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J Proteome Res. 2017 Oct 6;16(10):3623-3633. doi: 10.1021/acs.jproteome.7b00344. Epub 2017 Sep 8.

Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling.

Author information

1
Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K.
2
Farr Institute of Health Informatics Research, University College London Institute of Health Informatics , 222 Euston Road, NW1 2DA London, United Kingdom.
3
Department of Hygiene and Epidemiology, University of Ioannina Medical School , Ioannina 45110, Greece.
4
Department of Pathology and Laboratory Medicine, University of Vermont Larner College of Medicine , Burlington, Vermont 05405, United States.
5
Department of Preventive Medicine and the Institute for Public Health and Medicine, Northwestern University , Chicago, Illinois 60611, United States.
6
Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London , Sir Alexander Fleming Building, South Kensington, SW7 2AZ London, United Kingdom.
7
Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine , Medical Center Boulevard, Winston-Salem, North Carolina 27157, United States.

Abstract

1H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.

KEYWORDS:

MESA; cohort studies; full resolution 1H NMR; high-throughput analysis; metabolic profiling; metabolome wide association study; molecular epidemiology; multiple testing correction; results visualization and prioritization; significance level

PMID:
28823158
PMCID:
PMC5633829
DOI:
10.1021/acs.jproteome.7b00344
[Indexed for MEDLINE]
Free PMC Article

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