Evidence map›Paper›PMID 41769662›Full record

ArticleFrontiers in nutrition2026

Dysregulated high-density lipoprotein and low-density lipoprotein subfractions increase metabolic dysfunction-associated steatotic liver disease risk: a study of patients across body mass index categories.

Hao-Yun Yu, Jia-Qi Zhang, Pei-Qi Sun, Qing-Hua Li, Hong Lin, Jia-Yang Wang, Xiao-Jing Qian, Xiao-Di Yang, Cheng Hu, Ping Tian and 2 more

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Hao-Yun Yu *Department of Gastroenterology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Jia-Qi Zhang *Department of Pharmacy, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Pei-Qi Sun *Department of Gastroenterology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Qing-Hua LiState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, Innovation Research Institute of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Hong LinState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, Innovation Research Institute of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Jia-Yang WangDepartment of Gastroenterology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xiao-Jing QianDepartment of Pharmacy, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xiao-Di YangState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, Innovation Research Institute of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Cheng HuExperiment Center for Science and Technology, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Ping TianState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, Innovation Research Institute of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yuan-Ye JiangDepartment of Gastroenterology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Guo-Qiang LinState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, Innovation Research Institute of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To investigate biomarker differences among patients with metabolic dysfunction-associated steatotic liver disease (MASLD) across body mass index (BMI) types, we analyzed clinical data from 2,013 subjects and serum samples from 402 patients. The clinical characteristics and lipoprotein subclass profiles were evaluated. Methods: Participants were grouped based on BMI into overweight MASLD (113 participants), overweight controls (107 participants), lean MASLD (83 participants), and lean controls (99 participants). Serum samples from each group underwent nuclear magnetic resonance-based metabolomic analyses, and clinical and omics data were compared between the lean and overweight MASLD groups and paired control cohorts. Results: Our study demonstrated distinct omics characteristics for lean MASLD compared with their overweight equivalents. Metabolomic analysis of the serum from the four groups identified six lipoprotein subclasses with significant diagnostic accuracy (area under the curve (AUC) > 0.7), unique to lean individuals with MASLD. In contrast, overweight patients with MASLD had 13 unique lipoprotein subclasses that exhibited a high diagnostic value. These lipoproteins correlate with clinical parameters, such as uric acid, urea, creatinine, eosinophils, blood glucose, and alanine aminotransferase. Conclusion: Lean and overweight patients with MASLD display unique lipoprotein omics characteristics in an Asian population, primarily involving high-density lipoprotein (HDL) and low-density lipoprotein (LDL) subcomponents, suggesting their potential as effective biomarkers.

Indexed as

biomarkersbody mass indexlipoprotein subfractionsmetabolic dysfunction-associated steatotic liver diseaseNMR metabolomics

Identifiers

PMID41769662
PMCPMC12947705

What Socratic holds

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LicenceCC BY
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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 Socratic graph.