Disease Expression in Autosomal Recessive Retinal Dystrophy Associated With Mutations in the DRAM2 Gene

Purpose: To determine the disease course of retinal dystrophy caused by recessive variants in the DRAM2 (damage-regulated autophagy modulator 2) gene. Methods: Sixteen individuals with DRAM2-retinopathy were examined (six families; age range, 19–56 years, includes one pre-symptomatic case). The change in visual acuity over time was studied, and electrophysiology (n = 6), retina-tracking perimetry (n = 1), fundus autofluorescence (FAF) imaging (n = 6), and optical coherence tomography (OCT; n = 12) were performed. Results: All symptomatic patients presented with central visual loss (15/15) unaccompanied either by nyctalopia or light-hypersensitivity; most (11/15) developed symptoms in the third decade of life. A granular macular appearance, often with associated white/yellow dots, was an early fundoscopic feature. There was an ill-defined ring of hyperautofluorescence on FAF. Optical coherence tomography revealed loss of the ellipsoid zone perifoveally in a 19-year-old pre-symptomatic individual. The central atrophic area enlarged over time and fundoscopy showed peripheral degeneration in seven of the nine individuals that were examined ≥10 years after becoming symptomatic; some of these subjects developed nyctalopia and light hypersensitivity. Electrophysiology revealed generalized retinal dysfunction in three of the five individuals that were tested ≥10 years after becoming symptomatic. Conclusions: Patients with DRAM2-retinopathy are typically asymptomatic in the first two decades of life and present with central visual loss and a maculopathy. A faint hyperautofluorescent ring on FAF can be a suggestive feature. The retinal periphery is frequently affected later in the disease process. Photoreceptor degeneration is likely to be the primary event and future studies on DRAM2-retinopathy are expected to provide important insights into retinal autophagy

The exhaustive genomic scan approach, with an application to rare-variant association analysis

Region-based genome-wide scans are usually performed by use of a priori chosen analysis regions. Such an approach will likely miss the region comprising the strongest signal and, thus, may result in increased type II error rates and decreased power. Here, we propose a genomic exhaustive scan approach that analyzes all possible subsequences and does not rely on a prior definition of the analysis regions. As a prime instance, we present a computationally ultraefficient implementation using the rare-variant collapsing test for phenotypic association, the genomic exhaustive collapsing scan (GECS). Our implementation allows for the identification of regions comprising the strongest signals in large, genome-wide rare-variant association studies while controlling the family-wise error rate via permutation. Application of GECS to two genomic data sets revealed several novel significantly associated regions for age-related macular degeneration and for schizophrenia. Our approach also offers a high potential to improve genome-wide scans for selection, methylation, and other analyses