Demographic, health and lifestyle factors associated with the metabolome in older women

S. L. Navarro; G. A. Nagana Gowda; L. F. Bettcher; R. Pepin; N. Nguyen; M. Ellenberger; C. Zheng; L. F. Tinker; R. L. Prentice; Y. Huang; T. Yang; F. K. Tabung; Q. Chan; Ruey Leng Loo; S. Liu; J. Wactawski-Wende; J. W. Lampe; M. L. Neuhouser; D. Raftery

doi:10.3390/metabo13040514

Back

Demographic, health and lifestyle factors associated with the metabolome in older women

Journal article

Open access

Peer reviewed

Demographic, health and lifestyle factors associated with the metabolome in older women

S. L. Navarro, G. A. Nagana Gowda, L. F. Bettcher, R. Pepin, N. Nguyen, M. Ellenberger, C. Zheng, L. F. Tinker, R. L. Prentice, Y. Huang, …

Metabolites, Vol.13(4), Art. 514

2023

DOI: https://doi.org/10.3390/metabo13040514

Files and links (1)

pdf

Published316.41 kBDownload View

CC BY V4.0, Open Access

Abstract

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women’s Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2–0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

Details

Title: Demographic, health and lifestyle factors associated with the metabolome in older women
Authors/Creators: S. L. Navarro
G. A. Nagana Gowda
L. F. Bettcher
R. Pepin
N. Nguyen
M. Ellenberger
C. Zheng
L. F. Tinker
R. L. Prentice
Y. Huang
T. Yang
F. K. Tabung
Q. Chan
Ruey Leng Loo - Murdoch University, Centre for Computational and Systems Medicine
S. Liu
J. Wactawski-Wende
J. W. Lampe
M. L. Neuhouser
D. Raftery
Publication Details: Metabolites, Vol.13(4), Art. 514
Publisher: MDPI
Identifiers: 991005567369307891
Copyright: © 2023 by the authors.
Murdoch Affiliation: Australian National Phenome Centre; Centre for Computational and Systems Medicine
Resource Type: Journal article

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Metrics

157 File views/ downloads

69 Record Views

10 Times Cited - Web of Science

See more details

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Domestic collaboration; International collaboration
Citation topics: 2 Chemistry; 2.211 Mass Spectrometry; 2.211.990 Metabolomics
Web Of Science research areas: Biochemistry & Molecular Biology
ESI research areas: Biology & Biochemistry