Psoriatic arthritis (PsA) is distinctive amongst the inflammatory/autoimmune joint diseases in that its onset is commonly preceded by cutaneous psoriasis (PsC). There is a major unmet need for predictive biomarkers to determine which of the ~25% of psoriasis patients will develop PsA. Moreover, PsC and PsA exhibit significant life-threatening co-morbidity, notably from cardiovascular disease. Over the past eight years, we have collected 634 PsA patients at Michigan, 545 of whom have already been subjected to genome-wide association studies (GWAS). The International Psoriatic Arthritis Research Team (IPART) has collected DNA samples from 1,215 PsA patients, 1,062 of which have already been subjected to GWAS. Essentially all of these PsA samples already have extensive clinical follow-up (mean 6.7 years). Meta-analysis of existing GWAS and Immunochip data for psoriasis has increased the number of known European-origin psoriasis loci to at least 32, and our recently completed GWAS of 1,442 PsA cases vs. 1,433 normal controls reveals a strong MHC Class I / III association signal distinct from HLA-Cw6 as well as genome- wide significance for multiple non-MHC loci including IL12B, TNFAIP3, TNIP1, and TYK2, and TRAF3IP2 . However, these signals account for only a relatively small fraction of the heritability of PsA, likely due a least in part to the existence of rare disease-predisposing variants. Therefore, to further dissec the genetics and the biology of, we propose the following specific aims: (1) To maintain and expand our longitudinal clinical resource by (a) supporting critical core elements of the current IPART resource, (b) expanding the Michigan longitudinal cohort under the IPART protocol and (c) utilizing social networking to increase sample size via patient self-report;and (d) validating this resource in IPART subjects. (2) To identify rare genetic susceptibility variants for PsA and PsC, making use of an innovative exome variation microarray developed from 1000 Genomes Project sequencing data to genotype 4,450 PsA cases, 3,600 PsC cases, and 11,800 normal controls. (3) To develop biomarkers for PsA development, disease subtypes, drug responsiveness, and co-morbidities in PsV patients. This will be accomplished by RNA isolation and RNASeq transcriptome analysis of (a) blood samples stored at study entry, which will be paired with additional blood and skin samples from incident PsA cases at the onset of PsA development;(b) a cross- sectional sample of blood and skin from 70 additional definite PsC cases and 70 definite PsA cases;and (c) correlation of genetic and genomic data with (i) physician-assessed and patient-reported responses to biologics targeting the TNF and IL-23/IL-17 axes, (ii) axial vs. peripheral PsA and nail involvement, and (iii) systemic co-morbidities including obesity and cardiovascular disease.

Public Health Relevance

PsA is a major health problem in the United States. The mechanisms that predispose patients to PsA vs. PsC are unknown. The proposed research will utilize the power of genome-wide association studies, transcriptome analysis, and the largest longitudinal resource of PsA in the world to address a major gap in our mechanistic understanding of the causes of PsA and its associated co-morbidities. The results of this research are also likely to be relevant to other autoimmune diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR063611-03
Application #
8712139
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Cibotti, Ricardo
Project Start
2012-09-12
Project End
2017-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Dermatology
Type
Schools of Medicine
DUNS #
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Patrick, Matthew T; Stuart, Philip E; Raja, Kalpana et al. (2018) Genetic signature to provide robust risk assessment of psoriatic arthritis development in psoriasis patients. Nat Commun 9:4178
Tsoi, Lam C; Yang, Jingjing; Liang, Yun et al. (2018) Transcriptional determinants of individualized inflammatory responses at anatomically separate sites. J Allergy Clin Immunol 141:805-808
Patrick, Matthew T; Raja, Kalpana; Miller, Keylonnie et al. (2018) Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach. J Invest Dermatol :
Tsoi, Lam C; Patrick, Matthew T; Elder, James T (2018) Research Techniques Made Simple: Using Genome-Wide Association Studies to Understand Complex Cutaneous Disorders. J Invest Dermatol 138:e23-e29
Eder, Lihi; Harvey, Paula; Chandran, Vinod et al. (2018) Gaps in Diagnosis and Treatment of Cardiovascular Risk Factors in Patients with Psoriatic Disease: An International Multicenter Study. J Rheumatol 45:378-384
Sarkar, Mrinal K; Hile, Grace A; Tsoi, Lam C et al. (2018) Photosensitivity and type I IFN responses in cutaneous lupus are driven by epidermal-derived interferon kappa. Ann Rheum Dis 77:1653-1664
Yu, Ning; Lambert, Sylviane; Bornstein, Joshua et al. (2018) The Act1 D10N missense variant impairs CD40 signaling in human B-cells. Genes Immun :
Swindell, William R; Beamer, Maria A; Sarkar, Mrinal K et al. (2018) RNA-Seq Analysis of IL-1B and IL-36 Responses in Epidermal Keratinocytes Identifies a Shared MyD88-Dependent Gene Signature. Front Immunol 9:80
Enerbäck, C; Sandin, C; Lambert, S et al. (2018) The psoriasis-protective TYK2 I684S variant impairs IL-12 stimulated pSTAT4 response in skin-homing CD4+ and CD8+ memory T-cells. Sci Rep 8:7043
Raja, Kalpana; Patrick, Matthew; Elder, James T et al. (2017) Machine learning workflow to enhance predictions of Adverse Drug Reactions (ADRs) through drug-gene interactions: application to drugs for cutaneous diseases. Sci Rep 7:3690

Showing the most recent 10 out of 38 publications