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.