[MUSIC] From the ancient time of the Greeks, human blood was thought to contain markers of health and disease. During the last centuries, the concept of blood containing biomarkers has exploded with the development and application of various biomarkers in clinical biochemistry and molecular diagnostics. With development of technology such as DNA sequencing, liquid chromatography and mass-spectrometry, biomarkers research has been expanding rapidly. The clinical applicability of such technologies remains, however, limited. In this talk, I will introduce you to the world of omics, focusing on the application of mass-spectrometry-based proteomic analysis. Let's begin with an introduction to the world of omics. Omics refers to various large-scale measures of genes, proteins, peptides, metabolites, lipids, and so forth. Technologies such as mass-spectrometry or next-generation sequencing are used to generate omics data from biological material. Including blood, plasma, saliva, feces, cerebrospinal fluid, and tissue biopsies. For each class of molecules, the suffix -omics is added. As an example, studying genes by a next-generation sequencing technologies are term genomics. Whereas studying proteins by mass-spectrometry is termed proteomics. In some of the prior modules, we learned about how genomic analysis have identified common as well as rare genetic risk variants of NAFL. These studies support that several biological pathways are essential for maintaining a normal and healthy liver. And if disrupted by a mutation, the risk of liver disease may increase more than 100 fold. A major strength of genomic analysis is its technological maturity. As an example, the Human Genome Project was initiated in 1990 and finalized in 2003, whereas the human proteome is still under construction. Why is it we are still challenged to identify and apply biomarkers for NAFL? A simple answer does not exist, but let's explore some likely explanation. Two main challenges may be mentioned. The first is the complexity of the disease. Is it one disease or multiple subtypes? And the other challenge is the maturity of the technologies used are crucial denominators of success. Proteomic is the study of proteins, and one may use different technologies to profile the composition of circulating proteins. One example of such technology is mass-spectrometry. One strength of mass-spectrometry-based proteomic is that this method has a high specificity, and hence the risk of identifying a false-positive biomarker is reduced. Furthermore, rather than using 500 different assays to measure 500 different proteins, mass-spectrometry can measure all 500 proteins in one step. And finally, as protein in contrast to genes execute biological functions, proteomic may be advantageous, as one capture the function rather than a surrogate measure. With the development of large-scale computer power, it is now also possible to integrate omics data. Many tool exist for this, and at the Novo Nordisk Foundation Center for Protein Research, Professor Matthias Mann and colleagues have generated a toolbox, that not only integrate, for example, genomic data with proteomic data, but also allow the user to integrate clinical variables. Simplifying bioinformatic is not only an ambition, it is a necessity to improve science. In all sciences, reproduction of data is essential. Several biomarker studies using omics technologies have not been successful in the term that other scientific groups have been able to re-identify the proposed biomarkers. Or they never made it into clinical use. A potential explanation may relate to the bioinformatic filtering of data and the biological understanding of, for example, proteins derived from the skin of blood cells. One study showed that up to 50% of prior biomarker studies using proteomic analysis identify a quality marker as a biomarker. For example, if a protein derived from red blood cells contaminated the sample due to insufficient sample handling. The search for biomarkers in NAFL is similar to the search of the Holy Grail, almost impossible. Several studies have claimed to have identified markers of NAFL, but none have shown clinical applicability of such. The majority of these omics-based studies have used animal models to identify potential biomarkers of NAFL. With the development of more sensitive and large-scale human study, it has now become more viable to identify and study biomarkers of NAFLD in humans. At the Novo Nordisk Foundation Center for Protein Research, we have used mass-spectrometry-based proteomic to capture known as well as unknown biomarkers of liver disease. In this picture, we see patients with and without NAFL that we included for proteomic profiling. We also stratified the analysis based on patient presence of diabetes. Finally, we included proteomic analysis on blood from mice with mild and severe NAFLD. Mass-spectrometry-based proteomic profiling allowed us to identify novel biomarkers. For example, PIGR for potential diagnostics of NAFL. Several other omics technologies are being used to uncover not only the pathophysiology of NAFL, but also to discover novel biomarkers to be used for early detection and risk prediction of progression of this disease. We're awaiting the maturation of these omics technologies that will enable not only further biomarker discoveries, but importantly, also the clinical applicability of such. To wrap up this module, omic technologies are more and more frequently used in clinical sciences. But one need to be cautious about their clinical applicability. Mass-spectrometry-based proteomic may be a powerful tool to study diseases like NAFL, as highlighted in this showcase. [MUSIC]
