Title:Plasma Metabolome Signature in Patients with Early-stage Parkinson Disease
Volume: 6
Issue: 1
Author(s): Elena E. Balashova*, Petr G. Lokhov, Dmitry L. Maslov, Oxana P. Trifonova, Diana M. Khasanova, Zuleykha A. Zalyalova, Razina R. Nigmatullina, Alexander I. Archakov and Michael V. Ugrumov
Affiliation:
- Institute of Biomedical Chemistry, Pogodinskaya st.10, 119121, Moscow,Russian Federation
Keywords:
Metabolomics, parkinson disease, early diagnosis, patients, blood plasma, mass spectrometry.
Abstract: Background: Recent decades have been marked by advances in omics sciences based on
high-throughput technologies, which have enabled the measurement of enormous numbers of molecules
in biosamples. In metabolomics, a large number of small molecules (metabolome) can be detected
in a single run. The goal of this study was to evaluate the capacity for metabolomic analysis of
blood plasma for early-stage Parkinson Disease (PD) diagnosis.
Methods: Blood plasma samples collected from control subjects (n = 20) and patients with PD (Hoehn
and Yahr stages 1, 1.5, and 2; n = 16) were treated with methanol, and low-molecular-weight fractions
were analyzed by direct infusion mass spectrometry. Metabolite ions that exhibited strong association
with PD were included in a diagnostic signature compilation and corresponding characteristics for PD
diagnosis were calculated. For metabolite ions included in the signature, correspondence to specific
metabolites in metabolite databases was established.
Results: A total of 21 metabolite ions that were strongly associated with PD were used to compile a
metabolome signature. The area under a receiver operating characteristic curve (AUC) for PD diagnosis
calculated for the signature was 0.95 (accuracy 94%, specificity 95%, and sensitivity 94%). Metabolites
identified in this study were consistent with factors that had been associated with the development
of PD previously.
Conclusion: Direct infusion mass spectrometry of blood plasma metabolites represents a rapid singlestep
method with potential for application in early-stage PD diagnosis.
