Nilufer Ertekin-Taner, MD, PhD - US grants

Late-onset Alzheimer's disease (LOAD) is the most common cause of dementia in the elderly. Despite for aq substantial genetic component, much of the risk for LOAD remains unexplained. Using plasma amyloid beta peptide (Abeta) as a quantitative genetic marker, we recently identified linkage to a locus on chromosome 10 that increases the risk for LOAD by elevating Abeta levels. Our aims are to identify this novel LOAD risk gene on chromosome 10 and to characterize its effects on the metabolism of Abeta. We will use single nucleotide polymorphism (SNP)-based linkage and association studies in LOAD families and case- control groups to narrow the linkage region. We will continue to use the Abeta phenotype to group the subjects according to their phenotypes, thus enhancing homogeneity in the study group and enriching the genetic association. This w9ll also allow the evaluation of candidate genes at a mechanistic level, as the causative mutation in the risk gene is expected to increase Abeta and the risk for LOAD. Once the gene is identified, further studies are required to determine its mechanism of action and frequency in the general population. These studies could potentially provide new insights to the pathogenesis of AD, lead to the discovery of novel therapeutic targets and allow for the identification of "at risk" people by plasma Abeta as a biomarker.

DESCRIPTION (provided by applicant): Late-onset Alzheimer's disease (LOAD) has a substantial genetic component estimated to be as high as 80%, much of which remains unexplained. Genome-wide association studies (GWAS) are emerging as a powerful approach in deciphering the genetic risk factors for common-complex diseases. It has been proposed that the genetic basis of common-complex diseases is mainly due to regulatory factors. There have been several GWAS in humans utilizing messenger RNA (mRNA) expression levels from lymphoblasts and one using cortical tissue from human brains. These studies identified many cis-SNPs that show strong association with transcript levels. Many of these associations achieved genome wide significance when only hundreds of samples are analyzed. We have recently analyzed 313,504 single-nucleotide polymorphisms (SNPs) using the Illumina platform in 2,099 subjects from LOAD case-control series. Of these subjects, there are 200 pathologically confirmed AD cases and 197 non-AD subjects with cerebellar RNA samples. In our preliminary analysis of mRNA expression levels for 12 LOAD candidate genes from cerebella of <200 LOAD subjects, we identified a cis-SNP in a strong candidate LOAD gene, insulin degrading enzyme (IDE) that associated with IDE transcript levels at genome-wide significance (p=2.7 x 10-8). This SNP also associated with AD risk and was in complete linkage disequilibrium with a putative functional SNP that resided in an evolutionarily conserved region of IDE. Our results suggest that the use of brain mRNA levels as endophenotypes in LOAD GWAS may be a powerful way to identify LOAD susceptibility alleles. Our 200 AD cases and 197 non-AD subjects with whole genome SNP genotypes and rich neuropathologic characterization provide a highly valuable resource to pursue GWAS of gene expression levels using mRNA from their cerebellar tissue, the brain region least affected by AD pathology. Assessment of cis-SNP associations with whole-transcriptome cerebellar expression levels in our nearly 400 samples will generate a valuable resource that can be utilized for mapping complex diseases. Our data will also enable simultaneous assessment of cis-variants for their effects on gene expression and AD risk. SNPs that associate with both AD risk and mRNA levels will be candidate susceptibility variants for AD with plausible regulatory effects on gene expression. Finally, such candidate variants can then be tested in functional expression studies to establish their biological effects and to validate the results from the expression GWAS. Our specific aims are: 1. To obtain whole transcriptome expression levels from the cerebellar mRNA of 200 LOAD and 197 non-AD subjects with whole genome SNP genotypes;2. To perform GWAS of whole transcriptome expression levels to identify significant cis-SNP/transcript associations;3. To identify and validate cis-SNPs that associate with both LOAD and gene expression levels. PUBLIC HEALTH RELEVANCE: Alzheimer's disease (AD) is an epidemic that accounts for 60% of all dementias affecting an estimated 13.5 million individuals worldwide. Understanding its genetics will help understand its formation, may provide progress in its prevention and potential drug targets for its cure. Our proposal is aimed at the discovery of AD risk variants that work through regulation of gene expression using a genome-wide association study design.

Late-onset Alzheimer's disease (LOAD) has a substantial genetic component estimated to be as high as 80%, much of which remains unexplained. Genome-wide association studies (GWAS) are emerging as a powerful approach in deciphering the genetic risk factors for common-complex diseases. We recently genotyped 318,237 single-nucleotide polymorphisms (SNPs) in 2,465 subjects from LOAD case-control series. Of these subjects, there are 200 pathologically confirmed ADs and 197 non-ADs with cerebellar RNA samples. We measured cerebellar mRNA levels of 12 AD candidate genes in these 200 autopsy-confirmed AD subjects. We extracted the c/s-SNP genotypes for these 12 candidate genes from the GWAS and performed associations utilizing their expression levels as endophenotypes. We identified 3 SNPs that associate significantly with IDE (insulin degrading enzyme) expression levels after correcting for multiple testing. One SNP had IDE expression level association at p=2.73 x 108, which would be significant even at the genome-wide level. Minor allele carriers of all 3 SNPs had IDE expression levels 2.43-2.66 fold higher than the major homozygotes. Minor allele carriers of all 3 /DESNPs had protective odds ratio estimates, as expected biologically from their effects on IDE expression levels. These SNPs were in linkage disequilibrium with IDE SNPs residing in regions conserved between human and mouse. These results suggest the existence of functional IDE variants that modify risk of AD via effects on gene expression. Importantly, they provide strong proof of principle that use of expression levels as endophenotypes may be a powerful approach in the identification of disease susceptibility alleles in GWAS. Our 200 AD cases and 197 non-AD subjects with whole genome SNP genotypes and brain RNA provide a highly valuable resource to pursue whole genome expression analysis. Assessment of whole-genome SNP associations with expression levels will generate a valuable resource for mapping complex diseases. Our data will enable simultaneous assessment of whole-genome variation for their effects on gene expression and the AD phenotype. SNPs that associate with both AD and expression levels will be candidate susceptibility variants for AD with plausible regulatory effects. In this proposal our specific aims are: 1. To obtain whole transcriptome expression levels from subjects with whole genome SNP genotypes. 2. To perform GWAS of whole transcriptome expression levels. 3. To identify and validate variants that associate with both AD risk and gene expression levels. 4. To validate the /DESNP-expression and AD associations. RELEVANCE (See instructions): Alzheimer's disease (AD) is an epidemic that accounts for 60% of all dementias and affects an estimate of 13.5 million individuals worldwide. Understanding the underlying genetics of this common disease will help understand its formation, may provide advancement for its prevention as well as potential drug targets for its cure. Our proposed work is aimed at the discovery of AD susceptibility variants that work through regulation of gene expression using a genome-wide association study design.

DESCRIPTION (provided by applicant): An invariant feature of the pathological cascade in Alzheimer's diseases (AD) is a reactive gliosis, reflecting an underlying alteration in the innate immune activation state within the brain. Innate immune signaling is altered early in AD, but is also skewed towards an activated state as a consequence of brain aging. There is strong genetic evidence that innate immunity has a significant role in AD. Variants in two genetic loci that play roles in the complement cascade, CR1 and CLU, show significant genetic associations with AD, and rare coding variants in TREM2 also confer substantial risk for AD. Numerous experimental studies in AD mouse models show that manipulating innate immune pathways can have positive or negative effects on proteostasis, cognition and neurodegeneration. At least when assessing A? pathology as an endpoint, the beneficial effects of some innate immune system manipulations are robust. We propose to identify therapeutic targets within the innate immune signaling cascade in AD that could be safely manipulated to provide disease modification in AD. However, because of the complexity of, and the gaps in our knowledge regarding, innate immune signaling within the CNS, a systems level approach that integrates multiple types of data will be required to achieve this goal. Indeed, development of any innate immune therapy will need to be finely tuned and extensively validated in order to be further developed as a potential AD therapy. We will use a multifaceted systems level approach to identify targets within innate immune signaling pathways that can safely provide disease modifying effects in AD. Comprehensive, transcriptomic, genetic and pathological data from both humans and mouse models will be generated, integrated and analyzed in novel ways. This integrated data will then be used to guide multiple preclinical target validation studies of key innate immune targets in both APP and tau mouse models as well as non-transgenic mice. These studies will dramatically accelerate the identification and validation of disease modifying innate immune modulatory strategies in AD and will provide important insights into how these various manipulations of innate immune activation states alter normal behaviors with an emphasis on cognition.

DESCRIPTION (provided by applicant): Progressive supranuclear palsy (PSP) is a rapidly progressive neurodegenerative disorder with clinicopathologic heterogeneity and without any therapies. Genetic studies can be instrumental in the identification of the molecular pathophysiology underlying PSP risk and its heterogeneity, which may enable discovery of therapeutic targets. Until recently, H1 haplotype of MAPT, encoding tau, was the strongest genetic risk factor for PSP. A new PSP genome-wide association study (GWAS) identified six additional loci. The effective translation of these findings to therapy requires identification of he disease gene, the functional variants and their mechanism of action. These goals cannot be achieved by the disease GWAS alone and require alternative, powerful and mechanistic approaches. The current proposal aims to close this knowledge gap by joint analysis of the whole transcriptome and quantitative neuropathology measures in a well- characterized autopsied PSP cohort with existing GWAS data. Our long-term goal is to uncover the pathophysiology of PSP and the molecular substrates of its subtypes that will ultimately lead to drug discoveries. Given the clinicopathological overlap between PSP and other tauopathies, our proposal is expected to impact a wide range of neurodegenerative disorders and generate novel therapeutic avenues. Our central hypothesis, is that many PSP variants confer risk by regulating brain gene expression. Further, differential transcriptional regulation may underlie the heterogeneity in PSP. Our preliminary data identified brain transcript associations for some of the top PSP GWAS variants supporting our hypothesis. In our Brain Bank, we have access to nearly 500 brain samples from autopsied PSP subjects with existing GWAS, ~400 of which have typical and ~100 with atypical clinicopathology. All subjects have clinical data and detailed quantitative neuropathology measures. Our objective is to obtain brain transcriptome measurements in this unique cohort, which will be analyzed jointly with quantitative neuropathology measures to identify functional variants underlying PSP risk, its clinicopathological heterogeneity and to discover the mechanism of action of these variants. The expected outcomes of our specific aims are: 1) To identify a) genetic variants that influence gene expression in PSP brains, b) transcript level differences between subtypes of PSP that are not simply due to aging; 2) To discover a) genetic factors that influence both neuropathology and gene expression in PSP; b) transcripts that correlate with neuropathology; 3) To uncover the mechanism of transcriptional regulation in PSP by a) next-generation RNA sequencing of 200 select PSP brain samples; b) translational in- vitro studies. Results from all aims will be compared with the PSP disease GWAS. The overall knowledge will nominate genes and their transcriptional changes as novel disease mechanisms in PSP. These molecular mechanisms will constitute modifiable drug targets, which will impact PSP and other related neurodegenerative diseases.

? DESCRIPTION (provided by applicant): Genome-wide association studies (GWAS) in late-onset Alzheimer's disease (LOAD) identified candidate genetic loci, however cannot unequivocally uncover the disease gene or variants. Further, GWAS variants do not explain the full disease heritability. An important factor underlying this missing heritability may be rare functional disease variants of larger effect size that are missed by GWAS. Indeed, the recent identification of rare and strong AD risk variants in TREM2 via sequencing supports this hypothesis. Consequently, there are efforts for next-generation sequencing (NGS) in LOAD, however NGS comes with its own set of challenges. First, the large number of variants identified from NGS will require prioritization for downstream replication and functional studies. Second, appropriate assays are needed to test the functional consequences of these variants. Finally, NGS of large number of samples are still cost-prohibitive, precluding rapid functional assessment of variants. In this exploratory R21, we propose a cost-effective, novel alternative approach and plan to apply it to two intriguing nested candidate AD genes: CTNNA3 and LRRTM3. We will take advantage of existing and publicly available whole exome and genome sequence (WES, WGS) data to identify variants to test in our case-control cohort of ~11,000 subjects (Aim 1) and to assess the most promising, prioritized variants by in-vitro functional assays (Aim 2). Our preliminary data on the AD GWAS gene ABCA7, generated by this novel paradigm, as well as TREM2 findings, provide strong support for the feasibility of our approach. CTNNA3 and LRRTM3 reside in a linkage region of AD risk and amyloid ß levels identified independently by others and the co-PIs. They have opposite transcriptional orientation and strongly correlated gene expression levels in our published data, suggesting functional interactions. Both genes are implicated in synaptogenesis. We identified intronic variants in CTNNA3 that account for our Aß linkage signal. LRRTM3 influences APP processing. We showed protein interactions between LRRTM3, APP and BACE1 and herein demonstrate a role in long term potentiation. In summary, the nested CTNNA3/LRRTM3 are excellent candidate AD genes with potential roles in APP processing and/or synaptic physiology. We and others reported association of variants in both genes with AD risk, but replication has been inconsistent, which may in part be due to the lack of an assessment of rare variants. Our aims are: 1) To test rare variants in CTNNA3/LRRTM3 identified from 3 NIH funded NGS data, EVS (WES 4300 Caucasians, 2203 African-Americans), ADNI (WGS 246 Controls, 359 mild cognitive impairment, 184 AD), ADSP (584 subjects from 111 AD families), for AD risk association in our 11,000 subjects. 2) To test putative functional variants in CTNNA3/LRRTM3 in APP processing, cell toxicity and synaptic integrity. This exploratory R21 will enable a thorough and hypothesis-based study of two intriguing candidate AD genes and will also establish our cost-effective approach as a paradigm-shifting alternative to assess the deluge of genes being nominated in AD and other complex diseases.

PROJECT SUMMARY/ABSTRACT Alzheimer's disease (AD) is the most common cause of dementia characterized by brain accumulation of senile plaques and neurofibrillary tangles. AD risk is likely influenced by a multitude of genetic and environmental risk factors and their complex interplay, which subsequently lead to cascades of downstream pathophysiologic events that include but are not limited to aberrant proteostasis and lipid metabolism, as well as inflammatory, vascular, and oxidative mechanisms. The array of risk factors that lead to AD and their downstream influences are likely to be heterogeneous amongst AD patients, which complicates the search for drug targets, biomarkers and their potential downstream beneficial use in any given AD patient. For this reason, drug target and biomarker discovery efforts in AD have to focus on identification of both molecular mechanisms that are commonly perturbed in AD patients, as well as those mechanisms that may underlie heterogeneity in AD. To overcome this massive challenge, team-science efforts, including the NIH initiatives, Accelerating Medicines Partnership-AD (AMP-AD) and Molecular Mechanisms of the Vascular Etiology of AD (M2OVE-AD) Consortia, have launched large-scale generation and analyses of multi-omics data from well- phenotyped human cohorts and model systems. These consortia aim to integrate multi-omics and clinical endophenotype data to build a model(s) of AD that captures these common and heterogeneous pathomechanisms. Our teams are leading participants of both AMP-AD and M2OVE-AD. The initial findings from these consortia reveal concerted changes in networks of expressed genes and proteins in AD subjects and model systems, with biological significance. Despite this progress and wide and immediate sharing of the data generated by these programs, significant gaps remain in the available ?omics data, and the ability to integrate, harmonize and annotate these datasets. Our proposal is in response to the RFA-AG-17-054, which aims to close these gaps. In this proposal, we maintain the overall objective of our parent funded M2OVE-AD project (RF1 AG51504), which is to determine APOE- and sex-dependent effects, and uncover novel genes and pathways that influence vascular risk in aging, AD and other dementias. Our specific aims are: 1. Integrative functional genomic analysis of human brains to discover novel pathways in AD. 2. Integrative functional genomic analysis in a prospective cohort to validate and discover AD pathways. 3. Investigate the impact of APOE genotype and sex on transcriptional networks and the metabolome in model systems. 4. Perform single-cell profiling to annotate the transcriptome data from AMP-AD and M2OVE-AD. These studies will add key epigenetic data (H3K9Ac and RRBS methylome) to the human and transcriptome and metabolomics data to the mouse cohorts, generate human and mouse single cell transcriptome data, and perform integrative network analyses. We expect this proposal to fill key gaps in knowledge and further enhance the AMP-AD and M2OVE-AD initiatives in their drug and biomarker discovery goals.

Our funded U01 project in the AMP-AD consortium had the overarching aim of identifying therapeutic targets within innate immunity pathways. In the previous funding period, we made significant progress and met all milestones of our U01. We have nominated multiple targets in the immune system, and these targets are at various stages of validation. Nevertheless, key gaps in our understanding impede transformation of the collective AMP-AD knowledge to validated therapeutic targets. Despite identification of numerous perturbed transcriptional networks, some enriched for Alzheimer's disease (AD) risk genes, key tractable targets in these networks are not unequivocally identified and validated. Further, whether the observed transcriptional changes are a simple consequence of disease or actually, play a role in the pathologic cascade has, typically, not been determined. Finally, the direction of molecular changes that is beneficial vs. detrimental has, in most cases of nominated targets, not been established. To overcome these gaps in knowledge, we will i) leverage unique aspects of our existing data and tools along with data and analyses generated by the larger AMP-AD consortia, ii) generate complementary new data, and iii) apply innovative analytic approaches. Notably, our ability to perform comparative analysis of control (no pathology), PathAg, (Pathologic Aging, amyloid+), AD (tau+, amyloid+) and PSP (progressive supranuclear palsy, tau+) enables a framework to identify therapeutic targets that play a role in the transition to different disease stages of AD. Further, comparisons between two brain regions (TCX=affected and CER=largely spared in AD) and between AD and PSP can help distinguish whether the molecular changes identified are likely a cause or consequence of pathology. In this renewal application, we propose to: i) refine and genetically validate therapeutic targets ii) identify molecular mechanisms and targets that mediate disease transition from control to PathAg to AD iii) define the drug target mechanism(s) iv) evaluate select prioritized targets in relevant models, v) continue the collaboration with all AMP-AD partners to promote consortium wide-target validation and vi) share our data openly with the larger scientific community. These studies will include the final phase of modeling studies for more than 20 immune targets identified in the original grant cycle with a goal of making firm go, no-go, decisions on select targets. These studies will enable us to i) provide biologic insight into the mechanism of action of the proposed targets and ii) inform on the direction of change needed for therapeutic benefit. Identification of key targets that drive the transition from control to amyloid positivity, and then to tau pathology and neurodegeneration will enable us to propose alignments of future clinical testing of therapeutics that manipulate these targets in appropriate disease stages-increasing the likelihood to achieve clinical efficacy and avoiding costly testing of an agent in an intent to treat population that is unlikely to benefit.

Although protection from and resilience to Alzheimer's disease (AD) constitute a fundamental aspect to understanding AD pathophysiology, this is a relatively understudied area and the molecular basis of resilience to AD is largely unknown. This is a critical knowledge gap, as uncovering biological pathways of resilience could lead to the discovery of novel therapeutic or prophylactic drug targets in AD. It is clear that there are individuals who may be protected from developing AD pathology, despite advanced age and having highly penetrant genetic risk factors for AD, such as APOE ?4 allele. Additionally, there are people with cognitive resilience who remain free of cognitive decline despite having pathologic or biomarker changes of AD. Current therapeutic discovery efforts in AD are largely focused on uncovering the biological pathways that are perturbed in this condition, the key molecules in these pathways, and identification of therapeutic compounds to stop and/or reverse these perturbations. These efforts are based on the hypothesis that concerted perturbations of molecular networks that serve key biological functions underlie the pathophysiology of many common, complex diseases including AD. While it is critically important to discover perturbed molecular networks in AD, this is only one side of the coin. We postulate that application of network biology approaches to investigate individuals who are protected from and resilient to AD can uncover novel biological pathways that underlie resilience to AD. In addition to revealing novel resilience pathways, study of resilient individuals is also critical for the validation of perturbed disease networks, as we expect some of the susceptibility and resilience networks to overlap but have opposite direction of effect. Such validation efforts are essential for the translation of these discoveries to viable drug targets. In this proposal, we plan to study individuals who are protected from and resilient to AD by leveraging samples from autopsied and living human cohorts, to utilize existing and generate new molecular data, including RNA sequence (RNAseq) and whole genome sequence (WGS), and to apply analytic approaches to identify resilience networks. We will utilize single-nucleus RNAseq (snRNAseq) to identify cell-specific molecular changes of resilience in brain and validate these using iPSC- based models. To translate this knowledge to therapeutic targets, we will apply novel pharmacogenomics tools. Our proposal is responsive to the RFA-AG-18-029 and aims to: 1) Identify molecular targets of resilience to development and propagation of AD pathology in an autopsy cohort enriched for older controls; 2) Identify molecular targets of cognitive resilience in the presence of AD biomarkers in a longitudinally assessed older cohort enriched for clinically normal individuals with positive amyloid PET and APOE ?34 or ?44 genotypes; 3) Validate cell-specific molecular changes in iPSC-based models; 4) Decipher druggable targets of AD resilience and potential therapeutic compounds using systems-based pharmacogenomics tools. We will integrate our findings with those from AMP-AD, M2OVE-AD, ADNI and ADSP and share all generated data and tools.