Next-generation sequencing-based gene panel tests for the detection of rare variants and hypomorphic alleles associated with primary open-angle glaucoma.

Primary open-angle glaucoma (POAG) is a complex disease with a strong hereditably component. Several genetic variants have recently been associated with POAG, partially due to technological improvements such as next-generation sequencing (NGS). The aim of this study was to genetically analyze patients with POAG to determine the contribution of rare variants and hypomorphic alleles associated with glaucoma as a future method of diagnosis and early treatment. Seventy-two genes potentially associated with adult glaucoma were studied in 61 patients with POAG. Additionally, we sequenced the coding sequence of CYP1B1 gene in 13 independent patients to deep analyze the potential association of hypomorphic CYP1B1 alleles in the pathogenesis of POAG. We detected nine rare variants in 16% of POAG patients studied by NGS. Those rare variants are located in CYP1B1, SIX6, CARD10, MFN1, OPTC, OPTN, and WDR36 glaucoma-related genes. Hypomorphic variants in CYP1B1 and SIX6 genes have been identified in 8% of the total POAG patient assessed. Our findings suggest that NGS could be a valuable tool to clarify the impact of genetic component on adult glaucoma. However, in order to demonstrate the contribution of these rare variants and hypomorphic alleles to glaucoma, segregation and functional studies would be necessary. The identification of new variants and hypomorphic alleles in glaucoma patients will help to configure the genetic identity of these patients, in order to make an early and precise molecular diagnosis.

Classifying glaucoma exclusively with OCT: comparison of three clustering algorithms derived from machine learning.

BACKGROUND/AIMS: To objectively classify eyes as either healthy or glaucoma based exclusively on data provided by peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell-inner plexiform (GCIPL) measurements derived from spectral-domain optical coherence tomography (SD-OCT) using machine learning algorithms. METHODS: Three clustering methods (k-means, hierarchical cluster analysis -HCA- and model-based clustering-MBC-) were used separately to classify a training sample of 109 eyes as either healthy or glaucomatous using solely 13 SD-OCT parameters: pRNFL average and sector thicknesses and GCIPL average and minimum values together with the six macular wedge-shaped regions. Then, the best-performing algorithm was applied to an independent test sample of 102 eyes to derive close estimates of its actual performance (external validation). RESULTS: In the training sample, accuracy was 91.7% for MBC, 81.7% for k-means and 78.9% for HCA (p value = 0.02). The best MBC model was that in which subgroups were allowed to have variable volume and shape and equal orientation. The MBC algorithm in the independent test sample correctly classified 98 out of 102 cases for an overall accuracy of 96.1% (95% CI, 92.3-99.8%), with a sensitivity of 94.3 and 100% specificity. The accuracy for pRNFL was 92.2% (95% CI, 86.9-97.4%) and for GCIPL 98.0% (95% CI, 95.3-100%). CONCLUSIONS: Clustering algorithms in general (and MBC in particular) seem promising methods to help discriminate between healthy and glaucomatous eyes using exclusively SD-OCT-derived parameters. Understanding the relative merits of one method over others may also provide insights into the nature of the disease.

Differential Gene and Protein Expression of Conjunctival Bleb Hyperfibrosis in Early Failure of Glaucoma Surgery.

The early failure of glaucoma surgery is mainly caused by over-fibrosis at the subconjunctival space, causing obliteration of the filtration bleb. Because fibrosis has a suspected basis of genetic predisposition, we have undertaken a prospective study to identify upregulated profibrotic genes in a population of glaucoma patients with signs of conjunctival fibrosis and early postoperative surgical failure. Clinical data of re-operated fibrosis patients, hyperfibrosis patients who re-operated more than once in a short time, and control patients with no fibrosis were recorded and analyzed at each follow-up visit. Conjunctival-Tenon surgical specimens were obtained intraoperatively to evaluate the local expression of a panel of genes potentially associated with fibrosis. In order to correlate gene expression signatures with protein levels, we quantified secreted proteins in primary cultures of fibroblasts from patients. Expression of VEGFA, CXCL8, MYC, and CDKN1A was induced in the conjunctiva of hyperfibrosis patients. VEGFA and IL8 protein levels were also increased in fibroblast supernatants. We propose that an increase in these proteins could be useful in detecting conjunctival fibrosis in glaucoma patients undergoing filtering surgery. Molecular markers could be crucial for early detection of patients at high risk of failure of filtration surgery, leading to more optimal and personalized treatments.

External Validation and Clinical Applicability of Two Optical Coherence Tomography-Based Risk Calculators for Detecting Glaucoma.

Purpose: To clinically validate the diagnostic ability of two optical coherence tomography (OCT)-based glaucoma diagnostic calculators (GDCs). Methods: We conducted a retrospective, consecutive sampling of 76 patients with primary open-angle glaucoma, 107 glaucoma suspects, and 67 controls. Demographics, reliable visual field testing, and macular and optic disc OCT were collected. The reference diagnosis was compared against the probability of having glaucoma obtained from two GDCs derived from multivariate logistic regressions using quantitative and qualitative (GDC1) or only quantitative (GDC2) OCT data. The discrimination (area under the curve [AUC]) and calibration (calibration plots) were compared for both calculators and the best OCT parameters. Results: GDC2 was able to identify 46.9% more suspects and 14.7% more glaucomatous eyes than GDC1. Both GDCs obtained the highest discriminative ability in glaucomatous eyes (GDC1 AUC = 0.949; GDC2 = 0.943 vs inferior peripapillary retinal nerve fiber layer [pRNFL] = 0.931; P = 0.43). The discriminating ability was not as good for glaucoma suspects, but the GDCs were not inferior to pRNFL (GDC 1 AUC = 0.739; GDC2 = 0.730; inferior pRNFL = 0.760; P = 0.54) and GDC2 was still able to correctly identify up to 30.8% more cases than the conventional OCT classification. Calibration showed risk underestimation for both groups and calculators, but it was better in GDC2 and in patients with glaucoma. Conclusions: OCT-based calculators showed an excellent diagnostic performance in glaucomatous eyes. GDC2 was able to identify approximately 30% more cases than the conventional pRNFL inferior OCT classification in both groups, suggesting a potential role of these composite scores in clinical practice. Translational Relevance: These OCT-based calculators may improve glaucoma diagnosis in clinical care.

Effect of CPAP Therapy on 24-Hour Intraocular Pressure-Related Pattern From Contact Lens Sensors in Obstructive Sleep Apnea Syndrome.

Purpose: To evaluate the effect of continuous positive airway pressure (CPAP) therapy on 24-hour intraocular pressure (IOP)-related pattern from contact lens sensors (CLS) in obstructive sleep apnea syndrome (OSAS). Methods: Prospective, observational, case series study. Twenty-two eyes of 22 newly diagnosed patients with severe OSAS were included. A first 24-hour CLS measurement was performed before CPAP therapy was started, and a second 24-hour CLS monitoring was performed after beginning CPAP. We analyzed the amplitude and the maximum and minimum IOP-related values (m Veq). We also analyzed IOP-related measurements at five-minute intervals throughout the first hour of nocturnal acrophase, starting from when the patient fell asleep. Results: The baseline measurements showed significant fluctuations in the IOP, with the highest IOP readings being recorded at night (nocturnal acrophase) in 17 of 22 patients (77.27%). Nocturnal acrophase began when the patients laid down to sleep. During CPAP therapy, the patients showed a more marked increase in IOP in the initial phase of nocturnal acrophase, with significant differences at 20, 25, 30, and 55 minutes (P < 0.05). Conclusions: Most of patients with severe OSAS exhibited a nocturnal acrophase and the highest IOP readings at night. CPAP was associated with additional increase in IOP-related pattern for at least the first hour of CPAP use. Translational Relevance: Our results suggest that CPAP was associated with additional increase in IOP during the initial phase of nocturnal acrophase. This effect could be important in the management of patients with OSAS and glaucomatous progression.

Metástasis palpebral de un melanoma / Metastatic melanoma to the eyelid

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