Body mass index and variability in hippocampal volume in youth with major depressive disorder

Sex-Specific Association of Body Mass Index with Hippocampal Subfield Volume and Cognitive Function in Non-Demented Chinese Older Adults

Recent research suggests a possible association between midlife obesity and an increased risk of dementia in later life. However, the underlying mechanisms remain unclear. Little is known about the relationship between body mass index (BMI) and hippocampal subfield atrophy. In this study, we aimed to explore the associations between BMI and hippocampal subfield volumes and cognitive function in non-demented Chinese older adults. Hippocampal volumes were assessed using structural magnetic resonance imaging. Cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). A total of 66 participants were included in the final analysis, with 35 females and 31 males. We observed a significant correlation between BMI and the hippocampal fissure volume in older females. In addition, there was a negative association between BMI and the RBANS total scale score, the coding score, and the story recall score, whereas no significant correlations were observed in older males. In conclusion, our findings revealed sex-specific associations between BMI and hippocampal subfield volumes and cognitive performance, providing valuable insights into the development of effective interventions for the early prevention of cognitive decline.

Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease

Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Meta-analysis and Open-source Database for In Vivo Brain Magnetic Resonance Spectroscopy in Health and Disease

Proton ( 1 H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo . Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T 2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Brain structural and functional alterations in individuals with combined overweight/obesity and mood disorders: A systematic review of neuroimaging studies

Growing evidence suggests there is a bidirectional relationship between depression and obesity, which are associated with structural and functional brain abnormalities. However, the underlying neurobiological mechanisms subserving the foregoing associations have yet to be characterized. It is necessary to summarize the neuroplastic brain changes in relation to depression and obesity. We systematically searched articles from 1990 to November 2022 on databases including MEDLINE/PubMed, Web of Science, PsycINFO. Only neuroimaging studies within the scope of potential differences in brain function and structure in individuals with depression and obesity/ BMI changes were included. Twenty-four eligible studies were included in the review herein, consisting of 17 studies reporting changes in brain structure, 4 studies reporting abnormal brain function, and 3 studies reporting both changes in brain structure and function. Results indicated an interaction between depression and obesity on brain functions, and their influence on brain structure is both extensive and specific. Overall, reduced whole brain, intracranial, and gray matter volume (e.g. frontal, temporal gyri, thalamic, and hippocampal) and impaired white matter integrity was observed in persons with depression and obesity comorbidity. Additional evidence on resting state fMRI reveals select brain regions associated with cognitive control, emotion regulation, and reward functions. Due to the diversity of tasks in task fMRI, the distinct neural activation patterns are revealed separately. The bidirectional relationship between depression and obesity reflects different characteristics in brain structure and function. Longitudinal designs should be reinforced in follow-up studies.

Effect of depressive symptom and depressive disorder on glaucoma incidence in elderly

Although depression and glaucoma share several common pathophysiology, the risk of glaucoma in patients with depression has not been reported. Thus, we investigated the effect of depressive symptom and depressive disorder on glaucoma incidence. In this nationwide population-based cohort study, all subjects receiving the National Screening Program at the age of 66 during 2009-2014 were included. These subjects were divided into depression group and no depression group based on subjective depressive symptoms and clinically diagnosed depressive disorder and were tracked until 2017 for development of glaucoma. Of the 922,769 subjects included in the study, 191,636 (20.77%) subjects were categorized as depression group. Subjects with depression showed increased hazard of developing glaucoma (adjusted HR = 1.12[95% confidence interval (CI), 1.09-1.15]) than those without depression. The risk of glaucoma increased sequentially from those with no depression to those with subjective depressive symptom (adjusted HR = 1.09[95% CI, 1.06-1.13]), those with clinically diagnosed depressive disorder (adjusted HR = 1.23[95% CI, 1.14-1.32]), and those with both subjective depressive symptom and clinically diagnosed depressive disorder (adjusted HR = 1.36[95% CI, 1.22-1.52]). Our analyses suggest that individuals with depression had a greater risk of developing glaucoma than those without depression. Subjective depressive symptoms and clinically diagnosed depressive disorder independently and synergistically increased the risk of glaucoma incidence.