Metabolomics-Driven Biomarker Discovery and Translation

The greatest advantage of metabolomics over non-omics methods is the ability to identify as many metabolites that change as possible, to explore the metabolic changes in the body systematically and holistically, to explain the mechanisms of the changes, or to determine abnormal metabolic changes in advance.

How can reliable biomarkers that are closely related to disease onset or progression be accurately distinguished from the large number of changing metabolites, and from those differential metabolites that, although statistically significantly different, are not significantly related to disease? The following points can be drawn upon:

• Combining dynamic metabolic changes in the organism to find biomarkers

The metabolism of the organism is a dynamic process that can be altered by a variety of factors, but at the same time there is a strong metabolic homeostatic process to maintain its normal metabolic homeostasis. Metabolomics can detect metabolic changes at a particular state or time point of the organism in a timely manner. However, most current metabolomics studies only focus on metabolic changes at a point in time and do not dynamically analyze the metabolic changes of the organism. Screening biomarkers in isolation based on changes at a state or time point does not reflect the dynamic metabolic changes of the organism. The screened biomarkers may be difficult to reproduce in practical applications. Dynamic analysis of metabolites can provide a better understanding of the process and trend of changes in organism exposure or disease, exclude the influence of other extraneous factors, and screen for reliable biomarkers.

• Screening biomarkers based on the frequency of biomarker reports

The biomarkers found by different metabolomics studies vary widely. There are two main possible reasons for this. First, different analytical platforms have different coverage, sensitivity and selectivity for different chemical classes of substances. Even when using the same techniques and instruments, researchers can optimize the setup in different ways for sample and data collection under different standardized protocols. Second, some variation may arise from population diversity (i.e., effects of gene regulation, post-transcriptional regulation, environmental differences). For these reasons, few metabolites that have been identified in association with many diseases have been confirmed and translated into clinical practice.

However, if different researchers, under different conditions, with different instruments, races, and samples, obtain the same biomarker or a biomarker with a higher reported frequency, that may have a higher resistance to interference and practical application. Therefore, screening biomarkers with high frequency of occurrence based on the frequency of being reported has the potential to screen biomarkers with practical application potential.

• Screening biomarkers in combination with biological significance

Currently, most studies screen biomarkers based mainly on the diagnostic value and change multiplicity of the marker. However, the relevance of biomarkers to disease, especially the biological significance of biomarkers or changes in metabolic pathways, is overlooked while considering diagnostic value or change multiplicity. Many metabolic changes in the body revolve mainly around the tricarboxylic acid cycle or are interconverted through the tricarboxylic acid cycle. Many biomarkers are located in the tricarboxylic acid cycle, or in several other major metabolic pathways, which leads to many different diseases with the same or similar biomarkers or disordered metabolic pathways. This creates great confusion for follow-up studies and makes it difficult to conduct in-depth research.

Metabolomic biomarker discovery study (Njoku et al, 2020)

Multi-omics analysis to screen for reliable biomarkers

The metabolism of an organism is a whole, and the individual metabolic pathways are interconnected to form a complex metabolic network. Only by correlating all the genes, proteins, and metabolites can a complete metabolic pathway be formed.

Creative Proteomics has developed a multi-omics analysis platform to analyze metabolomics in combination with other omics, which has the potential to discover more reliable biomarkers and explain the specific mechanisms of their changes.

Biomarker metabolomics services enable:

• Diagnostic biomarker assays
• Monitoring biomarker assays
• Pharmacodynamic/response biomarker assays
• Predictive biomarker assays
• Safety biomarkers
• Susceptibility/risk biomarkers

Reference

1. Njoku, K., Sutton, C. J., et al. (2020). Metabolomic biomarkers for detection, prognosis and identifying recurrence in endometrial cancer. Metabolites, 10(8), 314.