Evidence map›Paper›PMID 41899424›Full record

ArticleCurrent issues in molecular biology2026

Circulating MicroRNA Profiling for Phenotypic Stratification in Patients with Metabolic Dysfunction-Associated Fatty Liver Disease: A Candidate-Based Study.

Sumbal Nida, Dilshad Ahmed Khan, Muhammad Amjad Pervez, Nayyar Chaudhry, Mohammad Qaiser Alam Khan, Alveena Younas

Abstract read
In one paragraph

Article in Current issues in molecular biology, 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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0cells of the map it votes in
0citing papers 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

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

6 authors.

Sumbal NidaArmed Forces Institute of Pathology, National University of Medical Sciences, Rawalpindi 46000, Pakistan.
Dilshad Ahmed KhanArmed Forces Institute of Pathology, National University of Medical Sciences, Rawalpindi 46000, Pakistan.
Muhammad Amjad PervezArmed Forces Institute of Pathology, National University of Medical Sciences, Rawalpindi 46000, Pakistan.ORCID 0000-0001-8562-4733
Nayyar ChaudhryArmed Forces Institute of Pathology, National University of Medical Sciences, Rawalpindi 46000, Pakistan.
Mohammad Qaiser Alam KhanArmed Forces Institute of Pathology, National University of Medical Sciences, Rawalpindi 46000, Pakistan.ORCID 0009-0003-0466-1631
Alveena YounasArmed Forces Institute of Pathology, National University of Medical Sciences, Rawalpindi 46000, Pakistan.

Funding

National University of Medical Sciences 02/Acct/NUMS/18/3/2021
6 · The paper itself

Abstract

Metabolic dysfunction-associated fatty liver disease (MAFLD) comprises phenotypic subgroups, including type-2 diabetes-associated MAFLD (T2D-MAFLD), obesity-associated MAFLD (OB-MAFLD), and lean MAFLD (L-MAFLD). Emerging evidence indicates that dysregulation of miRNAs plays a key role in MAFLD pathogenesis and progression. This study evaluated the diagnostic accuracy of a plasma miRNA-based signature as a non-invasive biomarker for early detection and phenotypic stratification of MAFLD. A total of 393 MAFLD patients and 109 healthy controls were enrolled. Plasma expression of miR-122, miR-103a, miR-222, miR-15a, miR-34a, miR-192, miR-197, and miR-99a was quantified using Reverse transcription polymerase chain reaction. Compared to controls, MAFLD patients exhibited significant upregulation of miR-122, miR-103a, miR-222, miR-15a, and miR-34a, alongside downregulation of miR-197 and miR-99a. Multinomial logistic regression revealed phenotype-specific associations: miR-103a, miR-34a, and miR-197 with T2D-MAFLD; miR-122, miR-222, and miR-99a with OB-MAFLD; and miR-15a with L-MAFLD. Receiver operating characteristic analysis demonstrated highest individual diagnostic accuracy for miR-197 in T2D-MAFLD (AUC = 0.784), miR-99a in OB-MAFLD (AUC = 0.869), and miR-15a in L-MAFLD (AUC = 0.776). Integrating combined miRNA panels with biochemical markers further improved diagnostic performance and clinical utility, achieving high positive and negative predictive values. In conclusion, plasma miRNA signatures enable phenotype-specific discrimination of MAFLD subtypes and may serve as promising non-invasive tools pending multi-center validation.

Indexed as

diagnostic accuracyinsulin resistanceMAFLD phenotypesmetabolic dysfunction-associated fatty liver diseasemetabolic risk factorsmicroRNAobesitytype 2 diabetes

Identifiers

PMID41899424
PMCPMC13024945

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.