Score tests based on a finite mixture model of Markov processes under intermittent observation.

A mixture model is described, which accommodates different Markov processes governing disease progression in a finite set of latent classes. We give special attention to the setting in which individuals are examined intermittently and transition times are consequently interval censored. A score test is developed to identify genetic markers associated with class membership. Simulation studies are conducted to validate the algorithm, assess the finite sample properties of the estimators, and assess the frequency properties of the score tests. A permutation test is recommended for settings when there is concern that the asymptotic approximation to the score test is poor. An application involving progression in joint damage in psoriatic arthritis (PsA) provides illustration and identifies human leukocyte antigen markers associated with unilateral and bilateral sacroiliac damage in individuals with PsA.

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

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.

Pharmacogenetics and pharmacogenomics in psoriasis treatment: current challenges and future prospects.

INTRODUCTION: Topical, systemic, oral disease modifying, and biologic agents are part of the armamentarium to manage psoriatic disease. The choice of therapy depends upon disease severity, relevant co-morbidities and patient preference. There is great variability in patient response with these agents, and there is still no clear method of selecting the preferred therapeutic agent for efficacy or lack of adverse events. AREAS COVERED: This article will review the pharmacogenetic and pharmacogenomic targets that are currently known with respect to psoriasis vulgaris, and the most frequent co-morbidity of psoriasis, psoriatic arthritis. EXPERT OPINION: Presently, no clinically actionable biomarker exists for any therapeutic agent used to treat psoriasis or psoriatic arthritis. The lack of validated outcome measures and conflicting results of open-label studies conducted may be attributed to a multitude of issues that confound discovery. Consequently, studies have been underpowered to identify genes or genetic variants worth translating to clinical practice. In order to achieve a pharmacogenetic/pharmacogenomic signature, improvements in study design of future investigations are required, including carefully designed prospective studies. It is imperative to combine known clinical, serological, and molecular markers with consistent outcomes and an adequate health economic evaluation before they can be adopted widely in clinical practice.

Comprehensive assessment of rheumatoid arthritis susceptibility loci in a large psoriatic arthritis cohort.

OBJECTIVE: A number of rheumatoid arthritis (RA) susceptibility genes have been identified in recent years. Given the overlap in phenotypic expression of synovial joint inflammation between RA and psoriatic arthritis (PsA), the authors explored whether RA susceptibility genes are also associated with PsA. METHODS: 56 single nucleotide polymorphisms (SNPs) mapping to 41 genes previously reported as RA susceptibility loci were selected for investigation. PsA was defined as an inflammatory arthritis associated with psoriasis and subjects were recruited from the UK and Ireland. Genotyping was performed using the Sequenom MassArray platform and frequencies compared with data derived from large UK control collections. RESULTS: Significant evidence for association with susceptibility to PsA was found toa SNP mapping to the REL (rs13017599, p(trend)=5.2×10(4)) gene, while nominal evidence for association (p(trend)<0.05) was found to seven other loci including PLCL2 (rs4535211, p=1.7×10(-3)); STAT4 (rs10181656, p=3.0×10(-3)) and the AFF3, CD28, CCL21, IL2 and KIF5A loci. Interestingly, three SNPs demonstrated opposite effects to those reported for RA. CONCLUSIONS: The REL gene, a key modulator of the NFκB pathway, is associated with PsA but the allele conferring risk to RA is protective in PsA suggesting that there are fundamental differences in the aetiological mechanisms underlying these two types of inflammatory arthritis.

Gene therapy for arthritis--where do we stand?

The successful use of biologicals in the treatment of rheumatoid arthritis, psoriatic arthritis and spondyloarthritis has had a major impact on the management of these conditions. The challenge in the development of gene therapy as an alternative to these current treatments is to demonstrate that such therapy is more advantageous for patients from the therapeutic and safety points of view. Also, it will need to be demonstrated that gene therapy for the arthritides is economically feasible and that patient populations worldwide will be able to access these treatments.