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MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank

OBJECTIVES: We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank. METHODS: We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci....

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Autores principales: Li, Xue, Meng, Xiangrui, Spiliopoulou, Athina, Timofeeva, Maria, Wei, Wei-Qi, Gifford, Aliya, Shen, Xia, He, Yazhou, Varley, Tim, McKeigue, Paul, Tzoulaki, Ioanna, Wright, Alan F, Joshi, Peter, Denny, Joshua C, Campbell, Harry, Theodoratou, Evropi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029646/
https://www.ncbi.nlm.nih.gov/pubmed/29437585
http://dx.doi.org/10.1136/annrheumdis-2017-212534
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author Li, Xue
Meng, Xiangrui
Spiliopoulou, Athina
Timofeeva, Maria
Wei, Wei-Qi
Gifford, Aliya
Shen, Xia
He, Yazhou
Varley, Tim
McKeigue, Paul
Tzoulaki, Ioanna
Wright, Alan F
Joshi, Peter
Denny, Joshua C
Campbell, Harry
Theodoratou, Evropi
author_facet Li, Xue
Meng, Xiangrui
Spiliopoulou, Athina
Timofeeva, Maria
Wei, Wei-Qi
Gifford, Aliya
Shen, Xia
He, Yazhou
Varley, Tim
McKeigue, Paul
Tzoulaki, Ioanna
Wright, Alan F
Joshi, Peter
Denny, Joshua C
Campbell, Harry
Theodoratou, Evropi
author_sort Li, Xue
collection PubMed
description OBJECTIVES: We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank. METHODS: We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci. We then implemented conventional Mendelianrandomisation (MR) analysis to investigate the causal relevance between SUA level and disease outcomes identified from PheWAS. We next applied MR Egger analysis to detect and account for potential pleiotropy, which conventional MR analysis might mistake for causality, and used the HEIDI (heterogeneity in dependent instruments) test to remove cross-phenotype associations that were likely due to genetic linkage. RESULTS: Our PheWAS identified 25 disease groups/outcomes associated with SUA genetic risk loci after multiple testing correction (P<8.57e-05). Our conventional MR analysis implicated a causal role of SUA level in three disease groups: inflammatory polyarthropathies (OR=1.22, 95% CI 1.11 to 1.34), hypertensive disease (OR=1.08, 95% CI 1.03 to 1.14) and disorders of metabolism (OR=1.07, 95% CI 1.01 to 1.14); and four disease outcomes: gout (OR=4.88, 95% CI 3.91 to 6.09), essential hypertension (OR=1.08, 95% CI 1.03 to 1.14), myocardial infarction (OR=1.16, 95% CI 1.03 to 1.30) and coeliac disease (OR=1.41, 95% CI 1.05 to 1.89). After balancing pleiotropic effects in MR Egger analysis, only gout and its encompassing disease group of inflammatory polyarthropathies were considered to be causally associated with SUA level. Our analysis highlighted a locus (ATXN2/S2HB3) that may influence SUA level and multiple cardiovascular and autoimmune diseases via pleiotropy. CONCLUSIONS: Elevated SUA level is convincing to cause gout and inflammatory polyarthropathies, and might act as a marker for the wider range of diseases with which it associates. Our findings support further investigation on the clinical relevance of SUA level with cardiovascular, metabolic, autoimmune and respiratory diseases.
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spelling pubmed-60296462018-07-06 MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank Li, Xue Meng, Xiangrui Spiliopoulou, Athina Timofeeva, Maria Wei, Wei-Qi Gifford, Aliya Shen, Xia He, Yazhou Varley, Tim McKeigue, Paul Tzoulaki, Ioanna Wright, Alan F Joshi, Peter Denny, Joshua C Campbell, Harry Theodoratou, Evropi Ann Rheum Dis Clinical and Epidemiological Research OBJECTIVES: We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank. METHODS: We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci. We then implemented conventional Mendelianrandomisation (MR) analysis to investigate the causal relevance between SUA level and disease outcomes identified from PheWAS. We next applied MR Egger analysis to detect and account for potential pleiotropy, which conventional MR analysis might mistake for causality, and used the HEIDI (heterogeneity in dependent instruments) test to remove cross-phenotype associations that were likely due to genetic linkage. RESULTS: Our PheWAS identified 25 disease groups/outcomes associated with SUA genetic risk loci after multiple testing correction (P<8.57e-05). Our conventional MR analysis implicated a causal role of SUA level in three disease groups: inflammatory polyarthropathies (OR=1.22, 95% CI 1.11 to 1.34), hypertensive disease (OR=1.08, 95% CI 1.03 to 1.14) and disorders of metabolism (OR=1.07, 95% CI 1.01 to 1.14); and four disease outcomes: gout (OR=4.88, 95% CI 3.91 to 6.09), essential hypertension (OR=1.08, 95% CI 1.03 to 1.14), myocardial infarction (OR=1.16, 95% CI 1.03 to 1.30) and coeliac disease (OR=1.41, 95% CI 1.05 to 1.89). After balancing pleiotropic effects in MR Egger analysis, only gout and its encompassing disease group of inflammatory polyarthropathies were considered to be causally associated with SUA level. Our analysis highlighted a locus (ATXN2/S2HB3) that may influence SUA level and multiple cardiovascular and autoimmune diseases via pleiotropy. CONCLUSIONS: Elevated SUA level is convincing to cause gout and inflammatory polyarthropathies, and might act as a marker for the wider range of diseases with which it associates. Our findings support further investigation on the clinical relevance of SUA level with cardiovascular, metabolic, autoimmune and respiratory diseases. BMJ Publishing Group 2018-07 2018-02-06 /pmc/articles/PMC6029646/ /pubmed/29437585 http://dx.doi.org/10.1136/annrheumdis-2017-212534 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Clinical and Epidemiological Research
Li, Xue
Meng, Xiangrui
Spiliopoulou, Athina
Timofeeva, Maria
Wei, Wei-Qi
Gifford, Aliya
Shen, Xia
He, Yazhou
Varley, Tim
McKeigue, Paul
Tzoulaki, Ioanna
Wright, Alan F
Joshi, Peter
Denny, Joshua C
Campbell, Harry
Theodoratou, Evropi
MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank
title MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank
title_full MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank
title_fullStr MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank
title_full_unstemmed MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank
title_short MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank
title_sort mr-phewas: exploring the causal effect of sua level on multiple disease outcomes by using genetic instruments in uk biobank
topic Clinical and Epidemiological Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029646/
https://www.ncbi.nlm.nih.gov/pubmed/29437585
http://dx.doi.org/10.1136/annrheumdis-2017-212534
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