Metabolomic Biomarkers

Metabolomics, defined as large-scale profiling of small molecular metabolites present in a cell, tissue, body fluids, or any biological system, has opened new avenues for biomarker identification. Metabolites include various low-molecular end products of diverse cellular processes, such as lipids, amino acids, peptides, vitamins, organic acids, carbohydrates, and nuclear acids. The levels of metabolites are considered to be the ultimate response of biological systems to genetic, environmental, and lifestyle factors under normal or diseased states. Current commonly used methods for studying metabolomics are nuclear magnetic resonance and mass spectrometry, along with gas chromatography, liquid chromatography, or capillary electrophoresis for sample separations [15].

Zhai and coworkers utilized targeted metabolite profiling to investigate the association of metabolite ratios in serum with the development of knee OA. They found 14 ratios that were significantly associated with knee OA at discovery stage in their cohort. By replicating this study in the Chingford cohort, two of these 14 ratios (valine/histidine and xleucine/histidine) were successfully confirmed to correlate with radiographic severity of OA. Mechanically, as these branched-chain amino acids (BCAAs) including valine and xleucine could not be synthesized by the body, an increase in BCAAs metabolites implied the breakdown of collagen. This was the first study using serum-based metabolomics and demonstrated that the BCAAs to histidine ratio have potential clinical use as an OA biomarker.

Jiang et al. reported a mass spectrometry-based metabolic study to identify the global metabolic defects in the serum of four major types of arthritis including RA (n= 27), OA (n= 27), ankylosing spondylitis (n= 27), and gout (n= 33) compared with healthy control subjects (n= 60). They identified a global metabolic profile in all arthritic patients, suggesting these four types of arthritis share common metabolic defects possibly resulting from joint inflammation. Meanwhile, a unique metabolic signature, potential biomarker for diagnosis, was discovered for each type of arthritis. This report demonstrated the applicability of metabolomic profiling as a novel diagnostic tool for arthritis including OA, along with current clinical detection methods [17].

These studies have linked abnormal metabolic changes to the pathogenesis of OA, and metabolomics have proven to be a new robust tool for biomarker discovery in OA. This is in accordance with the emerging new subtype of OA, metabolic syndrome OA, which has recently been recognized because of the increased incidence of OA in patients with metabolic syndrome such as dyslipidemia, hypertension, obesity, and type 2 diabetes. Therefore, biomarkers identified by metabolomics will also help discriminate between different OA subtypes [16].

MicroRNAs Biomarkers in Osteoarthritis