Neurometabolism and cognitive functioning in healthy children : a proton magnetic resonance spectroscopy study

This study investigated the role of sex, mean NAA/Cr and Cho/Cr, and variability in these metabolites in predicting memory and processing speed. This study utilized predictive models including sex, mean ratios of NAA/Cr and Cho/Cr, as well as the standard deviation of these ratios, within tissue type, among voxels in a supraventricular slice. In addition, models included interaction terms between each neurometabolic variable and sex. Tests of memory and processing speed were then regressed in a three-step hierarchical regression onto sex, main effects for neurometabolites, and interaction effects. The regression of memory was significant in the model including interaction terms, and showed higher mean NAA/Cr and lower standard deviation of NAA/Cr in gray matter related to better memory performance in boys, with the reverse pattern in girls. Lower standard deviation of NAA/Cr in the white matter was related to faster processing speed for both sexes. A model including sex, Cho/Cr mean and standard deviation by tissue type, and sex by Cho/Cr interactions significantly predicted memory performance. No model using Cho/Cr predicted processing speed. Posthoc analyses suggest that tests of working memory showed stronger relationships to metabolites than tests of learning. Moreover, relationships may differ by sex depending on whether digit span or spatial span is the working memory variable of interest

Måleegenskaper ved den norske versjonen av ADHD Rating Scale – IV Hjemmeversjon (ADHD-RS-IV Hjemme)

-Beskrivelse. ADHD-RS-IV Hjemme er et spørreskjema som skal fylles ut av mor, far, verge eller besteforeldre for å fange opp ADHD-symptomer hos barn og ungdom. Spørreskjemaet har 18 ledd med fire svaralternativer. Det tar under 20 minutter å fylle ut. Hovedskalaen og de to delskalaene skåres ved å summere enkeltskårer. Kompetansekrav for bruk av ADHD-RS-IV inkluderer generell opplæring i testbruk, samt yrkesstatus som psykolog, lege, annet helsepersonell med utdanning på mastergradsnivå, spesialpedagog eller pedagog med mastergrad . Litteratursøk. Vårt systematiske litteratursøk identifiserte fire publikasjoner fra fire norske studier. Psykometri. Én studie med et mindre utvalg rapporterte Cronbahcs α=0,73 , svært god test-retest intraklassekoeffisient(ICC)=0,95. Ingen av de inkluderte publikasjonene inneholdt dokumentasjon om normer eller validitet ved ADHD-RS-IV Hjemme. Konklusjon. Den indre konsistensen i ADHD-RS-IV Hjemme var tilfredsstillende og testretest reliabiliteten var svært god, men utvalgsstørrelsen var utilfredsstillende og tilfører disse målene stor usikkerhet. Normer og validiteten ved den norske versjonen av ADHDRS- IV Hjemme er ikke dokumentert

Multimodal neuroimaging signatures of early cART-treated paediatric HIV - Distinguishing perinatally HIV-infected 7-year-old children from uninfected controls

Introduction: HIV-related brain alterations can be identified using neuroimaging modalities such as proton magnetic resonance spectroscopy (1H-MRS), structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and functional MRI (fMRI). However, few studies have combined multiple MRI measures/features to identify a multivariate neuroimaging signature that typifies HIV infection. Elastic net (EN) regularisation uses penalised regression to perform variable selection, shrinking the weighting of unimportant variables to zero. We chose to use the embedded feature selection of EN logistic regression to identify a set of neuroimaging features characteristic of paediatric HIV infection. We aimed to determine 1) the most useful features across MRI modalities to separate HIV+ children from HIV- controls and 2) whether better classification performance is obtained by combining multimodal MRI features rather than using features from a single modality. Methods: The study sample comprised 72 HIV+ 7-year-old children from the Children with HIV Early Antiretroviral Therapy (CHER) trial in Cape Town, who initiated combination antiretroviral therapy (cART) in infancy and had their viral loads suppressed from a young age, and 55 HIV- control children. Neuroimaging features were extracted to generate 7 MRI-derived sets. For sMRI, 42 regional brain volumes (1st set), mean cortical thickness and gyrification in 68 brain regions (2nd and 3rd set) were used. For DTI data: radial (RD), axial (AD), mean (MD) diffusivities, and fractional anisotropy (FA) in each of 20 atlas regions were extracted for a total of 80 DTI features (4th set). For 1H-MRS, concentrations of 14 metabolites and their ratios to creatine in the basal ganglia, peritrigonal white matter, and midfrontal gray matter voxels (5th, 6th and 7th set) were considered. A logistic EN regression model with repeated 10-fold cross validation (CV) was implemented in R, initially on each feature set separately. Sex, age and total intracranial volume (TIV) were included as confounders with no shrinkage penalty. For each model, the classification performance for HIV+ vs HIV- was assessed by computing accuracy, specificity, sensitivity, and mean area under the receiver operator characteristic curve (AUC) across 10 CV folds and 100 iterations. To combine feature sets, the best performing set was concatenated with each of the other sets and further EN regressions were run. The combination giving the largest AUC was combined with each of the remaining sets until there was no further increase in AUC. Two concatenation techniques were explored: nested and non-nested modelling. All models were assessed for their goodness of fit using χ 2 likelihood ratio tests for non-nested models and Akaike information criterion (AIC) for nested models. To identify features most useful in distinguishing HIV infection, the EN model was retrained on all the data, to find features with non-zero weights. Finally, multivariate imputation using chained equations (MICE) was explored to investigate the effect of increased sample size on classification and feature selection. Results: The best performing modality in the single modality analysis was sMRI volume

Comparison of Magnetic Resonance Spectroscopy (MRS) data in children with and without HIV at 11-12 years

Although HIV and antiretroviral drugs have been shown to cause damage in the brain, the long-term impacts of perinatal infection, early treatment and exposure in children at 11 years, remain unclear. The effects of HIV and antiretroviral therapy (ART), whilst indistinguishable, can be investigated at a chemical level through proton magnetic resonance spectroscopy (1H-MRS). Previous studies in children have largely focused on individual metabolite changes. However, several adult studies have now advanced beyond this to address patterns of metabolic activity that are altered with HIV infection. Using a 3T Skyra scanner, 136 children (76 HIV+, 30 HEU, 30 HU; 71 males) between the ages of 11.0- 12.5 years, and from a similar socioeconomic background, were scanned. In this study metabolite concentrations were quantified within the basal ganglia (BG), midfrontal gray matter (MFGM) and peritrigonal white matter (PWM). We utilised linear regression to investigate individual metabolite differences, comparing HIV-infected (HIV+) children from the Children with HIV Early Antiretroviral Therapy (CHER) trial, and HIV-exposed-uninfected (HEU) children, to HIV-unexposed (HU) children. Pearson's correlation analysis, factor analysis and logistic regression were then used to study alterations in metabolic patterns between HIV+ and HIV-uninfected (HIV-) children. Analysis of the data was carried out in R. We found elevated total choline in the BG (p = 0.03) and MFGM (p < 0.001) of HIV+ children, as well as reduced PWM total NAA (p = 0.03) and total creatine (p = 0.01). Altered metabolite concentrations were further observed in HEU children. Additionally, we identified a cross-regional coupling of choline which distinguishes HIV+ from HIV- children (p < 0.001). These findings indicate that multiregional inflammation and PWM axonal damage are occurring in HIV+ children at 11 years. Ultimately, the consequences of perinatal HIV acquisition, in spite of early treatment, continue to be seen at 11 years, as do the impacts of exposure

Exploration of the biological mechanisms in neuropsychiatric disorders using multimodal imaging

The present doctoral thesis focused on the multimodal imaging investigation of brain mechanisms in neuropsychiatric disorders, emphasizing on the research questions of whether and how neurochemistry is associated with brain anatomical structures and brain functions. The aim of the thesis is to provide a biochemical insight underlying the altered brain morphology and functions in the two disorders studied, which might ultimately offer evidence for novel therapeutic implications. There are two brain imaging projects included in this thesis. In project I, the first aim was to explore the mechanism of partial volume recovery during the first two weeks of abstinence from alcohol at a whole-brain level. The hippocampus was then chosen as a seed region, to investigate the abstinence-induced neurochemical changes and whether the hyperglutamatergic state induced by alcohol withdrawal may affect GM volume recovery in the hippocampus. We found cortical thickness alteration corresponds to the partial cortical volumetric recovery. Moreover, alcohol differentially impacts on sulci and gyri of the neocortex. Sulci are more susceptive to excessive alcohol consumption and abstinence-induced recovery. Lower subcortical volume was found in alcohol dependent patients at withdrawal, and no subcortical volume regain was observed during the initial two weeks of abstinence. In support of a ‘hyperglutamatergic state’ induced by withdrawal, our rat model demonstrated elevated Glu/Gln ratios during acute withdrawal (12h and 60h after stopping alcohol intake) and a trend towards an increase in Glu levels at 12h compared to control rats. The main novel finding of this study was that in both species a negative association was found between Glu markers and GM volume in the hippocampus after alcohol withdrawal (but not during withdrawal), suggesting that this tissue damage is a consequence of withdrawal and results from withdrawal-induced hyperglutamatergic neurotoxicity. In project II, the study emphasized the additional value of multimodal imaging analyses to unravel group differences between BPD patients and HCs which could not be detected by BOLD response and ACC GABA levels per se. The superior aim was to explore the interrelationship between GABA, neural correlates of interference inhibition, and impulsivity traits in BPD. We found task-related functional connectivity and the association of fMRI measures with MRS derived GABA levels are significantly different between the two groups. These analyses give support for a disconnection of the fronto-striatal network during interference inhibition in BPD patients that is related to elevated impulsivity ratings, specifically the UPPS sensation seeking score. Our hierarchical analyses also give first evidence for the hypothesis that the fronto-striatal network during inhibitory control serves to mediate the association between ACC GABA levels and impulsivity symptomatology in patients with BPD. In other words, GABAergic transmission in the ACC drives the inhibitory-related fronto-striatal brain network, whereas the disruption of fronto-striatal connectivity is of core relevance to the sensation seeking symptom in BPD patients. Taken together, multimodal imaging fusion analysis of neurobiochemistry - structure/function relationship can offer opportunities to deepen our understanding of neurobiological mechanisms of brain disorders

Evaluation of Traumatic Brain Injury Using Magnetic Resonance Spectroscopy

Traumatic brain injury (TBI) is responsible for a third of all injury-related deaths in the United States. With the lack of structural imaging biomarkers available for the detection and evaluation of TBI sequelae, unambiguous diagnosis and prognosis in TBI still remain a huge challenge. Furthermore, complications arising from TBI can lead to cognitive, social, emotional and behavioral defects later in life. Even in confirmed cases of head injury, computed tomography (CT) and conventional MR techniques are limited in their ability to predict the neuropsychological outcome of patients. While the initial trauma can induce structural impairment of brain tissue, the bulk of the cerebral dysfunction ensuing from TBI is due to alterations in cellular biochemical processes that occur in the days and weeks following the traumatic incident. There is therefore a need for advanced imaging modalities that are able to probe the more underlying cellular changes that are induced by TBI. Understanding such cellular changes will be useful in predicting patient outcome and designing interventions to alleviate the injury sequelae. Magnetic Resonance Spectroscopy (MRS) is a non-invasive imaging modality that is capable of detecting cellular metabolic changes in in vivo tissue. In this study we will assess the use of MRS as a clinically relevant tool in the diagnostic and prognostic evaluation of TBI. To this end, we have laid out the following specific aims: (i) To understand the nature and implications of neurometabolic sequelae in mild traumatic brain injury (mTBI) by carrying out cross-sectional comparisons of mTBI patients to neurologically healthy subjects at different stages of injury and to determine associations between early neurometabolic patterns and chronic neuropsychological performance in mTBI patients (ii) To develop novel MRS pulse sequence acquisition and data processing techniques that will enable a more thorough neurometabolic evaluation of TBI and enhance quantification of MRS data (iii) To develop automated classification systems in mTBI using early neurometabolic information that will aid discrimination between subjects with and without injury related sequelae and allow the prediction of symptomatic outcome at the later stages of injury. The research presented herein will help to enhance the utility of MRS in the evaluation of TBI

Advances in Eating Disorders

Eating disorders (ED) are a group of mental disorders characterized by an altered food intake and the presence of inappropriate behaviors and thoughts about weight and shape. All EDs lead to physical and psychosocial functioning impairments in the patients which, in turn, may contribute to the persistence of the disease. The severity of EDs has been highlighted by their chronicity, medical complications, comorbidity, and high rates of mortality. Therefore, to address this important health issue, the current Special Issue collected 21 articles (i.e., three reviews and 18 research articles) focusing on the most recent and relevant scientific findings regarding advances in ED, such as genetic and epigenetic factors, biomarkers, comorbidity, clinical phenotypes, neurocognition, treatment predictors, and treatment models and therapeutic targets. Altogether, we believe that the articles contained in this Special Issue have largely achieved the initial objective of providing increased knowledge about the pathogenesis, the risk factors, the maintenance factors, and the most appropriate treatments tools for ED