Aberrations of anterior insular cortex functional connectivity in nontreatment-seeking alcoholics

An emergent literature suggests that resting state functional magnetic resonance imaging (rsfMRI) functional connectivity (FC) patterns are aberrant in alcohol use disorder (AUD) populations. The salience network (SAL) is an established set of brain regions prominent in salience attribution and valuation, and includes the anterior insular cortex (AIC). The SAL is thought to play a role in AUD through directing increased attention to interoceptive cues of intoxication. There is very little information on the salience network (SAL) in AUD, and, in particular, there are no data on SAL FC in currently drinking, nontreatment seeking individuals with AUD (NTS). rsfMRI data from 16 NTS and 21 social drinkers (SD) were compared using FC correlation maps from ten seed regions of interest in the bilateral AIC. As anticipated, SD subjects demonstrated greater insular FC with frontal and parietal regions. We also found that, compared to SD, NTS had higher insular FC with hippocampal and medial orbitofrontal regions. The apparent overactivity in brain networks involved in salience, learning, and behavioral control in NTS suggests possible mechanisms in the development and maintenance of AUD

Differences in White Matter Microstructure and Connectivity in Nontreatment‐Seeking Individuals with Alcohol Use Disorder

Background Diffusion‐weighted imaging (DWI) has been widely used to investigate the integrity of white matter (WM; indexed by fractional anisotropy [FA]) in alcohol dependence and cigarette smoking. These disorders are highly comorbid, yet cigarette use has often not been adequately controlled in neuroimaging studies of alcohol‐dependent populations. In addition, information on WM deficits in currently drinking, nontreatment‐seeking (NTS) individuals with alcohol dependence is limited. Therefore, the aim of this work was to investigate WM microstructural integrity in alcohol use disorder by comparing matched samples of cigarette smoking NTS and social drinkers (SD). Methods Thirty‐eight smoking NTS and 19 smoking SD subjects underwent DWI as well as structural magnetic resonance imaging. After an in‐house preprocessing of the DWI data, FA images were analyzed with tract‐based spatial statistics (TBSS). FA obtained from the TBSS skeleton was tested for correlation with recent alcohol consumption. Results Smoking NTS had lower FA relative to smoking SD, predominantly in the left hemisphere (p < 0.05, family‐wise error rate corrected across FA skeleton). Across the full sample, FA and number of drinks per week were negatively related (ρ = −0.348, p = 0.008). Qualitative analyses of the structural connections through compromised WM as identified by TBSS showed differential connectivity of gray matter in NTS compared to SD subjects of left frontal, temporal, and parietal regions. Conclusions NTS subjects had lower WM FA than SD, indicating compromised WM integrity in the NTS population. The inverse relationship of entire WM skeleton FA with self‐reported alcohol consumption supports previous evidence of a continuum of detrimental effects of alcohol consumption on WM. These results provide additional evidence that alcohol dependence is associated with reduced WM integrity in currently drinking NTS alcohol‐dependent individuals, after controlling for the key variable of cigarette smoking

Differential dopamine function in fibromyalgia

Approximately 30% of Americans suffer from chronic pain disorders, such as fibromyalgia (FM), which can cause debilitating pain. Many pain-killing drugs prescribed for chronic pain disorders are highly addictive, have limited clinical efficacy, and do not treat the cognitive symptoms reported by many patients. The neurobiological substrates of chronic pain are largely unknown, but evidence points to altered dopaminergic transmission in aberrant pain perception. We sought to characterize the dopamine (DA) system in individuals with FM. Positron emission tomography (PET) with [18F]fallypride (FAL) was used to assess changes in DA during a working memory challenge relative to a baseline task, and to test for associations between baseline D2/D3 availability and experimental pain measures. Twelve female subjects with FM and eleven female controls completed study procedures. Subjects received one FAL PET scan while performing a “2-back” task, and one while performing a “0-back” (attentional control, “baseline”) task. FM subjects had lower baseline FAL binding potential (BP) in several cortical regions relative to controls, including anterior cingulate cortex. In FM subjects, self-reported spontaneous pain negatively correlated with FAL BP in the left orbitofrontal cortex and parahippocampal gyrus. Baseline BP was significantly negatively correlated with experimental pain sensitivity and tolerance in both FM and CON subjects, although spatial patterns of these associations differed between groups. The data suggest that abnormal DA function may be associated with differential processing of pain perception in FM. Further studies are needed to explore the functional significance of DA in nociception and cognitive processing in chronic pain

Levetiracetam modulates brain metabolic networks and transcriptomic signatures in the 5XFAD mouse model of Alzheimer’s disease

IntroductionSubcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer’s disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core.MethodsChronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling.ResultsPharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-∞, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e., positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling.DiscussionThis study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration-dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value toward informing clinical study design

Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease

INTRODUCTION: Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage. METHODS: We performed 18F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis. RESULTS: The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model. DISCUSSION: The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.</p

Temporal stability of the ventral attention network and general cognition along the Alzheimer’s disease spectrum

Understanding the interrelationships of clinical manifestations of Alzheimer’s disease (AD) and functional connectivity (FC) as the disease progresses is necessary for use of FC as a potential neuroimaging biomarker. Degradation of resting-state networks in AD has been observed when FC is estimated over the entire scan, however, the temporal dynamics of these networks are less studied. We implemented a novel approach to investigate the modular structure of static (sFC) and time-varying (tvFC) connectivity along the AD spectrum in a two-sample Discovery/Validation design (n = 80 and 81, respectively). Cortical FC networks were estimated across 4 diagnostic groups (cognitively normal, subjective cognitive decline, mild cognitive impairment, and AD) for whole scan (sFC) and with sliding window correlation (tvFC). Modularity quality (across a range of spatial scales) did not differ in either sFC or tvFC. For tvFC, group differences in temporal stability within and between multiple resting state networks were observed; however, these differences were not consistent between samples. Correlation analyses identified a relationship between global cognition and temporal stability of the ventral attention network, which was reproduced in both samples. While the ventral attention system has been predominantly studied in task-evoked designs, the relationship between its intrinsic dynamics at-rest and general cognition along the AD spectrum highlights its relevance regarding clinical manifestation of the disease

Data_Sheet_1_Levetiracetam modulates brain metabolic networks and transcriptomic signatures in the 5XFAD mouse model of Alzheimer’s disease.PDF

IntroductionSubcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer’s disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core.MethodsChronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling.ResultsPharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-∞, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e., positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling.DiscussionThis study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration-dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value toward informing clinical study design.</p

Data_Sheet_1_Levetiracetam modulates brain metabolic networks and transcriptomic signatures in the 5XFAD mouse model of Alzheimer’s disease.PDF

IntroductionSubcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer’s disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core.MethodsChronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling.ResultsPharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-∞, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e., positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling.DiscussionThis study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration-dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value toward informing clinical study design.</p