Funding Opportunities

National Institute on Aging Analysis of Alzheimer's Disease Genome Sequencing Project Data [U19]

This Funding Opportunity Announcement (FOA) is issued by the National Institute on Aging (NIA), National Institutes of Health (NIH) in response to a Presidential Initiative on Alzheimer's Disease (AD).  The overarching goals of the research are to:  (1) identify new genes contributing to increased risk of developing the disease,  (2) identify new genes contributing to protection against developing AD,  (3) provide insight as to why individuals with known risk factor genes escape from developing AD, and  (4) identify potential avenues for therapeutic approaches and prevention of the disease.  This study of human genetic variation and its relationship to health and disease involves a large number of study participants and will capture not only common single nucleotide variations but also rare copy number and structural variants that are increasingly thought to play an important role in complex disease.  The National Human Genome Research Institute (NHGRI) Large-Scale Sequencing Program (LSSP) will produce the sequence data and potentially variant call data, which will be made available to the scientific community through an NIA approved data repository.  Analysis of the sequencing data is anticipated to identify new genetic risk and protective factors in older adults at risk for AD.  Both fundamental scientific discovery and leading edge analytical approaches will likely be needed to achieve the research goals.  Therefore awards funded under this FOA are anticipated to involve research conducted by multidisciplinary teams of investigators.  The proposed study should describe a comprehensive plan to develop leading edge innovative approaches for the analysis of whole genome sequencing data to extend previous discoveries that may ultimately result in new directions for AD therapeutics.  Grant applications will be evaluated and funded based on the strongest potential to reveal novel genetic markers for AD based on comprehensive analytical methods.