A Data Mining Metabolomics Exploration of Glaucoma

A Look into Ocular Diseases: The Pivotal Role of Omics Sciences in Ophthalmology Research

Precision medicine is a new medical approach which considers both population characteristics and individual variability to provide customized healthcare. The transition from traditional reactive medicine to personalized medicine is based on a biomarker-driven process and a deep knowledge of biological mechanisms according to which the development of diseases occurs. In this context, the advancements in high-throughput omics technologies represent a unique opportunity to discover novel biomarkers and to provide an unbiased picture of the biological system. One of the medical fields in which omics science has started to be recently applied is that of ophthalmology. Ocular diseases are very common, and some of them could be highly disabling, thus leading to vision loss and blindness. The pathogenic mechanism of most ocular diseases may be dependent on various genetic and environmental factors, whose effect has not been yet completely understood. In this context, large-scale omics approaches are fundamental to have a comprehensive evaluation of the whole system and represent an essential tool for the development of novel therapies. This Review summarizes the recent advancements in omics science applied to ophthalmology in the last ten years, in particular by focusing on proteomics, metabolomics and lipidomics applications from an analytical perspective. The role of high-efficiency separation techniques coupled to (high-resolution) mass spectrometry ((HR)MS) is also discussed, as well as the impact of sampling, sample preparation and data analysis as integrating parts of the analytical workflow.

Neuroprotective and anti-inflammatory effects of eicosane on glutamate and NMDA-induced retinal ganglion cell injury

AIM

To investigate the protective effects, antioxidant potential, and anti-inflammatory mechanisms of eicosane on glutamate-induced cell damage and on N-methyl-D-aspartate (NMDA)-induced retinal ganglion cell (RGC) injury in a mouse model of glaucoma.

METHODS

The protective effects of eicosane on the rat R28 retinal precursor cell line were assessed using cell counting kit-8 assays and Hoechst-propidium iodide staining. Intracellular reactive oxygen species (ROS) production was measured using the fluorescent probe 2'-7'-dichlorofluorescin diacetate and flow cytometry. The protective role of eicosane on NMDA-induced RGC injury in a mouse glaucoma model was determined by immunostaining of frozen sections of retina. The effects of eicosane on the metabolome of the retina in mice with NMDA-induced RGC damage were evaluated by liquid chromatography-mass spectroscopy (LC-MS) and untargeted metabolomics analyses.

RESULTS

Eicosane treatment significantly attenuated glutamate-induced damage to R28 cells in vitro. Eicosane also protected RGCs against NMDA-induced injury in a mouse glaucoma model. Untargeted metabolomics analyses showed that eicosane increased multiple metabolites, including L-arginine and L-carnitine, in the retina.

CONCLUSION

Eicosane has protective effects, antioxidant potential, and anti-inflammatory properties in an in vitro model of glutamate-induced cell damage and in an in vivo model of NMDA-induced RGC injury in mouse glaucoma through modulation of L-arginine and/or L-carnitine metabolism.

Identification of a circulating three-miRNA panel for the diagnosis of primary open angle glaucoma

PURPOSE

Conventional diagnosis of primary open angle glaucoma (POAG) needs a combination of ophthalmic examinations. An efficient assay is urgently needed for a timely POAG diagnosis. We aim to explore differential expressions of circulating microRNAs (miRNA) and provide novel miRNA biomarkers for POAG diagnosis.

METHODS

A total of 180 POAG patients and 210 age-related cataract (ARC) patients were enrolled. We collected aqueous humor (AH) and plasma samples from the recruited patients. The expressions of candidate miRNAs were measured using quantitative real time polymerase chain reaction. The diagnostic ability of candidate miRNAs was analyzed by receiver operating characteristic curve.

RESULTS

The expressions of miR-21-5p and miR-29b-3p were downregulated significantly in AH and plasma of POAG and miR-24-3p expression was significantly increased in AH and plasma of POAG, comparing with those of ARC. A three-miRNA panel was constructed by a binary logistic regression. And the panel could differentiate between POAG and ARC with an area under the curve of 0.8867 (sensitivity = 78.0%, specificity = 83.3%) in aqueous humor and 0.7547 (sensitivity = 73.8%, specificity = 81.2%) in plasma. Next, we verified the three-miRNA panel working as a potential diagnostic biomarker stable and reliable. At last, we identified related function and regulation pathways in vitro.

CONCLUSIONS

In conclusion, we built and identified a circulating three-miRNA panel as a potential diagnostic biomarker for POAG. It may be developed into an efficient assay and help improve the POAG diagnosis in the future.

Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review

PURPOSE

This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and their predictive accuracies. We also evaluate the integration of bioinformatics with AI tools.

METHODS

This scoping review was conducted across five electronic databases including EMBASE, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics were included.

RESULTS

A total of 10,262 articles were retrieved from all databases and 177 studies met the inclusion criteria. The most commonly studied ocular diseases were diabetic eye diseases, with 50 papers (28%), while glaucoma was explored in 25 studies (14%), age-related macular degeneration in 20 (11%), dry eye disease in 10 (6%), and uveitis in 9 (5%). Supervised learning was used in 91 papers (51%), unsupervised AI in 83 (46%), and bioinformatics in 85 (48%). Ninety-eight papers (55%) used more than one class of AI (e.g. > 1 of supervised, unsupervised, bioinformatics, or statistical techniques), while 79 (45%) used only one. Supervised learning techniques were often used to predict disease status or prognosis, and demonstrated strong accuracy. Unsupervised AI algorithms were used to bolster the accuracy of other algorithms, identify molecularly distinct subgroups, or cluster cases into distinct subgroups that are useful for prediction of the disease course. Finally, bioinformatic tools were used to translate complex biomarker profiles or findings into interpretable data.

CONCLUSION

AI analysis of biofluid markers displayed diagnostic accuracy, provided insight into mechanisms of molecular etiologies, and had the ability to provide individualized targeted therapeutic treatment for patients. Given the progression of AI towards use in both research and the clinic, ophthalmologists should be broadly aware of the commonly used algorithms and their applications. Future research may be aimed at validating algorithms and integrating them in clinical practice.

Distinct Metabolic Profiles of Ocular Hypertensives in Response to Hypoxia

Glaucoma is a neurodegenerative disease that affects the retinal ganglion cells (RGCs). The main risk factor is elevated intraocular pressure (IOP), but the actual cause of the disease remains unknown. Emerging evidence indicates that metabolic dysfunction plays a central role. The aim of the current study was to determine and compare the effect of universal hypoxia on the metabolomic signature in plasma samples from healthy controls (n = 10), patients with normal-tension glaucoma (NTG, n = 10), and ocular hypertension (OHT, n = 10). By subjecting humans to universal hypoxia, we aim to mimic a state in which the mitochondria in the body are universally stressed. Participants were exposed to normobaric hypoxia for two hours, followed by a 30 min recovery period in normobaric normoxia. Blood samples were collected at baseline, during hypoxia, and in recovery. Plasma samples were analyzed using a non-targeted metabolomics approach based on liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). Multivariate analyses were conducted using principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA), and univariate analysis using the Wilcoxon signed-rank test and false discovery rate (FDR) correction. Unique metabolites involved in fatty acid biosynthesis and ketone body metabolism were upregulated, while metabolites of the kynurenine pathway were downregulated in OHT patients exposed to universal hypoxia. Differential affection of metabolic pathways may explain why patients with OHT initially do not suffer or are more resilient from optic nerve degeneration. The metabolomes of NTG and OHT patients are regulated differently from control subjects and show dysregulation of metabolites important for energy production. These dysregulated processes may potentially contribute to the elevation of IOP and, ultimately, cell death of the RGCs.

Glial metabolic alterations during glaucoma pathogenesis

Glaucoma is the leading cause of irreversible blindness. Current treatment options are limited and often only slow disease progression. Metabolic dysfunction has recently been recognized as a key early and persistent mechanism in glaucoma pathophysiology. Several intrinsic metabolic dysfunctions have been identified and treated in retinal ganglion cells to provide neuroprotection. Growing pre-clinical and clinical evidence has confirmed that metabolic alterations in glaucoma are widespread, occurring across visual system tissues, in ocular fluids, in blood/serum, and at the level of genomic and mitochondrial DNA. This suggests that metabolic dysfunction is not constrained to retinal ganglion cells and that metabolic alterations extrinsic to retinal ganglion cells may contribute to their metabolic compromise. Retinal ganglion cells are reliant on glial metabolic support under normal physiological conditions, but the implications of metabolic dysfunction in glia are underexplored. We highlight emerging evidence that has demonstrated metabolic alterations occurring within glia in glaucoma, and how this may affect neuro-glial metabolic coupling and the metabolic vulnerability of retinal ganglion cells. In other neurodegenerative diseases which share features with glaucoma, several other glial metabolic alterations have been identified, suggesting that similar mechanisms and therapeutic targets may exist in glaucoma.

Metabolomic profiling of a neurodegenerative retina following optic nerve transection

The degeneration of retinal ganglion cells (RGCs) often causes irreversible vision impairment. Prevention of RGC degeneration can prevent or delay the deterioration of visual function. The present study aimed to investigate retinal metabolic profiles following optic nerve transection (ONT) injury and identify the potential metabolic targets for the prevention of RGC degeneration. Retinal samples were dissected from ONT group and non‑ONT group. The untargeted metabolomics were carried out using liquid chromatography‑tandem mass spectrometry. The involved pathways and biomarkers were analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and MetaboAnalyst 5.0. In the ONT group, 689 disparate metabolites were detected, including lipids and lipid‑like molecules. A total of 122 metabolites were successfully annotated and enriched in 50 KEGG pathways. Among them, 'sphingolipid metabolism' and 'primary bile acid biosynthesis' were identified involved in RGC degeneration. A total of five metabolites were selected as the candidate biomarkers for detecting RGC degeneration with an AUC value of 1. The present study revealed that lipid‑related metabolism was involved in the pathogenesis of retinal neurodegeneration. Taurine, taurochenodesoxycholic acid, taurocholic acid (TCA), sphingosine, and galabiosylceramide are shown as the promising biomarkers for the diagnosis of RGC degeneration.

Machine learning identifying peripheral circulating metabolites associated with intraocular pressure alterations

AIMS

To identify blood metabolite markers associated with intraocular pressure (IOP) in a population-based cross-sectional study.

METHODS

This study was conducted in a multiethnic Asian population (Chinese, n=2805; Indians, n=3045; Malays, n=3041 aged 40-80 years) in Singapore. All subjects underwent standardised systemic and ocular examinations, and biosamples were collected. Selected metabolites (n=228) in either serum or plasma were analysed and quantified using nuclear magnetic resonance spectroscopy. Least absolute shrinkage and selection operator regression was used for metabolites selection. Multivariable linear regression was used to evaluate the relationship between metabolites and IOP in each of the three ethnic groups, followed by a meta-analysis combining the three cohorts.

RESULTS

Six metabolites, including albumin, glucose, lactate, glutamine, ratio of saturated fatty acids to total fatty acids (SFAFA) and cholesterol esters in very large high-density lipoprotein (HDL), were significantly associated with IOP in all three cohorts. Higher levels of albumin (per SD, beta=0.24, p=0.002), lactate (per SD, beta=0.27, p=0.008), glucose (per SD, beta=0.11, p=0.010) and cholesterol esters in very large HDL (per SD, beta=0.47, p=0.006), along with lower levels of glutamine (per SD, beta=0.17, p<0.001) and SFAFA (per SD, beta=0.21, p=0.008) were associated with higher IOP levels.

CONCLUSION

We identify several novel blood metabolites associated with IOP. These findings may provide insight into the physiological and pathological processes underlying IOP control.

The role of artificial intelligence in analysis of biofluid markers for diagnosis and management of glaucoma: A systematic review

PURPOSE

This review focuses on utility of artificial intelligence (AI) in analysis of biofluid markers in glaucoma. We detail the accuracy and validity of AI in the exploration of biomarkers to provide insight into glaucoma pathogenesis.

METHODS

A comprehensive search was conducted across five electronic databases including Embase, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science. Studies pertaining to biofluid marker analysis using AI or bioinformatics in glaucoma were included. Identified studies were critically appraised and assessed for risk of bias using the Joanna Briggs Institute Critical Appraisal tools.

RESULTS

A total of 10,258 studies were screened and 39 studies met the inclusion criteria, including 23 cross-sectional studies (59%), nine prospective cohort studies (23%), six retrospective cohort studies (15%), and one case-control study (3%). Primary open angle glaucoma (POAG) was the most commonly studied subtype (55% of included studies). Twenty-four studies examined disease characteristics, 10 explored treatment decisions, and 5 provided diagnostic clarification. While studies examined at entire metabolomic or proteomic profiles to determine changes in POAG, there was heterogeneity in the data with over 175 unique, differentially expressed biomarkers reported. Discriminant analysis and artificial neural network predictive models displayed strong differentiating ability between glaucoma patients and controls, although these tools were untested in a clinical context.

CONCLUSION

The use of AI models could inform glaucoma diagnosis with high sensitivity and specificity. While insight into differentially expressed biomarkers is valuable in pathogenic exploration, no clear pathogenic mechanism in glaucoma has emerged.

Untargeted metabolomics in the aqueous humor reveals the involvement of TAAR pathway in glaucoma

Understanding the metabolic dysfunctions and underlying complex pathological mechanisms of neurodegeneration in glaucoma could help discover disease pathways, identify novel biomarkers, and rationalize newer therapeutics. Therefore, we aimed to investigate the local metabolomic alterations in the aqueous humor and plasma of primary glaucomatous patients. This study cohort comprised primary open-angle glaucoma (POAG), primary angle-closure glaucoma (PACG), and cataract control groups. Aqueous humor and plasma samples were collected from patients undergoing trabeculectomy or cataract surgery and subjected to high-resolution mass spectrometry (HRMS) analysis. Spectral information was processed, and the acquired data were subjected to uni-variate as well as multi-variate statistical analyses using MetaboAnalyst ver5.0. To further understand the localized metabolic abnormalities in glaucoma, metabolites affected in aqueous humor were distinguished from metabolites altered in plasma in this study. Nine and twelve metabolites were found to be significantly altered (p < 0.05, variable importance of projection >1 and log2 fold change ≥0.58/≤ -0.58) in the aqueous humor of PACG and POAG patients, respectively. The galactose and amino acid metabolic pathways were locally affected in the PACG and POAG groups, respectively. Based on the observation of the previous findings, gene expression profiles of trace amine-associated receptor-1 (TAAR-1) were studied in rat ocular tissues. The pharmacodynamics of TAAR-1 were explored in rabbits using topical administration of its agonist, β-phenyl-ethylamine (β-PEA). TAAR-1 was expressed in the rat's iris-ciliary body, optic nerve, lens, and cornea. β-PEA elicited a mydriatic response in rabbit eyes, without altering intraocular pressure. Targeted analysis of β-PEA levels in the aqueous humor of POAG patients showed an insignificant elevation. This study provides new insights regarding alterations in both localized and systemic metabolites in primary glaucomatous patients. This study also demonstrated the propensity of β-PEA to cause an adrenergic response through the TAAR-1 pathway.

Plasma metabolite profile for primary open-angle glaucoma in three US cohorts and the UK Biobank

Glaucoma is a progressive optic neuropathy and a leading cause of irreversible blindness worldwide. Primary open-angle glaucoma is the most common form, and yet the etiology of this multifactorial disease is poorly understood. We aimed to identify plasma metabolites associated with the risk of developing POAG in a case-control study (599 cases and 599 matched controls) nested within the Nurses' Health Studies, and Health Professionals' Follow-Up Study. Plasma metabolites were measured with LC-MS/MS at the Broad Institute (Cambridge, MA, USA); 369 metabolites from 18 metabolite classes passed quality control analyses. For comparison, in a cross-sectional study in the UK Biobank, 168 metabolites were measured in plasma samples from 2,238 prevalent glaucoma cases and 44,723 controls using NMR spectroscopy (Nightingale, Finland; version 2020). Here we show higher levels of diglycerides and triglycerides are adversely associated with glaucoma in all four cohorts, suggesting that they play an important role in glaucoma pathogenesis.

New insight of metabolomics in ocular diseases in the context of 3P medicine

Metabolomics refers to the high-through untargeted or targeted screening of metabolites in biofluids, cells, and tissues. Metabolome reflects the functional states of cells and organs of an individual, influenced by genes, RNA, proteins, and environment. Metabolomic analyses help to understand the interaction between metabolism and phenotype and reveal biomarkers for diseases. Advanced ocular diseases can lead to vision loss and blindness, reducing patients' quality of life and aggravating socio-economic burden. Contextually, the transition from reactive medicine to the predictive, preventive, and personalized (PPPM / 3P) medicine is needed. Clinicians and researchers dedicate a lot of efforts to explore effective ways for disease prevention, biomarkers for disease prediction, and personalized treatments, by taking advantages of metabolomics. In this way, metabolomics has great clinical utility in the primary and secondary care. In this review, we summarized much progress achieved by applying metabolomics to ocular diseases and pointed out potential biomarkers and metabolic pathways involved to promote 3P medicine approach in healthcare.

The Role of NAD+ and Nicotinamide (Vitamin B3) in Glaucoma: A Literature Review

Glaucoma is a collection of irreversible optic neuropathies which, if left untreated, lead to severe visual field loss. These diseases are a leading cause of blindness across the globe and are estimated to affect approximately 80 million people, particularly women and people of Asian descent (Quigley HA, Broman AT. 2006. Br J Ophthalmol 90: 262-267). This represents a major burden on healthcare systems worldwide. Recently, there has been increasing interest in the potential of nicotinamide (vitamin B3) as a novel option in the management of glaucoma. This review aims to analyse the currently available literature to determine whether there is evidence of an association between nicotinamide adenine dinucleotide (NAD⁺) and glaucomatous optic neuropathy, and whether nicotinamide has the potential to prevent or reverse these effects. The literature showed a strong connection between reduced NAD⁺ levels and retinal ganglion cell dysfunction through multiple different studies. There is also evidence of the positive effect of nicotinamide supplementation on retinal ganglion cell function in models of mouse glaucoma and in a study involving humans. Based on the literature findings, a recommendation has been made that more research into the efficacy, appropriate dosing, and potential side effects of nicotinamide supplementation is needed before it can be definitively determined whether it is appropriate for widespread prophylactic and therapeutic use against glaucoma in humans.

Glutamine Is Required for M1-like Polarization of Macrophages in Response to Mycobacterium tuberculosis Infection

In response to Mycobacterium tuberculosis infection, macrophages mount proinflammatory and antimicrobial responses similar to those observed in M1 macrophages activated by lipopolysaccharide (LPS) and interferon gamma (IFN-γ). A metabolic reprogramming to hypoxia-inducible-factor 1 (HIF-1)-mediated uptake of glucose and its metabolism by glycolysis is required for M1-like polarization, but little is known about other metabolic programs driving the M1-like polarization during infection. We report that glutamine serves as a carbon and nitrogen source for the metabolic reprogramming to M1-like macrophages. Widely targeted metabolite screening identified an association of glutamine and/or glutamate with highly affected metabolic pathways of M1-like macrophages. Moreover, stable isotope-assisted metabolomics of U¹³C glutamine and U¹³C glucose revealed that glutamine, rather than glucose, is catabolized in both the oxidative and reductive tricarboxylic acid (TCA) cycles of M1-like macrophages, thereby generating signaling molecules that include succinate, biosynthetic precursors such as aspartate, and itaconate. U¹⁵N glutamine-tracing metabolomics further revealed participation of glutamine nitrogen in synthesis of intermediates of purine and pyrimidine metabolism plus amino acids, including aspartate. These findings were corroborated by diminished M1 polarization from chemical inhibition of glutaminase (GLS), the key enzyme in the glutaminolysis pathway, and by genetic deletion of GLS in infected macrophages. Thus, the catabolism of glutamine is an integral component of metabolic reprogramming in activating macrophages and it coordinates with elevated cytosolic glycolysis to satisfy the cellular demand for bioenergetic and biosynthetic precursors of M1-like macrophages. Knowledge of these new immunometabolic features of M1-like macrophages should advance the development of host-directed therapies for tuberculosis.

Metabolomics in Primary Open Angle Glaucoma: A Systematic Review and Meta-Analysis

Glaucoma is a leading cause of blindness worldwide. It is suggested that primary open angle glaucoma (POAG), the most common form of glaucoma, may be associated with significant metabolic alternations, but the systemic literature review and meta-analysis in the area have been missing. Altered metabolomic profiles in the aqueous humor and plasma may serve as possible biomarkers for early detection or treatment targets. In this article, we performed a systematic meta-analysis of the current literature surrounding the metabolomics of patients with POAG and metabolites associated with the disease. Results suggest several metabolites found to be specifically altered in patients with POAG, suggesting broad generalizability and pathways for future research.

Glaucoma Characterization by Machine Learning of Tear Metabolic Fingerprinting

Glaucoma is a common optic neuropathy disease affecting over 76 million people. Both timely diagnosis and progression monitoring are critical but challenging. Conventional characterization of glaucoma needs a combination of methods, calling for tedious procedures and experienced doctors. Herein, a platform through machine learning of tear metabolic fingerprinting (TMF) using nanoparticle enhanced laser desorption-ionization mass spectrometry is built. Direct TMF is obtained noninvasively, with fast speed and high reproducibility, using trace tear samples (down to 10 nL). Consequently, glaucoma patients are screened against healthy controls with the area under the curve (AUC) of 0.866, through machine learning of TMF. Further, primary open-angle glaucoma (POAG) is differentiated from primary angle-closure glaucoma (PACG) and an early-stage POAG is identified. Finally, a biomarker panel of six metabolites for glaucoma characterization (including screening, subtyping, and early diagnosis) with AUC of 0.827-0.891 is constructed, showing related metabolic pathways. The work will provide insights into eye diseases not limited to glaucoma.

Metabolomics in Retinal Diseases: An Update

Retinal diseases are a leading cause of visual loss and blindness, affecting a significant proportion of the population worldwide and having a detrimental impact on quality of life, with consequent economic burden. The retina is highly metabolically active, and a number of retinal diseases are associated with metabolic dysfunction. To better understand the pathogenesis underlying such retinopathies, new technology has been developed to elucidate the mechanism behind retinal diseases. Metabolomics is a relatively new "omics" technology, which has developed subsequent to genomics, transcriptomics, and proteomics. This new technology can provide qualitative and quantitative information about low-molecular-weight metabolites (M.W. < 1500 Da) in a given biological system, which shed light on the physiological or pathological state of a cell or tissue sample at a particular time point. In this article we provide an extensive review of the application of metabolomics to retinal diseases, with focus on age-related macular degeneration (AMD), diabetic retinopathy (DR), retinopathy of prematurity (ROP), glaucoma, and retinitis pigmentosa (RP).

UPLC-MS-Based Serum Metabolic Profiling Reveals Potential Biomarkers for Predicting Propofol Responsiveness in Females

Although previous studies have shown that certain factors interfere with the sensitivity of propofol, the mechanisms for interindividual variability in response to propofol remain unclear. This study aimed to screen the metabolites to predict patients' sensitivity to propofol and to identify metabolic pathways to explore possible mechanisms associated with propofol resistance. Sera from 40 female patients undergoing elective hysteroscopic surgery in a prospective cohort propofol study were obtained before the administration of propofol. The patients' responsiveness to propofol was differentiated based on propofol effect-site concentration. Serum samples from two sets, a discovery set (n = 24) and an independent validation set (n = 16), were analyzed using ultraperformance liquid chromatography coupled with mass spectrometry based untargeted metabolomics. In the discovery set, 494 differential metabolites were screened out, and then 391 potential candidate biomarkers with the area under receiver operating characteristic curve >0.80 were selected. Pathway analysis showed that the pathway of glycerophospholipid metabolism was the most influential pathway. In the independent validation set, six potential biomarkers enabled the discrimination of poor responders from good and intermediate responders, which might be applied to predict propofol sensitivity. The mass spectrometry data are available via MetaboLights (http://www.ebi.ac.uk/metabolights/login) with the identifier MTBLS2311.

Candidate Glaucoma Biomarkers: From Proteins to Metabolites, and the Pitfalls to Clinical Applications

Glaucoma is an insidious group of eye diseases causing degeneration of the optic nerve, progressive loss of vision, and irreversible blindness. The number of people affected by glaucoma is estimated at 80 million in 2021, with 3.5% prevalence in people aged 40-80. The main biomarker and risk factor for the onset and progression of glaucoma is the elevation of intraocular pressure. However, when glaucoma is diagnosed, the level of retinal ganglion cell death usually amounts to 30-40%; hence, the urgent need for its early diagnosis. Molecular biomarkers of glaucoma, from proteins to metabolites, may be helpful as indicators of pathogenic processes observed during the disease's onset. The discovery of human glaucoma biomarkers is hampered by major limitations, including whether medications are influencing the expression of molecules in bodily fluids, or whether tests to validate glaucoma biomarker candidates should include human subjects with different types and stages of the disease, as well as patients with other ocular and neurodegenerative diseases. Moreover, the proper selection of the biofluid or tissue, as well as the analytical platform, should be mandatory. In this review, we have summarized current knowledge concerning proteomics- and metabolomics-based glaucoma biomarkers, with specificity to human eye tissue and fluid, as well the analytical approach and the main results obtained. The complex data published to date, which include at least 458 different molecules altered in human glaucoma, merit a new, integrative approach allowing for future diagnostic tests based on the absolute quantification of local and/or systemic biomarkers of glaucoma.

Elevated dimethylarginine, ATP, cytokines, metabolic remodeling involving tryptophan metabolism and potential microglial inflammation characterize primary open angle glaucoma

Glaucoma of which primary open angle glaucoma (POAG) constitutes 75%, is the second leading cause of blindness. Elevated intra ocular pressure and Nitric oxide synthase (NOS) dysfunction are hallmarks of POAG. We analyzed clinical data, cytokine profile, ATP level, metabolomics and GEO datasets to identify features unique to POAG. N9 microglial cells are used to gain mechanistic insights. Our POAG cohort showed elevated ATP in aqueous humor and cytokines in plasma. Metabolomic analysis showed changes in 21 metabolites including Dimethylarginine (DMAG) and activation of tryptophan metabolism in POAG. Analysis of GEO data sets and previously published proteomic data sets bins genes into signaling and metabolic pathways. Pathways from reanalyzed metabolomic data from literature significantly overlapped with those from our POAG data. DMAG modulated purinergic signaling, ATP secretion and cytokine expression were inhibited by N-Ethylmaleimide, NO donors, BAPTA and purinergic receptor inhibitors. ATP induced elevated intracellular calcium level and cytokines expression were inhibited by BAPTA. Metabolomics of cell culture supernatant from ATP treated sets showed metabolic deregulation and activation of tryptophan metabolism. DMAG and ATP induced IDO1/2 and TDO2 were inhibited by N-Ethylmaleimide, sodium nitroprusside and BAPTA. Our data obtained from clinical samples and cell culture studies reveal a strong association of elevated DMAG, ATP, cytokines and activation of tryptophan metabolism with POAG. DMAG mediated ATP signaling, inflammation and metabolic remodeling in microglia might have implications in management of POAG.

Metabolomics in Glaucoma: A Systematic Review

Purpose

Glaucoma remains a poorly understood disease, and identifying biomarkers for early diagnosis is critical to reducing the risk of glaucoma-related visual impairment and blindness. The aim of this review is to provide current metabolic profiles for glaucoma through a summary and analysis of reported metabolites associated with glaucoma.

Methods

We searched PubMed and Web of Science for metabolomics studies of humans on glaucoma published before November 11, 2020. Studies were included if they assessed the biomarkers of any types of glaucoma and performed mass spectrometry-based or nuclear magnetic resonance–based metabolomics approach. Pathway enrichment analysis and topology analysis were performed to generate a global view of metabolic signatures related to glaucoma using the MetaboAnalyst 3.0.

Results

In total, 18 articles were included in this review, among which 13 studies were focused on open-angle glaucoma (OAG). Seventeen metabolites related to OAG were repeatedly identified, including seven amino acids (arginine, glycine, alanine, lysine, methionine, phenylalanine, tyrosine), two phosphatidylcholine (PC aa C34:2, PC aa C36:4), three complements (acetylcarnitine, propionylcarnitine, butyrylcarnitine), carnitine, glutamine, hypoxanthine, spermine, and spermidine. The pathway analysis implied a major role of amino metabolism in OAG pathophysiology and revealed the metabolic characteristics between different biological samples.

Conclusions

In this review, we summarize existing metabolomic studies related to glaucoma biomarker identification and point out a series of metabolic disorders in OAG patients, providing information on the molecular mechanism changes in glaucoma. Additional studies are needed to validate existing findings, and future research will need to explore the potential overlap between different biological fluids.

Metabolomic Profiling of Aqueous Humor and Plasma in Primary Open Angle Glaucoma Patients Points Towards Novel Diagnostic and Therapeutic Strategy

Glaucoma is the second leading cause of blindness globally characterized by progressive loss of retinal ganglion cells (RGCs) and irreversible visual deficiency. As the most common type of glaucoma, primary open angle glaucoma (POAG) is currently an unmet medical need with limited therapy by lowering intraocular pressure (IOP). However, some patients continue to progress even though their IOP are controlled. Although early diagnosis and prompt treatment are crucial in preventing irreversible visual impairment, there are currently no biomarkers for screening POAG. Metabolomics has the advantages of illustrating the final downstream products of the genome and establishing the closest link to the phenotype. So far, there is no study investigating the metabolomic profiles in both aqueous humor and plasma of POAG patients. Therefore, to explore diagnostic biomarkers, unveil underlying pathophysiology and potential therapeutic strategies, a widely targeted metabolomic approach was applied using ultrahigh-resolution mass spectrometry with C18 liquid chromatography to characterize the metabolomic profiles in both aqueous humor and plasma of 28 POAG patients and 25 controls in our study. Partial least squares-discriminant analysis (PLS-DA) was performed to determine differentially expressed metabolites (DEMs) between POAG and age-matched controls. The area under the receiver operating characteristic curve (AUC) was calculated to assess the prediction accuracy of the DEMs. The correlation of DEMs with the clinical parameters was determined by Pearson correlation, and the metabolic pathways were analyzed using MetaboAnalyst 4.0. PLS-DA significantly separated POAG from controls with 22 DEMs in the aqueous humor and 11 DEMs in the plasma. Additionally, univariate ROC analysis and correlation analysis with clinical parameters revealed cyclic AMP (AUC = 0.87), 2-methylbenzoic acid (AUC = 0.75), 3'-sialyllactose (AUC = 0.73) in the aqueous humor and N-lac-phe (AUC = 0.76) in the plasma as potential biomarkers for POAG. Moreover, the metabolic profiles pointed towards the alteration in the purine metabolism pathway. In conclusion, the study identified potential and novel biomarkers for POAG by crosslinking the metabolomic profiles in aqueous humor and plasma and correlating with the clinical parameters. These findings have important clinical implications given that no biomarkers are currently available for glaucoma in the clinic, and the study provided new insights in exploring diagnostic biomarkers and potential therapeutic strategies of POAG by targeting metabolic pathways.

A plasma metabolomic signature of Leber hereditary optic neuropathy showing taurine and nicotinamide deficiencies

Leber's hereditary optic neuropathy (LHON) is the most common disorder due to mitochondrial DNA mutations and complex I deficiency. It is characterized by an acute vision loss, generally in young adults, with a higher penetrance in males. How complex I dysfunction induces the peculiar LHON clinical presentation remains an unanswered question. To gain an insight into this question, we carried out a non-targeted metabolomic investigation using the plasma of 18 LHON patients, during the chronic phase of the disease, comparing them to 18 healthy controls. A total of 500 metabolites were screened of which 156 were accurately detected. A supervised Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) highlighted a robust model for disease prediction with a Q2 (cum) of 55.5%, with a reliable performance during the permutation test (cross-validation analysis of variance, P-value = 5.02284e-05) and a good prediction of a test set (P = 0.05). This model highlighted 10 metabolites with variable importance in the projection (VIP) > 0.8. Univariate analyses revealed nine discriminating metabolites, six of which were the same as those found in the Orthogonal Projections to Latent Structures Discriminant Analysis model. In total, the 13 discriminating metabolites identified underlining dietary metabolites (nicotinamide, taurine, choline, 1-methylhistidine and hippurate), mitochondrial energetic substrates (acetoacetate, glutamate and fumarate) and purine metabolism (inosine). The decreased concentration of taurine and nicotinamide (vitamin B3) suggest interesting therapeutic targets, given their neuroprotective roles that have already been demonstrated for retinal ganglion cells. Our results show a reliable predictive metabolomic signature in the plasma of LHON patients and highlighted taurine and nicotinamide deficiencies.

Metabolomic analysis in ophthalmology

Modern science takes into account phenotype complexity and establishes approaches to track changes on every possible level. Many "omics" studies have been developed over the last decade. Metabolomic analysis enables dynamic measurement of the metabolic response of a living system to a variety of stimuli or genetic modifications. Important targets of metabolomics is biomarker development and translation to the clinic for personalized diagnosis and a greater understanding of disease pathogenesis. The current review highlights the major aspects of metabolomic analysis and its applications for the identification of relevant predictive, diagnostic and prognostic biomarkers for some ocular diseases including dry eye, keratoconus, retinal diseases, macular degeneration, and glaucoma. To date, possible biomarker candidates for dry eye disease are lipid metabolites and androgens, for keratoconus cytokeratins, urea, citrate cycle, and oxidative stress metabolites. Palmitoylcarnitine, sphingolipids, vitamin D related metabolites, and steroid precursors may be used for distinguishing glaucoma patients from healthy controls. Dysregulation of amino acid and carnitine metabolism is critical in the development and progression of diabetic retinopathy. Further work is needed to discover and validate metabolic biomarkers as a powerful tool for understanding the molecular mechanisms of ocular diseases, to provide knowledge on their etiology and pathophysiology and opportunities for personalized clinical intervention at an early stage.