Methods and tools for detecting, diagnosing, predicting, prognosticating, or treating a neurobehavioral phenotype in a subject
The present tools and methods for detecting, diagnosing, predicting, prognosticating, or treating a neurobehavioral phenotype in a subject. These tools and methods relates to a genotype and neurophenotype topography-based approach for analyzing brain neuroimaging and gene expression maps to identify drug targets associated with neurobehavioral phenotypes and, conversely, neurobehavioral phenotypes associated with potential drug targets, to develop rational design and application of pharmacological therapeutics for brain disorders, and to provide methods and tools for treatment of subjects in need of neurological therapy.
1. A method of identifying a therapeutic agent suitable for treating a neurobehavioral disorder in a patient, said method comprising:
scanning a patient using magnetic resonance imaging to output a set of neuroimaging data comprising a set of volumetric voxels;
processing, using one or more processors, the set of neuroimaging data into an anatomical segmentation of cortical and subcortical structures;
processing the set of volumetric voxels into a two-dimensional mesh of the cerebral cortex and a set of three-dimensional subcortical volume boundaries, based on the anatomical segmentation of cortical and subcortical structures, wherein the two-dimensional mesh and the set of three-dimensional subcortical volume boundaries comprise numerical values assigned to each of a set of brain regions represented by the two-dimensional mesh and the set of three-dimensional subcortical volume boundaries representing a magnitude of a neuroimaging feature processed from the patient's neuroimaging data in relation to reference neuroimaging data; and
computing a statistical association of the numerical values assigned to the set of brain regions represented by the two-dimensional mesh and the three-dimensional subcortical volume boundaries to numerical values assigned to the set of brain regions on a gene expression map, wherein the gene expression map comprises a two-dimensional cortical mesh and a set of three-dimensional subcortical volume boundaries with numerical values assigned to each of the set of brain regions representing a magnitude of expression for a particular gene.
2. The method of claim 1 , wherein computing the statistical association comprises computing a correlation.
3. The method of claim 2 , wherein the correlation is an autocorrelation.
4. The method of claim 1 , wherein the set of neuroimaging data is associated with a neurophenotype.
5. The method of claim 4 , wherein the neurophenotype comprises at least one of: an anxiety disorder, a panic disorder, a post-traumatic stress disorder, a mood disorder, an effective disorder, major depression, geriatric depression, bipolar disorder, a mood disorder in epilepsy, a personality disorder, borderline personality disorder, an obsessive-compulsive disorder, a cognitive change associated with chemotherapy, an attention deficit hyperactivity disorder (ADHD), a sex difference in brain function in health and disease, a premenstrual dysphoric disorder, and a traumatic brain injury.
6. A computing device, comprising:
a memory containing machine readable medium comprising machine executable code having stored thereon instructions for performing a method;
a processor coupled to the memory, the processor configured to execute the machine executable code to cause the processor to:
receive data output from a magnetic resonance imaging machine comprising a set of neuroimaging data comprising a set of volumetric voxels;
process, using one or more processors, the set of neuroimaging data into an anatomical segmentation of cortical and subcortical structures;
process the set of volumetric voxels into a two-dimensional cortical mesh of the cerebral cortex and a set of three-dimensional subcortical volume boundaries, based on the anatomical segmentation of cortical and subcortical structures[,] wherein the two dimensional mesh and the set of three-dimensional subcortical volume boundaries comprise numerical values assigned to each of a set of brain regions represented by the two-dimensional cortical mesh and the set of three-dimensional subcortical volume boundaries, representing a magnitude of a neuroimaging feature processed from the set of neuroimaging data in relation to reference neuroimaging data; and
computing a statistical association of the numerical values assigned to the set of brain regions represented by the two-dimensional mesh and the three-dimensional subcortical volume boundaries to numerical values assigned to the set of brain regions on a gene expression map, wherein the gene expression map comprises a two-dimensional cortical mesh and a set of three-dimensional subcortical volume boundaries with numerical values assigned to each of the set of brain regions representing a magnitude of expression for a particular gene.
7. A non-transitory computer readable medium, having stored thereon a computer program executable by a computing device, the computer program comprising a plurality of code sections for performing steps comprising:
processing, using one or more processors, a set of neuroimaging data from a patient comprising a set of volumetric voxels into an anatomical segmentation of cortical and subcortical structures;
processing the set of volumetric voxels into a two-dimensional cortical mesh of the cerebral cortex and a set of three-dimensional subcortical volume boundaries, based on the anatomical segmentation of cortical and subcortical structures wherein the two dimensional mesh and the set of three-dimensional subcortical volume boundaries comprise numerical values assigned to each of a set of brain regions represented by the two-dimensional cortical mesh and the set of three-dimensional subcortical volume boundaries, representing a magnitude of a neuroimaging feature processed from the set of neuroimaging data in relation to reference neuroimaging data; and
computing a statistical association of the numerical values assigned to the set of brain regions represented by the two-dimensional mesh and the three-dimensional subcortical volume boundaries to numerical values assigned to the set of brain regions on a gene expression map, wherein the gene expression map comprises a two-dimensional cortical mesh and a set of three-dimensional subcortical volume boundaries with numerical values assigned to each of the set of brain regions representing a magnitude of expression for a particular gene.