- 作者: Shiek S.S.J Ahmed; Winkins Santosh; Suresh Kumar; Hema T Thanka Christlet
- 作者服務機構: Department of Biotechnology, School of Bioengineering, SRM University, Kattankulathur, Tamil Nadu, India,
- 中文摘要: --
- 英文摘要:
Background :
Parkinson's disease (PD) is a neurodegenerative disorder. The diagnosis of Parkinsonism is
challenging because currently none of the clinical tests have been proven to help in
diagnosis. PD may produce characteristic perturbations in the metabolome and such
variations can be used as the marker for detection of disease. To test this hypothesis, we
used proton NMR and multivariate analysis followed by neural network pattern detection.
Methods & Results :
1H nuclear magnetic resonance spectroscopy analysis was carried out on plasma samples of
37 healthy controls and 43 drug-naive patients with PD. Focus on 22 targeted metabolites,
17 were decreased and 5 were elevated in PD patients (p<0.05). Partial least squares
discriminant analysis (PLS-DA) showed that pyruvate is the key metabolite, which
contributes to the separation of PD from control samples. Furthermore, gene expression
analysis shows significant (p<0.05) change in expression of PDHB and NPFF genes
leading to increased pyruvate concentration in blood plasma. Moreover, the
implementation of 1H- NMR spectral pattern in neural network algorithm shows 97.22%
accuracy in the detection of disease progression.
Conclusions :
The results increase the prospect of a robust molecular definition in detection of PD
through the early symptomatic phase of the disease. This is an ultimate opening for
therapeutic intervention. If validated in a genuinely prospective fashion in larger samples,
the biomarker trajectories described here will go a long way to facilitate the development
of useful therapies. Moreover, implementation of neural network will be a breakthrough in
clinical screening and rapid detection of PD. - 中文關鍵字: --
- 英文關鍵字: --