Nicole Schupf - US grants

This study will investigate genetic risk factors for dementia in individuals with Down syndrome (DS) and their relatives. The brains of virtually all adults with Down syndrome show high densities of senile plaques and neurofibrillary tangles characteristic of the pathological changes of Alzheimer disease (AD), and individuals with DS are at increased risk for clinical dementia. A shared genetic susceptibility to DS and AD is supported by the findings of increased prevalence of DS births to women who themselves have AD or whose relatives have AD, by findings of increased frequency of AD in relatives of individuals with DS, and by linkage of early-onset familial AD to chromosome 21. The gene for beta-amyloid precursor protein (APP) has been localized to chromosome 21 and the early occurrence of AD pathology in adults with DS has been attributed to increased expression of beta-amyloid. However, not all individuals with DS and AD pathology dement. Mosaicism for trisomy 21 may be associated with reduced expression of beta-amyloid and later age of onset of AD. In addition, mutations in the gene for APP have been shown to cosegregate with AD in several families with early onset AD. We will determine if these or related mutations in the APP gene are associated with increased expression of clinical dementia in individuals with Down syndrome or with a history of early-onset AD in their families. Subjects for this study will be drawn from a larger ongoing study of the familial aggregation of Down syndrome and Alzheimer disease. We will study the first 150 individuals with DS and their parents. Data from the larger study will provide information on the occurrence of AD and related disorders in first- and second-degree relatives of DS probands, on the medical status and functional skills level of DS probands and on the occurrence of clinically significant regression in DS probands consistent with a diagnosis of dementia. We will determine DS karyotype (trisomy, translocation, mosaicism) and estimate the age-specific prevalence of mosaicism for trisomy 21. We will determine whether the risk for dementia and age of onset of dementia is correlated with the level of mosaicism. We will screen all individuals with DS and their parents for mutations in the coding region and promoter sequences of the APP gene and estimate the prevalence of APP mutations. We will determine whether increased risk for clinical dementia in adults with DS is associated with APP mutations by comparing DS cases with and without mutations in terms of the lifetime cumulative incidence of dementia. We will determine whether increased risk for AD in relatives of DS probands is associated with APP mutations by comparing DS cases with and without mutations in the APP gene in terms of the cumulative incidence of AD in their first- and second-degree relatives.

DESCRIPTION (provided by applicant): The overall aim of this project is to investigate the contribution of polymorphisms in genes involved in estrogen biosynthesis and estrogen receptor function to rate of cognitive decline and risk of Alzheimer's disease (AD) in women with Down syndrome (DS). Prior studies in the general population suggest that the dramatic declines in estrogen levels following menopause may play an important role in the etiology of AD. Among women with DS, the average age at onset menopause is 46 and the average age at onset of AD is 50-55. Thus, in women with DS, the short interval between menopause and AD provides a unique opportunity to examine the influence of endogenous estrogen activity on disease risk in a prospective study. We hypothesize that women with genotypes associated with reduced levels of bioavailable E2 will have earlier onset and increased risk of AD. During our current study of women with DS, we have made several key observations: (a) earlier age at menopause was associated with earlier onset of AD in women with DS;(b) high levels of sex-hormone binding globulin and low levels of bioavailable estradiol were associated with earlier onset and increased risk of dementia. We now propose to expand our investigation of endogenous estrogen activity with new laboratory studies to identify genetic factors that may modify estrogen levels or estrogen activity and influence risk for AD. We will conduct a 5-year longitudinal study of in 336 women with DS, 40-59 years of age at baseline, followed at 18-month intervals. We will examine 5 candidate genes: ERalpha, ERbeta, CYP17, CYP19, and HSD17B1. We will determine whether polymorphisms in the genes for ERalpha (P and X), ERbeta (G), Cyp17 (Allele A2), CYP19 (TTTA repeat length) and HSD17B1 (A Allele) are (1) associated with differences in baseline levels and rates of change over time in systemic gonadal and steroid hormones;(i.e. serum estradiol, bioavailable estradiol, estrone, sex-hormone binding globulin, dehydroepiandrostcrone, follicle stimulating hormone and progesterone);(2) are predictors of the rate of decline in memory and related cognitive functions;and (3) are associated with earlier onset or increased risk of AD. The proposed studies will clarify biological mechanisms relating variations in estrogen to the development of AD.

The Epidemiology, Database Management, and Statistics (EDMS) Core will provide the central epidemiologic, data management and biostatistical resources for the projects and other Cores. The EDMS Core will participate in Core-to-Core acitvities by weekly meetings with the other Core leaders and the the program coordinator to review and discuss all data-related issues, including cohort follow-up and retention, data completeness, and data retrival. The Core has three components. Data generated by each of the other cores and research projects will be transferred to the Database Component for entry and storage in an integrated SIR/DBMS data management system designed to meet all the needs of the program project with respect to cleaning, organization and retrieval of data for planned analyses. The activities of the Database Component will be carried out on a networked system of computers especially configured for data management operations. The Epidemiology Component will provide expert consultation in epidemiolgic methods, hypothesis testing, and in the interpretation and presentation of research findings. It will provide guidance on methodological issues such as subject classification on risk factor, outcome and related variables, development of derived variables, matching, bias and confounding. These activities will be carried out by means of bi-weekly meetings with Core statisticians and individual project investigators on a rotating basis and by a monthly joint meeting of project investigators to review manuscripts in preparation. The Statistics Component will be responsible for the planning and implementation of all analyses conducted by investigators. Core Statisticans, in collaboration with the Clinical and Brain Imaging Cores, will provide common summary outcome measures related to cognitive and functional performance, and to brain imaging results and will employ a core set of strategies for the analysis of large prospective multivariable and multivariate longitudinal datasets that pose common problems for the projects. By centralizing data management, epidemiological and statistical oversight in the EDMS Core, we will ensure the consistency and facilitate interaction of the projects with respect to uniform definitions of variables, data summarization, choice of tests, model building and interpretation of study results.

DESCRIPTION (provided by applicant): The overall theme of this new project is to establish and validate blood- and imaging-based biomarkers associated with the risk and progression of late onset Alzheimer's disease (LOAD), mild cognitive impairment (MCI) and the rate of cognitive decline in late life. We also propose to develop a framework with which we can understand how biomarkers interact and how they fit into the temporal sequence from healthy aging to dementia. This proposal is built on two decades of epidemiological research and systematic data collection in the multi-ethnic, Washington Heights, Hamilton Heights, Inwood, Columbia Aging Project (PO1AG07232). Over the past 20 years, we have investigated the rates of LOAD, MCI and cognitive decline in this urban community in northern Manhattan. We have investigated environmental, health-related and genetic risk factors of disease and predictors of disease progression by collecting longitudinal data on cognitive performance, emotional health, independence in daily activities, blood pressure, anthropometric measures, cardiovascular status and selected biomarkers in this elderly, multi-ethnic cohort, including lipids, amyloid peptides, sex hormones, homocysteine, insulin and C-reactive protein (CRP), and MRI. We have reported that the rates of disease and the frequency of disease risk factors vary across ethnic groups. We have identified one of the largest, multi-ethnic groups of incident LOAD cases facilitating studies of disease progression. Clinical and genetic data as well as biological resources are present for several thousand individuals. Biomarkers, cellular, biochemical or molecular alterations measurable in human tissues, cells, or fluids or by radiological means, are typically chosen because they are directly or indirectly in the causal pathway of disease. The emergence of structural and functional brain imaging has revolutionized epidemiological studies, particularly those using biomarkers for Alzheimer's disease. Positron emission tomography brain imaging using 11C Pittsburgh compound B is considered an in vivo measure of brain amyloid plaque load, while structural MRI, especially changes in brain volume and cerebral blood flow (CBF), can be considered an in vivo measures of neurodegeneration. In this new proposal, we will focus this longitudinal investigation on two sets of blood biomarkers that not only show consistent and robust associations to the risk of LOAD, MCI and cognitive decline, but that address the putative mechanisms related to amyloid burden and insulin resistance. We will take full advantage of the prospective design in this multi-ethnic cohort and the clinical, biological and brain imaging data collected to address six major hypotheses. The first two primary specific aims consider blood biomarkers as not only predictors of cognitive decline, MCI, LOAD and LOAD progression, but also as intermediate steps in the disease pathway, including neurodegeneration and cerebrovascular burden (MRI) and amyloid plaque load (PIB). In the last primary specific aim, brain imaging variables are predictors and cognitive decline, MCI, LOAD as well as LOAD progression are main outcomes.

DESCRIPTION (provided by applicant): The Long Life Family Study (LLFS), established in 2005 in response to an NIA RFA, enrolled families enriched for exceptional longevity (EL), to discover factors that contribute to healthy aging and survival. From 2006 to 2009, LLFS enrolled 539 sibships (G1), their offspring (G2) and spouses (total 4,953). Comparison with a referent cohort reveals that LLFS families have strong exceptional clustering of EL. The G2 offspring have a variety of Healthy Aging Phenotypes (HAPs), defined as an unusually low age-specific prevalence of one or more specific conditions or risk factors, compared to population-based cohorts suggesting enrichment of shared (possibly genetic) protective effects in LLFS families. In the second funding period (2010-2013), we conducted a 2.5 million SNP GWAS (dbGaP phs000397); developed a high-throughput technique and sequenced ~450 candidate genes and replicated many variants and found additional ones associated with Healthy Aging Phenotypes (HAP) and longevity. 54% of LLFS G1 and 92% of G2 remain alive. Participant retention has been 94%. We now propose a third funding period to conduct a second in-person examination (V2) to prospectively study rates of change in HAPs with age and identify genetic and other factors contributing to HAPs and longevity. We hypothesize that EL and HAPs entail common and rare variants that individually have modest effects, but which in combinations strongly influence longevity and specific HAPs, and may only be detectable in family studies enriched for HAPs, such as LLFS. HAPs evaluated at the initial in-person visit show strong linkage peaks which are not explained by common haplotypes interrogated by GWAS (HLODs ranging from 6.0-45.1). These are likely driven by rare, lineage-private alleles that will only be found by sequencing specific families, and may point to important new biology. Specific Aim 1 is to conduct a second in-home examination on all surviving LLFS participants. Specific Aim 2 is to analyze cross-sectional and longitudinal phenotypes. The goal is to identify pathways for EL and HAPs by characterizing the shared and distinct LLFS phenotypes and environmental factors. We will characterize individual longitudinal patterns of HAPs to identify subgroups showing similar patterns and exceptional phenotypes. We will test whether these HAPs are heritable, and test for differences with internal and external referent groups. Specific Aim 3 is to find genes/variants associated with cross-sectional and longitudinal phenotypes using a) Whole Exome Sequencing to comprehensively search for coding variants associated with HAPs and EL and b) Targeted Regulatory Sequencing of regions under linkage peaks for HAPs in selected families showing the strongest linkage evidence. Specific Aim 4 is to replicate our genetic and epidemiological findings in other aging study cohorts. This study could lead to the discovery of pathways and potential therapeutic/prevention targets affecting HAPs and EL. A Data Management and Coordinating Center and 4 Field Centers comprise the major components of the LLFS. This renewal application is submitted by the Duke Uni./Uni. of Southern Denmark Field Center.

DESCRIPTION (provided by applicant): By age 40 years, individuals with Down syndrome (DS) show the neuropathological changes of Alzheimer's disease (AD) and have a high risk for dementia, but little is known about the biomarkers that may predict clinical onset or reflect disease progression. This study focuses on a longitudinal and multidisciplinary determination of key biomarkers that are likely to define this progression, including levels and rates of change in blood based biomarkers such as ?-amyloid peptides, protein and lipid profiles, and measures of amyloid and tau concentration in cerebrospinal fluid, neuroimaging-based changes and genetic polymorphisms. Using a neurocognitive battery that we have developed and tested, systematic profiles of longitudinal stability and of decline will allow us to define dementia status, includin Mild Cognitive Impairment in DS (MCI-DS), and characterize progression in clinical status. Previously generated protein, inflammatory and lipid signatures will be examined, as well as amyloid and tau profiles in cerebrospinal fluid (CSF). Imaging biomarkers will include structural MRI components and PET studies of brain amyloid uptake. Analysis of MRI imaging biomarkers will include longitudinal measures of atrophy, white matter abnormalities and intrinsic network connectivity paradigms. Amyloid positron tomography will delineate regional and whole brain uptake of amyloid. Polymorphisms in candidate genes for AD and related biomarkers will be studied as potential modifiers of risk and their relation to beta amyloid, proteomic, lipidomic and imaging biomarkers examined. Relationships among demographic, clinical, blood based and CSF biomarkers, imaging measures, and genetic variants will be examined to develop the most valid indicators of preclinical and early stages of AD. Importantly, the data and the biological samples will be archived and banked to establish a resource to be shared with other scientists. Collectively, our investigators have a combined clinical and research experience involving over 1500 patients (30% demented), over 850 banked blood samples, 500 DNA samples, and 50 imaging studies. Further, team investigators have previous experience with all methods that will be included in this new project. Thus, this application brings together a group of co-investigators with established expertise in studies of DS and makes available a combined cohort of 280 participants.