Psoriasis Genomics and Pathophysiology

The U-M Psoriasis Genomics & Pathophysiology research program is a world leader in the use of molecular biology and genetic linkage and association techniques to elucidate how the immune system activates the epidermal wound healing mechanism in psoriasis, and joint destruction in psoriatic arthritis.

In 2009, our program published the first comprehensive genome-wide association scan of psoriasis, identifying seven psoriasis-susceptibility loci. In subsequent studies, we have identified more than 60 genome-wide significant psoriasis loci. Many of these loci contain genes relevant to skin immune system function and relate directly to biological treatments known to be highly effective against psoriasis.

Our laboratories are working to describe the transcriptome (the measurement of which genes are turned on and by how much) of normal vs. psoriatic skin. As well as measuring the blood transcriptomes, in order to find additional biomarkers for predicting the risk of psoriatic arthritis.

This ongoing research is combining the power of large genome-wide association studies, transcriptome analysis, and the largest collection of psoriasis-related DNA/tissue samples in the world to enhance our mechanistic understanding of the causes of psoriasis, psoriatic arthritis and associated co-morbidities.

NIH Grants:

  • Linkage Analysis of Familial Psoriasis (NIH/NIAMS 5R01AR042742; PI: Elder)
  • Genetic and Genomic Dissection of Psoriatic Arthritis (NIH/NIAMS 4R01AR063611; PI: Elder)
  • Functional Genomics of Psoriasis (NIH/NIAMS 4R01AR065183; PI: Elder) 


James T. Elder, MD, PhD

James T. Elder, MD, PhD

Kirk D. Wuepper Professor of Molecular Genetic Dermatology
Director, Training Program in Cell and Molecular Dermatology
 Lam (Alex) C. Tsoi, MS, PhD

Lam C. (Alex) Tsoi, PhD

Assistant Professor of Dermatology, Medical School
Assistant Professor of Computational Medicine and Bioinformatics, Medical School
Research Assistant Professor, Mary H Weiser Food Allergy Center
Research Assistant Professor of Biostatistics, School of Public Health