Defining Lipedema’s Molecular Hallmarks by Multi-Omics Approach for Disease Prediction in Women

Authors

• Leon G Straub
• Jan-Bernd Funcke
• Nolwenn Joffin
• Chanmin Joung
• Sara Al-Ghadban
• Shangang Zhao
• Qingzhang Zhu
• Ilja L Kruglikov
• Yi Zhu
• Paul R Langlais
• Ruth Gordillo
• Karen L Herbst
• Philipp E Scherer

Language

English

Publication Date

7-1-2025

Journal

Metabolism

DOI

10.1016/j.metabol.2025.156191

PMID

40097137

Abstract

Lipedema is a chronic disease in females characterized by pathologic subcutaneous adipose tissue expansion and hitherto remains without druggable targets. In this observational study, we investigated the molecular hallmarks of lipedema using an unbiased multi-omics approach. We found adipokine dysregulation in lipedema patients participating in a cross-sectional clinical study (ClinicalTrial.gov, NCT02838277), pointing towards the adipocyte as a key player. Analyses of newly generated transcriptomic (SRA, PRJNA940039) and proteomic (ProteomeXchange, PXD058489) datasets of early- and late-stage lipedema samples revealed a local downregulation of factors involved in inflammation. Concomitantly, factors involved in cellular respiration, oxidative phosphorylation, as well as in mitochondrial organization were upregulated. Measuring a cytokine and chemokine panel in the serum of non-menopausal women, we observed little systemic changes in inflammatory markers, but a trend towards increased VEGF. Metabolomic and lipidomic analyses highlighted altered circulating glutamic acid, glutathione, and sphingolipid levels, suggesting a broader dysregulation of metabolic and inflammatory processes. We subsequently benchmarked a set of models to accurately predict lipedema using serum factor measurements (sLPM). Our study of the molecular signature of lipedema thus provides not only potential targets for therapeutic intervention, but also candidate markers of disease development and progression.

Keywords

Humans, Female, Lipedema, Cross-Sectional Studies, Middle Aged, Adult, Proteomics, Metabolomics, Adipokines, Biomarkers, Transcriptome, Inflammation, Aged, Multiomics, Adipose tissue, Complement, Disease prediction, ElasticNet, Inflammation, Lipedema, Machine learning, Multi-omics, Random Forest classifier, Support vector machine

Published Open-Access

yes

Recommended Citation

Straub, Leon G; Funcke, Jan-Bernd; Joffin, Nolwenn; et al., "Defining Lipedema’s Molecular Hallmarks by Multi-Omics Approach for Disease Prediction in Women" (2025). Children’s Nutrition Research Center Staff Publications. 382.
https://digitalcommons.library.tmc.edu/staff_pub/382