Background: Major depressive disorder (MDD) is characterized by increased oxidative and nitrosative stress. We compared nitric oxide metabolism, i.e., the global arginine bioavailability ratio (GABR) and related serum amino acids, between MDD patients and non-depressed controls, and between remitted and non-remitted MDD patients.
Methods: Ninety-nine MDD patients and 253 non-depressed controls, aged 20-71 years, provided background data via questionnaires. Fasting serum samples were analyzed using ultra-performance liquid chromatography coupled to mass spectrometry to determine the serum levels of ornithine, arginine, citrulline, and symmetric and asymmetric dimethylarginine. GABR was calculated as arginine divided by the sum of ornithine plus citrulline. We compared the above measures between: 1) MDD patients and controls, 2) remitted (n=33) and non-remitted (n = 45) MDD patients, and 3) baseline and follow-up within the remitted and non-remitted groups.
Results: Lower arginine levels (OR 0.98, 95% CI 0.97-0.99) and lower GABR (OR 0.13, 95% CI 0.03-0.50) were associated with the MDD vs. the non-depressed group after adjustments for potential confounders. The remitted group showed a decrease in GABR, arginine, and symmetric dimethylarginine, and an increase in ornithine after the follow-up compared with within-group baseline values. The non-remitted group displayed an increase in arginine and ornithine levels and a decrease in GABR. No significant differences were recorded between the remitted and non-remitted groups.
Limitations: The MDD group was not medication-free.
Conclusions: Arginine bioavailability may be decreased in MDD. This could impair the production of nitric oxide, and thus add to oxidative stress in the central nervous system.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jad.2017.12.030 | DOI Listing |
Background: Selecting the optimal dose for clinical development is especially problematic for drugs directed at CNS-specific targets. For drugs with a novel mechanism of action, these problems are often greater. We describe Xanamem's clinical pharmacology, including the approach to dose selection and proof-of-concept studies.
View Article and Find Full Text PDFMed J Islam Repub Iran
October 2024
Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Background: No study was conducted to investigate the association between principal component (PCA) derived meal-based dietary patterns and odds of major depressive disorder. We aimed to explore the association between major dietary patterns at breakfast and oddsof major depressive disorder (MDD).
Methods: A total of 200 drug-free patients with MDD and 200 healthy individuals were enrolled in this age- and sex-matched case-control study.
Biomed Eng Lett
January 2025
Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, 44919 Republic of Korea.
Unlabelled: Patients suffering from various neurological disorders, including major depressive disorder (MDD), often exhibit abnormal brain connectivity. In particular, patients with MDD show atypical brain oscillations propagation. This study aims to investigate an association between abnormal brain connectivity and atypical oscillatory propagation of electroencephalogram (EEG) signals in patients with a history of MDD.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Radiology, The 960th Hospital of People's Liberation Army Joint Logistic Support Force, Jinan, China.
Insomnia is a common mental illness seriously affecting people lives, that might progress to major depression. However, the neural mechanism of patients with CID comorbid MDD remain unclear. Combining fractional amplitude of low-frequency fluctuation (fALFF) and seed-based functional connectivity (FC), this study investigated abnormality in local and long-range neural activity of patients with CID comorbid MDD.
View Article and Find Full Text PDFPatterns (N Y)
December 2024
Medical Robot Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
This study developed an artificial intelligence (AI) system using a local-global multimodal fusion graph neural network (LGMF-GNN) to address the challenge of diagnosing major depressive disorder (MDD), a complex disease influenced by social, psychological, and biological factors. Utilizing functional MRI, structural MRI, and electronic health records, the system offers an objective diagnostic method by integrating individual brain regions and population data. Tested across cohorts from China, Japan, and Russia with 1,182 healthy controls and 1,260 MDD patients from 24 institutions, it achieved a classification accuracy of 78.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!