Abstract
Background: The chronic kidney disease (CKD) public health burden has not declined as expected with current interventions on treatments focusing only on the disease. This study aims to systematically estimate the causal roles of cardiometabolic risk factors on CKD in Europeans and East Asians using Mendelian randomization (MR). Methods: A total of 45 risk factors with genetic data in Europeans and 17 risk factors in East Asians were identified as exposures from PubMed. A total of 51,672 CKD cases and 958,102 controls in Europeans and 13,093 CKD cases and 238,118 controls of East Asian ancestry were used as outcome for this study. We defined the CKD case by clinical diagnosis or by estimated glomerular filtration rate (eGFR)<60 ml/min/1·73m2. Findings: Eight risk factors showed causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asian ancestry, BMI, T2D and nephrolithiasis showed causal effects. Comprehensive follow-up analyses suggested that: (1) increased hypertension is a risk factor for CKD in Europeans but not in East Asians, suggesting the possibility of ancestry-specific disease aetiology; (2) T2D may have glucose-independent mechanisms to influence CKD; (3) non-linear MR indicated BMI above 25 kg/m2 as a threshold for increasing CKD risk. Conclusion: This study built up a strong causal link between cardiometabolic risk factors and CKD in two ancestries. This evidence could inform the design of future interventions to reduce the burden of CKD and its cardiometabolic co-morbidities. Funding: J.Z. is funded by a Vice-Chancellor Fellowship from the University of Bristol. This research was also funded by the UK Medical Research Council Integrative Epidemiology Unit (MC_UU_00011/1, MC_UU_00011/4 and MC_UU_00011/7). Jie Zheng is supported by the Academy of Medical Sciences (AMS) Springboard Award, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy (BEIS), the British Heart Foundation and Diabetes UK (SBF006\1117). JZ is funded by the Vice-Chancellor Fellowship from the University of Bristol. This study was funded/supported by the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol (GDS, TRG and REW). This study received funding from the UK Medical Research Council (MR/R013942/1). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care. J.Z., Y.M.Z. and T.R.G are funded by a BBSRC Innovation fellowship. Y.M.Z. is supported by the National Natural Science Foundation of China (81800636). H.Z. is supported by the Training Program of the Major Research Plan of the National Natural Science Foundation of China (91642120), the Grant from the Science and Technology Project of Beijing, China (D18110700010000) and the University of Michigan Health System–Peking University Health Science Center Joint Institute for Translational and Clinical Research (BMU2017JI007). N.F. is supported by the National Institutes of Health awards R01-MD012765, R01- DK117445 and R21-HL140385. R.C. is funded by a Wellcome Trust GW4 Clinical Academic Training Fellowship (WT 212557/Z/18/Z). The Trondelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trondelag County Council, Central Norway Regional Health Authority, and the Norwegian Institute of Public Health. M.C.B. is supported by the UK Medical Research Council (MRC) Skills Development Fellowship (MR/P014054/1). S.F. is supported by a Wellcome Trust PhD studentship (WT108902/Z/15/Z). Q.Y. is funded by a China Scholarship Council PhD scholarship (CSC201808060273). Y.C. was supported by the National Key R&D Program of China (2016YFC0900500, 2016YFC0900501, 2016YFC0900504). The China Kadoorie Biobank baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (202922/Z/16/Z, 088158/Z/09/Z, 104085/Z/14/Z). Japan-Kidney-Biobank was supported by AMED under Grant Number 20km0405210. P.C.H. is supported by Cancer Research UK [grant number: C18281/A19169]. A.K. was supported by DFG KO 3598/5-1. N.F. is supported by NIH awards R01-DK117445, R01-MD012765, R21- HL140385. Declaration of Interest: T.R.G. and J.Z. receive funding from GlaxoSmithKline and Biogen for unrelated research. All other authors have nothing to declare. Ethical Approval: All participants included in the CKDGen, UK Biobank, HUNT, Biobank Japan, China Kadoorie Biobank and Japan Kidney Biobank/ToMMo provided written informed consent and studies were approved by their local research ethics committees and institutional review boards as applicable.
Highlights
Chronic kidney disease (CKD) affects 10–15% of the population worldwide
To better understand the causal mechanisms linking type 2 diabetes (T2D) with chronic kidney disease (CKD), four additional Mendelian randomization (MR) analyses were conducted: (i) we validated the effects of eight glycaemic phenotypes on CKD using Steiger filtering[28] and radial MR;[29] (ii) we considered the influence of the genetic liability for type 1 diabetes (T1D)[30] (Supplementary Table S2, available as Supplementary data at IJE online) on CKD; (iii) participants with estimated glomerular filtration rate (eGFR) measurements were stratified into diabetic (N 1⁄4 11 529) and non-diabetic populations (N 1⁄4 118 460)[31] and we conducted MR analyses of T2D and five glycaemic phenotypes on eGFR in these two subpopulations; (iv) diabetic retinopathy was included as a positive control outcome to validate the analytical approach
Distinguishable causal patterns between ancestries were observed when examining the effect of hypertension on CKD, with a strong causal estimate in Europeans that was not replicated in the analysis of East Asians. These findings indicate that careful consideration is needed before implementing interventions for CKD risk factors in participants of one ancestry based on the evidence from another ancestry
Summary
Chronic kidney disease (CKD) affects 10–15% of the population worldwide It has a major effect on global health, both as a direct cause of morbidity and mortality, and as an important complication for cardiometabolic diseases.[1,2,3] From 1990 to 2017, the global age-standardized mortality for many important non-communicable diseases has declined. This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization. Results: Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. Conclusions: Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD
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