Small molecule metabolites: discovery of biomarkers and therapeutic targets

Abstract

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Fig. 1

Analytical workflow of small molecule metabolites-based metabolomics. The first stage involves experimental design, followed by election of biological subjects, sample collection, preparation, and metabolite extraction. Next is acquisition and processing of data, then data analysis, and finally, making sense of the data through biomarker discovery, and functional interpretation. The images were obtained using the example data provided by the MetaboAnalyst 5.0 and figures created by BioRender

Fig. 2

Schematic representation of the most commonly used omic platforms for multi-omics studies. Metabolites are the downstream products of the genome, transcriptome, proteome, and enzymatic reactions, which are also affected by environmental exposures. The metabolome provides a functional readout of these upstream changes. Multi-omics (including genome, transcriptome, proteome, metabolome, and microbiome data) are collected from patients and integrated to identify personalized functional signatures using complex and comprehensive network analysis. The figures created by BioRender

Fig. 3

Overview of advanced technology platform for metabolite quantification in biomedicine. Step 1: Sample preparation through deproteinization and/or centrifugation of biofluids. Step 2: Detection of analyte signal through NMR or MS spectroscopy. Step 3: Small metabolites is filtered and quantified for significant biomarkers of interest. The images were obtained using the example data provided by the MetaboAnalyst 5.0 and figures created by BioRender

Fig. 4

Representative metabolite biomarkers associated with human diseases in clinical studies for disease phenotype, diagnosis, classification, prognosis, and treatment (the detailed information showed in Table 1)

Fig. 5

Potential roles and applications of small-molecule candidate metabolites for biomarker discovery, diseases diagnosis, prognosis, and monitoring treatments in biomedicine. Compound detection, metabolites are detected by using specific detection techniques; data pre-processing, raw signals are then pre-processed to produce data in a suitable format for subsequent statistical analysis; then, data normalization is used to reduce the system and technical bias; data processing, for untargeted studies, metabolites are identified from spectral information in some given database; statistical analyses, univariate and multivariate statistical analyses are used to identify significantly expressed metabolites; biomarker discovery from multicenter, the discriminant metabolites originated from metabolomics approaches may become promising candidate molecules to aid disease diagnosis, and risk stratification; function analyses, next, the significantly expressed metabolites are subsequently linked to the biological context by using enrichment and pathway analysis. The images were obtained using the example data provided by the MetaboAnalyst 5.0 and figures created by BioRender

Fig. 6

Schematic diagram of an integrated pharmacology framework for discovery of bioactivity-correlated constituents, target identification and action mechanism of herbal medicine and natural products. The first stage discovers active compounds of treatment-related herbs followed by construction of correlation analysis network of treatment-related herb-compound and small molecule metabolite (Correlations based on the abundance scored value). Next is that highlight the main active constituents from identification of new candidates from natural products, and then elucidate the underlying mechanisms by target virtual screening and identification, until the final step of in vitro and in vivo tests. The images were obtained using the example data provided by the MetaboAnalyst 5.0 and figures created by BioRender

Fig. 7

Schematic summary of interactions of bile acids and gut microbe participate in the host metabolism. Note: BAs, bile acids; BSEP, bile salt export protein; FGF, fibroblast growth factor; FGFR, FGF receptor; RXR, retinoid X receptor; NTCP, sodium taurocholate cotransporting polypeptide; OATP, organic anion-transporting polypeptide; SHP, small heterodimer partner; JNK, c-Jun N-terminal kinase; ERK, extracellular signal-regulated kinase; T3, thyroid hormone; T4, thyroxine; DIO2, type 2 iodothyronine deiodinase; ASBT, apical sodium-dependent bile acid transporter; OST, organic solute transporter. Primary bile acids are synthesized and then conjugated with taurine or glycine in hepatocytes. Conjugated bile acids are transported into the bile duct by BSEP. Most conjugated bile acids are reabsorbed via ASBT and circulate to the liver by OATP, OSTa/b, and NTCP. Bile acids acts as the endogenous ligands for FXR and TGR5 to generate distinct effects on metabolism regulation. The figures created by BioRender