Causal associations between risk factors and common diseases inferred from GWAS summary data

Zhu, Zhihong, Zheng, Zhili, Zhang, Futao, Wu, Yang, Trzaskowski, Maciej, Maier, Robert, Robinson, Matthew R., McGrath, John J, Visscher, Peter M, Wray, Naomi R and Yang, Jian (2018) Causal associations between risk factors and common diseases inferred from GWAS summary data. Nature Communications, 9 1: . doi:10.1038/s41467-017-02317-2


Author Zhu, Zhihong
Zheng, Zhili
Zhang, Futao
Wu, Yang
Trzaskowski, Maciej
Maier, Robert
Robinson, Matthew R.
McGrath, John J
Visscher, Peter M
Wray, Naomi R
Yang, Jian
Title Causal associations between risk factors and common diseases inferred from GWAS summary data
Journal name Nature Communications   Check publisher's open access policy
ISSN 2041-1723
Publication date 2018-01-15
Year available 2018
Sub-type Article (original research)
DOI 10.1038/s41467-017-02317-2
Open Access Status DOI
Volume 9
Issue 1
Total pages 12
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Language eng
Subject 1600 Chemistry
1300 Biochemistry, Genetics and Molecular Biology
3100 Physics and Astronomy
Abstract Health risk factors such as body mass index (BMI) and serum cholesterol are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. We develop and apply a method (called GSMR) that performs a multi-SNP Mendelian randomization analysis using summary-level data from genome-wide association studies to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height, and years of schooling (EduYears) with common diseases (sample sizes of up to 405,072). We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimer's disease, and bidirectional associations with opposite effects (e.g., higher BMI increases the risk of T2D but the effect of T2D on BMI is negative).
Keyword Genome-wide association
Body mass index
Multiple genetic variants
Type-2 diabetes mellitus
Coronary artery disease
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID DP160101343
Institutional Status UQ
Additional Notes Article number 224

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Brain Institute Publications
Institute for Molecular Bioscience - Publications
 
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Created: Wed, 24 Jan 2018, 12:22:20 EST