ArticleInflammation2025
Inflammatory Protein Signatures as Predictive Disease-Specific Markers for Non-Alcoholic Steatohepatitis (NASH).
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.
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.
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.
Who cites it
11 citing papers in PubMed, 9 citations in OpenAlex.
- Chemokines and chemokine receptors in metabolic dysfunction-associated steatohepatitis: pathogenic mechanisms and clinical implications.Cellular & molecular biology letters · 2026Review
- Hepatic lipid accumulation induced by mono-(2-ethylhexyl) phthalate and potential ERBB2-associated inflammatory signaling in NAFLD.Frontiers in pharmacology · 2026Article
- MCT4 alleviates lipid accumulation, inflammation and PANoptosis in non-alcoholic fatty liver disease by inhibiting JAK-STAT signaling transduction.American journal of translational research · 2026Article
- The Dual Role of IP-10/CXCL10 in Liver Injury: From Pathogenic Mediator to Clinical Biomarker and Therapeutic Target.Drug design, development and therapy · 2026Review
- Transcriptomic and Proteomic Analyses Identify THBS2, VWF, NFASC, and AKR1B10 as Diagnostic Biomarkers for Advanced Fibrosis in NAFLD.Journal of inflammation research · 2026Article
- Thykamine™: A New Player in the Field of Anti-Inflammatory Drugs.Biomedicines · 2025Article
- Deciphering the hepatoprotective mechanism of Sarcopyramis nepalensis wall against non-alcoholic fatty liver disease by network pharmacology and experimental validation.Scientific reports · 2025Article
- The Intriguing Roles of Cytokines in Metabolic Dysfunction-Associated Steatotic Liver Disease: A Narrative Review.Current obesity reports · 2025Review
- Article
- ACSS2 and metabolic diseases: from lipid metabolism to therapeutic target.Lipids in health and disease · 2025Review
- A new perspective on non-invasive diagnosis of non- alcoholic fatty liver disease: evidence integration of inflammatory and metabolic biomarkers based on a scoping review.Frontiers in endocrinology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.