ArticleFrontiers in endocrinology2026
A six-metabolite signature characterizes metabolically unhealthy obesity and reveals hidden metabolic risk within metabolically healthy obesity.
Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background/objectives: Metabolically healthy obesity (MHO) is commonly defined by the absence of metabolic syndrome-related abnormalities despite obesity. However, conventional clinical definitions may overlook substantial metabolic heterogeneity and hidden cardiometabolic risk. We aimed to identify metabolomic signatures distinguishing MHO from metabolically unhealthy obesity (MUHO), evaluate their discriminatory performance, and determine whether metabolomic profiling could further characterize heterogeneity within conventionally defined MHO. Methods: We analyzed 13215 UK Biobank adults with obesity and available clinical biomarker and NMR-based metabolomic data. Metabolic health was defined using triglycerides, HDL cholesterol, hypertension, fasting glucose, type 2 diabetes, and lipid-lowering medication use. Univariable logistic regression and LASSO regression were used for metabolite selection. Logistic regression and XGBoost models were developed using clinical variables, metabolomic markers, and their combination. A weighted metabolic signature score was applied within the MHO group to characterize cross-sectional metabolic and clinical heterogeneity, and proteomic analyses were performed in approximately 1408 participants. Results: A six-metabolite signature comprising HDL_size, S_HDL_CE, XL_HDL_TG, GlycA, M_VLDL_C, and Omega_3 was selected. The combined clinical-metabolomic model showed better discrimination than clinical variables alone in the test set, with AUCs of 0.78 and 0.69, respectively. Within MHO, higher metabolomic score was associated with higher triglycerides, HbA1c, waist-to-hip ratio, lower HDL cholesterol, and greater metabolic and cardiovascular comorbidity burden. Proteomic analyses identified 10 metabolite-associated core proteins implicating lipoprotein remodeling, adipokine signaling, inflammation, and vascular-related pathways. Conclusions: A six-metabolite signature distinguished MHO from MUHO and revealed hidden metabolic risk within conventionally defined MHO, provides a metabolomic framework for refining obesity phenotyping and warrants further validation before clinical translation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.