Metabolomic Analysis of Aqueous Humor Identifies Aberrant Amino Acid and Fatty Acid Metabolism in Vogt-Koyanagi-Harada and Behcet's Disease

Effect of serum metabolites on the risk of iridocyclitis: a bidirectional Mendelian randomization study

Previous research has linked serum metabolite levels to iridocyclitis, yet their causal relationship remains unexplored. This study investigated this potential causality by analyzing pooled data from 7824 iridocyclitis patients in a Genome-Wide Association Study (GWAS) using Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC). Employing rigorous quality control and comprehensive statistical methods, including sensitivity analyses, we examined the influence of 486 serum metabolites on iridocyclitis. Our MR analysis identified 23 metabolites with significant causal effects on iridocyclitis, comprising 17 known and 6 unidentified metabolites. Further refinement using Cochran's Q test and MR-PRESSO indicated 16 metabolites significantly associated with iridocyclitis risk. LDSC highlighted the heritability of certain metabolites, underscoring genetic influences on their levels. Notably, tryptophan, proline, theobromine, and 7-methylxanthine emerged as risk factors, while 3,4-dihydroxybutyrate appeared protective. These findings enhance our understanding of the metabolic interactions in iridocyclitis, offering insights for diagnosis, unraveling pathophysiological mechanisms, and informing potential avenues for prevention and personalized treatment.

Alternations in the human skin, gut and vaginal microbiomes in perimenopausal or postmenopausal Vulvar lichen sclerosus

Vulvar lichen sclerosus (VLS) is a chronic and progressive dermatologic condition that can cause physical dysfunction, disfigurement, and impaired quality of life. However, the etiology of VLS remains unknown. The vulvar skin, intestinal and vaginal microbiomes have been postulated to play important roles in the pathogenesis of this disease. The aim of this study was to compare the compositional characteristics of the vulvar skin, vagina, and gut microbiota between perimenopausal or postmenopausal VLS patients and healthy controls. The study involved six perimenopausal or postmenopausal VLS patients which were based on characteristic clinical manifestations and histologic confirmation and five healthy controls. The pruritus severity of each patient was evaluated using the NRS scale, and the dermatology-specific health-related quality of life was assessed using the Skindex-16. Metagenomic sequencing was performed, and the results were analyzed for alpha and beta diversity. LEfSe analysis were used to investigate the microbial alterations in vulvar skin, gut and vagina. KEGG databases were used to analyze differences in functional abundance. The study found significant differences in alpha diversity between the two groups in stool and vaginal samples (P < 0.05). Patients with VLS had a higher abundance of Enterobacter cloacae, Flavobacterium_branchiophilum, Mediterranea_sp._An20, Parabacteroides_johnsoniiand Streptococcus_bovimastitidis on the vulvar skin, while Corynebacterium_sp._zg-913 was less abundant compared to the control group. The relative abundance of Sphingomonas_sp._SCN_67_18, Sphingobium_sp._Ant17, and Pontibacter_sp_BT213 was significantly higher in the gut samples of patients with VLS.Paenibacillus_popilliae,Gemella_asaccharolytica, and Coriobacteriales_bacterium_DNF00809 compared to the control group. Additionally, the vaginal samples of patients with VLS exhibited a significantly lower relative abundance of Bacteroidales_bacterium_43_8, Bacteroides_sp._CAG:20, Blautia_sp._AM28-10, Fibrobacter_sp._UWB16, Lachnospiraceae_bacterium_AM25-39, Holdemania_filiformis, Lachnospiraceae_bacterium_GAM79, and Tolumonas_sp. Additionally, the butyrate-producing bacterium SS3/4 showed a significant difference compared to the controls. The study found a negative relationship between Sphingobium_sp._Ant17 in stool and Skindex-16 (P < 0.05), while Mediterranea_sp._An20 had a positive correlation with Skindex-16 (P < 0.05) in the skin. Additionally, our functional analysis revealed alterations in Aminoacyl_tRNA_biosynthesis, Glutathione_metabolism, the pentose phosphate pathway, and Alanine__aspartate_and_glutamate_metabolism in the VLS patient group. The study suggests that perimenopausal or postmenopausal patients with VLS have a modified microbiome in the vulvar skin, gut, and vagina. This modification is linked to abnormal energy metabolism, increased oxidative stress, and abnormal amino acid metabolism.

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.

Metabolomics in Corneal Diseases: A Narrative Review from Clinical Aspects

Corneal pathologies may have subtle manifestations in the initial stages, delaying diagnosis and timely treatment. This can lead to irreversible visual loss. Metabolomics is a rapidly developing field that allows the study of metabolites in a system, providing a complementary tool in the early diagnosis and management of corneal diseases. Early identification of biomarkers is key to prevent disease progression. The advancement of nuclear magnetic resonance and mass spectrometry allows the identification of new biomarkers in the analysis of tear, cornea, and aqueous humor. Novel perspectives on disease mechanisms are identified, which provide vital information for potential targeted therapies in the future. Current treatments are analyzed at a molecular level to offer further information regarding their efficacy. In this article, we provide a comprehensive review of the metabolomic studies undertaken in the cornea and various pathologies such as dry eye disease, Sjogren’s syndrome, keratoconus, post-refractive surgery, contact lens wearers, and diabetic corneas. Lastly, we discuss the exciting future that metabolomics plays in cornea research.

Proteomics Landscape Mapping of Organ-Resolved Behçet's Disease Using In-Depth Plasma Proteomics for Identifying Hyaluronic Binding Protein 2 Expression Associated With Vascular Involvement

OBJECTIVE

This study was undertaken to elucidate the pathogenesis and heterogeneity of Behçet's disease (BD) involving different organs using in-depth proteomics to identify the biomarkers for clinical assessment and treatment of patients with BD.

METHODS

We measured the expression levels of proteins in plasma samples from 98 patients with BD and from 31 healthy controls using our in-depth proteomics platform with a data-independent acquisition mass spectrometer and antibody microarray. We performed bioinformatics analyses of the biologic processes and signaling pathways that were changed in the BD group and constructed a proteomics landscape of organ-resolved BD pathogenesis. We then validated the biomarkers of disease severity and the vascular subset in an independent cohort of 108 BD patients and 29 healthy controls using an enzyme-linked immunosorbent assay.

RESULTS

The BD group had 220 differentially expressed proteins, which discriminated between BD patients (88.6%) and healthy controls (95.5%). The bioinformatics analyses revealed different biologic processes associated with BD pathogeneses, including complement activation, wound healing, angiogenesis, and leukocyte-mediated immunity. Furthermore, the constructed proteomics landscape of organ-resolved BD identified proteomics features of BD associated with different organs and protein targets that could be used for the development of therapeutic treatment. Hyaluronic binding protein 2, tenascin, and serpin A3 were validated as potential biomarkers for the clinical assessment of vascular BD and treatment targets.

CONCLUSION

Our results provide valuable insight into the pathogenesis of organ-resolved BD in terms of proteomics characteristics and potential biomarkers for clinical assessment and potential therapies for vascular BD.

Integrative metabolomics of plasma and PBMCs identifies distinctive metabolic signatures in Behçet's disease

BACKGROUND

Behçet's disease (BD) is a systemic inflammatory disease that involves various organs. The clinical manifestation-based diagnosis of BD is a time-consuming process, which makes it difficult to distinguish from patients with similar symptoms. Moreover, an authentic biomarker has not been developed for accurate diagnosis yet. Our current study investigated the unique metabolic signatures of BD and explored biomarkers for precise diagnosis based on an untargeted metabolomic approach.

METHODS

Integrative metabolomic and lipidomic profiling was performed on plasma samples of BD patients (n = 40), healthy controls (HCs, n = 18), and disease controls (DCs, n = 17) using GC-TOF MS and LC-Orbitrap MS. Additionally, the lipid profiles of 66 peripheral blood mononuclear cells (PBMCs) were analyzed from 29 BD patients, 18 HCs, and 19 DCs.

RESULTS

Plasma metabolic dysfunction in BD was determined in carbohydrate, hydroxy fatty acid, and polyunsaturated fatty acid metabolisms. A plasma biomarker panel with 13 compounds was constructed, which simultaneously distinguished BD from HC and DC (AUCs ranged from 0.810 to 0.966). Dysregulated PBMC metabolome was signatured by a significant elevation in lysophosphatidylcholines (LPCs) and ether-linked lysophosphatidylethanolamines (EtherLPEs). Ten PBMC-derived lipid composites showed good discrimination power (AUCs ranged from 0.900 to 0.973). Correlation analysis revealed a potential association between disease activity and the metabolites of plasma and PBMC, including sphingosine-1 phosphate and EtherLPE 18:2.

CONCLUSIONS

We identified metabolic biomarkers from plasma PBMC, which selectively discriminated BD from healthy control and patients with similar symptoms (recurrent mouth ulcers with/without genital ulcers). The strong correlation was determined between the BD activity and the lipid molecules. These findings may lead to the development for diagnostic and prognostic biomarkers based on a better understanding of the BD pathomechanism.

The Application of Artificial Intelligence in the Analysis of Biomarkers for Diagnosis and Management of Uveitis and Uveal Melanoma: A Systematic Review

Purpose

This study aims to identify the available literature describing the utilization of artificial intelligence (AI) as a clinical tool in uveal diseases.

Methods

A comprehensive literature search was conducted in 5 electronic databases, finding studies relating to AI and uveal diseases.

Results

After screening 10,258 studies,18 studies met the inclusion criteria. Uveal melanoma (44%) and uveitis (56%) were the two uveal diseases examined. Ten studies (56%) used complex AI, while 13 studies (72%) used regression methods. Lactate dehydrogenase (LDH), found in 50% of studies concerning uveal melanoma, was the only biomarker that overlapped in multiple studies. However, 94% of studies highlighted that the biomarkers of interest were significant.

Conclusion

This study highlights the value of using complex and simple AI tools as a clinical tool in uveal diseases. Particularly, complex AI methods can be used to weigh the merit of significant biomarkers, such as LDH, in order to create staging tools and predict treatment outcomes.

Comparison of metabolic profiles in aqueous humor of Fuchs' syndrome and presumed viral-induced anterior uveitis patients

PURPOSE

To investigate and compare the metabolic profiles in the aqueous humor of Han Chinese patients with Fuchs' syndrome and presumed viral-induced anterior uveitis (PVIAU).

METHODS

The metabolites in the aqueous humor of 20 Fuchs' syndrome patients, 20 PVIAU patients and 20 senile cataract control patients were detected by liquid chromatography with mass spectrometry. Differential metabolites were analyzed by Student's t-test, multivariate analysis, cluster analysis and correlation analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was applied to explore the potential disrupted metabolic pathways in Fuchs' syndrome and PVIAU.

RESULTS

Comparisons of metabolic profiles identified 29 differential metabolites between Fuchs' syndrome patients and controls, 36 differential metabolites between PVIAU patients and controls, and 30 differential metabolites between Fuchs' syndrome patients and PVIAU patients. DL-serine was markedly elevated in Fuchs' syndrome, and 1-palmitoyl-sn-glycero-3-phosphocholine in PVIAU. KEGG pathway analysis suggested that the differential metabolites in Fuchs' syndrome compared with control were mostly enriched in central carbon metabolism in cancer, adenosine triphosphate-binding cassette (ABC) transporters, and mineral absorption, while those in PVIAU compared with control were mostly enriched in protein digestion and absorption, biosynthesis of unsaturated fatty acids, and ABC transporters. The metabolic pathways differentially affected in Fuchs' syndrome compared to PVIAU included central carbon metabolism in cancer, protein digestion and absorption, and ascorbate and aldarate metabolism.

CONCLUSIONS

In Fuchs' syndrome and PVIAU patients, the aqueous humor exhibited specific metabolic profiles and enriched metabolic pathways, which provides a better understanding of the pathogenesis of Fuchs' syndrome and PVIAU in Han Chinese patients. This article is protected by copyright. All rights reserved.

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.

Vogt-Koyanagi-Harada disease

PURPOSE OF REVIEW

Here, we provide an overview of Vogt-Koyanagi-Harada disease (VKH), including recent updates in our understanding of disease pathophysiology, classification and therapeutics.

RECENT FINDINGS

Advancements in bioinformatics, metabolomics and genomics investigations continue to illuminate VKH pathogenesis, and may provide insight into future therapeutic options. Multimodal imaging is indispensable in the initial evaluation of VKH, and is becoming increasingly important in understanding disease pathogenesis, as well as monitoring therapeutic response. Enhanced VKH classification criteria, released in 2021, provide standardized guidelines and terminology for clinical and research purposes.

SUMMARY

Modern research and imaging techniques continue to improve our understanding of VKH; more work is needed to further elucidate pathogenic mechanisms and establish optimal therapeutic recommendations.

Untargeted LC/MS-Based Metabolic Phenotyping of Hypopituitarism in Young Males

Objective: Hypopituitarism (Hypo-Pit) is partial or complete insufficiency of anterior pituitary hormones. Besides hormone metabolism, the global metabolomics in Hypo-Pit are largely unknown. We aimed to explore potential biomarkers to aid in diagnosis and personalized treatment.

Methods: Using both univariate and multivariate statistical methods, we identified 72 differentially abundant features through liquid chromatography coupled to high-resolution mass spectrometry, obtained in 134 males with Hypo-Pit and 90 age matched healthy controls.

Results: Hypopituitarism exhibits an increased abundance of metabolites involved in amino acid degradation and glycerophospholipid synthesis, but decreased content of metabolites in steroid hormone synthesis and fatty acid beta-oxidation. Significantly changed metabolites included creatine, creatinine, L-alanine, phosphocholines, androstenedione, hydroprenenolone, and acylcarnitines. In Hypo-Pit patients, the increased ratio of creatine/creatinine suggested reduced creatine uptake and impaired creatine utilization, whereas the decreased level of beta-hydroxybutyrate, acetylcarnitine (C2) and a significantly decreased ratio of decanoylcarnitine (C10) to free carnitine suggested an impaired beta-oxidation. Furthermore, the creatine/creatinine and decanoylcarnitine/carnitine ratio were identified as diagnostic biomarkers for Hypo-Pit with AUCs of 0.976 and 0.988, respectively. Finally, we found that the creatinine and decanoylcarnitine/carnitine ratio could distinguish cases that were sensitive vs. resistant to human chorionic gonadotropin therapy.

Conclusion: We provided a global picture of altered metabolic pathways in Hypo-Pit, and the identified biomarkers in creatine metabolism and beta-oxidation might be useful for the preliminary screening and diagnosis of Hypo-Pit.