Abstract
Mendelian randomization has been widely used to assess the causal effect of a heritable exposure variable on an outcome of interest, using genetic variants as instrumental variables. In practice, data on the exposure variable can be incomplete due to high cost of measurement and technical limits of detection. In this paper, we propose a valid and efficient method to handle both unmeasured and undetectable values of the exposure variable in one-sample Mendelian randomization analysis with individual-level data. We estimate the causal effect of the exposure variable on the outcome using maximum likelihood estimation and develop an expectation maximization algorithm for the computation of the estimator. Simulation studies show that the proposed method performs well in making inference on the causal effect. We apply our method to the Hispanic Community Health Study/Study of Latinos, a community-based prospective cohort study, and estimate the causal effect of several metabolites on phenotypes of interest.
| Original language | English (US) |
|---|---|
| Article number | 100245 |
| Journal | Human Genetics and Genomics Advances |
| Volume | 5 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 11 2024 |
Funding
The authors thank the staff and participants of Hispanic Community Health Study/Study of Latinos (HCHS/SOL) for their important contributions (Investigators’ website: https://sites.cscc.unc.edu/hchs/ ). The HCHS/SOL is a collaborative study supported by contracts from the NHLBI to the University of North Carolina ( HHSN268201300001I / N01-HC-65233 ), University of Miami ( HHSN268201300004I / N01-HC-65234 ), Albert Einstein College of Medicine ( HHSN268201300002I / N01-HC-65235 ), University of Illinois at Chicago ( HHSN268201300003I / N01-HC-65236 Northwestern University), and San Diego State University ( HHSN268201300005I / N01-HC-65237 ). The following institutes/centers/offices have contributed to the HCHS/SOL through a transfer of funds to the NHLBI : National Institute on Minority Health and Health Disparities , National Institute on Deafness and Other Communication Disorders , National Institute of Dental and Craniofacial Research (NIDCR), National Institute of Diabetes and Digestive and Kidney Diseases , National Institute of Neurological Disorders and Stroke , and National Institutes of Health Office of Dietary Supplements . The Genetic Analysis Center at the University of Washington was supported by NHLBI and NIDCR contracts ( HHSN268201300005C AM03 and MOD03 ). Support for HCHS/SOL metabolomics data was graciously provided by the JLH Foundation (Houston, Texas). The authors are grateful to the support from the National Heart, Lung, and Blood Institute (NHLBI) under R01HL143885 to develop this methodology. The authors are also grateful to funding from the National Institute on Aging under P30AG066615 and the Population Architecture using Genomics and Epidemiology Study under R01HG010297 . The authors are grateful to the support from the National Heart, Lung, and Blood Institute (NHLBI) under R01HL143885 to develop this methodology. The authors are also grateful to funding from the National Institute on Aging under P30AG066615 and the Population Architecture using Genomics and Epidemiology Study under R01HG010297. The authors thank the staff and participants of Hispanic Community Health Study/Study of Latinos (HCHS/SOL) for their important contributions (Investigators’ website: https://sites.cscc.unc.edu/hchs/). The HCHS/SOL is a collaborative study supported by contracts from the NHLBI to the University of North Carolina (HHSN268201300001I/N01-HC-65233), University of Miami (HHSN268201300004I/N01-HC-65234), Albert Einstein College of Medicine (HHSN268201300002I/N01-HC-65235), University of Illinois at Chicago (HHSN268201300003I/N01-HC-65236 Northwestern University), and San Diego State University (HHSN268201300005I/N01-HC-65237). The following institutes/centers/offices have contributed to the HCHS/SOL through a transfer of funds to the NHLBI: National Institute on Minority Health and Health Disparities, National Institute on Deafness and Other Communication Disorders, National Institute of Dental and Craniofacial Research (NIDCR), National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, and National Institutes of Health Office of Dietary Supplements. The Genetic Analysis Center at the University of Washington was supported by NHLBI and NIDCR contracts (HHSN268201300005C AM03 and MOD03). Support for HCHS/SOL metabolomics data was graciously provided by the JLH Foundation (Houston, Texas). The authors also thank the Trans-Omics in Precision Medicine (TOPMed) program imputation panel (version TOPMed-r2), which is supported by the NHLBI; see www.nhlbiwgs.org. TOPMed study investigators contributed data to the reference panel, which can be accessed through the Michigan Imputation Server; see https://imputationserver.sph.umich.edu. The panel was constructed and implemented by the TOPMed Informatics Research Center at the University of Michigan (3R01HL-117626-02S1; contract HHSN268201800002I). The TOPMed Data Coordinating Center (3R01HL-120393-02S1; contract HHSN268201800001I) provided additional data management, sample identity checks, and overall program coordination and support. We gratefully acknowledge the participants who provided biological samples and the studies that provided data for TOPMed. The authors declare no competing interests.
Keywords
- causal inference
- detection limits
- instrumental variables
- metabolomics
- missing data
- unmeasured confounding
ASJC Scopus subject areas
- Molecular Medicine
- Genetics(clinical)