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.; Yang, Jian

doi:10.1038/s41467-017-02317-2

Cited by 960Genetic Associations and EpidemiologyGenetics and Physical PerformanceGenetic and phenotypic traits in livestock

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

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Zhu, Zhihong, Zheng, Zhili, Zhang, Futao, Wu, Yang, Trzaskowski, Maciej, Maier, Robert, Robinson, Matthew R., McGrath, John J. +3 more·2018·Nature Communications

DOI 10.1038/s41467-017-02317-2PMC PMC5768719

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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).

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GSMR can help differentiate the likely causal direction of association between two traits but cannot make any statement about the intermediate mechanisms involved in any potential causal process.
“This method can help differentiate the likely causal direction of association between two traits but cannot make any statement about the intermediate mechanisms involved in any potential causal process.”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [29]
The Methods section describes GSMR as testing whether an exposure causally affects an outcome, and the Results section uses forward and reverse GSMR analyses to assess direction. The Results also say it is difficult to distinguish whether an effect is mediated by other risk factors or driven by them. But the paper does examine associations among risk factors and conditional effects, so the categorical claim that GSMR cannot make any statement about intermediate mechanisms overstates its stated limitation. Page numbers are unavailable in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measured
The estimated GSMR causal effect coefficients (bxy) are approximately equal to the natural log odds ratio for a case-control trait.
“The estimated causal effect coefficients (b xy ) are approximately equal to the natural log odds ratio (OR) for a case-control trait 29 .”
From Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence (2018) · cites this paper as [29]

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Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways
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Single-cell RNA-seq reveals cell type–specific molecular and genetic associations to lupus
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Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions
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Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome
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Constrained maximum likelihood-based Mendelian randomization robust to both correlated and uncorrelated pleiotropic effects
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A single-cell atlas of the human substantia nigra reveals cell-specific pathways associated with neurological disorders
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Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
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Catalytic Mechanism of Oxygen Vacancies in Perovskite Oxides for Lithium–Sulfur Batteries
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GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression
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Is atypical rhythm a risk factor for developmental speech and language disorders?
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The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls
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Shared genetics of asthma and mental health disorders: a large-scale genome-wide cross-trait analysis
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Blood pressure lowering and risk of new-onset type 2 diabetes: an individual participant data meta-analysis
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Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank
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Causal Associations of Obesity With the Intervertebral Degeneration, Low Back Pain, and Sciatica: A Two-Sample Mendelian Randomization Study
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Authors: Zhu, Z., Zheng, Z., Zhang, F., Wu, Y., Trzaskowski, M., Maier, R., Robinson, M. R., McGrath, J. J., Visscher, P. M., Wray, N. R., & Yang, J.
Affiliations: The University of Queensland (AU)
Corresponding author: Yang, Jian
ORCID: 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
Venue: Nature Communications
Publisher: Springer Science and Business Media LLC
Published: 2018-01-15
Volume: 9
Issue: 1
Pages: 224-224
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1038/s41467-017-02317-2
PMC: PMC5768719
OpenAlex: W2949543964
Cited by: 951
References: 69
Citations by year: 2026: 92 · 2025: 136 · 2024: 134 · 2023: 129 · 2022: 115 · 2021: 122 · 2020: 102 · 2019: 81 · 2018: 35 · 2017: 1 · 2016: 1 · 2015: 1
FWCI: 51.44
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Nature Communications (publishedVersion, cc-by)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
SERVAL (Université de Lausanne) (publishedVersion, cc-by)
IRIS (submittedVersion, cc-by)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
IRIS (submittedVersion)
SERVAL (Université de Lausanne) (submittedVersion)
Funders: National Research Foundation
Danmarks Grundforskningsfond
Lundbeckfonden (R155-2014-1724, R248‐2017‐2003)
Medical Research Council (1107258, 1113400, 1078037, 1078901)
Australian Research Council (DP160101343, 1113400)
National Health and Medical Research Council (1113400, 1078901, 1056929, 1107258, 1078037, 1048853)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords: causal inference, Mendelian randomization, body mass index, waist-to-hip ratio, serum cholesterol, LDL cholesterol, type 2 diabetes, Alzheimer's disease, years of schooling, blood pressure, height, confounding, statin adverse effects
MeSH terms: Alzheimer Disease, Cholesterol, Diabetes Mellitus, Type 2, Disease, Humans, Cholesterol, LDL, Risk Factors, Body Mass Index, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Mendelian Randomization Analysis

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