Evidence map›Paper›PMID 41751848›Full record

ArticleInternational journal of molecular sciences2026

Impact of Sex on Plasma Biomarkers in ob/ob Mice.

Yunha Suh, Kwang-Eun Kim

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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

2 authors.

Yunha SuhOrganelle Medicine Research Center, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.
Kwang-Eun KimOrganelle Medicine Research Center, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.ORCID 0000-0002-5355-1979

Funding

National Research Foundation of Korea RS-2022-NR072270National Research Foundation of Korea RS-2024-00409403National Research Foundation of Korea RS-2024-00440802National Research Foundation of Korea RS-2025-15782968
6 · The paper itself

Abstract

Sex is a critical biological variable that influences disease incidence, progression, and therapeutic responses; therefore, it must be incorporated into biomedical research. Despite this, most mouse studies historically have not compared animals by sex. Recently, growing evidence has indicated that sex-specific analyses are important in obesity and metabolic disorders. The ob/ob mouse is a widely used model for metabolic disease research; however, sex differences in plasma biomarkers have not been fully characterized in this model. In this study, male and female ob/ob mice at 8 weeks of age exhibited comparable body weight, blood glucose levels, and adipose tissue mass. Plasma proteomics analysis using the Olink platform revealed that 27% (23/84) of quantified proteins exhibited sex differences, with 91% (21/23) of these proteins elevated in females. Notably, Enolase 2 (ENO2), also known as neuron-specific enolase (NSE), was consistently elevated in female ob/ob mice and showed a similar sex-associated pattern in female patients with non-alcoholic steatohepatitis (NASH). While the human NASH data provide correlative support rather than direct clinical validation, these observations underscore the importance of considering sex as a biological variable in metabolic disease research. Incorporating sex-specific biomarker profiles may help refine mechanistic interpretation and inform future studies toward personalized therapeutic approaches.

Indexed as

BiomarkersObesityAdipose TissueAnimalsFemaleHumansMaleMiceMice, ObesePhosphopyruvate HydrataseProteomeProteomicsSex CharacteristicsSex FactorsBiomarkersPhosphopyruvate HydrataseProteomebiomarkerENO2NSEob/obplasma proteomesex differences

Identifiers

PMID41751848
PMCPMC12940322

What OpenQuestion holds

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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.