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Historically diagnosing disorder or disease was largely based on gene and/or protein analysis,
overlooking an essential piece of the puzzle—metabolites. These small molecules provide
critical insight into a patient´s health/disease status, yet until recently, they were difficult to
detect. We now have the technology to analyze metabolites in a way that is not only
comprehensive but also non-invasive, fast, and highly sensitive.
Taking care of your metabolic system
By offering comprehensive metabolic insights through tiny, easy-to-collect samples, we support patients and doctors with the tools for earlier diagnoses, more personalized treatments, and ultimately, healthier people.
Metabolic phenotyping is at the forefront of precision medicine, aiming to identify biomarkers that enhance diagnosis, prognosis, and therapy outcomes. While significant strides have been made in the sensitive and parallel analysis of metabolites, integrating these as reliable biomarkers in clinical practice remains a significant challenge.
Traditional metabolic phenotyping techniques often provide only static snapshots due to the limitations of commonly used biological fluids like plasma and urine, which are not conducive to time-course studies. However, to comprehend the dynamic nature of metabolic responses, time-course analysis with short sampling intervals are crucial. Frequent sampling of the same individual requires a non-invasive method utilizing an alternative biological fluid: Sweat from the fingertips.
Sweat, a hypotonic and slightly acidic biofluid, offers a valuable resource for metabolic biomonitoring. Secreted by the eccrine, apocrine, and apo-eccrine glands on the skin surface, sweat's composition is highly dynamic and responsive to changes in the body's state.
The unique properties of sweat make it an excellent indicator of various health and disease factors. It can reflect dietary habits, metabolic conditions, and the use of drugs and supplements, revealing significant changes during pathological states. Remarkably, sweat and tear matrices provide more sensitive measurements compared to traditional biofluids like blood or synovial fluid. This is due to the lower abundance of interfering background matrix proteins, which allows for an unparalleled level of sensitivity.
This makes sweat analysis a powerful tool for understanding and monitoring metabolic health.
Eccrine sweat from the fingertips, primarily composed of water (~99%), contains a diverse array of substances including electrolytes, urea, lactate, amino acids, metal ions, and various endogenous metabolites like peptides, organic acids, carbohydrates, lipids, and lipid-derived metabolites, as well as xenobiotics. The eccrine glands on the fingertips are known to produce sweat at a rate of 50–500nL per cm² per minute, making it a rich source for metabolic analysis. Eccrine sweat glands are found throughout the body, with the highest density on the palms of the hands and fingertips.
With the sensitivity of modern instruments like mass spectrometry, analyzing metabolites from fingertip sweat is not only feasible but highly effective. At Metabognostics, we analyze microscopic amounts of sweat—about 100 nL—from the fingertips.
The collection process is straightforward, requiring no patient pre-treatment or specialized training. It's a safe, fast, and non-invasive method, making it an ideal choice for metabolic monitoring and research.
Metabolic phenotyping is at the cutting edge of personalized medicine, aiming to identify key biomarkers that enhance well-being, diagnose diseases, guide therapy choices, and monitor treatment progress with unprecedented precision. This approach promises to transform clinical practice by offering tailored, data-driven insights that support precision medicine.
Our innovative approach allows for the non-invasive collection of numerous data points from a single individual, enabling the interpretation of dynamic metabolic patterns crucial for advancing metabolic phenotyping. Using advanced mass spectrometry, we perform comprehensive biomolecule analysis, generating complex datasets that provide deep insights into ongoing biological processes.
By integrating various analytical workflows, we can identify molecular patterns through causal inference algorithms. These algorithms apply multiple constraints to interpret molecular data and link it to physiological processes, stress responses, or specific diseases and disorders.
Our revolutionary normalization strategy and scoring system, based on established reference values form the foundation for our application-specific software modules, delivering precision, accuracy, and actionable insights in metabolic phenotyping like never before.
Study Overview:
In two separate intervention studies, participants followed a caffeine- and theobromine-free diet for 12 to 72 hours before consuming a standardized cup of coffee or ingesting a caffeine capsule. Sweat samples were collected up to 20 times within 27 hours per participant, with the shortes sampling intervals as short as 15 minutes.
Key Findings:
Conclusion:
These proof-of-principle studies demonstrate Metabotip's ability to capture and analyze dynamic changes in metabolite levels in response to coffee consumption, showcasing its potential for detailed metabolic monitoring and assessment of physiological responses.
Since this first proof-of-principle experiment the technique has been further optimized, refined, and improved and is now available for routine application in precision medicine. In cooperation with the University Vienna, Faculty of Chemistry, Department of Analytical Chemistry, Metabognostics is continuously increasing the field of application.