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      No causal effects of serum urate levels on the risk of chronic kidney disease: A Mendelian randomization study

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          Abstract

          Background

          Studies have shown strong positive associations between serum urate (SU) levels and chronic kidney disease (CKD) risk; however, whether the relation is causal remains uncertain. We evaluate whether genetic data are consistent with a causal impact of SU level on the risk of CKD and estimated glomerular filtration rate (eGFR).

          Methods and findings

          We used Mendelian randomization (MR) methods to evaluate the presence of a causal effect. We used aggregated genome-wide association data ( N = 110,347 for SU, N = 69,374 for gout, N = 133,413 for eGFR, N = 117,165 for CKD), electronic-medical-record-linked UK Biobank data ( N = 335,212), and population-based cohorts ( N = 13,425), all in individuals of European ancestry, for SU levels and CKD. Our MR analysis showed that SU has a causal effect on neither eGFR level nor CKD risk across all MR analyses (all P > 0.05). These null associations contrasted with our epidemiological association findings from the 4 population-based cohorts (change in eGFR level per 1-mg/dl [59.48 μmol/l] increase in SU: −1.99 ml/min/1.73 m 2; 95% CI −2.86 to −1.11; P = 8.08 × 10 −6; odds ratio [OR] for CKD: 1.48; 95% CI 1.32 to 1.65; P = 1.52 × 10 −11). In contrast, the same MR approaches showed that SU has a causal effect on the risk of gout (OR estimates ranging from 3.41 to 6.04 per 1-mg/dl increase in SU, all P < 10 −3), which served as a positive control of our approach. Overall, our MR analysis had >99% power to detect a causal effect of SU level on the risk of CKD of the same magnitude as the observed epidemiological association between SU and CKD. Limitations of this study include the lifelong effect of a genetic perturbation not being the same as an acute perturbation, the inability to study non-European populations, and some sample overlap between the datasets used in the study.

          Conclusions

          Evidence from our series of causal inference approaches using genetics does not support a causal effect of SU level on eGFR level or CKD risk. Reducing SU levels is unlikely to reduce the risk of CKD development.

          Author summary

          Why was this study done?
          • Epidemiological studies have shown strong correlations between serum urate (SU) levels and chronic kidney disease (CKD) risk.

          • Elevated SU levels are often found in patients with CKD, but it is not clear whether high serum urate is a cause of kidney disease or just a common co-occurrence.

          • Previous studies examining whether SU levels had a causal effect on CKD were limited due to not having large enough samples to detect a true causal relationship if it existed and/or had limitations related to the methodology.

          • Several clinical trials have been started that aim to use urate-lowering medication to prevent CKD.

          What did the authors do and find?
          • To determine whether SU level has a causal effect on CKD, we used a methodology known as Mendelian randomization to test whether genetic variants known to increase SU level also increased the risk of CKD.

          • We used multiple datasets to perform Mendelian randomization analyses, which included meta-analyses performed across multiple population-based cohorts, 4 individual population-based cohorts, and the large electronic-medical-record-linked UK Biobank.

          • Across all datasets, we found no significant causal connection between SU level and risk of CKD.

          What do these findings mean?
          • Our findings do not support a causal role of SU level in CKD.

          • Lower SU levels would be unlikely to translate into reduced risk of CKD.

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          Most cited references19

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          Analysis of the Global Burden of Disease study highlights the global, regional, and national trends of chronic kidney disease epidemiology from 1990 to 2016

          The last quarter century witnessed significant population growth, aging, and major changes in epidemiologic trends, which may have shaped the state of chronic kidney disease (CKD) epidemiology. Here, we used the Global Burden of Disease study data and methodologies to describe the change in burden of CKD from 1990 to 2016 involving incidence, prevalence, death, and disability-adjusted-life-years (DALYs). Globally, the incidence of CKD increased by 89% to 21,328,972 (uncertainty interval 19,100,079- 23,599,380), prevalence increased by 87% to 275,929,799 (uncertainty interval 252,442,316-300,414,224), death due to CKD increased by 98% to 1,186,561 (uncertainty interval 1,150,743-1,236,564), and DALYs increased by 62% to 35,032,384 (uncertainty interval 32,622,073-37,954,350). Measures of burden varied substantially by level of development and geography. Decomposition analyses showed that the increase in CKD DALYs was driven by population growth and aging. Globally and in most Global Burden of Disease study regions, age-standardized DALY rates decreased, except in High-income North America, Central Latin America, Oceania, Southern Sub-Saharan Africa, and Central Asia, where the increased burden of CKD due to diabetes and to a lesser extent CKD due to hypertension and other causes outpaced burden expected by demographic expansion. More of the CKD burden (63%) was in low and lower-middle-income countries. There was an inverse relationship between age-standardized CKD DALY rate and health care access and quality of care. Frontier analyses showed significant opportunities for improvement at all levels of the development spectrum. Thus, the global toll of CKD is significant, rising, and unevenly distributed; it is primarily driven by demographic expansion and in some regions a significant tide of diabetes. Opportunities exist to reduce CKD burden at all levels of development.
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            A role for uric acid in the progression of renal disease.

            Hyperuricemia is associated with renal disease, but it is usually considered a marker of renal dysfunction rather than a risk factor for progression. Recent studies have reported that mild hyperuricemia in normal rats induced by the uricase inhibitor, oxonic acid (OA), results in hypertension, intrarenal vascular disease, and renal injury. This led to the hypothesis that uric acid may contribute to progressive renal disease. To examine the effect of hyperuricemia on renal disease progression, rats were fed 2% OA for 6 wk after 5/6 remnant kidney (RK) surgery with or without the xanthine oxidase inhibitor, allopurinol, or the uricosuric agent, benziodarone. Renal function and histologic studies were performed at 6 wk. Given observations that uric acid induces vascular disease, the effect of uric acid on vascular smooth muscle cells in culture was also examined. RK rats developed transient hyperuricemia (2.7 mg/dl at week 2), but then levels returned to baseline by week 6 (1.4 mg/dl). In contrast, RK+OA rats developed higher and more persistent hyperuricemia (6 wk, 3.2 mg/dl). Hyperuricemic rats demonstrated higher BP, greater proteinuria, and higher serum creatinine than RK rats. Hyperuricemic RK rats had more renal hypertrophy and greater glomerulosclerosis (24.2 +/- 2.5 versus 17.5 +/- 3.4%; P < 0.05) and interstitial fibrosis (1.89 +/- 0.45 versus 1.52 +/- 0.47; P < 0.05). Hyperuricemic rats developed vascular disease consisting of thickening of the preglomerular arteries with smooth muscle cell proliferation; these changes were significantly more severe than a historical RK group with similar BP. Allopurinol significantly reduced uric acid levels and blocked the renal functional and histologic changes. Benziodarone reduced uric acid levels less effectively and only partially improved BP and renal function, with minimal effect on the vascular changes. To better understand the mechanism for the vascular disease, the expression of COX-2 and renin were examined. Hyperuricemic rats showed increased renal renin and COX-2 expression, the latter especially in preglomerular arterial vessels. In in vitro studies, cultured vascular smooth muscle cells incubated with uric acid also generated COX-2 with time-dependent proliferation, which was prevented by either a COX-2 or TXA-2 receptor inhibitor. Hyperuricemia accelerates renal progression in the RK model via a mechanism linked to high systemic BP and COX-2-mediated, thromboxane-induced vascular disease. These studies provide direct evidence that uric acid may be a true mediator of renal disease and progression.
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              The Cardiovascular Health Study: design and rationale.

              The Cardiovascular Health Study (CHS) is a population-based, longitudinal study of coronary heart disease and stroke in adults aged 65 years and older. The main objective of the study is to identify factors related to the onset and course of coronary heart disease and stroke. CHS is designed to determine the importance of conventional cardiovascular disease (CVD) risk factors in older adults, and to identify new risk factors in this age group, especially those that may be protective and modifiable. The study design called for enrollment of 1250 men and women in each of four communities: Forsyth County, North Carolina; Sacramento County, California; Washington County, Maryland; and Pittsburgh, Pennsylvania. Eligible participants were sampled from Medicare eligibility lists in each area. Extensive physical and laboratory evaluations were performed at baseline to identify the presence and severity of CVD risk factors such as hypertension, hypercholesterolemia and glucose intolerance; subclinical disease such as carotid artery atherosclerosis, left ventricular enlargement, and transient ischemia; and clinically overt CVD. These examinations in CHS permit evaluation of CVD risk factors in older adults, particularly in groups previously under-represented in epidemiologic studies, such as women and the very old. The first of two examination cycles began in June 1989. A second comprehensive examination will be repeated three years later. Periodic interim contacts are scheduled to ascertain and verify the incidence of CVD events, the frequency of recurrent events, and the sequellae of CVD.
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                Author and article information

                Contributors
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                15 January 2019
                January 2019
                : 16
                : 1
                : e1002725
                Affiliations
                [1 ] Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
                [2 ] Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
                [3 ] Division of Rheumatology, Allergy and Immunology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
                [4 ] Department of Biochemistry, University of Otago, Dunedin, New Zealand
                [5 ] Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, South Korea
                [6 ] Department of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
                Imperial College London, UNITED KINGDOM
                Author notes

                I have read the journal’s policy and the authors of this manuscript have the following competing interests: HKC has received funding from grants from Astra-Zeneca during the conduct of the study. HKC has also received funding from grants from Selecta, Horizon Pharma, and Takeda, not related to the submitted work. GN has received funding from grants from Goldfinch Bio, personal fees from pulseData LLC, not related to the submitted work. GN is a co-founder of RenalytixAI and is a member advisory board of RenalytixAI and own equity in the same. TRM has received funding from Ardea Biosciences and Ironwood Pharmaceuticals, not related to the submitted work. RD has received funding from grants from AstraZeneca, during the conduct of the study. RD has also received funding from grants from Goldfinch Bio, not related to the submitted work.

                Author information
                http://orcid.org/0000-0002-5318-8225
                http://orcid.org/0000-0002-1669-572X
                http://orcid.org/0000-0002-9343-8911
                http://orcid.org/0000-0001-5719-0552
                http://orcid.org/0000-0001-6319-4314
                http://orcid.org/0000-0002-3144-3627
                Article
                PMEDICINE-D-18-01879
                10.1371/journal.pmed.1002725
                6333326
                30645594
                e769a4eb-ed0f-46d3-9cc4-6d9aafa39661
                © 2019 Jordan et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 May 2018
                : 11 December 2018
                Page count
                Figures: 3, Tables: 3, Pages: 15
                Funding
                DMJ was supported by a T32 molecular cardiology training grant (HL007824) by the National Institutes of Health. HKC was supported by R01 AR056291, R01 AR065944, P50 AR060772 from the National Institutes of Health and a research grant from AstraZeneca. RT and TRM were supported by the Health Research Council of New Zealand. HHW was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2016R1C1B2007920). GN was supported by the National Institute Of Diabetes And Digestive And Kidney Diseases of the National Institutes of Health under Award Number K23DK107908. RD was supported by R35GM124836 from the National Institute Of General Medical Sciences of the National Institutes of Health, R01HL139865 from the National Heart, Lung, Blood Institute of the National Institutes of Health, an American Heart Association Cardiovascular Genome-Phenome Discovery grant (15CVGPSD27130014) and research grants from AstraZeneca and Goldfinch Bio. The ARIC 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-HC-55021, N01-HC-55022, R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. The FHS and the Framingham SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute in collaboration with Boston University. The Framingham SHARe data used for the analyses described in this manuscript were obtained through dbGaP. The CHS research reported in this article was supported by contract numbers N01-HC-85079, N01-HC-85080, N01-HC-85081, N01-HC-85082, N01-HC-85083, N01-HC-85084, N01-HC-85085, N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133, N01-HC-85239 and HHSN268201200036C; grant numbers U01 HL080295 from the National Heart, Lung, and Blood Institute and R01 AG-023629 from the National Institute on Aging, with additional contribution from the National Institute of Neurological Disorders and Stroke. A full list of principal CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (N01-HC95095 & N01-HC48047), University of Minnesota (N01-HC48048), Northwestern University (N01-HC48049), and Kaiser Foundation Research Institute (N01-HC48050). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
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                Computational Biology
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                Inflammatory Diseases
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                Custom metadata
                All relevant GWAS summary statistic data are included in S1 Table. The data underlying the results for the Atherosclerosis Risk In Communities (ARIC), Coronary Artery Risk Development in Young Adults Study (CARDIA), Cardiovascular Health Study (CHS), and Framingham Heart Study (FHS) cohorts presented in the study are available from the database of Genotypes and Phenotypes (dbGap): https://www.ncbi.nlm.nih.gov/gap, for researchers who meet the criteria for access to the data. The data underlying the results for the UK Biobank presented in the study are available from the UK Biobank: https://www.ukbiobank.ac.uk/, for researchers who meet the criteria for access to the data.

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