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.