Impact of lifetime stressor exposure on neuroenergetics in schizophrenia spectrum disorders.

N-acetylasparate and lactate are two prominent brain metabolites closely related to mitochondrial functioning. Prior research revealing lower levels of NAA and higher levels of lactate in the cerebral cortex of patients with schizophrenia suggest possible abnormalities in the energy supply pathway necessary for brain function. Given that stress and adversity are a strong risk factor for a variety of mental health problems, including psychotic disorders, we investigated the hypothesis that stress contributes to abnormal neuroenergetics in patients with schizophrenia. To test this hypothesis, we used the Stress and Adversity Inventory (STRAIN) to comprehensively assess the lifetime stressor exposure profiles of 35 patients with schizophrenia spectrum disorders and 33 healthy controls who were also assessed with proton magnetic resonance spectroscopy at the anterior cingulate cortex using 3 Tesla scanner. Consistent with the hypothesis, greater lifetime stressor exposure was significantly associated with lower levels of N-acetylasparate (ß = -0.36, p = .005) and higher levels of lactate (ß = 0.43, p = .001). Moreover, these results were driven by patients, as these associations were significant for the patient but not control group. Though preliminary, these findings suggest a possible role for stress processes in the pathophysiology of abnormal neuroenergetics in schizophrenia.

Combining neuroimaging and brain stimulation to test alternative causal pathways for nicotine addiction in schizophrenia.

The smoking rate is high in patients with schizophrenia. Brain stimulation targeting conventional brain circuits associated with nicotine addiction has also yielded mixed results. We aimed to identify alternative circuitries associated with nicotine addiction in both the general population and schizophrenia, and then test whether modulation of such circuitries may alter nicotine addiction behaviors in schizophrenia. In Study I of 40 schizophrenia smokers and 51 non-psychiatric smokers, cross-sectional neuroimaging analysis identified resting state functional connectivity (rsFC) between the dorsomedial prefrontal cortex (dmPFC) and multiple extended amygdala regions to be most robustly associated with nicotine addiction severity in healthy controls and schizophrenia patients (p = 0.006 to 0.07). In Study II with another 30 patient smokers, a proof-of-concept, patient- and rater-blind, randomized, sham-controlled rTMS design was used to test whether targeting the newly identified dmPFC location may causally enhance the rsFC and reduce nicotine addiction in schizophrenia. Although significant interactions were not observed, exploratory analyses showed that this dmPFC-extended amygdala rsFC was enhanced by 4-week active 10Hz rTMS (p = 0.05) compared to baseline; the severity of nicotine addiction showed trends of reduction after 3 and 4 weeks (p ≤ 0.05) of active rTMS compared to sham; Increased rsFC by active rTMS predicted reduction of cigarettes/day (R = -0.56, p = 0.025 uncorrected) and morning smoking severity (R = -0.59, p = 0.016 uncorrected). These results suggest that the dmPFC-extended amygdala circuit may be linked to nicotine addiction in schizophrenia and healthy individuals, and future efforts targeting its underlying pathophysiological mechanisms may yield more effective treatment for nicotine addiction.

Revisiting delusion subtypes in schizophrenia based on their underlying structures.

A clear understanding of the pathophysiology of schizophrenia and related spectrum disorders has been limited by clinical heterogeneity. We investigated whether relative severity and predominance of one or more delusion subtypes might yield clinically differentiable patient profiles. Patients (N = 286) with schizophrenia spectrum disorders (SSD) completed the 21-item Peters et al. Delusions Inventory (PDI-21). We performed factor analysis followed by k-means clustering to identify delusion factors and patient subtypes. Patients were further assessed via the Brief Psychiatric Rating Scale, Brief Negative Symptom Scale, Digit Symbol and Digit Substitution tasks, use of cannabis and tobacco, and stressful life events. The overall patient sample clustered into subtypes corresponding to Low-Delusion, Grandiose-Predominant, Paranoid-Predominant, and Pan-Delusion patients. Paranoid-Predominant and Pan-Delusion patients showed significantly higher burden of positive symptoms, while Low-Delusion patients showed the highest burden of negative symptoms. The Paranoia delusion factor score showed a positive association with Digit Symbol and Digit Substitution tasks in the overall sample, and the Paranoid-Predominant subtype exhibited the best performance on both tasks. Grandiose-Predominant patients showed significantly higher tobacco smoking severity than other subtypes, while Paranoid-Predominant patients were significantly more likely to have a lifetime diagnosis of Cannabis Use Disorder. We suggest that delusion self-report inventories such as the PDI-21 may be of utility in identifying sub-syndromes in SSD. From the current study, a Paranoid-Predominant form may be most distinctive, with features including less cognitive impairment and a stronger association with cannabis use.

Reciprocal relationships between stress and depressive symptoms: the essential role of the nucleus accumbens.

BACKGROUND: Stress and depression have a reciprocal relationship, but the neural underpinnings of this reciprocity are unclear. We investigated neuroimaging phenotypes that facilitate the reciprocity between stress and depressive symptoms. METHODS: In total, 22 195 participants (52.0% females) from the population-based UK Biobank study completed two visits (initial visit: 2006-2010, age = 55.0 ± 7.5 [40-70] years; second visit: 2014-2019; age = 62.7 ± 7.5 [44-80] years). Structural equation modeling was used to examine the longitudinal relationship between self-report stressful life events (SLEs) and depressive symptoms. Cross-sectional data were used to examine the overlap between neuroimaging correlates of SLEs and depressive symptoms on the second visit among 138 multimodal imaging phenotypes. RESULTS: Longitudinal data were consistent with significant bidirectional causal relationship between SLEs and depressive symptoms. In cross-sectional analyses, SLEs were significantly associated with lower bilateral nucleus accumbal volume and lower fractional anisotropy of the forceps major. Depressive symptoms were significantly associated with extensive white matter hyperintensities, thinner cortex, lower subcortical volume, and white matter microstructural deficits, mainly in corticostriatal-limbic structures. Lower bilateral nucleus accumbal volume were the only imaging phenotypes with overlapping effects of depressive symptoms and SLEs (B = -0.032 to -0.023, p = 0.006-0.034). Depressive symptoms and SLEs significantly partially mediated the effects of each other on left and right nucleus accumbens volume (proportion of effects mediated = 12.7-14.3%, p < 0.001-p = 0.008). For the left nucleus accumbens, post-hoc seed-based analysis showed lower resting-state functional connectivity with the left orbitofrontal cortex (cluster size = 83 voxels, p = 5.4 × 10-5) in participants with high v. no SLEs. CONCLUSIONS: The nucleus accumbens may play a key role in the reciprocity between stress and depressive symptoms.

Effects of independent versus dependent stressful life events on major symptom domains of schizophrenia.

We evaluated two models to link stressful life events (SLEs) with the psychopathology of schizophrenia spectrum disorders (SSD). We separated SLEs into independent (iSLEs, unlikely influenced by one's behavior) and dependent (dSLEs, likely influenced by one's behavior). Stress-diathesis and stress generation models were evaluated for the relationship between total, i- and d- SLEs and the severity of positive, negative, and depressive symptoms in participants with SSD. Participants with SSD (n = 286; 196 males; age = 37.5 ± 13.5 years) and community controls (n = 121; 83 males; 35.4 ± 13.9 years) completed self-report of lifetime negative total, i- and d- SLEs. Participants with SSD reported a significantly higher number of total SLEs compared to controls (B = 1.11, p = 6.4 × 10-6). Positive symptom severity was positively associated with the total number of SLEs (ß = 0.20, p = 0.001). iSLEs (ß = 0.11, p = 0.09) and dSLEs (ß = 0.21, p = 0.0006) showed similar association with positive symptoms (p = 0.16) suggesting stress-diathesis effects. Negative symptom severity was negatively associated with the number of SLEs (ß = -0.19, p = 0.003) and dSLEs (ß = -0.20, p = 0.001) but not iSLEs (ß = -0.04, p = 0.52), suggesting stress generation effects. Depressive symptom severity was positively associated with SLEs (ß = 0.34, p = 1.0 × 10-8), and the association was not statistically stronger for dSLEs (ß = 0.33, p = 2.7 × 10-8) than iSLEs (ß = 0.21, p = 0.0006), p = 0.085, suggesting stress-diathesis effects. The SLE - symptom relationships in SSD may be attributed to stress generation or stress-diathesis, depending on symptom domain. Findings call for a domain-specific approach to clinical intervention for SLEs in SSD.

APOE4 poses opposite effects of plasma LDL on white matter integrity in older adults.

INTRODUCTION: APOE4 is a strong genetic risk factor of Alzheimer's disease and is associated with changes in metabolism. However, the interactive relationship between APOE4 and plasma metabolites on the brain remains largely unknown. MEHODS: In the UK Biobank, we investigated the moderation effects of APOE4 on the relationship between 249 plasma metabolites derived from nuclear magnetic resonance spectroscopy on whole-brain white matter integrity, measured by fractional anisotropy using diffusion magnetic resonance imaging. RESULTS: The increase in the concentration of metabolites, mainly LDL and VLDL, is associated with a decrease in white matter integrity (b= -0.12, CI= [-0.14, -0.10]) among older APOE4 carriers, whereas an increase (b= 0.05, CI= [0.04, 0.07]) among non-carriers, implying a significant moderation effect of APOE4 (b= -0.18, CI= [-0.20,-0.15]). DISCUSSION: The results suggest that lipid metabolism functions differently in APOE4 carriers compared to non-carriers, which may inform the development of targeted interventions for APOE4 carriers to mitigate cognitive decline.

Quantitative characterizations of visual fibrousness in meat analogues using automated image analysis.

A desirable quality of plant-based meat analogues is to resemble the fibrous structure of cooked muscle meat. While texture analysis can characterize fibrous structures mechanically, assessment of visual fibrous structures remains subjective. Quantitative assessment of visual fibrous structures of meat analogues relies on expert knowledge, is resource-intensive, and time-consuming. In this study, a novel image-based method (Fiberlyzer) is developed to provide automated, quantitative, and standardized assessment of visual fibrousness of meat analogues. The Fiberlyzer method segments fibrous regions from 2D images and extracts fiber shape features to characterize the fibrous structure of meat analogues made from mung bean, soy, and pea protein. The computed fiber scores (the ratio between fiber length and width) demonstrate a strong correlation with expert panel evaluations, particularly on a per-formulation basis (r2 = 0.93). Additionally, the Fiberlyzer method generates fiber shape features including fiber score, fiber area, and the number of fiber branches, facilitating comparisons of structural similarity between meat analogue samples and cooked chicken meat as a benchmark. With a simple measurement setup and user-friendly interface, the Fiberlyzer method can become a standard tool integrated into formulation development, quality control, and production routines of plant-based meat analogue. This method offers rapid, cheap, and standardized quantification of visual fibrousness, minimizing the need for expert knowledge in the process of quality control.

Resting-State Functional Connectivity Explained Psychotic-like Experiences in the General Population and Partially Generalized to Patients and Relatives.

Background: Psychotic-like experiences (PLEs) are considered the subclinical portion of the psychosis continuum. Research suggests that there are resting-state functional connectivity (rsFC) substrates of PLEs, yet it is unclear if the same substrates underlie more severe psychosis. Here, to our knowledge, we report the first study to build a cross-validated rsFC model of PLEs in a large community sample and directly test its ability to explain psychosis in an independent sample of patients with psychosis and their relatives. Methods: Resting-state FC of 855 healthy young adults from the WU-Minn Human Connectome Project (HCP) was used to predict PLEs with elastic net. An rsFC composite score based on the resulting model was correlated with psychotic traits and symptoms in 118 patients with psychosis, 71 nonpsychotic first-degree relatives, and 45 healthy control subjects from the psychosis HCP. Results: In the HCP, the cross-validated model explained 3.3% of variance in PLEs. Predictive connections spread primarily across the default, frontoparietal, cingulo-opercular, and dorsal attention networks. The model partially generalized to a younger, but not older, subsample in the psychosis HCP, explaining two measures of positive/disorganized psychotic traits (the Structured Interview for Schizotypy: ß = 0.25, pone-tailed = .027; the Schizotypy Personality Questionnaire positive factor: ß = 0.14, pone-tailed = .041). However, it did not differentiate patients from relatives and control subjects or explain psychotic symptoms in patients. Conclusions: Some rsFC substrates of PLEs are shared across the psychosis continuum. However, explanatory power was modest, and generalization was partial. It is equally important to understand shared versus distinct rsFC variances across the psychosis continuum.

Elevated blood pressure accelerates white matter brain aging among late middle-aged women: a Mendelian Randomization study in the UK Biobank.

BACKGROUND: Elevated blood pressure (BP) is a modifiable risk factor associated with cognitive impairment and cerebrovascular diseases. However, the causal effect of BP on white matter brain aging remains unclear. METHODS: In this study, we focused on N  = 228 473 individuals of European ancestry who had genotype data and clinical BP measurements available (103 929 men and 124 544 women, mean age = 56.49, including 16 901 participants with neuroimaging data available) collected from UK Biobank (UKB). We first established a machine learning model to compute the outcome variable brain age gap (BAG) based on white matter microstructure integrity measured by fractional anisotropy derived from diffusion tensor imaging data. We then performed a two-sample Mendelian randomization analysis to estimate the causal effect of BP on white matter BAG in the whole population and subgroups stratified by sex and age brackets using two nonoverlapping data sets. RESULTS: The hypertension group is on average 0.31 years (95% CI = 0.13-0.49; P  < 0.0001) older in white matter brain age than the nonhypertension group. Women are on average 0.81 years (95% CI = 0.68-0.95; P  < 0.0001) younger in white matter brain age than men. The Mendelian randomization analyses showed an overall significant positive causal effect of DBP on white matter BAG (0.37 years/10 mmHg, 95% CI 0.034-0.71, P  = 0.0311). In stratified analysis, the causal effect was found most prominent among women aged 50-59 and aged 60-69. CONCLUSION: High BP can accelerate white matter brain aging among late middle-aged women, providing insights on planning effective control of BP for women in this age group.

Deciphering the causal relationship between blood pressure and regional white matter integrity: A two-sample Mendelian randomization study.

Elevated arterial blood pressure (BP) is a common risk factor for cerebrovascular and cardiovascular diseases, but no causal relationship has been established between BP and cerebral white matter (WM) integrity. In this study, we performed a two-sample Mendelian randomization (MR) analysis with individual-level data by defining two nonoverlapping sets of European ancestry individuals (genetics-exposure set: N = 203,111; mean age = 56.71 years, genetics-outcome set: N = 16,156; mean age = 54.61 years) from UK Biobank to evaluate the causal effects of BP on regional WM integrity, measured by fractional anisotropy of diffusion tensor imaging. Two BP traits: systolic and diastolic blood pressure were used as exposures. Genetic variant was carefully selected as instrumental variable (IV) under the MR analysis assumptions. We existing large-scale genome-wide association study summary data for validation. The main method used was a generalized version of inverse-variance weight method while other MR methods were also applied for consistent findings. Two additional MR analyses were performed to exclude the possibility of reverse causality. We found significantly negative causal effects (FDR-adjusted p < .05; every 10 mmHg increase in BP leads to a decrease in FA value by .4% ~ 2%) of BP traits on a union set of 17 WM tracts, including brain regions related to cognitive function and memory. Our study extended the previous findings of association to causation for regional WM integrity, providing insights into the pathological processes of elevated BP that might chronically alter the brain microstructure in different regions.

Quantitative analysis of 3D food printing layer extrusion accuracy: Contextualizing automated image analysis with human evaluations: Quantifying 3D food printing accuracy.

3D food printing can customize food appearance, textures, and flavors to tailor to specific consumer needs. Current 3D food printing depends on trial-and-error optimization and experienced printer operators, which limits the adoption of the technology by general consumers. Digital image analysis can be applied to monitor the 3D printing process, quantify printing errors, and guide optimization of the printing process. We here propose an automated printing accuracy assessment tool based on layer-wise image analysis. Printing inaccuracies are quantified based on over- and under-extrusion with reference to the digital design. The measured defects are compared to human evaluations via an online survey to contextualize the errors and identify the most useful measurements to improve printing efficiency. The survey participants marked oozing and over-extrusion as inaccurate printing which matched the results obtained from automated image analysis. Although under-extrusion was also quantified by the more sensitive digital tool, the survey participants did not perceive consistent under-extrusion as inaccurate printing. The contextualized digital assessment tool provides useful estimations of printing accuracy and corrective actions to avoid printing defects. The digital monitoring approach may accelerate the consumer adoption of 3D food printing by improving the perceived accuracy and efficiency of customized food printing.

Evidence of Neurovascular Water Exchange and Endothelial Vascular Dysfunction in Schizophrenia: An Exploratory Study.

BACKGROUND AND HYPOTHESIS: Mounting evidence supports cerebrovascular contributions to schizophrenia spectrum disorder (SSD) but with unknown mechanisms. The blood-brain barrier (BBB) is at the nexus of neural-vascular exchanges, tasked with regulating cerebral homeostasis. BBB abnormalities in SSD, if any, are likely more subtle compared to typical neurological insults and imaging measures that assess large molecule BBB leakage in major neurological events may not be sensitive enough to directly examine BBB abnormalities in SSD. STUDY DESIGN: We tested the hypothesis that neurovascular water exchange (Kw) measured by non-invasive diffusion-prepared arterial spin label MRI (n = 27 healthy controls [HC], n = 32 SSD) is impaired in SSD and associated with clinical symptoms. Peripheral vascular endothelial health was examined by brachial artery flow-mediated dilation (n = 44 HC, n = 37 SSD) to examine whether centrally measured Kw is related to endothelial functions. STUDY RESULTS: Whole-brain average Kw was significantly reduced in SSD (P = .007). Exploratory analyses demonstrated neurovascular water exchange reductions in the right parietal lobe, including the supramarginal gyrus (P = .002) and postcentral gyrus (P = .008). Reduced right superior corona radiata (P = .001) and right angular gyrus Kw (P = .006) was associated with negative symptoms. Peripheral endothelial function was also significantly reduced in SSD (P = .0001). Kw in 94% of brain regions in HC positively associated with peripheral endothelial function, which was not observed in SSD, where the correlation was inversed in 52% of brain regions. CONCLUSIONS: This study provides initial evidence of neurovascular water exchange abnormalities, which appeared clinically associated, especially with negative symptoms, in schizophrenia.

Ancestral, Pregnancy, and Negative Early-Life Risks Shape Children's Brain (Dis)similarity to Schizophrenia.

BACKGROUND: Familial, obstetric, and early-life environmental risks for schizophrenia spectrum disorder (SSD) alter normal cerebral development, leading to the formation of characteristic brain deficit patterns prior to onset of symptoms. We hypothesized that the insidious effects of these risks may increase brain similarity to adult SSD deficit patterns in prepubescent children. METHODS: We used data collected by the Adolescent Brain Cognitive Development (ABCD) Study (N = 8940, age = 9.9 ± 0.1 years, 4307/4633 female/male), including 727 (age = 9.9 ± 0.1 years, 351/376 female/male) children with family history of SSD, to evaluate unfavorable cerebral effects of ancestral SSD history, pre/perinatal environment, and negative early-life environment. We used a regional vulnerability index to measure the alignment of a child's cerebral patterns with the adult SSD pattern derived from a large meta-analysis of case-control differences. RESULTS: In children with a family history of SSD, the regional vulnerability index captured significantly more variance in ancestral history than traditional whole-brain and regional brain measurements. In children with and without family history of SSD, the regional vulnerability index also captured more variance associated with negative pre/perinatal environment and early-life experiences than traditional brain measurements. CONCLUSIONS: In summary, in a cohort in which most children will not develop SSD, familial, pre/perinatal, and early developmental risks can alter brain patterns in the direction observed in adult patients with SSD. Individual similarity to adult SSD patterns may provide an early biomarker of the effects of genetic and developmental risks on the brain prior to psychotic or prodromal symptom onset.

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease.

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

Depression, stress and regional cerebral blood flow.

Decreased cerebral blood flow (CBF) may be an important mechanism associated with depression. In this study we aimed to determine if the association of CBF and depression is dependent on current level of depression or the tendency to experience depression over time (trait depression), and if CBF is influenced by depression-related factors such as stressful life experiences and antidepressant medication use. CBF was measured in 254 participants from the Amish Connectome Project (age 18-76, 99 men and 154 women) using arterial spin labeling. All participants underwent assessment of symptoms of depression measured with the Beck Depression Inventory and Maryland Trait and State Depression scales. Individuals diagnosed with a unipolar depressive disorder had significantly lower average gray matter CBF compared to individuals with no history of depression or to individuals with a history of depression that was in remission at time of study. Trait depression was significantly associated with lower CBF, with the associations strongest in cingulate gyrus and frontal white matter. Use of antidepressant medication and more stressful life experiences were also associated with significantly lower CBF. Resting CBF in specific brain regions is associated with trait depression, experience of stressful life events, and current antidepressant use, and may provide a valuable biomarker for further studies.

Comparing the functional neuroanatomy of proactive and reactive control between patients with schizophrenia and healthy controls.

Cognitive control deficits are associated with impaired executive functioning in schizophrenia. The Dual Mechanisms of Control framework suggests that proactive control requires sustained dorsolateral prefrontal activity, whereas reactive control marshals a larger network. However, primate studies suggest these processes are maintained by dual-encoding regions. To distinguish between these theories, we compared the distinctiveness of proactive and reactive control functional neuroanatomy. In a reanalysis of data from a previous study, 47 adults with schizophrenia and 56 controls completed the Dot Pattern Expectancy task during an fMRI scan examining proactive and reactive control in frontoparietal and medial temporal regions. Areas suggesting specialized control or between-group differences were tested for association with symptoms and task performance. Elastic net models additionally explored these areas' predictive abilities regarding performance. Most regions were active in both reactive and proactive control. However, evidence of specialized proactive control was found in the left middle and superior frontal gyri. Control participants showed greater proactive control in the left middle and right inferior frontal gyri. Elastic net models moderately predicted task performance and implicated various frontal gyri regions in control participants, with additional involvement of anterior cingulate and posterior parietal regions for reactive control. Elastic nets for patient participants implicated the inferior and superior frontal gyri, and posterior parietal lobe. Specialized cognitive control was unassociated with either performance or schizophrenia symptomatology. Future work is needed to clarify the distinctiveness of proactive and reactive control, and its role in executive deficits in severe psychopathology.

Association between brain similarity to severe mental illnesses and comorbid cerebral, physical, and cognitive impairments.

Severe mental illnesses (SMIs) are often associated with compromised brain health, physical comorbidities, and cognitive deficits, but it is incompletely understood whether these comorbidities are intrinsic to SMI pathophysiology or secondary to having SMIs. We tested the hypothesis that cerebral, cardiometabolic, and cognitive impairments commonly observed in SMIs can be observed in non-psychiatric individuals with SMI-like brain patterns of deviation as seen on magnetic resonance imaging. 22,883 participants free of common neuropsychiatric conditions from the UK Biobank (age = 63.4 ± 7.5 years, range = 45-82 years, 50.9% female) were split into discovery and replication samples. The regional vulnerability index (RVI) was used to quantify each participant's respective brain similarity to meta-analytical patterns of schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder in gray matter thickness, subcortical gray matter volume, and white matter integrity. Cluster analysis revealed five clusters with distinct RVI profiles. Compared with a cluster with no RVI elevation, a cluster with RVI elevation across all SMIs and brain structures showed significantly higher volume of white matter hyperintensities (Cohen's d = 0.59, pFDR < 10-16), poorer cardiovascular (Cohen's d = 0.30, pFDR < 10-16) and metabolic (Cohen's d = 0.12, pFDR = 1.3 × 10-4) health, and slower speed of information processing (|Cohen's d| = 0.11-0.17, pFDR = 1.6 × 10-3-4.6 × 10-8). This cluster also had significantly higher level of C-reactive protein and alcohol use (Cohen's d = 0.11 and 0.28, pFDR = 4.1 × 10-3 and 1.1 × 10-11). Three other clusters with respective RVI elevation in gray matter thickness, subcortical gray matter volume, and white matter integrity showed intermediate level of white matter hyperintensities, cardiometabolic health, and alcohol use. Our results suggest that cerebral, physical, and cognitive impairments in SMIs may be partly intrinsic via shared pathophysiological pathways with SMI-related brain anatomical changes.

Frontal white matter association with sleep quality and the role of stress.

An important measure of brain health is the integrity of white matter connectivity structures that link brain regions. Studies have found an association between poorer sleep quality and decreased white matter integrity. Stress is among the strongest predictors of sleep quality. This study aimed to evaluate the association between sleep quality and white matter and to test if the relationship persisted after accounting for stress. White matter microstructures were measured by diffusion tensor imaging in a population of Old Order Amish/Mennonite (N = 240). Sleep quality was determined by the Pittsburgh Sleep Quality Index. Current stress levels were measured by the perceived stress scale. Exposure to lifetime stress was measured by the lifetime stressor inventory. Microstructures of four white matter tracts: left and right anterior limbs of internal capsule, left anterior corona radiata, and genu of corpus callosum were significantly correlated with sleep quality (all p ≤ 0.001). The current stress level was a significant predictor of sleep quality (p ≤ 0.001) while lifetime stress was not. PSQI remained significantly associated with white matter integrity in these frontal tracts (all p < 0.01) after accounting for current stress and lifetime stress, while current and lifetime stress were not significant predictors of white matter in any of the four models. Sleep quality did not have any substantial mediation role between stress and white matter integrity. Sleep quality was significantly associated with several frontal white matter tracts that connect brain structures important for sleep regulation regardless of current or past stress levels.

Thalamocortical connectivity and its relationship with symptoms and cognition across the psychosis continuum.

BACKGROUND: Coordination between the thalamus and cortex is necessary for efficient processing of sensory information and appears disrupted in schizophrenia. The significance of this disrupted coordination (i.e. thalamocortical dysconnectivity) to the symptoms and cognitive deficits of schizophrenia is unclear. It is also unknown whether similar dysconnectivity is observed in other forms of psychotic psychopathology and associated with familial risk for psychosis. Here we examine the relevance of thalamocortical connectivity to the clinical symptoms and cognition of patients with psychotic psychopathology, their first-degree biological relatives, and a group of healthy controls. METHOD: Patients with a schizophrenia-spectrum diagnosis (N = 100) or bipolar disorder with a history of psychosis (N = 33), their first-degree relatives (N = 73), and a group of healthy controls (N = 43) underwent resting functional MRI in addition to clinical and cognitive assessments as part of the Psychosis Human Connectome Project. A bilateral mediodorsal thalamus seed-based analysis was used to measure thalamocortical connectivity and test for group differences, as well as associations with symptomatology and cognition. RESULTS: Reduced connectivity from mediodorsal thalamus to insular, orbitofrontal, and cerebellar regions was seen in schizophrenia. Across groups, greater symptomatology was related to less thalamocortical connectivity to the left middle frontal gyrus, anterior cingulate, right insula, and cerebellum. Poorer cognition was related to less thalamocortical connectivity to bilateral insula. Analyses revealed similar patterns of dysconnectivity across patient groups and their relatives. CONCLUSIONS: Reduced thalamo-prefrontal-cerebellar and thalamo-insular connectivity may contribute to clinical symptomatology and cognitive deficits in patients with psychosis as well as individuals with familial risk for psychotic psychopathology.

The causal effect of HbA1c on white matter brain aging by two-sample Mendelian randomization analysis.

Background: Poor glycemic control with elevated levels of hemoglobin A1c (HbA1c) is associated with increased risk of cognitive impairment, with potentially varying effects between sexes. However, the causal impact of poor glycemic control on white matter brain aging in men and women is uncertain. Methods: We used two nonoverlapping data sets from UK Biobank cohort: gene-outcome group (with neuroimaging data, (N = 15,193; males/females: 7,101/8,092)) and gene-exposure group (without neuroimaging data, (N = 279,011; males/females: 122,638/156,373)). HbA1c was considered the exposure and adjusted "brain age gap" (BAG) was calculated on fractional anisotropy (FA) obtained from brain imaging as the outcome, thereby representing the difference between predicted and chronological age. The causal effects of HbA1c on adjusted BAG were studied using the generalized inverse variance weighted (gen-IVW) and other sensitivity analysis methods, including Mendelian randomization (MR)-weighted median, MR-pleiotropy residual sum and outlier, MR-using mixture models, and leave-one-out analysis. Results: We found that for every 6.75 mmol/mol increase in HbA1c, there was an increase of 0.49 (95% CI = 0.24, 0.74; p-value = 1.30 × 10-4) years in adjusted BAG. Subgroup analyses by sex and age revealed significant causal effects of HbA1c on adjusted BAG, specifically among men aged 60-73 (p-value = 2.37 × 10-8). Conclusion: Poor glycemic control has a significant causal effect on brain aging, and is most pronounced among older men aged 60-73 years, which provides insights between glycemic control and the susceptibility to age-related neurodegenerative diseases.