Lindsay Farrer - US grants

The mission of the Framingham Heart Study?Brain Aging Program (FHS-BAP) is to conduct, facilitate and promote high impact research on the etiology, pathogenesis, diagnosis, treatment, and prevention of Alzheimer disease (AD) and related disorders. The Administrative Core serves as a focal organizational point to organize and harmonize research activities of the Clinical, Neuropsychology, and Data Cores and Projects 1-3 to maximize synergy, efficiency and productivity. In the proposed funding period, the Administrative Core will guide the extension and expansion of the rich FHS data resource and establish a management infrastructure that will greatly increase the sharing and utilization of this resource by other researchers worldwide. To accomplish these central goals, the Administrative Core will serve as the interface between internal FHS-BAP activities and external entities, and ensure that FHS-BAP activities meet all Core and project milestones and are consistent with the National Institute of Aging (NIA) AD research mission and in full compliance with all human subjects, and scientific integrity policy requirements of the NIH. We will form an External Advisory Committee (EAC) to advise on the formulation and execution of FHS-BAP priorities and proactively identify opportunities that will keep us on the forefront of forward-thinking science. Key to executing the Administrative Core's mission is to provide appropriate financial oversight of the entire FHS-BAP, track the disposition of materials provided and the outcomes of FHS-BAP supported research (publications and funded activities) and present progress in meeting the stated aims to the EAC feedback will be critical in assessing effectiveness of operational activities in meeting research priorities and their oversight and continuous input for improvements help ensure we achieve our stated goals. Additionally, consideration and coordination of FHS-BAP day-to-day operations with other FHS research programs (e.g., NHLBI funded FHS contract to support core health exams of FHS cohorts) and other ancillary studies that are collecting data from FHS participants at the FHS clinic based in Framingham, MA will be done in collaboration with an Internal Advisory Board (IAB), consisting of locally based BU faculty to better address time-sensitive logistical issues. The Administrative Core will also promote new innovative AD research using data generated by the FHS-BAP through a pilot project program that will encourage grant applications from junior faculty and postdoctoral fellows, as well as from established faculty who are new to the AD field, throughout BU and possibly other institutions. Additional efforts to foster innovative AD research will be facilitating cross-core/project interactions by promotion of collaborations between FHS-BAP investigators with local, national, and international research programs, by representing the FHS-BAP at scientific meetings and publicizing FHS-BAP data access and use through the Data Core and coordinating with the BU Alzheimer Disease Center to host seminars and symposia focused on AD research.

ABSTRACT A portion of the genetic component of Alzheimer disease (AD) is explained by genes identified by positional cloning, targeted gene analysis, GWAS and next generation sequencing approaches. With few notable exceptions, the functional variants in these genes and precise pathogenic mechanisms by which these variants lead to AD are unknown. We will continue to direct our efforts on persons of African ancestry (AA), a group with a high incidence of dementia but studied much less than persons of European ancestry (EA). We will leverage rich AD-related endophenotype and other risk factor data from the largest collection of AAs assembled by us, the Alzheimer Disease Genetics Consortium (ADGC) and Alzheimer Disease Sequencing Project (ADSP) for genetic studies of AD to promote further discovery of AD-related genes and variants as well as their mechanisms of action leading to AD. Previously, we demonstrated significant association of AD with SORL1, AKAP9, and other genes in AAs using standard and novel analytic approaches. In the next project period, we will perform RNA sequencing on brain tissue obtained from more than 140 AA AD cases and controls, and analyze these data using state-of-the-art bioinformatics approaches to assess the influence of AD risk variants on gene expression. We will construct AA-specific Bayesian elastic-net models of genetically- mediated gene expression using the AA brain cohort genotype and RNAseq data. These models will be applied to AA cohorts from the ADGC and ADSP (total n=9,200) using PrediXcan to construct AA-specific expression predictions In addition, we will identify non-genetic mediators of genetic influences on AD risk by (1) performing gene ? environment GWASs of AD in AAs using data for several established AD risk factors using data from the ADGC/ADSP, UK Biobank and Million Veterans Program; (2) applying mendelian randomization to assess the causal relationship between diabetes, cigarette smoking, hypertension, hypercholesterolemia, obesity and AD in AAs using existing GWAS summary statistics for these traits in AAs; and (3) conducting a phenome-wide association study (PheWAS) to identify pleiotropy by deriving a polygenic risk score for AD in AAs and testing its association with a range of phenotypes within the UK Biobank. We will also perform in vitro experiments (including knockdown by siRNA, gene and protein over-expression, immunofluorescence, and ELISA) in human neuronal cells and induced pluripotent stem cell-derived neurons containing AA AD risk variants inserted by CRISPR to understand how genetic variation in AKAP9 and other promising genes leads to AD-related pathologic states as well as to provide models that can be used in small molecule drug screens for potential AD treatments.

Many recent advances in genetics and genomics technologies and rapid growth in knowledge of genetic risk factors for Alzheimer disease (AD) reinforce the importance of and opportunities for incorporating genetic information and designs into AD research. The Genetics & Molecular Profiling (GMP) Core will support genetics and `omics research by ADRC investigators, trainees and established investigators who are ?breaking in? to AD research, and to build foundations for translational studies using ADRC resources. Given the centrality of genetics and `omics data to diverse scientific areas, unrealistic expectations that most AD researchers are capable and can afford to generate such data, and importance of avoiding costly duplicative data generation in order to preserve limited and precious specimen resources, the GMP Core will generate an array of genetic and `omic data. Although the GMP Core is a new component of the ADRC, it will build on our work of genetic and molecular characterization of BU ADC participants and other cohorts that has led to numerous important discoveries and greatly increased our understanding of mechanisms and biological pathways leading to AD. We will continue to serve as a centralized resource for the organization and analysis of genetic data within the ADRC and ADRC affiliated projects by providing an infrastructure needed to coordinate molecular research efforts that will lead to a better understanding of genotype-phenotype relationships for dementia and related endophenotypes. Specifically, the GMP Core will (1) process, extract DNA and RNA, store and distribute genetic material extracted from biological specimens (e.g., blood, brain, saliva) obtained from ADRC participants; (2) generate genome-wide array, DNA and RNA sequence, epigenetic and lipidomic data for use by ADRC and other BU investigators, as well as the scientific community; (3) track the collection and usage of genetic material; (4) manage all genetic and `omic data in collaboration with the Data Management & Statistics (DMS) Core; (5) maintain an integrated genetic and `omic database includes all genetic and `omic data generated from BU ADRC samples, as well as working libraries of extant genetic and `omic data; these data will be available with proper permissions as a resource for genetic analyses with guidance from the core investigators. The GMP Core will also facilitate access to an extensive set of genetic and genomic data from extant datasets that are available to the Core investigators including individual level and/or summarized data from the ADGC, ADSP, ADNI, AMP- AD, and UK Biobank; and (5) provide support for designing genetic and genomic studies, as well as for data analysis. In line with our vision for precision medicine, this profiling integrated with the extensive characterization performed in the Clinical, Biomarker and Neuropathology Cores will facilitate both agnostic and hypothesis- driven research. The Core will also partner with existing investigator-initiated research at Boston University (BU) and with the other Cores to strengthen existing programs and accelerate the incorporation of genetics and `omics into dementia research conducted by ADRC-affiliated as well as other BU investigators.

ABSTRACT Most discoveries of the genetic basis of Alzheimer disease (AD) were made in Caucasians of European ancestry (EAs) and required samples between 10,000 and 75,000 subjects to detect them. We and others have demonstrated that risk variants for AD can be identified in ethnic groups of a more homogeneous genetic background using samples comprising several thousand or fewer subjects. Studies of non-EA populations also afford the opportunity to discover variants that are rare or display a smaller effect size in EAs due to modification by other genes and environmental factors. We will direct our efforts to Koreans, a population which has a high prevalence of AD, but, like other East Asian populations, have not been included in large DNA sequencing studies and for whom little is known about the genetic basis of AD other than association with APOE. They have maintained a distinct genetic profile that reflects a unique component resulting from genetic drift and new mutations during the last two millennia. We will leverage the genetic architecture of Koreans to promote discovery of AD-related genes and variants by studying rare and common genetic variation, and the impact of AD- associated variants on gene expression. To accomplish our scientific goals, we will study AD cases and controls who are ascertained and followed longitudinally at the National Center for Research on Dementia at Chosun University located in the southwestern city of Gwangju, Republic of Korea, and obtain from each participant a blood specimen and phenotypic data including clinical exam, demographic, medical history and lifestyle information. In addition, most subjects will undergo an extensive neuropsychological test battery developed specifically for Koreans and a brain MRI scan. The cohort will comprise an unrelated group of 2,000 AD cases and 2,000 elderly controls ascertained from existing patient registries and prospectively identified subjects all of whom will have GWAS data available generated using a microarray designed for Koreans. DNA specimens from all subjects will be whole genome sequenced (WGS). WGS data will be processed using pipelines established by the Alzheimer Disease Sequencing Project. We will conduct a genome-wide association study for AD using methods for single variant and gene-based tests based on models that adjust for age, sex and population substructure. Top-findings will be replicated in datasets of other ethnicities assembled by the Genomics Center for Alzheimer Disease for the Alzheimer Disease Sequencing Project using trans-ethnic analysis and approaches that focus on variants affecting protein structure, transcription, and gene expression. Next we will perform a GWAS for age at onset and brain imaging and cognitive endophenotypes. Finally, we will identify gene targets of the top-ranked SNPs by performing expression quantitative trait locus analysis using public datasets containing genotype and gene expression data in brain and other tissues, and establish functional connections among the top-ranked SNPs and genes using pathway analysis and co-expression network analysis. We expect this project will identify novel targets for development of new drugs to treat or retard mechanisms leading to AD.

The lack of an effective treatment for Alzheimer's disease (AD) has led to a call to detect the disease earlier in its course. However, AD's insidious onset that can span many years, adds complexity to making an early diagnosis. It is widely accepted that even among individuals with well-documented AD risk factors (e.g., age, sex, low education, APOE ?4, high cardiovascular risk, high plasma A?40/42 ratio, tau pathology), diagnosis is not inevitable. By way of its longstanding investigation of cognitive aging and dementia/AD, the Framingham Heart Study (FHS) has amassed arguably one of richest databases acquired from a community-based cohort. Across its multi- generational cohorts, participants have undergone up to 7 decades of regular health examinations that document many co-morbid features linked to future risk of late life cognitive decline and dementia. Because AD- related processes are likely initiated many years before onset of disease symptoms, one primary objective of this project is to better elucidate mid-life vascular and inflammatory traits that are associated with AD risk. Additional unique goals of this project are to leverage this unprecedented resource to identify factors associated with longitudinal trajectories of cognitive decline, with longitudinal trajectories of neurodegeneration as measured by MRI, and with resilience to developing cognitive decline. To achieve these goals, we will first apply prediction modeling approaches to identify measured and derived traits associated with AD and related endophenotypes. From the extensive list of demographic, lifestyle, vascular/metabolic, plasma and omics measures (including whole genome, transcriptome, and methylome) already captured as part of the FHS, we will use traditional model building (guided by a priori determined AD pathways) and data driven approaches to identify traits associated with (a) MCI, dementia and AD, (b) longitudinal trajectories of cognitive decline, (c) longitudinal trajectories of structural MRI indices, and (d) AD-related neuropathological indices. We will perform pleiotropy GWAS to identify shared genetic underpinnings of significantly correlated traits in initial analyses and test whether using digital neuropsychological phenotypes strengthen findings. Next, using the same database of previously measured traits, we will apply prediction modeling approaches to identify measured and derived traits associated with cognitive resistance, as defined by lack of conversion to dementia. Finally, we will identify vascular and inflammatory moderators of genetic influences by performing Mendelian randomization to assess the causal relationship between vascular risk factors (e.g., blood glucose, lipid fractions, blood pressure, BMI, cigarette smoking) and inflammatory markers (e.g., CRP, IL-?, TNF?, IL6) and AD using existing GWAS summary statistics. For vascular and inflammatory risk factors with significant causal effects, we will assess gene ? environment interactions with variants in targeted genes previously implicated in AD. The novel factors identified in this project will inform AD prognostication as well as provide insight into disease mechanisms and new targets for prevention and therapy, heralding a personalized medicine approach to AD.

Since 1976, the Framingham Heart Study (FHS) has surveilled participants for incident dementia, initially, in the Generation 1 participants, starting 1979 in the Generation 2 cohorts and in 1994 with the smaller multi-ethnic Omni Generation 1 cohort. As the oldest of the Generation 3 and Omni Generation 2 move into the age of dementia risk, we extended surveillance to these two younger cohorts. Baseline and repeat neuropsychological (NP) assessments and brain magnetic resonance imaging (MRI) scans have been conducted since 1999 on the Gen 1, Gen 2 and OmniGen 2 cohorts and since 2008 with the younger cohorts. Importantly, over nearly 7 decades, FHS has collected many co- morbid features linked to future risk of late life cognitive decline and dementia across these cohorts when they were early to middle age. Complementing the health and lifestyle data is the availability of genetic and peripheral biomarker data. Further, beginning in 2005, digital capture of spoken responses was added to NP testing. This was extended to written responses in 2011, allowing quantification of spoken and written responses at levels of granularity that can detect preclinical cognitive changes that traditional NP test scores cannot measure. Previously, we have capitalized on the multi-generation uniqueness using genome-wide approaches to discern novel genetic associations for AD risk and AD-related traits that were not identified in datasets up to 20 times larger. The primary goal of this FHS Brain Aging Program (FHS-BAP) is to continue dementia surveillance, extend longitudinal characterization of cognitive phenotypes and brain structure, bring added resources to the brain donation program including neuropathological examination, in the FHS cohorts in order to identify new and expand on known AD-related genetic and other risk factors and biomarkers and to pursue innovative research about the vascular and inflammatory basis of AD. Another central objective of FHS-BAP is to facilitate more widespread sharing of this extraordinary AD data resource with the broader scientific community. Under a new organizational structure, Administrative, Clinical, Neuropathology and Data cores will provide a formal management and infrastructure to continue incident dementia surveillance, NP and MRI assessments of surviving participants of all FHS cohorts, and perform neuropathological examination of brains obtained through the FHS brain donation program. The FHS-BAP will feature three inter-related projects that have a focus on vascular and inflammatory contributors to AD. One project will identify factors that are associated with AD risk and resilience using longitudinal analyses of FHS data including genetic, various `omic genetic, clinical, imaging, lifestyle and other traits. A second project will investigate the link between AD genetic vulnerabilities and chronic peripheral inflammation. A third project will determine genetic and protein alterations of complement-related genes and glial cell phenotypes that modulate cognitive trajectories and neuropathological profiles. Finally, this program will promote using FHS-BAP data, especially by early-stage and non-AD investigators through a pilot projects program and through enhanced and proactive data sharing efforts.