Soumen Konar

photo de Soumen Konar


PhD Student
PhD Researcher in Nutritional Systems Biology, Multi-omics and Gut Microbiome
Equipe 1 Groupe 3
9 Av. de la Forêt de Haye, 54500 Vandœuvre-lès-Nancy
soumen.konar@univ-lorraine.fr
LinkedIn Orcid

My research focuses on the Developmental Origins of Health and Disease (DOHaD), with particular interest in the biological mechanisms linking maternal nutrition to childhood metabolic health. I investigate how one-carbon metabolism, epigenetic regulation, placental function, and the gut microbiome interact during early life to influence the risk of pediatric obesity and metabolic disorders.

My work integrates multi-omics datasets—including DNA methylation, metabolomics, proteomics, and microbiome data—from mother–child cohorts, combining biostatistics, systems biology, and genome-scale metabolic modelling. A major objective is to understand how nutritional exposures, particularly folate and vitamin B12 status, shape metabolic pathways and long-term health trajectories.

Keywords: DOHaD, fetal programming, pediatric obesity, one-carbon metabolism, folate, vitamin B12, epigenetics, DNA methylation, placental biology, gut microbiome, multi-omics integration, systems biology, metabolic modelling.

Multi-omics data analysis, systems biology and metabolic modelling to investigate the role of maternal nutrition, epigenetics and gut microbiome in fetal programming and childhood obesity.

Soumen Konar is a joint PhD researcher at Inserm U1256 NGERE, University of Lorraine, and the University of Luxembourg. He holds a degree in Medical Sciences (WBUHS, India), a Master’s degree in Genetics (MAKAUT, India), and an M2 Master’s degree in RNA and Enzyme Sciences from the University of Lorraine.

His research focuses on the developmental origins of health and disease (DOHaD), integrating epigenomics, metabolomics, proteomics, microbiome science, and systems biology approaches to understand the early-life mechanisms underlying pediatric obesity and metabolic disorders. He develops computational and genome-scale metabolic models to investigate host–microbiome interactions and nutritional influences on long-term health.