Jie V Zhao1, C Mary Schooling2,3. 1. School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 1/F, Patrick Manson Building, 7 Sassoon Road, Hong Kong, China. janezhao@hku.hk. 2. School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 1/F, Patrick Manson Building, 7 Sassoon Road, Hong Kong, China. 3. School of Public Health and Health Policy, City University of New York, New York, NY, USA.
Abstract
BACKGROUND: Angiotensin-converting enzyme (ACE) inhibitors and/or in combination with calcium channel blockers (CCBs) are generally recommended as the first-line antihypertensive therapy for people with hypertension and kidney dysfunction. Evidence from large randomized controlled trials comprehensively comparing renal effects of different classes of antihypertensive drugs is lacking. METHODS: We used a Mendelian randomization study to obtain unconfounded associations of genetic proxies for antihypertensives with kidney function. Specifically, we used published genetic variants in genes regulating target proteins of these drugs and then applied to a meta-analysis of the largest available genome-wide association studies of kidney function (estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (UACR), and albuminuria). Inverse variance weighting was used as the main analysis and to combine estimates from different sources. RESULTS: Genetically predicted ACE inhibition was associated with higher eGFR (effect size 0.06, 95% confidence interval (CI) 0.008, 0.11), while genetic proxies for beta-blockers were associated with lower eGFR (- 0.02, 95% CI - 0.04, - 0.004) when meta-analyzing the UK Biobank and CKDGen. Genetic proxies for CCBs were associated with lower UACR (- 0.15, 95% CI - 0.28, - 0.02) and lower risk of albuminuria (odds ratio 0.58, 95% CI 0.37, 0.90) in CKDGen. The associations were robust to using different analysis methods and different genetic instruments. CONCLUSIONS: Our findings suggest the reno-protective associations of genetically proxied ACE inhibitors and CCBs, while genetic proxies for beta-blockers may be related to lower eGFR. Understanding the underlying mechanisms would be valuable, with implications for drug development and repositioning of treatments for kidney disease.
BACKGROUND:Angiotensin-converting enzyme (ACE) inhibitors and/or in combination with calcium channel blockers (CCBs) are generally recommended as the first-line antihypertensive therapy for people with hypertension and kidney dysfunction. Evidence from large randomized controlled trials comprehensively comparing renal effects of different classes of antihypertensive drugs is lacking. METHODS: We used a Mendelian randomization study to obtain unconfounded associations of genetic proxies for antihypertensives with kidney function. Specifically, we used published genetic variants in genes regulating target proteins of these drugs and then applied to a meta-analysis of the largest available genome-wide association studies of kidney function (estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (UACR), and albuminuria). Inverse variance weighting was used as the main analysis and to combine estimates from different sources. RESULTS: Genetically predicted ACE inhibition was associated with higher eGFR (effect size 0.06, 95% confidence interval (CI) 0.008, 0.11), while genetic proxies for beta-blockers were associated with lower eGFR (- 0.02, 95% CI - 0.04, - 0.004) when meta-analyzing the UK Biobank and CKDGen. Genetic proxies for CCBs were associated with lower UACR (- 0.15, 95% CI - 0.28, - 0.02) and lower risk of albuminuria (odds ratio 0.58, 95% CI 0.37, 0.90) in CKDGen. The associations were robust to using different analysis methods and different genetic instruments. CONCLUSIONS: Our findings suggest the reno-protective associations of genetically proxied ACE inhibitors and CCBs, while genetic proxies for beta-blockers may be related to lower eGFR. Understanding the underlying mechanisms would be valuable, with implications for drug development and repositioning of treatments for kidney disease.
Authors: P Ruggenenti; A Perna; G Gherardi; G Garini; C Zoccali; M Salvadori; F Scolari; F P Schena; G Remuzzi Journal: Lancet Date: 1999-07-31 Impact factor: 79.321
Authors: Brian A Ference; John J P Kastelein; Kausik K Ray; Henry N Ginsberg; M John Chapman; Chris J Packard; Ulrich Laufs; Clare Oliver-Williams; Angela M Wood; Adam S Butterworth; Emanuele Di Angelantonio; John Danesh; Stephen J Nicholls; Deepak L Bhatt; Marc S Sabatine; Alberico L Catapano Journal: JAMA Date: 2019-01-29 Impact factor: 56.272
Authors: Jie V Zhao; Fangchao Liu; C Mary Schooling; Jianxin Li; Dongfeng Gu; Xiangfeng Lu Journal: Diabetologia Date: 2022-01-26 Impact factor: 10.122