Metabolic profiling employing hydrogen nuclear magnetic resonance (1H NMR) spectroscopy and chemometric analysis of human blood serum samples taken from the control group (n = 25) and patients with bipolar disorder (n = 25) was performed to identify molecular changes related to the disorder and to different drug treatments: lithium (n = 15) versus other medications (n = 10). This strategy showed significant potential for exploring pathophysiological and toxicological features involved in bipolar disorder. The investigated groups (control and patients with bipolar disorder under different treatments) could be distinguished according to their metabolic profiles, and the main differential metabolites found were lipids, lipid-metabolism-related molecules (acetate, choline, and myo-inositol), and some key amino acids (glutamate, glutamine). Our results suggest that some of the 24 identified metabolites may be linked to lithium- and other-medication-provoked metabolic changes or may even be directly related to the disorder. Thus, these findings may contribute to paving the way for future studies aiming at identifying potential biomarkers for bipolar disorder.

Download full-text PDF

Source
http://dx.doi.org/10.1021/ac901502jDOI Listing

Publication Analysis

Top Keywords

bipolar disorder
20
patients bipolar
12
metabolic profiling
8
human blood
8
blood serum
8
nmr spectroscopy
8
disorder
7
bipolar
5
metabolic
4
profiling human
4

Similar Publications

Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder.

Neuroradiology

January 2025

Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.

Introduction: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI and machine learning techniques to determine whether regional morphological differences could distinguish patients with BD and MDD.

Methods: A total of 123 participants, including BD (n = 31), MDD (n = 48), and healthy controls (HC, n = 44), underwent high-resolution 3D T1-weighted imaging.

View Article and Find Full Text PDF

Bipolar disorder (BD) involves altered reward processing and decision-making, with inconsistencies across studies. Here, we integrated hierarchical Bayesian modelling with magnetoencephalography (MEG) to characterise maladaptive belief updating in this condition. First, we determined if previously reported increased learning rates in BD stem from a heightened expectation of environmental changes.

View Article and Find Full Text PDF

Synaptic protein expression in bipolar disorder patient-derived neurons implicates PSD-95 as a marker of lithium response.

Neuropharmacology

January 2025

Department of Psychiatry and Center for Circadian Biology, University of California San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA. Electronic address:

Bipolar disorder (BD) is a severe mental illness characterized by recurrent episodes of depression and mania. Lithium is the gold standard pharmacotherapy for BD, but outcomes are variable, and the relevant therapeutic mechanisms underlying successful treatment response remain uncertain. To identify synaptic markers of BD and lithium response, we measured the effects of lithium on induced pluripotent stem cell-derived neurons from BD patients and controls.

View Article and Find Full Text PDF

Introduction: Unipolar and bipolar mood disorders in older adults are accompanied by cognitive impairment, including executive dysfunction, with a severe impact on daily life. Up and till now, strategies to improve cognitive functioning in late-life mood disorders (LLMD) are sparse. Therefore, we aimed to assess the efficacy of adaptive, computerized cognitive training (CT) on executive and subjective cognitive functioning in LLMD.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!