammesoo, Mari-Liis, Taylor, Kent D, Teder-Laving, Maris, Teumer, Alexander, Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Torp-Pedersen, Christian, Trompet, Stella, Tyl, Benoit, Uitterlinden, Andre G, Veluchamy, Abirami, Voelker, Uwe, Voors, Adriaan A, Wang, Xiaosong, Wareham, Nicholas J, Waterworth, Dawn, Weeke, Peter E, Weiss, Raul, Wiggins, Kerri L, Xing, Heming, Yerges-Armstrong, Laura M, Yu, Bing, Zannad, Faiez, Zhao, Jing Hua, Hemingway, Harry, Samani, Nilesh J, McMurray, John JV, Yang, Jian, Visscher, Peter M, Newton-Cheh, Christopher, Malarstig, Anders, Holm, Hilma, Lubitz, Steven A, Sattar, Naveed, Holmes, Michael V, Cappola, Thomas P, Asselbergs, Folkert W, Hingorani, Aroon D, Kuchenbaecker, Karoline, Ellinor, Patrick T, Lang, Chim C, Stefansson, Kari, Smith, J Gustav, Vasan, Ramachandran S, Swerdlow, Daniel I, Lumbers, R Thomas, Abecasis, Goncalo, Backman, Joshua, Bai, Xiaodong, Balasubramanian, Suganthi, Banerjee, Nilanjana, Baras, Aris, Barnard, Leland, Beechert, Christina, Blumenfeld, Andrew, Cantor, Michael, Chai, Yating, Coppola, Giovanni, Damask, Amy, Dewey, Frederick, Economides, Aris, Eom, Gisu, Forsythe, Caitlin, Fuller, Erin D, Gu, Zhenhua, Gurski, Lauren, Guzzardo, Paloma M, Habegger, Lukas, Hahn, Young, Hawes, Alicia, van Hout, Cristopher, Jones, Marcus B, Khalid, Shareef, Lattari, Michael, Li, Alexander, Lin, Nan, Liu, Daren, Lopez, Alexander, Manoochehri, Kia, Marchini, Jonathan, Marcketta, Anthony, Maxwell, Evan K, McCarthy, Shane, Mitnaul, Lyndon J, O'Dushlaine, Colm, Overton, John D, Padilla, Maria Sotiropoulos, Paulding, Charles, Penn, John, Pradhan, Manasi, Reid, Jeffrey G, Schleicher, Thomas D, Schurmann, Claudia, Shuldiner, Alan, Staples, Jeffrey C, Sun, Dylan, Toledo, Karina, Ulloa, Ricardo H, Widom, Louis, Wolf, Sarah E, Yadav, Ashish, Ye, Bin, Ctr, Regeneron Genetics, Shah, Sonia [0000-0001-5860-4526], Henry, Albert [0000-0001-7422-2288], Roselli, Carolina [0000-0001-5267-6756], Lin, Honghuang [0000-0003-3043-3942], Chaffin, Mark D. [0000-0002-1234-5562], Helgadottir, Anna [0000-0002-1806-2467], Verweij, Niek [0000-0002-4303-7685], Almgren, Peter [0000-0002-0473-0241], Chen, Xu [0000-0002-7299-3238], Ghanbari, Mohsen [0000-0002-9476-7143], Giedraitis, Vilmantas [0000-0003-3423-2021], Gross, Stefan [0000-0003-4121-7161], Guðbjartsson, Daníel F. [0000-0002-5222-9857], Hyde, Craig L. [0000-0002-6939-287X], Ingelsson, Erik [0000-0003-2256-6972], Jukema, J. Wouter [0000-0002-3246-8359], Kleber, Marcus E. [0000-0003-0663-7275], Koekemoer, Andrea [0000-0001-8222-3547], Langenberg, Claudia [0000-0002-5017-7344], Lindgren, Cecilia M. [0000-0002-4903-9374], Lovering, Ruth C. [0000-0002-9791-0064], Luan, Jian’an [0000-0003-3137-6337], Magnusson, Patrik [0000-0002-7315-7899], Mahajan, Anubha [0000-0001-5585-3420], Mordi, Ify R. [0000-0002-2686-729X], Morris, Andrew D. [0000-0002-1766-0473], Nagle, Michael W. [0000-0002-4677-7582], Nelson, Christopher P. [0000-0001-8025-2897], Palmer, Colin N. A. [0000-0002-6415-6560], Rice, Kenneth M. [0000-0002-3071-7278], Rotter, Jerome I. [0000-0001-7191-1723], Salomaa, Veikko [0000-0001-7563-5324], van Setten, Jessica [0000-0002-4934-7510], Svensson, Per [0000-0003-0372-6272], Taylor, Kent D. [0000-0002-2756-4370], Teder-Laving, Maris [0000-0002-5872-1850], Teumer, Alexander [0000-0002-8309-094X], Tyl, Benoit [0000-0001-5297-8412], Uitterlinden, Andre G. [0000-0002-7276-3387], Völker, Uwe [0000-0002-5689-3448], Wiggins, Kerri L. [0000-0003-2749-1279], Hemingway, Harry [0000-0003-2279-0624], Yang, Jian [0000-0003-2001-2474], Visscher, Peter M. [0000-0002-2143-8760], Lubitz, Steven A. [0000-0002-9599-4866], Sattar, Naveed [0000-0002-1604-2593], Cappola, Thomas P. [0000-0002-9630-7204], Asselbergs, Folkert W. [0000-0002-1692-8669], Kuchenbaecker, Karoline [0000-0001-9726-603X], Ellinor, Patrick T. [0000-0002-2067-0533], Vasan, Ramachandran S. [0000-0001-7357-5970], Lumbers, R. Thomas [0000-0002-9077-4741], Apollo - University of Cambridge Repository, Chaffin, Mark D [0000-0002-1234-5562], Guðbjartsson, Daníel F [0000-0002-5222-9857], Hyde, Craig L [0000-0002-6939-287X], Jukema, J Wouter [0000-0002-3246-8359], Kleber, Marcus E [0000-0003-0663-7275], Lindgren, Cecilia M [0000-0002-4903-9374], Lovering, Ruth C [0000-0002-9791-0064], Luan, Jian'an [0000-0003-3137-6337], Mordi, Ify R [0000-0002-2686-729X], Morris, Andrew D [0000-0002-1766-0473], Nagle, Michael W [0000-0002-4677-7582], Nelson, Christopher P [0000-0001-8025-2897], Palmer, Colin NA [0000-0002-6415-6560], Rice, Kenneth M [0000-0002-3071-7278], Rotter, Jerome I [0000-0001-7191-1723], Taylor, Kent D [0000-0002-2756-4370], Uitterlinden, Andre G [0000-0002-7276-3387], Wiggins, Kerri L [0000-0003-2749-1279], Visscher, Peter M [0000-0002-2143-8760], Lubitz, Steven A [0000-0002-9599-4866], Cappola, Thomas P [0000-0002-9630-7204], Asselbergs, Folkert W [0000-0002-1692-8669], Ellinor, Patrick T [0000-0002-2067-0533], Vasan, Ramachandran S [0000-0001-7357-5970], Lumbers, R Thomas [0000-0002-9077-4741], Palmer, Colin N A [0000-0002-6415-6560], Cardiovascular Centre (CVC), University of Queensland [Brisbane], University College of London [London] (UCL), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], University Medical Center Groningen [Groningen] (UMCG), Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Framingham Heart Study, National Heart, Lung, and Blood Institute [Bethesda] (NHLBI)-Boston University [Boston] (BU), deCODE genetics [Reykjavik], Karolinska Institutet [Stockholm], Pfizer, University of Pennsylvania [Philadelphia], University of Groningen [Groningen], Imperial College London, Lund University [Lund], Herlev and Gentofte Hospital, Massachusetts General Hospital [Boston], Department of Neurobiology, Care Sciences and Society [Stockholm, Sweden] (Division of Family Medicine), Dalarna University, Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, Department of Biostatistics, University of Washington [Seattle], Emory University School of Medicine, Emory University [Atlanta, GA], The University of Texas Medical School at Houston, Department of Molecular and Functional Genomics, Geisinger, Danville, PA, Brigham and Women's Hospital [Boston], Harvard Medical School [Boston] (HMS), Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY, Novartis Institutes for BioMedical Research (NIBR), University of Liverpool, Universität Heidelberg [Heidelberg], Medizinische Fakultät Mannheim, The Alan Turing Institute, Ninewells Hospital and Medical School [Dundee], Universität Greifswald - University of Greifswald, German Center for Cardiovascular Research (DZHK), Berlin Institute of Health (BIH), University of Minnesota System, Regeneron Pharmaceuticals [Tarrytown], Department of Clinical Sciences, Cardiovascular Epidemiology, Skane University Hospital [Lund], Institute of Genomics [Tartu, Estonia], University of Tartu, Robertson Centre for Biostatistics, University of Glasgow, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Uppsala University, Brigham & Women’s Hospital [Boston] (BWH), University of Maryland School of Medicine, University of Maryland System, School of Science and Engineering (Reykjavik University), Carver College of Medicine, University of Iowa, Geisinger Health System [Danville, PA, USA], Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, Stanford Cardiovascular Institute, Uppsala Universitet [Uppsala], Leiden University Medical Center (LUMC), Einthoven Laboratory for Experimental Vascular Medicine (ELEVM - LEIDEN), Department of Public Health and Primary Care, University of Cambridge [UK] (CAM), Rigshospitalet [Copenhagen], Copenhagen University Hospital, Glenfield Hospital, University Hospitals Leicester, MRC Epidemiology Unit, University of Cambridge [UK] (CAM)-Institute of Metabolic Science, Big Data Institute, University of Oxford [Oxford], University of Iowa [Iowa City], The Wellcome Trust Centre for Human Genetics [Oxford], Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Medical University Graz, Skane University Hospital [Malmo], Vanderbilt University School of Medicine [Nashville], University of Edinburgh, Université médicale de Vienne, Autriche, National Institute for Health and Welfare [Helsinki], University of Turku, Birmingham Women's and Children's NHS Foundation Trust, Kaiser Permanente, Harbor UCLA Medical Center [Torrance, Ca.], Los Angeles Biomedical Research Institute (LA BioMed), University Medical Center [Utrecht], University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Seattle Epidemiologic Research and Information Center [Seattle], Institute of Cardiovascular and Medical Sciences [Glasgow], University of Glasgow, Department of Cardiology, Södersjukhuset, Stockholm, Estonian Genome and Medicine, Landspitali National University Hospital of Iceland, University of Iceland [Reykjavik], Aalborg University [Denmark] (AAU), Institut de Recherches SERVIER (IRS), Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt-Universität Greifswald, GlaxoSmithKline, Glaxo Smith Kline, Northeastern Ohio Medical University (NEOMED), Centre d'investigation clinique plurithématique Pierre Drouin [Nancy] (CIC-P), Centre d'investigation clinique [Nancy] (CIC), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), Défaillance Cardiovasculaire Aiguë et Chronique (DCAC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Cardiovascular and Renal Clinical Trialists [Vandoeuvre-les-Nancy] (INI-CRCT), Institut Lorrain du Coeur et des Vaisseaux Louis Mathieu [Nancy], French-Clinical Research Infrastructure Network - F-CRIN [Paris] (Cardiovascular & Renal Clinical Trialists - CRCT ), MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, British Heart Foundation Glasgow Cardiovascular Research Centre (BHF GCRC), University of Glasgow-NHS Greater Glasgow and Clyde, Department of Cardiovascular Sciences [Leicester], University of Leicester, Queensland Brain Institute, Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, University of Dundee, National Heart and Lung Institute [London] (NHLI), Imperial College London-Royal Brompton and Harefield NHS Foundation Trust, Atherosclerosis Risk in Communities Study (ARIC)The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC- 55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC55021, N01-HC-55022, R01HL087641, R01HL59367, R01HL086694 and RC2 HL102419, National Human Genome Research Institute contract U01HG004402, and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. A systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT- CHF)This project was funded by a grant from the European Commission (FP7‐242209‐ BIOSTAT‐CHF, EudraCT 2010–020808–29). Cardiovascular Health Study (CHS) This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, HHSN268200960009C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and NHLBI grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, and U01HL130114 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. deCODE Heart Failure Study (deCODE) We at deCODE thank the women and men of Iceland that have participated in our studies and our colleagues that contributed to data collection and processing. DiscovEHR We acknowledge and thank all participants in Geisinger’s MyCode Community Health Initiative for their support and permission to use their health and genomic information in the DiscovEHR collaboration. This work was supported by the Regeneron Genetics Center and Geisinger. Estonian Genome Center at the University of Tartu (EGCUT) This study was supported by Estonian Research Council Grant IUT20-60, EU, H2020 grant 692145, European Union through the European Regional Development Fund (Project No. 2014-2020.4.01.15-0012) GENTRANSMED. Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study (EPHESUS) The EPHESUS was supported by Pfizer, Inc. The European Prospective Investigation of Cancer, Norfolk study (EPIC-Norfolk) The EPIC-Norfolk Study is supported by programme grants from the Medical Research Council UK (G1000143) and Cancer Research UK (C864/A14136) and with additional support from the European Union, Stroke Association, British Heart Foundation, Research into Ageing, Department of Health, The Wellcome Trust and the Food Standards Agency. NJW and CL also acknowledge support from the Medical Research Council, UK (MC_UU_12015/1, MC_PC_13048). We thank all EPIC participants and staff for their contribution to the study, and thank staff from the Technical, Field Epidemiology and Data Functional Group Teams of the Medical Research Council Epidemiology Unit in Cambridge, UK, for carrying out sample preparation, DNA provision and quality control, genotyping and data handling work. Framingham Heart Study (FHS) This work was conducted using data and resources from the Framingham Heart Study (FHS) of the National Heart Lung and Blood Institute and Boston University School of Medicine. The study was supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC-25195 and HHSN268201500001I) and its contract with Affymetrix, Inc for genotyping services (Contract No.N02-HL-6-4278). The work was also supported by R01 HL093328, R01 HL105993, and R01 HL71039 (PI: Ramachandran). FINRISK V.S. has been supported by the Finnish Foundation for Cardiovascular Research. Genetics of Diabetes Audit and Research Tayside Scotland GoDARTS) The Wellcome Trust United Kingdom Type 2 Diabetes Case Control Collection (supporting GoDARTS) was funded by the Wellcome Trust (072960/Z/03/Z, 084726/Z/08/Z, 084727/Z/08/Z, 085475/Z/08/Z, 085475/B/08/Z) and as part of the EU IMI-SUMMIT programme. We acknowledge the support of the Health Informatics Centre, University of Dundee, for managing and supplying the anonymized data and NHS Tayside, the original data owner. The Genetic Risk Assessment of Defibrillator Events (GRADE) NIH-NHLBI R01 HL77398 (Genetic Modulators of Sudden Death). S.L. is supported by NIH grant 1R01HL139731 and American Heart Association 18SFRN34250007. The LUdwigshafen RIsk and Cardiovascular Health (LURIC) study We extend our appreciation to the participants of the LURIC study, without their collaboration, this article would not have been written. We thank the LURIC study team who were either temporarily or permanently involved in patient recruitment as well as sample and data handling, in addition to the laboratory staff at the Ludwigshafen General Hospital and the Universities of Freiburg and Ulm, Germany. LURIC has received funding from the 7th Framework Program (RiskyCAD, grant agreement number 305739 and Atheroremo, grant agreement number 201668) of the European Union. Malmö Diet and Cancer Study (MDCS) J. Gustav Smith was supported by grants from the Swedish Heart-Lung Foundation (2016- 0134 and 2016-0315), the Swedish Research Council (2017-02554), the European Research Council (ERC-STG-2015-679242), the Crafoord Foundation, Skåne University Hospital, the Scania county, governmental funding of clinical research within the Swedish National Health Service, a generous donation from the Knut and Alice Wallenberg foundation to the Wallenberg Center for Molecular Medicine in Lund, and funding from the Swedish Research Council (Linnaeus grant Dnr 349-2006-237, Strategic Research Area Exodiab Dnr 2009-1039) and Swedish Foundation for Strategic Research (Dnr IRC15- 0067) to the Lund University Diabetes Center. The Malmo Diet and Cancer Study was made possible by grants from the Swedish Cancer Society, the Swedish Medical Research Council, the Swedish Dairy Association, and the Malmo city council. Penn Heart Failure Study (PHFS) The study was supported by NIH grants (NIH R01L088577 and NIH R01H105993). Prevention of REnal and Vascular ENd-stage Disease (PREVEND) The Prevention of Renal and Vascular Endstage Disease Study (PREVEND) genetics is supported by the Dutch Kidney Foundation (Grant E033), the EU project grant GENECURE (FP-6 LSHM CT 2006 037697), the National Institutes of Health (grant LM010098), the Netherlands organisation for health research and development (NWO VENI grant 916.761.70), and the Dutch Inter University Cardiology Institute Netherlands (ICIN). Niek Verweij was supported by NWO VENI grant 016.186.125. PROspective Study of Pravastatin in the Elderly at Risk for vascular disease (PROSPER)The PROSPER study was supported by an investigator-initiated grant obtained from Bristol- Myers Squibb. Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). J.W.J. is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Study of Health in Pomerania (SHIP) SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. Stabilization of Plaque using Darapladib-Thrombolysis in Myocardial Infarction 52 (SOLID)SOLID-TIMI 52 was funded by GlaxoSmithKline. TwinGene (TwinGene) TwinGene received funding from the Swedish Research Council (M-2005-1112), GenomEUtwin (EU/QLRT-2001-01254, QLG2-CT-2002-01254), NIH DK U01-066134, The Swedish Foundation for Strategic Research (SSF) and the Heart and Lung foundation no. 20070481. TwinGene is part of the Swedish Twin Registry which is managed by Karolinska Institutet and receives funding through the Swedish Research Council (2017–00641). UK Biobank (UKBiobank) This research has been conducted using the UK Biobank Resource under Application Number 15422. This work was supported in part by grants to R.T.L. from the EU/EFPIA Innovative Medicines Initiative 2 Joint Undertaking BigData@Heart grant no. 116074, MRC Proximity to Discovery Award Scheme, the American Heart Association Institute for Precision Mecidine, Pfizer Ltd, the University College London British Heart Foundation Research Accelerator (AA/18/6/34223), and was supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. A. H. is supported by the British Heart Foundation Cardiovascular Biomedicine PhD studentship. R.T.L is supported by a UK Research and Innovation Rutherford Fellowship and was previously supported by a National Institutes of Health Research Clinical Lectureship. Uppsala Longitudinal Study of Adult Men (ULSAM) J.Ä. is supported by the Swedish Research Council and the Swedish Heart Lung foundation. C.M.L is supported by the Li Ka Shing Foundation, WT-SSI/John Fell funds and by the NIHR Biomedical Research Centre, Oxford, by Widenlife and NIH (5P50HD028138- 27). Women’s Genome Health Study (WGHS) The WGHS is supported by the National Heart, Lung, and Blood Institute (HL043851 and HL080467, HL099355) and the National Cancer Institute (CA047988 and UM1CA182913), with collaborative scientific support and funding for genotyping provided by Amgen., Epidemiology, Internal Medicine, Læknadeild (HÍ), Faculty of Medicine (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Engineering and Natural Sciences (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, and University of Iceland
Subjects: 0301 basic medicine, Dánartíðni, Epidemiology, LOCI, 45/43, General Physics and Astronomy, Muscle Proteins, Genome-wide association study, Disease, Coronary Artery Disease, 030204 cardiovascular system & hematology, Bioinformatics, Genome-wide association studies, DISEASE, Ventricular Function, Left, Coronary artery disease, 0302 clinical medicine, Risk Factors, Atrial Fibrillation, IMPUTATION, Medicine, Blóðrásarsjúkdómar, 692/308/174, lcsh:Science, 2. Zero hunger, RISK, Multidisciplinary, Microfilament Proteins, article, Atrial fibrillation, Mendelian Randomization Analysis, CATALOG, 3. Good health, OBESITY, Erfðarannsóknir, Cardiomyopathies, Medical Genetics, Cyclin-Dependent Kinase Inhibitor p21, Science, 631/208/205/2138, Heart failure, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 631/443/592/2727, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, RESOURCE, Humans, Mortality, METAANALYSIS, Genetic association, Medicinsk genetik, Adaptor Proteins, Signal Transducing, Heart Failure, HYPERTENSION, business.industry, Case-control study, Klinisk medicin, 692/699/75/230, General Chemistry, Cardiovascular genetics, medicine.disease, R1, 030104 developmental biology, Case-Control Studies, lcsh:Q, Morbidity, Clinical Medicine, business, Apoptosis Regulatory Proteins, Carrier Proteins, Genome-Wide Association Study
Abstract: Publisher's version (útgefin grein), Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies., We acknowledge the contribution from the EchoGen Consortium.
Published: 2020
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10. Lipids, Lipoproteins, and Metabolites and Risk of Myocardial Infarction and Stroke

Author: Holmes, Michael V., Millwood, Iona Y., Kartsonaki, Christiana, Hill, Michael R., Bennett, Derrick A., Boxall, Ruth, Guo, Yu, Xu, Xin, Bian, Zheng, Hu, Ruying, Walters, Robin G., Chen, Junshi, Ala-Korpela, Mika, Parish, Sarah, Clarke, Robert J., Peto, Richard, Collins, Rory, Li, Liming, and Chen, Zhengming
Subjects: Adult, Male, CKB, China Kadoorie Biobank, etiology, BMI, body mass index, Lipoproteins, Myocardial Infarction, IS, ischemic stroke, CVD, cardiovascular disease, CHD, coronary heart disease, Article, Cohort Studies, HDL-C, high-density lipoprotein cholesterol, IDL, intermediate-density lipoprotein, Risk Factors, ischemic stroke, Humans, VLDL, very low-density lipoprotein, Prospective Studies, NMR, nuclear magnetic resonance, RCT, randomized controlled trial, Aged, PCI, percutaneous coronary intervention, SBP, systolic blood pressure, IHD, ischemic heart disease, Cholesterol, HDL, Cholesterol, LDL, Middle Aged, TG, triglycerides, Lipid Metabolism, intracerebral hemorrhage, metabolomics, Lipids, CI, confidence interval, Stroke, myocardial infarction, Cardiovascular Diseases, Case-Control Studies, MI, myocardial infarction, Female, lipids (amino acids, peptides, and proteins), epidemiology, LDL-C, low-density lipoprotein cholesterol, Biomarkers, CABG, coronary artery bypass grafting
Abstract: Background Blood lipids are established risk factors for myocardial infarction (MI), but uncertainty persists about the relevance of lipids, lipoprotein particles, and circulating metabolites for MI and stroke subtypes. Objectives This study sought to investigate the associations of plasma metabolic markers with risks of incident MI, ischemic stroke (IS), and intracerebral hemorrhage (ICH). Methods In a nested case-control study (912 MI, 1,146 IS, and 1,138 ICH cases, and 1,466 common control subjects) 30 to 79 years of age in China Kadoorie Biobank, nuclear magnetic resonance spectroscopy measured 225 metabolic markers in baseline plasma samples. Logistic regression was used to estimate adjusted odds ratios (ORs) for a 1-SD higher metabolic marker. Results Very low-, intermediate-, and low-density lipoprotein particles were positively associated with MI and IS. High-density lipoprotein (HDL) particles were inversely associated with MI apart from small HDL. In contrast, no lipoprotein particles were associated with ICH. Cholesterol in large HDL was inversely associated with MI and IS (OR: 0.79 and 0.88, respectively), whereas cholesterol in small HDL was not (OR: 0.99 and 1.06, respectively). Triglycerides within all lipoproteins, including most HDL particles, were positively associated with MI, with a similar pattern for IS. Glycoprotein acetyls, ketone bodies, glucose, and docosahexaenoic acid were associated with all 3 diseases. The 225 metabolic markers showed concordant associations between MI and IS, but not with ICH. Conclusions Lipoproteins and lipids showed similar associations with MI and IS, but not with ICH. Within HDL particles, cholesterol concentrations were inversely associated, whereas triglyceride concentrations were positively associated with MI. Glycoprotein acetyls and several non–lipid-related metabolites associated with all 3 diseases., Central Illustration
Published: 2018
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11. Association of physical activity with risk of hepatobiliary diseases in China: a prospective cohort study of 0.5 million people.

Author: Yuanjie Pang, Jun Lv, Kartsonaki, Christiana, Canqing Yu, Yu Guo, Huaidong Du, Bennett, Derrick, Zheng Bian, Yiping Chen, Ling Yang, Turnbull, Iain, Hao Wang, Hui Li, Holmes, Michael V., Junshi Chen, Zhengming Chen, Liming Li, Pang, Yuanjie, Lv, Jun, and Yu, Canqing
Subjects: GALLBLADDER cancer, FATTY liver, PHYSICAL activity, NON-alcoholic fatty liver disease, BILIARY tract cancer, METABOLIC equivalent, GALLSTONES
Abstract: Objective: There is limited prospective evidence on the association of physical activity with hepatobiliary cancer subtypes and other major hepatobiliary diseases, especially in China. We aimed to quantify the associations with risk of these diseases.Methods: The study population involved 460 937 participants of the prospective China Kadoorie Biobank aged 30-79 years from 10 diverse areas in China without history of cancer or hepatobiliary disease at baseline. Cox regression was used to estimate adjusted hazard ratios (HRs) for each disease associated with self-reported total and domain-specific physical activity (occupational and non-occupational, ie, leisure time, household and commuting).Results: During ~10 years of follow-up, 22 012 incident cases of hepatobiliary diseases were recorded. The overall mean (SD) total physical activity was 21.2 (13.9) metabolic equivalent of task (MET)-hours/day, with 62% from occupational activity. Total physical activity was inversely associated with hospitalised non-alcoholic fatty liver disease (HR comparing top vs bottom quintile: 0.62, 95% confidence interval (CI) 0.53 to 0.72), viral hepatitis (0.73, 95% CI 0.62 to 0.87), cirrhosis (0.76, 95% CI 0.66 to 0.88) and liver cancer (0.81, 95% CI 0.71 to 0.93), as well as gallstone disease (0.86, 95% CI 0.81 to 0.90), gallbladder cancer (0.51, 95% CI 0.32 to 0.80) and biliary tract cancer (0.55, 95% CI 0.38 to 0.78). The associations for occupational physical activity were similar to those for total physical activity, but for non-occupational physical activity they differed by disease subtype. For leisure-time physical activity, there was an inverse association with liver cancer and an inverse trend for gallstone disease (HR comparing ≥7.5 MET-hours/day with none: 0.83, 95% CI 0.75 to 0.91 and 0.82, 95% CI 0.66 to 1.01).Conclusion: Among Chinese adults, high total physical activity, particularly occupational physical activity, was inversely associated with risk of major hepatobiliary cancers and diseases, including non-alcoholic fatty liver disease, cirrhosis and certain types of cancer. [ABSTRACT FROM AUTHOR]
Published: 2021
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12. genetic variants and cognitive abilities: a large-scale Mendelian randomization study.

Author: Lyall, Donald M., Ward, Joey, Banach, Maciej, Smith, George Davey, Gill, Jason G., Pell, Jill P., Holmes, Michael V., and Sattar, Naveed
Subjects: COGNITIVE ability, VASCULAR diseases, CHOLESTERYL ester transfer protein, LOW density lipoproteins, COGNITION, CHOLESTEROL
Abstract: Introduction: PCSK9 inhibitors lower low-density lipoprotein (LDL) cholesterol and are efficacious at reducing vascular disease, however questions remain about potential effects on cognitive function.Methods: We examined the association of genetic variants in PCSK9 with continuous measures of cognitive ability in UK Biobank. Six independent polymorphisms in PCSK9 were used in up to 337,348 individuals.Results: The PCSK9 allele score was associated with a lower risk of CHD, and weakly with worse log reaction time.Conclusions: We are unable to rule out meaningful associations of PCSK9 genetic variants with cognition, emphasising the potential need for continued pharmacovigilance for patients currently treated with PCSK9 inhibitors. [ABSTRACT FROM AUTHOR]
Published: 2021
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13. Adult height, coronary heart disease and stroke : A multi-locus Mendelian randomization meta-analysis

Author: Nüesch, Eveline, Dale, Caroline, Palmer, Tom M., White, Jon, Keating, Brendan J., van Iperen, Erik P A, Goel, Anuj, Padmanabhan, Sandosh, Asselbergs, F. W., Verschuren, W. M., Wijmenga, C., Van der Schouw, Y. T., Onland-Moret, N. C., Lange, Leslie A., Hovingh, G. K., Sivapalaratnam, Suthesh, Morris, Richard W., Whincup, Peter H., Wannamethe, Goya S., Gaunt, Tom R., Ebrahim, Shah, Steel, Laura, Nair, Nikhil, Reiner, Alexander P., Kooperberg, Charles, Wilson, James F., Bolton, Jennifer L., McLachlan, Stela, Price, Jacqueline F., Strachan, Mark W J, Robertson, Christine M., Kleber, Marcus E., Delgado, Graciela, März, Winfried, Melander, Olle, Dominiczak, Anna F., Farrall, Martin, Watkins, Hugh, Leusink, Maarten, Maitland-van der Zee, Anke H., de Groot, Mark C H, Dudbridge, Frank, Hingorani, Aroon, Ben-Shlomo, Yoav, Lawlor, Debbie A., Amuzu, A., Caufield, M., Cavadino, A., Cooper, J., Davies, T. L., Day, I. N., Drenos, F., Engmann, J., Finan, C., Giambartolomei, C., Hardy, R., Humphries, S. E., Hypponen, E., Kivimaki, M., Kuh, D., Kumari, M., Ong, K., Plagnol, V., Power, C., Richards, M., Shah, S., Shah, T., Sofat, R., Talmud, P. J., Wareham, N., Warren, H., Whittaker, J. C., Wong, A., Zabaneh, D., Smith, George Davey, Wells, Jonathan C., Leon, David A., Holmes, Michael V., and Casas, Juan P.
Subjects: Medicine(all), procedure, Epidemiology, alleles, Journal Article, body mass index, cerebrovascular accident, triglycerides
Abstract: © The Author 2015; all rights reserved. Background: We investigated causal effect of completed growth, measured by adult height, on coronary heart disease (CHD), stroke and cardiovascular traits, using instrumental variable (IV) Mendelian randomization meta-analysis. Methods: We developed an allele score based on 69 single nucleotide polymorphisms (SNPs) associated with adult height, identified by the IBCCardioChip, and used it for IV analysis against cardiovascular risk factors and events in 21 studies and 60 028 participants. IV analysis on CHD was supplemented by summary data from 180 height-SNPs from the GIANT consortium and their corresponding CHD estimates derived from CARDIoGRAMplusC4D. Results: IV estimates from IBCCardioChip and GIANT-CARDIoGRAMplusC4D showed that a 6.5-cm increase in height reduced the odds of CHD by 10% [odds ratios 0.90; 95% confidence intervals (CIs): 0.78 to 1.03 and 0.85 to 0.95, respectively],which agrees with the estimate from the Emerging Risk Factors Collaboration (hazard ratio 0.93; 95% CI: 0.91 to 0.94). IV analysis revealed no association with stroke (odds ratio 0.97; 95% CI: 0.79 to 1.19). IV analysis showed that a 6.5-cm increase in height resulted in lower levels of body mass index (P < 0.001), triglycerides (P < 0.001), non high-density (non-HDL) cholesterol (P < 0.001), C-reactive protein (P = 0.042), and systolic blood pressure (P = 0.064) and higher levels of forced expiratory volume in 1 s and forced vital capacity (P < 0.001 for both). Conclusions: Taller individuals have a lower risk of CHD with potential explanations being that taller people have a better lung function and lower levels of body mass index, cholesterol and blood pressure.
Published: 2016

14. Mendelian randomization of blood lipids for coronary heart disease

Author: Holmes, Michael V, Asselbergs, Folkert W, Palmer, Tom M, Drenos, Fotios, Lanktree, Matthew B, Nelson, Christopher P, Dale, Caroline E, Padmanabhan, Sandosh, Finan, Chris, Swerdlow, Daniel I, Tragante, Vinicius, van Iperen, Erik P A, Sivapalaratnam, Suthesh, Shah, Sonia, Elbers, Clara C, Shah, Tina, Engmann, Jorgen, Giambartolomei, Claudia, White, Jon, Zabaneh, Delilah, Sofat, Reecha, McLachlan, Stela, Doevendans, Pieter A, Balmforth, Anthony J, Hall, Alistair S, North, Kari E, Almoguera, Berta, Hoogeveen, Ron C, Cushman, Mary, Fornage, Myriam, Patel, Sanjay R, Redline, Susan, Siscovick, David S, Tsai, Michael Y, Karczewski, Konrad J, Hofker, Marten H, Verschuren, W Monique, Bots, Michiel L, van der Schouw, Yvonne T, Melander, Olle, Dominiczak, Anna F, Morris, Richard, Ben-Shlomo, Yoav, Price, Jackie, Kumari, Meena, Baumert, Jens, Peters, Annette, Thorand, Barbara, Koenig, Wolfgang, Gaunt, Tom R, Center for Liver, Digestive and Metabolic Diseases (CLDM), Vascular Ageing Programme (VAP), APH - Amsterdam Public Health, Epidemiology and Data Science, Graduate School, and Vascular Medicine
Subjects: Epidemiology, VASCULAR-DISEASE, Heart disease, Lipids, TRIALS, ATHEROSCLEROSIS, GENETIC-VARIANTS, Mendelian randomization, INSTRUMENTAL VARIABLES, RISK-FACTORS, lipids (amino acids, peptides, and proteins), Aetiology, CHOLESTEROL LEVELS, CARDIOVASCULAR EVENTS, HIGH-DENSITY-LIPOPROTEIN, METAANALYSIS
Abstract: AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75).CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.
Published: 2015
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15. Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics.

Author: Tynkkynen, Tuulia, Wang, Qin, Ekholm, Jussi, Anufrieva, Olga, Ohukainen, Pauli, Vepsäläinen, Jouko, Männikkö, Minna, Keinänen-Kiukaanniemi, Sirkka, Holmes, Michael V, Goodwin, Matthew, Ring, Susan, Chambers, John C, Kooner, Jaspal, Järvelin, Marjo-Riitta, Kettunen, Johannes, Hill, Michael, Smith, George Davey, Ala-Korpela, Mika, and Davey Smith, George
Subjects: NUCLEAR magnetic resonance spectroscopy, URINE, PROOF of concept, GENETICS, PIPELINES, EPIDEMIOLOGY, BIOCHEMISTRY, COMPARATIVE studies, EPIDEMIOLOGICAL research, RESEARCH methodology, MEDICAL cooperation, RESEARCH, RESEARCH funding, EVALUATION research, SEQUENCE analysis
Abstract: Background: Quantitative molecular data from urine are rare in epidemiology and genetics. NMR spectroscopy could provide these data in high throughput, and it has already been applied in epidemiological settings to analyse urine samples. However, quantitative protocols for large-scale applications are not available.Methods: We describe in detail how to prepare urine samples and perform NMR experiments to obtain quantitative metabolic information. Semi-automated quantitative line shape fitting analyses were set up for 43 metabolites and applied to data from various analytical test samples and from 1004 individuals from a population-based epidemiological cohort. Novel analyses on how urine metabolites associate with quantitative serum NMR metabolomics data (61 metabolic measures; n = 995) were performed. In addition, confirmatory genome-wide analyses of urine metabolites were conducted (n = 578). The fully automated quantitative regression-based spectral analysis is demonstrated for creatinine and glucose (n = 4548).Results: Intra-assay metabolite variations were mostly <5%, indicating high robustness and accuracy of urine NMR spectroscopy methodology per se. Intra-individual metabolite variations were large, ranging from 6% to 194%. However, population-based inter-individual metabolite variations were even larger (from 14% to 1655%), providing a sound base for epidemiological applications. Metabolic associations between urine and serum were found to be clearly weaker than those within serum and within urine, indicating that urinary metabolomics data provide independent metabolic information. Two previous genome-wide hits for formate and 2-hydroxyisobutyrate were replicated at genome-wide significance.Conclusion: Quantitative urine metabolomics data suggest broad novelty for systems epidemiology. A roadmap for an open access methodology is provided. [ABSTRACT FROM AUTHOR]
Published: 2019
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16. Mendelian randomization of blood lipids for coronary heart disease

Author: Holmes, Michael V., Asselbergs, Folkert W., Palmer, Tom M., Drenos, Fotios, Lanktree, Matthew B., Nelson, Christopher P., Dale, Caroline E., Padmanabhan, Sandosh, Finan, Chris, Swerdlow, Daniel I., Tragante, Vinicius, van Iperen, Erik P.A., Sivapalaratnam, Suthesh, Shah, Sonia, Elbers, Clara C., Shah, Tina, Engmann, Jorgen, Giambartolomei, Claudia, White, Jon, Zabaneh, Delilah, Sofat, Reecha, McLachlan, Stela, Doevendans, Pieter A., Balmforth, Anthony J., Hall, Alistair S., North, Kari E., Almoguera, Berta, Hoogeveen, Ron C., Cushman, Mary, Fornage, Myriam, Patel, Sanjay R., Redline, Susan, Siscovick, David S., Tsai, Michael Y., Karczewski, Konrad J., Hofker, Marten H., Verschuren, W. Monique, Bots, Michiel L., van der Schouw, Yvonne T., Melander, Olle, Dominiczak, Anna F., Morris, Richard, Ben-Shlomo, Yoav, Price, Jackie, Kumari, Meena, Baumert, Jens, Peters, Annette, Thorand, Barbara, Koenig, Wolfgang, Gaunt, Tom R., Humphries, Steve E., Clarke, Robert, Watkins, Hugh, Farrall, Martin, Wilson, James G., Rich, Stephen S., de Bakker, Paul I.W., Lange, Leslie A., Davey Smith, George, Reiner, Alex P., Talmud, Philippa J., Kivimäki, Mika, Lawlor, Debbie A., Dudbridge, Frank, Samani, Nilesh J., Keating, Brendan J., Hingorani, Aroon D., and Casas, Juan P.
Subjects: Male, Cardiac & Cardiovascular Systems, Genotype, Genotyping Techniques, Epidemiology, Coronary Artery Disease, Heart disease, 1102 Cardiovascular Medicine And Haematology, Polymorphism, Single Nucleotide, Risk Assessment, Gene Frequency, Clinical Research, GENETIC-VARIANTS, INSTRUMENTAL VARIABLES, Mendelian randomization, Humans, Cardiac and Cardiovascular Systems, CHOLESTEROL LEVELS, Aetiology, CARDIOVASCULAR EVENTS, METAANALYSIS, Triglycerides, Science & Technology, Cholesterol, HDL, VASCULAR-DISEASE, UCLEB consortium, Mendelian Randomization Analysis, Middle Aged, Heart Disease, Lipids, Mendelian Randomization, TRIALS, ATHEROSCLEROSIS, Cardiovascular System & Hematology, Case-Control Studies, Cardiovascular System & Cardiology, RISK-FACTORS, Female, lipids (amino acids, peptides, and proteins), Cardiology and Cardiovascular Medicine, Life Sciences & Biomedicine, HIGH-DENSITY-LIPOPROTEIN
Abstract: Aims To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. Methods and results We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10−6); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). Conclusion The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain. M.V.H. was funded by a UK Medical Research Council Population Health Scientist Fellowship (G0802432). F.W.A. is supported by UCL Hospitals NIHR Biomedical Research Centre. D.I.S. is supported by a Medical Research Council Doctoral Training Award and a grant from the Rosetrees Foundation. ME.K. is supported by the National Institute of Aging and the National Heart, Lung and Blood Institute (HL36310). S.E.H. and P.J.T. are supported by the British Heart Foundation (BHF RG 08/008, PG/07/133/24260), UK Medical Research Council, the US National Institutes of Health (grant NHLBI 33014) and Du Pont Pharma, Wilmington, USA. N.J.S. holds a Chair funded by the British Heart Foundation and is an NIHR Senior Investigator. MI.K. is supported by the National Institute of Aging, the Medical Research Council, the British Heart Foundation, and the National Heart, Lung and Blood Institute and the Academy of Finland. A.D.H. and J.P.C. are supported by the National Institute of Health Research University College London Hospitals Biomedical Research Centre. Funding to pay the Open Access publication charges for this article was provided by RCUK.
Published: 2014

17. Secretory phospholipase A(2)-IIA and cardiovascular disease: a mendelian randomization study

Author: Holmes, Michael V., Simon, Tabassome, Exeter, Holly J., Folkersen, Lasse, Asselbergs, Folkert W., Guardiola, Montse, Cooper, Jackie A., Palmen, Jutta, Hubacek, Jaroslav A., Carruthers, Kathryn F., Horne, Benjamin D., Brunisholz, Kimberly D., Mega, Jessica L., van Iperen, Erik P. A., Li, Mingyao, Leusink, Maarten, Trompet, Stella, Verschuren, Jeffrey J. W., Hovingh, G. Kees, Dehghan, Abbas, Nelson, Christopher P., Kotti, Salma, Danchin, Nicolas, Scholz, Markus, Haase, Christiane L., Rothenbacher, Dietrich, Swerdlow, Daniel I., Kuchenbaecker, Karoline B., Staines-Urias, Eleonora, Goel, Anuj, van 't Hooft, Ferdinand, Gertow, Karl, de Faire, Ulf, Panayiotou, Andrie G., Tremoli, Elena, Baldassarre, Damiano, Veglia, Fabrizio, Holdt, Lesca M., Beutner, Frank, Gansevoort, Ron T., Navis, Gerjan J., Mateo Leach, Irene, Breitling, Lutz P., Brenner, Hermann, Thiery, Joachim, Dallmeier, Dhayana, Franco-Cereceda, Anders, Boer, Jolanda M. A., Stephens, Jeffrey W., Hofker, Marten H., Tedgui, Alain, Hofman, Albert, Uitterlinden, André G., Adamkova, Vera, Pitha, Jan, Onland-Moret, N. Charlotte, Cramer, Maarten J., Nathoe, Hendrik M., Spiering, Wilko, Klungel, Olaf H., Kumari, Meena, Whincup, Peter H., Morrow, David A., Braund, Peter S., Hall, Alistair S., Olsson, Anders G., Doevendans, Pieter A., Trip, Mieke D., Tobin, Martin D., Hamsten, Anders, Watkins, Hugh, Koenig, Wolfgang, Nicolaides, Andrew N., Teupser, Daniel, Day, Ian N. M., Carlquist, John F., Gaunt, Tom R., Ford, Ian, Sattar, Naveed, Tsimikas, Sotirios, Schwartz, Gregory G., Lawlor, Debbie A., Morris, Richard W., Sandhu, Manjinder S., Poledne, Rudolf, Maitland-van der Zee, Anke H., Khaw, Kay-Tee, Keating, Brendan J., van der Harst, Pim, Price, Jackie F., Mehta, Shamir R., Yusuf, Salim, Witteman, Jaqueline C. M., Franco, Oscar H., Jukema, J. Wouter, de Knijff, Peter, Tybjaerg-Hansen, Anne, Rader, Daniel J., Farrall, Martin, Samani, Nilesh J., Kivimaki, Mika, Fox, Keith A. A., Humphries, Steve E., Anderson, Jeffrey L., Boekholdt, S. Matthijs, Palmer, Tom M., Eriksson, Per, Paré, Guillaume, Hingorani, Aroon D., Sabatine, Marc S., Mallat, Ziad, Casas, Juan P., Talmud, Philippa J., Amsterdam Public Health, Epidemiology and Data Science, Graduate School, Amsterdam Cardiovascular Sciences, Vascular Medicine, Cardiology, and Pulmonology
Subjects: RISK, ACUTE CORONARY SYNDROMES, INHIBITOR, SERUM-LEVELS, HEALTHY-MEN, drug development, EPIC-NORFOLK, cardiovascular diseases, EVENTS, Mendelian randomization, MENDELIAN RANDOMIZATION, ARTERY-DISEASE, epidemiology, genetics, TRIAL
Abstract: OBJECTIVES: This study sought to investigate the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease.BACKGROUND: Higher circulating levels of sPLA2-IIA mass or sPLA2 enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA2 inhibitor (varespladib) was stopped prematurely for lack of efficacy.METHODS: We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA2-IIA isoenzyme, as an instrumental variable.RESULTS: PLA2G2A rs11573156 C allele associated with lower circulating sPLA2-IIA mass (38% to 44%) and sPLA2 enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA2-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE.CONCLUSIONS: Reducing sPLA2-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events.
Published: 2013
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18. Mendelian randomisation in cardiovascular research: an introduction for clinicians.

Author: Bennett, Derrick A. and Holmes, Michael V.
Subjects: CARDIOVASCULAR disease treatment, MEDICAL personnel, BIOMARKERS, RANDOMIZED controlled trials, CORONARY disease, CARDIOVASCULAR diseases, MEDICAL research
Abstract: Understanding the causal role of biomarkers in cardiovascular and other diseases is crucial in order to find effective approaches (including pharmacological therapies) for disease treatment and prevention. Classical observational studies provide naïve estimates of the likely role of biomarkers in disease development; however, such studies are prone to bias. This has direct relevance for drug development as if drug targets track to non-causal biomarkers, this can lead to expensive failure of these drugs in phase III randomised controlled trials. In an effort to provide a more reliable indication of the likely causal role of a biomarker in the development of disease, Mendelian randomisation studies are increasingly used, and this is facilitated by the availability of large-scale genetic data. We conducted a narrative review in order to provide a description of the utility of Mendelian randomisation for clinicians engaged in cardiovascular research. We describe the rationale and provide a basic description of the methods and potential limitations of Mendelian randomisation. We give examples from the literature where Mendelian randomisation has provided pivotal information for drug discovery including predicting efficacy, informing on target-mediated adverse effects and providing potential new evidence for drug repurposing. The variety of the examples presented illustrates the importance of Mendelian randomisation in order to prioritise drug targets for cardiovascular research. [ABSTRACT FROM AUTHOR]
Published: 2017
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19. Secretory Phospholipase A2-IIA and Cardiovascular Disease: A Mendelian Randomization Study.

Author: Holmes, Michael V., Simon, Tabassome, Exeter, Holly J., Folkersen, Lasse, Asselbergs, Folkert W., Guardiola, Montse, Cooper, Jackie A., Palmen, Jutta, Hubacek, Jaroslav A., Carruthers, Kathryn F., Horne, Benjamin D., Brunisholz, Kimberly D., Mega, Jessica L., van Iperen, Erik P.A., Li, Mingyao, Leusink, Maarten, Trompet, Stella, Verschuren, Jeffrey J.W., Hovingh, G. Kees, and Dehghan, Abbas
Subjects: *PHOSPHOLIPASE A2, *CARDIOVASCULAR diseases risk factors, *META-analysis, *ACUTE coronary syndrome, *COHORT analysis, *ISOENZYMES
Abstract: Objectives: This study sought to investigate the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease. Background: Higher circulating levels of sPLA2-IIA mass or sPLA2 enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA2 inhibitor (varespladib) was stopped prematurely for lack of efficacy. Methods: We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA2-IIA isoenzyme, as an instrumental variable. Results: PLA2G2A rs11573156 C allele associated with lower circulating sPLA2-IIA mass (38% to 44%) and sPLA2 enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA2-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE. Conclusions: Reducing sPLA2-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events. [Copyright &y& Elsevier]
Published: 2013
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20. Population Genomics of Cardiometabolic Traits: Design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium.

Author: Shah, Tina, Engmann, Jorgen, Dale, Caroline, Shah, Sonia, White, Jon, Giambartolomei, Claudia, McLachlan, Stela, Zabaneh, Delilah, Cavadino, Alana, Finan, Chris, Wong, Andrew, Amuzu, Antoinette, Ong, Ken, Gaunt, Tom, Holmes, Michael V., Warren, Helen, Davies, Teri-Louise, Drenos, Fotios, Cooper, Jackie, and Sofat, Reecha
Subjects: METAGENOMICS, CARDIOVASCULAR diseases, SINGLE nucleotide polymorphisms, HEALTH outcome assessment
Abstract: Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies. [ABSTRACT FROM AUTHOR]
Published: 2013
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21. Genome wide association studies of abdominal aortic aneurysms—Biological insights and potential translation applications

Author: Harrison, Seamus C., Holmes, Michael V., Agu, Obi, and Humphries, Steve E.
Subjects: *AORTIC aneurysms, *GENETIC disorders, *NUCLEOTIDES, *DISEASE risk factors, *EPIDEMIOLOGY, *GENETIC polymorphisms
Abstract: Abstract: Abdominal aortic aneurysm (AAA) is a complex disease with important environmental risk factors and a heritability of approximately 70%. Genome wide association studies have revolutionised the study of complex disorders and offer the potential for innovative insight into disease pathogenesis and development of individualised therapeutic options. This paper reviews the progress of genome wide association studies in AAA, highlighting novel disease pathways and potential translational applications of genomic discoveries. [Copyright &y& Elsevier]
Published: 2011
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22. Gene-centric Meta-analysis in 87,736 Individuals of European Ancestry Identifies Multiple Blood-Pressure-Related Loci

Author: Tragante, Vinicius, Barnes, Michael R., Ganesh, Santhi K., Lanktree, Matthew B., Guo, Wei, Franceschini, Nora, Smith, Erin N., Johnson, Toby, Holmes, Michael V., Padmanabhan, Sandosh, Karczewski, Konrad J., Almoguera, Berta, Barnard, John, Baumert, Jens, Chang, Yen-Pei Christy, Elbers, Clara C., Farrall, Martin, Fischer, Mary E., Gaunt, Tom R., Gho, Johannes M. I. H., Gieger, Christian, Goel, Anuj, Gong, Yan, Isaacs, Aaron, Kleber, Marcus E., Leach, Irene Mateo, McDonough, Caitrin W., Meijs, Matthijs F. L., Melander, Olle, Nelson, Christopher P., Nolte, Ilja M., Pankratz, Nathan, Price, Tom S., Shaffer, Jonathan, Shah, Sonia, Tomaszewski, Maciej, Van Der Most, Peter J., Van Iperen, Erik P. A., Vonk, Judith M., Witkowska, Kate, Wong, Caroline O. L., Zhang, Li, Beitelshees, Amber L., Berenson, Gerald S., Bhatt, Deepak L., Brown, Morris, Burt, Amber, Cooper-DeHoff, Rhonda M., Connell, John M., Cruickshanks, Karen J., Curtis, Sean P., Davey-Smith, George, Delles, Christian, Gansevoort, Ron T., Guo, Xiuqing, Haiqing, Shen, Hastie, Claire E., Hofker, Marten H., Hovingh, G. Kees, Kim, Daniel S., Kirkland, Susan A., Klein, Barbara E., Klein, Ronald, Li, Yun R., Maiwald, Steffi, Newton-Cheh, Christopher, O’Brien, Eoin T., Onland-Moret, N. Charlotte, Palmas, Walter R., Parsa, Afshin, Penninx, Brenda W., Pettinger, Mary, Vasan, Ramachandran S., Ranchalis, Jane E., Ridker, Paul M., Rose, Lynda M., Sever, Peter, Shimbo, Daichi, Steele, Laura, Stolk, Ronald P., Thorand, Barbara, Trip, Mieke D., Van Duijn, Cornelia M., Verschuren, W. Monique, Wijmenga, Cisca, Wyatt, Sharon, Young, J. Hunter, Zwinderman, Aeilko H., Bezzina, Connie R., Boerwinkle, Eric, Casas, Juan P., Caulfield, Mark J., Chakravarti, Aravinda, Chasman, Daniel I., Davidson, Karina W., Doevendans, Pieter A., Dominiczak, Anna F., FitzGerald, Garret A., Gums, John G., Fornage, Myriam, Hakonarson, Hakon, Halder, Indrani, Hillege, Hans L., Illig, Thomas, Jarvik, Gail P., Johnson, Julie A., Kastelein, John J. P., Koenig, Wolfgang, Kumari, Meena, Marz, Winfried, Murray, Sarah S., O’Connell, Jeffrey R., Oldehinkel, Albertine J., Pankow, James S., Rader, Daniel J., Redline, Susan, Reilly, Muredach P., Schadt, Eric E., Kottke-Marchant, Kandice, Snieder, Harold, Snyder, Michael, Stanton, Alice V., Tobin, Martin D., Uitterlinden, Andre G., Van Der Harst, Pim, Van Der Schouw, Yvonne T., Samani, Nilesh J., Watkins, Hugh, Johnson, Andrew D., Reiner, Alex P., Zhu, Xiaofeng, De Bakker, Paul I. W., Levy, Daniel, Asselbergs, Folkert W., Munroe, Patricia B., and Keating, Brendan J.
Subjects: Meta-analysis, Epidemiology, Molecular biology, FOS: Biological sciences, Blood pressure, Genetics, Human genetics--Research, 3. Good health
Abstract: Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ∼50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10−7) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.

23. Genetic analysis of emerging risk factors in coronary artery disease.

Author: van Iperen, Erik P.A., Sivapalaratnam, Suthesh, Holmes, Michael V., Hovingh, G. Kees, Zwinderman, Aeilko H., and Asselbergs, Folkert W.
Subjects: *CORONARY heart disease risk factors, *CORONARY disease, *LOW density lipoproteins, *BODY mass index, *BLOOD pressure, *GENETICS
Abstract: Background and aims Type 2 diabetes (T2D), low-density lipoprotein-cholesterol (LDL-c), body mass index (BMI), blood pressure and smoking are established risk factors that play a causal role in coronary artery disease (CAD). Numerous common genetic variants associating with these and other risk factors have been identified, but their association with CAD has not been comprehensively examined in a single study. Our goal was to comprehensively evaluate the associations of established and emerging risk factors with CAD using genetic variants identified from Genome-wide Association Studies (GWAS). Methods We tested the effect of 60 traditional and putative risk factors with CAD, using summary statistics obtained in GWAS. We approximated the regression of a response variable onto an additive multi-SNP genetic risk score in the Coronary Artery DIsease Genomewide Replication And Meta-analysis (CARDIoGRAM) consortium dataset weighted by the effect of the SNP on the risk factors. Results The strongest association with risk of CAD was for LDL-c SNPs ( p = 3.96E-34 ). For non-e stablished CAD risk factors, we found significant CAD associations for coronary artery calcification (CAC), Lp(a), LP-PLA2 activity, plaque, vWF and FVIII. In an attempt to identify independent associations between risk factors and CAD, only SNPs with an effect on the target trait were included. This identified CAD associations for Lp(a)( p = 1.77E-21), LDL-c ( p = 4.16E-06), triglycerides (TG) ( p = 1.94E-05), height ( p = 2.06E-05), CAC ( p = 3.13E-23) and carotid plaque ( p = 2.08E-05). Conclusions We identified SNPs associated with the emerging risk factors Lp(a), TG, plaque, height and CAC to be independently associated with risk of CAD. This provides further support for-ongoing clinical trials of Lp(a) and TG, and suggests that CAC and plaque could be used as surrogate markers for CAD in clinical trials. [ABSTRACT FROM AUTHOR]
Published: 2016
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24. Lipoprotein signatures of cholesteryl ester transfer protein and HMG-CoA reductase inhibition

Author: Qin Wang, Marjo-Riitta Järvelin, Terho Lehtimäki, Veikko Salomaa, Michael V. Holmes, Mika Ala-Korpela, Clare Oliver-Williams, Emanuele Di Angelantonio, Therese Tillin, Adam S. Butterworth, Elias Allara, Mika Kähönen, Johannes Kettunen, Nish Chaturvedi, George Davey Smith, Pauli Ohukainen, Markus Perola, John Danesh, Olli T. Raitakari, Jorma Viikari, Alun D. Hughes, Olga Anufrieva, Research Programs Unit, CAMM - Research Program for Clinical and Molecular Metabolism, University of Helsinki, Lääketieteen ja terveysteknologian tiedekunta - Faculty of Medicine and Health Technology, Tampere University, Holmes, Michael V [0000-0001-6617-0879], Allara, Elias [0000-0002-1634-8330], Ohukainen, Pauli [0000-0002-0919-7204], Oliver-Williams, Clare [0000-0002-3573-2426], Hughes, Alun D [0000-0001-5432-5271], Salomaa, Veikko [0000-0001-7563-5324], Järvelin, Marjo-Riitta [0000-0002-2149-0630], Davey Smith, George [0000-0002-1407-8314], Butterworth, Adam S [0000-0002-6915-9015], Ala-Korpela, Mika [0000-0001-5905-1206], Apollo - University of Cambridge Repository, UNIVERSITY OF OULU, Holmes, Michael V. [0000-0001-6617-0879], Hughes, Alun D. [0000-0001-5432-5271], and Butterworth, Adam S. [0000-0002-6915-9015]
Subjects: Life Sciences & Biomedicine - Other Topics, Male, 0301 basic medicine, Very low-density lipoprotein, Apolipoprotein B, LOCI, Coronary Disease, Biochemistry, Vascular Medicine, DISEASE, Cohort Studies, chemistry.chemical_compound, 0302 clinical medicine, Medicine and Health Sciences, Coronary Heart Disease, EPIDEMIOLOGY, Biology (General), Genetics of disease, 11 Medical and Health Sciences, education.field_of_study, biology, PLASMA, General Neuroscience, CARDIOVASCULAR RISK, Middle Aged, Lipids, Coronary heart disease, Cholesterol, HMG-CoA reductase, Female, lipids (amino acids, peptides, and proteins), General Agricultural and Biological Sciences, Life Sciences & Biomedicine, Research Article, Adult, Biochemistry & Molecular Biology, medicine.medical_specialty, Adolescent, Biolääketieteet - Biomedicine, QH301-705.5, Lipoproteins, Population, Cardiology, General Biochemistry, Genetics and Molecular Biology, LDL, Young Adult, 03 medical and health sciences, MAGNETIC-RESONANCE METABOLOMICS, 07 Agricultural and Veterinary Sciences, Internal medicine, Cholesterylester transfer protein, REVEALS, medicine, Genetics, Humans, GENOME-WIDE ASSOCIATION, education, Biology, Triglycerides, Alleles, Apolipoproteins B, Science & Technology, General Immunology and Microbiology, Triglyceride, Genetic Variation, Biology and Life Sciences, Proteins, Cholesterol, LDL, 06 Biological Sciences, Cholesterol Ester Transfer Proteins, Medical risk factors, 030104 developmental biology, Endocrinology, Apolipoproteins, chemistry, Genetic Loci, Medical Risk Factors, Genetics of Disease, biology.protein, COHORT PROFILE, 1182 Biochemistry, cell and molecular biology, Hydroxymethylglutaryl CoA Reductases, 3111 Biomedicine, Hydroxymethylglutaryl-CoA Reductase Inhibitors, 030217 neurology & neurosurgery, Follow-Up Studies, Developmental Biology, Lipoprotein
Abstract: Cholesteryl ester transfer protein (CETP) inhibition reduces vascular event risk, but confusion surrounds its effects on low-density lipoprotein (LDL) cholesterol. Here, we clarify associations of genetic inhibition of CETP on detailed lipoprotein measures and compare those to genetic inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR). We used an allele associated with lower CETP expression (rs247617) to mimic CETP inhibition and an allele associated with lower HMGCR expression (rs12916) to mimic the well-known effects of statins for comparison. The study consists of 65,427 participants of European ancestries with detailed lipoprotein subclass profiling from nuclear magnetic resonance spectroscopy. Genetic associations were scaled to 10% reduction in relative risk of coronary heart disease (CHD). We also examined observational associations of the lipoprotein subclass measures with risk of incident CHD in 3 population-based cohorts totalling 616 incident cases and 13,564 controls during 8-year follow-up. Genetic inhibition of CETP and HMGCR resulted in near-identical associations with LDL cholesterol concentration estimated by the Friedewald equation. Inhibition of HMGCR had relatively consistent associations on lower cholesterol concentrations across all apolipoprotein B-containing lipoproteins. In contrast, the associations of the inhibition of CETP were stronger on lower remnant and very-low-density lipoprotein (VLDL) cholesterol, but there were no associations on cholesterol concentrations in LDL defined by particle size (diameter 18–26 nm) (−0.02 SD LDL defined by particle size; 95% CI: −0.10 to 0.05 for CETP versus −0.24 SD, 95% CI −0.30 to −0.18 for HMGCR). Inhibition of CETP was strongly associated with lower proportion of triglycerides in all high-density lipoprotein (HDL) particles. In observational analyses, a higher triglyceride composition within HDL subclasses was associated with higher risk of CHD, independently of total cholesterol and triglycerides (strongest hazard ratio per 1 SD higher triglyceride composition in very large HDL 1.35; 95% CI: 1.18–1.54). In conclusion, CETP inhibition does not appear to affect size-specific LDL cholesterol but is likely to lower CHD risk by lowering concentrations of other atherogenic, apolipoprotein B-containing lipoproteins (such as remnant and VLDLs). Inhibition of CETP also lowers triglyceride composition in HDL particles, a phenomenon reflecting combined effects of circulating HDL, triglycerides, and apolipoprotein B-containing particles and is associated with a lower CHD risk in observational analyses. Our results reveal that conventional composite lipid assays may mask heterogeneous effects of emerging lipid-altering therapies., Inhibition of cholesteryl ester transfer protein does not affect size-specific low-density lipoprotein cholesterol, but may lower coronary heart disease risk by lowering cholesterol concentrations in other apolipoprotein-B containing atherogenic lipoproteins, and by lowering triglyceride content of high-density lipoprotein particles.
Published: 2020
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24 results on '"Holmes, Michael, V"'

1. Causal inference in health and disease: a review of the principles and applications of Mendelian randomization.

2. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

3. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data

4. Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci

5. Fibroblast Growth Factor-23 and Risk of Cardiovascular Diseases A Mendelian Randomization Study

6. The physiological paradox: reframing the polypill as a vaccine for cardiovascular disease

7. Circulating insulin-like growth factors and risks of overall, aggressive and early-onset prostate cancer:a collaborative analysis of 20 prospective studies and Mendelian randomization analysis

8. Putting genomics into practice: A new analysis casts doubt on the clinical utility of CYP2C19 genotype testing to help guide antiplatelet prescribing

9. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

10. Lipids, Lipoproteins, and Metabolites and Risk of Myocardial Infarction and Stroke

11. Association of physical activity with risk of hepatobiliary diseases in China: a prospective cohort study of 0.5 million people.

12. genetic variants and cognitive abilities: a large-scale Mendelian randomization study.

13. Adult height, coronary heart disease and stroke : A multi-locus Mendelian randomization meta-analysis

14. Mendelian randomization of blood lipids for coronary heart disease

15. Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics.

16. Mendelian randomization of blood lipids for coronary heart disease

17. Secretory phospholipase A(2)-IIA and cardiovascular disease: a mendelian randomization study

18. Mendelian randomisation in cardiovascular research: an introduction for clinicians.

19. Secretory Phospholipase A2-IIA and Cardiovascular Disease: A Mendelian Randomization Study.

20. Population Genomics of Cardiometabolic Traits: Design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium.

21. Genome wide association studies of abdominal aortic aneurysms—Biological insights and potential translation applications

22. Gene-centric Meta-analysis in 87,736 Individuals of European Ancestry Identifies Multiple Blood-Pressure-Related Loci

23. Genetic analysis of emerging risk factors in coronary artery disease.

24. Lipoprotein signatures of cholesteryl ester transfer protein and HMG-CoA reductase inhibition

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24 results on '"Holmes, Michael, V"'

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