Prenatal tobacco exposure on brain morphometry partially mediated poor cognitive performance in preadolescent children.

Objectives: To evaluate whether prenatal tobacco exposure (PTE) is related to poorer cognitive performance, abnormal brain morphometry, and whether poor cognitive performance is mediated by PTE-related structural brain differences.

Methods: The Adolescent Brain Cognitive Development study dataset was used to compare structural MRI data and neurocognitive (NIH Toolbox) scores in 9-to-10-year-old children with (n=620) and without PTE (n=10,989). We also evaluated whether PTE effects on brain morphometry mediated PTE effects on neurocognitive scores.

Neuronal and Glial Metabolite Abnormalities in Participants With Persistent Neuropsychiatric Symptoms After COVID-19: A Brain Proton Magnetic Resonance Spectroscopy Study.

Background: The aim of this study was to determine whether neurometabolite abnormalities indicating neuroinflammation and neuronal injury are detectable in individuals post-coronavirus disease 2019 (COVID-19) with persistent neuropsychiatric symptoms.

Methods: All participants were studied with proton magnetic resonance spectroscopy at 3 T to assess neurometabolite concentrations (point-resolved spectroscopy, relaxation time/echo time = 3000/30 ms) in frontal white matter (FWM) and anterior cingulate cortex-gray matter (ACC-GM). Participants also completed the National Institutes of Health Toolbox cognition and motor batteries and selected modules from the Patient-Reported Outcomes Measurement Information System.

Quantifying the Neuropsychiatric Symptoms in Post-Acute Sequelae of COVID-19 (PASC) using the NIH Toolbox and PROMIS.

Objective: To quantify neuropsychiatric symptoms reported by individuals with Post-Acute Sequelae of COVID-19 (PASC) using the NIH Toolbox for Assessment of Neurological and Behavioral Function (NIHTB) and Patient-Reported Outcomes Measurement Information System (PROMIS).

Methods: 30 PASC (20 women, 21-63 years) and 27 control (16 women, 25-68 years) participants completed three NIHTB batteries and selected PROMIS tests. Group differences on fully corrected T-scores were evaluated using analysis of covariance and Cohen's effect sizes.

Ongoing oxidative stress in individuals with post-acute sequelae of COVID-19.

Objectives: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection is associated with lower plasma glutathione (GSH) levels due to oxidative stress. However, plasma levels may not reflect brain GSH levels. Individuals with post-acute sequelae of COVID-19 (PASC) have a higher prevalence of cognitive fatigue, which might be related to altered brain γ-aminobutyric-acid (GABA) levels.

Changes in Brain Activation Patterns During Working Memory Tasks in People With Post-COVID Condition and Persistent Neuropsychiatric Symptoms.

Background And Objectives: Post-COVID condition (PCC) is common and often involves neuropsychiatric symptoms. This study aimed to use blood oxygenation level-dependent fMRI (BOLD-fMRI) to assess whether participants with PCC had abnormal brain activation during working memory (WM) and whether the abnormal brain activation could predict cognitive performance, motor function, or psychiatric symptoms.

Methods: The participants with PCC had documented coronavirus disease 2019 (COVID-19) at least 6 weeks before enrollment.

Abnormal brain diffusivity in participants with persistent neuropsychiatric symptoms after COVID-19.

Objectives: We aimed to compare brain white matter integrity in participants with post-COVID-19 conditions (PCC) and healthy controls.

Methods: We compared cognitive performance (NIH Toolbox), psychiatric symptoms and diffusion tensor imaging (DTI) metrics between 23 PCC participants and 24 controls. Fractional anisotropy (FA), axial (AD), radial (RD), and mean (MD) diffusivities were measured in 9 white matter tracts and 6 subcortical regions using MRICloud.

The additive impact of cardio-metabolic disorders and psychiatric illnesses on accelerated brain aging.

Severe mental illnesses (SMI) including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD) elevate accelerated brain aging risks. Cardio-metabolic disorders (CMD) are common comorbidities in SMI and negatively impact brain health. We validated a linear quantile regression index (QRI) approach against the machine learning "BrainAge" index in an independent SSD cohort (N = 206).

White matter brain aging in relationship to schizophrenia and its cognitive deficit.

We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronological age. Through this approach, we translated multivariate white matter imaging features into an age-scaled metric and used it to test the temporal trends of accelerated aging-related white matter deficit in SZ and its association with the cognition.

Comparison of regional brain deficit patterns in common psychiatric and neurological disorders as revealed by big data.

Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. The Regional Vulnerability Index (RVI) was developed toquantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We tested the specificity of the RVI approach for major depressive disorder (MDD) and Alzheimer's disease (AD) in a large epidemiological sample of UK Biobank (UKBB) participants (N = 19,393; 9138 M/10,255F; age = 64.

Allostatic Load Effects on Cortical and Cognitive Deficits in Essentially Normotensive, Normoweight Patients with Schizophrenia.

Reduced cortical gray matter integrity and cognitive abilities are among core deficits in schizophrenia. We hypothesized that higher allostatic load (AL) that accounts for exposure to chronic stress is a contributor to structural and cognitive deficits in schizophrenia. One hundred and sixty-seven schizophrenia patients who were on average with normal weight, normal systolic, and diastolic blood pressure and 72 healthy controls were enrolled in the study.

A White Matter Connection of Schizophrenia and Alzheimer's Disease.

Schizophrenia (SZ) is a severe psychiatric illness associated with an elevated risk for developing Alzheimer's disease (AD). Both SZ and AD have white matter abnormalities and cognitive deficits as core disease features. We hypothesized that aging in SZ patients may be associated with the development of cerebral white matter deficit patterns similar to those observed in AD.

Translating ENIGMA schizophrenia findings using the regional vulnerability index: Association with cognition, symptoms, and disease trajectory.

Patients with schizophrenia have patterns of brain deficits including reduced cortical thickness, subcortical gray matter volumes, and cerebral white matter integrity. We proposed the regional vulnerability index (RVI) to translate the results of Enhancing Neuro Imaging Genetics Meta-Analysis studies to the individual level. We calculated RVIs for cortical, subcortical, and white matter measurements and a multimodality RVI.

ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research.

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome.

Effects of ketamine and midazolam on resting state connectivity and comparison with ENIGMA connectivity deficit patterns in schizophrenia.

Subanesthetic administration of ketamine is a pharmacological model to elicit positive and negative symptoms of psychosis in healthy volunteers. We used resting-state pharmacological functional MRI (rsPhfMRI) to identify cerebral networks affected by ketamine and compared them to the functional connectivity (FC) in schizophrenia. Ketamine can produce sedation and we contrasted its effects with the effects of the anxiolytic drug midazolam.

White Matter in Schizophrenia Treatment Resistance.

Objective: Failure of antipsychotic medications to resolve symptoms in patients with schizophrenia creates a clinical challenge that is known as treatment resistance. The causes of treatment resistance are unknown, but it is associated with earlier age at onset and more severe cognitive deficits. The authors tested the hypothesis that white matter deficits that are involved in both neurodevelopment and severity of cognitive deficits in schizophrenia are associated with a higher risk of treatment resistance.

White matter and hypoxic hypobaria in humans.

Occupational exposure to hypobaria (low atmospheric pressure) is a risk factor for reduced white matter integrity, increased white matter hyperintensive burden, and decline in cognitive function. We tested the hypothesis that a discrete hypobaric exposure will have a transient impact on cerebral physiology. Cerebral blood flow, fractional anisotropy of water diffusion in cerebral white matter, white matter hyperintensity volume, and concentrations of neurochemicals were measured at baseline and 24 hr and 72 hr postexposure in N = 64 healthy aircrew undergoing standard US Air Force altitude chamber training and compared to N = 60 controls not exposed to hypobaria.

Miniature pig magnetic resonance spectroscopy model of normal adolescent brain development.

Background: We are developing the miniature pig (Sus scrofa domestica), an in-vivo translational, gyrencephalic model for brain development, as an alternative to laboratory rodents/non-human primates. We analyzed longitudinal changes in adolescent pigs using proton magnetic resonance spectroscopy (H-MRS) and examined the relationship with white matter (WM) integrity derived from diffusion weighted imaging (DWI).

New Method: Twelve female Sinclair pigs underwent three imaging/spectroscopy sessions every 23.

Miniature pig model of human adolescent brain white matter development.

Background: Neuroscience research in brain development and disorders can benefit from an in vivo animal model that portrays normal white matter (WM) development trajectories and has a sufficiently large cerebrum for imaging with human MRI scanners and protocols.

New Method: Twelve three-month-old Sinclair™ miniature pigs (Sus scrofa domestica) were longitudinally evaluated during adolescent development using advanced diffusion weighted imaging (DWI) focused on cerebral WM. Animals had three MRI scans every 23.

Integration of routine QA data into mega-analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies.

A novel mega-analytical approach that reduced methodological variance was evaluated using a multisite diffusion tensor imaging (DTI) fractional anisotropy (FA) data by comparing white matter integrity in people with schizophrenia to controls. Methodological variance was reduced through regression of variance captured from quality assurance (QA) and by using Marchenko-Pastur Principal Component Analysis (MP-PCA) denoising. N = 192 (119 patients/73 controls) data sets were collected at three sites equipped with 3T MRI systems: GE MR750, GE HDx, and Siemens Trio.