Metabolomics research in Graz

Metabolomics, one of CBmed’s Core Technologies, is an emerging but powerful tool for precision medicine. Recently, CBmed filed a promising patent for non-invasive diagnosis of pulmonary hypertension (PH) based on this technology.

 Metabolomics is defined as the study of chemical processes involving metabolites in a biological specimen. It is an emerging technology that can provide a better understanding of the state of cellular and biological processes at different stages. The term refers to the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues or organisms. Collectively, these small molecules and their interactions within a biological system are known as the metabolome. The metabolome is thought to be the closest representation of phenotype and shows tremendous potential in applications ranging from understanding cellular processes in both normal and diseased tissues, environmental research, agriculture to biomarker discovery and personalized medicine.

Metabolomics is an important area of study because metabolites directly reflect the underlying biochemical activity and state of cells and tissue – something that other -omics technologies such as genomics, transcriptomics, or proteomics are unable to capture. Historically, few metabolites could be efficiently identified standard clinical chemistry techniques (e.g., cholesterol) but advanced metabolomics technologies such as Liquid Chromatography-Mass Spectrometry (LC-MS) can identify hundreds to thousands of metabolites. While the analysis and interpretation of a complex metabolomic profile or fingerprint is still challenging, these advanced technologies enable precision medicine at many levels, including the characterization of metabolic derangements that underlie disease, the discovery of new therapeutic targets and biomarkers to diagnose and predict disease, or monitor the activity of therapeutics.

A data analysis workflow in metabolomics usually consists of feature extraction, compound identification, quality control statistical analysis, and subsequent statistical interpretation together with clinical data. These tasks are performed at CBmed in collaboration with Joanneum Research. In many cases, such as for advanced biomarker discovery and validation, integration with other datasets or the creation of robust predictive models, a more advanced analysis is required. These tasks are performed by the Data Science team, whose expertise is focused on statistics, data analysis, and machine learning, with an emphasis on deep learning for image data. In biomarker discovery, there is often al limited amount of data and no previous hypothesis, so data scientists work together with the laboratories and medical experts to help interpret, make sense, and validate their findings.