Longitudinal Analysis of Placental IRS1 DNA Methylation and Childhood Obesity

Accumulating evidence suggests that the predisposition to metabolic diseases is established in utero through epigenomic modifications. However, it remains unclear whether childhood obesity results from preexisting epigenomic alterations or whether obesity itself induces changes in the epigenome. This study aimed to identify DNA methylation marks in the placenta associated with obesity-related outcomes in children at age 6 and to assess these marks in blood samples at age 6 and whether they correlate with obesity-related outcomes at that time. Using an epigenome-wide DNA methylation microarray on 24 placental samples, we identified differentially methylated CpGs (DMCs) associated with offspring BMI-SDS at 6 years. Individual DMCs were validated in 147 additional placental and leukocyte samples from children at 6 years of age. The methylation and/or gene expression of <i>IRS1</i> in both placenta and offspring leukocytes were significantly associated with various metabolic risk parameters at age 6 (all <i>p</i> ≤ 0.05). Logistic regression models (LRM) and machine learning (ML) models indicated that <i>IRS1</i> methylation in the placenta could strongly predict offspring obesity. Our results suggest that <i>IRS1</i> may serve as a potential biomarker for the prediction of obesity and metabolic risk in children.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-03-28
DOI
https://doi.org/10.3390/ijms26073141
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Longitudinal Analysis of Placental IRS1 DNA Methylation and Childhood Obesity

Abel López‐Bermejo, José‐María Martínez‐Calcerrada, Ariadna Gómez‐Vilarrubla, Berta Mas‐Parés et al.
International Journal of Molecular Sciences
Epigenetics and DNA Methylation
article

Longitudinal Analysis of Placental IRS1 DNA Methylation and Childhood Obesity

Abel López‐Bermejo, José‐María Martínez‐Calcerrada, Ariadna Gómez‐Vilarrubla, Berta Mas‐Parés, Beatriz López, Judit Bassols, Francis de Zegher, Alexandra Bonmatí‐Santané, Lourdes Ibáñez, Maria Niubó-Pallàs, Aaron Peñas-Cruz
article en

Abstract

Accumulating evidence suggests that the predisposition to metabolic diseases is established in utero through epigenomic modifications. However, it remains unclear whether childhood obesity results from preexisting epigenomic alterations or whether obesity itself induces changes in the epigenome. This study aimed to identify DNA methylation marks in the placenta associated with obesity-related outcomes in children at age 6 and to assess these marks in blood samples at age 6 and whether they correlate with obesity-related outcomes at that time. Using an epigenome-wide DNA methylation microarray on 24 placental samples, we identified differentially methylated CpGs (DMCs) associated with offspring BMI-SDS at 6 years. Individual DMCs were validated in 147 additional placental and leukocyte samples from children at 6 years of age. The methylation and/or gene expression of <i>IRS1</i> in both placenta and offspring leukocytes were significantly associated with various metabolic risk parameters at age 6 (all <i>p</i> ≤ 0.05). Logistic regression models (LRM) and machine learning (ML) models indicated that <i>IRS1</i> methylation in the placenta could strongly predict offspring obesity. Our results suggest that <i>IRS1</i> may serve as a potential biomarker for the prediction of obesity and metabolic risk in children.

International Journal of Molecular SciencesVol. 26(7)
Hospital Sant Joan de Déu Barcelona (ES), Universitat de Girona (ES), Instituto de Salud Carlos III (ES), Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (ES), Institut d'Investigació Biomèdica de Girona (ES), Hospital Universitari de Girona Doctor Josep Trueta (ES), KU Leuven (BE)
Instituto de Salud Carlos III
Good health and well-being
Openalex Percentile: Top 95%
Epigenetics and DNA Methylation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.