Evidence map›Paper›PMID 38676759›Full record

ArticleInflammation2025

Inflammatory Protein Signatures as Predictive Disease-Specific Markers for Non-Alcoholic Steatohepatitis (NASH).

Nadella Mounika, Suraj Bhausaheb Mungase, Shivangi Verma, Savneet Kaur, Utpal Jyoti Deka, Tarini Shankar Ghosh, Ramu Adela

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In one paragraph

Article in Inflammation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

11 citing papers in PubMed, 9 citations in OpenAlex.

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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

7 authors at 4 institutions in 1 country.

Nadella MounikaDepartment of Pharmacy Practice, National Institute of Pharmaceutical Education and Research-Guwahati, Sila Katamur (Halugurisuk), Changsari, Kamrup, Assam-781101, India.
Suraj Bhausaheb MungaseDepartment of Pharmacy Practice, National Institute of Pharmaceutical Education and Research-Guwahati, Sila Katamur (Halugurisuk), Changsari, Kamrup, Assam-781101, India.
Shivangi VermaDepartment of Computational Biology, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), Okhla Phase III, New Delhi, 110020, India.
Savneet KaurDepartment of Molecular and Cellular Medicine, Institute of Liver & Biliary Science (ILBS), New Delhi-110 070, Vasant Kunj, India.
Utpal Jyoti DekaDepartment of Gastroenterology, Downtown Hospital, GS Road, Bormotoria, Guwahati, Assam-781006, India.
Tarini Shankar GhoshDepartment of Computational Biology, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), Okhla Phase III, New Delhi, 110020, India.
Ramu AdelaDepartment of Pharmacy Practice, National Institute of Pharmaceutical Education and Research-Guwahati, Sila Katamur (Halugurisuk), Changsari, Kamrup, Assam-781101, India. ramu@niperguwahati.in.
National Institute of Pharmaceutical Education and Research · INIndraprastha Institute of Information Technology Delhi · INAssam Down Town University · INInstitute of Liver and Biliary Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic disease worldwide, consisting of a broad spectrum of diseases such as simple steatosis (NAFL), non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma. Hepatic inflammation plays a key role in the pathophysiology of NAFLD. Inflammatory mediators such as cytokines and chemokines are considered as contributing factors to NAFLD development and progression. In the present study, we aimed to investigate the inflammatory protein signatures as predictive disease-specific markers for non-alcoholic fatty liver disease (NAFLD). This cross-sectional study included healthy control (n = 64), NAFL (n = 109), and NASH (n = 60) human subjects. Serum concentrations of various cytokines and chemokines were evaluated using sensitive multiplex assays. We used principal component analysis (PCoA) to reveal distinct differences in the levels of cytokines and chemokines between each of the study groups. Further, a random forest classification model was developed to identify the panel of markers that could predict diseases. The protein-protein network analysis was performed to determine the various signaling pathways associated with the disease-specific panel of markers. Serum concentrations of TNF-α, IL-1β, IL-1ra, G-CSF, PDGF-BB, MCP-1, MIP-1a, MIP-1b, RANTES, eotaxin, IL-8 and IP-10 were significantly increased in NASH group as compared to control group. Furthermore, serum concentrations of IL-9 and IL-13 were significantly lower in the NASH group, whereas IL-2 levels were significantly decreased in the NAFL group when compared to the control group. PCoA results demonstrated statistically significant differences in cytokines and chemokines between each of the study groups (PERMANOVA p = 0.001; R

Indexed as

CytokinesInflammation MediatorsNon-alcoholic Fatty Liver DiseaseAdultBiomarkersChemokinesCross-Sectional StudiesFemaleHumansInflammationMaleMiddle AgedBiomarkersChemokinesCytokinesInflammation Mediatorsbiomarkers.chemokinescytokinesnon-alcoholic fatty liver diseasenon-alcoholic steatohepatitis

Identifiers

PMID38676759
OpenAlexW4395695516

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.