Evidence map›Paper›PMID 42179465›Full record

ArticleThe EPMA journal2026

Sex-specific cardiometabolic phenotypes in MASLD: 3PM-centric stratification and trajectory mapping for proactive risk assessment.

Carlos José Pirola, Luis Diambra, Tomas Fernández Gianotti, Silvia Sookoian

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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.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Carlos José PirolaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.ORCID 0000-0001-8234-4058
Luis DiambraConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.
Tomas Fernández GianottiSystems Biology of Complex Diseases. Translational Research in Health Center (CENITRES), Maimónides University, Buenos Aires, Argentina.
Silvia SookoianConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.ORCID 0000-0001-5929-5470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

AlcoholCentral obesityHDL cholesterolHolistic health risk assessmentHypertensionLatent class analysisLiver fibrosisMASHMASLDMetabolic syndromeMulti-level diagnosticsMulti-parametric analysisNon-invasive approachesObesityPatient phenotyping and stratificationPersonalised protection against health-to-disease transition (primary care) and against disease progression (secondary care)Sexual dimorphismTreatments tailored to individualised patient profilesTriglyceridesType 2 diabetesWaist circumference

Identifiers

PMID42179465
PMCPMC13191013

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Registered trials

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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.