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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). We tested the direct and additive effects of SMI and CMD effects on accelerated brain aging in the N = 1,618 (604 M/1,014 F, average age = 63.53 ± 7.38) subjects with SMI and N = 11,849 (5,719 M/6,130 F; 64.42 ± 7.38) controls from the UK Biobank. Subjects were subdivided based on diagnostic status: SMI+/CMD+ (N = 665), SMI+/CMD- (N = 964), SMI-/CMD+ (N = 3,765), SMI-/CMD- (N = 8,083). SMI (F = 40.47, p = 2.06 × 10

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. We evaluated RVI as a measure sensitive to schizophrenia‐specific neuroanatomical deficits and symptoms and studied the timeline of deficit formations in: early (≤5 years since diagnosis, N = 45, age = 28.8 ± 8.5); intermediate (6–20 years, N = 30, age 43.3 ± 8.6); and chronic (21+ years, N = 44, age = 52.5 ± 5.2) patients and healthy controls (N = 76, age = 38.6 ± 12.4). All RVIs were significantly elevated in patients compared to controls, with the multimodal RVI showing the largest effect size, followed by cortical, white matter and subcortical RVIs (d = 1.57, 1.23, 1.09, and 0.61, all p, We developed the regional vulnerability index (RVI) to quantify individual similarity to the expected schizophrenia deficits patterns derived from large‐scale meta‐analyses performed by Enhancing Neuro Imaging Genetics Meta‐Analysis (ENIGMA) consortium. RVIs for cortical, subcortical, and white matter measurements and a cross‐modality RVI showed significant association with illness duration, cognitive deficits and symptoms. The similarity to expected disorder patterns captured by RVI may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter the formation of neuroanatomical deficits.

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. We observed that hypobaric exposure led to a significant rise in white matter cerebral blood flow (CBF) 24 hr postexposure that remained elevated, albeit not significantly, at 72 hr. No significant changes were observed in structural measurements or gray matter CBF. Subjects with higher baseline concentrations of neurochemicals associated with neuroprotection and maintenance of normal white matter physiology (glutathione, N‐acetylaspartate, glutamate/glutamine) showed proportionally less white matter CBF changes. Our findings suggest that discrete hypobaric exposure may provide a model to study white matter injury associated with occupational hypobaric exposure.

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. DTI protocol included five b = 0 and 60 diffusion-sensitized gradient directions (b = 1,000 s/mm2 ). In-house DTI QA protocol data was acquired weekly using a uniform phantom; factor analysis was used to distil into two orthogonal QA factors related to: SNR and FA. They were used as site-specific covariates to perform mega-analytic data aggregation. The effect size of patient-control differences was compared to these reported by the enhancing neuro imaging genetics meta-analysis (ENIGMA) consortium before and after regressing QA variance. Impact of MP-PCA filtering was evaluated likewise. QA-factors explained ∼3-4% variance in the whole-brain average FA values per site. Regression of QA factors improved the effect size of schizophrenia on whole brain average FA values-from Cohen's d = .53 to .57-and improved the agreement between the regional pattern of FA differences observed in this study versus ENIGMA from r = .54 to .70. Application of MP-PCA-denoising further improved the agreement to r = .81. Regression of methodological variances captured by routine QA and advanced denoising that led to a better agreement with a large mega-analytic study.

Objective To assess the association between peripheral lipid/fat profiles and cerebral gray matter (GM) and white matter (WM) in healthy Old Order Amish (OOA). Methods Blood lipids, abdominal adiposity, liver lipid contents, and cerebral microstructure were assessed in OOA (N = 64, 31 males/33 females, ages 18-77). Orthogonal factors were extracted from lipid and imaging adiposity measures. GM assessment used the Human Connectome Project protocol to measure whole-brain average cortical thickness. Diffusion-weighted imaging was used to derive WM fractional anisotropy and kurtosis anisotropy measurements. Results Lipid/fat measures were captured by three orthogonal factors explaining 80% of the variance. Factor one loaded on cholesterol and/or low-density lipoprotein cholesterol measurements; factor two loaded on triglyceride/liver measurements; and factor three loaded on abdominal fat measurements. A two-stage regression including age/sex (first stage) and the three factors (second stage) examined the peripheral lipid/fat effects. Factors two and three significantly contributed to WM measures after Bonferroni corrections (P

Introduction Quantitative longitudinal magnetic resonance imaging and spectroscopy (MRI/S) is used to assess progress of brain disorders and treatment effects. Understanding the significance of MRI/S changes requires knowledge of the inherent technical and physiological consistency of these measurements. This longitudinal study examined the variance and reproducibility of commonly used quantitative MRI/S measurements in healthy subjects while controlling physiological and technical parameters. Methods Twenty-five subjects were imaged three times over 5 days on a Siemens 3T Verio scanner equipped with a 32-channel phase array coil. Structural (T1, T2-weighted, and diffusion-weighted imaging) and physiological (pseudocontinuous arterial spin labeling, proton magnetic resonance spectroscopy) data were collected. Consistency of repeated images was evaluated with mean relative difference, mean coefficient of variation, and intraclass correlation (ICC). Finally, a “reproducibility rating” was calculated based on the number of subjects needed for a 3% and 10% difference. Results Structural measurements generally demonstrated excellent reproducibility (ICCs 0.872–0.998) with a few exceptions. Moderate-to-low reproducibility was observed for fractional anisotropy measurements in fornix and corticospinal tracts, for cortical gray matter thickness in the entorhinal, insula, and medial orbitofrontal regions, and for the count of the periependymal hyperintensive white matter regions. The reproducibility of physiological measurements ranged from excellent for most of the magnetic resonance spectroscopy measurements to moderate for permeability-diffusivity coefficients in cingulate gray matter to low for regional blood flow in gray and white matter. Discussion This study demonstrates a high degree of longitudinal consistency across structural and physiological measurements in healthy subjects, defining the inherent variability in these commonly used sequences. Additionally, this study identifies those areas where caution should be exercised in interpretation. Understanding this variability can serve as the basis for interpretation of MRI/S data in the assessment of neurological disorders and treatment effects.