Systemic sclerosis & Raynaud's
Integrative exome sequencing and machine learning identify MICB and interferon pathway genes as contributors to systemic sclerosis (SSc) risk
Authors' conclusion
This integrative genomic study identifies novel risk loci and mechanistic pathways in SSc, highlighting MICB, NOTCH4, and interferon-related genes.
Study context
- Population
- SSc cases and controls of Caucasian ancestry; replication in 9,846 cases and 18,333 controls of European ancestryreplication: 9,846 cases, 18,333 controls
- Participants
- 2,559 vs 893
- Exposure
- SSc cases vs controls
- SSc casesn = 2,559
- Controlsn = 893reference
- Outcome
- Novel protein-coding variants and pathogenic pathways contributing to SSc risk
Methodological detailsexome sequencing, Evolutionary Action-Machine Learning (EAML), replication cohort, single-cell RNA sequencing (scRNA-seq), expression quantitative trait locus (eQTL) analysis
- Exome sequencing
- Evolutionary Action-Machine Learning (EAML)
- Replication cohort
- scRNA-seq
- eQTL analysis
Main finding
As reported in the abstract
- Novel SSc risk locus at MICB (rs2516497), identified and replicated
- P = 3.66 × 10-13
- EAML genes enriched in interferon signaling
- 284
Observational data: associations, not effects.
Original publication
Integrative exome sequencing and machine learning identify MICB and interferon pathway genes as contributors to SSc risk. Ann Rheum Dis. Published 13 June 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →