Evidence map›Paper›PMID 42631767›Full record

ArticleJournal of physiology and biochemistry2026

Unveiling the role of age in MASLD development and biological process activation: Implications for translational research.

Lucía Lameroli Mauriz, Andrea Scelza-Figueredo, Miranda Sol Orellano, Brian L Martínez Ruiz, Juan Bayo, Esteban Fiore, María José Cantero, Barbara Bueloni, Mailin Casadei, Maite G Fernandez-Barrena and 4 more

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Article in Journal of physiology and biochemistry, 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

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Lucía Lameroli MaurizExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina.
Andrea Scelza-FigueredoFacultad de Ciencias Biomédicas, Universidad Austral, Pilar, Argentina.
Miranda Sol OrellanoImmuno-Endocrinology, Diabetes & Metabolism Laboratory, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina.
Brian L Martínez RuizFacultad de Ciencias Biomédicas, Universidad Austral, Pilar, Argentina.
Juan BayoExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina.
Esteban FioreExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina.
María José CanteroExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina.
Barbara BueloniExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina.
Mailin CasadeiExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina.
Maite G Fernandez-BarrenaHepatology Laboratory, Solid Tumors Program, CIMA, CCUN, University of Navarra, Pamplona, Spain.
Matias A AvilaHepatology Laboratory, Solid Tumors Program, CIMA, CCUN, University of Navarra, Pamplona, Spain.
Luz AndreoneFacultad de Ciencias Biomédicas, Universidad Austral, Pilar, Argentina.
Guillermo D MazzoliniExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina. GMAZZOLI@austral.edu.ar.
Catalina AtorrasagastiExperimental Hepatology and Gene Therapy Program, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET - Universidad Austral, Pilar, Argentina. CAtorrasagasti@austral.edu.ar.

Funding

Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) PICT 2021-CAT-II-00123Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) PICT-2021-GRF-T2-00283
6 · The paper itself

Abstract

Age is a risk factor for severity and progression of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), yet its specific contributions to liver injury and molecular alterations remain unclear. Current animal models often overlook this variable. This study investigates how aging influences MASLD progression in a murine model, focusing on histological, biochemical, and transcriptomic differences. Young (2-month-old) and middle-aged (10-month-old) C57BL/6N male and female mice were fed chow (CD) or high-fat diet (HFD) for 20 weeks. Metabolic and biochemical parameters were assessed, and liver tissue analyzed by histology and RNA sequencing. Differentially expressed genes were identified with Limma, followed by gene ontolgy enrichment. Translational relevance was evaluated using the MASLD Human Proximity Score (MHPS). Middle-aged males developed insulin resistance and more severe hepatic injury than young males after HFD. Histological and biochemical assessments confirmed advanced disease in middle-aged mice, with extensive lipid accumulation, hepatocellular hypertrophy, inflammation and fibrosis. Females showed milder damage. Diet was the main determinant of transcriptomic changes in males: young HFD mice activated tissue remodeling pathways, whereas middle-aged mice showed inflammatory activation and reduced energy metabolism. In females, transcriptomic responses were attenuated, with metabolic and stress-related changes restricted mostly to young HFD animals. MHPS ranked the middle-aged male model highest in similarity to human MASLD. Age is a critical determinant of hepatic responses to dietary stress, with sex-specific modulation. The middle-aged male model closely mirrors human MASLD, providing a more relevant preclinical platform to improve patient stratification and therapeutic discovery.

Indexed as

AgingFatty LiverNon-alcoholic Fatty Liver DiseaseAge FactorsAnimalsDiet, High-FatDisease Models, AnimalFemaleHumansInsulin ResistanceLiverMaleMiceMice, Inbred C57BLSex FactorsTranscriptomeAgeMASLDMASLD human proximity score (MHPS)Mouse modelSexTranscriptome

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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.