Adult-onset foveomacular vitelliform dystrophy: epidemiology, pathophysiology, imaging, and prognosis.
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ABSTRACT:
SUBMITTER: Nipp GE
PROVIDER: S-EPMC11182240 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature
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Adult-onset foveomacular vitelliform dystrophy: epidemiology, pathophysiology, imaging, and prognosis.
Nipp Grace E GE Lee Terry T Sarici Kubra K Malek Goldis G Hadziahmetovic Majda M
Frontiers in ophthalmology 20230810
Adult-onset foveomacular dystrophy (AOFVD) is a retinal pattern dystrophy that may affect up to 1 in 7,400 individuals. There is much that is unknown regarding this disease's epidemiology, risk factors for development, and rate of progression through its four stages. Advancements in retinal imaging over the past 15 years have enabled improved characterization of the different stages of AOFVD. These imaging advancements also offer new ways of differentiating AOFVD from phenotypically similar reti ...[more]
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Project description:PurposeAdult-onset foveomacular vitelliform dystrophy (AFVD) shares phenotypic similarities with age-related macular degeneration (AMD). The genetic factors associated with AFVD are unknown in >80% of cases. This study evaluated the association of known AMD genetic risk variants with AFVD and compared systemic complement activation in these conditions.MethodsClinical, imaging, and genetic data were collected from 50 patients with AFVD (men/women = 25/25, mean age ± SD 73 ± 10 years), 917 patients with AMD (men/women = 377/540, mean age ± SD 77 ± 9 years), and 432 unaffected healthy controls (men/women = 202/230, mean age ± SD 71 ± 8 years). Genotyping focused on 52 single nucleotide polymorphisms (SNPs) linked to AMD. Weighted genetic risk scores (GRS) for 19 complement system associated variants, 7 lipid metabolism associated variants, the remaining 26 variants (other pathways GRS), and for all 52 variants (global score) were derived and correlated with phenotype.ResultsOf the 52 SNPs evaluated, CFH (rs570618) and C2/CFB/SKIV2L (rs116503776 and rs114254831) were associated with AFVD compared with healthy controls (odds ratio [OR] = 2.73, 95% confidence interval [CI] = 1.32-5.73, P = 0.01; OR = 0.31, 95% CI = 0.14-0.71, P = 0.0036; and OR = 0.41, 95% CI = 0.22-0.74, P = 0.0025, respectively). MIR6130/RORB (rs10781182) was negatively associated with AFVD compared with the healthy controls (OR = 0.13, CI = 0.06-0.25, P < 0.0001) and AMD (OR = 0.19, CI = 0.10-0.34, P < 0.0001). Regression analysis showed complement GRS was positively associated with AFVD compared with controls (OR = 1.42, 95% CI = 1.04-1.95, P = 0.03), whereas the other pathways' GRS was negatively associated (OR = 0.46, 95% CI = 0.21-0.98, P = 0.04). AMD was positively associated with the complement score, global score, and ARMS2/HTRA1 compared with controls.ConclusionsNon-monogenic AFVD is associated with AMD risk alleles in the complement cascade, but not in other pathways. Further research is needed to explore complement inhibition for AFVD.
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Project description:PurposeIn patients diagnosed with Best vitelliform macular dystrophy (BVMD), quantitative fundus autofluorescence (qAF), near-infrared fundus autofluorescence (NIR-AF), and spectral-domain optical coherence tomography (SD-OCT) were used to elucidate pathogenic mechanisms.MethodsFourteen patients heterozygous for BEST1 mutations were recruited. qAF was analyzed using short-wavelength fundus autofluorescence (SW-AF) images. Mean gray levels (GL) were determined in nonlesion areas (7 to 9° eccentricity) and adjusted by GL measured in an internal fluorescent reference. NIR-AF images (787 nm; sensitivity of 96) were captured and saved in non-normalized mode. Horizontal SD-OCT images also were acquired and BVMD was staged according to the OCT findings.ResultsIn the pre-vitelliform stage, NIR-AF imaging revealed an area of reduced fluorescence, whereas in the vitelliruptive stage, puncta of elevated NIR-AF signal were present. In both SW-AF and NIR-AF images, the vitelliform lesion in the atrophic stage was marked by reduced signal. At all stages of BVMD, nonlesion qAF was within the 95% confidence intervals for healthy eyes. Similarly, the NIR-AF intensity measurements outside the vitelliform lesion were comparable to the healthy control eye. SD-OCT scans revealed a fluid-filled detachment between the ellipsoid zone and the hyperreflectivity band attributable to RPE/Bruch's membrane.ConclusionsNIR-AF imaging can identify the pre-vitelliform stage of BVMD. Mutations in BEST1 are not associated with increased levels of SW-AF outside the vitelliform lesion. Elevated SW-AF within the fluid-filled lesion likely reflects the inability of RPE to phagocytose outer segments due to separation of RPE from photoreceptor cells, together with progressive photoreceptor cell impairment.
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Project description:Best Vitelliform Macular Dystrophy (BVMD) is a dominantly inherited retinal disease caused by dominant variants in the BEST1 gene. The original classification of BVMD is based on biomicroscopy and color fundus photography (CFP); however, advancements in retinal imaging provided unique structural, vascular, and functional data and novel insights on disease pathogenesis. Quantitative fundus autofluorescence studies informed us that lipofuscin accumulation, the hallmark of BVMD, is unlikely to be a primary effect of the genetic defect. It could be due to a lack of apposition between photoreceptors and retinal pigment epithelium in the macula with subsequent accumulation of shed outer segments over time. Optical Coherence Tomography (OCT) and adaptive optics imaging revealed that vitelliform lesions are characterized by progressive changes in the cone mosaic corresponding to a thinning of the outer nuclear layer and then disruption of the ellipsoid zone, which are associated with a decreased sensitivity and visual acuity. Therefore, an OCT staging system based on lesion composition, thus reflecting disease evolution, has been recently developed. Lastly, the emerging role of OCT Angiography proved a greater prevalence of macular neovascularization, the majority of which are non-exudative and develop in late disease stages. In conclusion, effective diagnosis, staging, and clinical management of BVMD will likely require a deep understanding of the multimodal imaging features of this disease.
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