The Relationship between Intelligence and Anxiety: An Association with Subcortical White Matter Metabolism

We have demonstrated in a previous study that a high degree of worry in patients with generalized anxiety disorder (GAD) correlates positively with intelligence and that a low degree of worry in healthy subjects correlates positively with intelligence. We have also shown that both worry and intelligence exhibit an inverse correlation with certain metabolites in the subcortical white matter. Here we re-examine the relationships among generalized anxiety, worry, intelligence, and subcortical white matter metabolism in an extended sample. Results from the original study were combined with results from a second study to create a sample comprised of 26 patients with GAD and 18 healthy volunteers. Subjects were evaluated using the Penn State Worry Questionnaire, the Wechsler Brief intelligence quotient (IQ) assessment, and proton magnetic resonance spectroscopic imaging (1H-MRSI) to measure subcortical white matter metabolism of choline and related compounds (CHO). Patients with GAD exhibited higher IQ’s and lower metabolite concentrations of CHO in the subcortical white matter in comparison to healthy volunteers. When data from GAD patients and healthy controls were combined, relatively low CHO predicted both relatively higher IQ and worry scores. Relatively high anxiety in patients with GAD predicted high IQ whereas relatively low anxiety in controls also predicted high IQ. That is, the relationship between anxiety and intelligence was positive in GAD patients but inverse in healthy volunteers. The collective data suggest that both worry and intelligence are characterized by depletion of metabolic substrate in the subcortical white matter and that intelligence may have co-evolved with worry in humans

Correlations between Diffusion Tensor Imaging (DTI) and Magnetic Resonance Spectroscopy (1H MRS) in schizophrenic patients and normal controls

<p>Abstract</p> <p>Background</p> <p>Evidence suggests that white matter integrity may play an underlying pathophysiological role in schizophrenia. N-acetylaspartate (NAA), as measured by Magnetic Resonance Spectroscopy (MRS), is a neuronal marker and is decreased in white matter lesions and regions of axonal loss. It has also been found to be reduced in the prefrontal and temporal regions in patients with schizophrenia. Diffusion Tensor Imaging (DTI) allows one to measure the orientations of axonal tracts as well as the coherence of axonal bundles. DTI is thus sensitive to demyelination and other structural abnormalities. DTI has also shown abnormalities in these regions.</p> <p>Methods</p> <p>MRS and DTI were obtained on 42 healthy subjects and 40 subjects with schizophrenia. The data was analyzed using regions of interests in the Dorso-Lateral Prefrontal white matter, Medial Temporal white matter and Occipital white matter using both imaging modalities.</p> <p>Results</p> <p>NAA was significantly reduced in the patient population in the Medial Temporal regions. DTI anisotropy indices were also reduced in the same Medial Temporal regions. NAA and DTI-anisotropy indices were also correlated in the left medial temporal region.</p> <p>Conclusion</p> <p>Our results implicate defects in the medial temporal white matter in patients with schizophrenia. Moreover, MRS and DTI are complementary modalities for the study of white matter disruptions in patients with schizophrenia.</p

Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis

Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan’s unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p &lt; 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p &lt; 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = −0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = −0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = −0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p &lt; 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p &lt; 0.001). Proportion of males was negatively associated with MFC glutamate (z = −0.02, p &lt; 0.001) and frontal white matter Glx (z = −0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies

Magnetic Resonance Spectroscopy, Positron Emission Tomography and Radiogenomics—Relevance to Glioma

Advances in metabolic imaging techniques have allowed for more precise characterization of gliomas, particularly as it relates to tumor recurrence or pseudoprogression. Furthermore, the emerging field of radiogenomics where radiographic features are systemically correlated with molecular markers has the potential to achieve the holy grail of neuro-oncologic neuro-radiology, namely molecular diagnosis without requiring tissue specimens. In this section, we will review the utility of metabolic imaging and discuss the current state of the art related to the radiogenomics of glioblastoma

1 Non-negative Matrix Factorization for Rapid Recovery of Constituent Spectra in Magnetic Resonance Chemical Shift Imaging of the Brain

We present an algorithm for blindly recovering constituent source spectra from magnetic resonance (MR) chemical shift imaging (CSI) of human brain. The algorithm, which we call constrained non-negative matrix factorization (cNMF), does not enforce independence or sparsity, instead only requiring the source and mixing matrices to be non-negative. It is based on the non-negative matrix factorization (NMF) algorithm extending it to include a constraint on the positivity of the amplitudes of the recovered spectra. This constraint enables recovery of physically meaningful spectra even in the presence of noise that causes a significant number of the observation amplitudes to be negative. We demonstrate and characterize the algorithm’s performance using P volumetric brain data, comparing the results with two different blind source separation methods: Bayesian spectral decomposition (BSD) and non-negative sparse coding (NNSC). We then incorporate the cNMF algorithm into a hierarchical decomposition framework, showing that it can be used to recover tissuespecific spectra given a processing hierarchy that proceeds coarse-to-fine. We demonstrate the hierarchical procedure on H brain data and conclude that the computational efficiency of the algorithm makes it wellsuite

Decreased Anterior Cingulate Cortex γ-Aminobutyric Acid in Youth With Tourette's Disorder

γ-Aminobutyric acid has been implicated in the pathophysiology of Tourette's disorder. The present study primarily sought to examine in vivo γ-aminobutyric acid levels in the anterior cingulate cortex in psychotropic medication-free adolescents and young adults. Secondarily, we sought to determine associations between γ-aminobutyric acid in the anterior cingulate cortex and measures of tic severity, tic-related impairment, and anxiety and depression symptoms. γ-Aminobutyric acid levels were measured using proton magnetic resonance spectroscopy. Analysis of covariance compared γ-aminobutyric acid levels in 15 youth with Tourette's disorder (mean age = 15.0, S.D. = 2.7) and 36 healthy comparison subjects (mean age = 15.9, S.D. = 2.1). Within the Tourette disorder group, we examined correlations between γ-aminobutyric acid levels and tic severity and tic-related impairment, as well as anxiety and depression severity. Anterior cingulate cortex γ-aminobutyric acid levels were lower in participants with Tourette's disorder compared with control subjects. Within the Tourette disorder group, γ-aminobutyric acid levels did not correlate with any clinical measures. Our findings support a role for γ-aminobutyric acid in Tourette's disorder. Larger prospective studies will further elucidate this role

Riluzole effect on occipital cortex: A structural and spectroscopy pilot study

Background: To investigate the mechanism underlying the anxiolytic properties of riluzole, a glutamate-modulating agent, we previously studied the effect of this drug on hippocampal N-acetylaspartate (NAA) and volume in patients with generalized anxiety disorder (GAD). in the same cohort, we now extend our investigation to the occipital cortex, a brain region that was recently implicated in the antidepressant effect of riluzole.Methods: Fourteen medication-free adult patients with GAD received 8-week of open-label riluzole. Ten healthy subjects served as a comparison group. the healthy group did not receive riluzole treatment. Both groups underwent magnetic resonance imaging and spectroscopy at baseline and at the end of Week 8. Hamilton Anxiety Rating Scale (HAM-A) and Penn State Worry Questionnaire (PSWQ) were used as the primary and secondary outcome measures, respectively.Results: At baseline, we found clusters of increased cortical thickness in the occipital region in GAD compared to healthy subjects. in the right hemisphere, 8 weeks of treatment reduced occipital cortical thickness in the GAD group (t = 3.67, p = 0.004). in addition, the improvement in HAM-A scores was negatively correlated with post-treatment right occipital NAA (r = -0.68, p = 0.008), and with changes in NAA levels (r = -0.53, p = 0.051). in the left hemisphere, we found positive associations between changes in occipital cortical thickness and improvement in HAM-A (r = 0.60, p = 0.04) and PSWQ (r = 0.62, p = 0.03).Conclusion: These pilot findings implicate the occipital cortex as a brain region associated with pathology and clinical improvement in GAD. in addition, the region specific effect of riluzole implies a distinct pathophysiology in the occipital cortex - compared to other, previously studied, frontolimbic brain structures. (C) 2012 Elsevier Ireland Ltd. All rights reserved.NIMHNYSTEMGlaxoSmithKlinePfizerAlexza PharmaceuticalsBanner Family FundBrain and Behavior Fund (NARSAD)Brown Foundation, Inc.Bristol-Myers SquibbDepartment of Veterans AffairsEvotecJohnson JohnsonNational Institute of Mental HealthAllerganAstraZenecaCephalonCorceptNovenRocheTakedaBrain and Behavior Research FoundationSackler Institute of Columbia UniversityNational Institute on Drug AbuseYale Univ, Sch Med, Dept Psychiat, New Haven, CT USASuny Downstate Med Ctr, Div Neuropsychopharmacol, Dept Psychiat, Brooklyn, NY 11203 USAUniversidade Federal de São Paulo, LiNC, Dept Psiquiatria, São Paulo, SP, BrazilUniv Fed ABC, Ctr Math Computat & Cognit, Santo Andre, BrazilCornell Univ, Dept Radiol, Weill Med Coll, New York, NY 10021 USACornell Univ, Dept Psychiat, Weill Med Coll, New York, NY 10021 USACornell Univ, Dept Biophys, Weill Med Coll, New York, NY 10021 USAMichael E Debakey VA Med Ctr, Houston, TX USABaylor Coll Med, Menninger Dept Psychiat & Behav Sci, Houston, TX 77030 USAUniversidade Federal de São Paulo, LiNC, Dept Psiquiatria, São Paulo, SP, BrazilNational Institute of Mental Health: K23-MH-069656National Institute on Drug Abuse: T32-DA-022975Web of Scienc

IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 23, NO. 12, DECEMBER 2004 1453 Nonnegative Matrix Factorization for Rapid Recovery of Constituent Spectra in Magnetic Resonance

We present an algorithm for blindly recovering constituent source spectra from magnetic resonance (MR) chemical shift imaging (CSI) of the human brain. The algorithm, which we call constrained nonnegative matrix factorization (cNMF), does not enforce independence or sparsity, instead only requiring the source and mixing matrices to be nonnegative. It is based on the nonnegative matrix factorization (NMF) algorithm, extending it to include a constraint on the positivity of the amplitudes of the recovered spectra. This constraint enables recovery of physically meaningful spectra even in the presence of noise that causes a significant number of the observation amplitudes to be negative. We demonstrate and characterize the algorithm&apos;s performance using 31 P volumetric brain data, comparing the results with two different blind source separation methods: Bayesian spectral decomposition (BSD) and nonnegative sparse coding (NNSC). We then incorporate the cNMF algorithm into a hierarchical decomposition framework, showing that it can be used to recover tissue-specific spectra given a processing hierarchy that proceeds coarse-to-fine. We demonstrate the hierarchical procedure on H brain data and conclude that the computational efficiency of the algorithm makes it well-suited for use in diagnostic work-up