Multi-cytokine based TWAS for seven inflammatory skin disorders identify candidate causal genes in keratinocytes.
Source: PubMed, NCBI / U.S. National Library of Medicine
Transcriptome-wide association studies (TWAS) identify genetically regulated expression (GReX) components and can pinpoint causal genes in GWAS, but are often limited by using a single cellular context. We hypothesized that modeling GReX across multiple conditions could enhance power to identify causal genes for complex inflammatory diseases. We conducted TWAS on 400 transcriptomes under eight pro-inflammatory cytokine stimulations in keratinocytes, modeling GReX for 18,599 genes against GWAS from seven inflammatory skin diseases: atopic dermatitis, psoriasis, acne, alopecia areata, systemic sclerosis, SLE, and vitiligo. Our TWAS identified 274 loci from the seven diseases that harbor a single significant TWAS gene association. We nominated causal genes and their associated pro-inflammatory cytokine stimuli, including ERAP2 for psoriasis with IL-17A+TNF stimulation; WNT10A for acne with IFNγ stimulation; RAET1L, MAP3K11, and ITGAM for alopecia areata, acne, and SLE, respectively, with TNF stimulation. Notably, our TWAS-identified genes showed overwhelming evidence of colocalization with GWAS signals (p = 1.03×10), and our method successfully captured over 85% of all genes with colocalizing eQTLs. Using single cell resolution spatial profiling, we further demonstrated the modulation of TWAS signals in keratinocytes by close proximity to TNF/IL-17 expressing cells in psoriatic skin. Modeling gene expression across relevant cellular states substantially improves the p
Abstract
Transcriptome-wide association studies (TWAS) identify genetically regulated expression (GReX) components and can pinpoint causal genes in GWAS, but are often limited by using a single cellular context. We hypothesized that modeling GReX across multiple conditions could enhance power to identify causal genes for complex inflammatory diseases. We conducted TWAS on 400 transcriptomes under eight pro-inflammatory cytokine stimulations in keratinocytes, modeling GReX for 18,599 genes against GWAS from seven inflammatory skin diseases: atopic dermatitis, psoriasis, acne, alopecia areata, systemic sclerosis, SLE, and vitiligo. Our TWAS identified 274 loci from the seven diseases that harbor a single significant TWAS gene association. We nominated causal genes and their associated pro-inflammatory cytokine stimuli, including ERAP2 for psoriasis with IL-17A+TNF stimulation; WNT10A for acne with IFNγ stimulation; RAET1L, MAP3K11, and ITGAM for alopecia areata, acne, and SLE, respectively, with TNF stimulation. Notably, our TWAS-identified genes showed overwhelming evidence of colocalization with GWAS signals (p = 1.03×10), and our method successfully captured over 85% of all genes with colocalizing eQTLs. Using single cell resolution spatial profiling, we further demonstrated the modulation of TWAS signals in keratinocytes by close proximity to TNF/IL-17 expressing cells in psoriatic skin. Modeling gene expression across relevant cellular states substantially improves the power and resolution of TWAS. Our findings indicate that genetic signals for complex skin conditions shape inflammatory responses in the epithelium and provide a roadmap of how susceptibility loci modulate shared and unique cytokine responses in keratinocytes for different inflammatory skin diseases.