Jie V Zhao1, Fangchao Liu2, C Mary Schooling3,4, Jianxin Li2, Dongfeng Gu2,5, Xiangfeng Lu6. 1. School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China. janezhao@hku.hk. 2. Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 3. School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China. 4. School of Public Health and Health Policy, City University of New York, New York, NY, USA. 5. Shenzhen Key Laboratory of Cardiovascular Health and Precision Medicine, Southern University of Science and Technology, Shenzhen, China. 6. Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. luxf@pumc.edu.cn.
Abstract
AIMS/HYPOTHESIS: Diabetes and hyperlipidaemia are common comorbidities in people with hypertension. Despite similar protective effects on CVD, different classes of antihypertensive drugs have different effects on CVD risk factors, including diabetes, glucose metabolism and lipids. However, these pleiotropic effects have not been assessed in long-term, large randomised controlled trials, especially for East Asians. METHODS: We used Mendelian randomisation to obtain unconfounded associations of ACE inhibitors, β-blockers (BBs) and calcium channel blockers (CCBs). Specifically, we used genetic variants in drug target genes and related to systolic BP in Europeans and East Asians, and applied them to the largest available genome-wide association studies of diabetes (74,124 cases and 824,006 controls in Europeans, 77,418 cases and 356,122 controls in East Asians), blood glucose levels, HbA1c, and lipids (LDL-cholesterol, HDL-cholesterol and triacylglycerols) (approximately 0.5 million Europeans and 0.1 million East Asians). We used coronary artery disease (CAD) as a control outcome and used different genetic instruments and analysis methods as sensitivity analyses. RESULTS: As expected, genetically proxied ACE inhibition, BBs and CCBs were related to lower risk of CAD in both ancestries. Genetically proxied ACE inhibition was associated with a lower risk of diabetes (OR 0.85, 95% CI 0.78-0.93), and genetic proxies for BBs were associated with a higher risk of diabetes (OR 1.05, 95% CI 1.02-1.09). The estimates were similar in East Asians, and were corroborated by systematic review and meta-analyses of randomised controlled trials. In both ancestries, genetic proxies for BBs were associated with lower HDL-cholesterol and higher triacylglycerols, and genetic proxies for CCBs were associated with higher LDL-cholesterol. The estimates were robust to the use of different genetic instruments and analytical methods. CONCLUSIONS/ INTERPRETATION: Our findings suggest protective association of genetically proxied ACE inhibition with diabetes, while genetic proxies for BBs and CCBs possibly relate to an unfavourable metabolic profile. Developing a deeper understanding of the pathways underlying these diverse associations would be worthwhile, with implications for drug repositioning as well as optimal CVD prevention and treatment strategies in people with hypertension, diabetes and/or hyperlipidaemia.
AIMS/HYPOTHESIS: Diabetes and hyperlipidaemia are common comorbidities in people with hypertension. Despite similar protective effects on CVD, different classes of antihypertensive drugs have different effects on CVD risk factors, including diabetes, glucose metabolism and lipids. However, these pleiotropic effects have not been assessed in long-term, large randomised controlled trials, especially for East Asians. METHODS: We used Mendelian randomisation to obtain unconfounded associations of ACE inhibitors, β-blockers (BBs) and calcium channel blockers (CCBs). Specifically, we used genetic variants in drug target genes and related to systolic BP in Europeans and East Asians, and applied them to the largest available genome-wide association studies of diabetes (74,124 cases and 824,006 controls in Europeans, 77,418 cases and 356,122 controls in East Asians), blood glucose levels, HbA1c, and lipids (LDL-cholesterol, HDL-cholesterol and triacylglycerols) (approximately 0.5 million Europeans and 0.1 million East Asians). We used coronary artery disease (CAD) as a control outcome and used different genetic instruments and analysis methods as sensitivity analyses. RESULTS: As expected, genetically proxied ACE inhibition, BBs and CCBs were related to lower risk of CAD in both ancestries. Genetically proxied ACE inhibition was associated with a lower risk of diabetes (OR 0.85, 95% CI 0.78-0.93), and genetic proxies for BBs were associated with a higher risk of diabetes (OR 1.05, 95% CI 1.02-1.09). The estimates were similar in East Asians, and were corroborated by systematic review and meta-analyses of randomised controlled trials. In both ancestries, genetic proxies for BBs were associated with lower HDL-cholesterol and higher triacylglycerols, and genetic proxies for CCBs were associated with higher LDL-cholesterol. The estimates were robust to the use of different genetic instruments and analytical methods. CONCLUSIONS/ INTERPRETATION: Our findings suggest protective association of genetically proxied ACE inhibition with diabetes, while genetic proxies for BBs and CCBs possibly relate to an unfavourable metabolic profile. Developing a deeper understanding of the pathways underlying these diverse associations would be worthwhile, with implications for drug repositioning as well as optimal CVD prevention and treatment strategies in people with hypertension, diabetes and/or hyperlipidaemia.
Authors: L Hansson; L H Lindholm; L Niskanen; J Lanke; T Hedner; A Niklason; K Luomanmäki; B Dahlöf; U de Faire; C Mörlin; B E Karlberg; P O Wester; J E Björck Journal: Lancet Date: 1999-02-20 Impact factor: 79.321
Authors: Henry R Black; Barry Davis; Joshua Barzilay; Chuke Nwachuku; Charles Baimbridge; Horia Marginean; Jackson T Wright; Jan Basile; Nathan D Wong; Paul Whelton; Richard A Dart; Udho Thadani Journal: Diabetes Care Date: 2007-11-13 Impact factor: 19.112
Authors: Dipender Gill; Marios K Georgakis; Venexia M Walker; A Floriaan Schmidt; Apostolos Gkatzionis; Daniel F Freitag; Chris Finan; Aroon D Hingorani; Joanna M M Howson; Stephen Burgess; Daniel I Swerdlow; George Davey Smith; Michael V Holmes; Martin Dichgans; Robert A Scott; Jie Zheng; Bruce M Psaty; Neil M Davies Journal: Wellcome Open Res Date: 2021-02-10