ArticleThe EPMA journal2026
Sex-specific cardiometabolic phenotypes in MASLD: 3PM-centric stratification and trajectory mapping for proactive risk assessment.
Article in The EPMA journal, 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) poses a challenge for Predictive, Preventive, and Personalised Medicine (3PM) due to intrinsic heterogeneity. Current management is reactive. This study's rationale is that one-size-fits-all labels fail to capture systemic effects and early metabolic shifts. We hypothesized that sex-specific metabolic architectures and transitional hubs can be identified using probabilistic modeling to shift MASLD management toward predictive diagnostics and targeted prevention. Methods: We performed unsupervised computational phenotyping using GSEM-based Latent Class Analysis (LCA) across two cohorts: Bogalusa Heart Study ( Results: LCA disaggregated MASLD into sex-specific cardiometabolic risk architectures. While aging increased fibrosis risk equally across sexes, evolutionary pathways were profoundly dimorphic. PAGA revealed that females follow interconnected, potentially reversible trajectories-suggesting unique bioenergetic flexibility-whereas males exhibit polarized, abrupt transitions. Clinical relevance varied: in females, a singular high-risk subtype drove mortality (HR = 6.05), whereas risk was broadly distributed in males. Findings were translated into a Python-based 3PM-Risk Calculator for real-time stratification available at https://applacmetsynmasld-i9m9ctxj5icdtyyvdv8tkz.streamlit.app. Conclusion: Our framework enables holistic health risk assessment by identifying high-priority metabolic phenotypes that traditional diagnostics overlook. Pinpointing sex-specific transitional hubs provides a critical window for targeted prevention to intercept disease before irreversible damage occurs. This digital tool facilitates the translation of individualised profiles into clinical practice, fulfilling the 3PM mission to shift from reactive care to proactive, personalised healthcare strategies across the life-course. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-026-00448-5.
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.