Evidence map›Paper›PMID 39216827›Full record

ArticleVirus research2024

New insights into potential biomarkers and their roles in biological processes associated with hepatitis C-related liver cirrhosis by hepatic RNA-seq-based transcriptome profiling.

Hossein Nasr Azadani, Mohssen Nassiri Toosi, Shohreh Shahmahmoodi, Ahmad Nejati, Hamzeh Rahimi, Mohammad Farahmand, Abolfazl Keshavarz, Fatemeh Ghorbani Motlagh, Katayoun Samimi-Rad

Abstract read
In one paragraph

Article in Virus research, 2024. 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. Genes · 2024
    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

9 authors.

Hossein Nasr AzadaniDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mohssen Nassiri ToosiLiver Transplantation Research Center, Imam-Khomeini Hospital, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Shohreh ShahmahmoodiDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; Food Microbiology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Ahmad NejatiDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Hamzeh RahimiDepartment of Molecular Medicine, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Mohammad FarahmandPediatric Infectious Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Abolfazl KeshavarzDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Fatemeh Ghorbani MotlaghDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Katayoun Samimi-RadDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: ksamimirad@sina.tums.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic hepatitis C virus infection is a major cause of mortality due to liver cirrhosis globally. Despite the advances in recent therapeutic strategies, there is yet a high burden of HCV-related cirrhosis worldwide concerning low coverage of newly developed antiviral therapies, insufficient validity of the current diagnostic methods for cirrhosis, and incomplete understanding of the pathogenesis in this stage of liver disease. Hence we aimed to clarify the molecular events in HCV-related cirrhosis and identify a liver-specific gene signature to potentially improve diagnosis and prognosis of the disease. Through RNA-seq transcriptome profiling of liver samples of Iranian patients with HCV-related cirrhosis, the differentially expressed genes (DEGs) were identified and subjected to functional annotation including biological process (BP) and molecular function (MF) analysis and also KEGG pathway enrichment analysis. Furthermore, the validation of RNA-seq data was investigated for seven candidate genes using qRT-PCR. Moreover, the diagnostic and prognostic power of validated DEGs were analyzed in both forms of individual DEG and combined biomarkers through receiver operating characteristic (ROC) analysis. Finally, we explored the pair-wise correlation of these six validated DEGs in a new approach. We identified 838 significant DEGs (padj ˂0.05) enriching 375 and 15 significant terms subjected to BP and MF, respectively (false discovery rate ˂ 0.01) and 46 significant pathways (p-value ˂ 0.05). Most of these biological processes and pathways were related to inflammation, immune responses, and cellular processes participating somewhat in the pathogenesis of liver disease. Interestingly, some neurological-associated genes and pathways were involved in HCV cirrhosis-related neuropsychiatric disorders. Out of seven candidate genes, six DEGs, including inflammation-related genes ISLR, LTB, ZAP70, KLRB1, and neuronal-related genes MOXD1 and Slitrk3 were significantly confirmed by qRT-PCR. There was a close agreement in the expression change results between RNA-seq and qRT-PCR for our candidate genes except for SAA2-SAA4 (P= 0.8). High validity and reproducibility of six novel DEGs as diagnostic and prognostic biomarkers were observed. We also found several pair-wise correlations between validated DEGs. Our findings indicate that the six genes LTB, ZAP70, KLRB1, ISLR, MOXD1, and Slitrk3 could stand as promising biomarkers for diagnosing of HCV-related cirrhosis. However, further studies are recommended to validate the diagnostic potential of these biomarkers and evaluate their capability as targets for the prevention and treatment of cirrhosis disease.

Indexed as

BiomarkersGene Expression ProfilingHepatitis C, ChronicLiver CirrhosisFemaleHepacivirusHepatitis CHumansIranLiverMaleMiddle AgedPrognosisRNA-SeqROC CurveTranscriptomeBiomarkersBiomarkersCirrhosisGene expressionHCVNeuropsychiatric disorders

Identifiers

PMID39216827
PMCPMC11415974

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.