Dataset Information

Assessing Neural Mechanisms using MRI and Magnetic Resonance Spectroscopy

ABSTRACT:

Urea cycle disorders represent a group of rare inborn errors of metabolism that lead to accumulation of ammonia, a toxic product of protein metabolism. Individuals with urea cycle disorders cannot metabolize the ammonia that accumulates due to enzyme deficiency. The symptoms of these disorders may present at birth, childhood or adulthood (milder deficiencies). There are currently eight enzyme deficiencies that constitute the range of inborn errors of ureagenesis. This project will focus on the most common enzyme disorder of the urea cycle, ornithine transcarbamylase deficiency, inherited as an X-linked trait.

This project will study cognitive and motor dysfunction in patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non -invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies will range from ages 18-60 years and will be compared to an age-matched typically developed (TD) comparison group.

For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

PROVIDER: phs001108 | dbGaP |

SECONDARY ACCESSION(S): PRJNA318557PRJNA318558

REPOSITORIES: dbGaP

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	GapExchange_phs001108.v1.p1.xml	Xml
	dbGaPEx2.1.5.xsd	Other
	phs001108.v1-Documents.zip	Other
	Study_Report.phs001108.UCDC_5104.v1.p1.MULTI.pdf	Pdf
	manifest_phs001108.UCDC_5104.v1.p1.c1.GRU-IRB-PUB.pdf	Pdf

Items per page:

1 - 5 of 26

Similar Datasets

Project description:This is a case controlled, observational study. This project studies cognitive and motor dysfunction in adult and pediatric patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation (outside of the newborn period) of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non-invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies ranged from ages 7-60 years and were compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

Project description:Winter2017 - Brain Energy Metabolism with PPP This model is described in the article: Mathematical analysis of the influence of brain metabolism on the BOLD signal in Alzheimer's disease Felix Winter1,2, Catrin Bludszuweit-Philipp1 and Olaf Wolkenhauer2,3 Journal of Cerebral Blood Flow & Metabolism Abstract: Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a standard clinical tool for the detection of brain activation. In Alzheimer’s disease (AD), task-related and resting state fMRI have been used to detect brain dysfunction. It has been shown that the shape of the BOLD response is affected in early AD. To correctly interpret these changes, the mechanisms responsible for the observed behaviour need to be known. The parameters of the canonical hemodynamic response function (HRF) commonly used in the analysis of fMRI data have no direct biological interpretation and cannot be used to answer this question. We here present a model that allows relating AD-specific changes in the BOLD shape to changes in the underlying energy metabolism. According to our findings, the classic view that differences in the BOLD shape are only attributed to changes in strength and duration of the stimulus does not hold. Instead, peak height, peak timing and full width at half maximum are sensitive to changes in the reaction rate of several metabolic reactions. Our systems-theoretic approach allows the use of patient-specific clinical data to predict dementia- driven changes in the HRF, which can be used to improve the results of fMRI analyses in AD patients. This model is hosted on BioModels Database and identified by: BIOMD0000000627. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Understanding the genetic factors that control brain growth during childhood and adolescence is a priority for neuroscience. Its importance lies partly in the finding that disturbances in the course of brain development characterizes many common childhood behavioral problems. Recent advances in neuroimaging such as the use of non-invasive magnetic resonance imaging have provided a chance to define these trajectories in the living child. The intramural programs of the NIMH and NHGRI have conducted repeated neuroanatomic imaging on children along with the banking of DNA, providing a cohort which is studied for defining developmental trajectories of the brain. A central goal of this cohort is to define the disturbances in brain development that are linked with common behavioral problems, such as excessive impulsivity, hyperactivity and inattention. Studies have demonstrated that problems in these domains are distributed across the entire population and that children with Attention Deficit Hyperactivity Disorder (ADHD) lie at the extreme end of these behavioral dimensions. We found a similar dimensionality in the development of brain regions that are associated with these behavioral problems. Specifically, we showed that the rate of change in both the lateral prefrontal cortex and interconnected striatum during childhood and adolescence was linked to the severity of symptoms of hyperactivity and impulsivity. As symptoms increased, the rate of growth of both structures decreased. The lateral prefrontal cortex and striatum are core components of richly interconnected 'loops' that support a host of cognitive processes, including attention, cognitive control and motor planning. Anomalies in these structures and their connections have been implicated in many childhood behavioral problems, including ADHD. In summary, we aim to identify the common and rare genetic variants that are associated with the developmental trajectories of the lateral-prefrontal cortex and striatum. Identifying genetic variants influencing the growth of these structures may reveal the biological mechanisms underlying dysregulated control of attention, impulse and activity level, which in the extreme constitute ADHD. The study thus could inform our understanding of neurobiology underpinning one of the most common neuropsychiatric disorders of childhood.

Project description:Aubert2002 - Coupling between Brain electrical activity, Metabolism and Hemodynamics Felix Winter encoded this model in SBML as part of his work at ASD GmbH This model is described in the article: A model of the coupling between brain electrical activity, metabolism, and hemodynamics: application to the interpretation of functional neuroimaging. Aubert A, Costalat R. Neuroimage 2002 Nov; 17(3): 1162-1181 Abstract: In order to improve the interpretation of functional neuroimaging data, we implemented a mathematical model of the coupling between membrane ionic currents, energy metabolism (i.e., ATP regeneration via phosphocreatine buffer effect, glycolysis, and mitochondrial respiration), blood-brain barrier exchanges, and hemodynamics. Various hypotheses were tested for the variation of the cerebral metabolic rate of oxygen (CMRO(2)): (H1) the CMRO(2) remains at its baseline level; (H2) the CMRO(2) is enhanced as soon as the cerebral blood flow (CBF) increases; (H3) the CMRO(2) increase depends on intracellular oxygen and pyruvate concentrations, and intracellular ATP/ADP ratio; (H4) in addition to hypothesis H3, the CMRO(2) progressively increases, due to the action of a second messenger. A good agreement with experimental data from magnetic resonance imaging and spectroscopy (MRI and MRS) was obtained when we simulated sustained and repetitive activation protocols using hypotheses (H3) or (H4), rather than hypotheses (H1) or (H2). Furthermore, by studying the effect of the variation of some physiologically important parameters on the time course of the modeled blood-oxygenation-level-dependent (BOLD) signal, we were able to formulate hypotheses about the physiological or biochemical significance of functional magnetic resonance data, especially the poststimulus undershoot and the baseline drift. This model is hosted on BioModels Database and identified by: BIOMD0000000570. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

Assessing Neural Mechanisms using MRI and Magnetic Resonance Spectroscopy

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets