Cone photoreceptor definition on adaptive optics retinal imaging

To quantitatively analyse cone photoreceptor matrices on images captured on an adaptive optics (AO) camera and assess their correlation to well-established parameters in the retinal histology literature

Electrophysiological Characterization of Macular Telangiectasia Type 2 and Structure-Function Correlation

PURPOSE: To investigate the electrophysiological features of macular telangiectasia Type 2 and their relationship to structure as determined by optical coherence tomography imaging. METHODS: Forty-two eyes from 21 patients enrolled in the Macular Telangiectasia Natural History Observation Study were reviewed. All patients had full-field and pattern electroretinography (ERG; PERG) with some patients additionally having multifocal electroretinography (mfERG; N = 15) or electrooculography (N = 12). Multiple linear regression modeling assessed the relationship between the ellipsoid zone break size on optical coherence tomography and the central mfERG response. RESULTS: Full-field ERG and electrooculography were normal in all eyes. Six eyes (14%) from five patients had subnormal PERG P50 amplitudes. Twenty-two of 30 eyes (73%) had reduced central or paracentral stimulus on mfERG. There was a significant correlation between ellipsoid zone break size and both the P1 amplitude (R = 0.37, P = 0.002) and P1:N1 ratio (R = 0.32, P = 0.002) of the central response on mfERG. CONCLUSION: The electrophysiological findings in macular telangiectasia Type 2 are those of localized central dysfunction and are consistent with the structural data available from imaging and histologic studies. The ellipsoid zone break size correlates with mfERG reduction. The reduced mfERG P1:N1 ratio is consistent with inner retinal dysfunction

Macular Telangiectasia Type 2: A Classification System Using MultiModal Imaging MacTel Project Report Number 10

Purpose: To develop a severity classification for macular telangiectasia type 2 (MacTel) disease using multimodal imaging. Design: An algorithm was used on data from a prospective natural history study of MacTel for classification development. Subjects: A total of 1733 participants enrolled in an international natural history study of MacTel. Methods: The Classification and Regression Trees (CART), a predictive nonparametric algorithm used in machine learning, analyzed the features of the multimodal imaging important for the development of a classification, including reading center gradings of the following digital images: stereoscopic color and red-free fundus photographs, fluorescein angiographic images, fundus autofluorescence images, and spectral-domain (SD)-OCT images. Regression models that used least square method created a decision tree using features of the ocular images into different categories of disease severity. Main Outcome Measures: The primary target of interest for the algorithm development by CART was the change in best-corrected visual acuity (BCVA) at baseline for the right and left eyes. These analyses using the algorithm were repeated for the BCVA obtained at the last study visit of the natural history study for the right and left eyes. Results: The CART analyses demonstrated 3 important features from the multimodal imaging for the classification: OCT hyper-reflectivity, pigment, and ellipsoid zone loss. By combining these 3 features (as absent, present, noncentral involvement, and central involvement of the macula), a 7-step scale was created, ranging from excellent to poor visual acuity. At grade 0, 3 features are not present. At the most severe grade, pigment and exudative neovascularization are present. To further validate the classification, using the Generalized Estimating Equation regression models, analyses for the annual relative risk of progression over a period of 5 years for vision loss and for progression along the scale were performed. Conclusions: This analysis using the data from current imaging modalities in participants followed in the MacTel natural history study informed a classification for MacTel disease severity featuring variables from SD-OCT. This classification is designed to provide better communications to other clinicians, researchers, and patients. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references

Abnormal Retinal Reflectivity To Short-Wavelength Light In Type 2 Idiopathic Macular Telangiectasia

PURPOSE: Macular telangiectasia Type 2 (MacTel) is a bilateral, progressive, potentially blinding retinal disease characterized by vascular and neurodegenerative signs, including an increased parafoveal reflectivity to blue light. Our aim was to investigate the relationship of this sign with other signs of macular telangiectasia Type 2 in multiple imaging modalities. METHODS: Participants were selected from the MacTel Type 2 study, based on a confirmed diagnosis and the availability of images. The extent of signs in blue-light reflectance, fluorescein angiographic, optical coherence tomographic, and single- and dual-wavelength autofluorescence images were analyzed. RESULTS: A well-defined abnormality of the perifovea is demonstrated by dual-wavelength autofluorescence and blue-light reflectance in early disease. The agreement in area size of the abnormalities in dual-wavelength autofluorescence and in blue-light reflectance images was excellent: for right eyes: ρ = 0.917 (P < 0.0001, 95% confidence interval 0.855-0.954, n = 46) and for left eyes: ρ = 0.952 (P < 0.0001, 95% confidence interval 0.916-0.973, n = 49). Other changes are less extensive initially and expand later to occupy that area and do not extend beyond it. CONCLUSION: Our findings indicate that abnormal metabolic handling of luteal pigment and physical changes giving rise to increased reflectance are widespread in the macula throughout the natural history of the disease, precede other changes, and are relevant to early diagnosis

Identifying subtypes of patients with neovascular age-related macular degeneration by genotypic and cardiovascular risk characteristics

<p>Abstract</p> <p>Background</p> <p>One of the challenges in the interpretation of studies showing associations between environmental and genotypic data with disease outcomes such as neovascular age-related macular degeneration (AMD) is understanding the phenotypic heterogeneity within a patient population with regard to any risk factor associated with the condition. This is critical when considering the potential therapeutic response of patients to any drug developed to treat the condition. In the present study, we identify patient subtypes or clusters which could represent several different targets for treatment development, based on genetic pathways in AMD and cardiovascular pathology.</p> <p>Methods</p> <p>We identified a sample of patients with neovascular AMD, that in previous studies had been shown to be at elevated risk for the disease through environmental factors such as cigarette smoking and genetic variants including the complement factor H gene (<it>CFH</it>) on chromosome 1q25 and variants in the <it>ARMS2</it>/HtrA serine peptidase 1 (<it>HTRA1</it>) gene(s) on chromosome 10q26. We conducted a multivariate segmentation analysis of 253 of these patients utilizing available epidemiologic and genetic data.</p> <p>Results</p> <p>In a multivariate model, cigarette smoking failed to differentiate subtypes of patients. However, four meaningfully distinct clusters of patients were identified that were most strongly differentiated by their cardiovascular health status (histories of hypercholesterolemia and hypertension), and the alleles of <it>ARMS2</it>/<it>HTRA1 </it>rs1049331.</p> <p>Conclusions</p> <p>These results have significant personalized medicine implications for drug developers attempting to determine the effective size of the treatable neovascular AMD population. Patient subtypes or clusters may represent different targets for therapeutic development based on genetic pathways in AMD and cardiovascular pathology, and treatments developed that may elevate CV risk, may be ill advised for certain of the clusters identified.</p

Insights into the Genetic Architecture of Early Stage Age-Related Macular Degeneration: A Genome-Wide Association Study Meta-Analysis

10.1371/journal.pone.0053830PLoS ONE81

Genetic disruption of serine biosynthesis is a key driver of macular telangiectasia type 2 aetiology and progression

BACKGROUND: Macular telangiectasia type 2 (MacTel) is a rare, heritable and largely untreatable retinal disorder, often comorbid with diabetes. Genetic risk loci subtend retinal vascular calibre and glycine/serine/threonine metabolism genes. Serine deficiency may contribute to MacTel via neurotoxic deoxysphingolipid production; however, an independent vascular contribution is also suspected. Here, we use statistical genetics to dissect the causal mechanisms underpinning this complex disease. METHODS: We integrated genetic markers for MacTel, vascular and metabolic traits, and applied Mendelian randomisation and conditional and interaction genome-wide association analyses to discover the causal contributors to both disease and spatial retinal imaging sub-phenotypes. RESULTS: Genetically induced serine deficiency is the primary causal metabolic driver of disease occurrence and progression, with a lesser, but significant, causal contribution of type 2 diabetes genetic risk. Conversely, glycine, threonine and retinal vascular traits are unlikely to be causal for MacTel. Conditional regression analysis identified three novel disease loci independent of endogenous serine biosynthetic capacity. By aggregating spatial retinal phenotypes into endophenotypes, we demonstrate that SNPs constituting independent risk loci act via related endophenotypes. CONCLUSIONS: Follow-up studies after GWAS integrating publicly available data with deep phenotyping are still rare. Here, we describe such analysis, where we integrated retinal imaging data with MacTel and other traits genomics data to identify biochemical mechanisms likely causing this disorder. Our findings will aid in early diagnosis and accurate prognosis of MacTel and improve prospects for effective therapeutic intervention. Our integrative genetics approach also serves as a useful template for post-GWAS analyses in other disorders