Unique and shared transcriptomic signatures underlying localized scleroderma pathogenesis identified using...

Area of Science:

• Immunology
• Genomics
• Dermatology

Background:

• Localized scleroderma (LS) is an inflammatory fibrotic skin condition with distinct adult and pediatric presentations.
• Understanding the molecular drivers of LS pathogenesis is crucial for developing targeted therapies.

Purpose of the Study:

• To investigate cell-intrinsic and cell-extrinsic molecular signatures in adult and pediatric localized scleroderma (LS).
• To identify latent factors underlying LS pathophysiology using advanced machine learning.
• To compare molecular profiles between pediatric and adult LS and with systemic sclerosis (SSc).

Main Methods:

• Single-cell RNA sequencing (scRNA-Seq) was performed on LS patients (adult and pediatric) and healthy controls.
• Analysis utilized the Significant Latent Factor Interaction Discovery and Exploration (SLIDE) machine learning framework.
• SLIDE infers latent factors with statistical guarantees for identifiability and inference.

Main Results:

• Distinct differences in molecular signatures were observed between adult and pediatric LS.
• SLIDE identified cell type-specific determinants of LS related to age and disease severity.
• Shared signaling mechanisms between LS and SSc were revealed, alongside pediatric-specific onset differences.

Conclusions:

• Single-cell transcriptomics and SLIDE provide deep insights into LS pathophysiology.
• Age and severity-specific cellular drivers and shared signaling pathways with SSc are identified.
• These findings can stratify LS subtypes and inform therapeutic strategies.