Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities

Richard J. Reynolds; M. Ryan Irvin; S. Louis Bridges; Hwasoon Kim; Tony R. Merriman; Donna K. Arnett; Jasvinder A. Singh; Nicholas A. Sumpter; Alexa S. Lupi; Ana I. Vazquez

doi:10.1038/s41431-021-00830-z

Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities

Richard J. Reynolds, M. Ryan Irvin, S. Louis Bridges, Hwasoon Kim, Tony R. Merriman, Donna K. Arnett, Jasvinder A. Singh, Nicholas A. Sumpter, Alexa S. Lupi, Ana I. Vazquez

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

Hypertension, obesity, chronic kidney disease and type 2 diabetes are comorbidities that have very high prevalence among persons with hyperuricemia (serum urate > 6.8 mg/dL) and gout. Here we use multivariate genetic models to test the hypothesis that the co-association of traits representing hyperuricemia and its comorbidities is genetically based. Using Bayesian whole-genome regression models, we estimated the genetic marker-based variance and the covariance between serum urate, serum creatinine, systolic blood pressure (SBP), blood glucose and body mass index (BMI) from two independent family-based studies: The Framingham Heart Study-FHS and the Hypertension Genetic Epidemiology Network study-HyperGEN. The main genetic findings that replicated in both FHS and HyperGEN, were (1) creatinine was genetically correlated only with urate and (2) BMI was genetically correlated with urate, SBP, and glucose. The environmental covariance among the traits was generally highest for trait pairs involving BMI. The genetic overlap of traits representing the comorbidities of hyperuricemia and gout appears to cluster in two separate axes of genetic covariance. Because creatinine is genetically correlated with urate but not with metabolic traits, this suggests there is one genetic module of shared loci associated with hyperuricemia and chronic kidney disease. Another module of shared loci may account for the association of hyperuricemia and metabolic syndrome. This study provides a clear quantitative genetic basis for the clustering of comorbidities with hyperuricemia.

Original language	English
Pages (from-to)	1438-1445
Number of pages	8
Journal	European Journal of Human Genetics
Volume	29
Issue number	9
DOIs	https://doi.org/10.1038/s41431-021-00830-z
State	Published - Sep 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to European Society of Human Genetics.

Funding

Acknowledgements RJR, SLB, TRM, JAS, and AIV acknowledge support from P50 AR060772. RJR acknowledges support from K01 AR060848 and the Arthritis National Research Foundation. AIV acknowledges financial support from NIH grant 7-R01-DK-062148-10-S1, R01GM09992, and R01GM101219. The Hypertension Genetic Epidemiology Network (HyperGEN) Study is part of the NHLBI Family Blood Pressure Program. Collection of the data represented here was supported by grants U01 HL054472, U01 HL054473, U01 HL054495, and U01 HL054509. The HyperGEN: Genetics of Left Ventricular Hypertrophy Study was supported by NHLBI grant R01 HL055673. We gratefully acknowledge scientists conducting the HyperGEN and Framingham Heart Study for collecting, analyzing, and providing the genotypic and phenotypic data used in the present study, as well as the invaluable dedication of the HyperGEN and Framingham Heart Study participants. The Framingham Heart Study is conducted and supported by the NHLBI in collaboration with Boston University (Contract No. N01-HC-25195 and HHSN268201500001I). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract N02-HL64278. SHARe Illumina genotyping was provided under an agreement between Illumina and Boston University. Funding for Affymetrix genotyping of the FHS Omni cohorts was provided by Intramural NHLBI funds from Andrew D. Johnson and Christopher J. O’Donnell.

Funders	Funder number
Andrew D. Johnson and Christopher J. O’Donnell
National Institutes of Health (NIH)	R01GM09992, 7-R01-DK-062148-10-S1, U01 HL054509, R01GM101219, U01 HL054472, U01 HL054473
National Institutes of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)	R01 HL055673, U01HL054495
National Heart, Lung, and Blood Institute (NHLBI)
Arthritis National Research Foundation
Boston University School of Public Health/Boston University Medical Campus	N01-HC-25195, HHSN268201500001I, N02-HL64278
Boston University School of Public Health/Boston University Medical Campus

ASJC Scopus subject areas

Genetics
Genetics(clinical)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

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abstract = "Hypertension, obesity, chronic kidney disease and type 2 diabetes are comorbidities that have very high prevalence among persons with hyperuricemia (serum urate > 6.8 mg/dL) and gout. Here we use multivariate genetic models to test the hypothesis that the co-association of traits representing hyperuricemia and its comorbidities is genetically based. Using Bayesian whole-genome regression models, we estimated the genetic marker-based variance and the covariance between serum urate, serum creatinine, systolic blood pressure (SBP), blood glucose and body mass index (BMI) from two independent family-based studies: The Framingham Heart Study-FHS and the Hypertension Genetic Epidemiology Network study-HyperGEN. The main genetic findings that replicated in both FHS and HyperGEN, were (1) creatinine was genetically correlated only with urate and (2) BMI was genetically correlated with urate, SBP, and glucose. The environmental covariance among the traits was generally highest for trait pairs involving BMI. The genetic overlap of traits representing the comorbidities of hyperuricemia and gout appears to cluster in two separate axes of genetic covariance. Because creatinine is genetically correlated with urate but not with metabolic traits, this suggests there is one genetic module of shared loci associated with hyperuricemia and chronic kidney disease. Another module of shared loci may account for the association of hyperuricemia and metabolic syndrome. This study provides a clear quantitative genetic basis for the clustering of comorbidities with hyperuricemia.",

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Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities

Abstract

Bibliographical note

Funding

ASJC Scopus subject areas

UN SDGs

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