Personalized medicine aims to utilize genomic information about patients to tailor treatment. Gene replacement therapy for ra- re genetic disorders is perhaps the most extreme form of personalized medicine, in that th...Personalized medicine aims to utilize genomic information about patients to tailor treatment. Gene replacement therapy for ra- re genetic disorders is perhaps the most extreme form of personalized medicine, in that the patients＇ genome wholly determines their treatment regimen. Gene therapy for retinal disorders is poised to become a clinical reality. The eye is an optimal site for gene therapy due to the relative ease of precise vector delivery, immune system isolation, and availability for monitoring of any potential damage or side effects. Due to these advantages, clinical trials for gene therapy of retinal diseases are currently underway. A necessary precursor to such gene therapies is accurate molecular diagnosis of the mutation（s） underlying disease. In this review, we discuss the application of Next Generation Sequencing （NGS） to obtain such a diagnosis and identify disease causing genes, using retinal disorders as a case study. After reviewing ocular gene therapy, we discuss the application of NGS to the identification of novel Mendelian disease genes. We then compare current, array based mutation detection methods against next NGS-based methods in three retinal diseases： Leber＇s Congenital Amaurosis, Retinitis Pigmentosa, and Stargardt＇s disease. We conclude that next-generation sequencing based diagnosis offers several advantages over array based methods, including a higher rate of successful diagnosis and the ability to more deeply and efficiently assay a broad spectrum of mutations. However, the relative difficulty of interpreting sequence results and the development of standardized, reliable bioinforrnatic tools remain outstanding concerns. In this review, recent advances NGS based molecular diagnoses are discussed, as well as their implications for the development of personalized medicine.展开更多
Inherited retinal degeneration is a major cause of incurable blindness characterized by loss of retinal photoreceptor cells.Inherited retinal degeneration is characterized by high genetic and phenotypic heterogeneity ...Inherited retinal degeneration is a major cause of incurable blindness characterized by loss of retinal photoreceptor cells.Inherited retinal degeneration is characterized by high genetic and phenotypic heterogeneity with several genes mutated in patients affected by these genetic diseases.The high genetic heterogeneity of these diseases hampers the development of effective therapeutic interventions for the cure of a large cohort of patients.Common cell demise mechanisms can be envisioned as targets to treat patients regardless the specific mutation.One of these targets is the increase of intracellular calcium ions,that has been detected in several murine models of inherited retinal degeneration.Recently,neurotrophic factors that favor the efflux of calcium ions to concentrations below toxic levels have been identified as promising molecules that should be evaluated as new treatments for retinal degeneration.Here,we discuss therapeutic options for inherited retinal degeneration and we will focus on neuroprotective approaches,such as the neuroprotective activity of the Pigment epithelium-derived factor.The characterization of specific targets for neuroprotection opens new perspectives together with many questions that require deep analyses to take advantage of this knowledge and develop new therapeutic approaches.We believe that minimizing cell demise by neuroprotection may represent a promising treatment strategy for retinal degeneration.展开更多
Stargardt disease(also known as juvenile macular degeneration or Stargardt macular degeneration)is an inherited disorder of the retina,which can occur in the eyes of children and young adults.It is the most prevalent ...Stargardt disease(also known as juvenile macular degeneration or Stargardt macular degeneration)is an inherited disorder of the retina,which can occur in the eyes of children and young adults.It is the most prevalent form of juvenile-onset macular dystrophy,causing progressive(and often severe)vision loss.Images with Stargardt disease are characterized by the appearance of flecks in early and intermediate stages,and the appearance of atrophy,due to cells wasting away and dying,in the advanced stage.The primary measure of late-stage Stargardt disease is the appearance of atrophy.Fundus autofluorescence is a widely available two-dimensional imaging technique,which can aid in the diagnosis of the disease.Spectral-domain optical coherence tomography,in contrast,provides three-dimensional visualization of the retinal microstructure,thereby allowing the status of the individual retinal layers.Stargardt disease may cause various levels of disruption to the photoreceptor segments as well as other outer retinal layers.In recent years,there has been an exponential growth in the number of applications utilizing artificial intelligence for help with processing such diseases,heavily fueled by the amazing successes in image recognition using deep learning.This review regarding artificial intelligence deep learning approaches for the Stargardt atrophy screening and segmentation on fundus autofluorescence images is first provided,followed by a review of the automated retinal layer segmentation with atrophic-appearing lesions and fleck features using artificial intelligence deep learning construct.The paper concludes with a perspective about using artificial intelligence to potentially find early risk factors or biomarkers that can aid in the prediction of Stargardt disease progression.展开更多
●AIM:To describe the complex,overlapping phenotype of four Chinese patients with inherited retinal dystrophies(IRDs)who harbored two pathogenic genes simultaneously.●METHODS:This retrospective study included 4 patie...●AIM:To describe the complex,overlapping phenotype of four Chinese patients with inherited retinal dystrophies(IRDs)who harbored two pathogenic genes simultaneously.●METHODS:This retrospective study included 4 patients affected with IRDs.Medical and ophthalmic histories were obtained,and clinical examinations were performed.A specific Hereditary Eye Disease Enrichment Panel(HEDEP)based on exome capture technology was used for genetic screening.●RESULTS:Four patients were identified to harbor disease-causing variants in two different genes.Patient retinitis pigmentosa(RP)01-II:1 exhibited both classical ABCA4-induced Stargardt disease(STGD)1 and USH2 Aassociated RP,patient RP02-III:2 exhibited both classical ABCA4-induced STGD1 and CDH23-associated RP,patient RP03-II:1 exhibited both USH2 A-induced autosomal recessive retinitis pigmentosa(arRP)syndrome and SNRNP200-induced autosomal dominant retinitis pigmentosa(adRP),and patient RP04-II:2 exhibited USH2 Ainduced arRP syndrome and EYS-induced arRP at the same time.●CONCLUSION:Our study demonstrates that genotype–phenotype correlations and comprehensive genetic screening is crucial for diagnosing IRDs and helping family planning for patients suffering from the disease.展开更多
基金Jacques Zaneveld is supported by NIH training grant T32 EY007102Chen Rui is supported by grants from the Retinal Research Foundation and National Eye Institute (R01EY018571,R01EY022356)
文摘Personalized medicine aims to utilize genomic information about patients to tailor treatment. Gene replacement therapy for ra- re genetic disorders is perhaps the most extreme form of personalized medicine, in that the patients＇ genome wholly determines their treatment regimen. Gene therapy for retinal disorders is poised to become a clinical reality. The eye is an optimal site for gene therapy due to the relative ease of precise vector delivery, immune system isolation, and availability for monitoring of any potential damage or side effects. Due to these advantages, clinical trials for gene therapy of retinal diseases are currently underway. A necessary precursor to such gene therapies is accurate molecular diagnosis of the mutation（s） underlying disease. In this review, we discuss the application of Next Generation Sequencing （NGS） to obtain such a diagnosis and identify disease causing genes, using retinal disorders as a case study. After reviewing ocular gene therapy, we discuss the application of NGS to the identification of novel Mendelian disease genes. We then compare current, array based mutation detection methods against next NGS-based methods in three retinal diseases： Leber＇s Congenital Amaurosis, Retinitis Pigmentosa, and Stargardt＇s disease. We conclude that next-generation sequencing based diagnosis offers several advantages over array based methods, including a higher rate of successful diagnosis and the ability to more deeply and efficiently assay a broad spectrum of mutations. However, the relative difficulty of interpreting sequence results and the development of standardized, reliable bioinforrnatic tools remain outstanding concerns. In this review, recent advances NGS based molecular diagnoses are discussed, as well as their implications for the development of personalized medicine.
基金supported by grants from the Telethon Foundation(GGP14180,GGP19113)the European Union(LSHGCT-2005-512036 and transMed,MSCA-ITN-2017-765441)(all to VM)
文摘Inherited retinal degeneration is a major cause of incurable blindness characterized by loss of retinal photoreceptor cells.Inherited retinal degeneration is characterized by high genetic and phenotypic heterogeneity with several genes mutated in patients affected by these genetic diseases.The high genetic heterogeneity of these diseases hampers the development of effective therapeutic interventions for the cure of a large cohort of patients.Common cell demise mechanisms can be envisioned as targets to treat patients regardless the specific mutation.One of these targets is the increase of intracellular calcium ions,that has been detected in several murine models of inherited retinal degeneration.Recently,neurotrophic factors that favor the efflux of calcium ions to concentrations below toxic levels have been identified as promising molecules that should be evaluated as new treatments for retinal degeneration.Here,we discuss therapeutic options for inherited retinal degeneration and we will focus on neuroprotective approaches,such as the neuroprotective activity of the Pigment epithelium-derived factor.The characterization of specific targets for neuroprotection opens new perspectives together with many questions that require deep analyses to take advantage of this knowledge and develop new therapeutic approaches.We believe that minimizing cell demise by neuroprotection may represent a promising treatment strategy for retinal degeneration.
基金supported by the National Eye Institute of the National Institutes of Health under Award Number R21EY029839 (to ZJH)
文摘Stargardt disease(also known as juvenile macular degeneration or Stargardt macular degeneration)is an inherited disorder of the retina,which can occur in the eyes of children and young adults.It is the most prevalent form of juvenile-onset macular dystrophy,causing progressive(and often severe)vision loss.Images with Stargardt disease are characterized by the appearance of flecks in early and intermediate stages,and the appearance of atrophy,due to cells wasting away and dying,in the advanced stage.The primary measure of late-stage Stargardt disease is the appearance of atrophy.Fundus autofluorescence is a widely available two-dimensional imaging technique,which can aid in the diagnosis of the disease.Spectral-domain optical coherence tomography,in contrast,provides three-dimensional visualization of the retinal microstructure,thereby allowing the status of the individual retinal layers.Stargardt disease may cause various levels of disruption to the photoreceptor segments as well as other outer retinal layers.In recent years,there has been an exponential growth in the number of applications utilizing artificial intelligence for help with processing such diseases,heavily fueled by the amazing successes in image recognition using deep learning.This review regarding artificial intelligence deep learning approaches for the Stargardt atrophy screening and segmentation on fundus autofluorescence images is first provided,followed by a review of the automated retinal layer segmentation with atrophic-appearing lesions and fleck features using artificial intelligence deep learning construct.The paper concludes with a perspective about using artificial intelligence to potentially find early risk factors or biomarkers that can aid in the prediction of Stargardt disease progression.
基金Supported by the National Natural Science Foundation of China(No.81770966,No.81470666,No.81271046)a Joint Program of Beijing Municipal NaturalScience Foundation(Category B)Beijing Educational committee(No.KZ201510025025).
文摘●AIM:To describe the complex,overlapping phenotype of four Chinese patients with inherited retinal dystrophies(IRDs)who harbored two pathogenic genes simultaneously.●METHODS:This retrospective study included 4 patients affected with IRDs.Medical and ophthalmic histories were obtained,and clinical examinations were performed.A specific Hereditary Eye Disease Enrichment Panel(HEDEP)based on exome capture technology was used for genetic screening.●RESULTS:Four patients were identified to harbor disease-causing variants in two different genes.Patient retinitis pigmentosa(RP)01-II:1 exhibited both classical ABCA4-induced Stargardt disease(STGD)1 and USH2 Aassociated RP,patient RP02-III:2 exhibited both classical ABCA4-induced STGD1 and CDH23-associated RP,patient RP03-II:1 exhibited both USH2 A-induced autosomal recessive retinitis pigmentosa(arRP)syndrome and SNRNP200-induced autosomal dominant retinitis pigmentosa(adRP),and patient RP04-II:2 exhibited USH2 Ainduced arRP syndrome and EYS-induced arRP at the same time.●CONCLUSION:Our study demonstrates that genotype–phenotype correlations and comprehensive genetic screening is crucial for diagnosing IRDs and helping family planning for patients suffering from the disease.
