Pan-Fibrotic Gene Expression Signature in Major Chronic Diseases by Integrative Bulk and Single-Cell Transcriptomic Analyses
5 affiliations
- 1Department of Biomarker Research, Mosaiques Diagnostics GmbH, D-30659 Hannover, Germany
- 2Systems Biology Center, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
- 3Institut National de la Santé et de la Recherche Médicale (INSERM), Institute of Metabolic and Cardiovascular Diseases, 31432 Toulouse, France
- 4Faculty of Health, Université Toulouse III Paul-Sabatier, 31432 Toulouse, France
- 5Pôle d’Endocrinologie, Diabète et Nutrition, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, B-1200 Brussels, Belgium
Abstract
Fibrosis is a shared feature of chronic liver, kidney and heart disease, yet no molecular signature captures the mechanisms common to these organs. We integrated human microarray, bulk and single-nucleus RNA sequencing (snRNA-seq) data across 2022 unique tissue samples to identify a conserved pan-fibrotic signature. The pan-fibrotic signature was defined in a microarray discovery cohort (n = 1051) and verified in a microarray liver (n = 325), two RNA-seq (n = 414) and four integrated snRNA-seq validation datasets (n = 69). Diagnostic models were built using five machine learning approaches in separate RNA-seq cohorts (training n = 209; liver validation n = 70; kidney validation n = 24). 492 fibrosis-associated genes were identified across organs, including 23 hallmark genes, a subset of which correlated with disease severity. A novel finding was consistent metallothionein (MT1E, MT1X) downregulation; snRNA-seq resolved cell-type-specific expression of 12 hallmark genes, including MT1E/MT1X predominantly expressed in hepatocytes and liver sinusoidal endothelial cells. Elastic Net performed best across all three gene sets (AUROC 0.765–0.830), with scores correlating significantly with interstitial fibrosis and tubular atrophy (%IFTA; rho 0.58–0.73). This study defines a cross-organ pan-fibrotic signature, providing potential candidate therapeutic targets and biomarkers applicable across tissues affected by fibrosis.
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BibTeX
@article{jaimescampos2026panfibrotic,
title = {{Pan-Fibrotic Gene Expression Signature in Major Chronic Diseases by Integrative Bulk and Single-Cell Transcriptomic Analyses}},
author = {Mayra Alejandra Jaimes-Campos and Rafael Stroggilos and Joost P. Schanstra and Antonia Vlahou and Manon Brunet and Jean-Christophe Jonas and Mohammed Bensellam and Harald Mischak and Agnieszka Latosinska},
journal = {International Journal of Molecular Sciences},
year = {2026},
month = sep,
doi = {10.3390/ijms27198755},
url = {https://www.mdpi.com/1422-0067/27/19/8755},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Pan-Fibrotic Gene Expression Signature in Major Chronic Diseases by Integrative Bulk and Single-Cell Transcriptomic Analyses
AU - Mayra Alejandra Jaimes-Campos
AU - Rafael Stroggilos
AU - Joost P. Schanstra
AU - Antonia Vlahou
AU - Manon Brunet
AU - Jean-Christophe Jonas
AU - Mohammed Bensellam
AU - Harald Mischak
AU - Agnieszka Latosinska
PY - 2026
DA - 2026/09/30
JO - International Journal of Molecular Sciences
DO - 10.3390/ijms27198755
UR - https://www.mdpi.com/1422-0067/27/19/8755
AB - Fibrosis is a shared feature of chronic liver, kidney and heart disease, yet no molecular signature captures the mechanisms common to these organs. We integrated human microarray, bulk and single-nucleus RNA sequencing (snRNA-seq) data across 2022 unique tissue samples to identify a conserved pan-fibrotic signature. The pan-fibrotic signature was defined in a microarray discovery cohort (n = 1051) and verified in a microarray liver (n = 325), two RNA-seq (n = 414) and four integrated snRNA-seq validation datasets (n = 69). Diagnostic models were built using five machine learning approaches in separate RNA-seq cohorts (training n = 209; liver validation n = 70; kidney validation n = 24). 492 fibrosis-associated genes were identified across organs, including 23 hallmark genes, a subset of which correlated with disease severity. A novel finding was consistent metallothionein (MT1E, MT1X) downregulation; snRNA-seq resolved cell-type-specific expression of 12 hallmark genes, including MT1E/MT1X predominantly expressed in hepatocytes and liver sinusoidal endothelial cells. Elastic Net performed best across all three gene sets (AUROC 0.765–0.830), with scores correlating significantly with interstitial fibrosis and tubular atrophy (%IFTA; rho 0.58–0.73). This study defines a cross-organ pan-fibrotic signature, providing potential candidate therapeutic targets and biomarkers applicable across tissues affected by fibrosis.
SN - 1422-0067
ER -