Genetic signature to provide robust risk assessment of psoriatic arthritis development in psoriasis patients

Matthew T. Patrick, Philip E. Stuart, Kalpana Raja, Johann E. Gudjonsson, Trilokraj Tejasvi, Jingjing Yang, Vinod Chandran, Sayantan Das, Kristina Callis-Duffin, Eva Ellinghaus, Charlotta Enerbäck, Tõnu Esko, Andre Franke, Hyun M. Kang, Gerald G. Krueger, Henry W. Lim, Proton Rahman, Cheryl F. Rosen, Stephan Weidinger, Michael Weichenthal, Xiaoquan Wen, John J. Voorhees, Gonçalo R. Abecasis, Dafna D. Gladman, Rajan P. Nair, James T. Elder and Lam C. Tsoi ()
Additional contact information
Matthew T. Patrick: University of Michigan Medical School
Philip E. Stuart: University of Michigan Medical School
Kalpana Raja: University of Michigan Medical School
Johann E. Gudjonsson: University of Michigan Medical School
Trilokraj Tejasvi: University of Michigan Medical School
Jingjing Yang: Center for Statistical Genetics, University of Michigan
Vinod Chandran: Division of Rheumatology, University of Toronto
Sayantan Das: Center for Statistical Genetics, University of Michigan
Kristina Callis-Duffin: University of Utah
Eva Ellinghaus: Christian-Albrechts-University of Kiel
Charlotta Enerbäck: Linköping University
Tõnu Esko: University of Tartu
Andre Franke: Christian-Albrechts-University of Kiel
Hyun M. Kang: Center for Statistical Genetics, University of Michigan
Gerald G. Krueger: University of Utah
Henry W. Lim: Department of Dermatology, Henry Ford Hospital
Proton Rahman: Memorial University
Cheryl F. Rosen: Division of Dermatology, Toronto Western Hospital, University of Toronto
Stephan Weidinger: University Medical Center Schleswig-Holstein
Michael Weichenthal: University Medical Center Schleswig-Holstein
Xiaoquan Wen: Center for Statistical Genetics, University of Michigan
John J. Voorhees: University of Michigan Medical School
Gonçalo R. Abecasis: Center for Statistical Genetics, University of Michigan
Dafna D. Gladman: Division of Rheumatology, University of Toronto
Rajan P. Nair: University of Michigan Medical School
James T. Elder: University of Michigan Medical School
Lam C. Tsoi: University of Michigan Medical School

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract Psoriatic arthritis (PsA) is a complex chronic musculoskeletal condition that occurs in ~30% of psoriasis patients. Currently, no systematic strategy is available that utilizes the differences in genetic architecture between PsA and cutaneous-only psoriasis (PsC) to assess PsA risk before symptoms appear. Here, we introduce a computational pipeline for predicting PsA among psoriasis patients using data from six cohorts with >7000 genotyped PsA and PsC patients. We identify 9 new loci for psoriasis or its subtypes and achieve 0.82 area under the receiver operator curve in distinguishing PsA vs. PsC when using 200 genetic markers. Among the top 5% of our PsA prediction we achieve >90% precision with 100% specificity and 16% recall for predicting PsA among psoriatic patients, using conditional inference forest or shrinkage discriminant analysis. Combining statistical and machine-learning techniques, we show that the underlying genetic differences between psoriasis subtypes can be used for individualized subtype risk assessment.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06672-6

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DOI: 10.1038/s41467-018-06672-6

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