Integrative exome sequencing and machine learning identify MICB and interferon pathway genes as contributors to SSc risk.
Journal:
Annals of the rheumatic diseases
Published Date:
Aug 1, 2025
Abstract
OBJECTIVES: Systemic sclerosis (SSc) is a complex autoimmune disease with both known and unidentified genetic contributors. While genome-wide association studies (GWAS) have implicated multiple loci, many reside in noncoding regions. We aimed to identify novel protein-coding variants and pathogenic pathways using exome sequencing (ES) integrated with an Evolutionary Action-Machine Learning (EAML) framework, single-cell RNA sequencing (scRNA-seq), and expression quantitative trait locus (eQTL) analysis.