Genomic Architecture of a Key Alzheimer's Disease Mimic: CARTS

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Brain diseases other than Alzheimer’s disease (AD) are common but understudied causes of dementia. A particularly prevalent subtype of non-Alzheimer’s dementia is termed hippocampal sclerosis dementia, or cerebral age-related TDP-43 with sclerosis (CARTS). This neuropathology (NP) defined disease, which is often misdiagnosed clinically as AD, affects ~20% of the elderly, with substantial impact on cognition. The long-term goal is to resolve the genomic factors that modulate CARTS severity and heterogeneity. To accomplish this, we will establish, test, and apply a robust pipeline to elucidate the mechanisms influenced by genetic risk factors for CARTS, factoring in other non-AD brain pathologies. This requires a seasoned, multidisciplinary team with expertise in NP, molecular biology, neuroimaging, “large data” analyses, and, in particular, statistical genomics. The central hypothesis, based on considerable preliminary data, is that alleles modifying CARTS risk that were discovered via candidate gene and genome-wide association studies (GWAS) are proxies for phenomena more directly involved in disease pathogenesis. To test this hypothesis, the team will execute the following Specific Aims: 1. Develop and validate a classification framework to analyze the genetic drivers of CARTS. The proposed effort to optimize classification of CARTS for genotyping will test and validate a revised set of pathology-based criteria to differentiate CARTS, AD-related TDP-43 pathology, and brain arteriolosclerosis (B- ASC) to refine understanding of disease-defining “border zones.” Disease severity will be operationalized for use as a quantitative trait, and rubrics for disease subtypes will be developed for correlation with genomic studies. 2. Construct a robust and harmonized ‘omics database and localize genetic regions influencing CARTS. Genetics data augmented with rich NP endophenotypes will enable discovery and refinement of novel insights regarding the mechanisms driving CARTS dementia. Large-scale datasets (NACC, ADGC, ADNI, ADSP, AMP- AD) will be aggregated and harmonized to test the genetic drivers of clinical and NP-based CARTS endophenotypes, prioritizing subtype-specific candidate genetic regions. 3. Develop a systems biology analytic pipeline that extends beyond DNA variation to establish and test candidate functional molecular outcomes of specific gene variants/regions that are associated with CARTS pathology. Most GWAS findings are not causal but rather proxies for true underlying genetic influences of disease manifested through mechanisms that include (a) expression quantitative trait loci (eQTL), (b) differential isoform splicing QTL (sQTL), (c) brain imaging QTL (iQTL), and (d) protein QTL (pQTL). These will be detected with recently developed statistical methodologies. Successful completion of the aims will produce mechanistic insights into CARTS, potentially leading to new therapeutics. The proposed studies are distinct from prior efforts, exploiting next-generation sequencing, focusing on a common, yet recently characterized brain disease (CARTS). We will deposit results online via NIAGADS for use by the research community.