Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities
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 hyp...
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| Veröffentlicht in: | European journal of human genetics : EJHG 2021-09, Vol.29 (9), p.1438-1445 |
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| creator | Reynolds, Richard J Irvin, M Ryan Bridges, S Louis Kim, Hwasoon Merriman, Tony R Arnett, Donna K Singh, Jasvinder A Sumpter, Nicholas A Lupi, Alexa S Vazquez, Ana I |
| description | 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. |
| doi_str_mv | 10.1038/s41431-021-00830-z |
| format | Article |
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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.</description><identifier>ISSN: 1018-4813</identifier><identifier>EISSN: 1476-5438</identifier><identifier>DOI: 10.1038/s41431-021-00830-z</identifier><identifier>PMID: 33637890</identifier><language>eng</language><publisher>England: Nature Publishing Group</publisher><subject>Bayes Theorem ; Bayesian analysis ; Blood Pressure ; Body mass index ; Cardiometabolic Risk Factors ; Comorbidity ; Creatinine ; Creatinine - blood ; Diabetes mellitus (non-insulin dependent) ; Epidemiology ; Genetic markers ; Genome-Wide Association Study ; Genomes ; Gout ; Gout - epidemiology ; Gout - genetics ; Humans ; Hypertension ; Hyperuricemia ; Hyperuricemia - epidemiology ; Hyperuricemia - genetics ; Kidney diseases ; Mathematical models ; Metabolic syndrome ; Metabolism ; Quantitative genetics ; Quantitative Trait Loci ; Regression analysis ; Uric acid ; Uric Acid - blood</subject><ispartof>European journal of human genetics : EJHG, 2021-09, Vol.29 (9), p.1438-1445</ispartof><rights>2021. The Author(s), under exclusive licence to European Society of Human Genetics.</rights><rights>The Author(s), under exclusive licence to European Society of Human Genetics 2021.</rights><rights>The Author(s), under exclusive licence to European Society of Human Genetics 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c430t-cc039bc9ae5c2985d74a515fe20ea9355c91fc5460aaf3bb19b123dc60c6ec73</citedby><cites>FETCH-LOGICAL-c430t-cc039bc9ae5c2985d74a515fe20ea9355c91fc5460aaf3bb19b123dc60c6ec73</cites><orcidid>0000-0001-6618-7486 ; 0000-0001-6419-7779 ; 0000-0003-0844-8726 ; 0000-0002-0561-3186 ; 0000-0003-2219-657X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440599/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440599/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27915,27916,53782,53784</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33637890$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Reynolds, Richard J</creatorcontrib><creatorcontrib>Irvin, M Ryan</creatorcontrib><creatorcontrib>Bridges, S Louis</creatorcontrib><creatorcontrib>Kim, Hwasoon</creatorcontrib><creatorcontrib>Merriman, Tony R</creatorcontrib><creatorcontrib>Arnett, Donna K</creatorcontrib><creatorcontrib>Singh, Jasvinder A</creatorcontrib><creatorcontrib>Sumpter, Nicholas A</creatorcontrib><creatorcontrib>Lupi, Alexa S</creatorcontrib><creatorcontrib>Vazquez, Ana I</creatorcontrib><title>Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities</title><title>European journal of human genetics : EJHG</title><addtitle>Eur J Hum Genet</addtitle><description>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.</description><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Blood Pressure</subject><subject>Body mass index</subject><subject>Cardiometabolic Risk Factors</subject><subject>Comorbidity</subject><subject>Creatinine</subject><subject>Creatinine - blood</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Epidemiology</subject><subject>Genetic markers</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Gout</subject><subject>Gout - epidemiology</subject><subject>Gout - genetics</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Hyperuricemia</subject><subject>Hyperuricemia - epidemiology</subject><subject>Hyperuricemia - genetics</subject><subject>Kidney diseases</subject><subject>Mathematical models</subject><subject>Metabolic syndrome</subject><subject>Metabolism</subject><subject>Quantitative genetics</subject><subject>Quantitative Trait Loci</subject><subject>Regression analysis</subject><subject>Uric acid</subject><subject>Uric Acid - 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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.</abstract><cop>England</cop><pub>Nature Publishing Group</pub><pmid>33637890</pmid><doi>10.1038/s41431-021-00830-z</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-6618-7486</orcidid><orcidid>https://orcid.org/0000-0001-6419-7779</orcidid><orcidid>https://orcid.org/0000-0003-0844-8726</orcidid><orcidid>https://orcid.org/0000-0002-0561-3186</orcidid><orcidid>https://orcid.org/0000-0003-2219-657X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Bayes Theorem Bayesian analysis Blood Pressure Body mass index Cardiometabolic Risk Factors Comorbidity Creatinine Creatinine - blood Diabetes mellitus (non-insulin dependent) Epidemiology Genetic markers Genome-Wide Association Study Genomes Gout Gout - epidemiology Gout - genetics Humans Hypertension Hyperuricemia Hyperuricemia - epidemiology Hyperuricemia - genetics Kidney diseases Mathematical models Metabolic syndrome Metabolism Quantitative genetics Quantitative Trait Loci Regression analysis Uric acid Uric Acid - blood |
| title | Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities |
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