As the average age of the population increases, understanding the biology of longevity and diseases of aging
is increasingly important. The key role of mitochondria in Alzheimer’s disease (AD) and pathogenic aging has
been established in studies across species and mechanistically validated using genetically engineered
models. Mitochondrial DNA copy number (mtDNAcn) changes with age and diet, in various tissues, and
across species. Higher mtDNAcn is associated with better health outcomes in aging and with increased
longevity, while decreased mtDNAcn is linked to disorders of aging including AD. However, we do not
understand the mechanistic interaction between genetic variants, mtDNAcn, diet, sex, aging and AD. Here
we propose to identify gene-by-environment interactions (GxE) that link mtDNAcn to AD- and aging- relevant
phenotypes already collected in the recombinant inbred BXD and transgenic AD-BXD mouse lines, including
longevity, memory, learning, motor, and neuroanatomical phenotypes. In Aims 1 and 2, we will test GxE, and
identify loci underlying these interactions in three “peripheral” (skin, blood, muscle) and three “central” (liver,
kidney, hippocampus) tissues. We will use previously gathered tissue from 45 BXD strains between 6- and
24-months old that had been fed either standard chow or high-fat diet, and quantify mtDNAcn. In Aim 3, we
will identify relationships between mtDNAcn, age, sex and the familial AD transgenes (5XFAD), using tissue
already collected from the AD-BXD. As part of Aims 2 and 3, we will re-produce a subset of the above strains
and carry out analysis of mitochondrial function and reactive oxygen species generation to determine the link
between mtDNAcn and mitochondrial function across tissues. In Aim 4, we will integrate our generated data
with extensive behavioral data on age-related cognitive and other behavioral and CNS changes generated
from BXD and AD-BXD. This will allow us to define loci, candidate genes, and mechanisms of AD and
longevity and to systematically test for associations with age, sex, diet, and linked changes in mitochondrial
DNAcn or function. Finally, we will integrate previously generated -omics data that we have for BXD and other
genomes (e.g., RNA-seq, meth-seq, metabolomes and proteomes) with data from large human AD and
mtDNAcn GWASs, and other existing -omics data. All results will be shared openly using robust internet
services—Mouse Phenome Database, GeneNetwork, etc. Data and workflows will be FAIR-compliant. Key
deliverables are far more quantitative, unbiased, global, and replicable data on genetic, molecular, and
environmental processes that act with mitochondria to mediate cognitive loss, AD and longevity. We will also
deliver causal molecular and mechanistic models that incorporate realistically high levels of genetic diversity—
6 million DNA variants. This work empowers in-depth, unbiased analyses of age-related functional decline
that translates to human populations. Success will provide a platform in which to test novel interventions in
this genomically- and environmentally- replicable population — so called “experimental precision medicine”.
