# PBMC proteome is altered in children with high body fat percentage

## TL;DR

This study finds that children with higher body fat have altered proteins in blood cells linked to inflammation and metabolism.

## Contribution

The study identifies 148 proteins in PBMCs associated with body fat percentage in children, emphasizing body composition over traditional metrics.

## Key findings

- 148 proteins in PBMCs were significantly associated with body fat percentage in children.
- Obesity-related proteomic changes are better explained by body fat percentage than by height- and weight-based metrics.
- Key altered proteins include CutA, GTPase-related proteins, and mitochondrial proteins.

## Abstract

Obesity in children is an increasing public health issue. Excess adipose tissue, especially in the form of visceral obesity, is associated with poorer cardiometabolic health, persistent low-grade inflammation and oxidative stress. Mass-spectrometry based analysis of peripheral blood mononuclear cells (PBMC) can reveal changes associated with dietary patterns, inflammatory diseases and obesity in adults. We aimed to identify proteomic dysregulations in PBMC of children with obesity, focusing on pathways linked to inflammation and metabolic dysfunction. We isolated cell lysate proteins from blood samples obtained from 71 children and adolescents (aged 5–18) with normal weight, overweight or obesity, measured body composition using bioelectrical impedance analysis, while protein abundances in PBMC lysates were determined using nano-electrospray liquid chromatography coupled with tandem mass spectrometry. Controlling for participant sex, age and leukocyte count, we identified 148 proteins with abundance that was significantly associated with body fat percentage, including protein CutA, several proteins with GTPase activity, and multiple mitochondrial proteins. These obesity-associated changes are better explained by body fat percentage than by height- and weight-based metrics alone, highlighting the utility of body composition analysis for interpreting proteomic results in childhood obesity.

The online version contains supplementary material available at 10.1038/s41598-025-24461-2.