Metabolomic Profiling of the Aqueous Humor in Patients with Wet Age-Related Macular Degeneration Using UHPLC-MS/MS

Untargeted Metabolomic Study of Patients with Macular Edema Secondary to Retinal Vein Occlusion in Aqueous Humor

Purpose

The aim of this study was to identify metabolic biomarkers and investigate the metabolic changes associated with aqueous humor in retinal vein occlusion macular edema (RVO-ME).

Methods

Aqueous humor (AH) samples were collected from patients, including those diagnosed with central retinal vein occlusion macular edema (CRVO-ME), branch retinal vein occlusion macular edema (BRVO-ME), and a control group undergoing cataract surgery. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilized to analyze the metabolomic profiles in aqueous humor.

Results

A total of 28 metabolites were identified as potential biomarkers capable of distinguishing RVO-ME patients from the control group. Of these, 26 metabolites were specific for distinguishing CRVO-ME patients from controls, and 24 metabolites were specific for differentiating BRVO-ME patients from controls. Additionally, 9 metabolites were identified that could differentiate CRVO-ME patients from BRVO-ME patients.

Conclusion

This study successfully identified significant metabolic biomarkers that enhance our understanding of the pathogenesis of RVO-ME. These findings may offer new avenues for the treatment of RVO-ME and aid in differentiating between CRVO-ME and BRVO-ME patients.

Aqueous Proteomic and Metabolomic Profiles in Low-Energy vs High-Energy Femtosecond Laser-Assisted Cataract Surgery

Purpose

To investigate the aqueous proteomics and metabolomics in low-energy and high-energy femtosecond laser-assisted cataract surgery (FLACS).

Methods

In this prospective observational study, 72 patients were randomized to 3 groups: low-energy FLACS, high-energy FLACS, and conventional phacoemulsification (controls). Aqueous was collected after femtosecond laser treatment or at the beginning of surgery (controls). Proteomic analysis was conducted using a data-independent acquisition method, whereas aqueous metabolomics were analyzed with liquid chromatography-tandem mass spectrometry. Bioinformatics analyses were performed to integrate the results of proteomics and metabolomics.

Results

Compared with low-energy FLACS, significantly elevated aqueous hemoglobin subunit beta, G protein subunit beta, carbonic anhydrase 1, and asymmetric dimethylarginine were observed in high-energy FLACS, suggesting significantly greater oxidative stress, inflammation, immunity, metabolism, and mitochondrial fatty acids oxidation. Compared with controls, significantly increased aqueous proteins and metabolites related to immune and inflammation (beta-crystallin B1, hemoglobin subunit beta, putrescine, and spermine) and oxidative stress (heat shock proteins, peroxiredoxins, and long-chain acylcarnitines) were observed in FLACS. Joint pathway analysis revealed nicotinate/nicotinamide metabolism and riboflavin metabolism were significantly overexpressed in high-energy FLACS compared with low-energy FLACS, whereas the pentose phosphate pathway and glycolysis were the most significant pathways when comparing FLACS with controls.

Conclusions

FLACS induced higher immunological and inflammatory responses, oxidative stress reactions, and mitochondrial fatty acid oxidative stress compared with controls. These differential effects were more pronounced when a higher laser energy was used.

Analysis of biofluid metabolomic profiles to the discovery of biomarkers in age-related macular degeneration

OBJECTIVE

Age-related macular degeneration (AMD) is one of the leading causes of irreversible visual impairment and blindness in the elderly. As AMD is a multifactorial disease, it is critical to explore useful biomarkers and pathological pathways underlying it. The purpose of this study is to summarise current metabolic profiles and further identify potential metabolic biomarkers and therapeutic targets in AMD, which could facilitate clinical diagnosis and treatment.

METHODS AND ANALYSIS

Relevant metabolomics studies published before 10 December 2021 were generally reviewed from online resources by two investigators. Studies with sufficient information and data were included in this systematic review and repeatedly identified metabolites were extracted. Pathway and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were performed. The public Gene Expression Omnibus (GEO) database was used for coanalysis with differential metabolites to construct a pathway network via MetaboAnalyst V.5.0.

RESULTS

16 studies were included in our analysis. 24 metabolites were repeatedly detected and regarded as potential biomarkers for AMD. Pathway analysis implied a major role of phenylalanine, tyrosine and tryptophan pathways in AMD pathology. 11 KEGG pathways were enriched, meanwhile, 11 metabolic pathway clusters were identified by coanalysing the differential metabolites and gene profiles using the GEO database.

CONCLUSION

In this study, we summarised 16 metabolomic studies on AMD, and 24 metabolites were identified as potential biofluid biomarkers. This provided novel insights into the pathogenic mechanisms underlying AMD. Further studies are warranted to validate and expand an effective pattern for AMD diagnosis and treatment.

Serum metabolite biomarkers for the early diagnosis and monitoring of age-related macular degeneration

INTRODUCTION

Age-related macular degeneration (AMD) is a leading cause of irreversible blindness worldwide, with significant challenges for early diagnosis and treatment.

OBJECTIVES

To identify new biomarkers that are important for the early diagnosis and monitoring of the severity/progression of AMD.

METHODS

We investigated the diagnostic and monitoring potential of blood metabolites in a cohort of 547 individuals (167 healthy controls, 240 individuals with other eye diseases as eye disease controls, and 140 individuals with AMD) from 2 centers over three phases: discovery phase 1, discovery phase 2, and an external validation phase. The samples were analyzed via a mass spectrometry-based, widely targeted metabolomic workflow. In discovery phases 1 and 2, we built a machine learning algorithm to predict the probability of AMD. In the external validation phase, we further confirmed the performance of the biomarker panel identified by the algorithm. We subsequently evaluated the performance of the identified biomarker panel in monitoring the progression and severity of AMD.

RESULTS

We developed a clinically specific three-metabolite panel (hypoxanthine, 2-furoylglycine, and 1-hexadecyl-2-azelaoyl-sn-glycero-3-phosphocholine) via five machine learning models. The random forest model effectively discriminated patients with AMD from patents in the other two groups and showed acceptable calibration (area under the curve (AUC) = 1.0; accuracy = 1.0) in both discovery phases 1 and 2. An independent validation phase confirmed the diagnostic model's efficacy (AUC = 0.962; accuracy = 0.88). The three-biomarker panel model demonstrated an AUC of 1.0 in differentiating the severity of AMD via RF machine learning, which was consistent across both the discovery and external validation phases. Additionally, the biomarker concentrations remained stable under repeated freeze-thaw cycles (P > 0.05).

CONCLUSIONS

This study reveals distinct metabolite variations in the serum of AMD patients, paving the way for the development of the first routine laboratory test for AMD.

Untargeted Metabolomic Study of Patients with Wet Age-Related Macular Degeneration in Aqueous Humor

Purpose

The objective of this study was to ascertain metabolic biomarkers and investigate the metabolic alterations associated with aqueous humor (AH) in wet age-related macular degeneration (AMD).

Methods

AH samples were collected from a total of 20 participants, including 10 individuals diagnosed with wet AMD and 10 individuals undergoing cataract surgery, serving as the control group. Metabolomics analysis was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify and quantify metabolites.

Results

A total of 155 metabolites were identified in the AH samples. Among them, 10 metabolites emerged as potential biomarkers capable of differentiating patients with wet AMD from the control group. In the AH of wet AMD patients, there was increased expression of Cardiolipin (CL) (72:5), Diglyceride (DG) (18:3_18:2), DG (36:5e) and Triglyceride (TG) (24:7), while the expression of Ceramides (Cer) (d32:0), Cer (d34:0), Cer (d36:0), Monogalactosyldiacylglycerol (MGDG) (16:1_18:3), Sphingosine (SPH) (d18:0) and TG (16:0_10:4_16:0) was down regulated.

Conclusion

Through metabolomics analysis of AH, this study successfully uncovered valuable metabolic biomarkers linked to wet AMD. These findings contribute to a more comprehensive understanding of the pathogenesis of wet AMD and offer potential avenues for the development of innovative treatment strategies for this condition.

Olink Profiling of Aqueous Humor Identifies Novel Biomarkers for Wet Age-Related Macular Degeneration

Metabolic dysfunction is recognized as a contributing factor in the pathogenesis of wet age-related macular degeneration (wAMD). However, the specific metabolism-related proteins implicated in wAMD remain elusive. In this study, we assessed the expression profiles of 92 metabolism-related proteins in aqueous humor (AH) samples obtained from 44 wAMD patients and 44 cataract control patients. Our findings revealed significant alterations in the expression of 60 metabolism-related proteins between the two groups. Notably, ANGPTL7 and METRNL displayed promising diagnostic potential for wAMD, as evidenced by area under the curve values of 0.88 and 0.85, respectively. Subsequent validation studies confirmed the upregulation of ANGPTL7 and METRNL in the AH of wAMD patients and in choroidal neovascularization (CNV) models. Functional assays revealed that increased ANGPTL7 and METRNL played a pro-angiogenic role in endothelial biology by promoting endothelial cell proliferation, migration, tube formation, and spouting in vitro. Moreover, in vivo studies revealed the pro-angiogenic effects of ANGPTL7 and METRNL in CNV formation. In conclusion, our findings highlight the association between elevated ANGPTL7 and METRNL levels and wAMD, suggesting their potential as novel predictive and diagnostic biomarkers for this condition. These results underscore the significance of ANGPTL7 and METRNL in the context of wAMD pathogenesis and offer new avenues for future research and therapeutic interventions.

Metabolomic profiling of the aqueous humor in patients with pediatric cataract

Pediatric cataract, including congenital and developmental cataract, is a kind of pediatric vision-threatening disease with extensive phenotypic heterogeneity and multiple mechanisms. We aimed to investigate the metabolite profile of aqueous humor (AH) in patients with pediatric cataracts, and identify underlying mutual correlations between differential metabolites. Metabolomic profiles of AH were analyzed and compared between pediatric cataract patients (n = 33) and age-related cataract patients without metabolic diseases (n = 29), using global untargeted metabolomics with ultra-high-performance liquid chromatography tandem mass spectrometry. Principal component analysis, partial least squares discriminant analysis and heat map were applied. Enriched pathway analysis was conducted using Kyoto Encyclopedia of Genes and Genomes. Receiver-operating characteristic (ROC) analyses were employed to select potential biomarkers. A total of 318 metabolites were identified, of which 54 differential metabolites (25 upregulated and 29 downregulated) were detected in pediatric cataract group compared with controls (variable importance of projection >1.0, fold change ≥1.5 or ≤ 0.667 and P < 0.05). A significant accumulation of N-Acetyl-Dl-glutamic acid was observed in pediatric cataract group. The differential metabolites were mainly enriched in histidine metabolism (increased L-Histidine and decreased 1-Methylhistamine) and the tryptophan metabolism (increased N-Formylkynurenine and L-Kynurenine). 5-Aminosalicylic acid showed strong positive mutual inter-correlation with L-Tyrosinemethylester and N,N-Diethylethanolamine, both of which were down-regulated in pediatric cataract group. The ROC analysis implied 11 metabolites served as potential biomarkers for pediatric cataract patients (all area under the ROC curve ≥0.900). These results illustrated novel potential metabolites and metabolic pathways in pediatric cataract, which provides new insights into the pathophysiology of pediatric cataract.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

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.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Comparative untargeted and targeted metabonomics reveal discriminations in metabolite profiles between Mycoplasma capricolum subsp. capripneumoniae and Mycoplasma capricolum subsp. capricolum

Background

Mycoplasmas are among the smallest prokaryotic microbes that can grow and proliferate on non-living media. They have reduced genomes, which may be associated with a concomitant reduction in their metabolic capacity. Mycoplasma capricolum subsp. capripneumoniae (Mccp) and Mycoplasma capricolum subsp. capricolum (Mcc), both belong to the Mycoplasma mycoides cluster, are significant important pathogenic Mycoplasma species in veterinary research field. They share high degree of genome homology but Mcc grows markedly faster and has higher growth titer than Mccp.

Methods

This study investigated the metabolites of these two pathogenic bacteria from the middle and late stages of the logarithmic growth phase through liquid chromatography-mass spectrometry-based metabolomics and targeted energy metabolomics. The multivariate analysis was conducted to identify significant differences between the two important Mycoplasma species.

Results

A total of 173 metabolites were identified. Of them, 33 and 34 metabolites involved in purine and pyrimidine, pyruvate metabolism, and amino acid synthesis were found to significantly differ in the middle and late stages, respectively. The abundance of fructose 1,6-bisphosphate, ADP, and pyruvate was higher in Mcc than in Mccp during the whole logarithmic period. Lactate was upregulated in slow-growing Mccp. The pH buffering agent N-[2-hydroxyethyl]piperazine-N'-[2-ethanesulfonic acid] added to media effectively prevented pH reduction and increase bacterial viability and protein biomass. The multivariate analysis revealed that the two Mycoplasma species significantly differed in glucose metabolism, growth factor transport and metabolism, cholesterol utilization, and environmental regulation.

Conclusion

The study data are beneficial for understanding the metabolomic characteristics of these two crucial Mycoplasma species and shedding more light on mycoplasma metabolism, and serve as a resource for the pathogenesis and development of related vaccines.

Construction of an Exudative Age-Related Macular Degeneration Diagnostic and Therapeutic Molecular Network Using Multi-Layer Network Analysis, a Fuzzy Logic Model, and Deep Learning Techniques: Are Retinal and Brain Neurodegenerative Disorders Related?

Neovascular age-related macular degeneration (nAMD) is a leading cause of irreversible visual impairment in the elderly. The current management of nAMD is limited and involves regular intravitreal administration of anti-vascular endothelial growth factor (anti-VEGF). However, the effectiveness of these treatments is limited by overlapping and compensatory pathways leading to unresponsiveness to anti-VEGF treatments in a significant portion of nAMD patients. Therefore, a system view of pathways involved in pathophysiology of nAMD will have significant clinical value. The aim of this study was to identify proteins, miRNAs, long non-coding RNAs (lncRNAs), various metabolites, and single-nucleotide polymorphisms (SNPs) with a significant role in the pathogenesis of nAMD. To accomplish this goal, we conducted a multi-layer network analysis, which identified 30 key genes, six miRNAs, and four lncRNAs. We also found three key metabolites that are common with AMD, Alzheimer's disease (AD) and schizophrenia. Moreover, we identified nine key SNPs and their related genes that are common among AMD, AD, schizophrenia, multiple sclerosis (MS), and Parkinson's disease (PD). Thus, our findings suggest that there exists a connection between nAMD and the aforementioned neurodegenerative disorders. In addition, our study also demonstrates the effectiveness of using artificial intelligence, specifically the LSTM network, a fuzzy logic model, and genetic algorithms, to identify important metabolites in complex metabolic pathways to open new avenues for the design and/or repurposing of drugs for nAMD treatment.

High-Fat Diet Alters Acylcarnitine Metabolism of the Retina and Retinal Pigment Epithelium/Choroidal Tissues in Laser-Induced Choroidal Neovascularization Rat Models

SCOPE

Choroidal neovascularization (CNV) is age-related macular degeneration's (AMD) main pathological change. High-fat diet (HFD) is associated with a form of CNV; however, the specific mechanism is unclear. Mitochondrial dysfunction, characterized by abnormal acylcarnitine, occurs during metabolic screening of serum or other body tissues in AMD. This study investigates HFD's role in retinal and retinal pigment epithelium (RPE)/choroidal acylcarnitine metabolism in CNV formation.

METHODS AND RESULTS

Chow diet and HFD-BN rats are laser-treated to induce CNV. Acylcarnitine species are quantitatively characterized by ultrahigh-performance liquid chromatography-tandem mass spectrometry. Optical coherence tomography and fundus fluorescein angiography evaluate CNV severity. HFD promotes weight gain, dyslipidemia, and CNV formation. In CNV rats, few medium-chain fatty acids (MCFAs) acylcarnitine in the RPE/choroid are initially affected. When an HFD is administered to these, even MCFA acylcarnitine in the RPE/choroid is found to decline. However, in the retina, odd acylcarnitines are increased, revealing "an opposite" change within the RPE/choroid, accompanied by influencing glycolytic key enzymes. The HFD+CNV group incorporated fewer long-chain acylcarnitines, like C18:2, into the retina than controls.

CONCLUSIONS

HFD hastens choroidal neovascularization. The study comprehensively documented acylcarnitine profiles in a CNV rat model. Acylcarnitine's odd-even and carbon-chain length properties may guide future therapeutics.

Comprehensive metabolic profiling of diabetic retinopathy

Diabetic retinopathy (DR) is an important complication of diabetes mellitus and a prevalent blind-causing ophthalmic disease. Despite years of efforts, rapid and accurate diagnosis of DR remains a challenging task. Metabolomics has been used as a diagnostic tool for disease progression and therapy monitoring. In this study, retinal tissues were collected from diabetic mice and age-matched non-diabetic mice. An unbiased metabolic profiling was performed to identify the altered metabolites and metabolic pathways in DR. 311 differential metabolites were identified between diabetic retinas and non-diabetic retinas under the criteria of variable importance in projection (VIP) > 1 and P < 0.05. These differential metabolites were highly enriched in purine metabolism, amino acid metabolism, glycerophospholipid metabolism, and pantaothenate and CoA biosynthesis. We then evaluated the sensitivity and specificity of purine metabolites as the candidate biomarkers for DR through the area under the receiver-operating characteristic curves (AUC-ROCs). Compared with other purine metabolites, adenosine, guanine, and inosine had higher sensitivity, specificity, and accuracy for DR prediction. In conclusion, this study sheds new light on the metabolic mechanism of DR, which can facilitate clinical diagnosis, therapy, and prognosis of DR in the future.

Aqueous Fluid Transcriptome Profiling Differentiates Between Non-Neovascular and Neovascular AMD

Purpose

Early and intermediate non-neovascular AMD (NN-AMD) has the potential to progress to either advanced NN-AMD with geographic atrophy, or to neovascular AMD (N-AMD) with CNV. This exploratory study performed an unbiased analysis of aqueous humor transcriptome in patients with early or intermediate NN-AMD vs. treatment-naïve N-AMD to determine the feasibility of using this method in future studies investigating pathways and triggers for conversion from one form to another.

Methods

Aqueous humor samples were obtained from 20 patients with early or intermediate NN-AMD and 20 patients with untreated N-AMD, graded on clinical examination and optical coherence tomography. Transcriptome profiles were generated using next-generation sequencing methods optimized for ocular samples. Top-ranked transcripts were compared between groups, and pathway enrichment analysis was performed.

Results

Seventy-eight differentially expressed transcripts were identified. Unsupervised clustering of differentially expressed transcripts was able to successfully differentiate between the two groups based on aqueous transcriptome alone. Pathway analysis highlighted changes in expression of genes associated with mitochondrial respiration, oxidative stress, ubiquitination, and neurogenesis between the two groups.

Conclusions

This pilot study compared the aqueous fluid transcriptome of patients with early or intermediate NN-AMD and untreated N-AMD. Differences in transcripts and transcriptome pathways identified in the aqueous of patients with early or intermediate NN-AMD compared with patients with N-AMD are consistent with those previously implicated in the pathogenesis of these distinct AMD subtypes. The findings from this exploratory study warrant further investigation using a larger, prospective study design, with the inclusion of a control group of eyes without AMD.

Vitreous Fatty Amides and Acyl Carnitines Are Altered in Intermediate Age-Related Macular Degeneration

Purpose

Age-related macular degeneration (AMD) is the leading cause of visual impairment worldwide. In this study, we aimed to investigate the vitreous humor metabolite profiles of patients with intermediate AMD using untargeted metabolomics.

Methods

We performed metabolomics using high-resolution liquid chromatography mass spectrometry on the vitreous humor of 31 patients with intermediate AMD and 30 controls who underwent vitrectomy for epiretinal membrane with or without cataract surgery. Univariate analyses after false discovery rate correction were performed to discriminate the metabolites and identify the significant metabolites of intermediate AMD. For biologic interpretation, enrichment and pathway analysis were conducted using MetaboAnalyst 5.0.

Results

Of the 858 metabolites analyzed in the vitreous humor, 258 metabolites that distinguished patients with AMD from controls were identified (P values < 0.05). Ascorbic acid and uric acid levels increased in the AMD group (all P values < 0.05). The acyl carnitines, such as acetyl L-carnitine (1.37-fold), and fatty amides, such as anandamide (0.9-fold) and docosanamide (0.67-fold), were higher in patients with intermediate AMD. In contrast, nicotinamide (-0.55-fold), and succinic acid (-1.69-fold) were lower in patients with intermediate AMD. The metabolic pathway related oxidation of branched chain fatty acids and carnitine synthesis showed enrichment.

Conclusions

Multiple metabolites related to fatty amides and acyl carnitine were found to be increased in the vitreous humor of patients with intermediate AMD, whereas succinic acid and nicotinamide were reduced, suggesting that altered metabolites related to fatty amides and acyl carnitines and energy metabolism may be implicated in the etiology of AMD.

Tissue-Specific Sex Difference in Mouse Eye and Brain Metabolome Under Fed and Fasted States

Purpose

Visual physiology and various ocular diseases demonstrate sexual dimorphisms; however, how sex influences metabolism in different eye tissues remains undetermined. This study aims to address common and tissue-specific sex differences in metabolism in the retina, RPE, lens, and brain under fed and fasted conditions.

Methods

After ad libitum fed or being deprived of food for 18 hours, mouse eye tissues (retina, RPE/choroid, and lens), brain, and plasma were harvested for targeted metabolomics. The data were analyzed with both partial least squares-discriminant analysis and volcano plot analysis.

Results

Among 133 metabolites that cover major metabolic pathways, we found 9 to 45 metabolites that are sex different in different tissues under the fed state and 6 to 18 metabolites under the fasted state. Among these sex-different metabolites, 33 were changed in 2 or more tissues, and 64 were tissue specific. Pantothenic acid, hypotaurine, and 4-hydroxyproline were the top commonly changed metabolites. The lens and the retina had the most tissue-specific, sex-different metabolites enriched in the metabolism of amino acid, nucleotide, lipids, and tricarboxylic acid cycle. The lens and the brain had more similar sex-different metabolites than other ocular tissues. The female RPE and female brain were more sensitive to fasting with more decreased metabolites in amino acid metabolism, tricarboxylic acid cycles, and glycolysis. The plasma had the fewest sex-different metabolites, with very few overlapping changes with tissues.

Conclusions

Sex has a strong influence on eye and brain metabolism in tissue-specific and metabolic state-specific manners. Our findings may implicate the sexual dimorphisms in eye physiology and susceptibility to ocular diseases.

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.

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.

Amino Acids Metabolism in Retinopathy: From Clinical and Basic Research Perspective

Retinopathy, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinopathy of prematurity (ROP), are the leading cause of blindness among seniors, working-age populations, and children. However, the pathophysiology of retinopathy remains unclear. Accumulating studies demonstrate that amino acid metabolism is associated with retinopathy. This study discusses the characterization of amino acids in DR, AMD, and ROP by metabolomics from clinical and basic research perspectives. The features of amino acids in retinopathy were summarized using a comparative approach based on existing high-throughput metabolomics studies from PubMed. Besides taking up a large proportion, amino acids appear in both human and animal, intraocular and peripheral samples. Among them, some metabolites differ significantly in all three types of retinopathy, including glutamine, glutamate, alanine, and others. Studies on the mechanisms behind retinal cell death caused by glutamate accumulation are on the verge of making some progress. To develop potential therapeutics, it is imperative to understand amino acid-induced retinal functional alterations and the underlying mechanisms. This review delineates the significance of amino acid metabolism in retinopathy and provides possible direction to discover therapeutic targets for retinopathy.

Metabolic Characterization of Ocular Tissues in Relation to Laser-Induced Choroidal Neovascularization in Rats

Age-related macular degeneration is a metabolic compromise disorder whose main pathological feature is choroidal neovascularization (CNV) formation. Using untargeted metabolomics analysis, we determined to assess the metabolomic alterations in a CNV rat model to provide an insight into its pathogenesis. In the CNV model, there were 24 significantly changed metabolites in the plasma and 71 in various ocular tissues. Pathway analysis showed that certain metabolic pathways changed in interrelated tissues: for instance, in terms of the altered urea cycle, arginine and proline metabolism were increased in the plasma, while spermidine and spermine biosynthesis activities were increased in the retinal pigment epithelium (RPE)/choroid. The retina and RPE/choroid shared the same changed metabolites of branched-chain amino acid metabolism. Fatty acid metabolism was found to be the significant altered metabolic pathway in the retina of this CNV model. Although the metabolism pattern of different substances is specific for each ocular tissue, there is also a certain material exchange between different tissues. Dysregulated metabolomic profiles in differential tissues may point to an interconnected pathway, oxidative stress response, which may lead to RPE cell degeneration and, ultimately, CNV development.

Ferulic acid attenuates high-fat diet-induced hypercholesterolemia by activating classic bile acid synthesis pathway

Ferulic acid (FA), a natural phenolic phytochemical abundantly present in whole grains, displays promising therapeutic effects on hypercholesterolemia while its underlying mechanism not fully elucidated. This study aimed to investigate the cholesterol-lowering effect of FA in high-fat diet (HFD)-fed mice and its potential molecular mechanism. FA supplementation alleviated HFD-induced hypercholesterolemia (–13.2%, p < 0.05), along with increased excretion of bile acids (BAs) in feces (37.0%, p < 0.05). Mechanism studies showed that FA activated the expression of cholesterol 7α hydroxylase (CYP7A1), a rate-limiting enzyme in BA biosynthesis in the liver, which increased the BAs biosynthesis from cholesterol. Surprisingly, increased excretion of BAs in feces is a consequence, not a cause, of CYP7A1 activation. Furthermore, enterohepatic farnesoid X receptor (FXR) signaling is not involved in the activation of hepatic CYP7A1 by FA. In conclusion, FA activates CYP7A1 through non-FXR signaling, which on the one hand effectively prevents hypercholesterolemia, and on the other hand leads to secondary BAs elevation in plasma. The latter may be the key to the anti-obesity and hypoglycemic effects of FA.

Metabolomics and Biomarkers in Retinal and Choroidal Vascular Diseases

The retina is one of the most important structures in the eye, and the vascular health of the retina and choroid is critical to visual function. Metabolomics provides an analytical approach to endogenous small molecule metabolites in organisms, summarizes the results of “gene-environment interactions”, and is an ideal analytical tool to obtain “biomarkers” related to disease information. This study discusses the metabolic changes in neovascular diseases involving the retina and discusses the progress of the study from the perspective of metabolomics design and analysis. This study advocates a comparative strategy based on existing studies, which encompasses optimization of the performance of newly identified biomarkers and the consideration of the basis of existing studies, which facilitates quality control of newly discovered biomarkers and is recommended as an additional reference strategy for new biomarker discovery. Finally, by describing the metabolic mechanisms of retinal and choroidal neovascularization, based on the results of existing studies, this study provides potential opportunities to find new therapeutic approaches.

Artificial Intelligence Analysis of Biofluid Markers in Age-Related Macular Degeneration: A Systematic Review

This systematic review explores the use of artificial intelligence (AI) in the analysis of biofluid markers in age-related macular degeneration (AMD). We detail the accuracy and validity of AI in diagnostic and prognostic models and biofluid markers that provide insight into AMD pathogenesis and progression. This review was conducted in accordance with the Preferred Reporting Items for a Systematic Review and Meta-analysis guidelines. A comprehensive search was conducted across 5 electronic databases including Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, EMBASE, Medline, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics in AMD were included. Identified studies were assessed for risk of bias and critically appraised using the Joanna Briggs Institute Critical Appraisal tools. A total of 10,264 articles were retrieved from all databases and 37 studies met the inclusion criteria, including 15 cross-sectional studies, 15 prospective cohort studies, five retrospective cohort studies, one randomized controlled trial, and one case–control study. The majority of studies had a general focus on AMD (58%), while neovascular AMD (nAMD) was the focus in 11 studies (30%), and geographic atrophy (GA) was highlighted by three studies. Fifteen studies examined disease characteristics, 15 studied risk factors, and seven guided treatment decisions. Altered lipid metabolism (HDL-cholesterol, total serum triglycerides), inflammation (c-reactive protein), oxidative stress, and protein digestion were implicated in AMD development and progression. AI tools were able to both accurately differentiate controls and AMD patients with accuracies as high as 87% and predict responsiveness to anti-VEGF therapy in nAMD patients. Use of AI models such as discriminant analysis could inform prognostic and diagnostic decision-making in a clinical setting. The identified pathways provide opportunity for future studies of AMD development and could be valuable in the advancement of novel treatments.

Metabolite Changes in the Aqueous Humor of Patients With Retinal Vein Occlusion Macular Edema: A Metabolomics Analysis

Macular edema (ME) is the main cause of visual impairment in patients with retinal vein occlusion (RVO). The degree of ME affects the prognosis of RVO patients, while it lacks objective laboratory biomarkers. We aimed to compare aqueous humor samples from 28 patients with retinal vein occlusion macular edema (RVO-ME) to 27 age- and sex-matched controls by ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry, so as to identify the key biomarkers and to increase the understanding of the mechanism of RVO-ME at the molecular level. Through univariate and multivariate statistical analyses, we identified 60 metabolites between RVO-ME patients and controls and 40 differential metabolites in mild RVO-ME [300 μm ≤ central retinal thickness (CRT) < 400 μm] patients compared with severe RVO-ME (CRT ≥ 400 μm). Pathway enrichment analysis showed that valine, leucine, and isoleucine biosynthesis; ascorbate and aldarate metabolism; and pantothenate and coenzyme A biosynthesis were significantly altered in RVO-ME in comparison with controls. Compared with mild RVO-ME, degradation and biosynthesis of valine, leucine, and isoleucine; histidine metabolism; beta-alanine metabolism; and pantothenate and coenzyme A biosynthesis were significantly changed in severe RVO-ME. Furthermore, the receiver operating characteristic (ROC) curve analysis revealed that adenosine, threonic acid, pyruvic acid, and pyro-L-glutaminyl-l-glutamine could differentiate RVO-ME from controls with an area under the curve (AUC) of >0.813. Urocanic acid, diethanolamine, 8-butanoylneosolaniol, niacinamide, paraldehyde, phytosphingosine, 4-aminobutyraldehyde, dihydrolipoate, and 1-(beta-D-ribofuranosyl)-1,4-dihydronicotinamide had an AUC of >0.848 for distinguishing mild RVO-ME from severe RVO-ME. Our study expanded the understanding of metabolomic changes in RVO-ME, which could help us to have a good understanding of the pathogenesis of RVO-ME.

Plasma Metabolomics of Intermediate and Neovascular Age-Related Macular Degeneration Patients

To characterize metabolites and metabolic pathways altered in intermediate and neovascular age-related macular degeneration (IAMD and NVAMD), high resolution untargeted metabolomics was performed via liquid chromatography-mass spectrometry on plasma samples obtained from 91 IAMD patients, 100 NVAMD patients, and 195 controls. Plasma metabolite levels were compared between: AMD patients and controls, IAMD patients and controls, and NVAMD and IAMD patients. Partial least-squares discriminant analysis and linear regression were used to identify discriminatory metabolites. Pathway analysis was performed to determine metabolic pathways altered in AMD. Among the comparisons, we identified 435 unique discriminatory metabolic features. Using computational methods and tandem mass spectrometry, we identified 11 metabolic features whose molecular identities had been previously verified and confirmed the molecular identities of three additional discriminatory features. Included among the discriminatory metabolites were acylcarnitines, phospholipids, amino acids, and steroid metabolites. Pathway analysis revealed that lipid, amino acid, and vitamin metabolism pathways were altered in NVAMD, IAMD, or AMD in general, including the carnitine shuttle pathway which was significantly altered in all comparisons. Finally, few discriminatory features were identified between IAMD patients and controls, suggesting that plasma metabolic profiles of IAMD patients are more similar to controls than to NVAMD 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).

Metabolomics Analyses of Mouse Retinas in Oxygen-Induced Retinopathy

Purpose

Retinal neovascularization is a severe pathological process leading to irreversible blindness. This study aims to identify the altered metabolites and their related pathways that are involved in retinal neovascularization.

Methods

To reveal the global metabolomic profile change in the retinal neovascularization process, an untargeted metabolomics analysis of oxygen-induced retinopathy (OIR) mice retinas was carried out first, followed by the validation of amino acids and their derivatives through a targeted metabolomics analysis. The involved pathways were predicted by bioinformatic analysis.

Results

By untargeted metabolomics, a total of 58 and 49 metabolites altered significantly in OIR retinas under cationic and anionic modes, respectively. By bioinformatics analysis, “ABC transporters,” “central carbon metabolism in cancer.” and “alanine, aspartate, and glutamate metabolism” were the most enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with the changed metabolites. By targeted metabolomics, no significant change was found in the assessed amino acids and their derivatives at postnatal day (P) 12, whereas significantly altered amino acids and their derivatives were recognized at P13, P17, and P42 in OIR retinas.

Conclusions

The metabolomic profile was significantly altered in the neovascularized retinas. In particular, numerous amino acids and their derivatives were significantly changed in OIR retinas. These altered metabolites, together with their associated pathways, might be involved in the pathogenesis of retinal neovascular diseases.

Plasma levels of amino acids and derivatives in retinopathy of prematurity

Background: Retinopathy of prematurity (ROP) is a retinal disease that causes blindness in premature infants. This study aimed to reveal the changes in amino acids and derivatives in the plasma of ROP patients compared with premature infants without ROP. Methods: Metabolomics targeting amino acids and their derivatives was conducted to assess their plasma levels in ROP patients (n=58) and premature infants without ROP (n=25), and KEGG pathway analysis was used to identify the involved pathways. Results: Among the 31 assessed metabolites, the levels of 4 amino acids were significantly altered in the ROP group. Creatinine was downregulated in the plasma of the ROP patients, while the levels of citrulline, arginine, and aminoadipic acid were upregulated in the ROP group. Significant correlations were identified between the ROP stage and plasma levels of citrulline, creatinine, and aminoadipic acid. The involved pathways included biosynthesis of amino acids, arginine and proline metabolism, and arginine biosynthesis. Conclusion: The plasma levels of citrulline, creatinine, arginine, and aminoadipic acid were significantly changed in ROP patients. These metabolites could be considered potential biomarkers of ROP, and their related metabolic pathways might be involved in ROP pathogenesis.

Metabolomics in Age-Related Macular Degeneration: A Systematic Review

Purpose

Age-related macular degeneration (AMD) is one of the leading causes of blindness among the elderly, and the exact pathogenesis of the AMD remains unclear. The purpose of this review is to summarize potential metabolic biomarkers and pathways of AMD that might facilitate risk predictions and clinical diagnoses of AMD.

Methods

We obtained relevant publications of metabolomics studies of human beings by systematically searching the MEDLINE (PubMed) database before June 2020. Studies were included if they performed mass spectrometry-based or nuclear magnetic resonance-based metabolomics approach for humans. In addition, AMD was assessed from fundus photographs based on standardized protocols. The metabolic pathway analysis was performed using MetaboAnalyst 3.0.

Results

Thirteen studies were included in this review. Repeatedly identified metabolites including phenylalanine, adenosine, hypoxanthine, tyrosine, creatine, citrate, carnitine, proline, and maltose have the possibility of being biomarkers of AMD. Validation of the biomarker panels was observed in one study. Dysregulation of metabolic pathways involves lipid metabolism, carbohydrate metabolism, nucleotide metabolism, amino acid metabolism, and translation, which might play important roles in the development and progression of AMD.

Conclusions

This review summarizes the potential metabolic biomarkers and pathways related to AMD, providing opportunities for the construction of diagnostic or predictive models for AMD and the discovery of new therapeutic targets.

Acylcarnitine Abnormalities Implicate Mitochondrial Dysfunction in Patients With Neovascular Age-Related Macular Degeneration

Purpose

Abnormalities in lipid metabolism are implicated in age-related macular degeneration (AMD), but the pathways involved remain unclear. We assessed whether acylcarnitine concentrations, a marker of lipid and mitochondrial metabolism, differed between patients with AMD and controls.

Methods

In this cross-sectional case-control study, cases (n = 81) had neovascular AMD and controls (n = 79) had cataract with no other ocular pathology. Participants were recruited from eye clinics in Western Sydney, Australia, between 2016 and 2018. Plasma blood samples were collected and liquid chromatography mass spectrometry analyses performed to identify acylcarnitine concentrations. Acylcarnitine levels were adjusted for age, gender and smoking in multivariable models. Confirmation of key acylcarnitine identities was conducted using high mass accuracy liquid chromatography-tandem mass spectrometry.

Results

After multivariable adjustment, C2-carnitine (acetylcarnitine) levels were significantly lower in patients with neovascular AMD compared to controls (0.810 ± 0.053 (standard error) compared to 1.060 ± 0.053), p = 0.002). C18:2-DC carnitine (a dicarboxylic acylcarnitine with a 18 carbon side chain and 2 double bonds), levels were significantly higher in patients with neovascular AMD compared to controls (1.244 ± 0.046 compared to 1.013 ± 0.046), p = 0.001). Other acylcarnitines examined were not significantly different between cases and controls.

Conclusions

Reduced plasma levels of C2-carnitine (acetylcarnitine) and increased plasma levels of C18:2-DC carnitine were observed in patients with neovascular AMD compared to controls. These findings suggest mitochondrial dysfunction could be involved in the pathogenesis of neovascular AMD.

Metabolomic analysis of the aqueous humor from patients with central retinal vein occlusion using UHPLC-MS/MS

Central retinal vein occlusion (CRVO) is one of the retinal fundus diseases and may result in irreversible visual impairment. Metabolic dysfunction has been proved to play an essential role in the pathogenesis of CRVO. We performed untargeted metabolomic analysis of the aqueous humor (AH) of patients with CRVO and controls using UHPLC-MS/MS. A total of 248 metabolites were identified in the tested AH samples, 37 of which allowed for the construction of an orthogonal partial least squares discriminant analysis model with good predictive capability (Q2cum = 0.834) and low risk of overfitting. The components contributing the most to the metabolomic signature of CRVO were those related to amino acid metabolism, carbohydrates, and fatty acid metabolites (variable importance on projection>1.0 and p < 0.05). The CRVO group appeared to have a lower AH concentration of carbohydrates and amino acids, but a relative higher concentration of carnitine-associated energetic substrates (butyryl carnitine, deoxycarnitine, N6-trimethyl-l-lysine) and osmolytes compared with those of the control group. These results indicate that patients with CRVO may have ocular aberrations in metabolic pathways involving certain amino acids, fatty acids, and carbohydrates. These metabolite changes might correlate with energy dysfunction and inflammation response in the AH of CRVO patients. This finding may provide insight into the pathophysiology of CRVO for the development of new therapeutic strategies.