Purpose of Review Whole exome sequencing (WES) and whole-genome sequencing (WGS) are frontline approaches for the genetic diagnosis of rare diseases. However, WES/WGS fails in up to 75% of cases. Transcriptomics via RNA-sequencing (RNA-Seq) is a novel approach that aims to increase the diagnostic yield in rare diseases. Recent Findings Recent publications focus on the success of RNA-Seq for increasing diagnosis rates in WES/WGS-negative patients in up to 36% of cases, across a range of different diseases, sample sizes, and tissue types. Summary RNA-Seq is beneficial for aiding prioritisation of causative variants currently not detected or often overlooked by WES/WGS alone. An improvement in diagnostic yields has been demonstrated using multiple source tissues, with muscle and fibroblasts being the most representative, but the more accessible blood still demonstrating diagnostic success, particularly in neuromuscular disorders. The introduction of RNA-Seq to the genetic diagnosis toolbox promises to be a useful complementary tool to WES/WGS for improving genetic diagnosis in patients with rare disease.

Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of patients leading to ‘trial and error’ drug management approaches, adverse reactions and increasing healthcare costs. Robust and well-validated biomarker identification, and subsequent development of sensitive and specific assays, would facilitate the implementation of a stratified approach into clinical care. This review will summarise potential genetic biomarkers for TNF-i (adalimumab, etanercept and infliximab) response that have been reported to date. It will also comment upon the importance of managing clinical confounders when understanding drug response prediction. Variants in multiple gene regions including TNF-A, FCGR2A, TNFAIP3, TNFR1/TNFR1A/TNFRSF1A, TRAIL-R1/TNFRSF10A, FCGR3A have been reported to correlate with TNF-i response at various levels of statistical significance in patients with PsA. However, results were often from heterogenous and underpowered cohorts and none are currently implemented into clinical practice. External validation of genetic biomarkers in large, well-documented cohorts is required, and assessment of the predictive value of combining multiple genetic biomarkers with clinical measures is essential to clinically embed pharmacogenomics into PsA drug management.

Suboptimal treatment adherence has been reported in patients with arthritic diseases; is associated with psychological factors, including anxiety; and correlates with future treatment response.1,2During the coronavirus disease 2019 (COVID-19) pandemic, patients who identified as clinically extremely vulnerable, including people prescribed ≥ 2 immunosuppressives, were advised to shield and continue treatment unless they developed COVID-19 symptoms.