Biology subjects

Prasanna, G.

Publications and source records attributed to Prasanna, G..

5 recordsLinked to original sources

bioRxiv2025

Identification of cellular and molecular risk signatures for progression to late-stage age-related macular degeneration using the 9-step Minnesota Grading System

Age-related macular degeneration (AMD) is a complex multifactorial disease, and the molecular mechanisms underpinning the progression of intermediate AMD to geographic atrophy are not fully understood. To better understand mechanisms driving progression, we performed bulk RNA sequencing on dissected macular and peripheral RPE/choroid and neural retina tissue from postmortem human eyes graded using the 9-step Minnesota Grading System (MGS). Binning of intermediate AMD cases into three distinct groups (AMD3L, AMD3M, AMD3H) based on the 5-year risk of progression enabled identification of distinct gene and pathway changes associated with progression to late-stage disease. Identified changes in gene expression were validated using ELISA or histological methods. RPE-specific genes and lipid metabolic pathways showed a transient increase in AMD3L followed by a pronounced decrease in AMD3H. In AMD3H, immune response genes such as C3, TREM2, and OLR1 were upregulated when compared to AMD3L samples, as well as genes specific to Muller glia/astrocytes (NGFR, SPP1, GPX3). Our findings support complement inhibition as a promising therapeutic option for slowing conversion to advanced AMD and identify macrophage and Muller/astrocyte genes as potential cell types to target in AMD. Further, we demonstrate the value of combining emerging, outcomes-based, clinically relevant grading systems with profiling technologies to generate new insights into ocular diseases. HighlightsO_LIIntermediate AMD (AMD3) can be further divided into 3 stages - AMD3L (low risk), AMD3M (intermediate risk), AMD3H (high risk) - using the MGS9 grading system based on the risk of disease progression to late AMD. C_LIO_LIRNA sequencing of the macular RPE/choroid shows opposing changes in gene expression of multiple biological pathways for both RPE and immune cells between AMD3L and AMD3H stages. C_LIO_LIIn the macular neural retina, most biological pathways were downregulated in AMD2 (early AMD) but upregulated in AMD4 (late AMD) compared to AMD1 (non-AMD control). C_LIO_LIMolecular and cellular signatures associated with a high risk of progression to AMD4 include activation of complement C3, two subtypes of macrophages expressing either TREM2 or OLR1, and Muller glia/astrocytes as evidenced by the upregulation of GFAP and NGFR. C_LIO_LIUnderstanding the roles of these high-risk associated genes in AMD progression will facilitate the development of new treatments that prevent or delay the irreversible central vision loss in AMD patients. C_LI

neuroscience↗

bioRxiv2024

Use of machine learning for quantification of retinal pigment epithelium tight junctions improves assay sensitivity

The retinal pigment epithelium (RPE) is critical for maintaining outer retinal barrier homeostasis. In age-related macular degeneration (AMD), the RPE can undergo a dedifferentiation process that includes tight junction (TJ) loss and displacement of zonula occludens-1 (ZO-1), which may impair structural and functional integrity of the RPE barrier and contribute to disease pathogenesis. Our objective was to develop an automated and sensitive quantification method for TJ aberrations in an RPE immunofluorescence imaging assay, following treatment with TNF or TGF{beta}2. However, quantifying ZO-1 morphological changes in the RPE using standard image analysis methods did not provide a satisfactory assay window. To address this challenge, we developed an imaging assay to quantify ZO-1 changes using a machine learning approach, enabling enhanced phenotypic characterization of the ZO-1 changes in RPE cells and improved assay sensitivity. We were also able to capture and quantify the reversal of these changes using etanercept, an TNF inhibitor, with this imaging assay. Our findings indicated that this machine learning ZO-1 quantification assay could serve as a potential phenotypic readout for RPE dedifferentiation and enabling large-scale mechanistic studies.

bioinformatics↗

bioRxiv2024

Multiparametric grading of glaucoma severity by histopathology can enable post-mortem substratification of disease state

Neurodegeneration in glaucoma patients is clinically identified through longitudinal assessment of structure-function changes, including intraocular pressure, cup-to-disc ratios from fundus images, and optical coherence tomography imaging of the retinal nerve fiber layer. Use of human post-mortem ocular tissue for basic research is rising in the glaucoma field, yet there are challenges in assessing disease stage and severity, since tissue donations with informed consent are often unaccompanied by detailed pre-mortem clinical information. Further, the interpretation of disease severity based solely on anatomical and morphological assessments by histology can be affected by differences in death-to-preservation time and tissue processing. These are difficult confounders that cannot be easily controlled. As pathogenesis and molecular mechanisms can vary depending on the stage and severity of glaucoma, there is a need for the field to maximize use of donated tissue to better understand the molecular mechanisms of glaucoma and develop new therapeutic hypotheses. Further, there is a lack of consensus around the molecular RNA and protein markers that can be used to classify glaucoma severity. Here, we describe a multiparametric grading system that combines structural measurements of the retinal nerve fiber layer with linear regression and principal component analyses of molecular markers of retinal ganglion cells and glia (RBPMS, NEFL, IBA1 and GFAP) to stratify post-mortem glaucoma eyes by the severity of disease. Our findings show that a quantitative grading approach can stratify post-mortem glaucoma samples with minimal clinical histories into at least three severity groups and suggest that this type of approach may be useful for researchers aiming to maximize insights derived from eye bank donor tissue.

pathology↗

bioRxiv2024

Biomarker Identification by Proteomic Analysis of Vitreous Humor and Plasma in Diabetic Retinopathy

ImportanceIdentify detectable plasma and/or vitreous signals to potentially predict diabetic retinopathy (DR) progression for earlier disease intervention. ObjectiveTo determine the mediators and potential disease progression biomarkers of DR in vitreous humor (VH) and plasma samples using the SomaScan proteome profiling platform. DesignDifferential expression analysis was conducted on VH and plasma samples using the SomaScan Assay. SettingA non-interventional study conducted to collect and analyze VH and plasma samples from patients with diabetic retinopathy. ParticipantsSamples from DR (60 nonproliferative diabetic retinopathy/NPDR, 60 proliferative diabetic retinopathy/PDR) and 60 control patients were collected. Main outcomes and MeasuresDifferentially expressed proteins between disease and control groups were identified. Pathway enrichment analysis was conducted to identify significantly perturbed pathways in DR. Finally, a random forest model was used to identify predictive biomarkers of disease progression. ResultsSomaScan v3 is a pooled aptamer hybridization assay using 5080 SOMAmers to probe over 4100 proteoforms in VH and plasma samples from 3 groups (control, NPDR, and PDR). The most profound protein content change was observed in the VH samples of PDR patients, while minimal changes were measured in plasma samples, highlighting the regionality of PDR pathogenesis. Many key molecules and molecular pathways such as VEGF-A, erythropoietin, and inflammation-associated proteins implicated in DR were significantly affected in the VH of PDR patients. In addition to the classic pathways (hypoxia, immune response, mTORC1 signaling) known to be involved in PDR, novel signaling pathways, including HEME metabolism and adipogenesis, were identified in VH samples. Application of a machine learning algorithm identified a panel of plasma PDR predictive biomarkers and revealed SCARA5 as the top one based on the largest average Gini decrease in the model. ConclusionOur study identified profound alteration of protein expression and molecular pathways in the VH of PDR patients, supporting the key role of local pathogenic changes in DR progression compared to systemic factors. Although the systemic changes related to DR were small, a few disease progression predictive candidate biomarkers (SCARA5, PTK7, FAM3Band FAM3D) were identified, prompting further investigation. Key PointsQuestion: Are plasma/ vitreous humor (VH) proteins predictive of diabetic retinopathy (DR) progression? Findings: This study identifies substantial protein changes in the VH of proliferative diabetic retinopathy (PDR) patients, while early nonproliferative DR (NPDR) patients show minimal change. We identify multiple proteins linked to angiogenesis, inflammation, immune cells (microglia/macrophage/neutrophil), and leukostasis associated with PDR and reveal a potential plasma panel of disease progression (from NPDR to PDR) biomarkers (SCARA5, PTK7, FAM3B, FAM3D). Meaning: Identified disease progression predictive biomarkers permits potential development of prognostic tools to identify individuals most at risk for PDR progression and offering reduced disease burden by earlier intervention.

physiology↗

bioRxiv2024

Proteomic profile analysis of plasma and aqueous humor from glaucoma and non-glaucomatous patients

PurposeGlaucoma, a multifactorial ocular neuropathy, can lead to irreversible vision loss. Diagnosis involves assessing optic cupping (increased cup-to-disc ratios) and structural changes (like retinal nerve fiber layer thinning) through clinical imaging. Elevated intraocular pressure (IOP) is commonly associated with glaucoma, but not always. However, understanding disease progression is hindered by limited access to donor ocular tissue and consistent clinical data. We hypothesize that the proteome of aqueous humor and plasma may be altered in disease and correlates with clinical parameters such as IOP and cup-to-disc ratios. MethodsAqueous humor (AH) and plasma samples were collected from 36 glaucoma patients (17 male, 19 female), and 35 non-glaucomatous control patients (16 male, 19 female) undergoing cataract surgery. The protein profile was compared using the SOMAscan(R) assay system for proteome profiling. From glaucomatous donors, correlations between IOP and cup- to-disc ratios to proteome differences were determined. ResultsOverall proteomics profiles between both AH and plasma were compared by combining all samples (glaucoma and non-glaucoma) and then performing correlation analyses. This study revealed similar protein abundance in the two biological fluids. Additionally, it identified different abundance of proteins in plasma and AH between glaucoma and non- glaucoma samples. The differential proteins identified were involved in pathways related to vascular integrity, inflammation, immune response, cell adhesion, and complement activation. Generally, glaucomatous AH showed higher protein levels. Neurofilament light chain (NEFL) protein correlated with elevated IOP and inflammatory markers, but not with cup-to-disc ratios. ConclusionsTogether, our data demonstrate that the proteins identified in this study from glaucomatous donors correspond to markers of neurodegeneration and those that may inhibit cell proliferation or disrupt vascular integrity.

cell biology↗