Comprehensive microRNA analyses using vitreous humor of ocular sarcoidosis.

PURPOSE: MicroRNAs (miRNAs) are non-coding RNAs which have attracted attention as biomarkers in a variety of diseases. However, extensive unbiased analysis of miRNA in vitreous humor of sarcoidosis patients has not been reported. In the present study, we comprehensively analyzed the dysregulated miRNAs in ocular sarcoidosis to search for potential biomarkers. MATERIALS AND METHODS: This study included seven patients diagnosed with ocular sarcoidosis (five definite and two presumed). Five patients with unclassified uveitis and 24 with non-inflammatory diseases served as controls. MicroRNA expression levels in vitreous humor samples were measured by microarray, and differentially expressed miRNAs between sarcoidosis and other diseases were explored. Next, pathway enrichment analysis was performed to evaluate the functions of the dysregulated miRNAs, and machine learning was used to search for candidate biomarkers. RESULTS: A total of 614 upregulated miRNAs and 8 downregulated miRNAs were detected in vitreous humor of patients with ocular sarcoidosis compared with patients with unclassified uveitis and non-inflammatory diseases. Some dysregulated miRNAs were involved in the TGF-ß signaling pathway. Furthermore, we identified miR-764 as the best predictor for ocular sarcoidosis using Boruta selection. CONCLUSIONS: In this study, comprehensive miRNA analysis of vitreous humor samples identified dysregulated miRNAs in ocular sarcoidosis. This study suggests new insights into molecular pathogenetic mechanisms of sarcoidosis and may provide useful information toward developing novel diagnostic biomarkers and therapeutic targets for sarcoidosis.

Vitreous Humor Proteomic Profile in Patients With Vitreoretinal Lymphoma.

Purpose: Vitreoretinal lymphoma is a high-grade malignant non-Hodgkin lymphoma with poor prognosis. The objective of this study was to elucidate the proteome profile of the vitreous in patients with vitreoretinal lymphoma (VRL), aiming to advance understanding of the pathophysiology of VRL. Methods: Comprehensive proteomic analyses of vitreous humor using liquid chromatography with tandem mass spectrometry were performed for 10 patients with VRL, 10 control patients with idiopathic epiretinal membrane or macular hole, and 10 patients with ocular sarcoidosis. Differentially expressed proteins (DEPs) were identified by comparing VRL with controls and sarcoidosis, and functional pathway analysis was performed. Finally, vitreous concentrations of representative DEPs that were significantly upregulated in proteomics study were measured by ELISA using a separate cohort. Results: In total, 1594 proteins were identified in the vitreous humor of VRL, control, and sarcoidosis samples. Also, 282 DEPs were detected in VRL, 249 upregulated and 33 downregulated, compared with controls. Enrichment pathway analysis showed alterations in proteasome-related pathways. Compared to controls and sarcoidosis, 14 DEPs in VRL showed significant upregulation. In the validation study, ELISA confirmed significantly higher vitreous concentrations of PSAT1, YWHAG, and 20S/26S proteasome complex in VRL compared with controls and sarcoidosis. Among the upregulated DEPs, vitreous PITHD1 and NCSTN concentrations correlated positively with vitreous IL-10 concentrations. Conclusions: This study highlights aberrations in protein expression pattern in the vitreous of patients with VRL. The DEPs identified in this study may play pivotal roles in VRL pathogenesis, providing insights to enhance understanding of VRL pathophysiology and contribute to the development of VRL biomarkers.

Comprehensive Proteomic Profiling of Vitreous Humor in Ocular Sarcoidosis Compared with Other Vitreoretinal Diseases.

Ocular sarcoidosis is an inflammatory disease that manifests as uveitis, and is often difficult to distinguish from other forms of uveitis based on nonspecific findings alone. Comprehensive proteomic analyses of vitreous humor using LC-MS/MS were performed in each patient with ocular sarcoidosis, vitreoretinal lymphoma (VRL), and controls with epiretinal membrane or macular hole. Differential expression proteins (DEPs) were identified by comparing with VRL and controls, and functional pathway analysis was performed. The candidate biomarker proteins for ocular sarcoidosis were validated using enzyme-linked immunosorbent assay. A total of 1590 proteins were identified in all samples. Of these, 290 and 174 DEPs were detected in vitreous of ocular sarcoidosis compared with controls and VRL, respectively. Enrichment pathway analysis revealed that pathways related to the immune system were most upregulated. Validation of two candidate biomarkers for ocular sarcoidosis, neutrophil gelatinase-associated lipocalin (NGAL) and junctional adhesion molecules B (JAMB), confirmed upregulated NGAL and JAMB protein expressions in ocular sarcoidosis compared to controls and VRL. The results of this study revealed that altered vitreous protein expression levels may discriminate ocular sarcoidosis from other uveitis diseases. Vitreous NGAL and JAMB are potential biomarkers and may serve as an auxiliary tool for the diagnosis of ocular sarcoidosis.

Machine Learning Approach for Intraocular Disease Prediction Based on Aqueous Humor Immune Mediator Profiles.

PURPOSE: Various immune mediators have crucial roles in the pathogenesis of intraocular diseases. Machine learning can be used to automatically select and weigh various predictors to develop models maximizing predictive power. However, these techniques have not yet been applied extensively in studies focused on intraocular diseases. We evaluated whether 5 machine learning algorithms applied to the data of immune-mediator levels in aqueous humor can predict the actual diagnoses of 17 selected intraocular diseases and identified which immune mediators drive the predictive power of a machine learning model. DESIGN: Cross-sectional study. PARTICIPANTS: Five hundred twelve eyes with diagnoses from among 17 intraocular diseases. METHODS: Aqueous humor samples were collected, and the concentrations of 28 immune mediators were determined using a cytometric bead array. Each immune mediator was ranked according to its importance using 5 machine learning algorithms. Stratified k-fold cross-validation was used in evaluation of algorithms with the dataset divided into training and test datasets. MAIN OUTCOME MEASURES: The algorithms were evaluated in terms of precision, recall, accuracy, F-score, area under the receiver operating characteristic curve, area under the precision-recall curve, and mean decrease in Gini index. RESULTS: Among the 5 machine learning models, random forest (RF) yielded the highest classification accuracy in multiclass differentiation of 17 intraocular diseases. The RF prediction models for vitreoretinal lymphoma, acute retinal necrosis, endophthalmitis, rhegmatogenous retinal detachment, and primary open-angle glaucoma achieved the highest classification accuracy, precision, and recall. Random forest recognized vitreoretinal lymphoma, acute retinal necrosis, endophthalmitis, rhegmatogenous retinal detachment, and primary open-angle glaucoma with the top 5 F-scores. The 3 highest-ranking relevant immune mediators were interleukin (IL)-10, interferon-γ-inducible protein (IP)-10, and angiogenin for prediction of vitreoretinal lymphoma; monokine induced by interferon γ, interferon γ, and IP-10 for acute retinal necrosis; and IL-6, granulocyte colony-stimulating factor, and IL-8 for endophthalmitis. CONCLUSIONS: Random forest algorithms based on 28 immune mediators in aqueous humor successfully predicted the diagnosis of vitreoretinal lymphoma, acute retinal necrosis, and endophthalmitis. Overall, the findings of the present study contribute to increased knowledge on new biomarkers that potentially can facilitate diagnosis of intraocular diseases in the future.

Differential Tissue Metabolic Signatures in IgG4-Related Ophthalmic Disease and Orbital Mucosa-Associated Lymphoid Tissue Lymphoma.

Purpose: To identify tissue metabolomic profiles in biopsy specimens with IgG4-related ophthalmic disease (IgG4-ROD) and mucosa-associated lymphoid tissue (MALT) lymphoma and investigate their potential implication in the disease pathogenesis and biomarkers. Methods: We conducted a comprehensive analysis of the metabolomes and lipidomes of biopsy-proven IgG4-ROD (n = 22) and orbital MALT lymphoma (n = 21) specimens and matched adjacent microscopically normal adipose tissues using liquid chromatography time-of-flight mass spectrometry. The altered metabolomic profiles were visualized by heat map and principal component analysis. Metabolic pathway analysis was performed by Metabo Analyst 4.0 using differentially expressed metabolites. The diagnostic performance of the metabolic markers was evaluated using receiver operating characteristic curves. Machine learning algorithms were implemented by random forest using the R environment. Finally, an independent set of 18 IgG4-ROD and 17 orbital MALT lymphoma specimens were used to validate the identified biomarkers. Results: The principal component analysis showed a significant difference of both IgG4-ROD and orbital MALT lymphoma for biopsy specimens and controls. Interestingly, lesions in IgG4-ROD were uniquely enriched in arachidonic metabolism, whereas those in orbital MALT lymphoma were enriched in tricarboxylic acid cycle metabolism. We identified spermine as the best discriminator between IgG4-ROD and orbital MALT lymphoma, and the area under the receiver operating characteristic curve of the spermine to discriminate between the two diseases was 0.89 (95% confidence interval, 0.803-0.984). A random forest model incorporating a panel of five metabolites showed a high area under the receiver operating characteristic curve value of 0.983 (95% confidence interval, 0.981-0.984). The results of validation revealed that four tissue metabolites: N1,N12-diacetylspermine, spermine, malate, and glycolate, had statistically significant differences between IgG4-ROD and orbital MALT lymphoma with receiver operating characteristic values from 0.708 to 0.863. Conclusions: These data revealed the characteristic differences in metabolomic profiles between IgG4-ROD and orbital MALT lymphoma, which may be useful for developing new diagnostic biomarkers and elucidating the pathogenic mechanisms of these common orbital lymphoproliferative disorders.

Serum Metabolomic Profiling of Patients with Non-Infectious Uveitis.

The activities of various metabolic pathways can influence the pathogeneses of autoimmune diseases, and intrinsic metabolites can potentially be used to diagnose diseases. However, the metabolomic analysis of patients with uveitis has not yet been conducted. Here, we profiled the serum metabolomes of patients with three major forms of uveitis (BehÒ«et's disease (BD), sarcoidosis, and Vogt-Koyanagi-Harada disease (VKH)) to identify potential biomarkers. This study included 19 BD, 20 sarcoidosis, and 15 VKH patients alongside 16 healthy control subjects. The metabolite concentrations in their sera were quantified using liquid chromatography with time-of-flight mass spectrometry. The discriminative abilities of quantified metabolites were evaluated by four comparisons: control vs. three diseases, and each disease vs. the other two diseases (such as sarcoidosis vs. BD + VKH). Among 78 quantified metabolites, 24 kinds of metabolites showed significant differences in these comparisons. Four multiple logistic regression models were developed and validated. The area under the receiver operating characteristic (ROC) curve (AUC) in the model to discriminate disease groups from control was 0.72. The AUC of the other models to discriminate sarcoidosis, BD, and VKH from the other two diseases were 0.84, 0.83, and 0.73, respectively. This study provides potential diagnostic abilities of sarcoidosis, BD, and VKH using routinely available serum samples that can be collected with minimal invasiveness.

Comprehensive Gene Analysis of IgG4-Related Ophthalmic Disease Using RNA Sequencing.

High-throughput RNA sequencing (RNA-seq) uses massive parallel sequencing technology, allowing the unbiased analysis of genome-wide transcription levels and tumor mutation status. Immunoglobulin G4-related ophthalmic disease (IgG4-ROD) is a fibroinflammatory disease characterized by the enlargement of the ocular adnexal tissues. We analyzed RNA expression levels via RNA-seq in the biopsy specimens of three patients diagnosed with IgG4-ROD. Mucosa-associated lymphoid tissue (MALT) lymphoma, reactive lymphoid hyperplasia (RLH), normal lacrimal gland tissue, and adjacent adipose tissue were used as the controls (n = 3 each). RNA-seq was performed using the NextSeq 500 system, and genes with |fold change| ≥ 2 and p < 0.05 relative to the controls were defined as differentially expressed genes (DEGs) in IgG4-ROD. To validate the results of RNA-seq, real-time polymerase chain reaction (PCR) was performed in 30 IgG4-ROD and 30 orbital MALT lymphoma tissue samples. RNA-seq identified 35 up-regulated genes, including matrix metallopeptidase 12 (MMP12) and secreted phosphoprotein 1 (SPP1), in IgG4-ROD tissues when compared to all the controls. Many pathways related to the immune system were included when compared to all the controls. Expressions of MMP12 and SPP1 in IgG4-ROD tissues were confirmed by real-time PCR and immunohistochemistry. In conclusion, we identified novel DEGs, including those associated with extracellular matrix degradation, fibrosis, and inflammation, in IgG4-ROD biopsy specimens. These data provide new insights into molecular pathogenetic mechanisms and may contribute to the development of new biomarkers for diagnosis and molecular targeted drugs.

Comprehensive miRNA Analysis Using Serum From Patients With Noninfectious Uveitis.

Purpose: MicroRNAs (miRNAs) are noncoding RNAs and have attracted attention as a biomarker in a variety of diseases. However, extensive unbiased miRNAs analysis in patients with uveitis has not been completely explored. In the present study, we comprehensively analyzed the deregulated miRNAs in three major forms of uveitis (BehÒ«et's disease [BD], sarcoidosis and Vogt-Koyanagi-Harada disease [VKH]) to search for potential biomarkers. Methods: This study included 10 patients with BD, 17 patients with sarcoidosis, and 13 patients with VKH. Eleven healthy subjects were used as controls. The miRNAs expression levels were studied by microarray using serum samples from patients with uveitis and healthy controls. Results: A total of 281 upregulated miRNAs and 137 downregulated miRNAs were detected in patients with BD, 35 upregulated miRNAs and 86 downregulated miRNAs in patients with sarcoidosis, and 153 upregulated miRNAs and 35 downregulated miRNAs in patients with VKH. Some deregulated miRNAs were involved in the mitogen-activated protein kinase signaling pathway and inflammatory cytokine pathways. Furthermore, we identified miR-4708-3p, miR-4323, and let-7g-3p as the best predictor miRNAs for BD, sarcoidosis, and VKH, respectively. Panels of miRNAs with diagnostic potential for the three diseases were generated using machine learning. Conclusions: In this study, comprehensive miRNA analysis identified deregulated miRNAs in three major forms of noninfectious uveitis. This study provides new insights into molecular pathogenetic mechanisms and useful information toward developing novel diagnostic biomarkers and therapeutic targets for BD, sarcoidosis, and VKH.

Distinctive Tissue and Serum MicroRNA Profile of IgG4-Related Ophthalmic Disease and MALT Lymphoma.

The molecular pathogenesis of orbital lymphoproliferative disorders, such as immunoglobulin G4-related ophthalmic disease (IgG4-ROD) and orbital mucosa-associated lymphoid tissue (MALT) lymphoma, remains essentially unknown. Differentiation between the two disorders, which is important since the work-up and treatment can vary greatly, is often challenging due to the lack of specific biomarkers. Although miRNAs play an important role in the regulation of carcinogenesis and inflammation, the relationship between miRNA and orbital lymphoproliferative diseases remains unknown. We performed a comprehensive analysis of 2565 miRNAs from biopsy and serum specimens of 17 cases with IgG4-ROD, where 21 cases with orbital MALT lymphoma were performed. We identified specific miRNA signatures and their miRNA target pathways, as well as the network analysis for IgG4-ROD and orbital MALT lymphoma. Machine-learning analysis identified miR-202-3p and miR-7112-3p as the best discriminators of IgG4-ROD and orbital MALT lymphoma, respectively. Enrichment analyses of biological pathways showed that the longevity-regulating pathway in IgG4-ROD and the mitogen-activated protein kinase (MAPK) signaling pathway in orbital MALT lymphoma was most enriched by target genes of downregulated miRNAs. This is the first evidence of miRNA profiles of biopsy and serum specimens of patients with IgG4-ROD and orbital MALT lymphoma. These data will be useful for developing diagnostic and therapeutic interventions, as well as elucidating the pathogenesis of these disorders.

High-Throughput MicroRNA Profiling of Vitreoretinal Lymphoma: Vitreous and Serum MicroRNA Profiles Distinct from Uveitis.

PURPOSE: Vitreoretinal lymphoma (VRL) is a non-Hodgkin lymphoma of the diffuse large B cell type (DLBCL), which is an aggressive cancer causing central nervous system related mortality. The pathogenesis of VRL is largely unknown. The role of microRNAs (miRNAs) has recently acquired remarkable importance in the pathogenesis of many diseases including cancers. Furthermore, miRNAs have shown promise as diagnostic and prognostic markers of cancers. In this study, we aimed to identify differentially expressed miRNAs and pathways in the vitreous and serum of patients with VRL and to investigate the pathogenesis of the disease. MATERIALS AND METHODS: Vitreous and serum samples were obtained from 14 patients with VRL and from controls comprising 40 patients with uveitis, 12 with macular hole, 14 with epiretinal membrane, 12 healthy individuals. The expression levels of 2565 miRNAs in serum and vitreous samples were analyzed. RESULTS: Expression of the miRNAs correlated significantly with the extracellular matrix (ECM) ‒receptor interaction pathway in VRL. Analyses showed that miR-326 was a key driver of B-cell proliferation, and miR-6513-3p could discriminate VRL from uveitis. MiR-1236-3p correlated with vitreous interleukin (IL)-10 concentrations. Machine learning analysis identified miR-361-3p expression as a discriminator between VRL and uveitis. CONCLUSIONS: Our findings demonstrate that aberrant microRNA expression in VRL may affect the expression of genes in a variety of cancer-related pathways. The altered serum miRNAs may discriminate VRL from uveitis, and serum miR-6513-3p has the potential to serve as an auxiliary tool for the diagnosis of VRL.

Clinical Analysis of Uveal Melanoma.

Purpose: To clarify clinical features of patients with uveal melanoma. Method: We analyzed 125 eyes of 125 patients diagnosed as uveal melanoma from 1992 to 2014 retrospectively. Results: The mean age of the patients at the time of diagnosis was 58.1±14.4 years. Tumors were originated in the choroid (93%), ciliary body (4%) and iris (3%). The main reasons leading to diagnosis included decreased vision (27%), visual field loss (17%), and no significant symptoms (16%). Average tumor size of the choroidal melanoma was 10.4 mm in largest basal diameter and 7.2 mm in height. Treatment included enucleation of eyeball (53 cases), local resection of the tumor (4 cases), heavy particle beam therapy (18 cases), and brachytherapy (4 cases). Extraocular metastasis was detected in 22% of the patients, and 89% of them died within 5 years. Five-year survival rate was 20% in 6 cases (13.6%) in whom histopathologic studies revealed extrascleral invasions. Conclusions: Prognosis of patients with metastatic uveal melanoma is extremely poor. Early diagnosis and treatment, and establishment of follow-up system after local treatment are critical. Further development and dissemination of novel treatment for metastatic melanoma is desired.