ArticleBiology2025
Dissecting the Cellular Heterogeneity Underlying Liver Diseases Through the Integration of GWASs and Single-Cell RNA Sequencing.
Article in Biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Psychiatric Comorbidity and Metabolic Heterogeneity in a Multimorbid Cardiometabolic Cohort: An Exploratory Real-World Analysis.Healthcare (Basel, Switzerland) · 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
3 authors.
Funding
Abstract
Liver diseases encompass a wide range of etiologies and involve highly heterogeneous cellular environments, yet the specific cellular states through which genetic risk contributes to disease remain incompletely understood. In this study, we integrated genome-wide association study (GWAS) data from six liver diseases and two metabolic traits with transcriptomic profiles of approximately 168,000 human liver cells at single-cell resolution, using the single-cell disease relevance score (scDRS) approach. Our results revealed that disease-associated genetic signals are predominantly localized to non-parenchymal cells-particularly liver sinusoidal endothelial cells (LSECs), cholangiocytes, and specific subsets of lymphocytes. Notably, we identified marked intra-cell-type heterogeneity, with disease associations confined to specific subpopulations exhibiting immune activation or stress-responsive transcriptional programs. For example, autoimmune and viral liver diseases were linked to immunologically active LSECs and cholangiocytes, whereas their metabolically active counterparts showed no enrichment. These findings highlight the necessity of resolving liver cell complexity to uncover the functional basis of genetic risk and suggest that susceptibility to liver disease is driven by specialized cell states within broader cellular categories. Our study provides a refined cellular map of liver disease susceptibility, offering new perspectives for understanding pathogenic mechanisms and informing targeted therapeutic strategies.
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.