Meta-Analysis

. 2024 Jan 10;4(1):100468.

doi: 10.1016/j.xgen.2023.100468. Epub 2023 Dec 22.

Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

Odessica Hughes¹, Amy R Bentley², Charles E Breeze³, Francois Aguet⁴, Xiaoguang Xu⁵, Girish Nadkarni⁶, Quan Sun⁷, Bridget M Lin⁷, Thomas Gilliland⁸, Mariah C Meyer⁹, Jiawen Du⁷, Laura M Raffield¹⁰, Holly Kramer¹¹, Robert W Morton¹², Mateus H Gouveia², Elizabeth G Atkinson¹³, Adan Valladares-Salgado¹⁴, Niels Wacher-Rodarte¹⁵, Nicole D Dueker¹⁶, Xiuqing Guo¹⁷, Yang Hai¹⁷, Adebowale Adeyemo², Lyle G Best¹⁸, Jianwen Cai⁷, Guanjie Chen², Michael Chong¹², Ayo Doumatey², James Eales⁵, Mark O Goodarzi¹⁹, Eli Ipp²⁰, Marguerite Ryan Irvin²¹, Minzhi Jiang²², Alana C Jones²¹, Charles Kooperberg²³, Jose E Krieger²⁴, Ethan M Lange⁹, Matthew B Lanktree²⁵, James P Lash²⁶, Paulo A Lotufo²⁷, Ruth J F Loos²⁸, Vy Thi Ha My⁶, Jesús Peralta-Romero¹⁴, Lihong Qi²⁹, Leslie J Raffel³⁰, Stephen S Rich³¹, Erik J Rodriquez³², Eduardo Tarazona-Santos³³, Kent D Taylor¹⁷, Jason G Umans³⁴, Jia Wen¹⁰, Bessie A Young³⁵, Zhi Yu³⁶, Ying Zhang³⁷, Yii-Der Ida Chen¹⁷, Tanja Rundek³⁸, Jerome I Rotter¹⁷, Miguel Cruz¹⁴, Myriam Fornage³⁹, Maria Fernanda Lima-Costa⁴⁰, Alexandre C Pereira⁴¹, Guillaume Paré¹², Pradeep Natarajan⁸, Shelley A Cole⁴², April P Carson⁴³, Leslie A Lange⁹, Yun Li⁷, Eliseo J Perez-Stable⁴⁴, Ron Do⁶, Fadi J Charchar⁴⁵, Maciej Tomaszewski⁴⁶, Josyf C Mychaleckyj²⁹, Charles Rotimi², Andrew P Morris⁴⁷, Nora Franceschini⁴⁸

Affiliations

¹ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.
² Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
³ Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department Health and Human Services, Bethesda, MD, USA; UCL Cancer Institute, University College London, London, UK.
⁴ The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁵ Division of Cardiovascular Sciences, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, UK.
⁶ The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁷ Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
⁸ Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA.
⁹ Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹⁰ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹¹ Division of Nephrology and Hypertension, Loyola University Chicago, Maywood, IL, USA.
¹² Population Health Research Institute, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada.
¹³ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
¹⁴ Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
¹⁵ Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
¹⁶ John P Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA.
¹⁷ 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.
¹⁸ Missouri Breaks Industries Research Inc., Eagle Butte, SD, USA.
¹⁹ Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
²⁰ Division of Endocrinology and Metabolism, Department of Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
²¹ Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
²² Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
²³ Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
²⁴ Laboratório de Genética e Cardiologia Molecular do Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
²⁵ Division of Nephrology, Department of Medicine, McMaster University, Hamilton, ON, Canada.
²⁶ Division of Nephrology, Department of Medicine, University of Illinois, Chicago, IL, USA.
²⁷ Center for Clinical and Epidemiological Research, Hospital Universitário, Universidade de São Paulo (USP), São Paulo, Brazil.
²⁸ The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
²⁹ Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA, USA.
³⁰ Department of Pediatrics, Genetic and Genomic Medicine, University of California, Irvine, Irvine, CA, USA.
³¹ Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
³² Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
³³ Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
³⁴ MedStar Health Research Institute, Hyattsville MD and Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA.
³⁵ University of Washington School of Medicine, Seattle, WA, USA; Office of Healthcare Equity, UW Justice, Equity, Diversity, and Inclusion Center for Transformational Research (UW JEDI-CTR), University of Washington, Seattle, WA, USA; Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, USA; Kidney Research Institute, Department of Medicine, University of Washington, Seattle, WA, USA.
³⁶ Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA.
³⁷ Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, The University of Oklahoma Health Sciences Center, Oklahoma, OK, USA.
³⁸ Department of Neurology, Epidemiology and Public Health, Miller School of Medicine, University of Miami, Miami, FL, USA.
³⁹ Brown Foundation Institute of Molecular Medicine, Houston, TX, USA.
⁴⁰ Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Brazil.
⁴¹ Laboratório de Genética e Cardiologia Molecular do Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Aging Division, Brigham Women's Hospital, Department of Medicine, Harvard Medical School, Boston, MA, USA.
⁴² Texas Biomedical Research Institute, San Antonio, TX, USA.
⁴³ Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
⁴⁴ National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA.
⁴⁵ School of Science, Psychology and Sport, Federation University, Ballarat, VIC, Australia; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; Department of Physiology, University of Melbourne, Melbourne, VIC, Australia.
⁴⁶ Division of Cardiovascular Sciences, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, UK; Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
⁴⁷ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK. Electronic address: andrew.morris-5@manchester.ac.uk.
⁴⁸ Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: noraf@unc.edu.

PMID: 38190104
PMCID: PMC10794846
DOI: 10.1016/j.xgen.2023.100468

Meta-Analysis

Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

Odessica Hughes et al. Cell Genom. 2024.

. 2024 Jan 10;4(1):100468.

doi: 10.1016/j.xgen.2023.100468. Epub 2023 Dec 22.

Authors

Affiliations

¹ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.
² Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
³ Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department Health and Human Services, Bethesda, MD, USA; UCL Cancer Institute, University College London, London, UK.
⁴ The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁵ Division of Cardiovascular Sciences, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, UK.
⁶ The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁷ Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
⁸ Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA.
⁹ Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹⁰ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹¹ Division of Nephrology and Hypertension, Loyola University Chicago, Maywood, IL, USA.
¹² Population Health Research Institute, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada.
¹³ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
¹⁴ Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
¹⁵ Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
¹⁶ John P Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA.
¹⁷ 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.
¹⁸ Missouri Breaks Industries Research Inc., Eagle Butte, SD, USA.
¹⁹ Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
²⁰ Division of Endocrinology and Metabolism, Department of Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
²¹ Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
²² Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
²³ Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
²⁴ Laboratório de Genética e Cardiologia Molecular do Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
²⁵ Division of Nephrology, Department of Medicine, McMaster University, Hamilton, ON, Canada.
²⁶ Division of Nephrology, Department of Medicine, University of Illinois, Chicago, IL, USA.
²⁷ Center for Clinical and Epidemiological Research, Hospital Universitário, Universidade de São Paulo (USP), São Paulo, Brazil.
²⁸ The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
²⁹ Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA, USA.
³⁰ Department of Pediatrics, Genetic and Genomic Medicine, University of California, Irvine, Irvine, CA, USA.
³¹ Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
³² Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
³³ Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
³⁴ MedStar Health Research Institute, Hyattsville MD and Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA.
³⁵ University of Washington School of Medicine, Seattle, WA, USA; Office of Healthcare Equity, UW Justice, Equity, Diversity, and Inclusion Center for Transformational Research (UW JEDI-CTR), University of Washington, Seattle, WA, USA; Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, USA; Kidney Research Institute, Department of Medicine, University of Washington, Seattle, WA, USA.
³⁶ Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA.
³⁷ Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, The University of Oklahoma Health Sciences Center, Oklahoma, OK, USA.
³⁸ Department of Neurology, Epidemiology and Public Health, Miller School of Medicine, University of Miami, Miami, FL, USA.
³⁹ Brown Foundation Institute of Molecular Medicine, Houston, TX, USA.
⁴⁰ Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Brazil.
⁴¹ Laboratório de Genética e Cardiologia Molecular do Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Aging Division, Brigham Women's Hospital, Department of Medicine, Harvard Medical School, Boston, MA, USA.
⁴² Texas Biomedical Research Institute, San Antonio, TX, USA.
⁴³ Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
⁴⁴ National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA.
⁴⁵ School of Science, Psychology and Sport, Federation University, Ballarat, VIC, Australia; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; Department of Physiology, University of Melbourne, Melbourne, VIC, Australia.
⁴⁶ Division of Cardiovascular Sciences, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, UK; Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
⁴⁷ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK. Electronic address: andrew.morris-5@manchester.ac.uk.
⁴⁸ Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: noraf@unc.edu.

PMID: 38190104
PMCID: PMC10794846
DOI: 10.1016/j.xgen.2023.100468

Abstract

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10^-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.

Keywords: admixed populations; chronic kidney disease; eGFR; expression quantitative trait locus; fine-mapping; genome-wide association study; kidney function; multi-ancestry; polygenic scores.

PubMed Disclaimer

Conflict of interest statement

Declaration of interests P.N. reports investigator-initiated research grants from Allelica, Apple, Amgen, Boston Scientific, Genentech/Roche, and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Eli Lilly & Co, Foresite Labs, Genentech/Roche, GV, HeartFlow, Magnet Biomedicine, and Novartis, scientific advisory board membership of Esperion Therapeutics, Preciseli, and TenSixteen Bio, scientific co-founder of TenSixteen Bio, equity in MyOme, Preciseli, and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. M.B.L. has received speaker and advisory fees from Otsuka, Reata, Bayer, and Sanofi Genzyme. G.P. has received speaker and advisory fees from Amgen, Bayer, Novartis, and Sanofi, and has received research grants from Bayer and Sanofi. L.M.R. is a consultant for the TOPMed Administrative Coordinating Center (through Westat).

Figures

**Figure 1**
Analytical pipeline In step 1, we conducted multi-ancestry meta-analysis of eGFR GWAS in 145,732 AFR and AMS individuals from the COGENT Kidney Consortium and Million Veteran Program (MVP). In step 2, we performed downstream integration with functional genomics resources to understand the effector genes and molecular mechanisms through which eGFR association signals are mediated. These analyses included correlation with eQTL in kidney from the Human Kidney Tissue Resource and The Cancer Genome Atlas, and in blood from the Genes-Environments and Admixture in Latino Asthmatics study and the Study of African Americans, Asthma, Genes, and Environments, and the Multi-Ethnic Study of Atherosclerosis. In step 3, we assessed evidence of heterogeneity in allelic effects at eGFR association signals that is driven by sex and/or ancestry. In step 4, we constructed ancestry-specific and multi-ancestry polygenic scores to assess transferability into AFR and AMS individuals.

**Figure 2**
Manhattan plot and quantile-quantile (QQ) plot of genome-wide eGFR association from combined meta-analysis of up to 145,732 AFR and AMS individuals In the Manhattan plot, each point represents an SNV passing quality control in the meta-analysis, plotted with their observed association p value (on a –log₁₀ scale) as a function of genomic position (NCBI build 37). The genome-wide significance threshold (p < 5 × 10⁻⁸) is highlighted by the horizontal red line. The names and locations of novel loci are indicated. In the QQ plot, each point represents an SNV passing quality control in the meta-analysis, plotted with the observed association p value (on a –log₁₀ scale) as a function of their expected association p value (on a –log₁₀ scale).

**Figure 3**
Genomic variants associated with eGFR highlight kidney regulatory elements Shown are the results of FORGE2 analysis for the top 1,000 eGFR SNVs. The horizontal axis shows FORGE2 enrichment (–log₁₀ p value) of the eGFR SNV set with DNase I hotspots for a range of cell and tissue samples (vertical axis, significant samples in black). The top ranked sample set (highest black points) indicate the most significant association is for kidney samples (i.e., are highly ranked for the top 1,000 SNVs associated with eGFR).

**Figure 4**
Transferability of multi-ancestry and ancestry-specific polygenic scores for eGFR into AFR and AMS test GWAS Polygenic scores were constructed using PRS-CS, and their performance assessed in eight test GWASs. For each test GWAS, five polygenic scores were constructed: multi-ancestry (AFR + AMS), AFR specific, AMS specific, East Asian (EAS) specific from BioBank Japan, and European (EUR) specific from the CKDGen Consortium. Linkage disequilibrium (LD) was matched to the ancestry of the test GWAS. The eGFR variance explained by each polygenic score was estimated in each test GWAS. The relative performance of the polygenic scores varied across test GWAS. The multi-ancestry (AFR + AMS) and AFR-specific polygenic scores explained the highest proportion of eGFR variance in African American test GWAS (REGARDS, WHI-AA, BIOME-AA). In contrast, the EUR-specific polygenic score explained the highest proportion of eGFR variance in the AMS test GWAS (BIOME-HA, HCHS/SOL-MAIN, BAMBUI, SHS). All polygenic scores explained a low proportion of eGFR variance in West Africans from Nigeria and Ghana (AADM).

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Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

Affiliations

Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources