Integrated Single-Cell RNA Sequencing and Proteome-Wide Mendelian Randomization Identifies Therapeutic Targets for Psoriasis and Associated Complications

Ping Zheng*, Yanyun Cao, Ao Wang, Ke Yi*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

Background:
To identify new targets for protein-based treatments in psoriasis and evaluate the possible negative impacts of these druggable proteins.

Methods:
We carried out an extensive analysis of the entire set of proteins in the blood (proteome-wide) to determine if there are causal links between certain blood proteins and the likelihood of developing psoriasis. The proteins were selected from the UK Biobank Pharma Proteomics Project (UKBPPP) database, which includes genetic data for 2,940 different blood proteins. We obtained the cis-expression quantitative trait locus (cis-eQTL) of druggable genes from eQTLGen Consortium as exposure and the genome-wide association study (GWAS) of psoriasis.

Results:
Our research discovered a strong genetic link between plasma APOF, ATP6V1G2, IFNLR1, CRELD1, PRSS8, and TNF proteins and a higher chance of having psoriasis. These proteins share genetic variations associated with psoriasis (PPH3+PPH4> 0.8). The ROC curves derived from these protein quantity trait loci (pQTLs) demonstrate that they can distinguish between individuals with psoriasis and those without. The druggable gene analysis showed that simvastatin is related to TNF based on the Drug SIGnatures DataBase webtool.

Conclusion:
Our study has explored the causal relationships between six blood proteins and psoriasis, offering a detailed insight into potential therapeutic targets. Among them, simvastatin might have an effect on psoriasis via TNF.
Original languageEnglish
Pages (from-to)501-511
Number of pages11
JournalPsoriasis: Targets and Therapy
Volume15
DOIs
Publication statusPublished - 10 Oct 2025

User-Defined Keywords

  • PheWAS
  • Complication
  • proteome-wide Mendelian randomization
  • Psoriasis
  • Single cell rna sequencing

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