Human Genetics and Genomics AdvancesGenetic & Genomic MedicinePeer-reviewed journal article
Transcriptome-wide analyses delineate the genetic architecture of expression variation in atopic dermatitis
Charalabos AntonatosiD, Dimitra Mitsoudi, Alexandros PontikasiD, Adam Akritidis, Panagiotis XiropotamosiD, Georgios K. GeorgakilasiD, Sophia GeorgiouiD, Aikaterini TsiogkaiD, Stamatios GregoriouiD, Katerina GrafanakiiD, Yiannis VasilopoulosiD
Abstract
Genome-wide association studies (GWASs) for atopic dermatitis (AD) have uncovered 81 risk loci in European participants, however translating these findings into functional and therapeutic insights remains challenging. We conducted a transcriptome-wide association study (TWAS) in AD leveraging cis-eQTL data from 3 central AD tissues and the latest GWAS of AD in Europeans. We implemented the OTTERS pipeline that combines polygenic risk score (PRS) techniques accommodating diverse assumptions in the architecture of gene regulation. We also used differential expression datasets and co-expression networks to characterize the transcriptomic landscape of AD. We identified 176 gene-tissue associations covering 126 unique genes (53 novel). Most TWAS risk genes were identified by adaptive PRS frameworks, with non-significant differences compared to clumping and thresholding approaches. The novel TWAS risk genes were enriched in allergic reactions (e.g., AQP7, AFF4), skin barrier integrity (e.g., ACER3) and inflammatory pathways (e.g., TAPBPL). By integrating co-expression networks of lesional AD skin, we identified 16 hub genes previously identified as TWAS risk genes (6 novel) that orchestrate inflammatory responses (e.g., HSPA4) and keratinization (e.g., LCE3E, LCE3D), serving as potential drug targets through drug-gene interactions. Collectively, our findings provide additional risk genes for AD with potential implications in therapeutic approaches.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- approach: matrix factorization
- Citations
- 5
- FWCI
- 4.75
- Field percentile
- top 6%
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