Long-chain unsaturated fatty acids as possible important metabolites for primary angle-closure glaucoma based on targeted metabolomic analysis

Association between glaucoma susceptibility with combined defects in mitochondrial oxidative phosphorylation and fatty acid beta oxidation

Glaucoma is one of the leading causes of visual impairment and blindness worldwide, and is characterized by the progressive damage of retinal ganglion cells (RGCs) and the atrophy of the optic nerve head (ONH). The exact cause of RGC loss and optic nerve damage in glaucoma is not fully understood. The high energy demands of these cells imply a higher sensitivity to mitochondrial defects. Moreover, it has been postulated that the optic nerve is vulnerable towards damage from oxidative stress and mitochondrial dysfunction. To investigate this further, we conducted a pooled analysis of mitochondrial variants related to energy production, specifically focusing on oxidative phosphorylation (OXPHOS) and fatty acid β-oxidation (FAO). Our findings revealed that patients carrying non-synonymous (NS) mitochondrial DNA (mtDNA) variants within the OXPHOS complexes had an almost two-fold increased risk of developing glaucoma. Regarding FAO, our results demonstrated that longer-chain acylcarnitines (AC) tended to decrease, while shorter-chain AC tended to increase in patients with glaucoma. Furthermore, we observed that the knocking down cpt1a (a key rate-limiting enzyme involved in FAO) in zebrafish induced a degenerative process in the optic nerve and RGC, which resembled the characteristics observed in glaucoma. In conclusion, our study provides evidence that genes encoding mitochondrial proteins involved in energy metabolisms, such as OXPHOS and FAO, are associated with glaucoma. These findings contribute to a better understanding of the molecular mechanisms underlying glaucoma pathogenesis and may offer potential targets for therapeutic interventions in the future.

Metabolomics identifies and validates serum androstenedione as novel biomarker for diagnosing primary angle closure glaucoma and predicting the visual field progression

Background

Primary angle closure glaucoma (PACG) is the leading cause of irreversible blindness in Asia, and no reliable, effective diagnostic, and predictive biomarkers are used in clinical routines. A growing body of evidence shows metabolic alterations in patients with glaucoma. We aimed to develop and validate potential metabolite biomarkers to diagnose and predict the visual field progression of PACG.

Methods

Here, we used a five-phase (discovery phase, validation phase 1, validation phase 2, supplementary phase, and cohort phase) multicenter (EENT hospital, Shanghai Xuhui Central Hospital), cross-sectional, prospective cohort study designed to perform widely targeted metabolomics and chemiluminescence immunoassay to determine candidate biomarkers. Five machine learning (random forest, support vector machine, lasso, K-nearest neighbor, and GaussianNaive Bayes [NB]) approaches were used to identify an optimal algorithm. The discrimination ability was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration was assessed by Hosmer-Lemeshow tests and calibration plots.

Results

Studied serum samples were collected from 616 participants, and 1464 metabolites were identified. Machine learning algorithm determines that androstenedione exhibited excellent discrimination and acceptable calibration in discriminating PACG across the discovery phase (discovery set 1, AUCs=1.0 [95% CI, 1.00-1.00]; discovery set 2, AUCs = 0.85 [95% CI, 0.80-0.90]) and validation phases (internal validation, AUCs = 0.86 [95% CI, 0.81-0.91]; external validation, AUCs = 0.87 [95% CI, 0.80-0.95]). Androstenedione also exhibited a higher AUC (0.92-0.98) to discriminate the severity of PACG. In the supplemental phase, serum androstenedione levels were consistent with those in aqueous humor (r=0.82, p=0.038) and significantly (p=0.021) decreased after treatment. Further, cohort phase demonstrates that higher baseline androstenedione levels (hazard ratio = 2.71 [95% CI: 1.199-6.104], p=0.017) were associated with faster visual field progression.

Conclusions

Our study identifies serum androstenedione as a potential biomarker for diagnosing PACG and indicating visual field progression.

Funding

This work was supported by Youth Medical Talents - Clinical Laboratory Practitioner Program (2022-65), the National Natural Science Foundation of China (82302582), Shanghai Municipal Health Commission Project (20224Y0317), and Higher Education Industry-Academic-Research Innovation Fund of China (2023JQ006).

3D superstructure based metabolite profiling for glaucoma diagnosis

Metabolome analysis has gained widespread application in disease diagnosis owing to its ability to provide comprehensive information, including disease phenotypes. In this study, we utilized 3D superstructures fabricated through evaporation-induced microprinting to analyze the metabolome for glaucoma diagnosis. 3D superstructures offer the following advantages: high hotspot density per unit volume of the structure extending from two to three dimensions, excellent signal repeatability due to the reproducibility and defect tolerance of 3D printing, and high thermal stability due to the PVP-enclosed capsule form. Leveraging the superior optical properties of the 3D superstructure, we aimed to classify patients with glaucoma. The signal obtained from the 3D superstructure was employed in a Deep Neural Network (DNN) classification model to accurately classify glaucoma patients. The sensitivity and specificity of the model were determined as 92.05% and 93.51%, respectively. Additionally, the fabrication of 3D superstructures can be performed at any stage, significantly reducing measurement time. Furthermore, their thermal stability allows for the analysis of smaller samples. One notable advantage of 3D superstructures is their versatility in accommodating different target materials. Consequently, they can be utilized for a wide range of metabolic analyses and disease diagnoses.

The role of the microbiota in glaucoma

Glaucoma is a common irreversible vision loss disorder because of the gradual loss of retinal ganglion cells (RGCs) and the optic nerve axons. Major risk factors include elder age and high intraocular pressure (IOP). However, high IOP is neither necessary nor sufficient to cause glaucoma. Some non-IOP signaling cascades can mediate RGC degeneration. In addition, gender, diet, obesity, depression, or anxiety also contribute to the development of glaucoma. Understanding the mechanism of glaucoma development is crucial for timely diagnosis and establishing new strategies to improve current IOP-reducing therapies. The microbiota exerts a marked influence on the human body during homeostasis and disease. Many glaucoma patients have abnormal compositions of the microbiota (dysbiosis) in multiple locations, including the ocular surface, intraocular cavity, oral cavity, stomach, and gut. Here, we discuss findings in the last ten years or more about the microbiota and metabolite changes in animal models, patients with three risk factors (aging, obesity, and depression), and glaucoma patients. Antigenic mimicry and heat stress protein (HSP)-specific T-cell infiltration in the retina may be responsible for commensal microbes contributing to glaucomatous RGC damage. LPS-TLR4 pathway may be the primary mechanism of oral and ocular surface dysbiosis affecting glaucoma. Microbe-derived metabolites may also affect glaucoma pathogenesis. Homocysteine accumulation, inflammatory factor release, and direct dissemination may link gastric H. pylori infection and anterior chamber viral infection (such as cytomegalovirus) to glaucoma. Potential therapeutic protocols targeting microbiota include antibiotics, modified diet, and stool transplant. Later investigations will uncover the underlying molecular mechanism connecting dysbiosis to glaucoma and its clinical applications in glaucoma management.

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.

Relationship between plasma amino acid and carnitine levels and primary angle-closure glaucoma based on mass spectrometry metabolomics

World blindness is primarily caused by glaucoma. It has been predicted that by 2040, 118 million individuals will have glaucoma. Among Asians and Africans, primary angle-closure glaucoma (PACG) is the most prevalent type of glaucoma, for which treatment options are currently very limited. At present, lowering intraocular pressure (IOP) is the primary approach for PACG treatment. However, some PACG patients with decreased IOP measurements still advance. Additionally, because of the complicated pathophysiology, there are no biomarkers for diagnosis. Metabolomics is the study of the metabolites produced by all cellular processes in a biological sample, providing a method for identifying biomarkers and early diagnosis. Nevertheless, metabolomics has infrequently been applied to PACG. Previous research conducted by our lab on plasma metabolite fatty acids in PACG patients revealed reduced free fatty acid (FFA) levels, which may be connected to lipid peroxidation. To ascertain the relationship between other metabolites and PACG. We compared levels of amino acids and carnitine in patients with PACG (n = 147) and non-glaucoma (n = 340). Using metabolomics analysis, twenty-one amino acids and twenty-six carnitines (a total of ninety-six indicators) were examined. Odds ratios (OR) and 95% confidence intervals (CI) for these metabolites in relation to PACG were calculated. The relationship between ocular measures and metabolites was assessed by Spearman's rank correlation. Predictive performance was evaluated using the receiver operating characteristic (ROC). The C8/C2 level was comparable across patients with PACG and individuals without glaucoma based on the Wilcoxon rank-sum test. The PACG group had lower levels of Arginine (Arg), Ornithine (Orn), Arg/Orn, Orn/Cit, and C26/C20 than the nonglaucoma group, whereas Cit/Arg and C4/C2 ratios were greater. Both univariate and multivariate models showed a negative correlation between Orn and Orn/Cit and PACG. In the univariate model, palmitoylcarnitine (C16) had a negative correlation with PACG. According to our findings, metabolic profiles of plasma amino acids and carnitine between PACG patients and controls are different. The combination of amino acids and carnitine increased the predictive value of PACG. The Orn and Arg were negatively correlated with the local ocular neurodegenerative pathology. We speculate lipid peroxidation may explain the reduction in C16, and the decrease in Orn may be associated with hyperammonia neurotoxicity.

Acylcarnitines in Ophthalmology: Promising Emerging Biomarkers

Several common ocular diseases are leading causes of irreversible visual impairment. Over the last decade, various mainly untargeted metabolic studies have been performed to show that metabolic dysfunction plays an important role in the pathogenesis of ocular diseases. A number of metabolites in plasma/serum, aqueous or vitreous humor, or in tears have been found to differ between patients and controls; among them are L-carnitine and acylcarnitines, which are essential for mitochondrial fatty acid oxidation. The metabolic profile of carnitines regarding a variety of diseases has attracted researchers' interest. In this review, we present and discuss recent advances that have been made in the identification of carnitines as potential metabolic biomarkers in common ocular diseases, such as age-related macular degeneration, diabetic retinopathy, retinopathy of prematurity, central retinal vein occlusion, primary open-angle glaucoma, rhegmatogenous retinal detachment, and dry eye syndrome.

Circulating fatty acids and risk of primary open-angle glaucoma: A mendelian randomization study

PURPOSE

The relationship between fatty acids (FAs) and glaucoma remains controversial despite several observational studies. We organized a mendelian randomization (MR) study to determine the genetic causal association between circulating FAs and primary open-angle glaucoma (POAG).

METHODS

The two-sample MR method was used to acquire causal estimates. Fourteen distinct single nucleotide polymorphisms (SNPs) of ten FAs were chosen as instrumental variables (IVs) at a genome-wide significance level (p < 5 × 10^-8). Summary statistics for POAG were available from a genome-wide association meta-analysis of 216,257 individuals of European ancestry (16,677 cases, 199,580 controls). The inverse-variance weighted (IVW) method was adopted to evaluate the causality of FAs and POAG. Multiple sensitivity analyses were applied to avoid pleiotropy.

RESULTS

The IVW method suggested no evidence to support causal effects of ten FAs on POAG. The odds ratio (OR) per one SD increment of each FA was OR_ALA = 1.64 (95% CI, 0.441-6.098, p = 0.46), OR_EPA = 0.815 (95% CI, 0.604-1.101, p = 0.182), OR_DPA = 0.896 (95% CI, 0.669-1.198, p = 0.458), OR_DHA = 1.014 (95% CI, 0.801-1.283, p = 0.91), OR_LA = 1.008 (95% CI, 0.971-1.045, p = 0.683), OR_AA = 0.993 (95% CI, 0.973-1.013, p = 0.483), OR_POA = 0.731 (95% CI, 0.261-2.048, p = 0.551), OR_OA = 1.048 (95% CI, 0.934-1.175, p = 0.425), OR_PA = 1.039 (95% CI, 0.903-1.196, p = 0.593), OR_SA = 0.967 (95% CI, 0.879-1.062, p = 0.477). Moreover, Sensitivity analysis indicated no pleiotropy.

CONCLUSION

This MR study does not support causal associations between ten FAs and POAG.

The profile of gut microbiota and central carbon-related metabolites in primary angle-closure glaucoma patients

PURPOSE

To explore the profile of gut microbiota and central carbon-related metabolites in patients with primary angle-closure glaucoma (PACG).

METHODS

The fecal microbiotas of 30 PACG patients and 30 healthy participants were detected via 16S rRNA sequencing. Targeted liquid chromatography-mass spectrometry was used to examine serum central carbon-related metabolites. The correlations among metabolites, microbiotas and clinical presentations were also explored.

RESULTS

Although the α and β diversity between the PACG and control groups did not show a significant difference, the distribution of Blautia and Fusicatenibacter decreased significantly in the PACG group. Functional annotations of microbiota enrichment showed that the most dominant pathway was related to host metabolism. In the PACG patients, seven central carbon metabolites, namely adenosine 5'-diphosphate, dGDP, phosphoenolpyruvic acid, d-ribulose 5-phosphate, d-xylulose 5-phosphate, glucuronic acid, and malonic acid, decreased significantly, whereas two metabolites, citric acid and isocitrate, increased obviously. The mean RNFL thickness was positively correlated with phosphoenolpyruvic acid, the VF-MD was positively correlated with glucuronic acid, and the abundance of Blautia was negatively associated with citric acid.

CONCLUSION

Few species of gut microbiota were altered in the PACG patients compared to the healthy subjects. A distinct difference in the phenotype of the central carbon-related metabolites of PACG and their correlation with clinical presentations and microbiota suggests potential mechanisms of RGC impairment and novel intervention targets.

Association between plasma free fatty acid levels and primary angle-closure glaucoma based on a mass spectrometry metabolomics analysis

PURPOSE

To determine the association between plasma free fatty acid (FFA) levels and primary angle-closure glaucoma (PACG).

METHODS

Free fatty acid (FFA) levels in patients with PACG (n = 181) and people without glaucoma (n = 340) were compared. Twenty-two FFAs and six lipid classes were measured using metabolomics analysis. Odds ratio (OR) of these metabolites and their 95% confidence intervals (95%CI) for PACG were obtained by logistic regression. Stepwise forward selection was performed to identify FFAs that influenced PACG risk. Areas under the curve (AUC) were applied to assess the predictive performance. Spearman's rank correlation was used to assess the relationship between ocular parameters and FFAs.

RESULTS

Most FFAs in the PACG group were lower than those in the non-glaucoma group. Docosahexaenoic acid (DHA; OR for fourth quartile (Q4) vs. first quartile (Q1): 0.32 (0.16-0.66); per standard deviation (SD) increase: 0.64 (0.49-0.83); p for trend: 0.0007) and total saturated fatty acids (SFAs; OR for Q4 versus Q1: 0.27 (0.13-0.56); per SD increase: 0.65 (0.50-0.87); p for trend: 0.0004) were associated with decreased PACG risk. The AUC of the model that included DHA, total SFAs, demographic and ophthalmic factors increased from 0.8230 (0.7811-0.8649) to 0.8512 (0.8133-0.8891) (increased AUC: 0.0282 (0.0112-0.0453); p for increased AUC: 0.0012). Additionally, the cup-disc ratio had a weak negative correlation with DHA and total SFAs (DHA: r = -0.12085, p = 0.0065; total SFAs: r = -0.13318, p = 0.0024).

CONCLUSIONS

Decrease in FFA levels may be related to lipid peroxidation. Docosahexaenoic acid (DHA) and total SFAs may be screening indices for PACG patients.

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).

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.

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 from glaucoma patients - The metabolomics in surgical ophthalmological patients (MISO) study

Glaucoma is still a poorly understood disease with a clear need for new biomarkers to help in diagnosis and potentially offer new therapeutic targets. We aimed to determine if the metabolic profile of aqueous humor (AH) as determined by nuclear magnetic resonance (NMR) spectroscopy allows the distinction between primary open-angle glaucoma patients and control subjects, and to distinguish between high-tension (POAG) and normal-tension glaucoma (NTG). We analysed the AH of patients with POAG, NTG and control subjects (n = 30/group). ¹H NMR spectra were acquired using a 400 MHz spectrometer. Principle component analysis (PCA), machine learning algorithms and descriptive statistics were applied to analyse the metabolic variance between groups, identify the spectral regions, and hereby potential metabolites that can act as biomarkers for glaucoma. According to PCA, fourteen regions of the NMR spectra were significant in explaining the metabolic variance between the glaucoma and control groups, with no differences found between POAG and NTG groups. These regions were further used in building a classifier for separating glaucoma from control patients, which achieved an AUC of 0.93. Peak integration was performed on these regions and a statistical analysis, after false discovery rate correction and adjustment for the different perioperative topical drug regimen, revealed that five of them were significantly different between groups. The glaucoma group showed a higher content in regions typical for betaine and taurine, possibly linked to neuroprotective mechanisms, and also a higher content in regions that are typical for glutamate, which can indicate damaged neurons and oxidative stress. These results show how aqueous humor metabolomics based on NMR spectroscopy can distinguish glaucoma patients from controls with a high accuracy. Further studies are needed to validate these results in order to incorporate them in clinical practice.

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.

A Metabolomics Profiling of Glaucoma Points to Mitochondrial Dysfunction, Senescence, and Polyamines Deficiency

Purpose

To determine the plasma metabolomic signature of primary open-angle glaucoma (POAG).

Methods

We compared the metabolomic profiles of plasma from individuals with POAG (n = 36) with age- and sex-matched controls with cataract (n = 27). A targeted metabolomics study was performed using the standardized p180 Biocrates Absolute IDQ p180 kit with a QTRAP 5500 mass spectrometer. Multivariate analyses were performed using principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) method.

Results

Among the 151 metabolites accurately measured, combined univariate and multivariate analyses revealed 18 discriminant metabolites belonging to the carbohydrate, acyl-carnitine, phosphatidylcholine, amino acids, and polyamine families. The metabolomic signature of POAG points to three closely interdependent pathophysiologic conditions; that is, defective mitochondrial oxidation of energetic substrates, altered metabolism resembling that observed in senescence, and a deficiency in spermidine and spermine, both polyamines being involved in the protection of retinal ganglion cells.

Conclusions

Our results highlight a systemic and age-related mitochondrial defect in the pathogenesis of POAG.

Metabolomic Profiles of a Midge (Procladius villosimanus, Kieffer) Are Associated with Sediment Contamination in Urban Wetlands

Metabolomic techniques are powerful tools for investigating organism-environment interactions. Metabolite profiles have the potential to identify exposure or toxicity before populations are disrupted and can provide useful information for environmental assessment. However, under complex environmental scenarios, metabolomic responses to exposure can be distorted by background and/or organismal variation. In the current study, we use LC-MS (liquid chromatography-mass spectrometry) and GC-MS (gas chromatography-mass spectrometry) to measure metabolites of the midge Procladius villosimanus inhabiting 21 urban wetlands. These metabolites were tested against common sediment contaminants using random forest models and metabolite enrichment analysis. Sediment contaminant concentrations in the field correlated with several P. villosimanus metabolites despite natural environmental and organismal variation. Furthermore, enrichment analysis indicated that metabolite sets implicated in stress responses were enriched, pointing to specific cellular functions affected by exposure. Methionine metabolism, sugar metabolism and glycerolipid metabolism associated with total petroleum hydrocarbon and metal concentrations, while mitochondrial electron transport and urea cycle sets associated only with bifenthrin. These results demonstrate the potential for metabolomics approaches to provide useful information in field-based environmental assessments.