SEARCHING FOR METABOLIC MARKERS OF CHARCOT-MARIE-TOOTH DISEASE

Objectives
Charcot–Marie–Tooth disease (CMT) is the most common hereditary neuromuscular disorder. It is a clinically and genetically heterogeneous group of disorders with the phenotype of chronic, slowly progressive neuropathy affecting both the motor and the sensory nerves. Currently, there are no effective pharmacological treatments for CMT available. Biomarkers that could detect the effect of treatment on disease progression are crucial for successful clinical trials. Metabolome analysis is the characterization of small molecules (<1500 Daltons) in biological matrices using analytical chemistry techniques. It has been widely used for discovering diagnostic and prognostic markers. This study aimed to analyse selected plasma metabolite concentrations in CMT cohort and compare them to healthy controls.
Materials and Methods
A cohort of 84 patients with CMT and 34 healthy controls were recruited to this study. All CMT individuals underwent genetic testing. As a control group, our study included healthy individuals without known neurological diseases or symptoms. Targeted plasma metabolic analysis was performed by ultrahigh performance liquid chromatography-mass spectrometry (UHPLC-MS) to determine plasma levels of 55 selected metabolites. Statistical analysis was performed with Prism 9 and MetaboAnalyst 6.0. The study was approved by the Central Medical Ethics Committee of Latvia (No. 3/18-03- 21). Written informed consent was obtained from all participants in the study.
Results
A total of 33 metabolites were analysed in plasma. We found that plasma ratio of acetylcarnitine was elevated and plasma ratio of glycine was decreased in the CMT group compared with controls. Next we subdivided CMT group according to the genetic findings: CMT1A (n=37), CMTX1 (n=17), CMT2A (n=4), HINT1 (n=5), other genetic subtypes (n=14), unknown genetic type (n=7). Consequently, we screened for differential plasma metabolites between separate genetic CMT groups. We discovered that acetylcarnitine in the CMT1A group and glycine and valine in the CMT1X group are different from the controls. However, prediction analysis showed poor accuracy for predicting the disease.
Conclusions
In this study we performed targeted plasma metabolic analysis in CMT patients and healthy controls. We have identified that CMT patients have significantly higher levels of acetylcarnitine and decreased glycine levels compared to controls. In addition, the CMTX1 subgroup has decreased valine levels compared to controls. However, our predictive models suggest no good predictive power of the detected plasma metabolites for any CMT group. In general, above mentioned metabolites have been reported before as contributors of pathogenesis in peripheral neuropathies. However, more data and longitudinal evaluation is needed to establish whether these metabolites could potentially become specific CMT biomarkers.