Spondyloarthropathies (SpA), including ankylosing spondylitis (AS) and psoriatic arthritis (PsA), have been shown to have a substantial genetic predisposition based on heritability estimates derived from family studies and genome-wide association studies (GWAS). GWAS have uncovered numerous genetic loci associated with susceptibility to SpA, with significant associations to human leukocyte antigen (HLA) genes, which are major genetic risk factors for both AS and PsA. Specific loci differentiating PsA from cutaneous-only psoriasis have been identified, though these remain limited. Further research with larger sample sizes is necessary to identify more PsA-specific genetic markers. Current research focuses on translating these genetic insights into clinical applications. For example, polygenic risk scores are showing promise for the classification of disease risk and diagnosis and future research should focus on refining these risk assessment tools to improve clinical outcomes for individuals with SpA. Addressing these challenges will help integrate genetic testing into patients care and impact clinical practice.
Rheumatic diseases, those that affect the musculoskeletal system, cause significant morbidity. Among risk factors of these diseases is a significant genetic component. Recent advances in high-throughput omics techniques now allow a comprehensive profiling of patients at a genetic level through genome-wide association studies. Without functional interpretation of variants identified through these studies, clinical insight remains limited. Strategies include statistical fine-mapping that refine the list of variants in loci associated with disease, whilst colocalization techniques attempt to attribute function to variants that overlap a genetically active chromatin annotation. Functional validation using genome editing techniques can be used to further refine genetic signals and identify key pathways in cell types relevant to rheumatic disease biology. Insight gained from the combination of genetic studies and functional validation can be used to improve precision medicine in rheumatic diseases by allowing risk prediction and drug repositioning.