Prevalence of mutations in inherited retinal diseases: A comparison between the United States and India

Next-generation sequencing--based genetic testing and phenotype correlation in retinitis pigmentosa patients from India

Purpose

Inherited retinal dystrophies (IRD) are a heterogeneous group of retinal diseases leading to progressive loss of photoreceptors through apoptosis. Retinitis pigmentosa (RP) is considered the most common form of IRD. Panel-based testing in RP has proven effective in identifying the causative genetic mutations in 70% and 80% of the patients. This is a retrospective, observational, single-center study of 107 RP patients who had undergone next-generation sequencing-based targeted gene panel testing for IRD genes. These patients were inspected for common phenotypic features to arrive at meaningful genotype-phenotype correlation.

Methods

Patients underwent complete ophthalmic examination, and blood was collected from the proband for DNA extraction after documenting the pedigree. Targeted Next Generation Sequencing (NGS) was done by panel-based testing for IRD genes followed by co-segregation analysis wherever applicable.

Results

Of the 107 patients, 72 patients had pathogenic mutations. The mean age of onset of symptoms was 14 ± 12 years (range: 5-55). Mean (Best Corrected Visual Acuity) BCVA was 6/48 (0.9 logMAR) (range 0.0-3.0). At presentation, over one-third of eyes had BCVA worse than 6/60 (<1 logMAR). Phenotype analysis with the gene defects showed overlapping features, such as peripheral well-defined chorioretinal atrophic patches in patients with CERKL, PROM1, and RPE65 gene mutations and large macular lesions in patients with RDH12 and CRX gene mutations, respectively. Nummular or clump-like pigmentation was noted in CRB1, TTC8, PDE6A, and PDE6B.

Conclusion

NGS-based genetic testing can help clinicians to diagnose RP more accurately, and phenotypic correlations can also help in better patient counselling with respect to prognosis and guidance regarding ongoing newer gene-based therapies.

SynthEye: Investigating the Impact of Synthetic Data on Artificial Intelligence-assisted Gene Diagnosis of Inherited Retinal Disease

Purpose

Rare disease diagnosis is challenging in medical image-based artificial intelligence due to a natural class imbalance in datasets, leading to biased prediction models. Inherited retinal diseases (IRDs) are a research domain that particularly faces this issue. This study investigates the applicability of synthetic data in improving artificial intelligence-enabled diagnosis of IRDs using generative adversarial networks (GANs).

Design

Diagnostic study of gene-labeled fundus autofluorescence (FAF) IRD images using deep learning.

Participants

Moorfields Eye Hospital (MEH) dataset of 15 692 FAF images obtained from 1800 patients with confirmed genetic diagnosis of 1 of 36 IRD genes.

Methods

A StyleGAN2 model is trained on the IRD dataset to generate 512 × 512 resolution images. Convolutional neural networks are trained for classification using different synthetically augmented datasets, including real IRD images plus 1800 and 3600 synthetic images, and a fully rebalanced dataset. We also perform an experiment with only synthetic data. All models are compared against a baseline convolutional neural network trained only on real data.

Main Outcome Measures

We evaluated synthetic data quality using a Visual Turing Test conducted with 4 ophthalmologists from MEH. Synthetic and real images were compared using feature space visualization, similarity analysis to detect memorized images, and Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) score for no-reference-based quality evaluation. Convolutional neural network diagnostic performance was determined on a held-out test set using the area under the receiver operating characteristic curve (AUROC) and Cohen's Kappa (κ).

Results

An average true recognition rate of 63% and fake recognition rate of 47% was obtained from the Visual Turing Test. Thus, a considerable proportion of the synthetic images were classified as real by clinical experts. Similarity analysis showed that the synthetic images were not copies of the real images, indicating that copied real images, meaning the GAN was able to generalize. However, BRISQUE score analysis indicated that synthetic images were of significantly lower quality overall than real images (P < 0.05). Comparing the rebalanced model (RB) with the baseline (R), no significant change in the average AUROC and κ was found (R-AUROC = 0.86[0.85-88], RB-AUROC = 0.88[0.86-0.89], R-k = 0.51[0.49-0.53], and RB-k = 0.52[0.50-0.54]). The synthetic data trained model (S) achieved similar performance as the baseline (S-AUROC = 0.86[0.85-87], S-k = 0.48[0.46-0.50]).

Conclusions

Synthetic generation of realistic IRD FAF images is feasible. Synthetic data augmentation does not deliver improvements in classification performance. However, synthetic data alone deliver a similar performance as real data, and hence may be useful as a proxy to real data. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

Disparities in Inherited Retinal Degenerations

To review disparities in the field of inherited retinal degenerations to establish foundations for future discussions oriented toward finding possible solutions. A narrative overview of the literature. Despite collective efforts towards democratization of genetic testing and investigation, genetic databases containing primarily European populations are heavily relied upon. Access to specialized care and other resources is also still not available to all. Recognizing and addressing disparities and inequities within the field of inherited retinal degenerations will improve our care of these patients and our knowledge of their conditions.

Inherited retinal disorders: a genotype-phenotype correlation in an Indian cohort and the importance of genetic testing and genetic counselling

PURPOSE

Recent advances in sequencing technologies have enabled radical and rapid progress in the genetic diagnosis of inherited retinal disorders (IRDs). Although the list of gene variations continues to grow, it lacks the genetic etiology of ethnic groups like South Asians. Differences in racial backgrounds and consanguinity add to genetic heterogeneity and phenotypic overlaps.

METHODS

This retrospective study includes documented data from the Gen-Eye clinic from years 2014 to 2019. Medical records and pedigrees of 591 IRD patients of Indian origin and genetic reports of 117 probands were reviewed. Genotype-phenotype correlations were performed to classify as correlating, non-correlating and unsolved cases.

RESULTS

Among the 591 patients, we observed a higher prevalence of clinically diagnosed retinitis pigmentosa (38.9%) followed by unspecified diagnoses (28.5%). Consanguinity was reported to be high (55.6%) in this cohort. Among the variants identified in 117 probands, 36.4% of variants were pathogenic, 19.2% were likely pathogenic, and 44.4% were of uncertain significance. Among the pathogenic and likely pathogenic variants, autosomal recessive inheritance showed higher prevalence. About 35% (41/117) of cases showed genotype-phenotype correlation. Within the correlating cases, retinitis pigmentosa and Stargardt disease were predominant. Novel variants identified in RP, Stargardt, and LCA are reported here.

CONCLUSION

This first-of-a-kind report on an Indian cohort contributes to existing knowledge and expansion of variant databases, presenting relevant and plausible novel variants. Phenotypic overlap and variability lead to a differential diagnosis and hence a clear genotype-phenotype correlation helps in precise clinical confirmation. The study also emphasizes the importance of genetic counselling and testing for personalized vision care in a tertiary eye hospital.

The Diagnostic Yield of Next Generation Sequencing in Inherited Retinal Diseases: A Systematic Review and Meta-analysis

PURPOSE

Accurate genotyping of individuals with inherited retinal diseases (IRD) is essential for patient management and identifying suitable candidates for gene therapies. This study evaluated the diagnostic yield of next generation sequencing (NGS) in IRDs.

DESIGN

Systematic review and meta-analysis.

METHODS

This systematic review was prospectively registered (CRD42021293619). Ovid MEDLINE and Ovid Embase were searched on 6 June 2022. Clinical studies evaluating the diagnostic yield of NGS in individuals with IRDs were eligible for inclusion. Risk of bias assessment was performed. Studies were pooled using a random...effects inverse variance model. Sources of heterogeneity were explored using stratified analysis, meta-regression, and sensitivity analysis.

RESULTS

This study included 105 publications from 28 countries. Most studies (90 studies) used targeted gene panels. The diagnostic yield of NGS was 61.3% (95% confidence interval: 57.8-64.7%; 51 studies) in mixed IRD phenotypes, 58.2% (51.6-64.6%; 41 studies) in rod-cone dystrophies, 57.7% (46.8-68.3%; eight studies) in macular and cone/cone-rod dystrophies, and 47.6% (95% CI: 41.0-54.3%; four studies) in familial exudative vitreoretinopathy. For mixed IRD phenotypes, a higher diagnostic yield was achieved pooling studies published between 2018-2022 (64.2% [59.5-68.7%]), studies using exome sequencing (73.5% [58.9-86.1%]), and studies using the American College of Medical Genetics variant interpretation standards (65.6% [60.8-70.4%]).

CONCLUSION

The current diagnostic yield of NGS in IRDs is between 52-74%. The certainty of the evidence was judged as low or very low. A key limitation of the current evidence is the significant heterogeneity between studies. Adoption of standardized reporting guidelines could improve confidence in future meta-analyses.

Advancing precision medicines for ocular disorders: Diagnostic genomics to tailored therapies

Successful sequencing of the human genome and evolving functional knowledge of gene products has taken genomic medicine to the forefront, soon combining broadly with traditional diagnostics, therapeutics, and prognostics in patients. Recent years have witnessed an extraordinary leap in our understanding of ocular diseases and their respective genetic underpinnings. As we are entering the age of genomic medicine, rapid advances in genome sequencing, gene delivery, genome surgery, and computational genomics enable an ever-increasing capacity to provide a precise and robust diagnosis of diseases and the development of targeted treatment strategies. Inherited retinal diseases are a major source of blindness around the world where a large number of causative genes have been identified, paving the way for personalized diagnostics in the clinic. Developments in functional genetics and gene transfer techniques has also led to the first FDA approval of gene therapy for LCA, a childhood blindness. Many such retinal diseases are the focus of various clinical trials, making clinical diagnoses of retinal diseases, their underlying genetics and the studies of natural history important. Here, we review methodologies for identifying new genes and variants associated with various ocular disorders and the complexities associated with them. Thereafter we discuss briefly, various retinal diseases and the application of genomic technologies in their diagnosis. We also discuss the strategies, challenges, and potential of gene therapy for the treatment of inherited and acquired retinal diseases. Additionally, we discuss the translational aspects of gene therapy, the important vector types and considerations for human trials that may help advance personalized therapeutics in ophthalmology. Retinal disease research has led the application of precision diagnostics and precision therapies; therefore, this review provides a general understanding of the current status of precision medicine in ophthalmology.

Gene-Based Therapeutics for Inherited Retinal Diseases

Inherited retinal diseases (IRDs) are a heterogenous group of orphan eye diseases that typically result from monogenic mutations and are considered attractive targets for gene-based therapeutics. Following the approval of an IRD gene replacement therapy for Leber's congenital amaurosis due to RPE65 mutations, there has been an intensive international research effort to identify the optimal gene therapy approaches for a range of IRDs and many are now undergoing clinical trials. In this review we explore therapeutic challenges posed by IRDs and review current and future approaches that may be applicable to different subsets of IRD mutations. Emphasis is placed on five distinct approaches to gene-based therapy that have potential to treat the full spectrum of IRDs: 1) gene replacement using adeno-associated virus (AAV) and nonviral delivery vectors, 2) genome editing via the CRISPR/Cas9 system, 3) RNA editing by endogenous and exogenous ADAR, 4) mRNA targeting with antisense oligonucleotides for gene knockdown and splicing modification, and 5) optogenetic approaches that aim to replace the function of native retinal photoreceptors by engineering other retinal cell types to become capable of phototransduction.

Ophthalmic genetics practice and research in India: Vision in 2020

Ophthalmic genetics is a much needed and growing area in India. Ethnic diversity, with a high degree of consanguinity, has led to a high prevalence of genetic disorders in the country. As the second most populous country in the world, this naturally results in a significant number of affected people overall. Practice involves coherent association between ophthalmologists, genetic counselor and pediatricians. Eye genetics in India in recent times has witnessed advanced research using cutting edge diagnostics, next generation sequencing (NGS) approaches, stem cell therapies, gene therapy and genomic editing. This article will highlight the studies reporting genetic variations in the country, challenges in practice, and the latest advances in ophthalmic genetic research in India.

Prevalence of mutations in inherited retinal diseases: A comparison between the United States and India

Background

Studies evaluating next‐generation sequencing (NGS) for retinal disorders may not reflect clinical practice. We report results of retrospective analysis of patients referred for clinical testing at two institutions (US and India).

Methods

This retrospective study of 131 patients who underwent clinically validated targeted NGS or exome sequencing for a wide variety of clinical phenotypes categorized results into a definitive, indeterminate, or negative molecular diagnosis.

Results

A definitive molecular diagnosis (52%) was more common in the India cohort (62% vs. 39%, p = .009), while an indeterminate molecular diagnosis occurred only in the US cohort (12%). In the US cohort, a lower diagnostic rate in Hispanic, non‐Caucasians (23%) was seen compared to Caucasians (57%). The India cohort had a high rate of homozygous variants (61%) and different frequency of genes involved compared to the US cohort.

Conclusion

Despite inherent limitations in clinical testing, the diagnostic rate across the two cohorts (52%) was similar to the 50%–65% diagnostic rate in the literature. However, the diagnostic rate was lower in the US cohort and appears partly explained by racial background. The high rate of consanguinity in the Indian population is reflected in the high rate of homozygosity for pathogenic mutations and may have implications for population level screening and genetic counseling. Clinical laboratories may note diagnostic rates that differ from the literature, due to factors such as heterogeneity in racial background or consanguinity rates in the populations being tested. This information may be useful for post‐test counseling.