Reports regarding the associations between major depressive disorder (MDD) and diabetes remain heterogeneous. Our aim was to investigate whether glucose homeostasis and insulin sensitivity were impaired in the MDD patients and its mechanisms. A total of 30 patients with MDD and 30 matched controls were recruited. The oral glucose tolerance test and dual-energy X-ray absorptiometry scan were performed in each participant. Insulin signaling in postmortem brain tissues from other depressive patients and controls (obtained from Alabama brain bank) was examined. Insulin sensitivity was reduced substantially in the MDD patients, however, the fasting and 2-h glucose concentrations remained within the normal range through compensatory insulin secretion. Despite increased insulin secretion, 1-h glucose concentrations in the MDD patients were significantly elevated compared with the controls. MDD patients had greater visceral fat mass but lower adiponectin levels compared with the controls. Furthermore, phosphorylated-AKT levels in insulin signaling were decreased in postmortem brain tissues in patients with MDD. These results suggest that MDD patients are at a greater risk for diabetes due to decreased insulin sensitivity, reduced disposition index, and impaired glucose tolerance as manifested by elevated 1-h glucose concentrations following an oral glucose challenge. Mechanistic studies reveal that decreased insulin sensitivity is associated with increased visceral fat mass, lower adiponectin levels and impaired insulin action in postmortem brain tissues in the MDD patients. Our findings emphasize the importance of screening depressive patients to identify susceptible individuals for developing future diabetes with the hope of improving their health outcomes.
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http://dx.doi.org/10.4172/2155-6156.1000664 | DOI Listing |
Sensors (Basel)
January 2025
University of Zagreb Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia.
Major depressive disorder (MDD) is associated with substantial morbidity and mortality, yet its diagnosis and treatment rates remain low due to its diverse and often overlapping clinical manifestations. In this context, electroencephalography (EEG) has gained attention as a potential objective tool for diagnosing depression. This study aimed to evaluate the effectiveness of EEG in identifying MDD by analyzing 140 EEG recordings from patients diagnosed with depression and healthy volunteers.
View Article and Find Full Text PDFJ ECT
January 2025
From the Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA.
Background: Electroconvulsive therapy (ECT) is an effective treatment for treatment-resistant depression (TRD). There are limited data on the improvement of anxiety symptoms in patients receiving ECT for TRD.
Objective: The aim of the study was to examine the extent to which anxiety symptom severity improves, relative to improvements in depressive symptoms, in TRD patients receiving an acute course of ECT.
Circ Cardiovasc Interv
January 2025
Division of Cardiology, Department of Medicine, University of Washington Medical Center, Seattle (E.J.S., T. Salahuddin, J.A.D.).
Background: Intravascular imaging (IVI) is widely recognized to improve outcomes after percutaneous coronary intervention (PCI). However, IVI is underutilized and is not yet established as a performance measure for quality PCI.
Methods: We examined temporal trends of IVI use for all PCIs performed at Veterans Affairs hospitals in the United States from 2010 to 2022 using retrospective observational cohorts.
Front Psychiatry
January 2025
Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea.
Background: Stress is a significant risk factor for psychiatric disorders such as major depressive disorder (MDD) and panic disorder (PD). This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the autonomic nervous system, which can be evaluated via heart rate variability (HRV).
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