Classifying Individuals Into a Dietary Pattern Based on Metabolomic Data.

Mol Nutr Food Res

UCD School of Agriculture and Food Science, UCD Institute of Food and Health, University College Dublin, Belfield, Dublin 4, Ireland.

Published: June 2021

Scope: The objectives are to develop a metabolomic-based model capable of classifying individuals into dietary patterns and to investigate the reproducibility of the model.

Methods And Results: K-means cluster analysis is employed to derive dietary patterns using metabolomic data. Differences across the dietary patterns are examined using nutrient biomarkers. The model is used to assign individuals to a dietary pattern in an independent cohort, A-DIET Confirm (n = 175) at four time points. The stability of participants to a dietary pattern is assessed. Four dietary patterns are derived: moderately unhealthy, convenience, moderately healthy, and prudent. The moderately unhealthy and convenience patterns has lower adherence to the alternative healthy eating index (AHEI) and the alternative mediterranean diet score (AMDS) compared to the moderately healthy and prudent patterns (AHEI = 24.5 and 22.9 vs 26.7 and 28.4, p < 0.001). The dietary patterns are replicated in A-DIET Confirm, with good reproducibility across four time points. The stability of participants' dietary pattern membership ranged from 25.0% to 61.5%.

Conclusion: The multivariate model classifies individuals into dietary patterns based on metabolomic data. In an independent cohort, the model classifies individuals into dietary patterns at multiple time points furthering the potential of such an approach for nutrition research.

Download full-text PDF

Source
http://dx.doi.org/10.1002/mnfr.202001183DOI Listing

Publication Analysis

Top Keywords

dietary patterns
16
individuals dietary
12
dietary pattern
12
classifying individuals
8
metabolomic data
8
moderately unhealthy
8
unhealthy convenience
8
moderately healthy
8
healthy prudent
8
dietary
7

Similar Publications

Background: Precision nutrition-based methods develop tailored interventions and/or recommendations accounting for determinants of intra- and inter-individual variation in response to the same diet, compared to current 'one-size-fits-all' population-level approaches. Determinants may include genetics, current dietary habits and eating patterns, circadian rhythms, health status, gut microbiome, socioeconomic and psychosocial characteristics, and physical activity. ​​​​In this systematic review, we examined the evidence base for the effect of interventions based on precision nutrition approaches on overweight and obesity in children and adolescents to help inform future research and global guidelines.

View Article and Find Full Text PDF

Feeding disruptions lead to a significant increase in disease modules in adult mice.

Heliyon

January 2025

CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.

Feeding disruption is closely linked to numerous diseases, yet the underlying molecular mechanisms remain an important but unresolved issue at the molecular level. We hypothesize that, at the network level, dietary disruptions can alter gene co-expression patterns, leading to an increase in disease-associated modules, and thereby elevating the likelihood of disease occurrence. Here, we investigate this hypothesis using transcriptomic data from a large cohort of adult mice subjected to feeding disruptions.

View Article and Find Full Text PDF

Introduction: The coverage of vitamin A supplementation (VAS) is still short of the target set by the government to reach 90% coverage of VAS in Bangladesh. The present study aims to examine the socioeconomic and geographical inequalities in receiving VAS among children aged 6-59 months in Bangladesh from 2004 to 2017.

Methods: The Bangladesh Demographic and Health Surveys for the years 2004-2017 were accessed through the WHO's Health Equity Assessment Toolkit.

View Article and Find Full Text PDF

Due to the challenges of conducting randomised controlled trials (randomised trials) of dietary interventions, evidence in nutrition often comes from non-randomised (observational) studies of nutritional exposures-called nutritional epidemiology studies. When using systematic reviews of such studies to advise patients or populations on optimal dietary habits, users of the evidence (eg, healthcare professionals such as clinicians, health service and policy workers) should first evaluate the rigour (validity) and utility (applicability) of the systematic review. Issues in making this judgement include whether the review addressed a sensible question; included an exhaustive literature search; was scrupulous in the selection of studies and the collection of data; and presented results in a useful manner.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!