Distinct systemic metabolic signatures in premenopausal women with lipedema revealed by composite indices.

BACKGROUND

Lipedema is a chronic adipose tissue disorder with disproportionate fat accumulation in the extremities and is often misdiagnosed as obesity. Although women with lipedema appear to be metabolically distinct from body mass index (BMI)-matched controls, their fasting metabolism remains insufficiently characterized. We therefore aimed to define the metabolic signature of lipedema using serum NMR metabolomics and anthropometric profiling.

METHODS

We conducted a study with 24 premenopausal women with lipedema and 21 BMI-matched controls. Fasting serum samples were analyzed using NMR spectroscopy and anthropometric data were collected. Regional body composition was additionally assessed in an exploratory matched DXA subset (n=12). To characterize coordinated metabolic differences beyond single analytes, we derived exploratory composite indices and applied multivariate analyses.

RESULTS

Despite similar BMI, women with lipedema showed lower waist circumference, waist-to-hip ratio and lower fasting insulin than controls (age-adjusted p = 0.032). NMR profiling revealed lower alanine (p < 0.001), lactate (p = 0.004), pyruvate (p = 0.021), and elevated ketone bodies (3-hydroxybutyric acid: p = 0.009; acetoacetic acid: p = 0.035; acetone: p = 0.006). These alterations were reflected by significant group differences in composite indices for fat distribution (g = 1.26; p < 0.001), glycolysis (g = 0.74; p = 0.018), and ketone metabolism (g = 0.70; p = 0.018). Principal component analysis of the selected indices explained 78% of the total variance and showed partial group separation between lipedema and controls.

CONCLUSION

Lipedema is associated with a distinct fasting metabolic profile characterized by reduced glycolytic intermediates, enhanced ketone body signals, and a more peripheral fat distribution despite comparable BMI. These findings support the concept of lipedema as a metabolically distinct phenotype and suggest that multivariate metabolic signatures may help refine future diagnostic and interventional approaches.