Proteomic Study of Aqueous Humor and Its Application in the Treatment of Neovascular Glaucoma

Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases

Purpose

To assess the impact of ocular confounding factors on aqueous humor (AH) proteomic and metabolomic analyses for retinal disease characterization.

Methods

This study recruited 138 subjects (eyes): 102 with neovascular age-related macular degeneration (nAMD), 18 with diabetic macular edema (DME), and 18 with cataract (control group). AH samples underwent analysis using Olink Target 96 proteomics and Metabolon's metabolomics platform Data analysis included correlation, differential abundance, and gene-set analysis.

Results

In total, 756 proteins and 408 metabolites were quantified in AH. Total AH protein concentration was notably higher in nAMD (3.2-fold) and DME (4.1-fold) compared to controls. Pseudophakic eyes showed higher total AH protein concentrations than phakic eyes (e.g., 1.6-fold in nAMD) and a specific protein signature indicative of matrix remodeling. Unexpectedly, pupil-dilating drugs containing phenylephrine/tropicamide increased several AH proteins, notably interleukin-6 (5.4-fold in nAMD). Correcting for these factors revealed functionally relevant protein correlation clusters and disease-relevant, differentially abundant proteins across the groups. Metabolomics analysis, for which the relevance of confounder adjustment was less apparent, suggested insufficiently controlled diabetes and chronic hyperglycemia in the DME group.

Conclusions

AH protein concentration, pseudophakia, and pupil dilation with phenylephrine/tropicamide are important confounding factors for AH protein analyses. When these factors are considered, AH analyses can more clearly reveal disease-relevant factors.

Translational Relevance

Considering AH protein concentration, lens status, and phenylephrine/tropicamide administration as confounders is crucial for accurate interpretation of AH protein data.

Analysis aqueous humor lipid profile of neovascular glaucoma secondary to diabetic retinopathy and lipidomic alteration response to anti-VEGF treatment

The objective of this study was to examine the lipid spectrum of aqueous humor (AH) in patients with neovascular glaucoma (NVG) secondary to proliferative diabetic retinopathy and to investigate the lipid alteration response to anti-vascular endothelial growth factor (anti-VEGF) treatment. Lipidomic analysis using ultra-high performance liquid chromatography-tandem mass spectrometry was conducted to compare the lipid profiles of the AH in NVG patients with those of a control group. Lipid changes in the AH of NVG patients before and after intravitreal conbercept injections were also evaluated. The identification of lipids showing differential expression was accomplished through both multivariate and univariate analyses. This study included 13 NVG patients and 20 control subjects. Based on LipidSearch software, 639 lipid species across 33 lipid classes were detected in the participants' AH. The combination of univariate and multivariate statistical analyses yielded 53 differentially expressed lipids (VIP >1 and P < 0.05). In addition, 9 lipids were found to be differentially expressed before and after the intravitreal conbercept injections in the NVG patients. Significant alterations in the metabolic pathways of glycerophospholipid and glycerolipid exhibited notable changes. Our results highlighted the lipid changes in patients' AH in relation to the progression of NVG, and indicated that the modified lipids could potentially be utilized as therapeutic targets for NVG.

AHP DB: a reference database of proteins in the human aqueous humor

The aqueous humor (AH) is a low-viscosity biofluid that continuously circulates from the posterior chamber to the anterior chamber of the eye. Recent advances in high-resolution mass-spectrometry workflows have facilitated the study of proteomic content in small-volume biofluids like AH, highlighting the potential clinical implications of the AH proteome. Nevertheless, in-depth investigations into the role of AH proteins in ocular diseases have encountered challenges due to limited accessibility to these workflows, difficulties in large-scale AH sample collection and the absence of a reference AH proteomic database. In response to these obstacles, and to promote further research on the involvement of AH proteins in ocular physiology and pathology, we have developed the web-based Aqueous Humor Proteomics Database (AHP DB). The current version of AHP DB contains proteomic data from 307 human AH samples, which were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The database offers comprehensive information on 1683 proteins identified in the AH samples. Furthermore, relevant clinical data are provided for each analyzed sample. Researchers also have the option to download these datasets individually for offline use, rendering it a valuable resource for the scientific community. Database URL: https://ahp.augusta.edu/.

Complement System Proteins in the Human Aqueous Humor and Their Association with Primary Open-Angle Glaucoma

This study discovers the complement protein profile in the aqueous humor (AH) of human subjects and investigates its association with primary open-angle glaucoma (POAG) pathogenesis. Among the 32 complement proteins identified, 22 were highly abundant and detected in more than 50% of AH samples. The most predominant active complement proteins in the AH are C3, C4B, C4A, CFB, CFD, and C9. Additionally, the most prevalent complement regulators and receptors include CLU, SERPING1, F2, CFH, CFI, and VTN. Significant alterations in complement proteins were observed in individuals with POAG compared to those with cataracts. Specifically, complement protein F2 was upregulated, while C8G, C6, and CFH were downregulated in POAG samples. Stratification of the samples by race and sex revealed distinct alterations of complement proteins in patients with POAG. In the African American cohort, five complement proteins (C4A, C4B, F2, C7, and C3) were upregulated in POAG compared to cataract patients. In the Caucasian cohort, eight complement proteins (C3, SERPING1, CFI, CLU, CFHR1, C8G, C6, and CFH) were downregulated in the POAG samples compared to the cataract samples. Within the male cohort, three complement proteins (CLU, C6, and CFH) were downregulated in POAG patients compared to those with cataracts. Whereas, within the female cohort, two complement proteins (C4B and F2) were upregulated and one (C8G) downregulated in the POAG samples when compared to cataracts. Discerning these changes in the AH complement protein profile will assist in the development of tailored therapies to modulate the complement system for managing ocular disorders. These insights may also lead to novel biomarkers for diagnosing and monitoring disease progression.

Proteomic Study of Middle Ear Effusion and Its Clinical Application for Otitis Media with Effusion

Background

Proteins found in middle ear effusion play crucial roles in the physiological and pathological processes of otitis media with effusion (OME), influencing the etiology and clinical characteristics of this disease. The qualitative and quantitative composition of these proteins depending on the underlying pathogenesis of middle ear effusion. Understanding their physiological and pathological functions is of great importance.

Methods

We collected samples from 19 volunteers diagnosed with OME. After offline separation using high-pH reversed-phase liquid chromatography (RPLC), the pooled sample was subjected to LC-MS/MS analysis to obtain a comprehensive profile of the OME proteome. Functional analysis was performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Ingenuity Pathway Analysis (IPA) annotations. Data-independent acquisition (DIA) technology was utilized to analyze samples and fix whether the OME proteome could replicate the pathophysiological features associated with this disease. We conducted a differential proteomic analysis between patients with simple OME and patients who had received radiotherapy. The radiotherapy-reduced group was further divided into two subgroups: nasopharyngeal carcinoma (NPC) and other types of carcinoma. Parallel reaction monitoring (PRM) technology was used for validation of 36 differentially expressed proteins (DEPs).

Results

A number of 732 proteins were identified in the OME proteome database. Among them, 527 proteins were quantified using peak intensity-based semi-quantification (iBAQ), covering a wide dynamic range of approximately 8 orders of magnitude. Based on the functional analysis, we proposed a hypothetical mechanism of OME.

Conclusion

This study managed to put up an inclusive analysis of the OME proteome, establishing the first human OME proteome database. We focused on differential proteomic analysis among different groups to gain a more comprehensive concept of the OME proteome and search for meaningful biomarkers.

Infrared analysis in the aqueous humor of patients with uveitis: Preliminary results

Inflammatory processes affecting the uvea result in a temporary o permanent blurred vision and represent an important cause of visual impairment worldwide. It is often hard to make a precise diagnosis which is dependent on the clinical expertise, diagnostic tests, laboratory investigations in blood and sometimes in the aqueous humor (AH). With the aim of obtaining proof of principle Fourier Transformed Infrared (FT-IR) absorbance spectroscopy was applied to study the molecular composition of 72 AH samples collected in 26 patients with uveitis and in 44 controls. The unsupervised exploration of the internal structure of the dataset by principal component analysis reduced hundreds IR variables to those most representative allowing to obtain the predictive model that distinguished the AH spectra of patients with uveitis from controls. The same result was obtained by unsupervised agglomerative cluster analysis. After labeling the spectra with some clinical information it was observed that most severe uveitis with active processes were grouped separately from chronic and relapsing uveitis and controls. The consistence of prediction models is discussed in the light of supporting etiological diagnosis by machine learning processes. In conclusion, proof of principle has been obtained that the IR spectral pattern of AH may reflect particular uveal diseases.

Proteomic and Metabolomic Analyses of Right Ventricular Failure due to Pulmonary Arterial Hypertension

Right ventricular failure (RVF) is the independent and strongest predictor of mortality in pulmonary arterial hypertension (PAH), but, at present, there are no preventive and therapeutic strategies directly targeting the failing right ventricle (RV). The underlying mechanism of RV hypertrophy (RVH) and dysfunction needs to be explored in depth. In this study, we used myocardial proteomics combined with metabolomics to elucidate potential pathophysiological changes of RV remodeling in a monocrotaline (MCT)-induced PAH rat model. The proteins and metabolites extracted from the RV myocardium were identified using label-free liquid chromatography–tandem mass spectrometry (LC-MS/MS). The bioinformatic analysis indicated that elevated intracellular Ca²⁺ concentrations and inflammation may contribute to myocardial proliferation and contraction, which may be beneficial for maintaining the compensated state of the RV. In the RVF stage, ferroptosis, mitochondrial metabolic shift, and insulin resistance are significantly involved. Dysregulated iron homeostasis, glutathione metabolism, and lipid peroxidation related to ferroptosis may contribute to RV decompensation. In conclusion, we depicted a proteomic and metabolomic profile of the RV myocardium during the progression of MCT-induced PAH, and also provided the insights for potential therapeutic targets facilitating the retardation or reversal of RV dysfunction in PAH.

COVID-19 Variants and Transfer Learning for the Emerging Stringency Indices

The pandemics in the history of world health organization have always left memorable hallmarks, on the health care systems and on the economy of highly effected areas. The ongoing pandemic is one of the most harmful pandemics and is threatening due to its transformation to more contiguous variants. Here in this manuscript, we will first outline the variants and then their impact on the associated health issues. The deep learning algorithms are useful in developing models, from a higher dimensional problem/ dataset, but these algorithms fail to provide insight during the training process and do not generalize the conditions. Transfer learning, a new subfield of machine learning has acquired fame due to its ability to exploit the information/learning gained from a previous process to improve generalization for the next. In short, transfer learning is the optimization of the stored knowledge. With the aid of transfer learning, we will show that the stringency index and cardiovascular death rates were the most important and appropriate predictors to develop the model for the forecasting of the COVID-19 death rates.

Blood and aqueous humor phoenixin, endocan and spexin in patients with diabetes mellitus and cataract with and without diabetic retinopathy

Peptide phoenixin (PNX), endocan (EDC), and spexin (SPX) are associated with diabetes. Therefore, the purpose of this study was to investigate the levels of PNX, EDC and SPX in the blood and aqueous humor (AH) of patient with type 2 diabetes with and without DRP and cataract. 30 type 2 diabetes patients with cataract (DM + C), 30 DRP patient with cataract (DRP + C), 30 non-diabetic patient with only cataract and 30 control participants were enrolled into this study. PNX, EDC, and SPX were measured in blood and AH by ELISA. In patients with DRP + C, the levels of PNX and EDC were significantly higher in both AH and blood samples compared with the group of patients without DRP + C (<0.05). Also, in patients with DM + C, the levels of PNX and EDC were higher in both AH and blood samples compared with the group of patients without DM + C. However, in patients with DRP + C, the levels of SPX were significantly lower in both AH and blood samples compared with the group of patients without DRP + C (<0.05). Also, in patients with DM + C, the levels of SPX were also lower in both AH and blood samples compared with the group of patients without DM + C. These findings suggest that increased PNX, EDC, and decreased SPX amounts in blood and AH of DM + C and DRP + C groups when compared with control and cataract groups show that they might have a role in the pathophysiology of DM + C, especially in the DRP + C.

Aqueous humor proteomic analysis of acute angle-closure glaucoma with visual field loss

Background

Acute angle-closure glaucoma (AACG) is an ophthalmic emergency that occurs over the course of hours or days and may cause irreversible blindness if not treated immediately. In most cases, optic nerve damage is the cause of visual field (VF) loss in AACG. There has been no reliable biomarker found to evaluate optic nerve damage to date. Aqueous humor (AH) proteome analysis might reveal the proteomic alterations in AACG and provide helpful clues in the search for an AH biomarker of optic nerve damage and VF loss.

Methods

In this study, we used the AH proteome to explore the functions of differentially expressed proteins (DEPs) during disease progression. The AH proteins from the early-stage group and late-stage group were extracted and analyzed by the data-independent acquisition (DIA) method. The DEPs functions were annotated, and parallel reaction monitoring (PRM) was used to validate the key DEPs.

Results

A total of 87 DEPs were found. Gene Ontology analysis showed that most DEPs were enriched in immunology, hemodynamics, and apoptosis. Ingenuity pathway analysis found that vascular endothelial growth factor (VEGF) signaling, the production of reactive oxygen species (ROS) in macrophages, and the nuclear factor erythroid 2-related factor 2 (NRF2)-mediated oxidative stress response were active pathways in the late stage of AACG. The mechanism of retinal ganglion cell (RGC) death was hypothesized on the basis of DEP functional analysis. A total of 20 DEPs were validated by using PRM, and prostaglandin-H2 D-isomerase was found to have the potential to evaluate optic nerve damage.

Conclusions

This study showed that AH proteomic analysis could reveal the proteomic alterations in the pathogenesis of VF loss in AACG and help to provide objective protein biomarkers to evaluate VF loss. These findings will benefit the application of the AH proteome to clinical research.

Forecasting the action of CAR-T cells against SARS-corona virus-II infection with branching process

The CAR-T cells are the genetically engineered T cells, designed to work specifically for the virus antigens (or other antigens, such as tumour specific antigens). The CAR-T cells work as the living drug and thus provides an adoptive immunotherapy strategy. The novel corona virus treatment and control designs are still under clinical trials. One of such techniques is the injection of CAR-T cells to fight against the COVID-19 infection. In this manuscript, the hypothesis is based on the CAR-T cells, that are suitably engineered towards SARS-2 viral antigen, by the N protein. The N protein binds to the SARS-2 viral RNA and is found in abundance in this virus, thus for the engineered cell research, this protein sequence is chosen as a potential target. The use of the sub-population of T-reg cells is also outlined. Mathematical modeling of such complex line of action can help to understand the dynamics. The modeling approach is inspired from the probabilistic rules, including the branching process, the Moran process and kinetic models. The Moran processes are well recognized in the fields of artificial intelligence and data science. The model depicts the infectious axis “virus—CAR-T cells—memory cells”. The theoretical analysis provides a positive therapeutic action; the delay in viral production may have a significant impact on the early stages of infection. Although it is necessary to carefully evaluate the possible side effects of therapy. This work introduces the possibility of hypothesizing an antiviral use by CAR-T cells.

Furin and the adaptive mutation of SARS-COV2: a computational framework

SARS-2 virus has reached its most harmful mutated form and has damaged the world’s economy, integrity, health system and peace to a limit. An open problem is to address the release of antibodies after the infection and after getting the individuals vaccinated against the virus. The viral fusion process is linked with the furin enzyme and the adaptation is linked with the mutation, called D614G mutation. The cell-protein studies are extremely challenging. We have developed a mathematical model to address the process at the cell-protein level and the delay is linked with this biological process. Genetic algorithm is used to approximate the parametric values. The mathematical model proposed during this research consists of virus concentration, the infected cells count at different stages and the effect of interferon. To improve the understanding of this model of SARS-CoV2 infection process, the action of interferon (IFN) is quantified using a variable for the non-linear mathematical model, that is based on a degradation parameter \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma$$\end{document}γ. This parameter is responsible for the delay in the dynamics of this viral action. We emphasize that this delay responds to the evasion by SARS-CoV2 via antagonizing IFN production, inhibiting IFN signaling and improving viral IFN resistance. We have provided videos to explain the modeling scheme.

Forecasting the impact of environmental stresses on the frequent waves of COVID19

A novel approach to link the environmental stresses with the COVID-19 cases is adopted during this research. The time-dependent data are extracted from the online repositories that are freely available for knowledge and research. Since the time series data analysis is desired for the COVID-19 time-dependent frequent waves, here in this manuscript, we have developed a time series model with the aid of "nonlinear autoregressive network with exogenous inputs (NARX)" approach. The distribution of infectious agent-containing droplets from an infected person to an uninfected person is a common form of respiratory disease transmission. SARS-CoV-2 has mainly spread via short-range respiratory droplet transmission. Airborne transmission of SARS-CoV-2 seems to have occurred over long distances or times in unusual conditions; SARS-CoV-2 RNA was found in PM10 collected in Italy. This research shows that SARS-CoV-2 particles adsorbed to outdoor PM remained viable for a long time, given the epidemiology of COVID-19, outdoor air pollution is unlikely to be a significant route of transmission. In this research, ANN time series is used to analyze the data resulting from the COVID-19 first and second waves and the forecasted results show that air pollution affects people in different areas of Italy and make more people sick with covid-19. The model is developed based on the disease transmission data of Italy.