Serum metabolic signatures of high myopia among older Chinese adults

Glutathione and a Pool of Metabolites Partly Related to Oxidative Stress Are Associated with Low and High Myopia in an Altered Bioenergetic Environment

Oxidative stress forms part of the molecular basis contributing to the development and manifestation of myopia, a refractive error with associated pathology that is increasingly prevalent worldwide and that subsequently leads to an upsurge in degenerative visual impairment due to conditions that are especially associated with high myopia. The purpose of our study was to examine the interrelation of potential oxidative-stress-related metabolites found in the aqueous humor of high-myopic, low-myopic, and non-myopic patients within a clinical study. We conducted a cross-sectional study, selecting two sets of patients undergoing cataract surgery. The first set, which was used to analyze metabolites through an NMR assay, comprised 116 patients. A total of 59 metabolites were assigned and quantified. The PLS-DA score plot clearly showed a separation with minimal overlap between the HM and control samples. The PLS-DA model allowed us to determine 31 major metabolite differences in the aqueous humor of the study groups. Complementary statistical analysis of the data allowed us to determine six metabolites that presented significant differences among the experimental groups (p < 005). A significant number of these metabolites were discovered to have a direct or indirect connection to oxidative stress linked with conditions of myopic eyes. Notably, we identified metabolites associated with bioenergetic pathways and metabolites that have undergone methylation, along with choline and its derivatives. The second set consisted of 73 patients who underwent a glutathione assay. Here, we showed significant variations in both reduced and oxidized glutathione in aqueous humor among all patient groups (p < 0.01) for the first time. Axial length, refractive status, and complete ophthalmologic examination were also recorded, and interrelations among metabolic and clinical parameters were evaluated.

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.

Metabolomic profiling of ocular tissues in rabbit myopia: Uncovering differential metabolites and pathways

To investigate the metabolic difference among tissue layers of the rabbits' eye during the development of myopia using metabolomic techniques and explore any metabolic links or cascades within the ocular wall. Ultra Performance Liquid Chromatography - Mass Spectrometry (UPLC-MS) was utilized for untargeted metabolite screening (UMS) to identify the significant differential metabolites produced between myopia (MY) and control (CT) (horizontal). Subsequently, we compared those key metabolites among tissues (Sclera, Choroid, Retina) of MY for distribution and variation (longitudinal). A total of 6285 metabolites were detected in the three tissues. The differential metabolites were screened and the metabolic pathways of these metabolites in each myopic tissue were labeled, including tryptophan and its metabolites, pyruvate, taurine, caffeine metabolites, as well as neurotransmitters like glutamate and dopamine. Our study suggests that multiple metabolic pathways or different metabolites under the same pathway, might act on different parts of the eyeball and contribute to the occurrence and development of myopia by affecting the energy supply to the ocular tissues, preventing antioxidant stress, affecting scleral collagen synthesis, and regulating various neurotransmitters mutually.

Differences in change of post-operative antioxidant levels between laser-assisted lenticule extraction and femtosecond laser in situ keratomileusis

To evaluate the change of total antioxidant capacity (TAC) and ascorbic acid (AA) between femtosecond laser in situ keratomileusis (FS-LASIK) and laser-assisted lenticule extraction (LALEX). A prospective non-randomized study was conducted, and 33 and 75 eyes that had undergone FS-LASIK or LALEX surgeries were enrolled, respectively. The tear films near corneal incisions were collected, and the concentrations of TAC and AA were determined. The generalized linear mixed model was adopted to calculate the adjusted odds ratio (aOR) with 95% confidence interval (CI) of TAC and AA between the two groups. The AA reduction was significant 1 month after the LALEX and FS-LASIK procedures (both p < 0.05), and the decrement in AA level was significantly larger in the FS-LASIK group compared to the LALEX group (p = 0.0002). In the subgroup analysis, the LALEX group demonstrated a lower decrement in TAC level in the individuals with dry eye disease (DED) than the FS-LASIK group (p = 0.0424), and the LALEX group demonstrated a significantly lower AA decrement in the participants with high myopia (p = 0.0165) and DED (p = 0.0043). The LALEX surgery causes lesser AA decrement compared to FS-LASIK surgery especially for the patients with DED.

Corneal metabolic biomarkers for moderate and high myopia in human

This study aimed to identify the corneal metabolic biomarkers for moderate and high myopia in human. We enrolled 221 eyes from 221 subjects with myopia to perform the femtosecond laser small incision lenticule extraction (SMILE) surgery. Among these, 71 eyes of 71 subjects were enrolled in the low myopic group, 75 eyes of 75 subjects in the moderate myopic group and 75 eyes of 75 subjects in the high myopic group. The untargeted metabolomics analysis was performed to analyze the corneal tissues extracted during the SMILE surgery using an ultra-high-performance liquid chromatography (UHPLC) coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometry (MS). The one-way analysis of variance (ANOVA) was used to identify the different metabolites among the three myopic groups, the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was used to reveal the different metabolites between moderate myopia and low myopia, and between high myopia and low myopia. The Venn gram was used to find the overlapped metabolites of the three datasets of the different metabolites. The stepwise multiple linear regression analysis was used to determine the metabolic molecules associated with manifest refractive spherical equivalents (MRSE). The Receiver Operating Characteristics (ROC) analysis was performed to reveal the corneal biomarkers for moderate and high myopia. The hub biomarker was further selected by the networks among different metabolites created by the Cytoscape software. A total of 1594 metabolites were identified in myopic corneas. 321 metabolites were different among the three myopic groups, 106 metabolites were different between high myopic corneas and low myopic corneas, 104 metabolites were different between moderate myopic corneas and low myopic corneas, and 30 metabolic molecules overlapped among the three datasets. The multivariate linear regression analysis revealed the myopic degree was significantly influenced by the corneal levels of azelaic acid, arginine-proline (Arg-Pro), 1-stearoyl-2-myristoyl-sn-glycero-3-phosphocholine, and hypoxanthine. The ROC curve analysis showed that azelaic acid, Arg-Pro and hypoxanthine were effective in discriminating low myopia from moderate to high myopia with the area under the curve (AUC) values as 0.982, 0.991 and 0.982 for azelaic acid, Arg-Pro and hypoxanthine respectively. The network analysis suggested that Arg-Pro had the maximum connections among these three biomarkers. Thus, this study identified azelaic acid, Arg-Pro and hypoxanthine as corneal biomarkers to discriminate low myopia from moderate to high myopia, with Arg-Pro serving as the hub biomarker for moderate and high myopia.

RNA-Sequencing Analysis Reveals the Role of Mitochondrial Energy Metabolism Alterations and Immune Cell Activation in Form-Deprivation and Lens-Induced Myopia in Mice

Myopia is a substantial global public health concern primarily linked to the elongation of the axial length of the eyeball. While numerous animal models have been employed to investigate myopia, the specific contributions of genetic factors and the intricate signaling pathways involved remain incompletely understood. In this study, we conducted RNA-seq analysis to explore genes and pathways in two distinct myopia-inducing mouse models: form-deprivation myopia (FDM) and lens-induced myopia (LIM). Comparative analysis with a control group revealed significant differential expression of 2362 genes in FDM and 503 genes in LIM. Gene Set Enrichment Analysis (GSEA) identified a common immune-associated pathway between LIM and FDM, with LIM exhibiting more extensive interactions. Notably, downregulation was observed in OxPhos complex III of FDM and complex IV of LIM. Subunit A of complex I was downregulated in LIM but upregulated in FDM. Additionally, complex V was upregulated in LIM but downregulated in FDM. These findings suggest a connection between alterations in energy metabolism and immune cell activation, shedding light on a novel avenue for understanding myopia's pathophysiology. Our research underscores the necessity for a comprehensive approach to comprehending myopia development, which integrates insights from energy metabolism, oxidative stress, and immune response pathways.

Prevalent falls, fall frequencies and health-related quality of life among community-dwelling older Chinese adults

PURPOSE

Fall is a serious health hazard to older adults. The aim of our study was to investigate the relationship between falls and health-related quality of life (HRQOL) in mainland China.

METHODS

Data from 4579 Chinese community-dwelling older adults was analyzed. Data of falls was self-reported by participants, the HRQOL of older adults was measured by the 3-Level EQ-5D (EQ-5D-3L, 3L). Regression models were built to explore the associations of falls (experience and frequency) with the 3L data (index score, EQ-VAS score and health problems). The potential interaction effects between falls and gender on HRQOL were assessed using a likelihood ratio test, sex-stratified analysis was also performed to separately investigate the associations in men and women.

RESULTS

A total of 368 (8.0%) participants had the experience of fall during the last year. Falls (experience and frequency) were significantly related to EQ-5D-3L index and EQ-VAS scores, fall experience contributed to pain/discomfort and anxiety/depression problems, while fall frequency was associated with physical-related problems and pain/discomfort. Significant interactions between falls and sex in several EQ-5D measures were also observed, and men had lager magnitude of associations than women.

CONCLUSION

Falls were negative associated with overall HRQOL as well as separate HRQOL dimensions among older adults. It also appears that the HRQOL influence on older men is more evident than older women.

Tear inflammatory cytokines as potential biomarkers for myopic macular degeneration

Previous studies have reported that inflammatory cytokine levels increase in the intraocular fluids (aqueous humor and vitreous) of highly myopic eyes, However, there has been currently no study revealing the levels of inflammatory cytokines in tear. Therefore, this study aimed to determine tear cytokine levels of highly myopic eyes, and their relationships with myopic macular degeneration (MMD). This case-control study screened inflammatory cytokines of tear samples from 132 highly myopic and 105 emmetropic eyes using a multiplex cytokine antibody array, and cytokines showing significant intergroup differences were further validated using ProQuantum immunoassays in tear samples from another 60 highly myopic and 60 emmetropic eyes. Ultra-widefield fundus photographs of eyes were classified according to the meta-analyses of the Pathologic Myopia Classification. Associations between tear cytokine levels and MMD category were investigated. As a result, tear levels of interleukin (IL)-6, IL-13 and monocyte chemoattractant protein (MCP)-1 were screened significantly higher in highly myopic eyes than in emmetropic controls (IL-6: 11.70 ± 16.81 versus 8.22 ± 10.76 pg/mL; MCP-1: 63.60 ± 54.40 versus 33.87 ± 43.82 pg/mL; both P < 0.05). Validation assays further demonstrated the elevated concentrations of IL-6 and MCP-1 (IL-6: 13.97 ± 8.41 versus 8.06 ± 7.94 pg/mL, P < 0.001; MCP-1: 32.69 ± 8.41 versus 18.07 ± 8.41 pg/mL, P = 0.003). Tear levels of IL-6 and MCP-1 differed significantly among MMD categories (both P < 0.05). The area under receiver operating characteristic curve were 0.783 and 0.682 respectively (both P < 0.05), when using tear IL-6 and MCP-1 levels to predict the presence of MMD (category ≥2). The ordered logistic regression model also indicated that longer axial length, and higher IL-6 and MCP-1 tear levels were independent predictors of higher MMD category. In our study, highly myopic eyes presented significantly higher levels of tear IL-6 and MCP-1, which may also serve as potential biomarkers for MMD.

Vitreous metabolomic signatures of pathological myopia with complications

BACKGROUND

Pathological myopia (PM) is closely associated with blinding ocular morbidities. Identifying biomarkers can provide clues on pathogeneses. This study aimed to identify metabolic biomarkers and underlying mechanisms in the vitreous humour (VH) of PM patients with complications.

METHODS

VH samples were collected from 39 PM patients with rhegmatogenous retinal detachment (RRD) (n = 23) or macular hole (MH)/myopic retinoschisis (MRS) (n = 16) and 23 controls (MH with axial length < 26 mm) who underwent surgical treatment. VH metabolomic profiles were investigated using ultra-performance liquid chromatography‒mass spectrometry. The area under the receiver operating characteristic curve (AUC) was computed to identify potential biomarkers for PM diagnosis.

RESULTS

Bioinformatics analysis identified nineteen and four metabolites altered in positive and negative modes, respectively, and these metabolites were involved in tryptophan metabolism. Receiver operating characteristic analysis showed that seventeen metabolites (AUC > 0.6) in the positive mode and uric acid in the negative mode represent potential biomarkers for PM with complications (AUC = 0.894). Pairwise and pathway analyses among the RRD-PM, MH/MRS-PM and control groups showed that tryptophan metabolism and uric acid were closely correlated with PM. Altered metabolites and pathways in our study were characterized by increased oxidative stress and altered energy metabolism. These results contribute to a better understanding of myopia progression with or without related complications.

CONCLUSIONS

Our study provides metabolomic signatures and related immunopathological features in the VH of PM patients, revealing new insight into the prevention and treatment of PM and related complications.

Retinal Neurotransmitter Alteration in Response to Dopamine D2 Receptor Antagonist from Myopic Guinea Pigs

This study aimed to investigate the changes in retinal neurotransmitters and the role of the dopamine D2 receptor (D2R) pathway in regulating the myopic refractive state. Tricolor guinea pigs were randomly divided into two groups: the normal control group (NC) and the form-deprivation myopia group (FDM). Animals in the FDM group had their right eye covered with a balloon for 4 weeks. These two groups were further divided into two subgroups based on intravitreal injection with D2R antagonist sulpiride once a week for 3 weeks (NC, NC-Sul, FDM, and FDM-Sul groups). Ultrahigh-performance liquid chromatography-tandem mass spectrometry was used to quantitatively detect the changes in 17 retinal neurotransmitters. Compared to the NC group, the concentrations of dopamine (DA) and γ-aminobutyric acid (GABA) decreased, while those of glutamate (Glu), 3-methoxytyramine (3-MT), and glycine increased, accompanied by an increase in myopic refraction and axial length (AL) in the FDM group. In the FDM-Sul group, glycine and DA levels were upregulated, whereas 3-MT and Glu levels were downregulated, accompanied by a decrease in myopic refraction and AL. The ratio of Glu to GABA (RGG) represents the balance between excitatory and inhibitory neurotransmitters. Notably, RGG changes occurred with corresponding AL changes, which increased in the FDM group and decreased in the FDM-Sul group. Decreased retinal DA concentration, with an increase in Glu, may be involved in the myopia progression. D2R antagonists might effectively slow myopia progression by increasing retinal DA, regulating Glu concentration to match GABA, and maintaining the balance between excitatory and inhibitory neurotransmitters.

Effects of Hypoxemia by Acute High-Altitude Exposure on Human Intestinal Flora and Metabolism

This study examined the effects of hypoxemia caused by acute high-altitude hypoxia (AHAH) exposure on the human intestinal flora and its metabolites. The changes in the intestinal flora, metabolism, and erythropoietin content in the AHAH population under altitude hypoxia conditions were comprehensively analyzed using 16S rRNA sequencing, metabonomics, and erythropoietin content. The results showed that compared with those in the control group (C group), the flora and metabolites in the hypoxemia group (D group) were altered. We found alterations in the flora according to the metabolic marker tyrosine through random forest and ROC analyses. Fecal and serum metabonomics analyses revealed that microbial metabolites could be absorbed into the blood and participate in human metabolism. Finally, a significant correlation between tyrosine and erythropoietin (EPO) content was found, which shows that human intestinal flora and its metabolites can help to confront altitude stress by regulating EPO levels. Our findings provide new insights into the adaptive mechanism and prevention of AHAH.

Metabolomic Profiling of Aqueous Humor from Pathological Myopia Patients with Choroidal Neovascularization

Choroidal neovascularization (CNV) is a severe complication observed in individuals with pathological myopia (PM). Our hypothesis is that specific metabolic alterations occur during the development of CNV in patients with PM. To investigate this, an untargeted metabolomics analysis was conducted using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) on aqueous humor (AH) samples obtained from meticulously matched PM patients, including those with CNV (n = 11) and without CNV (n = 11). The analysis aimed to identify differentially expressed metabolites between the two groups. Furthermore, the discriminative ability of each metabolite was evaluated using the area under the receiver operating characteristic curve (AUC). Enriched metabolic pathways were determined using the KEGG and MetaboAnalyst databases. Our results revealed the detection of 272 metabolites using GC-MS and 1457 metabolites using LC-MS in AH samples. Among them, 97 metabolites exhibited significant differential expression between the CNV and non-CNV groups. Noteworthy candidates, including D-citramalic acid, biphenyl, and isoleucylproline, demonstrated high AUC values ranging from 0.801 to 1, indicating their potential as disease biomarkers. Additionally, all three metabolites showed a strong association with retinal cystoid edema in CNV patients. Furthermore, the study identified 12 altered metabolic pathways, with five of them related to carbohydrate metabolism, suggesting their involvement in the occurrence of myopic CNV. These findings provide possible disease-specific biomarkers of CNV in PM and suggest the role of disturbed carbohydrate metabolism in its pathogenesis. Larger studies are needed to validate these findings.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Metabolomics facilitates the discovery of metabolic profiles and pathways for myopia: A systematic review

BACKGROUND

Myopia is one of the major eye disorders and the global burden is increasing rapidly. Our purpose is to systematically summarize potential metabolic biomarkers and pathways in myopia to facilitate the understanding of disease mechanisms as well as the discovery of novel therapeutic measures.

METHODS

Myopia-related metabolomics studies were searched in electronic databases of PubMed and Web of Science until June 2021. Information regarding clinical and demographic characteristics of included studies and metabolomics findings were extracted. Myopia-related metabolic pathways were analysed for differential metabolic profiles, and the quality of included studies was assessed based on the QUADOMICS tool. Pathway analyses of differential metabolites were performed using bioinformatics tools and online software such as the Metaboanalyst 5.0.

RESULTS

The myopia-related metabolomics studies included in this study consisted of seven human and two animal studies. The results of the study quality assessment showed that studies were all phase I studies and all met the evaluation criteria of 70% or more. The myopia-control serum study identified 23 differential metabolites with the Sphingolipid metabolism pathway beings enriched. The high myopia-cataract aqueous humour study identified 40 differential metabolites with the Arginine biosynthesis pathway being enriched. The high myopia-control serum study identified 43 differential metabolites and 4 pathways were significantly associated with metabolites including Citrate cycle; Alanine, aspartate and glutamate metabolism; Glyoxylate and dicarboxylate metabolism; Biosynthesis of unsaturated fatty acids (all P value < 0.05).

CONCLUSIONS

This study summarizes potential metabolic biomarkers and pathways in myopia, providing new clues to elucidate disease mechanisms.

Machine Learning-Based Integration of Metabolomics Characterisation Predicts Progression of Myopic Retinopathy in Children and Adolescents

Myopic retinopathy is an important cause of irreversible vision loss and blindness. As metabolomics has recently been successfully applied in myopia research, this study sought to characterize the serum metabolic profile of myopic retinopathy in children and adolescents (4-18 years) and to develop a diagnostic model that combines clinical and metabolic features. We selected clinical and serum metabolic data from children and adolescents at different time points as the training set (n = 516) and the validation set (n = 60). All participants underwent an ophthalmologic examination. Untargeted metabolomics analysis of serum was performed. Three machine learning (ML) models were trained by combining metabolic features and conventional clinical factors that were screened for significance in discrimination. The better-performing model was validated in an independent point-in-time cohort and risk nomograms were developed. Retinopathy was present in 34.2% of participants (n = 185) in the training set, including 109 (28.61%) with mild to moderate myopia. A total of 27 metabolites showed significant variation between groups. After combining Lasso and random forest (RF), 12 modelled metabolites (mainly those involved in energy metabolism) were screened. Both the logistic regression and extreme Gradient Boosting (XGBoost) algorithms showed good discriminatory ability. In the time-validation cohort, logistic regression (AUC 0.842, 95% CI 0.724-0.96) and XGBoost (AUC 0.897, 95% CI 0.807-0.986) also showed good prediction accuracy and had well-fitted calibration curves. Three clinical characteristic coefficients remained significant in the multivariate joint model (p < 0.05), as did 8/12 metabolic characteristic coefficients. Myopic retinopathy may have abnormal energy metabolism. Machine learning models based on metabolic profiles and clinical data demonstrate good predictive performance and facilitate the development of individual interventions for myopia in children and adolescents.

A review of study designs and data analyses in metabolomics studies in myopia

Metabolomics analyzes the entire range of small molecule metabolites in biological systems to reveal the response signals that are transmitted from "genetics and environment", which could help us understand complex phenotypes of diseases. Metabolomics has been successfully applied to the study of eye diseases including age-related macular degeneration, glaucoma, and diabetic retinopathy. In this review, we summarize the findings of myopic metabolomics and discuss them from a design and analysis perspective. Finally, we provide new ideas for the future development of myopia metabolomics research based on the broader ocular metabolomics study.

Omics in Myopia

Myopia is a globally emerging issue, with multiple medical and socio-economic burdens and no well-established causal treatment thus far. A better insight into altered biochemical pathways and underlying pathogenesis might facilitate early diagnosis and treatment of myopia, ultimately leading to the development of more effective preventive and therapeutic measures. In this review, we summarize current data about the metabolomics and proteomics of myopia in humans and present various experimental approaches and animal models, along with their strengths and weaknesses. We also discuss the potential applicability of these findings to medical practice and suggest directions for future research.