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ArticleJHEP reports : innovation in hepatology2026

Integrative multi-omics analysis identifies stellate cell-derived complement component 7 as a predictor of fibrosis and liver-related events in MASLD.

Shohei Kondo, Takefumi Kimura, Takanobu Iwadare, Mohammad Taufeeq, Takao Miwa, Naoyuki Fujimori, Tomoyuki Nakajima, Shun-Ichi Wakabayashi, Taiki Okumura, Hiroyuki Kobayashi and 10 more

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Article in JHEP reports : innovation in hepatology, 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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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

20 authors.

Shohei KondoDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Takefumi KimuraDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan; Consultation Center for Liver Diseases, Shinshu University Hospital, Matsumoto, Japan; Institute of Biomedical Sciences, Shinshu University, Matsumoto, Japan. Electronic address: kimuratakefumii@yahoo.co.jp.
Takanobu IwadareDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Mohammad TaufeeqDepartment of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India.
Takao MiwaDepartment of Medicine, University of California San Diego, La Jolla, CA, USA; Department of Gastroenterology/Internal Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan.
Naoyuki FujimoriDepartment of Gastroenterology, Shinshu Ueda Medical Center, Ueda, Japan.
Tomoyuki NakajimaDepartment of Laboratory Medicine, Shinshu University School of Medicine, Matsumoto, Japan.
Shun-Ichi WakabayashiDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Taiki OkumuraDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Hiroyuki KobayashiDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Yuki YamashitaDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Satsuki IsogaiDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Tomoo YamazakiDepartment of Medicine, Division of Gastroenterology, Shinshu University School of Medicine, Matsumoto, Japan.
Mai IwayaDepartment of Laboratory Medicine, Shinshu University School of Medicine, Matsumoto, Japan.
Takeshi UeharaDepartment of Laboratory Medicine, Shinshu University School of Medicine, Matsumoto, Japan.
Takeji UmemuraShinshu University School of Medicine, Matsumoto, Japan.
Saket ChoudharyKoita Centre for Digital Health, Indian Institute of Technology Bombay, Mumbai, India.
Bernd SchnablDepartment of Medicine, University of California San Diego, La Jolla, CA, USA; Department of Medicine, VA San Diego Healthcare System, San Diego, CA, USA.
Shanu JainDepartment of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India.
Naoki TanakaInstitute of Biomedical Sciences, Shinshu University, Matsumoto, Japan; Department of Global Medical Research Promotion, Shinshu University Graduate School of Medicine, Matsumoto, Japan; International Relations Office, Shinshu University School of Medicine, Matsumoto, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

aimsMetabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health burden, with advanced fibrosis and liver-related events (LREs) being key prognostic factors. However, existing non-invasive biomarkers insufficiently capture fibrosis severity and LRE risk. We aim at identifying a mechanistically grounded biomarker for clinical risk stratification.

methodsWe performed an integrative multi-omics analysis using publicly available hepatic transcriptomic and plasma proteomic datasets together with in-house spatial transcriptomic analyses, followed by validation in three MASLD cohorts: biopsy-confirmed Japanese (n = 430), vibration-controlled transient elastography-based (n = 120), and UK Biobank (n = 4,486) cohorts. LRE risk was assessed using Kaplan-Meier and Cox regression analyses. Single-nucleus RNA sequencing, in situ hybridization, and in vitro assays using hepatic stellate cells (HSCs) were performed to assess molecular localization and functional relevance.

resultsComplement component 7 (C7) was consistently identified as the top candidate. Spatial transcriptomics and in situ hybridization localized C7 expression to activated HSCs within fibrotic regions. Serum C7 levels strongly correlated with fibrosis stage and liver stiffness. A threshold ≥140 μg/ml predicted significantly higher LRE risk and remained independently predictive (hazard ratio 4.54, 95% confidence interval 1.49-13.82). In area under the receiver operating characteristic curve analysis, C7 outperformed FIB-4, autotaxin, AST-to-platelet ratio index (APRI), FibroScan-AST (FAST), and AST-to-ALT ratio (AAR), with AUROCs of 0.90 vs. 0.85, 0.84, 0.77, 0.75, 0.67, respectively). External validation in UK Biobank supported these findings. Spatial module-score analyses linked C7-enriched regions to extracellular matrix/HSC-related fibrogenic programs and progenitor/ductular reaction signatures. C7 knockdown in LX-2 cells suppressed extracellular matrix genes including LAMA2, LAMB1, and COL6A3.

conclusionsC7 is a mechanistically supported, non-invasive biomarker that surpasses conventional indices in predicting fibrosis and LREs in MASLD. These findings highlight complement-mediated fibrogenesis and C7 as a potential tool for clinical risk stratification. IMPACT AND IMPLICATIONS: This study identifies complement component 7 (C7) as a non-invasive biomarker associated with fibrosis severity and liver-related events in MASLD through an integrative multi-omics approach. C7 was linked to HSC-rich fibrotic niches, extracellular matrix remodeling, and future liver-related risk, with external validation in the UK Biobank cohort. These findings suggest that serum C7 may improve risk stratification by capturing both fibrosis burden and clinically relevant disease progression in MASLD.

Indexed as

BiomarkerC7ComplementFibrosisLiver-related eventsMASLDMulti-omicsNAFLDUK Biobank

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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 OpenQuestion graph.