The association between body mass index and metabolite response to a liquid mixed meal challenge: a Mendelian randomization study.

causal inference instrumental variable analysis lipidomics metabolomics obesity

Journal

The American journal of clinical nutrition
ISSN: 1938-3207
Titre abrégé: Am J Clin Nutr
Pays: United States
ID NLM: 0376027

Informations de publication

Date de publication:
15 Mar 2024
Historique:
received: 09 10 2023
revised: 30 01 2024
accepted: 12 03 2024
medline: 18 3 2024
pubmed: 18 3 2024
entrez: 17 3 2024
Statut: aheadofprint

Résumé

Metabolite abundance is a dynamic trait that varies in response to environmental stimuli and phenotypic traits, such as food consumption and body mass index (BMI). Here we use the Netherlands Epidemiology of Obesity (NEO) study to identify observational and causal associations between BMI and metabolite response to a liquid meal. A liquid meal challenge was performed and Nightingale Health metabolite profiles were collected in 5744 NEO participants. Observational and one-sample MR analysis were conducted to estimate the effect of BMI on metabolites (n = 229) in the fasting, postprandial and response (or change in abundance) states. We observed 473 associations with BMI (175 fasting, 188 postprandial, 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, 3 response) to be associated with BMI. MR associations included the glucogenic amino acid alanine which was inversely associated with BMI in the response state (beta = -0.081, se = 0.023, P = 5.91x10 Overall, MR estimates were strongly correlated with observational effect estimates suggesting that the broad associations seen between BMI and metabolite variation has a causal underpinning. Specific effects in previously unassessed postprandial and response states were detected and these may likely mark novel life course risk exposures driven by regular nutrition.

Sections du résumé

BACKGROUND BACKGROUND
Metabolite abundance is a dynamic trait that varies in response to environmental stimuli and phenotypic traits, such as food consumption and body mass index (BMI).
OBJECTIVES OBJECTIVE
Here we use the Netherlands Epidemiology of Obesity (NEO) study to identify observational and causal associations between BMI and metabolite response to a liquid meal.
METHODS METHODS
A liquid meal challenge was performed and Nightingale Health metabolite profiles were collected in 5744 NEO participants. Observational and one-sample MR analysis were conducted to estimate the effect of BMI on metabolites (n = 229) in the fasting, postprandial and response (or change in abundance) states.
RESULTS RESULTS
We observed 473 associations with BMI (175 fasting, 188 postprandial, 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, 3 response) to be associated with BMI. MR associations included the glucogenic amino acid alanine which was inversely associated with BMI in the response state (beta = -0.081, se = 0.023, P = 5.91x10
CONCLUSIONS CONCLUSIONS
Overall, MR estimates were strongly correlated with observational effect estimates suggesting that the broad associations seen between BMI and metabolite variation has a causal underpinning. Specific effects in previously unassessed postprandial and response states were detected and these may likely mark novel life course risk exposures driven by regular nutrition.

Identifiants

pubmed: 38494119
pii: S0002-9165(24)00344-7
doi: 10.1016/j.ajcnut.2024.03.009
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Auteurs

David A Hughes (DA)

MRC Integrative Epidemiology Unit at the University of Bristol, UK; Population Health Science, Bristol Medical School, University of Bristol, UK. Electronic address: david.hughes@pbrc.edu.

Ruifang Li-Gao (R)

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

Caroline J Bull (CJ)

MRC Integrative Epidemiology Unit at the University of Bristol, UK; Population Health Science, Bristol Medical School, University of Bristol, UK.

Renée de Mutsert (R)

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

Frits R Rosendaal (FR)

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

Dennis O Mook-Kanamori (DO)

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands.

Ko Willems van Dijk (K)

Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands; Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands.

Nicholas J Timpson (NJ)

MRC Integrative Epidemiology Unit at the University of Bristol, UK; Population Health Science, Bristol Medical School, University of Bristol, UK.

Classifications MeSH