Prediagnostic Plasma Metabolomics and the Risk of Exfoliation Glaucoma

Machine Learning on Prediagnostic Metabolite Data Identifies Etiologic Endotypes of Exfoliation Glaucoma in United States Health Professionals

Purpose

Exfoliation glaucoma (XFG) etiology is poorly understood. Metabolomics-based etiologic endotypes of XFG may provide novel etiologic insights. We aimed to use unsupervised machine learning on prediagnostic plasma metabolites to characterize etiologic XFG endotypes.

Design

Prospective case-only analysis.

Participants

Among Nurses' Health Study and Health Professionals Follow-up Study participants, 205 (174 female and 31 male) incident XFG cases diagnosed with an average of 11.8 years following blood collection (1989-1995) were included.

Methods

We identified and confirmed incident cases of XFG or XFG suspect (collectively called "XFG" henceforth) through 2016 with medical record review. Liquid chromatography-mass spectrometry was used to profile 341 plasma metabolites. After preprocessing prediagnostic metabolites with adjustment for season, time of blood draw, and fasting status, we computed a distance matrix using Pearson distance and computed gap statistics to identify distinct endotypes.

Main Outcome Measures

Metabolomics-based XFG etiologic endotypes. Metabolomic profiles were compared across endotypes; false discovery rate (FDR) was used to account for multiple comparisons in Metabolite Set Enrichment Analyses. Exfoliation glaucoma environmental risk factors (e.g., lifetime ultraviolet (UV) exposure, folate consumption), a genetic risk score incorporating 8 major single nucleotide polymorphisms for exfoliation syndrome, and clinical presentations were compared across endotypes.

Results

We identified 3 distinct XFG metabolomic endotypes. Compared with the most common endotype 2 (reference group [n = 90; 43.9%]), endotype 1 (n = 56; 27.3%) tended to include more male southern US residents with greater UV exposure and were the least likely to have cardiovascular disease; among women, a higher percentage were postmenopausal. Endotype 3 (n = 59; 28.8%) was associated with being a male northern US resident; a higher prevalence of cardiovascular disease and risk factors such as higher body mass index, diabetes, hypertension, and dyslipidemia; and the lowest genetic susceptibility score. There were no differences in ophthalmic characteristics (e.g., maximum intraocular pressure, bilaterality, age at diagnosis) across endotypes (P ≥ 0.6). In metabolite class analyses, compared with endotype 2, organic acids and carnitines were positively associated with endotype 1, whereas diacylglycerols and triacylglycerols were positively associated with endotype 3 (FDR <0.05).

Conclusions

Integrated metabolomic profiling can identify distinct XFG etiologic endotypes, suggesting different pathobiological mechanisms.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Exfoliation syndrome genetics in the era of post-GWAS

Exfoliation syndrome (XFS), or pseudoexfoliation syndrome, is considered a systemic disorder that leads to glaucoma with progressive visual field loss. A better insight into the underlying pathogenic mechanism will help diagnose the disease and prevent and slow progression. Here, we provide an overview of disease pathogenesis in the light of GWAS and multi-omics research. We discuss possible environmental interactions related to XFS. We investigate the potential interactions in differentially expressed genes from RNA-Seq by using Ingenuity Pathway Analysis. MAPK pathway was identified as the top network of these genes. Further investigation is needed to verify our results in vivo. It is necessary to establish an animal model mimicking exfoliation syndrome phenotypes.

Impact of Forms of Visual Attenuation on Short-Term Eye Changes Under Controlled Reading Visibility

Purpose

Animal studies have suggested that visual degradation impacts eye growth due to the attenuation of high spatial frequencies. However, the influence of perceptual visibility remains unclear in humans. The aim of this study was to investigate the impact of visibility on visual attenuation-related eye changes during reading.

Methods

Axial length (AxL) and choroidal thickness (ChT) changes associated with reading tasks were measured in two separate experiments. In the first experiment, the reading task was conducted under different forms of visual attenuation (contrast, resolution, defocus, noise, and crowding). For each form of visual attenuation, the text was set at a sub-threshold level of visibility, evaluated via prior measurement of reading performance, and kept constant via adaptive control of the intensity of the stimulation. Each sub-threshold reading condition was compared with a supra-threshold reading text, serving as control. In the second experiment, the effect of visibility on lens-induced defocus was further examined by comparing the effect of text stimulation with an equivalent dioptric of 5.5 D under sub- and supra-threshold levels of resolution.

Results

Near distance reading with supra-threshold texts caused eye elongation (AxL: +12.942 µm ± 2.147 µm; ChT: -3.192 µm ± 1.158 µm). Additional defocusing failed to exacerbate axial elongation under sub-threshold text visibility (mean difference: -0.135 µm ± 2.783 µm), revealing a clear inhibitory effect of lowering visibility on eye changes. Other forms of visual degradation, including crowding (mean difference: 6.153 µm ± 2.127 µm) and noise (mean difference: 5.02 µm ± 2.812 µm) also showed an inhibitory effect on eye elongation. The significant effect of crowding indicated that post-retinal mechanisms, involving attentional processes related to crowded characters, may play a role in the influence of visibility.

Conclusion

Although the featural composition of visual stimulation can drastically influence eye changes, this study revealed an important mediating role of visibility, previously underscored in chick studies, which warrants further explorations of the impact of post-retinal processes in eye growth.

Metabolomics studies in common multifactorial eye disorders: a review of biomarker discovery for age-related macular degeneration, glaucoma, diabetic retinopathy and myopia

Introduction

Multifactorial Eye disorders are a significant public health concern and have a huge impact on quality of life. The pathophysiological mechanisms underlying these eye disorders were not completely understood since functional and low-throughput biological tests were used. By identifying biomarkers linked to eye disorders, metabolomics enables early identification, tracking of the course of the disease, and personalized treatment.

Methods

The electronic databases of PubMed, Scopus, PsycINFO, and Web of Science were searched for research related to Age-Related macular degeneration (AMD), glaucoma, myopia, and diabetic retinopathy (DR). The search was conducted in August 2023. The number of cases and controls, the study's design, the analytical methods used, and the results of the metabolomics analysis were all extracted. Using the QUADOMICS tool, the quality of the studies included was evaluated, and metabolic pathways were examined for distinct metabolic profiles. We used MetaboAnalyst 5.0 to undertake pathway analysis of differential metabolites.

Results

Metabolomics studies included in this review consisted of 36 human studies (5 Age-related macular degeneration, 10 Glaucoma, 13 Diabetic retinopathy, and 8 Myopia). The most networked metabolites in AMD include glycine and adenosine monophosphate, while methionine, lysine, alanine, glyoxylic acid, and cysteine were identified in glaucoma. Furthermore, in myopia, glycerol, glutamic acid, pyruvic acid, glycine, cysteine, and oxoglutaric acid constituted significant metabolites, while glycerol, glutamic acid, lysine, citric acid, alanine, and serotonin are highly networked metabolites in cases of diabetic retinopathy. The common top metabolic pathways significantly enriched and associated with AMD, glaucoma, DR, and myopia were arginine and proline metabolism, methionine metabolism, glycine and serine metabolism, urea cycle metabolism, and purine metabolism.

Conclusion

This review recapitulates potential metabolic biomarkers, networks and pathways in AMD, glaucoma, DR, and myopia, providing new clues to elucidate disease mechanisms and therapeutic targets. The emergence of advanced metabolomics techniques has significantly enhanced the capability of metabolic profiling and provides novel perspectives on the metabolism and underlying pathogenesis of these multifactorial eye conditions. The advancement of metabolomics is anticipated to foster a deeper comprehension of disease etiology, facilitate the identification of novel therapeutic targets, and usher in an era of personalized medicine in eye research.

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).