Integrated single-cell chromatin and transcriptomic analyses of human scalp identify gene-regulatory programs and critical cell types for hair and skin diseases

Single-cell RNA- and ATAC-seq analysis of human scalp biopsies characterizes the regulatory programs of heterogeneous cell types. Integration with genome-wide association studies of hair and skin diseases implicates critical cell types, transcription factors and candidate causal variants. Genome-wide association studies have identified many loci associated with hair and skin disease, but identification of causal variants requires deciphering of gene-regulatory networks in relevant cell types. We generated matched single-cell chromatin profiles and transcriptomes from scalp tissue from healthy controls and patients with alopecia areata, identifying diverse cell types of the hair follicle niche. By interrogating these datasets at multiple levels of cellular resolution, we infer 50-100% more enhancer-gene links than previous approaches and show that aggregate enhancer accessibility for highly regulated genes predicts expression. We use these gene-regulatory maps to prioritize cell types, genes and causal variants implicated in the pathobiology of androgenetic alopecia (AGA), eczema and other complex traits. AGA genome-wide association studies signals are enriched in dermal papilla regulatory regions, supporting the role of these cells as drivers of AGA pathogenesis. Finally, we train machine learning models to nominate single-nucleotide polymorphisms that affect gene expression through disruption of transcription factor binding, predicting candidate functional single-nucleotide polymorphism for AGA and eczema.

Automated summary

Single-cell RNA- and ATAC-seq analysis of human scalp biopsies identified the regulatory programs of different cell types, which were integrated with genome-wide association studies to explore the genetic basis of hair and skin diseases. This study provides valuable insights into the gene-regulatory networks in relevant cell types, contributing to the identification of causal variants and potential therapeutic targets.