Recent observations in Alzheimer's disease suggest that factors, which influence the relationship between pathological features in the brain and clinical symptoms, play a significant role in the disease process. First, more than 25% of non-demented, elderly individuals have brain pathology that is indistinguishable from known Alzheimer's disease individuals. Second, among those with a clinical diagnosis of disease there are clearly """"""""fast progressors"""""""" and """"""""slow progressors"""""""". We will perform a genome-wide screen for relationship loci (rQTL) that modify the known relationship (correlation) between cerebrospinal fluid A?42 levels and case/control status, thus screening for loci that explain the observation of non-demented individuals with Alzheimer's disease pathology. With slight adjustments to our models we can also screen for loci, which modify the known relationship between cerebrospinal fluid A?42 levels and tau levels, and may explain the variation in the rate of progression of disease. For these analyses we have assembled over 2,000 samples with cerebrospinal fluid biomarker measurements, clinical evaluations, and whole-genome marker data for discovery and nearly 1000 samples with cerebrospinal fluid biomarker measurements and clinical evaluations for replication (genotyping to be completed as part of this proposal). We will then test the replicated variants for association with risk and rate of progression of Alzheimer's disease in approximately 20,000 cases and 30,000 controls (over 1900 of which have longitudinal measurements of disease progression). As demonstrated by our preliminary analyses, this promising approach will leverage the largest sample of its kind to identify genetic variation that is associated with Alzheimer's disease and Alzheimer's disease biomarkers via pleiotropic and interaction effects. This will provide insight into variation in important disease related processes such as protein aggregation and inflammatory and immune response. These findings are likely to be important for other protein aggregation and/or protein misfolding diseases.

Public Health Relevance

The broad; long-term goal of our research is to solve the complex genetic architecture of Alzheimer's Disease; which will lead to better strategies for treatment and prevention of this devastating disease. In this proposal we will test hypotheses that genetic factors influence important clinical observations; such as the observation of Pleiotropic effects of APOE e4 on cerebrospinal fluid A and tau levels; non-demented individuals with Alzheimer's disease pathology and variation in the rate of progression in clinically diagnosed Alzheimer's disease cases. We will use genome-wide marker data to detect loci that simultaneously affect cerebrospinal fluid amyloid beta and tau levels (pleiotropy); the relationships between Alzheimer's disease biomarkers (cerebrospinal fluid amyloid beta and tau) and Alzheimer's disease (referred to as rQTL); and gene-by-gene interactions. Identified loci are likely to affect both risk and/or progression of AD and will shed light on pathways connecting cerebrospinal fluid amyloid beta; tau; and Alzheimer's Disease.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
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Molecular Neurogenetics Study Section (MNG)
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Miller, Marilyn
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Brigham Young University
Schools of Arts and Sciences
United States
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Ridge, Perry G; Wadsworth, Mark E; Miller, Justin B et al. (2018) Assembly of 809 whole mitochondrial genomes with clinical, imaging, and fluid biomarker phenotyping. Alzheimers Dement 14:514-519
Maxwell, Taylor J; Corcoran, Chris; Del-Aguila, Jorge L et al. (2018) Genome-wide association study for variants that modulate relationships between cerebrospinal fluid amyloid-beta 42, tau, and p-tau levels. Alzheimers Res Ther 10:86
Sims, Rebecca (see original citation for additional authors) (2017) Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease. Nat Genet 49:1373-1384
Ridge, Perry G; Karch, Celeste M; Hsu, Simon et al. (2017) Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer's disease resilience. Genome Med 9:100
Chapuis, Julien; Flaig, Amandine; Grenier-Boley, Benjamin et al. (2017) Genome-wide, high-content siRNA screening identifies the Alzheimer's genetic risk factor FERMT2 as a major modulator of APP metabolism. Acta Neuropathol 133:955-966
Staley, Lyndsay A; Ebbert, Mark T W; Bunker, Daniel et al. (2016) Variants in ACPP are associated with cerebrospinal fluid Prostatic Acid Phosphatase levels. BMC Genomics 17 Suppl 3:439
Ebbert, Mark T W; Boehme, Kevin L; Wadsworth, Mark E et al. (2016) Interaction between variants in CLU and MS4A4E modulates Alzheimer's disease risk. Alzheimers Dement 12:121-129
Hippen, Ariel A; Ebbert, Mark T W; Norton, Maria C et al. (2016) Presenilin E318G variant and Alzheimer's disease risk: the Cache County study. BMC Genomics 17 Suppl 3:438
Allen, Genevera I; Amoroso, Nicola; Anghel, Catalina et al. (2016) Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease. Alzheimers Dement 12:645-53
Ebbert, Mark T W; Wadsworth, Mark E; Staley, Lyndsay A et al. (2016) Evaluating the necessity of PCR duplicate removal from next-generation sequencing data and a comparison of approaches. BMC Bioinformatics 17 Suppl 7:239

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