Metabolomic Profiling of Bipolar Disorder by 1 H-NMR in Serbian Patients.
Katarina SimićZoran MiladinovićNina TodorovićSnežana TrifunovićNataša AvramovićAleksandra GavrilovićSilvana JovanovićDejan GođevacLjubodrag VujisićVele TeševićLjubica TasicBoris MandićPublished in: Metabolites (2023)
Bipolar disorder (BD) is a brain disorder that causes changes in a person's mood, energy, and ability to function. It has a prevalence of 60 million people worldwide, and it is among the top 20 diseases with the highest global burden. The complexity of this disease, including diverse genetic, environmental, and biochemical factors, and diagnoses based on the subjective recognition of symptoms without any clinical test of biomarker identification create significant difficulties in understanding and diagnosing BD. A 1 H-NMR-based metabolomic study applying chemometrics of serum samples of Serbian patients with BD (33) and healthy controls (39) was explored, providing the identification of 22 metabolites for this disease. A biomarker set including threonine, aspartate, gamma-aminobutyric acid, 2-hydroxybutyric acid, serine, and mannose was established for the first time in BD serum samples by an NMR-based metabolomics study. Six identified metabolites (3-hydroxybutyric acid, arginine, lysine, tyrosine, phenylalanine, and glycerol) are in agreement with the previously determined NMR-based sets of serum biomarkers in Brazilian and/or Chinese patient samples. The same established metabolites (lactate, alanine, valine, leucine, isoleucine, glutamine, glutamate, glucose, and choline) in three different ethnic and geographic origins (Serbia, Brazil, and China) might have a crucial role in the realization of a universal set of NMR biomarkers for BD.
Keyphrases
- bipolar disorder
- magnetic resonance
- high resolution
- solid state
- major depressive disorder
- ms ms
- ejection fraction
- end stage renal disease
- nitric oxide
- newly diagnosed
- multiple sclerosis
- metabolic syndrome
- genome wide
- case report
- skeletal muscle
- climate change
- protein kinase
- prognostic factors
- insulin resistance
- bioinformatics analysis
- brain injury
- amino acid
- life cycle
- physical activity
- liquid chromatography