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MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank.
Ann Rheum Dis. 2018 07; 77(7):1039-1047.AR

Abstract

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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Authors+Show Affiliations

Li X
Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Meng X
Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Spiliopoulou A
Centre for Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Timofeeva M
Colon Cancer Genetics Group, Medical Research Council Human Genetics Unit, Medical Research Council, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
Wei WQ
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Gifford A
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Shen X
Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
He Y
Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK. West China School of Medicine, West China Hospital, Sichuan University, Sichuan, China.
Varley T
Public Health and Intelligence, NHS National Services Scotland, Edinburgh, UK.
McKeigue P
Centre for Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Tzoulaki I
Department Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. MRC-PHE Centre for Environment, School of Public Health, Imperial College London, London, UK. Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.
Wright AF
Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
Joshi P
Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Denny JC
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Campbell H
Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Theodoratou E
Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK. Edinburgh Cancer Research Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.

MeSH

AdultArthritisAutoimmune DiseasesBiological Specimen BanksCeliac DiseaseFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyGoutHumansHypertensionMaleMendelian Randomization AnalysisMiddle AgedMultimorbidityMyocardial InfarctionPrognosisRisk AssessmentUnited KingdomUric Acid

Pub Type(s)

Comparative Study
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

29437585

Citation

Li, Xue, et al. "MR-PheWAS: Exploring the Causal Effect of SUA Level On Multiple Disease Outcomes By Using Genetic Instruments in UK Biobank." Annals of the Rheumatic Diseases, vol. 77, no. 7, 2018, pp. 1039-1047.
Li X, Meng X, Spiliopoulou A, et al. MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank. Ann Rheum Dis. 2018;77(7):1039-1047.
Li, X., Meng, X., Spiliopoulou, A., Timofeeva, M., Wei, W. Q., Gifford, A., Shen, X., He, Y., Varley, T., McKeigue, P., Tzoulaki, I., Wright, A. F., Joshi, P., Denny, J. C., Campbell, H., & Theodoratou, E. (2018). MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank. Annals of the Rheumatic Diseases, 77(7), 1039-1047. https://doi.org/10.1136/annrheumdis-2017-212534
Li X, et al. MR-PheWAS: Exploring the Causal Effect of SUA Level On Multiple Disease Outcomes By Using Genetic Instruments in UK Biobank. Ann Rheum Dis. 2018;77(7):1039-1047. PubMed PMID: 29437585.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank. AU - Li,Xue, AU - Meng,Xiangrui, AU - Spiliopoulou,Athina, AU - Timofeeva,Maria, AU - Wei,Wei-Qi, AU - Gifford,Aliya, AU - Shen,Xia, AU - He,Yazhou, AU - Varley,Tim, AU - McKeigue,Paul, AU - Tzoulaki,Ioanna, AU - Wright,Alan F, AU - Joshi,Peter, AU - Denny,Joshua C, AU - Campbell,Harry, AU - Theodoratou,Evropi, Y1 - 2018/02/06/ PY - 2017/10/13/received PY - 2018/01/12/revised PY - 2018/01/21/accepted PY - 2018/2/14/pubmed PY - 2019/8/7/medline PY - 2018/2/14/entrez KW - epidemiology KW - gene polymorphism KW - gout SP - 1039 EP - 1047 JF - Annals of the rheumatic diseases JO - Ann Rheum Dis VL - 77 IS - 7 N2 - 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. SN - 1468-2060 UR - https://www.unboundmedicine.com/medline/citation/29437585/MR_PheWAS:_exploring_the_causal_effect_of_SUA_level_on_multiple_disease_outcomes_by_using_genetic_instruments_in_UK_Biobank_ DB - PRIME DP - Unbound Medicine ER -