Timothy J. Hohman, Ph.D. - US grants

? DESCRIPTION (provided by applicant): This project will identify genetic factors that predict individual resilience to cognitive impairment arising from Alzheimer's disease (AD) or cerebrovascular disease. At autopsy, approximately 30% of cognitively normal individuals have the pathological features of AD or cerebrovascular disease. Yet, to date very little research has focused on the genetic factors that might contribute to such resilience. The objective of this project is to delineate the genetic architecture of asymptomatic AD. The identification of such novel genes will provide targets for clinical intervention aimed at activating natural biological defenses to neuropathology. This work will apply an innovative method to calculate predicted-gene-expression levels rather than relying solely on genome-wide association study (GWAS) analyses. I will also leverage 2 autopsy datasets: the National Alzheimer's Coordinating Center (n=882) and the Religious Orders Study/Memory and Aging Project (n=954). My mentorship team has extensive experience with these datasets and will provide expert guidance through the research methods and parallel training plan. My central hypothesis is that genetic effects will predict cognitive resilience to the damaging effects of AD and cerebrovascular pathologies. Based on this hypothesis, the primary aims of this application will identify and replicate genetic effects that (1) predict cognitive resilience to AD pathology, and (2) predict cognitive resilience to cerebrovascular pathology. The complementary training plan will equip me with the skills necessary to build out an independent research career focused on genetic resilience by emphasizing the following training content areas: (1) neuropathology, (2) advanced bioinformatics to bridge the gap from genotype to gene expression, and (3) the clinical characterization of AD and vascular dementia. The mentor team is made up of experts in each of these content areas. Their expert training will be augmented by the interdisciplinary training program at the Vanderbilt Memory and Alzheimer's Center, and the cutting edge computational and genomic resources available at Vanderbilt University Medical Center. Together, these practical and intellectual resources provide the ideal training environment. My primary mentor, Dr. Angela Jefferson, has a strong funding history and all the financial and intellectual resources needed to support my transition to independence. These extensive resources will allow me to dedicate 100% protected effort as an Assistant Professor to focus on research and career development. This will ensure that I am fully prepared to compete for independent funding (R01) over the course of the proposed award period.

Abstract As the population ages, late-onset Alzheimer's disease (AD) is becoming an increasingly important public health issue. Clinical trials targeted at reducing AD progression have demonstrated that patients continue to decline despite therapeutic intervention. Thus, there is a pressing need for new treatments aimed at novel therapeutic targets. A shift in focus from risk to resilience has tremendous potential to have a major public health impact by highlighting mechanisms that naturally counteract the damaging effects of AD neuropathology. Interestingly, at autopsy, approximately 30% of cognitively normal individuals have the pathological features of AD. Research from both our group and others has begun to uncover genetic factors that explain some of the observed disconnect between neuropathology and clinical dementia. However, small sample sizes have limited advances in characterizing the heritability and genetic architecture of resilience in a comprehensive manner. Therefore, this project will perform a large, comprehensive analysis of genetic resilience by integrating in vivo biomarker and autopsy data into a unified model of resilience. We propose to leverage a Vanderbilt resource called the Resilience from Alzheimer's Disease (RAD) database to uncover novel protective genetic effects. In RAD, we have developed and validated continuous metrics of resilience that quantify the degree to which an individual is resilient to both the cognitive deficits and the neurodegeneration associated with AD neuropathology. Our strong interdisciplinary team is uniquely positioned to characterize the genetic architecture of resilience leveraging the infrastructure and rich data resources of the AD genetic consortium and the AD sequencing project. We will identify and replicate common and rare genetic variants that predict protection from cognitive impairment and protection from neurodegeneration. Additionally, we will integrate known sex differences in the downstream consequences of AD neuropathology to identify sex- specific genes and pathways that promote resilience. The genes and pathways identified will offer novel therapeutic targets for intervention aimed at activating compensatory mechanisms that confer resilience to the damaging effects of AD neuropathology.

As the population ages, late-onset Alzheimer's disease (AD) is becoming an increasingly important public health issue. AD disproportionately affects women. Of the more than 5 million people in the United States afflicted with this disease, two-thirds are women. Women with AD have more neuropathology than men with AD, have more severe cognitive symptoms, and more severe neurodegeneration, suggesting that the disease affects male and female brains in different ways. Thus, a focus on sex differences in AD is essential to move the field towards effective interventions. The identification of sex-specific genetic drivers of AD neuropathology and cognitive decline could transform the way treatments are administered, and be a critical step towards personalized interventions for AD. Research from both our group and others has begun to uncover genetic factors that explain some of the observed discrepancies between males and females, specifically in terms of neuropathology and cognitive decline. To advance the field, additional genetic effects must be discovered and the underlying mechanisms of sex-specific pathways of injury must be examined. The objective of this project is to identify and replicate genetic effects that act in a sex-specific manner to drive the neuropathological presentation and clinical progression of AD. The present proposal will advance our understanding of sex- specific genetic contributors to AD by leveraging 8 existing in vivo biomarker cohorts (n=3,433) and 6 existing autopsy cohorts (n=4,821) to assess genetic associations with AD neuropathology and cognitive decline. The outcome of this project will highlight new candidate pathways, and begin the process of characterizing the mechanisms by which genetic variation among males and females affects the risk and clinical symptoms of AD. The sex-specific pathways identified will offer therapeutic targets and help move the field towards personalized interventions that consider an individual's sex and neuropathological presentation.

Abstract Vascular endothelial growth factor (VEGF) is a protein that has been implicated in protection against Alzheimer's disease (AD). High levels of cerebrospinal fluid (CSF) VEGF are associated with slower rates of cognitive decline and slower rates of brain atrophy. Furthermore, the neuroprotective effects of VEGF are particularly strong among individuals who are harboring high levels of AD neuropathology, suggesting VEGF may protect against the clinical consequences of AD. Indeed, when treating the hippocampus of AD mice with stem cells expression VEGF, the memory deficits associated with AD are reversed. Yet, the development of VEGF as a therapeutic target has been limited due to the large number of biological process impacted by VEGF signaling. The VEGF family consists of 5 ligand genes, 3 known tyrosine-kinase receptor genes, and 2 modulating receptor (neuropilins) genes. Interactions between this diverse set of ligands and receptors drive vastly different signaling cascades. Such biological variation provides an exciting opportunity to interrogate the various VEGF pathways through targeted genomics and proteomics. This proposal will seek to identify the VEGF signaling molecules that most strongly predict neuroprotection, and clarify the pathways that underly the beneficial effects of VEGF. We will leverage advanced genomic and proteomic approaches using human samples from well characterized longitudinal cohort studies of aging, with a particular focus on gene and protein expression in brain tissue. Our multi-disciplinary team is uniquely positioned to perform this detailed analysis of VEGF signaling by leveraging the Resilience from Alzheimer's Disease (RAD) database, which includes a harmonized and validated continuous metric of resilience across 8 large cohort studies of AD. In RAD, we have quantified the degree to which an individual is resilient to the cognitive deficits associated with AD neuropathology, providing the ideal phenotype to evaluate the effects of VEGF. The RAD includes genotype data (n=3037), gene expression data from brain tissue (n=588), and access to stored brain tissue for novel proteomic analyses (n=1433). This proposal will first perform a comprehensive analysis of VEGF ligand and receptor genes in brain tissue to identify which gene isoforms mostly strongly relate to resilience. Second, we will perform a detailed proteomic analysis in which we perform comprehensive measurement of all VEGF ligand and receptor proteoforms, including post-translational modifications, to clarify VEGF effects in brain at the protein level. Finally, we will leverage the rich VEGF signaling data generated from this proposal to identify additional genetic markers of resilience that fall along this same signaling pathway. Knowledge about the mechanisms, signaling pathways, and specific forms of VEGF that most strongly predict resilience will accelerate the development of VEGF signaling molecules as targets for pharmacological intervention.

PROJECT SUMMARY ? BIOMARKER CORE The Exploratory Vanderbilt Alzheimer?s Disease Research Center (VADRC) Biomarker Core will leverage Vanderbilt?s institutional strengths in proteomics, neuroimaging, and genetics to provide a scalable infrastructure that can support biomarker collection, storage, analysis, integration, and distribution. Under the leadership of Dr. Timothy Hohman, we have established Vanderbilt as the Genomics Core for the Preclinical Alzheimer?s Disease Consortium, established the Biomarker Core for a multi-site cohort and autopsy study of Alzheimer?s disease and dementia correlates of delirium, led multiple large-scale discovery and candidate proteomic analyses emphasizing novel markers of risk and resilience to Alzheimer?s disease, and established the Resilience from Alzheimer?s Disease database, a local biomarker data repository that harmonizes fluid, neuroimaging, and genomic data across 10+ independent cohort studies. For the P20, we will leverage our local rich infrastructure and resources to acquire robust fluid, neuroimaging, and genetic biomarkers for the Clinical Core and affiliated cohort studies within the VADRC. The Biomarker Core and Clinical Core will work closely to ensure proper collection of relevant biomarkers using established, standardized protocols reflecting current best practices. Fluid, neuroimaging, and genetic data will be processed and stored within an established relational database, and the Biomarker Core will work to ensure proper storage and processing of all samples and data, with multiple quality control measures in place. Samples collected by the Clinical Core will be integrated by the Biomarker Core into funded, ongoing projects that support the VADRC?s thematic focus on establishing effective prevention and treatment strategies for non-amyloid pathways of injury that commonly co-occur with core Alzheimer?s disease pathology. Examples include discovery proteomic projects using mass-spectrometry, neuroimaging projects through the Preclinical Alzheimer?s Disease Consortium, and genomics projects as part of the Alzheimer?s Disease Genetics Consortium and Alzheimer?s Disease Sequencing Project. All data will be harmonized with large-scale cohort studies, and the Biomarker Core will coordinate with the Administrative Core to distribute all biomarker data to support local and national research activities. The Biomarker Core will also promote educational activities in biospecimen collection, neuroimage processing, and genetics to promote standardized practices and facilitate novel training experiences for students, fellows, and faculty. The Biomarker Core is uniquely positioned to integrate proteomic, neuroimaging, and genomic data pipelines for the VADRC into well-established workflows from national consortia and ensure that the VADRC remains at the forefront of prevention, large-scale discovery, and therapeutic intervention of Alzheimer?s disease and related dementias.

Abstract In response to PAR-20-099 ?Harmonization of Alzheimer?s Disease and Related Dementias (AD/RD) Genetic, Epidemiologic, and Clinical Data to Enhance Therapeutic Target Discovery?, we have assembled a multidisciplinary team that includes experts in neuroimaging, neuropsychology, fluid biomarkers, neuropathology, and vascular contributions to ADRD to work in close partnership with the NIH and the Alzheimer?s Disease Sequencing Project (ADSP). Our ADSP Phenotype Harmonization Consortium, or ?ADSP-PHC?, seeks to work in coordination with existing ADSP workgroups and initiatives to (1) streamline access to endophenotype data, (2) provide high quality endophenotype harmonization across multiple research domains, and (3) provide comprehensive documentation of both data availability and harmonization procedures. This project includes two coordinating centers, three cores, and eight domain- specific harmonization teams led by world-renowned experts in their fields. While our efforts will focus on data access, documentation, and harmonization, we will work closely with other ADSP workgroups and other large-scale harmonization efforts to maximize the impact and align with NIH priorities. In particular, we will focus harmonization on ADRD-related endophenotypes, including cognitive scores derived from detailed neuropsychological assessments, measures of neuropathology measured both ex vivo (neuropathological assessment at autopsy) and in vivo (fluid biomarkers and positron emission tomography biomarkers), concomitant pathways of injury (vascular risk factors and vascular brain injury), and measures of neurodegeneration focusing on both white (diffusion-weighted MRI) and grey matter (T1-weighted MRI). The proposed harmonization effort will provide an unprecedented opportunity to disentangle the genetic architecture of individual biological contributors to ADRD risk and progression. The harmonized data, protocols, and educational tools developed by the ADSP-PHC will transform the ADRD landscape, accelerate discovery, and facilitate the application of emerging big data analytic approaches leveraging machine learning and artificial intelligence.

PROJECT SUMMARY Our proposed research aims to identify sex-specific genetic drivers of neuropathologic, cognitive, and metabolic phenotypes of Alzheimer?s disease by integrating longitudinal behavioral and molecular data from AD mice with genetic, genomic and clinical data from human cohorts. We will leverage a newly generated mouse population that incorporates high-risk familial AD (FAD) mutations on a genetically diverse background (BXD panel) to identify modifiers that contribute to AD resilience in this ?humanized? mouse population. In parallel, we will incorporate cutting-edge single-cell omic approachs to generate a molecular atlas of human brains from carriers of FAD mutations (in APP, PSEN1 and PSEN2) and non-carriers with sporadic AD. By combining and validating analyses in both mouse and human datasets, we expect to find molecular candidates that robustly contribute to sex-specific variation in symptoms of AD. We will further validate these candidates using unparalleled in vivo mouse technology to not only empircally assess their role in sex-specific mechanisms of disease, but also to evaluate sex X genotype X treatment interactions in a subset of candidates (i.e., Apoe) to inform more personalized therapeutic approaches. The approach we propose benefits from the enhanced discovery power and value of existing human genetics resources and novel, precision AD mouse models across multiple institutions to investigate the mechanisms of sex differences in AD.