Metabolic phenotyping of tear fluid as a prognostic tool for personalised medicine exemplified by T2DM patients

Abstract

Background/aims Concerning healthcare approaches, a paradigm change from reactive medicine to predictive approaches, targeted prevention, and personalisation of medical services is highly desirable. This raises demand for biomarker signatures that support the prediction and diagnosis of diseases, as well as monitoring strategies regarding therapeutic efficacy and supporting individualised treatments. New methodological developments should preferably rely on non-invasively sampled biofluids like sweat and tears in order to provide optimal compliance, reduce costs, and ensure availability of the biomaterial. Here, we have thus investigated the metabolic composition of human tears in comparison to finger sweat in order to find biofluid-specific marker molecules derived from distinct secretory glands. The comprehensive investigation of numerous biofluids may lead to the identification of novel biomarker signatures. Moreover, tear fluid analysis may not only provide insight into eye pathologies but may also be relevant for the prediction and monitoring of disease progression and/ or treatment of systemic disorders such as type 2 diabetes mellitus. Methods Sweat and tear fluid were sampled from 20 healthy volunteers using filter paper and commercially available Schirmer strips, respectively. Finger sweat analysis has already been successfully established in our laboratory. In this study, we set up and evaluated methods for tear fluid extraction and analysis using high-resolution mass spectrometry hyphenated with liquid chromatography, using optimised gradients each for metabolites and eicosanoids. Sweat and tears were systematically compared using statistical analysis. As second approach, we performed a clinical pilot study with 8 diabetic patients and compared them to 19 healthy subjects. Results Tear fluid was found to be a rich source for metabolic phenotyping. Remarkably, several molecules previously identified by us in sweat were found significantly enriched in tear fluid, including creatine or taurine. Furthermore, other metabolites such as kahweol and various eicosanoids were exclusively detectable in tears, demonstrating the orthogonal power for biofluid analysis in order to gain information on individual health states. The clinical pilot study revealed that many endogenous metabolites that have previously been linked to type 2 diabetes such as carnitine, tyrosine, uric acid, and valine were indeed found significantly up-regulated in tears of diabetic patients. Nicotinic acid and taurine were elevated in the diabetic cohort as well and may represent new biomarkers for diabetes specifically identified in tear fluid. Additionally, systemic medications, like metformin, bisoprolol, and gabapentin, were readily detectable in tears of patients. Conclusions The high number of identified marker molecules found in tear fluid apparently supports disease development prediction, developing preventive approaches as well as tailoring individual patients’ treatments and monitoring treatment efficacy. Tear fluid analysis may also support pharmacokinetic studies and patient compliance control.

Managing chronic disease with individualized metabolomics & artificial intelligence

“…(3) Currently, Metabo-tip stands out as the only technique capable of shortinterval metabolic biomonitoring/phenotyping in humans. (3) Such methods at hand mean that the biomedical challenge associated with chronic diseases boils down to mathematical problems. Methods for metabolic biomonitoring deliver a large number of data points, which depend on physiological activities affected by multiple factors related to your state of health, lifestyle parameters (eating, smoking, physical exercise) or pharmacological therapy.…”

Towards Multiplexed and Multimodal Biosensor Platforms in Real-Time Monitoring of Metabolic Disorders

“…Glucose and lactate are two well-established tear analytes [ 75 , 76 , 77 , 78 , 79 ]. In addition, tear fluid is a rich source for metabolic phenotyping [ 80 ]. Tears of diabetic patients show elevated levels of several metabolites, such as carnitine, tyrosine, uric acid, and valine [ 80 ].…”

“…In addition, tear fluid is a rich source for metabolic phenotyping [ 80 ]. Tears of diabetic patients show elevated levels of several metabolites, such as carnitine, tyrosine, uric acid, and valine [ 80 ]. Increased levels of inflammatory cytokines and chemokines in tears, including IL-6, IL-1, IL-8, IL-10, and TMF-α, have been investigated in patients with dry eye disease.…”

“…Increased levels of inflammatory cytokines and chemokines in tears, including IL-6, IL-1, IL-8, IL-10, and TMF-α, have been investigated in patients with dry eye disease. Moreover, drugs such as metformin, bisoprolol, and gabapentin are also detectable in tears [ 80 ], thus highlighting the potential of tear fluids in monitoring therapeutic outcomes. However, there is a gap in knowledge regarding the levels of MS biomarkers in tears, and the relationship between tear and blood biomarker levels remains unclear.…”

Mutual effect of homocysteine and uric acid on arterial stiffness and cardiovascular risk in the context of predictive, preventive, and personalized medicine

“…Development of innovative screening method contributes to promote population health by health risk assessment, individualized, and cost-effective profiling. It has been highlighted that homocysteine (Hcy)/uric acid (UA) metabolism and cardiovascular diseases are several areas considered to be potentially strongly benefiting from the PPPM/3PM paradigm [ 11 , 12 ]. Koklesova et al reported that the metabolic pathway of Hcy is closely related to coronary artery disease and atherosclerosis, which is of great value for disease diagnosis and prediction, and helps to optimize the individualized comprehensive treatment of patients [ 11 ].…”