Genetic diagnostic profiling in axial spondyloarthritis: a real world study

TLDR: In a clinical setting of referred back pain patients suspected to have axial SpA, genetic data was unable to use genetic data to construct a predictive model better than that based on existing clinical data.

Abstract: Objective Spondyloarthritis (SpA) is often diagnosed late in the course of the disease and improved methods for early diagnosis are required. We have tested the ability of genetic profiling to diagnose axial SpA (axSpA) as a whole group, or ankylosing spondylitis (AS) alone, in a cohort of chronic back pain patients. Methods 282 patients were recruited from centres in the United Kingdom, Germany, Taiwan, Canada, Columbia and Turkey as part of the ASAS classification criteria for axSpA study (ASAS cohort). Subjects were classified according to the ASAS axSpA criteria, and the modified New York Criteria for AS. Patients were genotyped for ~200,000 immune-mediated disease SNPs using the Illumina Immunochip. Results We first established the predictive accuracy of genetic data comparing 9,638 healthy controls and 4,428 AS cases from the homogenous International Genetics of AS (IGAS) Consortium Immunochip study which showed excellent predictive power (AUC=0.91). Genetic risk scores had lower predictive power (AUC=0.83) comparing ASAS cohort axSpA cases meeting the ASAS imaging criteria with IGAS controls. Comparing genetic risk scores showed moderate discriminatory capacity between IGAS AS and ASAS imaging positive cases (AUC 0.67±0.05), indicating that significant differences in genetic makeup exist between the cohorts. Conclusion In a clinical setting of referred back pain patients suspected to have axial SpA we were unable to use genetic data to construct a predictive model better than that based on existing clinical data. Potential confounding factors include significant heterogeneity in the ASAS cohort, possibly reflecting the disease heterogeneity of axSpA, or differences between centres in ascertainment or classification performance.