Wound-Healing Markers Revealed by Proximity Extension Assay in Tears of Patients following Glaucoma Surgery

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.

Tear Fluid Inflammatory Proteome Analysis Highlights Similarities Between Keratoconus and Allergic Conjunctivitis

Purpose

Keratoconus is characterized by the progressive thinning of the cornea, which leads to a cone-like appearance of the eye over time. Although conventionally defined as a noninflammatory condition, a number of recent studies have associated keratoconus (KC) with allergic conjunctivitis (AC) based on clinical parameters. This study aimed to consolidate this association by performing a proteomic analysis of tear fluid from patients with keratoconus and/or allergic conjunctivitis.

Methods

Of 51 patients, 17 were diagnosed with KC, 17 were diagnosed with AC, and 17 were diagnosed with both KC and AC (combined). Nine of 34 patients with KC had a progressive form of the disease. Tear fluid samples (n = 51, one eye per patient) were collected by the Schirmer's strips. Tear proteins were extracted from the Schirmer's strips. Proteomic profiling of 384 inflammatory proteins was assessed by a multiplex proximity extension assay (Olink Explore 384 Inflammation Panel I).

Results

A total of 384 inflammatory proteins were measured. Two hundred seventy-two of the 384 proteins passed stringent data cleaning and were compared among the patient groups. Compared to the 2 other groups, LGALS9 was upregulated uniquely in KC, whereas FGF19, PDGFB, HPCAL1, OSM, and FCAR were downregulated in KC. Similarly, TNFRSF4 and CCL13 were specifically upregulated in AC, whereas ectodysplasin A receptor (EDAR) was uniquely downregulated in AC.

Conclusions

High-throughput proteomic profiling of tear fluid confirms the association between KC and AC on a molecular level and raise the importance of redefining KC as an inflammatory condition.

The role of artificial intelligence in analysis of biofluid markers for diagnosis and management of glaucoma: A systematic review

PURPOSE

This review focuses on utility of artificial intelligence (AI) in analysis of biofluid markers in glaucoma. We detail the accuracy and validity of AI in the exploration of biomarkers to provide insight into glaucoma pathogenesis.

METHODS

A comprehensive search was conducted across five electronic databases including Embase, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science. Studies pertaining to biofluid marker analysis using AI or bioinformatics in glaucoma were included. Identified studies were critically appraised and assessed for risk of bias using the Joanna Briggs Institute Critical Appraisal tools.

RESULTS

A total of 10,258 studies were screened and 39 studies met the inclusion criteria, including 23 cross-sectional studies (59%), nine prospective cohort studies (23%), six retrospective cohort studies (15%), and one case-control study (3%). Primary open angle glaucoma (POAG) was the most commonly studied subtype (55% of included studies). Twenty-four studies examined disease characteristics, 10 explored treatment decisions, and 5 provided diagnostic clarification. While studies examined at entire metabolomic or proteomic profiles to determine changes in POAG, there was heterogeneity in the data with over 175 unique, differentially expressed biomarkers reported. Discriminant analysis and artificial neural network predictive models displayed strong differentiating ability between glaucoma patients and controls, although these tools were untested in a clinical context.

CONCLUSION

The use of AI models could inform glaucoma diagnosis with high sensitivity and specificity. While insight into differentially expressed biomarkers is valuable in pathogenic exploration, no clear pathogenic mechanism in glaucoma has emerged.

Evaluation of pre-processing methods for tear fluid proteomics using proximity extension assays

Tear fluid forms a potential source for biomarker identification, and can be minimal invasively collected via Schirmer strips. The lack of knowledge on the processing of Schirmer strips however complicates the analysis and between-study comparisons. We studied two different pre-processing methods, specifically the use of punches of the strip versus elution of the strip in a buffer. Tear fluid filled Schirmer strips were collected from 5 healthy participants, and divided into two halves over the length of the strip. In either part, punches or eluates were obtained from 4 different locations, from the first part touching the eye (head) to the end, to assess the protein distribution along the strips. The levels of 92 inflammatory proteins were measured in the punches/eluates using proximity extension assays. The punch method yielded higher protein detectability compared to the elution method (76% vs 66%; p ≤ 0.001). Protein expression level was found to be slightly higher in the head of the strip, however, 3 out of 5 punches from the head failed quality control. Protein expression levels over the remaining parts of the strips were similar. Our study showed beneficial use of punches of any part of the strip except the head in future biomarker research.

Clinical Tear Fluid Proteomics—A Novel Tool in Glaucoma Research

Tear fluid forms the outermost layer of the ocular surface and its characteristics and composition have been connected to various ocular surface diseases. As tear proteomics enables the non-invasive investigation of protein levels in the tear fluid, it has become an increasingly popular approach in ocular surface and systemic disease studies. Glaucoma, which is a set of multifactorial diseases affecting mainly the optic nerve and retinal ganglion cells, has also been studied using tear proteomics. In this condition, the complete set of pathophysiological changes occurring in the eye is not yet fully understood, and biomarkers for early diagnosis and accurate treatment selection are needed. More in-depth analyses of glaucoma tear proteomics have started to emerge only more recently with the implementation of LC-MS/MS and other modern technologies. The aim of this review was to examine the published data of the tear protein changes occurring during glaucoma, its topical treatment, and surgical interventions.

Fast and Sensitive Quantification of AccQ-Tag Derivatized Amino Acids and Biogenic Amines by UHPLC-UV Analysis from Complex Biological Samples

Metabolomic analysis of different body fluids bears high importance in medical sciences. Our aim was to develop and validate a fast UHPLC-UV method for the analysis of 33 amino acids and biogenic amines from complex biological samples. AccQ-Tag derivatization was conducted on target molecules and the derivatized targets were analyzed by UHPLC-UV. The detection of the analytes was carried out with UV analysis and by Selected Reaction Monitoring (SRM)-based targeted mass spectrometry. The method was validated according to the FDA guidelines. Serum and non-stimulated tear samples were collected from five healthy individuals and the samples were analyzed by the method. The method was successfully validated with appropriate accuracy and precision for all 33 biomolecules. A total of 29 analytes were detected in serum samples and 26 of them were quantified. In the tears, 30 amino acids and biogenic amines were identified and 20 of them were quantified. The developed and validated UHPLC-UV method enables the fast and precise analysis of amino acids and biogenic amines from complex biological samples.

Identification of tear-based protein and non-protein biomarkers: Its application in diagnosis of human diseases using biosensors

Discovery of robust, selective and specific biomarkers are important for early diagnosis and monitor progression of human diseases. Eye being a common target for several human diseases, vision impediment and complications are often associated with systemic and ocular diseases. Tears are bodily fluids that are closest to eye and are rich in protein content and other metabolites. As a biomarker repository, it advantages over other bodily fluids due to the ability to collect it non-invasively. In this review, we highlight some recent advancements in identification of tear-based protein biomarkers like lacryglobin and cystatin SA for cancer; interleukin-6 and immunoglobulin-A antibody for COVID-19; tau, amyloid-β-42 and lysozyme-C for Alzheimer's disease; peroxiredoxin-6 and α-synuclein for Parkinson's disease; kallikrein, angiotensin converting enzyme and lipocalin-1 for glaucoma; lactotransferrin and lipophilin-A for diabetic retinopathy and zinc-alpha-2 glycoprotein-1, prolactin and calcium binding protein-A4 for eye thyroid disease. We also discussed identification of tear based non-protein biomarkers like lysophospholipids and acetylcarnitine for glaucoma, 8-hydroxy-2'-deoxyquanosine and malondialdehyde for thyroid eye disease. We elucidate technological advancement in developing tear-based biosensors for diagnosis and monitoring diseases such as diabetes, diabetic retinopathy and Alzheimer's disease. Altogether, the study of tears as potential biomarkers for early diagnosis of human diseases is promising.

Psoriasis to Psoriatic Arthritis: The Application of Proteomics Technologies

Psoriatic disease (PsD) is a spectrum of diseases that affect both skin [cutaneous psoriasis (PsC)] and musculoskeletal features [psoriatic arthritis (PsA)]. A considerable number of patients with PsC have asymptomatic synovio-entheseal inflammations, and approximately one-third of those eventually progress to PsA with an enigmatic mechanism. Published studies have shown that early interventions to the very early-stage PsA would effectively prevent substantial bone destructions or deformities, suggesting an unmet goal for exploring early PsA biomarkers. The emergence of proteomics technologies brings a complete view of all involved proteins in PsA transitions, offers a unique chance to map all potential peptides, and allows a direct head-to-head comparison of interaction pathways in PsC and PsA. This review summarized the latest development of proteomics technologies, highlighted its application in PsA biomarker discovery, and discussed the possible clinical detectable PsA risk factors in patients with PsC.

Reduced Level of Tear Antimicrobial and Immunomodulatory Proteins as a Possible Reason for Higher Ocular Infections in Diabetic Patients

(1) Background: Diabetes mellitus is one of the most common metabolic disorders and a risk factor for bacterial ocular infections. Our aim was to examine the antibacterial activity of tears from patients with diabetes mellitus with and without diabetic retinopathy and to link this activity to the level of tear proteins. (2) Methods: Non-stimulated basal tears were collected from 39 eyes of 35 subjects. The antibacterial activity of tear pools was tested against pathogenic Staphylococcus aureus ATCC 29213, Escherichia coli ATCC 26922 and Pseudomonas aeruginosa ATCC 27853 strains. The levels of 10 antimicrobial and immunomodulatory proteins were analyzed in the individual tear samples of the studied groups by SRM-based targeted mass spectrometry analysis. (3) Results: Disease stage-specific antimicrobial effect was observed in case of Staphylococcus aureus ATCC 29213 strain, and a non-disease specific inhibitory effect was observed in case of Pseudomonas aeruginosa ATCC 27853 strain. Changes in the levels of the studied antimicrobial and immunomodulatory proteins in the tears of the studied groups were also observed. (4) Conclusions: The higher ocular infection rate observed in diabetic patients may be the consequence of the decreased antimicrobial activity of tears possibly caused by the changes in the levels of antimicrobial and immunomodulatory proteins.

Examination of Oral Squamous Cell Carcinoma and Precancerous Lesions Using Proximity Extension Assay and Salivary RNA Quantification

Saliva is an easy-to access body fluid with high diagnostic potential. The utilization of saliva for oral cancer diagnosis can be an attractive possibility. Besides the oral cancer, it is important to better understand the precancerous lesions such as oral lichen planus (OLP) and leukoplakia (OLK). In order to examine the changes of salivary proteins in controls, patients with oral cancer, and patients with precancerous conditions, proximity extension assay was utilized. Some proteins and functions were characteristic to the examined groups and can serve as a starting point for further biomarker studies. The different nature of OLK and OLP was demonstrated, showing the malignant transformation and the inflammation as the prominent biological processes in the OLK and OLP, respectively. The salivary level of IL6 was verified using quantitative ELISA and the mRNA level was also studied. Elevated IL6 levels could be detected in precancerous groups compared to controls.

Effectiveness and Safety of Trabeculectomy along with Amniotic Membrane Transplantation on Glaucoma: A Systematic Review

Purpose

To determine the effectiveness and safety of trabeculectomy along with amniotic membrane transplantation (AMT) for glaucoma.

Methods

This systematic review was performed using RevMan 5.3. We searched PubMed, EMBASE, and the Cochrane Library and included studies published until September 2019. The treatment group included patients with AMT and trabeculectomy (group A), and the control group had only trabeculectomy (group B). We only included randomized controlled trials. The outcomes were intraocular pressure (IOP), complete success rate, number of antiglaucoma medications, and complications.

Results

Five studies, including 174 eyes (87 eyes in the AMT group and 87 eyes in the control group), were eligible in this review. The parameters had no significant difference in heterogeneity between the AMT and control groups preoperatively. In the AMT group, the mean IOP was significantly lower at 3 and 12 months after operation (P < 0.0001 and P = 0.02, respectively), while the number of complete successes in the AMT group was significantly higher at 6 and 12 months (P = 0.02 and P = 0.003, respectively) compared with the control group. Complications, including a flat anterior chamber and hyphema, appeared to be decreased in the AMT group compared to the control group (P = 0.02 and P = 0.02, respectively). No differences were observed in the number of antiglaucoma medications, hypotony, encapsulated bleb, or choroidal detachment.

Conclusion

Compared with only trabeculectomy, it is more efficient and safer to add AMT to trabeculectomy during glaucoma filtering surgery.

Integrated Skin Transcriptomics and Serum Multiplex Assays Reveal Novel Mechanisms of Wound Healing in Diabetic Foot Ulcers

Nonhealing diabetic foot ulcers (DFUs) are characterized by low-grade chronic inflammation, both locally and systemically. We prospectively followed a group of patients who either healed or developed nonhealing chronic DFUs. Serum and forearm skin analysis, both at the protein expression and the transcriptomic level, indicated that increased expression of factors such as interferon-γ (IFN-γ), vascular endothelial growth factor, and soluble vascular cell adhesion molecule-1 were associated with DFU healing. Furthermore, foot skin single-cell RNA sequencing analysis showed multiple fibroblast cell clusters and increased inflammation in the dorsal skin of patients with diabetes mellitus (DM) and DFU specimens compared with control subjects. In addition, in myeloid cell DM and DFU upstream regulator analysis, we observed inhibition of interleukin-13 and IFN-γ and dysregulation of biological processes that included cell movement of monocytes, migration of dendritic cells, and chemotaxis of antigen-presenting cells pointing to an impaired migratory profile of immune cells in DM skin. The SLCO2A1 and CYP1A1 genes, which were upregulated at the forearm of nonhealers, were mainly expressed by the vascular endothelial cell cluster almost exclusively in DFU, indicating a potential important role in wound healing. These results from integrated protein and transcriptome analyses identified individual genes and pathways that can potentially be targeted for enhancing DFU healing.

MULTIOMIC PATTERNS IN BODY FLUIDS: TECHNOLOGICAL CHALLENGE WITH A GREAT POTENTIAL TO IMPLEMENT THE ADVANCED PARADIGM OF 3P MEDICINE

Liquid biopsy (LB) is defined as a sample of any of body fluids (blood, saliva, tear fluid, urine, sweat, amniotic, cerebrospinal and pleural fluids, cervicovaginal secretion, and wound efflux, amongst others), which can be ex vivo analysed to detect and quantity the target(s) of interest. LB represents diagnostic approach relevant for organ-specific changes and systemic health conditions including both manifested diseases and their prestages such as suboptimal health. Further, experts emphasise that DNA-based analysis alone does not provide sufficient information for optimal diagnostics and effective treatments. Consequently, of great scientific and clinical utility are molecular patterns detected by hybrid technologies such as metabolomic tools and molecular imaging. Future proposed strategies utilise multiomic pillars (generally genome, tanscriptome, proteome, metabolome, epigenome, radiome, and microbiome), system-biological approach, and multivariable algorithms for diagnostic, prognostic, and therapeutic purposes. Current article analyses pros and cons of the mass spectrometry-based technologies, provides eminent examples of a success story "from discovery to clinical application," and demonstrates a "road-map" for the technology-driven paradigm change from reactive to predictive, preventive and personalised medical services as the medicine of the future benefiting the patient and healthcare at large. © 2019 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.