Integrated multi-omics approach to identify early protein biomarkers in Alzheimer's disease and cognitive decline

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SUMMARY: The purpose of this K01 proposal is twofold: 1) to identify early protein biomarkers in Alzheimer’s disease (AD) and cognitive decline; and 2) to provide Alison Fohner, PhD with the mentorship and resources to pursue an independent research career using multi-omic and longitudinal data to improve prevention and treatment of AD. Every year, 500,000 people are diagnosed with AD in the US. AD has no cure; and between 2002 and 2012, nearly every clinical trial for new therapeutics failed. Plasma proteins are easily measured in routine care, and protein levels may reflect underlying pathology. New technology that rapidly assays thousands of proteins in large samples promises to improve protein biomarker discovery, and could lead to new strategies for early risk stratification and for novel therapeutics. This proposal leverages the extensive existing data from the Cardiovascular Health Study (CHS), an NHLBI-funded prospective population-based cohort study of 5888 White and African American men and women recruited in the early 1990s. Available CHS data include plasma protein level data on 1300 proteins, whole genome sequencing data, yearly cognitive assessments covering different functional domains, diagnostic information on AD, and stored biospecimens. This proposal aims 1) to identify plasma proteins associated with time-to-incident AD and with rate of cognitive decline; 2) to assess genetic evidence for and against causal roles of high-signal proteins in AD and cognitive decline; and 3) to estimate the association of plasma p-tau181 concentrations, a biomarker of AD pathology, with subsequent clinical diagnosis of AD and cognitive decline. This proposed research will not only advance our understanding of AD pathology, but may also identify important clinical biomarkers and therapeutic targets for AD. Dr. Fohner is an Assistant Professor in the Department of Epidemiology at the University of Washington. With her background in genomics and high-dimensional data analysis, Dr. Fohner is well-positioned to pursue the Aims of this proposal. She has composed an experienced and collaborative mentorship team, and has developed an innovative training plan that will help her achieve research independence. The research and training plans in this proposal will prepare Dr. Fohner to successfully compete for future R01 funding by enabling her to build research skills and domain expertise, to learn new analytical techniques, to forge productive collaborations, and to generate preliminary data. In summary, with the support of this K01 award, Dr. Fohner can launch a successful career developing strategies to predict, prevent, and treat AD.