PI: Liana Apostolova
Institution: Indiana University


Biomarkers are presently the only feasible approach for diagnosing and quantifying disease-associated changes in prodromal Alzheimer’s disease (AD) during which a successful disease-modifying therapeutic intervention would realize the greatest impact. High-throughput neuroimaging and genetics have a proven track record for critically advancing our understanding of disease mechanisms and promoting therapeutic development. Grant goals are to develop a multimodal biomarker AD risk assessment tool using the prospectively collected imaging, genetic and gene expression ImaGene data set. The discovery of critical disease-related pathways will fundamentally advance our understanding of the molecular and genetic triggers of AD and bring us closer to genomic-based interventions and personalized risk assessment. The project applies advanced imaging genetics statistical approaches to achieve the following three aims: 1) identify a discovery set of AD-relevant candidate imaging and genetic biomarkers; 2) select gene expression variables with strong evidence for biological relevance to AD; and 3) develop and validate a multimodal classifier capable of accurately assessing one’s risk for future conversion to AD.