Iris Heid, Gonçalo Abecasis, Sudha Iyengar and colleagues report the results of a large genome-wide association meta-analysis of macular degeneration based on over 43,000 subjects. They identify 16 new risk loci, including some very rare coding variants. Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10−8) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10−10). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these require in-depth and time-consuming analysis of fundus images. Herein, we present an automated computer-based classification algorithm. Algorithm development for AMD classification based on a large collection of color fundus images. Validation is performed on a cross-sectional, population-based study. We included 120 656 manually graded color fundus images from 3654 Age-Related Eye Disease Study (AREDS) participants. AREDS participants were >55 years of age, and non-AMD sight-threatening diseases were excluded at recruitment. In addition, performance of our algorithm was evaluated in 5555 fundus images from the population-based Kooperative Gesundheitsforschung in der Region Augsburg (KORA; Cooperative Health Research in the Region of Augsburg) study. We defined 13 classes (9 AREDS steps, 3 late AMD stages, and 1 for ungradable images) and trained several convolution deep learning architectures. An ensemble of network architectures improved prediction accuracy. An independent dataset was used to evaluate the performance of our algorithm in a population-based study. κ Statistics and accuracy to evaluate the concordance between predicted and expert human grader classification. A network ensemble of 6 different neural net architectures predicted the 13 classes in the AREDS test set with a quadratic weighted κ of 92% (95% confidence interval, 89%-92%) and an overall accuracy of 63.3%. In the independent KORA dataset, images wrongly classified as AMD were mainly the result of a macular reflex observed in young individuals. By restricting the KORA analysis to individuals >55 years of age and prior exclusion of other retinopathies, the weighted and unweighted κ increased to 50% and 63%, respectively. Importantly, the algorithm detected 84.2% of all fundus images with definite signs of early or late AMD. Overall, 94.3% of healthy fundus images were classified correctly. Our deep learning algoritm revealed a weighted κ outperforming human graders in the AREDS study and is suitable to classify AMD fundus images in other datasets using individuals >55 years of age.

In response to cell swelling, volume-regulated anion channels (VRACs) participate in a process known as regulatory volume decrease (RVD). Only recently, first insight into the molecular identity of mammalian VRACs was obtained by the discovery of the leucine-rich repeats containing 8A (LRRC8A) gene. Here, we show that bestrophin 1 (BEST1) but not LRRC8A is crucial for volume regulation in human retinal pigment epithelium (RPE) cells. Whole-cell patch-clamp recordings in RPE derived from human-induced pluripotent stem cells (hiPSC) exhibit an outwardly rectifying chloride current with characteristic functional properties of VRACs. This current is severely reduced in hiPSC-RPE cells derived from macular dystrophy patients with pathologic BEST1 mutations. Disruption of the orthologous mouse gene (Best1^−/−) does not result in obvious retinal pathology but leads to a severe subfertility phenotype in agreement with minor endogenous expression of Best1 in murine RPE but highly abundant expression in mouse testis. Sperm from Best1^−/− mice showed reduced motility and abnormal sperm morphology, indicating an inability in RVD. Together, our data suggest that the molecular identity of VRACs is more complex—that is, instead of a single ubiquitous channel, VRACs could be formed by cell type- or tissue-specific subunit composition. Our findings provide the basis to further examine VRAC diversity in normal and diseased cell physiology, which is key to exploring novel therapeutic approaches in VRAC-associated pathologies. Significance First insight into the molecular identity of volume-regulated anion channel (VRAC) emerged only recently by demonstrating a role for leucine-rich repeats containing 8A (LRRC8A) in channel activity. Our results now expand on VRAC biology, suggesting a model where VRAC subunit composition is cell type- or tissue-specific rather than a single ubiquitous channel formed solely by LRRC8A. Here, we show that bestrophin 1 (BEST1), but not LRCC8A, is crucial in cell volume regulation in retinal pigment epithelium (RPE) cells differentiated from human-induced pluripotent stem cells (hiPSCs). VRAC-mediated currents were strongly reduced in hiPSC-RPE from macular dystrophy patients with pathologic BEST1 mutations. Our model is further supported by in vivo effects of Best1 deficiency in the mouse that manifest as severe subfertility phenotype due to enhanced abnormal sperm morphology related to impaired volume regulation.

Induced pluripotent stem cell (iPSC)-derived retinal pigment epithelium (RPE) has widely been appreciated as a promising tool to model human ocular disease emanating from primary RPE pathology. Here, we describe the successful reprogramming of adult human dermal fibroblasts to iPSCs and their differentiation to pure expandable RPE cells with structural and functional features characteristic for native RPE. Fibroblast cultures were established from skin biopsy material and subsequently reprogrammed following polycistronic lentiviral transduction with OCT4, SOX2, KLF4 and L-Myc. Fibroblast-derived iPSCs showed typical morphology, chromosomal integrity and a distinctive stem cell marker profile. Subsequent differentiation resulted in expandable pigmented hexagonal RPE cells. The cells revealed stable RNA expression of mature RPE markers RPE65, RLBP and BEST1. Immunolabelling verified localisation of BEST1 at the basolateral plasma membrane, and scanning electron microscopy showed typical microvilli at the apical side of iPSC-derived RPE cells. Transepithelial resistance was maintained at high levels during cell culture indicating functional formation of tight junctions. Secretion capacity was demonstrated for VEGF-A. Feeding of porcine photoreceptor outer segments revealed the proper ability of these cells for phagocytosis. IPSC-derived RPE cells largely maintained these properties after cryopreservation. Together, our study underlines that adult dermal fibroblasts can serve as a valuable resource for iPSC-derived RPE with characteristics highly reminiscent of true RPE cells. This will allow its broad application to establish cellular models for RPE-related human diseases.

Purpose: To systematically analyze thicknesses of retinal layers in an older population and their link to early age-related macular degeneration (AMD). Methods: In the AugUR baseline survey from a population aged ≥70 years, we conducted multimodal retinal imaging, including spectral-domain optical coherence tomography. Autosegmentation of eight distinct retinal layers was followed by manual correction of segmentation errors. AMD status was graded on color fundus images according to the Three Continent AMD Consortium Severity Scale. We tested the association of early AMD on retinal layer thicknesses by using linear mixed models and replicated significant results in independent data also from the AugUR platform. Results: When comparing layer thicknesses between early AMD and no AMD (822 eyes, 449 participants), the retinal pigment epithelium/Bruch's membrane complex demonstrated a statistically significant thickening (e.g., P = 6.41 × 10⁻⁹² for severe early versus no AMD) and photoreceptor layers showed a significant thinning. Autosegmented retinal layer thicknesses revealed similar associations as manually corrected values but underestimated some effects. Independent replication analysis in 1026 eyes (546 participants) confirmed associations (e.g., P = 9.38 × 10⁻³⁶ for retinal pigment epithelium/Bruch's membrane complex, severe early versus no AMD). Conclusions: This first population-based study on spectral-domain optical coherence tomography-derived retinal layer thicknesses in a total of ∼1000 individuals provides insights into the reliability of autosegmentation and layer-specific reference values for an older population. Our findings show a difference in thicknesses between early AMD and no AMD for some retinal layers, suggesting these as potential imaging biomarkers. The thinning of photoreceptor layers substantiates a photoreceptor cell loss/damage already occurring in early AMD.