Multicytokine-based transcriptome-wide association study for 7 inflammatory skin disorders identifies candidate causal genes in keratinocytes

Haihan Zhang; Matthew T Patrick; Mrinal K Sarkar; Rachael Bogle; Qinmengge Li; Ranjitha Uppala; Bethany E Perez White; Lynn Petukhova; Nick Dand; Philip E Stuart; Angela M Christiano; Michael A Simpson; Jonathan N Barker; Stephan Weidinger; Robert L Modlin; Regina C Betz; Dinesh Khanna; John Varga; J Michelle Kahlenberg; Kevin He; James T Elder; Xiang Zhou; Johann E Gudjonsson; Lam C Tsoi

doi:10.1016/j.jaci.2026.05.013

Multicytokine-based transcriptome-wide association study for 7 inflammatory skin disorders identifies candidate causal genes in keratinocytes

J Allergy Clin Immunol. 2026 May 26:S0091-6749(26)00368-4. doi: 10.1016/j.jaci.2026.05.013. Online ahead of print.

Authors

Haihan Zhang¹, Matthew T Patrick², Mrinal K Sarkar², Rachael Bogle², Qinmengge Li¹, Ranjitha Uppala², Bethany E Perez White³, Lynn Petukhova⁴, Nick Dand⁵, Philip E Stuart², Angela M Christiano⁶, Michael A Simpson⁵, Jonathan N Barker⁷, Stephan Weidinger⁸, Robert L Modlin⁹, Regina C Betz¹⁰, Dinesh Khanna¹¹, John Varga¹¹, J Michelle Kahlenberg¹², Kevin He¹, James T Elder¹³, Xiang Zhou¹⁴, Johann E Gudjonsson¹⁵, Lam C Tsoi¹⁶

Affiliations

¹ Department of Biostatistics, University of Michigan, Ann Arbor, Mich.
² Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich.
³ Department of Dermatology, Feinberg School of Medicine, Northwestern University, Chicago, Ill.
⁴ Department of Dermatology, Grossman School of Medicine, New York University, New York, New York.
⁵ Department of Medical and Molecular Genetics, School of Basic & Medical Biosciences, King's College London, London, United Kingdom.
⁶ Department of Dermatology, Columbia University, New York, New York.
⁷ St John's Institute of Dermatology, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.
⁸ Department of Dermatology, University Hospital, Schleswig-Holstein, Christian-Albrechts-University, Kiel, Germany.
⁹ Department of Internal Medicine, Division of Dermatology, University of California, Los Angeles, Calif.
¹⁰ Institute of Human Genetics, University of Bonn, Medical Faculty & University Hospital Bonn, Bonn, Germany.
¹¹ Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Mich.
¹² Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Mich; Taubman Medical Research Institute, University of Michigan Medical School, Ann Arbor, Mich.
¹³ Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Ann Arbor Veterans Affairs Hospital, Ann Arbor, Mich.
¹⁴ Department of Statistics and Data Science, Yale University, New Haven, Conn.
¹⁵ Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Mich; Ann Arbor Veterans Affairs Hospital, Ann Arbor, Mich.
¹⁶ Department of Biostatistics, University of Michigan, Ann Arbor, Mich; Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Mich. Electronic address: alextsoi@umich.edu.

PMID: 42203178
DOI: 10.1016/j.jaci.2026.05.013

Abstract

Background: Transcriptome-wide association studies (TWAS) identify genetically regulated expression (GReX) components and can pinpoint causal genes in genome-wide association studies but are often limited by a single-cell context.

Objective: We hypothesized that modeling GReX across multiple conditions could enhance power to identify causal genes for complex inflammatory diseases.

Methods: We conducted TWAS on 400 transcriptomes under 8 proinflammatory cytokine stimulations in keratinocytes, modeling GReX for 18,599 genes against genome-wide association studies from 7 inflammatory skin diseases: atopic dermatitis, psoriasis, acne, alopecia areata, systemic sclerosis, systemic lupus erythematosus, and vitiligo.

Results: Our TWAS identified 274 loci from the 7 diseases that harbor a single significant TWAS gene association. We nominated causal genes and their associated proinflammatory cytokine stimuli, including ERAP2 for psoriasis with IL-17A + TNF-α stimulation; WNT10A for acne with IFN-γ stimulation; and RAET1L, MAP3K11, and ITGAM for alopecia areata, acne, and systemic lupus erythematosus, respectively, with TNF stimulation. Notably, our TWAS-identified genes showed overwhelming evidence of colocalization with genome-wide association study signals (P = 1.03 × 10^-15), and our method successfully captured >85% of all genes with colocalizing expression quantitative trait loci. Single-cell-resolution spatial profiling further demonstrated the modulation of TWAS signals in keratinocytes by close proximity to TNF/IL-17-expressing cells in psoriatic skin.

Conclusion: Modeling gene expression across relevant cellular states substantially improves the power and resolution of TWAS.

Keywords: TWAS; cytokine stimulation; inflammatory skin disorder; keratinocyte.