Genetic Mechanisms Controlling Resilience to Huntington's Disease

控制亨廷顿病抵抗力​​的遗传机制

• 批准号: 10531136
• 负责人: JAMES F GUSELLA
• 金额: $ 12.32万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10531136
• 关键词: Age; Alleles; Alzheimer' s Disease; Animal Model; Animals; Attention; Behavior; Brain; Brain region; CAG repeat; Candidate Disease Gene; Clustered Regularly Interspaced Short Palindromic Repeats; Cognitive; Corpus striatum structure; DNA; Data; Dimensions; Disease; Disease model; Emotional; Exons; Functional Imaging; Genes; Genetic; Genetic Variation; Genomic Segment; Genotype; Health; Heterozygote; Hippocampus; Human; Human Genetics; Human Genome; Huntington Disease; Huntington gene; Impaired cognition; Individual; Individual Differences; Inherited; Knock-in; Knock-out; Knockout Mice; Length; Link; Longevity; Maps; Mediating; Medical; Mental Depression; Methods; Modification; Molecular; Molecular Analysis; Motor; Motor Cortex; Mus; Mutation; Nerve Degeneration; Neurobehavioral Manifestations; Neurobiology; Neurodegenerative Disorders; Neurologist; Pathologic; Pathology; Patients; Population; Predisposition; Prefrontal Cortex; Prevention; Psyche structure; Quantitative Trait Loci; RNA; Resolution; Rest; Severities; Symptoms; System; Testing; The Jackson Laboratory; Transgenic Organisms; Translating; Validation; Variant; abnormal involuntary movement; age related neurodegeneration; aging brain; autosome; behavioral phenotyping; brain tissue; candidate validation; cognitive function; cohort; gene interaction; genetic approach; genetic resource; genome-wide; high dimensionality; human data; humanized mouse; innovation; insight; motor disorder; motor symptom; mouse genetics; mutant; nervous system disorder; neuropathology; new therapeutic target; novel; resilience; resilience factor; segregation; structural imaging; success; synergism; trait; transcriptome sequencing; translational model

PROJECT SUMMARY/ABSTRACT Huntington’s disease (HD), an autosomal dominant neurodegenerative disorder caused by a mutational expansion in a CAG repeat tract in the huntingtin (HTT) gene, termed mHTT, is characterized by abnormal involuntary movements, a severe mental decline, and emotional changes including irritability and depression. The symptoms primarily occur during prime working years (ages of 30 to 50), and there is currently no treatment to delay onset or progression. Resilience to HD, a phenomenon whereby motor and cognitive functioning is better than predicted based on genotype, is due in part to as-yet-unidentified genetic factors. These factors may provide key targets for treatment and prevention of HD and other age-related neurodegenerative diseases. However, significant barriers limit discovery of the mechanisms of resilience using human genetic methods alone because highly resilient individuals are rare, and asymptomatic carriers may escape attention or be misclassified by neurologists. Further, it is not possible to conduct longitudinal molecular analyses on human brain tissues. Animal models of HD provide a more tractable opportunity for discovery and characterization of resilience mechanisms, but they do not on their own allow us to identify the specific genes and variants that govern resilience in humans. These limitations create a critical need for innovative approaches to synergize the power of animal HD models with the wealth of medically relevant human data. The overall objective of this proposal is to identify drivers of resilience to HD motor, cognitive and survival traits by applying system genetics approaches that integrate high-dimensional molecular data from individual strains resilient to mHTT with cognitive and pathologic data collected in the same strains longitudinally to provide candidate genes that are then tested for disease modification in human HD. To this end, a novel mouse panel that incorporates a mHTT heterozygous knock-in allele expressing full-length mutant huntingtin at endogenous levels, on a segregated background of genetic diversity (BXD panel) will be generated to identify modifiers that contribute to HD resilience in a ‘humanized’ mouse population (Aim 1). Network approaches will be used to integrate these novel data with existing human HD data to identify modifiers of human HD resilience (Aim 2). Finally, these modifiers will be validated by performing in-depth neurobiological and behavioral phenotyping on new precision HD models (Aim 3). These studies will enable the discovery and validation of novel targets for promoting healthy brain aging overall and resilience to HD in particular.

项目总结/文摘