Purpose: Variants in the ABCA4 gene are causal for a variety of retinal dystrophy phenotypes, including Stargardt disease (STGD1). However, 15% of patients who present with symptoms compatible with STGD1/ABCA4 disease do not have identifiable causal ABCA4 variants. We hypothesized that a case-control collapsing analysis in ABCA4-negative patients with compatible symptoms would provide an objective measure to identify additional disease genes.
Methods: We performed a genome-wide enrichment analysis of "qualifying variants"-ultrarare variants predicted to impact protein function-in protein-coding genes in 79 unrelated cases and 9028 unrelated controls.
Results: Despite modest sample size, two known retinal dystrophy genes, PRPH2 and CRX, achieved study-wide significance (p < 1.33 × 10-6) under a dominant disease model, and eight additional known retinal dystrophy genes achieved nominal significance (p < 0.05). Across these ten genes, the excess of qualifying variants explained up to 36.8% of affected individuals. Furthermore, under a recessive model, the cone-rod dystrophy gene CERKL approached study-wide significance.
Conclusion: Our results indicate that case-control collapsing analyses can efficiently identify pathogenic variants in genes in non-ABCA4 retinal dystrophies. The genome-wide collapsing analysis framework is an objective discovery method particularly suitable in settings with overlapping disease phenotypes.
Keywords: ABCA4 disease; collapsing analysis; exome sequencing; retinal dystrophy.