Metabolomic Signature Discriminates Normal Human Cornea from Keratoconus-A Pilot GC/MS Study

Corneal Morphological and Biomechanical Changes in Thyroid-Associated Ophthalmopathy

PURPOSE

This study aimed to evaluate corneal morphological and biomechanical changes in patients with thyroid-associated ophthalmopathy (TAO) and their correlations with activity and severity.

METHODS

Patients diagnosed with TAO were recruited and divided into groups by activity and severity. All subjects underwent a complete ophthalmic examination, including magnetic resonance imaging. Corneal topography was measured using a Pentacam device, and biomechanical parameters were obtained using a CorVis ST tonometer. Correlations among the corneal parameters, clinical activity score, and NOSPECS score were analyzed. Areas under the receiver operating characteristic curves were calculated to evaluate the diagnostic accuracy of corneal changes for active and severe TAO.

RESULTS

Fifty-three eyes with TAO and 16 healthy eyes were enrolled in our study. The back elevation, CorVis biomechanical index, tomographic and biomechanical index, stiffness parameter at the first applanation, deviation from normality in back elevation, relational thickness, and overall deviation from normality were significantly increased in patients with TAO (all P <0.05), whereas the smallest corneal thickness, maximum Ambrósio relational thickness, and deformation amplitude (DA) ratio were significantly decreased (all P <0.05). The clinical activity score was strongly positively correlated with back elevation (γ = 0.515, P <0.001). The NOSPECS score was strongly positively correlated with relational thickness and tomographic and biomechanical index (γ = 0.429 and 0.515, P <0.001) and negatively correlated with maximum Ambrósio relational thickness (γ = -0.53, P <0.001). Moreover, maximum Ambrósio relational thickness and the Ambrósio relational thickness through the horizontal meridian showed desirable diagnostic capacity in distinguishing mild TAO from moderate-severe TAO (areas under the receiver operating characteristic curve, 0.799 and 0.769).

CONCLUSIONS

Corneal morphological and biomechanical changes were found in patients with TAO, which might be related to the presence of inflammation. Measurements of corneal morphological and biomechanical parameters could serve as references in evaluating TAO.

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.

Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review

Corneal and ocular surface diseases (OSDs) carry significant psychosocial and economic burden worldwide. We set out to review the literature on the application of artificial intelligence (AI) and bioinformatics for analysis of biofluid biomarkers in corneal and OSDs and evaluate their utility in clinical decision making. MEDLINE, EMBASE, Cochrane and Web of Science were systematically queried for articles using AI or bioinformatics methodology in corneal and OSDs and examining biofluids from inception to August 2021. In total, 10,264 articles were screened, and 23 articles consisting of 1058 individuals were included. Using various AI/bioinformatics tools, changes in certain tear film cytokines that are proinflammatory such as increased expression of apolipoprotein, haptoglobin, annexin 1, S100A8, S100A9, Glutathione S-transferase, and decreased expression of supportive tear film components such as lipocalin-1, prolactin inducible protein, lysozyme C, lactotransferrin, cystatin S, and mammaglobin-b, proline rich protein, were found to be correlated with pathogenesis and/or treatment outcomes of dry eye, keratoconus, meibomian gland dysfunction, and Sjögren's. Overall, most AI/bioinformatics tools were used to classify biofluids into diseases subgroups, distinguish between OSD, identify risk factors, or make predictions about treatment response, and/or prognosis. To conclude, AI models such as artificial neural networks, hierarchical clustering, random forest, etc., in conjunction with proteomic or metabolomic profiling using bioinformatics tools such as Gene Ontology or Kyoto Encylopedia of Genes and Genomes pathway analysis, were found to inform biomarker discovery, distinguish between OSDs, help define subgroups with OSDs and make predictions about treatment response in a clinical setting.

Prevalence and risk factors of keratoconus (including oxidative stress biomarkers) in a cohort study of Shiraz university of medical science employees in Iran

BACKGROUND

To determine the prevalence of keratoconus in Shiraz University of Medical Sciences Employees and the related risk factors including oxidative stress biomarkers.

METHODS

2546 subjects' mean age ± SD, 40.35 ± 6.70 (46% male) were recruited. All participants underwent objective refraction using auto-refractometer and retinoscopy, followed by subjective refraction, and bio-microscopy. Pentacam imaging was performed for the detected keratoconus patients. The prevalence of keratoconus and frequency of the visual impairment among keratoconus cases were evaluated. Potential risk factors of sex, age, family history of keratoconus, body mass index ≥ 30 kg/m², serum levels of glucose ≥ 100 mg/d, low-density-lipoprotein-cholesterol (LDL) ≥ 110 mg/dL, high-density-lipoprotein-cholesterol ≤ 40 mg/d, and triglycerides ≥ 150 mg/dL in the blood were evaluated.

RESULTS

The prevalence of keratoconus at least in one eye was 0.98% (95% CI: 0.6- 1.4%). The best corrected visual acuity in the keratoconus group was 0.06 ± 0.1 and the rest of the population was 0.01 ± 0.07 logMAR (p < 0.001). The frequency of visual impairment in the keratoconus group was zero. Odds ratios of the family history of keratoconus (21.00, 95% CI: 9.00-48.00, p < 0.001) and LDL ≥ 110 mg/dL (3.00, 95% CI: 1.20-6.40, p = 0.01) were significant.

CONCLUSIONS

Keratoconus is rare and is not considered a risk factor for visual impairment. A family history of keratoconus and elevated serum LDL levels are contributing risk factors, suggesting an inflammatory background for the disease. Serum levels of LDL ≥ 110 mg/dL in the blood increased the risk of keratoconus three folds.

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.

Role of Oxidative Stress in Ocular Diseases: A Balancing Act

Redox homeostasis is a delicate balancing act of maintaining appropriate levels of antioxidant defense mechanisms and reactive oxidizing oxygen and nitrogen species. Any disruption of this balance leads to oxidative stress, which is a key pathogenic factor in several ocular diseases. In this review, we present the current evidence for oxidative stress and mitochondrial dysfunction in conditions affecting both the anterior segment (e.g., dry eye disease, keratoconus, cataract) and posterior segment (age-related macular degeneration, proliferative vitreoretinopathy, diabetic retinopathy, glaucoma) of the human eye. We posit that further development of therapeutic interventions to promote pro-regenerative responses and maintenance of the redox balance may delay or prevent the progression of these major ocular pathologies. Continued efforts in this field will not only yield a better understanding of the molecular mechanisms underlying the pathogenesis of ocular diseases but also enable the identification of novel druggable redox targets and antioxidant therapies.

Biochemical and molecular alterations and potential clinical applications of biomarkers in keratoconus

Keratoconus (KC) is a complex multifactorial corneal ectatic disorder, with disease onset commonly in the second-third decades significantly affecting quantity, quality of vision, and quality of life. Several pathways and factors such as eye rubbing, inflammatory, oxidative, metabolic, genetic, and hormonal among others have been studied in the last two decades. However, the management of KC is still based on a few "one-size fits all" approaches and is predominantly guided by topo/tomographic parameters. Consideration of the several novel factors which have the potential to be biomarkers in addressing several unanswered questions in the disease process could help in the better predictive ability of progression or vision loss and customization of treatment options. This article delves into the understanding of these novel factors or biomarkers based on the pathogenesis of KC and features a special focus on their potential clinical applications and their future role in personalized medicine.

Pathogenesis of keratoconus: NRF2-antioxidant, extracellular matrix and cellular dysfunctions

Keratoconus (KC) is a degenerative disease associated with cell and extracellular matrix (ECM) loss that causes gradual thinning and steepening of the cornea and loss of vision. Collagen cross linking with ultraviolet light treatment can strengthen the ECM and delay weakening of the cornea, but severe cases require corneal transplantation. KC is multifactorial and multigenic, but its pathophysiology is still an enigma. Multiple approaches are being pursued to elucidate the molecular changes that underlie the corneal phenotype to identify relevant genes for tailored candidate searches and to develop potential biomarkers and targets for therapeutic interventions. Recent proteomic and transcriptomic studies suggest dysregulations in oxidative stress, NRF2-regulated antioxidant programs, WNT-signaling, TGF-β, ECM and matrix metalloproteinases. This review aims to provide a broad update on the transcriptomic and proteomic studies of KC with a focus on findings that relate to oxidative stress, and dysregulations in cellular and extracellular matrix functions.

Nutritional and Metabolic Imbalance in Keratoconus

Keratoconus (KC) is a progressive corneal degeneration characterized by structural changes consisting of progressive thinning and steepening of the cornea. These alterations result in biomechanical weakening and, clinically, in vision loss. While the etiology of KC has been the object of study for over a century, no single agent has been found. Recent reviews suggest that KC is a multifactorial disease that is associated with a wide variety of genetic and environmental factors. While KC is typically considered a disease of the cornea, associations with systemic conditions have been well described over the years. In particular, nutritional and metabolic imbalance, such as the redox status, hormones, metabolites, and micronutrients (vitamins and metal ions), can deeply influence KC initiation and progression. In this paper, we comprehensively review the different nutritional (vitamins and minerals) and metabolic (hormones and metabolites) factors that are altered in KC, discussing their possible implication in the pathophysiology of the disease.

Plasma Metabolites-Based Prediction in Cardiac Surgery-Associated Acute Kidney Injury

Background

Cardiac surgery–associated acute kidney injury (CSA‐AKI) is a common postoperative complication following cardiac surgery. Currently, there are no reliable methods for the early prediction of CSA‐AKI in hospitalized patients. This study developed and evaluated the diagnostic use of metabolomics‐based biomarkers in patients with CSA‐AKI.

Methods and Results

A total of 214 individuals (122 patients with acute kidney injury [AKI], 92 patients without AKI as controls) were enrolled in this study. Plasma samples were analyzed by liquid chromatography tandem mass spectrometry using untargeted and targeted metabolomic approaches. Time‐dependent effects of selected metabolites were investigated in an AKI swine model. Multiple machine learning algorithms were used to identify plasma metabolites positively associated with CSA‐AKI. Metabolomic analyses from plasma samples taken within 24 hours following cardiac surgery were useful for distinguishing patients with AKI from controls without AKI. Gluconic acid, fumaric acid, and pseudouridine were significantly upregulated in patients with AKI. A random forest model constructed with selected clinical parameters and metabolites exhibited excellent discriminative ability (area under curve, 0.939; 95% CI, 0.879–0.998). In the AKI swine model, plasma levels of the 3 discriminating metabolites increased in a time‐dependent manner (R², 0.480–0.945). Use of this AKI predictive model was then confirmed in the validation cohort (area under curve, 0.972; 95% CI, 0.947–0.996). The predictive model remained robust when tested in a subset of patients with early‐stage AKI in the validation cohort (area under curve, 0.943; 95% CI, 0.883–1.000).

Conclusions

High‐resolution metabolomics is sufficiently powerful for developing novel biomarkers. Plasma levels of 3 metabolites were useful for the early identification of CSA‐AKI.

Identification of potential serum metabolic biomarkers for patient with keratoconus using untargeted metabolomics approach

This study aimed to investigate the metabolite differences between patients with keratoconus and control subjects and identify potential serum biomarkers for keratoconus using a non-targeted metabolomics approach. Venous blood samples were obtained from patients with keratoconus (n = 20) as well as from age-, gender- and race-matched control subjects (n = 20). Metabolites extracted from serum were separated and analyzed by liquid chromatography/quadrupole time-of-flight mass spectrometer. Processing of raw data and analysis of the data files was performed using Agilent Mass Hunter Qualitative software. The identified metabolites were subjected to a principal component and hierarchical cluster analysis. Appropriate statistical tests were used to analyze the metabolomic profiling data. Together, the analysis revealed that the dehydroepiandrosterone sulfate from the steroidal hormone synthesis pathway was significantly upregulated in patients with keratoconus (p < 0.05). Also, a combination of eicosanoids from the arachidonic acid pathway, mainly prostaglandin F2α, prostaglandin A2, 16,16-dimethyl prostaglandin E2, and 5-hydroxyeicosatetraenoic acid were collectively up-regulated as a group in keratoconus patients (p < 0.05). On the other hand, glycerophospholipid PS(17:2(9Z,12Z)/20:4(5Z,8Z,11Z,14Z)) was found to be significantly upregulated in the metabolomics profiles of control subjects (p < 0.05). The differently regulated metabolites provide insights into the pathophysiology of keratoconus and could potentially be used as biomarkers for keratoconus to aid in screening for individuals at risk hence, enabling early diagnosis and timely monitoring of disease.

Biochemical Markers and Alterations in Keratoconus

Keratoconus (KC) is a corneal ectatic condition characterized by focal structural changes, resulting in progressive thinning, biomechanical weakening, and steeping of the cornea that can lead to worsening visual acuity due to irregular astigmatism and corneal scarring in more advanced cases. It is a relatively common ectatic disease of the cornea predominantly affecting the younger population. Despite its worldwide prevalence, its incidence is rather varied with a higher incidence among the Middle Eastern and South Asian population. Dysregulated corneal extracellular matrix remodeling underlies KC pathogenesis. However, a lack of absolute clarity regarding the factors that initiate and drive progression poses a significant challenge in its prevention and management. KC is a complex multifactorial disease as it is associated with a wide variety of etiological factors such as environmental stimuli/insults, oxidative stress, genetic predisposition, comorbidities, and eye rubbing. A series of studies using corneal tissues (epithelium, stroma), cultured corneal fibroblasts/keratocytes, tear fluid, aqueous humor, and blood from KC subjects has reported significant alterations in various biochemical factors such as extracellular matrix components, cellular homeostasis regulators, inflammatory factors, hormones, metabolic products, and chemical elements. It has become apparent that alterations in the biochemical mediators (related to various etiologies) could contribute to KC pathogenesis by altering the dynamics of extracellular matrix remodeling events such as collagen deposition, degradation, and cross-linking in the cornea. Determining key disease contributing biochemical mediators would aid in disease monitoring, prediction or abatement of disease progression, and development of targeted therapeutics to improve disease prognosis.