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Growing evidence indicates a reciprocal relationship between low-grade systemic inflammation and stress exposure towards increased vulnerability to neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, the neural correlates of this reciprocity and their influence on the subsequent development of PTSD are largely unknown. Here we investigated alterations in functional connectivity among brain networks related to low-grade inflammation and stress exposure using two large independent data sets. Functional couplings among the higher-order cognitive network system including the salience, default mode, and central executive networks were reduced in association with low-grade inflammation and stress exposure. This reduced functional coupling may also be related to subsequent posttraumatic stress symptom severity. The current findings propose functional couplings among the higher-order cognitive network system as neural correlates of low-grade inflammation and stress exposure, and suggest that low-grade inflammation, alongside with stress, may render individuals more vulnerable to PTSD. Low-grade systemic inflammation and stress increase vulnerability to neuropsychiatric disorders. Here, the authors show that inflammation and stress-induced changes in higher order cognitive networks increase vulnerability to posttraumatic stress disorder.

Serotonin (5-HT) plays an important role in cerebrovascular homeostasis and psychiatric disorders, including suicidality. Methylation of the serotonin transporter gene ( SLC6A4 ) is associated with 5-HT expression. However, the prognostic roles of SLC6A4 methylation and suicidal ideation (SI) in long-term outcomes of stroke have not been evaluated. We investigated the independent and interactive effects of SLC6A4 methylation and SI immediately after stroke on long-term outcomes. Blood SLC6A4 methylation status and SI based on the suicide item of the Montgomery–Åsberg Depression Rating Scale were assessed in 278 patients at 2 weeks after stroke. After the index stroke, cerebro-cardiovascular events by SLC6A4 methylation status and SI were investigated over an 8–14-year follow-up period and using Cox regression models adjusted for a range of covariates. SLC6A4 hypermethylation and SI within 2 weeks of stroke both predicted worse long-term outcomes, independent of covariates. A significant interaction effect of SI and the methylation status of CpG 4 on long-term stroke outcomes was also identified. The association between SLC6A4 methylation and long-term adverse outcomes may be strengthened in the presence of SI within 2 weeks after stroke. Evaluation of methylation and SI status during the acute phase can be helpful when assessing stroke patients.

Effects of Type 1 Diabetes on Gray Matter Density as Measured by Voxel-Based Morphometry Gail Musen 1 2 , In Kyoon Lyoo 3 4 , Caitlin R. Sparks 1 , Katie Weinger 1 2 , Jaeuk Hwang 4 , Christopher M. Ryan 5 , David C. Jimerson 2 6 , John Hennen 2 7 † , Perry F. Renshaw 2 3 and Alan M. Jacobson 1 2 1 Research Division, Joslin Diabetes Center, Boston, Massachusetts 2 Department of Psychiatry, Harvard Medical School, Boston, Massachusetts 3 Brain Imaging Center, McLean Hospital, Belmont, Massachusetts 4 Seoul National University College of Medicine and Hospital, Seoul, Korea 5 Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 6 Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts 7 Biostatistics Laboratory, McLean Hospital, Belmont, Massachusetts Address correspondence and reprint requests to Gail Musen, PhD, Joslin Diabetes Center, 1 Joslin Place, Room 350, Boston, MA 02215. E-mail: gail.musen{at}joslin.harvard.edu Abstract The effects of type 1 diabetes and key metabolic variables on brain structure are not well understood. Sensitive methods of assessing brain structure, such as voxel-based morphometry (VBM), have not previously been used to investigate central nervous system changes in a diabetic population. Using VBM, we compared type 1 diabetic patients aged 25–40 years with disease duration of 15–25 years and minimal diabetes complications with an age-matched, nondiabetic control group. We investigated whether lower than expected gray matter densities were present, and if so, whether they were associated with glycemic control and history of severe hypoglycemic events. In comparison with control subjects, diabetic patients showed lower density of gray matter in several brain regions. Moreover, in the patient group, higher HbA 1c levels and severe hypoglycemic events were associated with lower density of gray matter in brain regions responsible for language processing and memory. Our study represents the first comprehensive study of gray matter density changes in type 1 diabetes and suggests that persistent hyperglycemia and acute severe hypoglycemia have an impact on brain structure. CNS, central nervous system MRI, magnetic resonance imaging STG, superior temporal gyrus VBM, voxel-based morphometry WASI, Wechsler Abbreviated Scale of Intelligence Footnotes † † J.H. is deceased. Accepted October 24, 2005. Received May 5, 2005. DIABETES

The clinical applications of brain age prediction have expanded, particularly in anticipating the onset and prognosis of various neurodegenerative diseases. In the current study, we proposed a deep learning algorithm that leverages brain structural imaging data and enhances prediction accuracy by integrating biological sex information. Our model for brain age prediction, built on deep neural networks, employed a dataset of 3004 healthy subjects aged 18 and above. The T1-weighted images were minimally preprocessed and analyzed using the convolutional neural network (CNN) algorithm. The categorical sex information was then incorporated using the multi-layer perceptron (MLP) algorithm. We trained and validated both a CNN-only algorithm (utilizing only brain structural imaging data), and a combined CNN-MLP algorithm (using both structural brain imaging data and sex information) for age prediction. By integrating sex information with T1-weighted imaging data, our proposed CNN-MLP algorithm outperformed not only the CNN-only algorithm but also established algorithms, such as brainageR, in prediction accuracy. Notably, this hybrid CNN-MLP algorithm effectively distinguished between mild cognitive impairment and Alzheimer’s disease groups by identifying variances in brain age gaps between them, highlighting the algorithm’s potential for clinical application. Overall, these results underscore the enhanced precision of the CNN-MLP algorithm in brain age prediction, achieved through the integration of sex information.

Background Growing literature continues to identify brain regions that are functionally altered in bipolar disorder. However, precise functional network correlates of bipolar disorder have yet to be determined due to inconsistent results. The overview of neurological alterations from a large‐scale network perspective may provide more comprehensive results and elucidate the neuropathology of bipolar disorder. Here, we critically review recent neuroimaging research on bipolar disorder using a network‐based approach. Methods A systematic search was conducted on studies published from 2009 through 2019 in PubMed and Google Scholar. Articles that utilized functional magnetic resonance imaging technique to examine altered functional activity of major regions belonging to a large‐scale brain network in bipolar disorder were selected. Results A total of 49 studies were reviewed. Within‐network hypoconnectivity was reported in bipolar disorder at rest among the default mode, salience, and central executive networks. In contrast, when performing a cognitive task, hyperconnectivity among the central executive network was found. Internetwork functional connectivity in the brain of bipolar disorder was greater between the salience and default mode networks, while reduced between the salience and central executive networks at rest, compared to control. Conclusion This systematic review suggests disruption in the functional activity of large‐scale brain networks at rest as well as during a task stimuli in bipolar disorder. Disrupted intra‐ and internetwork functional connectivity that are also associated with clinical symptoms suggest altered functional connectivity of and between large‐scale networks plays an important role in the pathophysiology of bipolar disorder. The investigation of the brain alterations with a large‐scale network perspective may provide a more comprehensive way in elucidating the neuropathology of a disorder. This systematic review evaluates recent literature and suggests alteration in the functional activity of large‐scale brain networks including the default mode, salience, and central executive networks in bipolar disorder. Furthermore, disrupted intra‐ and internetwork functional connectivity are also associated with clinical symptoms of bipolar disorder, which highlight the importance of large‐scale networks in the pathophysiology of bipolar disorder.

There is a need to improve the understanding of the neurobiological underpinnings of traumatic brain injury (TBI). Individuals with TBI experience comorbidities such as posttraumatic stress disorder (PTSD) with considerable symptom overlap including depression and hyperarousal, confounding the ability to identify specific TBI-related brain changes. The aims of the current study were to investigate hippocampal and amygdalar volumes in Veterans with TBI with (TBI + PTSD, n = 32) and without (TBI - PTSD, n = 25) PTSD. Shape analysis was employed to reveal any relationship between the hippocampus and depressive symptoms in TBI subgroups. 32 TBI + PTSD, 25 TBI - PTSD, and 25 age-matched healthy male Veterans underwent an MRI scan on a 3 Tesla scanner and a clinical evaluation. The TBI + PTSD and the TBI + hyperarousal (met criteria for the hyperarousal symptom cluster, regardless of PTSD diagnosis) subgroup had trend-level larger left amygdalar volume than the TBI - PTSD subgroup and the TBI - hyperarousal subgroup, respectively. However, there was no significant difference between the TBI group as a whole and healthy controls (HC). There was a significant negative correlation between the Hamilton Rating Scale for Depression score (HAM-D) and left hippocampal volume and a positive correlation between the HAM-D score and left amygdalar volume in the TBI group. Left hippocampal volume was correlated with the HAM-D score only in the TBI + PTSD and not in TBI - PTSD subgroup. Shape analyses revealed a significant correlation between the HAM-D score and the CA1 and subiculum regions of the left hippocampus. Our results suggest that the amygdala may be a neuroanatomical correlate in mediating PTSD-like symptoms in Veterans with TBI. The results of shape analysis suggest that alterations in the CA1 and subiculum subregions of hippocampus may have a role in depression and PTSD.

Repeated exposure to traumatic experiences may put professional firefighters at increased risk of developing posttraumatic stress disorder (PTSD). To date, however, the rate of PTSD symptoms, unmet need for mental health treatment, and barriers to treatment have only been investigated in subsamples rather than the total population of firefighters. We conducted a nationwide, total population-based survey of all currently employed South Korean firefighters (n = 39,562). The overall response rate was 93.8% (n = 37,093), with 68.0% (n = 26,887) complete responses for all variables. The rate of current probable PTSD was estimated as 5.4%. Among those with current probable PTSD (n = 1,995), only a small proportion (9.7%) had received mental health treatment during the past month. For those who had not received treatment, perceived barriers of accessibility to treatment (29.3%) and concerns about potential stigma (33.8%) were reasons for not receiving treatment. Although those with higher PTSD symptom severity and functional impairment were more likely to seek treatment, greater symptom severity and functional impairment were most strongly associated with increased concerns about potential stigma. This nationwide study points to the need for new approaches to promote access to mental health treatment in professional firefighters.

This study investigated changes in neuroinflammation and cognitive function in adult zebrafish exposed to acute hypoxia and protective effects of glucosamine (GlcN) against hypoxia-induced brain damage. The survival rate of zebrafish following exposure to hypoxia was improved by GlcN pretreatment. Moreover, hypoxia-induced upregulation of neuroglobin, NOS2α, glial fibrillary acidic protein, and S100β in zebrafish was suppressed by GlcN. Hypoxia stimulated cell proliferation in the telencephalic ventral domain and in cerebellum subregions. GlcN decreased the number of bromodeoxyuridine (BrdU)-positive cells in the telencephalon region, but not in cerebellum regions. Transient motor neuron defects, assessed by measuring the locomotor and exploratory activity of zebrafish exposed to hypoxia recovered quickly. GlcN did not affect hypoxia-induced motor activity changes. In passive avoidance tests, hypoxia impaired learning and memory ability, deficits that were rescued by GlcN. A learning stimulus increased the nuclear translocation of phosphorylated cAMP response element binding protein (p-CREB), an effect that was greatly inhibited by hypoxia. GlcN restored nuclear p-CREB after a learning trial in hypoxia-exposed zebrafish. The neurotransmitters, γ-aminobutyric acid and glutamate, were increased after hypoxia in the zebrafish brain, and GlcN further increased their levels. In contrast, acetylcholine levels were reduced by hypoxia and restored by GlcN. Acetylcholinesterase inhibitor physostigmine partially reversed the impaired learning and memory of hypoxic zebrafish. This study represents the first examination of the molecular mechanisms underlying hypoxia-induced memory and learning defects in a zebrafish model. Our results further suggest that GlcN-associated hexosamine metabolic pathway could be an important therapeutic target for hypoxic brain damage.

The adolescent brain may be susceptible to the influences of illicit drug use. While compensatory network reorganization is a unique developmental characteristic that may restore several brain disorders, its association with methamphetamine (MA) use-induced damage during adolescence is unclear. Using independent component (IC) analysis on structural magnetic resonance imaging data, spatially ICs described as morphometric networks were extracted to examine the effects of MA use on gray matter (GM) volumes and network module connectivity in adolescents (51 MA users v. 60 controls) and adults (54 MA users v. 60 controls). MA use was related to significant GM volume reductions in the default mode, cognitive control, salience, limbic, sensory and visual network modules in adolescents. GM volumes were also reduced in the limbic and visual network modules of the adult MA group as compared to the adult control group. Differential patterns of structural connectivity between the basal ganglia (BG) and network modules were found between the adolescent and adult MA groups. Specifically, adult MA users exhibited significantly reduced connectivity of the BG with the default network modules compared to control adults, while adolescent MA users, despite the greater extent of network GM volume reductions, did not show alterations in network connectivity relative to control adolescents. Our findings suggest the potential of compensatory network reorganization in adolescent brains in response to MA use. The developmental characteristic to compensate for MA-induced brain damage can be considered as an age-specific therapeutic target for adolescent MA users.

Childhood overweight/obesity has been associated with negative consequences related to brain function and may involve alterations in white matter pathways important for cognitive and emotional processing. Aerobic physical activity is a promising lifestyle factor that could restore white matter alterations. However, little is known about either regional white matter alterations in children with overweight/obesity or the effects of aerobic physical activity targeting the obesity-related brain alterations in children. Using a large-scale cross-sectional population-based dataset of US children aged 9 to 10 years ( n = 8019), this study explored the associations between overweight/obesity and microstructure of limbic white matter tracts, and examined whether aerobic physical activity may reduce the overweight/obesity-related white matter alterations in children. The primary outcome measure was restriction spectrum imaging (RSI)-derived white matter microstructural integrity measures. The number of days in a week that children engaged in aerobic physical activity for at least 60 minutes per day was assessed. We found that females with overweight/obesity had lower measures of integrity of the fimbria-fornix, a major limbic-hippocampal white matter tract, than their lean peers, while this difference was not significant in males. We also found a positive relationship between the number of days of aerobic physical activity completed in a week and integrity measures of the fimbria-fornix in females with overweight/obesity. Our results provide cross-sectional evidence of sex-specific microstructural alteration in the fimbria-fornix in children with overweight/obesity and suggest that aerobic physical activity may play a role in reducing this alteration. Future work should examine the causal direction of the relationship between childhood overweight/obesity and brain alterations and evaluate potential interventions to validate the effects of aerobic physical activity on this relationship.