1
|
Noels H, van der Vorst EPC, Rubin S, Emmett A, Marx N, Tomaszewski M, Jankowski J. Renal-Cardiac Crosstalk in the Pathogenesis and Progression of Heart Failure. Circ Res 2025; 136:1306-1334. [PMID: 40403103 DOI: 10.1161/circresaha.124.325488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2024] [Revised: 02/14/2025] [Accepted: 03/11/2025] [Indexed: 05/24/2025]
Abstract
Chronic kidney disease (CKD) represents a global health issue with a high socioeconomic impact. Beyond a progressive decline of kidney function, patients with CKD are at increased risk of cardiovascular diseases, including heart failure (HF) and sudden cardiac death. HF in CKD can manifest both as HF with reduced ejection fraction and HF with preserved ejection fraction, with the latter further increasing in relative importance in the more advanced stages of CKD. Typical cardiac remodeling characteristics in uremic cardiomyopathy include left ventricular hypertrophy, myocardial fibrosis, cardiac electrical dysregulation, capillary rarefaction, and microvascular dysfunction, which are triggered by increased cardiac preload, cardiac afterload, and preload and afterload-independent factors. The pathophysiological mechanisms underlying cardiac remodeling in CKD are multifactorial and include neurohormonal activation (with increased activation of the renin-angiotensin-aldosterone system, the sympathetic nervous system, and mineralocorticoid receptor signaling), cardiac steroid activation, mitochondrial dysfunction, inflammation, innate immune activation, and oxidative stress. Furthermore, disturbances in cardiac metabolism and calcium homeostasis, macrovascular and microvascular dysfunction, increased cellular profibrotic responses, the accumulation of uremic retention solutes, and mineral and bone disorders also contribute to cardiovascular disease and HF in CKD. Here, we review the current knowledge of HF in CKD, including the clinical characteristics and pathophysiological mechanisms revealed in animal studies. We also elaborate on the detrimental impact of comorbidities of CKD on HF using hypertension as an example and discuss the clinical characteristics of hypertensive heart disease and the genetic predisposition. Overall, this review aims to increase the understanding of HF in CKD to support future research and clinical translational approaches for improved diagnosis and therapy of this vulnerable patient population.
Collapse
Affiliation(s)
- Heidi Noels
- Institute for Molecular Cardiovascular Research (H.N., E.P.C.v.d.V., J.J.), Uniklinik RWTH Aachen, RWTH Aachen University, Germany
- Aachen-Maastricht Institute for Cardiorenal Disease (H.N., E.P.C.v.d.V., J.J.), Uniklinik RWTH Aachen, RWTH Aachen University, Germany
- Biochemistry Department (H.N.), Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| | - Emiel P C van der Vorst
- Institute for Molecular Cardiovascular Research (H.N., E.P.C.v.d.V., J.J.), Uniklinik RWTH Aachen, RWTH Aachen University, Germany
- Aachen-Maastricht Institute for Cardiorenal Disease (H.N., E.P.C.v.d.V., J.J.), Uniklinik RWTH Aachen, RWTH Aachen University, Germany
- Interdisciplinary Center for Clinical Research (IZKF) (E.P.C.v.d.V.), RWTH Aachen University, Germany
- Institute for Cardiovascular Prevention, Ludwig-Maximilians-University Munich, Germany (E.P.C.v.d.V.)
| | - Sébastien Rubin
- L'Institut national de la santé et de la recherche médicale (INSERM), BMC, U1034, University of Bordeaux, Pessac, France (S.R.)
- Renal Unit, University Hospital of Bordeaux, France (S.R.)
| | - Amber Emmett
- Faculty of Medicine, Biology and Health, Division of Cardiovascular Sciences, The University of Manchester, United Kingdom (A.E., M.T.)
| | - Nikolaus Marx
- Department of Internal Medicine I-Cardiology, Angiology and Internal Intensive Care Medicine (N.M.), RWTH Aachen University, Germany
| | - Maciej Tomaszewski
- Faculty of Medicine, Biology and Health, Division of Cardiovascular Sciences, The University of Manchester, United Kingdom (A.E., M.T.)
- British Heart Foundation Manchester Centre of Research Excellence, United Kingdom (M.T.)
- Manchester Academic Health Science Centre, Manchester University National Health Service (NHS) Foundation Trust, United Kingdom (M.T.)
- Signature Research Programme in Health Services and Systems Research, Duke-National University of Singapore (M.T.)
| | - Joachim Jankowski
- Institute for Molecular Cardiovascular Research (H.N., E.P.C.v.d.V., J.J.), Uniklinik RWTH Aachen, RWTH Aachen University, Germany
- Biochemistry Department (H.N.), Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
- Pathology Department (J.J.), Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| |
Collapse
|
2
|
Zanoni F, Marasa M, Carlassara L, Verbitsky M, Khan A, Wang C, Bundy JD, Canetta PA, Bomback AS, Parsa A, Feldman HI, Gharavi AG, Kiryluk K. Family History in the Context of CKD. J Am Soc Nephrol 2025:00001751-990000000-00583. [PMID: 40067412 DOI: 10.1681/asn.0000000653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Accepted: 03/05/2025] [Indexed: 03/19/2025] Open
Abstract
Background A family history of health conditions may reflect shared genetic and/or environmental risk. It is not well known to what extent family history affects outcomes among patients with CKD. In this study, we investigated the associations of family history of CKD, diabetes, and other conditions with common comorbidities and kidney disease progression among patients with CKD. Methods We performed an observational study of two prospective CKD cohorts, 2573 adults and children from the Cure Glomerulopathy Network and 3939 Chronic Renal Insufficiency Cohort adult participants. Self-reported first-degree family history of CKD, diabetes, and other common diseases was tested for associations with the risk of comorbidities and CKD progression using multivariable models. Results Family history of common comorbid conditions was associated with higher risk of these conditions in the context of CKD, including approximately by over three-fold for diabetes (adjusted odds ratio [OR], 3.37; 95% confidence interval [CI], 2.73 to 4.15), 48% for cancer (adjusted OR, 1.48; 95% CI, 1.05 to 2.09), and 69% for cardiovascular disease (adjusted OR, 1.69; 95% CI, 1.36 to 2.10 in combined cohorts). While polygenic risk score (PRS) for CKD was associated with kidney disease progression (adjusted hazards ratio, 1.11; 95% CI, 1.06 to 1.16 in combined cohorts), family history of kidney disease was not an independent risk factor of disease progression in the context of existing CKD. By contrast, family history of diabetes was significantly associated with a higher risk of CKD progression independently of diabetes occurrence or PRS for diabetes (adjusted hazards ratio, 1.19; 95% CI, 1.05 to 1.35 in combined cohorts). Conclusions Broad collection of family history in the context of CKD improved clinical risk stratification. Family history of diabetes was consistently associated with a higher risk of CKD progression independently of diabetes status or PRS for diabetes in both cohorts.
Collapse
Affiliation(s)
- Francesca Zanoni
- Department of Nephrology, Dialysis, and Kidney Transplantation, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Maddalena Marasa
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Lucrezia Carlassara
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Miguel Verbitsky
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Chen Wang
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Joshua D Bundy
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Pietro A Canetta
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Andrew S Bomback
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Afshin Parsa
- Division of Kidney, Urologic and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Harold I Feldman
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| |
Collapse
|
3
|
Qi X, Wang J, Wang T, Wang W, Zhang D. Epigenome-wide association study of Chinese monozygotic twins identifies DNA methylation loci associated with estimated glomerular filtration rate. J Transl Med 2025; 23:101. [PMID: 39844292 PMCID: PMC11752939 DOI: 10.1186/s12967-025-06067-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2024] [Accepted: 01/05/2025] [Indexed: 01/24/2025] Open
Abstract
BACKGROUND DNA methylation (DNAm) has been shown in multiple studies to be associated with the estimated glomerular filtration rate (eGFR). However, studies focusing on Chinese populations are lacking. We conducted an epigenome-wide association study to investigate the association between DNAm and eGFR in Chinese monozygotic twins. METHODS Genome-wide DNAm level was detected using Reduced Representation Bisulfite Sequencing test. Generalized estimation equation (GEE) was used to examine the association between Cytosine-phosphate-Guanines (CpGs) DNAm and eGFR. Inference about Causation from Examination of FAmiliaL CONfounding was employed to infer the causal relationship. The comb-p was used to identify differentially methylated regions (DMRs). GeneMANIA was used to analyze the gene interaction network. The Genomic Regions Enrichment of Annotations Tool enriched biological functions and pathways. Gene expression profiling sequencing was employed to measure mRNA expression levels, and the GEE model was used to investigate the association between gene expression and eGFR. The candidate gene was validated in a community population by calculating the methylation risk score (MRS). RESULTS A total of 80 CpGs and 28 DMRs, located at genes such as OLIG2, SYNGR3, LONP1, CDCP1, and SHANK1, achieved genome-wide significance level (FDR < 0.05). The causal effect of DNAm on eGFR was supported by 12 CpGs located at genes such as SYNGR3 and C9orf3. In contrast, the causal effect of eGFR on DNAm is proved by 13 CpGs located at genes such as EPHB3 and MLLT1. Enrichment analysis revealed several important biological functions and pathways related to eGFR, including alpha-2A adrenergic receptor binding pathway and corticotropin-releasing hormone receptor activity pathway. GeneMANIA results showed that SYNGR3 was co-expressed with MLLT1 and had genetic interactions with AFF4 and EDIL3. Gene expression analysis found that SYNGR3 expression was negatively associated with eGFR. Validation analysis showed that the MRS of SYNGR3 was positively associated with low eGFR levels. CONCLUSIONS We identified a set of CpGs, DMRs, and pathways potentially associated with eGFR, particularly in the SYNGR3 gene. These findings provided new insights into the epigenetic modifications related to the decline in eGFR and chronic kidney disease.
Collapse
Affiliation(s)
- Xueting Qi
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Jingjing Wang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Tong Wang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, 266071, Shandong, People's Republic of China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, 266071, Shandong, People's Republic of China.
| |
Collapse
|
4
|
Khan A, Kiryluk K. Polygenic scores and their applications in kidney disease. Nat Rev Nephrol 2025; 21:24-38. [PMID: 39271761 DOI: 10.1038/s41581-024-00886-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2024] [Indexed: 09/15/2024]
Abstract
Genome-wide association studies (GWAS) have uncovered thousands of risk variants that individually have small effects on the risk of human diseases, including chronic kidney disease, type 2 diabetes, heart diseases and inflammatory disorders, but cumulatively explain a substantial fraction of disease risk, underscoring the complexity and pervasive polygenicity of common disorders. This complexity poses unique challenges to the clinical translation of GWAS findings. Polygenic scores combine small effects of individual GWAS risk variants across the genome to improve personalized risk prediction. Several polygenic scores have now been developed that exhibit sufficiently large effects to be considered clinically actionable. However, their clinical use is limited by their partial transferability across ancestries and a lack of validated models that combine polygenic, monogenic, family history and clinical risk factors. Moreover, prospective studies are still needed to demonstrate the clinical utility and cost-effectiveness of polygenic scores in clinical practice. Here, we discuss evolving methods for developing polygenic scores, best practices for validating and reporting their performance, and the study designs that will empower their clinical implementation. We specifically focus on the polygenic scores relevant to nephrology and other chronic, complex diseases and review their key limitations, necessary refinements and potential clinical applications.
Collapse
Affiliation(s)
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.
| |
Collapse
|
5
|
Vos M, Wang R, Rommelse NNJ, Snieder H, Larsson H, Hartman CA. Familial co-aggregation and shared familiality among neurodevelopmental problems and with aggressive behavior, depression, anxiety, and substance use. Psychol Med 2024:1-13. [PMID: 39679547 DOI: 10.1017/s003329172400309x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2024]
Abstract
OBJECTIVE To refine the knowledge on familial transmission, we examined the (shared) familial components among neurodevelopmental problems (i.e. two attention-deficit/hyperactivity-impulsivity disorder [ADHD] and six autism spectrum disorder [ASD] subdomains) and with aggressive behavior, depression, anxiety, and substance use. METHODS Data were obtained from a cross-sectional study encompassing 37 688 participants across three generations from the general population. ADHD subdomains, ASD subdomains, aggressive behavior, depression, anxiety, and substance use were assessed. To evaluate familial (co-)aggregation, recurrence risk ratios (λR) were estimated using Cox proportional hazards models. The (shared) familiality (f2), which is closely related to (shared) heritability, was assessed using residual maximum likelihood-based variance decomposition methods. All analyses were adjusted for sex, age, and age2. RESULTS The familial aggregation and familiality of neurodevelopmental problems were moderate (λR = 2.40-4.04; f2 = 0.22-0.39). The familial co-aggregation and shared familiality among neurodevelopmental problems (λR = 1.39-2.56; rF = 0.52-0.94), and with aggressive behavior (λR = 1.79-2.56; rF = 0.60-0.78), depression (λR = 1.45-2.29; rF = 0.43-0.76), and anxiety (λR = 1.44-2.31; rF = 0.62-0.84) were substantial. The familial co-aggregation and shared familiality between all neurodevelopmental problems and all types of substance use were weak (λR = 0.53-1.57; rF = -0.06-0.35). CONCLUSIONS Neurodevelopmental problems belonging to the same disorder were more akin than cross-disorder problems. That said, there is a clear (shared) familial component to neurodevelopmental problems, in part shared with other psychiatric problems (except for substance use). This suggests that neurodevelopmental disorders, disruptive behavior disorders, and internalizing disorders share genetic and environmental risk factors.
Collapse
Affiliation(s)
- Melissa Vos
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rujia Wang
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Nanda N J Rommelse
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Catharina A Hartman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| |
Collapse
|
6
|
Jones AC, Patki A, Srinivasasainagendra V, Tiwari HK, Armstrong ND, Chaudhary NS, Limdi NA, Hidalgo BA, Davis B, Cimino JJ, Khan A, Kiryluk K, Lange LA, Lange EM, Arnett DK, Young BA, Diamantidis CJ, Franceschini N, Wassertheil-Smoller S, Rich SS, Rotter JI, Mychaleckyj JC, Kramer HJ, Chen YDI, Psaty BM, Brody JA, de Boer IH, Bansal N, Bis JC, Irvin MR. Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in Black American Populations. J Am Soc Nephrol 2024; 35:1558-1569. [PMID: 39073889 PMCID: PMC11543021 DOI: 10.1681/asn.0000000000000437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 06/28/2024] [Indexed: 07/31/2024] Open
Abstract
Key Points The predictive performance of an African ancestry–specific polygenic risk score (PRS) was comparable to a European ancestry–derived PRS for kidney traits. However, multi-ancestry PRSs outperform single-ancestry PRSs in Black American populations. Predictive accuracy of PRSs for CKD was improved with the use of race-free eGFR. Background CKD is a risk factor of cardiovascular disease and early death. Recently, polygenic risk scores (PRSs) have been developed to quantify risk for CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PRS development overall. Moreover, European ancestry–derived PRSs demonstrate diminished predictive performance in African ancestry populations. Methods This study aimed to develop a PRS for CKD in Black American populations. We obtained score weights from a meta-analysis of genome-wide association studies for eGFR in the Million Veteran Program and Reasons for Geographic and Racial Differences in Stroke Study to develop an eGFR PRS. We optimized the PRS risk model in a cohort of participants from the Hypertension Genetic Epidemiology Network. Validation was performed in subsets of Black participants of the Trans-Omics in Precision Medicine Consortium and Genetics of Hypertension Associated Treatment Study. Results The prevalence of CKD—defined as stage 3 or higher—was associated with the PRS as a continuous predictor (odds ratio [95% confidence interval]: 1.35 [1.08 to 1.68]) and in a threshold-dependent manner. Furthermore, including APOL1 risk status—a putative variant for CKD with higher prevalence among those of sub-Saharan African descent—improved the score's accuracy. PRS associations were robust to sensitivity analyses accounting for traditional CKD risk factors, as well as CKD classification based on prior eGFR equations. Compared with previously published PRS, the predictive performance of our PRS was comparable with a European ancestry–derived PRS for kidney traits. However, single-ancestry PRSs were less predictive than multi-ancestry–derived PRSs. Conclusions In this study, we developed a PRS that was significantly associated with CKD with improved predictive accuracy when including APOL1 risk status. However, PRS generated from multi-ancestry populations outperformed single-ancestry PRS in our study.
Collapse
Affiliation(s)
- Alana C. Jones
- Medical Scientist Training Program, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Amit Patki
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Hemant K. Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Nicole D. Armstrong
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Ninad S. Chaudhary
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Nita A. Limdi
- Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Bertha A. Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Brittney Davis
- Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - James J. Cimino
- Department of Biomedical Informatics and Data Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University Medical Center, New York, New York
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia University Medical Center, New York, New York
| | - Leslie A. Lange
- Department of Biomedical Informatics, University of Colorado-Anschutz, Aurora, Colorado
| | - Ethan M. Lange
- Department of Biomedical Informatics, University of Colorado-Anschutz, Aurora, Colorado
| | - Donna K. Arnett
- Office of the Provost, University of South Carolina, Columbia, South Carolina
| | - Bessie A. Young
- Division of Nephrology, University of Washington, Seattle, Washington
| | | | - Nora Franceschini
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, New York
| | - Stephen S. Rich
- Department of Genome Sciences, University of Virginia, Charlottesville, Virginia
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomic and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbort-UCLA Medical Center, Torrance, California
| | - Josyf C. Mychaleckyj
- Department of Genome Sciences, University of Virginia, Charlottesville, Virginia
| | - Holly J. Kramer
- Departments of Public Health Sciences and Medicine, Loyola University Medical Center, Taywood, Illinois
| | - Yii-Der I. Chen
- Department of Pediatrics, The Institute for Translational Genomic and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbort-UCLA Medical Center, Torrance, California
| | - Bruce M. Psaty
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington
| | - Ian H. de Boer
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Nisha Bansal
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington
| | - Marguerite R. Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| |
Collapse
|
7
|
Jones AC, Patki A, Srinivasasainagendra V, Hidalgo BA, Tiwari HK, Limdi NA, Armstrong ND, Chaudhary NS, Minniefield B, Absher D, Arnett DK, Lange LA, Lange EM, Young BA, Diamantidis CJ, Rich SS, Mychaleckyj JC, Rotter JI, Taylor KD, Kramer HJ, Tracy RP, Durda P, Kasela S, Lappalinen T, Liu Y, Johnson WC, Van Den Berg DJ, Franceschini N, Liu S, Mouton CP, Bhatti P, Horvath S, Whitsel EA, Irvin MR. A methylation risk score for chronic kidney disease: a HyperGEN study. Sci Rep 2024; 14:17757. [PMID: 39085340 PMCID: PMC11291488 DOI: 10.1038/s41598-024-68470-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 07/24/2024] [Indexed: 08/02/2024] Open
Abstract
Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.
Collapse
Affiliation(s)
- Alana C Jones
- Medical Scientist Training Program, University of Alabama at Birmingham, 912 18th St S, Birmingham, AL, 35233, USA.
- Department of Epidemiology, University of Alabama at Birmingham, 912 18th St S, Birmingham, AL, 35233, USA.
| | - Amit Patki
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Bertha A Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, 912 18th St S, Birmingham, AL, 35233, USA
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Nita A Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Nicole D Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, 912 18th St S, Birmingham, AL, 35233, USA
| | | | - Bré Minniefield
- Department of Biology, Florida State University-Panama City, Panama City, FL, USA
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Donna K Arnett
- Office of the Provost, University of South Carolina, Columbia, SC, USA
| | - Leslie A Lange
- Department of Biomedical Informatics, University of Colorado-Anschutz, Aurora, CO, USA
| | - Ethan M Lange
- Department of Biomedical Informatics, University of Colorado-Anschutz, Aurora, CO, USA
| | - Bessie A Young
- Division of Nephrology, University of Washington, Seattle, WA, USA
| | | | - Stephen S Rich
- Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA
| | - Josyf C Mychaleckyj
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Holly J Kramer
- Departments of Public Health Sciences and Medicine, Loyola University Medical Center, Taywood, IL, USA
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine, University of Vermont, Colchester, VT, USA
| | - Peter Durda
- Department of Pathology and Laboratory Medicine, University of Vermont, Colchester, VT, USA
| | - Silva Kasela
- Department of Systems Biology, New York Genome Center, Columbia University, New York, NY, USA
| | - Tuuli Lappalinen
- Department of Systems Biology, New York Genome Center, Columbia University, New York, NY, USA
| | - Yongmei Liu
- Department of Medicine, Cardiology and Neurology, Duke University Medical Center, Durham, NC, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David J Van Den Berg
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Simin Liu
- Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
| | - Charles P Mouton
- Department of Family Medicine, University of Texas Medical Branch Health, Galveston, TX, USA
| | - Parveen Bhatti
- Department of Medicine, School of Population and Public Health, University of British Columbia, Vancouver, BC, CAN, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, Gonda Research Center, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, 912 18th St S, Birmingham, AL, 35233, USA
| |
Collapse
|
8
|
Jefferis J, Hudson R, Lacaze P, Bakshi A, Hawley C, Patel C, Mallett A. Monogenic and polygenic concepts in chronic kidney disease (CKD). J Nephrol 2024; 37:7-21. [PMID: 37989975 PMCID: PMC10920206 DOI: 10.1007/s40620-023-01804-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 10/11/2023] [Indexed: 11/23/2023]
Abstract
Kidney function is strongly influenced by genetic factors with both monogenic and polygenic factors contributing to kidney function. Monogenic disorders with primarily autosomal dominant inheritance patterns account for 10% of adult and 50% of paediatric kidney diseases. However, kidney function is also a complex trait with polygenic architecture, where genetic factors interact with environment and lifestyle factors. Family studies suggest that kidney function has significant heritability at 35-69%, capturing complexities of the genome with shared environmental factors. Genome-wide association studies estimate the single nucleotide polymorphism-based heritability of kidney function between 7.1 and 20.3%. These heritability estimates, measuring the extent to which genetic variation contributes to CKD risk, indicate a strong genetic contribution. Polygenic Risk Scores have recently been developed for chronic kidney disease and kidney function, and validated in large populations. Polygenic Risk Scores show correlation with kidney function but lack the specificity to predict individual-level changes in kidney function. Certain kidney diseases, such as membranous nephropathy and IgA nephropathy that have significant genetic components, may benefit most from polygenic risk scores for improved risk stratification. Genetic studies of kidney function also provide a potential avenue for the development of more targeted therapies and interventions. Understanding the development and validation of genomic scores is required to guide their implementation and identify the most appropriate potential implications in clinical practice. In this review, we provide an overview of the heritability of kidney function traits in population studies, explore both monogenic and polygenic concepts in kidney disease, with a focus on recently developed polygenic risk scores in kidney function and chronic kidney disease, and review specific diseases which are most amenable to incorporation of genomic scores.
Collapse
Affiliation(s)
- Julia Jefferis
- Genetic Health Queensland, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia.
- Faculty of Medicine, University of Queensland, Brisbane, Australia.
- Kidney Health Service, Royal Brisbane and Women's Hospital, Brisbane, Australia.
| | - Rebecca Hudson
- Faculty of Medicine, University of Queensland, Brisbane, Australia
- Kidney Health Service, Royal Brisbane and Women's Hospital, Brisbane, Australia
| | - Paul Lacaze
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Andrew Bakshi
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Carmel Hawley
- Department of Nephrology, Princess Alexandra Hospital, Woolloongabba, QLD, Australia
- Australasian Kidney Trials Network, The University of Queensland, Brisbane, QLD, Australia
- Translational Research Institute, Brisbane, QLD, Australia
| | - Chirag Patel
- Genetic Health Queensland, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia
| | - Andrew Mallett
- Institutional for Molecular Bioscience and Faculty of Medicine, The University of Queensland, Saint Lucia, Australia.
- Department of Renal Medicine, Townsville University Hospital, Douglas, QLD, Australia.
- College of Medicine and Dentistry, James Cook University, Douglas, QLD, Australia.
| |
Collapse
|
9
|
Belay AS, Manaye GA, Kebede KM, Abateneh DD, Debebe S. Chronic kidney disease and its predictors among highly active antiretroviral therapy naïve and experienced HIV-infected individuals at the selected hospitals, Southwest Ethiopia: a comparative cross-sectional study. BMJ PUBLIC HEALTH 2023; 1:e000235. [PMID: 40017843 PMCID: PMC11812716 DOI: 10.1136/bmjph-2023-000235] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 11/27/2023] [Indexed: 03/01/2025]
Abstract
Objective This study aimed to determine the prevalence of chronic kidney disease (CKD) and its predictors among highly active antiretroviral therapy (HAART) naïve and experienced HIV-infected individuals. Method and analysis Hospital-based comparative cross-sectional study design was used at Mizan-Tepi University Teaching Hospital, Bonga General Hospital and Tepi General Hospital. A total of 616 naïve and experienced HIV-infected individuals participated. A systematic random sampling and consecutive sampling methods were applied to select the HAART experienced and naïve HIV-infected individuals, respectively. Descriptive statistics were used for all study variables. Independent t-test and logistic regression analysis were performed to compare the mean between naïve and experienced patients and to identify its predictor variables considering a <0.05 and 95% CI, respectively. Results A total of 616 HIV-positive respondents were enrolled in this study. The prevalence of CKD was 41 (29.3%) of 140 and 78 (16.4%) of 476 HAART-naïve and HAART-experienced HIV patients, respectively. Rural residency, being anaemic, being hypertensive, having had a family history of kidney disease and stage IV current WHO) clinical stage were independent risk factors of CKD among naïve HIV patients, whereas, rural residency, utilisation of drinking water per day below the recommended amount, being anaemic, being hypertensive, stage IV current WHO clinical stage and obesity were predictors of CKD among experienced HIV patients. Statistically significant difference was observed between HAART naïve and HAART experienced participants with regard to the mean glomerular filtration rate level (t=-3.987, 95% CI -18.29 to -6.22). Conclusion CKD was higher among HAART-naïve than HAART-experienced study participants. Therefore, early initiation of antiretroviral therapy (ART) drugs, modification of lifestyles to decrease obesity and early detection and treatment of comorbidities such as anaemia and hypertension may have profound effects in reducing CKD and increasing patients' quality of life.
Collapse
Affiliation(s)
| | | | | | | | - Shibihon Debebe
- Department of Medical Laboratory, Bahir Dar Health Science College, Bahir Dar, Ethiopia
| |
Collapse
|
10
|
Triatin RD, Chen Z, Ani A, Wang R, Hartman CA, Nolte IM, Thio CHL, Snieder H. Familial co-aggregation and shared genetics of cardiometabolic disorders and traits: data from the multi-generational Lifelines Cohort Study. Cardiovasc Diabetol 2023; 22:282. [PMID: 37865744 PMCID: PMC10590015 DOI: 10.1186/s12933-023-02017-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/07/2023] [Indexed: 10/23/2023] Open
Abstract
BACKGROUND It is unclear to what extent genetics explain the familial clustering and the co-occurrence of distinct cardiometabolic disorders in the general population. We therefore aimed to quantify the familial (co-)aggregation of various cardiometabolic disorders and to estimate the heritability of cardiometabolic traits and their genetic correlations using the large, multi-generational Lifelines Cohort Study. METHODS We used baseline data of 162,416 participants from Lifelines. Cardiometabolic disorders including type 2 diabetes (T2D), cardiovascular diseases, hypertension, obesity, hypercholesterolemia, and metabolic syndrome (MetS), were defined in adult participants. Fifteen additional cardiometabolic traits indexing obesity, blood pressure, inflammation, glucose regulation, and lipid levels were measured in all included participants. Recurrence risk ratios (λR) for first-degree relatives (FDR) indexed familial (co-)aggregation of cardiometabolic disorders using modified conditional Cox proportional hazards models and were compared to those of spouses. Heritability (h2), shared environment, and genetic correlation (rg) were estimated using restricted maximum likelihood variance decomposition methods, adjusted for age, age2, and sex. RESULTS Individuals with a first-degree relative with a cardiometabolic disorder had a higher risk of the same disorder, ranging from λFDR of 1.23 (95% CI 1.20-1.25) for hypertension to λFDR of 2.48 (95% CI 2.15-2.86) for T2D. Most of these were higher than in spouses (λSpouses < λFDR), except for obesity which was slightly higher in spouses. We found moderate heritability for cardiometabolic traits (from h2CRP: 0.26 to h2HDL: 0.50). Cardiometabolic disorders showed positive familial co-aggregation, particularly between T2D, MetS, and obesity (from λFDR obesity-MetS: 1.28 (95% CI 1.24-1.32) to λFDR MetS-T2D: 1.61 (95% CI 1.52-1.70)), consistent with the genetic correlations between continuous intermediate traits (ranging from rg HDL-Triglycerides: - 0.53 to rg LDL-Apolipoprotein B: 0.94). CONCLUSIONS There is positive familial (co-)aggregation of cardiometabolic disorder, moderate heritability of intermediate traits, and moderate genetic correlations between traits. These results indicate that shared genetics and common genetic architecture contribute to cardiometabolic disease.
Collapse
Affiliation(s)
- Rima D Triatin
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
- Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia
| | - Zekai Chen
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
| | - Alireza Ani
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran
| | - Rujia Wang
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
| | - Chris H L Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands.
- Department of Population Health Sciences, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands.
| |
Collapse
|
11
|
Wang A, Zhang T, Li J, Wang W, Xu C, Duan H, Tian X, Zhang D. Genetic and Environmental Correlation Analysis of Serum Creatinine Levels in Chinese Twins. Twin Res Hum Genet 2023; 26:219-222. [PMID: 37170793 DOI: 10.1017/thg.2023.20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Almost all creatinine is excreted by the kidney in individuals. Serum creatinine concentration, a widely used renal function index in clinical practice, can be affected by both genetic and environmental factors, as evidenced by current research exploring the relationship between these factors and kidney function. However, few studies have explored the heritability of serum creatinine in Asian populations. Therefore, we explored the genetic and environmental factors that affect the serum creatinine level in Asian populations. Participants in this study came from the Qingdao Twin Registry in China, and 374 pairs of twins were included, of which 139 pairs were dizygotic twins, whose ages ranged from 40 to 80 years old, and the serum creatinine level ranged from 10 to 126 μmol/L. Structural equation models were constructed using Mx software to calculate heritability, with adjusted covariates being age, sex, and body mass index. The results of heritability analysis showed that ACE was the best fit model. Serum creatinine level is influenced by genetic and environmental factors. The result of heritability was 35.44%, and the influence of shared environmental factors accounted for 52.13%. This study provided the relevant basis for future research on genetic and environmental factors affecting serum creatinine levels in Asian populations.
Collapse
Affiliation(s)
- Anni Wang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
| | - Tianhao Zhang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
| | - Jingxian Li
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
| | - Chunsheng Xu
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong Province, China
| | - Haiping Duan
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong Province, China
| | - Xiaocao Tian
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong Province, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
| |
Collapse
|
12
|
Kim JY, Chun SY, Lim H, Chang TI. Association between familial aggregation of chronic kidney disease and its incidence and progression. Sci Rep 2023; 13:5131. [PMID: 36991140 PMCID: PMC10060248 DOI: 10.1038/s41598-023-32362-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 03/27/2023] [Indexed: 03/31/2023] Open
Abstract
This study aimed to examine the association between familial aggregation of chronic kidney disease (CKD) and risk of CKD development and its progression. This nationwide family study comprised 881,453 cases with newly diagnosed CKD between 2004 and 2017 and 881,453 controls without CKD matched by age and sex, using data from the Korean National Health Insurance Service with linkage to the family tree database. The risks of CKD development and disease progression, defined as an incident end-stage renal disease (ESRD), were evaluated. The presence of any affected family member with CKD was associated with a significantly higher risk of CKD with adjusted ORs (95% CI) of 1.42 (1.38-1.45), 1.50 (1.46-1.55), 1.70 (1.64-1.77), and 1.30 (1.27-1.33) for individuals with affected parents, offspring, siblings, and spouses, respectively. In Cox models conducted on patients with predialysis CKD, risk of incident ESRD was significantly higher in those with affected family members with ESRD. The corresponding HRs (95% CI) were 1.10 (1.05-1.15), 1.38 (1.32-1.46), 1.57 (1.49-1.65), and 1.14 (1.08-1.19) for individuals listed above, respectively. Familial aggregation of CKD was strongly associated with a higher risk of CKD development and disease progression to ESRD.
Collapse
Affiliation(s)
- Jae Young Kim
- Department of Internal Medicine, National Health Insurance Service Ilsan Hospital, 100 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 10444, Republic of Korea
- Department of Internal Medicine, Institute of Kidney Disease Research, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sung-Youn Chun
- Research and Analysis Team, National Health Insurance Service Ilsan Hospital, Goyang-si, Gyeonggi-do, Republic of Korea
| | - Hyunsun Lim
- Research and Analysis Team, National Health Insurance Service Ilsan Hospital, Goyang-si, Gyeonggi-do, Republic of Korea
| | - Tae Ik Chang
- Department of Internal Medicine, National Health Insurance Service Ilsan Hospital, 100 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 10444, Republic of Korea.
| |
Collapse
|
13
|
Zhong Y, Wu Y, Yang Y, Chen Y, Hui R, Zhang M, Zhang W. Association of MPPED2 gene variant rs10767873 with kidney function and risk of cardiovascular disease in patients with hypertension. J Hum Genet 2023; 68:393-398. [PMID: 36797372 DOI: 10.1038/s10038-022-01118-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/23/2022] [Accepted: 12/25/2022] [Indexed: 02/18/2023]
Abstract
Changes in kidney function and the progression of chronic kidney disease (CKD) are associated with the risk of cardiovascular disease (CVD) and influenced by genetic factors. However, the association between genetic variants and kidney function in patients treated with antihypertensive drugs remains uncertain. This study aimed to examine the association between 30 variants locating at the 22 genes and the risk of kidney function evaluated by the estimated glomerular filtration rate (eGFR) in 1911 patients with hypertension from a Chinese community-based longitudinal cohort (including 1220 participants with CKD and 691 without CKD at baseline). By using multivariate linear regression analysis after adjustment for age, sex, traditional cardiovascular risk factors, and the use of antihypertensive drugs, as well as after correction for multiple comparison, patients with rs10767873T allele of the metallophosphoesterase domain containing 2 (MPPED2) gene were associated with higher level of eGFR (β = 0.041, p = 0.01) and lower levels of serum creatinine (β = -0.068, p = 0.001) and serum uric acid (β = -0.047, p = 0.02). But variant rs10767873 was not found to be associated with the risk of CKD, regardless of the types of antihypertensive drugs used. During a median 2.25-year follow-up, 152 CVD events were documented. Interestingly, patients with the rs10767873TT genotype had an increased risk of CVD events (hazard ratio, 1.74, 95% confidence interval, 1.11 to 2.73; p = 0.02) compared with patients carrying the wild-type genotype of rs10767873CC. In conclusion, our findings suggest variant rs10767873 of the MPPED2 gene is associated with kidney function and risk of CVD in Chinese hypertensive patients.
Collapse
Affiliation(s)
- Yixuan Zhong
- National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Yiyi Wu
- National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 100037, China.,The First Affiliated Hospital of Anhui University of Science and Technology (The First People's Hospital of Huainan City), Huainan, 232000, Anhui, China
| | - Yunyun Yang
- The First Affiliated Hospital of Xiamen University; Clinical laboratory; Xiamen Key Laboratory of Genetic Testing, Xiamen, 361000, Fujian, China
| | - Yu Chen
- National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Rutai Hui
- National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Mei Zhang
- The First Affiliated Hospital of Anhui University of Science and Technology (The First People's Hospital of Huainan City), Huainan, 232000, Anhui, China.
| | - Weili Zhang
- National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 100037, China. .,Central-China Branch of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Fuwai Central-China Hospital, Zhengzhou, 450046, China.
| |
Collapse
|
14
|
Chivers JM, Whiles SA, Miles CB, Biederman BE, Ellison MF, Lovingood CW, Wright MH, Hoover DB, Raafey MA, Youngberg GA, Venkatachalam MA, Zheleznova NN, Yang C, Liu P, Kriegel AJ, Cowley AW, O'Connor PM, Picken MM, Polichnowski AJ. Brown-Norway chromosome 1 mitigates the upregulation of proinflammatory pathways in mTAL cells and subsequent age-related CKD in Dahl SS/JrHsdMcwi rats. Am J Physiol Renal Physiol 2023; 324:F193-F210. [PMID: 36475869 PMCID: PMC9886360 DOI: 10.1152/ajprenal.00145.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 11/23/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Chronic kidney disease (CKD) has a strong genetic component; however, the underlying pathways are not well understood. Dahl salt-sensitive (SS)/Jr rats spontaneously develop CKD with age and are used to investigate the genetic determinants of CKD. However, there are currently several genetically diverse Dahl SS rats maintained at various institutions and the extent to which some exhibit age-related CKD is unclear. We assessed glomerulosclerosis (GS) and tubulointerstitial fibrosis (TIF) in 3- and 6-mo-old male and female SS/JrHsdMcwi, BN/NHsd/Mcwi [Brown-Norway (BN)], and consomic SS-Chr 1BN/Mcwi (SS.BN1) rats, in which chromosome 1 from the BN rat was introgressed into the genome of the SS/JrHsdMcwi rat. Rats were fed a 0.4% NaCl diet. GS (31 ± 3% vs. 7 ± 1%) and TIF (2.3 ± 0.2 vs. 0.5 ± 0.1) were significantly greater in 6-mo-old compared with 3-mo-old SS/JrHsdMcwi rats, and CKD was exacerbated in males. GS was minimal in 6- and 3-mo-old BN (3.9 ± 0.6% vs. 1.2 ± 0.4%) and SS.BN1 (2.4 ± 0.5% vs. 1.0 ± 0.3%) rats, and neither exhibited TIF. In SS/JrHsdMcwi and SS.BN1 rats, mean arterial blood pressure was significantly greater in 6-mo-old compared with 3-mo-old SS/JrHsdMcwi (162 ± 4 vs. 131 ± 2 mmHg) but not SS.BN1 (115 ± 2 vs. 116 ± 1 mmHg) rats. In 6-mo-old SS/JrHsdMcwi rats, blood pressure was significantly greater in females. RNA-sequencing analysis revealed that inflammatory pathways were upregulated in isolated medullary thick ascending tubules in 7-wk-old SS/JrHsdMcwi rats, before the development of tubule pathology, compared with SS.BN1 rats. In summary, SS/JrHsdMcwi rats exhibit robust age-related progression of medullary thick ascending limb abnormalities, CKD, and hypertension, and gene(s) on chromosome 1 have a major pathogenic role in such changes.NEW & NOTEWORTHY This study shows that the robust age-related progression of kidney disease in Dahl SS/JrHsdMcw rats maintained on a normal-salt diet is abolished in consomic SS.BN1 rats. Evidence that medullary thick ascending limb segments of SS/JrHsdMcw rats are structurally abnormal and enriched in proinflammatory pathways before the development of protein casts provides new insights into the pathogenesis of kidney disease in this model.
Collapse
Affiliation(s)
- Jacqueline M Chivers
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
| | - Shannon A Whiles
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
| | - Conor B Miles
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
| | - Brianna E Biederman
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
| | - Megan F Ellison
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
| | - Connor W Lovingood
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
| | - Marie H Wright
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
| | - Donald B Hoover
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
- Center of Excellence in Inflammation, Infectious Disease and Immunity, East Tennessee State University, Johnson City, Tennessee
| | - Muhammad A Raafey
- Department of Pathology, Quillen College of Medicine, East Tennessee State University, Johnson City, Tennessee
| | - George A Youngberg
- Department of Pathology, Quillen College of Medicine, East Tennessee State University, Johnson City, Tennessee
| | | | | | - Chun Yang
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Pengyuan Liu
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Alison J Kriegel
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Allen W Cowley
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Paul M O'Connor
- Department of Physiology, Augusta University, Augusta, Georgia
| | - Maria M Picken
- Department of Pathology, Loyola University Medical Center, Maywood, Illinois
| | - Aaron J Polichnowski
- Department of Biomedical Sciences, East Tennessee State University, Johnson City, Tennessee
- Center of Excellence in Inflammation, Infectious Disease and Immunity, East Tennessee State University, Johnson City, Tennessee
| |
Collapse
|
15
|
Abstract
Hundreds of different genetic causes of chronic kidney disease are now recognized, and while individually rare, taken together they are significant contributors to both adult and pediatric diseases. Traditional genetics approaches relied heavily on the identification of large families with multiple affected members and have been fundamental to the identification of genetic kidney diseases. With the increased utilization of massively parallel sequencing and improvements to genotype imputation, we can analyze rare variants in large cohorts of unrelated individuals, leading to personalized care for patients and significant research advancements. This review evaluates the contribution of rare disorders to patient care and the study of genetic kidney diseases and highlights key advancements that utilize new techniques to improve our ability to identify new gene-disease associations.
Collapse
Affiliation(s)
- Mark D Elliott
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA;
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
- Institute for Genomic Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Hila Milo Rasouly
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA;
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA;
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
- Institute for Genomic Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| |
Collapse
|
16
|
Guiney H, Walker R, Broadbent J, Caspi A, Goodin E, Kokaua J, Moffitt TE, Robertson S, Theodore R, Poulton R, Endre Z. Kidney-Function Trajectories From Young Adulthood to Midlife: Identifying Risk Strata and Opportunities for Intervention. Kidney Int Rep 2023; 8:51-63. [PMID: 36644353 PMCID: PMC9831942 DOI: 10.1016/j.ekir.2022.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 09/26/2022] [Accepted: 10/03/2022] [Indexed: 11/06/2022] Open
Abstract
Introduction Understanding normative patterns of change in kidney function over the life course may allow targeting of early interventions to slow or prevent the onset of kidney disease, but knowledge about kidney functional change before middle age is limited. This study used prospective longitudinal data from a representative birth cohort to examine common patterns of change from young to midadulthood and to identify risk factors and outcomes associated with poorer trajectories. Methods We used group-based trajectory modeling in the Dunedin study birth cohort (n = 857) to identify the following: (i) common kidney function trajectories between the ages 32 and 45 years, (ii) early-life factors associated with those trajectories, (iii) modifiable physical and psychosocial factors across adulthood associated with differences in trajectory slope, and (iv) links between trajectories and kidney-related outcomes at age 45 years. Results Three trajectory groups were identified and could be differentiated by age 32 years as follows: normal (58% of participants), low-normal (36%), and high-risk (6%) groups. Those from low socioeconomic backgrounds had higher odds of following a high-risk (vs. normal) trajectory. Modifiable factors (blood pressure, body mass index, inflammation, glycated hemoglobin, smoking, and socioeconomic status) across adulthood were associated with steeper age-related declines in kidney function, particularly among those in the low-normal and high-risk groups. Those in the low-normal and high-risk groups also had more adverse kidney-related outcomes at age 45 years. Conclusion The current findings could be used to inform the development of early interventions and point to socioeconomic conditions across the life course and health-related risk factors and behaviors in adulthood as kidney health promotion targets.
Collapse
Affiliation(s)
- Hayley Guiney
- Department of Psychology, Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand
| | - Robert Walker
- Department of Medicine, Otago Medical School, University of Otago, Dunedin, New Zealand
| | | | - Avshalom Caspi
- Social, Genetic, and Developmental Psychiatry Center, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina, USA
| | - Elizabeth Goodin
- Department of Women’s and Children’s Health, Otago Medical School, University of Otago, Dunedin, New Zealand
| | - Jesse Kokaua
- Department of Psychology, Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand
- Centre for Pacific Health, Va’a O Tautai, Division of Health Sciences, University of Otago, Dunedin, New Zealand
| | - Terrie E. Moffitt
- Social, Genetic, and Developmental Psychiatry Center, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina, USA
| | - Stephen Robertson
- Department of Women’s and Children’s Health, Otago Medical School, University of Otago, Dunedin, New Zealand
| | - Reremoana Theodore
- Department of Psychology, Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand
| | - Richie Poulton
- Department of Psychology, Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand
| | - Zoltan Endre
- Department of Nephrology, Prince of Wales Hospital, Randwick, New South Wales, Australia
- University of New South Wales, Kensington, New South Wales, Australia
- Department of Medicine, University of Otago, Christchurch, New Zealand
| |
Collapse
|
17
|
Haj AK, Hasan H, Raife TJ. Heritability of Protein and Metabolite Biomarkers Associated with COVID-19 Severity: A Metabolomics and Proteomics Analysis. Biomolecules 2022; 13:46. [PMID: 36671431 PMCID: PMC9855380 DOI: 10.3390/biom13010046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/20/2022] [Accepted: 12/24/2022] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVES Prior studies have characterized protein and metabolite changes associated with SARS-CoV-2 infection; we hypothesized that these biomarkers may be part of heritable metabolic pathways in erythrocytes. METHODS Using a twin study of erythrocyte protein and metabolite levels, we describe the heritability of, and correlations among, previously identified biomarkers that correlate with COVID-19 severity. We used gene ontology and pathway enrichment analysis tools to identify pathways and biological processes enriched among these biomarkers. RESULTS Many COVID-19 biomarkers are highly heritable in erythrocytes. Among heritable metabolites downregulated in COVID-19, metabolites involved in amino acid metabolism and biosynthesis are enriched. Specific amino acid metabolism pathways (valine, leucine, and isoleucine biosynthesis; glycine, serine, and threonine metabolism; and arginine biosynthesis) are heritable in erythrocytes. CONCLUSIONS Metabolic pathways downregulated in COVID-19, particularly amino acid biosynthesis and metabolism pathways, are heritable in erythrocytes. This finding suggests that a component of the variation in COVID-19 severity may be the result of phenotypic variation in heritable metabolic pathways; future studies will be necessary to determine whether individual variation in amino acid metabolism pathways correlates with heritable outcomes of COVID-19.
Collapse
Affiliation(s)
| | | | - Thomas J. Raife
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, 3170 UW Medical Foundation Centennial Building (MFCB), Madison, WI 53705-2281, USA
| |
Collapse
|
18
|
Chen YC, Wong HSC, Wu MY, Chou WH, Kao CC, Chao CH, Chang WC, Wu MS. Genome-Wide Association Study for eGFR in a Taiwanese Population. Clin J Am Soc Nephrol 2022; 17:1598-1608. [PMID: 36223920 PMCID: PMC9718044 DOI: 10.2215/cjn.02180222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND OBJECTIVES Chronic kidney disease (CKD) is a global public health issue associated with large economic burdens. CKD contributes to higher risks of cardiovascular complications, kidney failure, and mortality. The incidence and prevalence rates of kidney failure in Taiwan have remained the highest in the world. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Assessing genetic factors that influence kidney function in specific populations has substantial clinical relevance. We investigated associations of genetic variants with eGFR. The quality control filtering and genotype imputation resulted in 10,008 Taiwan Biobank participants and 6,553,511 variants for final analyses. We examined these loci with in silico replication in individuals of European and African ancestry. RESULTS Our results revealed one significant locus (4q21.1) and three suggestive significant loci (17q23.2, 22q13.2, and 3q29) for eGFR in the Taiwanese population. In total, four conditional-independent single nucleotide polymorphisms were identified as the most important variants within these regions, including rs55948430 (Coiled-Coil Domain Containing 158), rs1010269 (BCAS3), rs56108505 (MKL1), and rs34796810 (upstream of DLG1). By performing a meta-analysis, we found that the 4q21.1 and 17q23.2 loci were successfully replicated in the European population, whereas only the 17q23.2 locus was replicated in African ancestry. Therefore, these two loci are suggested to be transethnic loci, and the other two eGFR-associated loci (22q13.2 and 3q29) are likely population specific. CONCLUSIONS We identified four susceptibility loci on 4q21.1, 17q23.2, 22q13.2, and 3q29 that associated with kidney-related traits in a Taiwanese population. The 22q13.2 (MKL1) and 3q29 (DLG1) were prioritized as critical candidates. Functional analyses delineated novel pathways related to kidney physiology in Taiwanese and East Asian ancestries.
Collapse
Affiliation(s)
- Ying-Chun Chen
- Master Program in Clinical Genomics and Proteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
| | - Henry Sung-Ching Wong
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Mei-Yi Wu
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Department of Primary Care Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
- Division of Nephrology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Division of Nephrology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
- Taipei Medical University Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan
| | - Wan-Hsuan Chou
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Chih-Chin Kao
- Division of Nephrology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Taipei Medical University Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan
- Division of Nephrology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan
| | - Ching-Hsuan Chao
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Wei-Chiao Chang
- Master Program in Clinical Genomics and Proteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Department of Pharmacy, Taipei Medical University–Wan Fang Hospital, Taipei, Taiwan
- Integrative Research Center for Critical Care, Department of Pharmacy, Wanfang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Mai-Szu Wu
- Master Program in Clinical Genomics and Proteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
- Division of Nephrology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
- Taipei Medical University Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan
- Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| |
Collapse
|
19
|
Akinnibosun OA, Maier MC, Eales J, Tomaszewski M, Charchar FJ. Telomere therapy for chronic kidney disease. Epigenomics 2022; 14:1039-1054. [PMID: 36177720 DOI: 10.2217/epi-2022-0073] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Chronic kidney disease (CKD) is estimated to affect almost 10% of individuals worldwide and is one of the leading causes of morbidity and mortality. Renal fibrosis, a central pathway in CKD progression (irrespective of etiology), is associated with shortened or dysfunctional telomeres in animal studies. Telomeres are specialized nucleoprotein structures located at the chromosome end that maintain genomic integrity. The mechanisms of associations between telomere length and CKD have not yet been fully elucidated, however, CKD patients with shorter telomere length may have decreased renal function and a higher mortality rate. A plethora of ongoing research has focused on possible therapeutic applications of telomeres with the overall goal to preserve telomere length as a therapy to treat CKD.
Collapse
Affiliation(s)
| | - Michelle C Maier
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Victoria, Australia
| | - James Eales
- Division of Cardiovascular Sciences, University of Manchester, Manchester, UK
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, University of Manchester, Manchester, UK.,Manchester Heart Centre and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Fadi J Charchar
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Victoria, Australia.,Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.,Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
20
|
Khan A, Turchin MC, Patki A, Srinivasasainagendra V, Shang N, Nadukuru R, Jones AC, Malolepsza E, Dikilitas O, Kullo IJ, Schaid DJ, Karlson E, Ge T, Meigs JB, Smoller JW, Lange C, Crosslin DR, Jarvik GP, Bhatraju PK, Hellwege JN, Chandler P, Torvik LR, Fedotov A, Liu C, Kachulis C, Lennon N, Abul-Husn NS, Cho JH, Ionita-Laza I, Gharavi AG, Chung WK, Hripcsak G, Weng C, Nadkarni G, Irvin MR, Tiwari HK, Kenny EE, Limdi NA, Kiryluk K. Genome-wide polygenic score to predict chronic kidney disease across ancestries. Nat Med 2022; 28:1412-1420. [PMID: 35710995 PMCID: PMC9329233 DOI: 10.1038/s41591-022-01869-1] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 05/11/2022] [Indexed: 01/03/2023]
Abstract
Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.
Collapse
Affiliation(s)
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Michael C Turchin
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amit Patki
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ning Shang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Rajiv Nadukuru
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alana C Jones
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Ozan Dikilitas
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Daniel J Schaid
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Elizabeth Karlson
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tian Ge
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - James B Meigs
- Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Jordan W Smoller
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Christoph Lange
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - David R Crosslin
- Division of Biomedical Informatics and Genomics, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA
| | - Pavan K Bhatraju
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jacklyn N Hellwege
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paulette Chandler
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Laura Rasmussen Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Alex Fedotov
- Irving Institute for Clinical and Translational Research, Columbia University, New York, NY, USA
| | - Cong Liu
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | | | - Niall Lennon
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Noura S Abul-Husn
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Judy H Cho
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Girish Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nita A Limdi
- Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.
| |
Collapse
|
21
|
Hill C, Avila-Palencia I, Maxwell AP, Hunter RF, McKnight AJ. Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease. FRONTIERS IN NEPHROLOGY 2022; 2:923068. [PMID: 37674991 PMCID: PMC10479694 DOI: 10.3389/fneph.2022.923068] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 05/30/2022] [Indexed: 09/08/2023]
Abstract
Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.
Collapse
Affiliation(s)
| | | | | | | | - Amy Jayne McKnight
- Centre for Public Health, Queen’s University Belfast, Belfast, United Kingdom
| |
Collapse
|
22
|
Kim J, Jensen A, Ko S, Raghavan S, Phillips LS, Hung A, Sun Y, Zhou H, Reaven P, Zhou JJ. Systematic Heritability and Heritability Enrichment Analysis for Diabetes Complications in UK Biobank and ACCORD Studies. Diabetes 2022; 71:1137-1148. [PMID: 35133398 PMCID: PMC9044130 DOI: 10.2337/db21-0839] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 02/02/2022] [Indexed: 11/13/2022]
Abstract
Diabetes-related complications reflect longstanding damage to small and large vessels throughout the body. In addition to the duration of diabetes and poor glycemic control, genetic factors are important contributors to the variability in the development of vascular complications. Early heritability studies found strong familial clustering of both macrovascular and microvascular complications. However, they were limited by small sample sizes and large phenotypic heterogeneity, leading to less accurate estimates. We take advantage of two independent studies-UK Biobank and the Action to Control Cardiovascular Risk in Diabetes trial-to survey the single nucleotide polymorphism heritability for diabetes microvascular (diabetic kidney disease and diabetic retinopathy) and macrovascular (cardiovascular events) complications. Heritability for diabetic kidney disease was estimated at 29%. The heritability estimate for microalbuminuria ranged from 24 to 60% and was 41% for macroalbuminuria. Heritability estimates of diabetic retinopathy ranged from 6 to 33%, depending on the phenotype definition. More severe diabetes retinopathy possessed higher genetic contributions. We show, for the first time, that rare variants account for much of the heritability of diabetic retinopathy. This study suggests that a large portion of the genetic risk of diabetes complications is yet to be discovered and emphasizes the need for additional genetic studies of diabetes complications.
Collapse
Affiliation(s)
- Juhyun Kim
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI
| | - Aubrey Jensen
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA
| | - Seyoon Ko
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA
| | - Sridharan Raghavan
- University of Colorado School of Medicine, Aurora, CO
- Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO
| | - Lawrence S. Phillips
- Division of Endocrinology, Emory University School of Medicine, Atlanta, GA
- Atlanta Veterans Affairs Medical Center, Decatur, GA
| | - Adriana Hung
- Tennessee Valley Healthcare System and Vanderbilt University, Nashville, TN
| | - Yan Sun
- Department of Epidemiology, Emory University, Atlanta, GA
| | - Hua Zhou
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA
| | - Peter Reaven
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | - Jin J. Zhou
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA
| |
Collapse
|
23
|
Wang R, Snieder H, Hartman CA. Familial co-aggregation and shared heritability between depression, anxiety, obesity and substance use. Transl Psychiatry 2022; 12:108. [PMID: 35296640 PMCID: PMC8927111 DOI: 10.1038/s41398-022-01868-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 02/22/2022] [Accepted: 02/24/2022] [Indexed: 11/09/2022] Open
Abstract
Depression, anxiety, obesity and substance use are heritable and often co-occur. However, the mechanisms underlying this co-occurrence are not fully understood. We estimated their familial aggregation and co-aggregation as well as heritabilities and genetic correlations to improve etiological understanding. Data came from the multi-generational population-based Lifelines Cohort Study (n = 162,439). Current depression and anxiety were determined using the MINI International Neuropsychiatric Interview. Smoking, alcohol and drug use were assessed by self-report questionnaires. Body mass index (BMI) and obesity were calculated by measured height and weight. Modified Cox proportional hazards models estimated recurrence risk ratios (λR), and restricted maximum likelihood variance decomposition methods estimated heritabilities (h2) and genetic correlations (rG). All analyses were adjusted for age, age2, and sex. Depression, anxiety, obesity and substance use aggregated within families (λR first-degree relative = 1.08-2.74) as well as between spouses (λR = 1.11-6.60). All phenotypes were moderately heritable (from h2depression = 0.25 to h2BMI = 0.53). Depression, anxiety, obesity and smoking showed positive familial co-aggregation. That is, each of these traits confers increased risk on the other ones within families, consistent with the positive genetic correlations between these phenotypes (rG = 0.16-0.94). The exception was obesity, which showed a negative co-aggregation with alcohol and drug use and vice versa, consistent with the negative genetic correlations of BMI with alcohol (rG = -0.14) and soft drug use (rG = -0.10). Patterns of cross-phenotype recurrence risk highlight the co-occurrence among depression, anxiety, obesity and substance use within families. Patterns of genetic overlap between these phenotypes provide clues to uncovering the mechanisms underlying familial co-aggregation.
Collapse
Affiliation(s)
- Rujia Wang
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.
| | - Harold Snieder
- grid.4494.d0000 0000 9558 4598Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Catharina A. Hartman
- grid.4494.d0000 0000 9558 4598Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| |
Collapse
|
24
|
Piras D, Lepori N, Cabiddu G, Pani A. How Genetics Can Improve Clinical Practice in Chronic Kidney Disease: From Bench to Bedside. J Pers Med 2022; 12:jpm12020193. [PMID: 35207681 PMCID: PMC8875178 DOI: 10.3390/jpm12020193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/17/2022] [Accepted: 01/24/2022] [Indexed: 01/27/2023] Open
Abstract
Chronic kidney disease (CKD) is considered a major global health problem with high socio-economic costs: the risk of CKD in individuals with an affected first degree relative has been found to be three times higher than in the general population. Genetic factors are known to be involved in CKD pathogenesis, both due to the possible presence of monogenic pathologies as causes of CKD, and to the role of numerous gene variants in determining susceptibility to the development of CKD. The genetic study of CKD patients can represent a useful tool in the hands of the clinician; not only in the diagnostic and prognostic field, but potentially also in guiding therapeutic choices and in designing clinical trials. In this review we discuss the various aspects of the role of genetic analysis on clinical management of patients with CKD with a focus on clinical applications. Several topics are discussed in an effort to provide useful information for daily clinical practice: definition of susceptibility to the development of CKD, identification of unrecognized monogenic diseases, reclassification of the etiological diagnosis, role of pharmacogenetics.
Collapse
Affiliation(s)
- Doloretta Piras
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Correspondence:
| | - Nicola Lepori
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
| | - Gianfranca Cabiddu
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Dipartimento di Scienze Mediche e Sanità Pubblica, Università degli Studi di Cagliari, 09134 Cagliari, Italy
| | - Antonello Pani
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Dipartimento di Scienze Mediche e Sanità Pubblica, Università degli Studi di Cagliari, 09134 Cagliari, Italy
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerce (CNR), 09042 Monserrato, Italy
| |
Collapse
|
25
|
Dhande IS, Braun MC, Doris PA. Emerging Insights Into Chronic Renal Disease Pathogenesis in Hypertension From Human and Animal Genomic Studies. Hypertension 2021; 78:1689-1700. [PMID: 34757770 PMCID: PMC8577298 DOI: 10.1161/hypertensionaha.121.18112] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The pathogenic links between elevated blood pressure and chronic kidney disease remain obscure. This article examines progress in population genetics and in animal models of hypertension and chronic kidney disease. It also provides a critique of the application of genome-wide association studies to understanding the heritability of renal function. Emerging themes identified indicate that heritable risk of chronic kidney disease in hypertension can arise from genetic variation in (1) glomerular and tubular protein handling mechanisms; (2) autoregulatory capacity of the renal vasculature; and (3) innate and adaptive immune mechanisms. Increased prevalence of hypertension-associated chronic kidney disease that occurs with aging may reflect amplification of heritable risks by normal aging processes affecting immunity and autoregulation.
Collapse
Affiliation(s)
- Isha S. Dhande
- Center for Human Genetics, Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas HSC, Houston (I.S.D., P.A.D.)
| | - Michael C. Braun
- Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston (M.C.B.)
| | - Peter A. Doris
- Center for Human Genetics, Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas HSC, Houston (I.S.D., P.A.D.)
| |
Collapse
|
26
|
Ibrahim HN, Murad DN, Hebert SA, Adrogue HE, Nguyen H, Nguyen DT, Matas AJ, Graviss EA. Intermediate Renal Outcomes, Kidney Failure, and Mortality in Obese Kidney Donors. J Am Soc Nephrol 2021; 32:2933-2947. [PMID: 34675059 PMCID: PMC8806092 DOI: 10.1681/asn.2021040548] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 08/04/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Obesity is associated with the two archetypal kidney disease risk factors: hypertension and diabetes. Concerns that the effects of diabetes and hypertension in obese kidney donors might be magnified in their remaining kidney have led to the exclusion of many obese candidates from kidney donation. METHODS We compared mortality, diabetes, hypertension, proteinuria, reduced eGFR and its trajectory, and the development of kidney failure in 8583 kidney donors, according to body mass index (BMI). The study included 6822 individuals with a BMI of <30 kg/m2, 1338 with a BMI of 30-34.9 kg/m2, and 423 with a BMI of ≥35 kg/m2. We used Cox regression models, adjusting for baseline covariates only, and models adjusting for postdonation diabetes, hypertension, and kidney failure as time-varying covariates. RESULTS Obese donors were more likely than nonobese donors to develop diabetes, hypertension, and proteinuria. The increase in eGFR in obese versus nonobese donors was significantly higher in the first 10 years (3.5 ml/min per 1.73m2 per year versus 2.4 ml/min per 1.73m2 per year; P<0.001), but comparable thereafter. At a mean±SD follow-up of 19.3±10.3 years after donation, 31 (0.5%) nonobese and 12 (0.7%) obese donors developed ESKD. Of the 12 patients with ESKD in obese donors, 10 occurred in 1445 White donors who were related to the recipient (0.9%). Risk of death in obese donors was not significantly increased compared with nonobese donors. CONCLUSIONS Obesity in kidney donors, as in nondonors, is associated with increased risk of developing diabetes and hypertension. The absolute risk of ESKD is small and the risk of death is comparable to that of nonobese donors.
Collapse
Affiliation(s)
| | - Dina N. Murad
- Department of Medicine, Houston Methodist Hospital, Houston, Texas
| | - Sean A. Hebert
- Department of Medicine, Houston Methodist Hospital, Houston, Texas
| | | | - Hana Nguyen
- Department of Medicine, Houston Methodist Hospital, Houston, Texas
| | - Duc T. Nguyen
- Department of Pathology and Genomic Medicine, Institute for Academic Medicine, Houston Methodist Research Institute, Houston, Texas
| | - Arthur J. Matas
- Department of Surgery, University of Minnesota, Minneapolis, Minnesota
| | - Edward A. Graviss
- Department of Pathology and Genomic Medicine, Institute for Academic Medicine, Houston Methodist Research Institute, Houston, Texas
- Department of Surgery, Houston Methodist Hospital, Houston, Texas
| |
Collapse
|
27
|
Tran NK, Lea RA, Holland S, Nguyen Q, Raghubar AM, Sutherland HG, Benton MC, Haupt LM, Blackburn NB, Curran JE, Blangero J, Mallett AJ, Griffiths LR. Multi-phenotype genome-wide association studies of the Norfolk Island isolate implicate pleiotropic loci involved in chronic kidney disease. Sci Rep 2021; 11:19425. [PMID: 34593906 PMCID: PMC8484585 DOI: 10.1038/s41598-021-98935-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 09/14/2021] [Indexed: 11/14/2022] Open
Abstract
Chronic kidney disease (CKD) is a persistent impairment of kidney function. Genome-wide association studies (GWAS) have revealed multiple genetic loci associated with CKD susceptibility but the complete genetic basis is not yet clear. Since CKD shares risk factors with cardiovascular diseases and diabetes, there may be pleiotropic loci at play but may go undetected when using single phenotype GWAS. Here, we used multi-phenotype GWAS in the Norfolk Island isolate (n = 380) to identify new loci associated with CKD. We performed a principal components analysis on different combinations of 29 quantitative traits to extract principal components (PCs) representative of multiple correlated phenotypes. GWAS of a PC derived from glomerular filtration rate, serum creatinine, and serum urea identified a suggestive peak (pmin = 1.67 × 10-7) that mapped to KCNIP4. Inclusion of other secondary CKD measurements with these three kidney function traits identified the KCNIP4 locus with GWAS significance (pmin = 1.59 × 10-9). Finally, we identified a group of two SNPs with increased minor allele frequencies as potential functional variants. With the use of genetic isolate and the PCA-based multi-phenotype GWAS approach, we have revealed a potential pleotropic effect locus for CKD. Further studies are required to assess functional relevance of this locus.
Collapse
Affiliation(s)
- Ngan K Tran
- School of Biomedical Sciences, Centre for Genomics and Personalised Health, Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia
| | - Rodney A Lea
- School of Biomedical Sciences, Centre for Genomics and Personalised Health, Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia
| | - Samuel Holland
- Institute for Molecular Bioscience & Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Quan Nguyen
- Institute for Molecular Bioscience & Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Arti M Raghubar
- Institute for Molecular Bioscience & Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Heidi G Sutherland
- School of Biomedical Sciences, Centre for Genomics and Personalised Health, Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia
| | - Miles C Benton
- Institute of Environmental Science and Research, Kenepuru, New Zealand
| | - Larisa M Haupt
- School of Biomedical Sciences, Centre for Genomics and Personalised Health, Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia
| | - Nicholas B Blackburn
- School of Medicine, South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley, Brownsville, TX, USA
- Department of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Joanne E Curran
- School of Medicine, South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley, Brownsville, TX, USA
- Department of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - John Blangero
- School of Medicine, South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley, Brownsville, TX, USA
- Department of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Andrew J Mallett
- Institute for Molecular Bioscience & Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Department of Renal Medicine, Townsville University Hospital, Townsville, QLD, Australia
- College of Medicine & Dentistry, James Cook University, Townsville, QLD, Australia
| | - Lyn R Griffiths
- School of Biomedical Sciences, Centre for Genomics and Personalised Health, Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia.
| |
Collapse
|
28
|
Carlassara L, Zanoni F, Gharavi AG. Familial Aggregation of CKD: Gene or Environment? Am J Kidney Dis 2021; 77:861-862. [PMID: 33583624 DOI: 10.1053/j.ajkd.2020.12.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 12/31/2020] [Indexed: 11/11/2022]
Affiliation(s)
- Lucrezia Carlassara
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York; Division of Nephrology and Dialysis, Hospital of Belluno, Belluno, Italy
| | - Francesca Zanoni
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York
| | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
| |
Collapse
|