Corey T. McMillan - US grants

[unreadable] DESCRIPTION (provided by candidate): This application seeks to deepen our understanding of the complex psychological and physiological processes that underlie the production of human speech. Using the SLIP task, a speech error eliciting technique, we will investigate why previous research has led to conflicting findings. In particular, we will discriminate between feedforward and interactive models of speech. Additionally, the role of articulation in speech errors will be investigated, extending the models to account for post-planning influences on speech production. This will be accomplished by recording articulation errors using electropalatography (EPG), electromagnetic articulography (EMA), and ultrasound techniques during the SLIP task. Lastly, we will extend the scope of the psychological and physiological evidence from the SLIP task to a more natural task, the Network task which allows participants to produce connected, purposeful speech under experimental control. This project will make a substantial contribution to our understanding of the interplay between mental and physical processes of speech and develop a unified approach to articulatory analysis across a number of techniques, including EPG, EMA, and ultrasound. [unreadable] [unreadable]

DESCRIPTION (provided by applicant): In daily conversation individuals regularly encounter ambiguous words. For example, "pitcher" could refer to a baseball player or a water container. However, it is not clear how speakers choose words to minimize ambiguities (e.g., saying "baseball player instead of "pitcher"). It also is not clear how listeners choose to interpret an ambiguous word when they are encountered in conversation. One account for minimizing ambiguity during conversation is lexically-based: a linguistic mechanism detects that two conceptual representations share a single word-form representation. We hypothesize the lexical account will be supported by middle temporal cortex, a region often implicated for conceptual and word-form representation. An alternative account is based on neuroeconomics: individuals choose the word with the highest expected individual utility. In this context utility refers to the balance between the risks associated with producing or comprehending an ambiguity and the resources required for producing each term. We hypothesize that the neuroeconomic account will be additionally supported by ventromedial prefrontal (vmPFC) and inferior parietal (IP) cortices, which are often implicated for decision-making processes. The overall aim of this project is to investigate the cognitive and neural basis for minimizing ambiguity in sentence processing. Specific Aim 1 will investigate neurodegenerative disease patients'abilities to minimize ambiguity during sentence production. We will focus on semantic dementia who have middle temporal cortex disease, corticobasal degeneration who have IP disease, and frontotemporal dementia patients who have vmPFC disease. Specific Aim 2 will obtain converging evidence on the neural basis for minimizing ambiguity during sentence production using fMRI studies of healthy subjects. We predict that middle temporal, IP, and vmPFC will all contribute to minimizing ambiguity. Specific Aim 3 will investigate whether minimizing ambiguity is supported by a similar neurological network during both sentence production and sentence comprehension. Understanding the cognitive and neural basis of minimizing ambiguity in sentence processing will improve patient-caregiver communication and yield an improved quality of life, care, and safety for patients. It will also contribute to our understanding of the neural basis for a crucial, but elusive, property of human cognition.

DESCRIPTION (provided by applicant): This K01 award will support my development as an independent investigator with a translational research program that specializes in the cognitive and biological basis of neurodegenerative diseases such as frontotemporal lobar degeneration (FTLD). Candidate: My research experience as a cognitive neuroscientist ideally positions me to achieve my career goal of becoming an independent investigator with expertise on the cognitive and biological basis of neurodegenerative disease. I have strong cognitive training with an M.Sc in Psycholinguistics and Ph.D in Psychology from the University of Edinburgh, where I was supported by an NRSA Individual Predoctoral Award. During my postdoctoral IGERT fellowship at the Institute for Research in Cognitive Science at the University of Pennsylvania, I was awarded an NRSA Individual Postdoctoral Fellowship Award to investigate the role of decision-making in language. In this research I have gained experience investigating neurodegenerative disease patients comparatively in order to obtain converging evidence to complement fMRI studies of healthy adults. I have become increasingly interested in translating my research to optimize the diagnosis and treatment of patients with neurodegenerative diseases. I was recently award the Society for the Neurobiology of Language Postdoctoral Merit Award in recognition of my novel research investigating how social limitations in patients contribute to difficulty in discourse. I have committed to four years of clinical research the NIH Loan Repayment Program, and I intend to commit to clinical research for the duration of my career. I have learned that cognitive and neuroimaging studies provide only one perspective on neurodegenerative diseases. In this proposal, I plan to gain the necessary expertise in biological aspects of FTLD and related conditions to complement my past experiences, and thus achieve my goal of becoming a multifaceted independent investigator with expertise in the cognitive and biological basis for neurodegenerative diseases. With the support of this K01, I will develop expertise to conduct investigations of cerebrospinal fluid (CSF), genetic, and neuropathological aspects of neurodegenerative diseases. I will ultimately integrate the biological expertise gained in this proposal with language studies from my cognitive neuroscience research in an effort to identify non-invasive biomarkers that can be used to screen patients for clinical trials and to measure the efficacy of disease-modifying agents. Environment: This award will be conducted at the Perelman School of Medicine at the University of Pennsylvania in the Department of Neurology, the Center for Neurodegenerative Disease Research (CNDR), and the Penn Bioinformatics Center where I have strong institutional support. The proposed institution is an exceptional environment that has expert centers for neuroimaging, cerebrospinal fluid biomarker analysis, a leading genetic research core, expert neuropathology, outstanding biostatisical support, and relevant clinical research laboratories. The University of Pennsylvania is unique in comparison to other institutions in the country because all of the above methods are available in one center. My mentor, Dr. Murray Grossman, and my co-mentor, Dr. John Trojanowksi, have international reputations for neurodegenerative disease research. My career development will also be supported by my co-mentor, Dr. Lyle Ungar, who has extensive expertise in statistical learning algorithms and in the analysis of proteomic and genomics datasets. Together, this mentorship team will facilitate my development as an independent investigator by providing access to existing and future collaborators, laboratory resources, and exceptional training environments. The CNDR is a world- leading center for neurodegenerative disease research with human and animal models of disease and exceptional translational science. Biofluid biomarker experience is extensive, and several national biofluid cores are centered at Penn (e.g. ADNI). There is a wealth of internationally-recognized neuroimaging expertise at the University of Pennsylvania in the Penn Imaging and Computer Science Laboratory, and I will benefit by integrating neuroimaging resources from these facilities with other modalities of biomarker research. Training: I will develop my expertise in the biological basis of neurodegenerative disease with the support of my mentor, Dr. Murray Grossman, and my co-mentors, Dr. John Trojanowski and Dr. Lyle Ungar. Specifically, with Dr. Trojanowksi I will engage in training related to biofluid and genetic biomarkers of FTLD. I will develop advanced neuroimaging skills and cutting-edge biostatistical methods with Dr. Ungar. Each of these training modalities will be supported by complementary formal coursework, participation in seminars, attendance of conferences, and regularly scheduled meetings with mentorship team. Research: FTLD is a neurodegenerative disease affecting approximately 15 out of 100,000 individuals. In recent years detailed neuropathological investigations at autopsy have demonstrated distinct sources of histopathological abnormalities in FTLD, including the presence of tau inclusions (FTLD-tau) and TDP-43 proteinopathies (FTLD-TDP). However, there are currently no in vivo methods for discriminating between FTLD-tau and FTLD-TDP. There is an urgent need to improve the in vivo diagnosis of FTLD to appropriately enter patients into emerging clinical trials, and to develop sensitive and specific endpoints in trials that can quantify response to these treatments. The overall research aim of this proposal is to develop multimodal methods to improve in vivo diagnosis of FTLD.

Aging is among the most well-established risk factors for the accumulation of molecular pathology and neurodegeneration with <1% of older adults lacking molecular pathology. As individuals age there is an increased risk of neurofibrillary tau tangles (NFTs) co-occurring with amyloid-beta plaques (A?) consistent with Alzheimer's disease (AD) neuropathological criteria. However, nearly all adults >50 years of age have pathological evidence of NFTs which may occur in a similar spatial distribution to AD but typically less severe in nature and in the absence of A? molecular pathology, consistent with a neuropathological diagnosis of primary age-related tauopathy (PART). Therefore, it is currently unclear why most aging individuals develop NFT pathology (i.e., either in PART or AD) and in variable degrees of severity while only a proportion of individuals also develop A? pathology (i.e., in AD). To date the vast majority of aging research has defined age-related pathological risk in chronological measurements (i.e., years since birth). However, the rates of actual ?biological? aspects of aging appear to differ between individuals, with some individuals displaying features of aging that are accelerated (biological age older than their chronological age) or delayed (biological age younger than their chronological age). The overarching goal of this proposal is to evaluate three sources of biological aging mechanisms underlying risk and severity for NFT and A? molecular pathology and associated neurodegeneration. First, DNA methylation (mDNA), or ?the epigenetic clock?, can be measured to reliably predict chronological age as well as accelerated or delayed aging. Second, telomeres are repetitive DNA sequences and associated proteins that protect chromosome ends and shorten with cell division and age in most human tissues, including brain. Third, we will evaluate single nucleotide polymorphisms (SNPs) associated with reduced longevity and shortened telomere length to help identify risk factors of poor biological aging to facilitate early interventions and pinpoint candidate genetic mechanisms for novel therapeutic approaches. Together, we propose to use mDNA and shortest telomere length analysis (TeSLA) along with complementary SNP association tests to evaluate the hypothesis that accelerated aging (biological age older than chronological age) will increase the risk of molecular pathology and neurodegeneration. We will assess biological aging in well-characterized PART and AD autopsy-confirmed samples and in vivo structural MRI and PET molecular markers of 18F-floretaucipir (tau) and 18F-florbetaben (A?) in aging controls from our NIA-funded Alzheimer's Disease Center (ADC) and collaborating ADCs. By investigating the biological aging mechanisms of NFT and A? pathology, this proposal addresses a NIH priority to improve our ?Understanding of Alzheimer's Disease in the Context of the Aging Brain?. A significant proportion of the aging population has varying levels of molecular pathology and this research will help establish mechanisms by which heterogeneity in biological brain aging impacts the development and progression of pathological accumulation and neurodegeneration.

PROJECT SUMMARY/ABSTRACT Despite decades of research and dozens of trials, effective disease-modifying treatments for amyotrophic lateral sclerosis (ALS) and other neurodegenerative disorders still elude us. A primary source of the litany of negative trials is the increasing recognition that experimental therapeutics are frequently administered too late in the course of disease, after irreversible neuronal loss has already occurred. These delays stem in part from the fact that the degenerative processes in ALS begins prior to overt clinical disease, and in part from delays in diagnosis (approximately 12 months from symptom onset) and delays between onset and clinical trial enrollment (approximately 17 months interventional delay). The overall goal of this project is to address the challenge to ALS drug development that is posed by the relatively late stage in the course of disease when diagnosis is made and patients are enrolled in clinical trials. The study of pre-symptomatic disease is currently only possible in (but also most relevant to) those with the genetic forms of ALS, most commonly due to point mutations in the SOD1 gene or a repeat expansion in C9orf72. But earlier diagnosis of symptomatic disease is relevant to patients with all forms of ALS (both genetic and non-genetic). In this project, we outline two strategies for addressing these challenges, with a view to preparing for a future of clinical trials that enroll patients at significantly earlier stages in the course of their disease. In Aim 1 of this project we propose to use multimodal neuroimaging (MRI, DTI, and perfusion MRI) combined with pseudo-longitudinal, exploratory longitudinal, and multivariate network statistical techniques to characterize the anatomic distribution and temporal course of structural and functional changes in pre-symptomatic C9orf72 and SOD1 mutation carriers. We hypothesize that this approach will help us better understand how and when anatomic changes occur across adult aging in pre-symptomatic individuals at risk for ALS (or FTD) relative to age-matched non- mutation controls. We also hypothesize that network and multivariate approaches will help increase our biological understanding of C9orf72 and SOD1, as well as how these distinct etiologies of familial ALS may differ from one another. In Aim 2 of this project we will use a ?cohort? approach to evaluate the diagnostic accuracy (sensitivity, specificity and positive/negative predictive value) of serum and CSF measurement of neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH) for the early diagnosis of ALS. This approach will fill a critical gap in the current literature about the utility of neurofilaments for the diagnosis, and particularly in earlier stages of ALS. Since the currently available evidence is based on case-control studies (i.e. a comparison of patients already known to have ALS vs. patients already known to have some other disease), current estimates of sensitivity, specificity and positive/negative predictive value may be inflated and cut-offs need to be redefined. Together, by identifying the earliest anatomic loci of neurodegeneration and recalibrating biofluid biomarkers using a cohort rather than case-control design, we will facilitate the critical need for earlier interventions to ensure the success of emergent clinical trials.

Project Summary/Abstract Detailed neuropathological investigations suggest that nearly all adults >50 years of age have pathological evidence of neurofibrillary tau tangles (NFTs) and rarely (<1%) are lacking any form of molecular pathology. As individuals age there is also an increased risk of NFTs co-occurring with amyloid-beta plaques (A?) consistent with Alzheimer's disease (AD) molecular pathology. However, the recently coined term primary age-related tauopathy (PART) describes the presence of NFTs in a subset of older adults in an identical distribution to AD but with absent-to-minimal A? pathology. In contrast, there is increasing evidence that AD neuropathology can additionally be accompanied by alpha-synuclein (ASYN), the hallmark of Parkinson's disease (PD), and/or tar- DNA binding protein (TDP-43), the hallmark molecular basis of frontotemporal degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). To date, the mechanisms underlying the age-related neuropathological spectrum of NFTs-only in PART and inclusions of ASYN and TDP-43 pathology in AD are unclear. In this proposal we introduce the ?resistance hypothesis? that suggests that some individuals have neuro-protective resources that limit their accumulation of A? in PART and their accumulation of ASYN and/or TDP-43 pathology in AD. We also consider the co-occurrence of molecular pathologies in related disorders, including ALS and PD. The overarching goal of this proposal is to test the hypothesis that genetic and biological aging mechanisms provide resistance to age-related molecular pathologies and to uncover mechanisms supporting resistance in this aging population. To achieve this goal we will analyze neuropathological and genetic data in >1160 well-characterized autopsy-confirmed samples from our NIA-funded Alzheimer's Disease Center (ADC) and related neuropathology cores, as we as supplement these analyses with similar public datasets. We propose 3 specific aims: (1) Determine whether resistance to age-related molecular pathology is associated with reduced severity and admixture of pathologies; (2) Investigate whether ?protective? alleles of single nucleotide polymorphisms associate with resistance against molecular pathology; (3) Evaluate whether efficient ?biological? aging of regional brain tissue is protective against molecular pathology, including a DNA measure of single telomere length analysis (STELA), a transcriptional measure of p16 cyclin-dependent kinase inhibitor expression, and an epigenetic measure of DNA methylation (mDNA). Together, by investigating mechanisms of resistance to molecular pathology in aging, this proposal addresses a NIH priority to better understand the common mechanisms and interactions among neurodegenerative diseases. By better understanding the genetic factors that contribute to resistance of molecular pathology we aim to identify candidate pathways for treatment approaches to prevent accumulation of proteinopathies. A significant proportion of the aging neurodegenerative disease population has mixed pathology and this research will provide a template for developing treatment approaches that address this important issue of heterogeneity.

Frontotemporal degeneration (FTD) is a progressive disorder characterized by pathology and neurodegeneration in a predominantly frontal and temporal anatomic distribution. However, there is extensive heterogeneity of disease distribution across individuals with FTD, including several clinical phenotypes, several underlying pathological sources of disease, and distinct sources of genetic contributions. Multimodal neuroimaging, including structural MRI (sMRI) and diffusion MRI (dMRI), provides an important tool to characterize the heterogeneous and distributed loci of FTD in individuals in order to objectively improve the diagnostic discrimination between FTLD-tau and FTLD-TDP, relate these pathologies to phenotypes, and inform the biological mechanisms of these complex network disorders. Functional perfusion MRI (pMRI) and resting state BOLD fMRI (rsfMRI) approaches enhance sMRI and dMRI by providing additional unique insights into the origin, rate, and pattern of early disease and longitudinal progression. 7T MRI provides a unique opportunity to better understand the microstructural mechanisms that distinguish FTLD-TDP from FTLD-Tau. Thus, the overall goal of Imaging Core C is to provide the necessary infrastructure to support state-of-the-art 3T and 7T MRI acquisition and network analyses of neuroimaging data in Projects I-V of this research program. This Core will also be closely integrated with Cores B-E to facilitate our interdisciplinary and convergent in vivo and ex vivo approach to improving our understanding of FTD as a network disorder. In particular, we will generate graph ?nodes? reflecting MRI-derived structural properties of FTD brains and graph ?edges? reflecting structural and/or functional connectivity to facilitate the network neuroscience approach of each individual project. To accomplish this goal we propose 3 Specific Aims: (1) Collect state-of-the-art in vivo 3T MRI multimodal neuroimaging data in FTD patients including sMRI, dMRI, pMRI, and rsfMRI; (2) Provide a cross-sectional and longitudinal image processing pipeline for standard operating procedure (SOP) neuroimaging measurements; and (3) Develop novel 7 Tesla (7T) acquisition strategies to yield ultra-high- resolution (<0.3mm3) data and test biologically-motivated hypotheses.

TDP-43 pathological inclusions are associated with a spectrum of clinical syndromes including behavioral variant frontotemporal degeneration (bvFTD), primary progressive aphasia (PPA), or amyotrophic lateral sclerosis (ALS). Moreover, approximately 10% of bvFTD or PPA patients share neuromuscular features of ALS (ALS-FTD). Beyond the clinical complexities of the FTD and ALS spectrum associated with TDP-43, there are also many shared genetic links between these conditions including C9orf72 repeat expansions and TARDBP mutations that can result in bvFTD and/or ALS as well as disparate genetic mutations that exclusively result in FTD (e.g., GRN) or ALS (e.g., SOD1). The overall hypothesis of this project is that molecular heterogeneity, and specifically regionally-variable gene expression, contributes to macroscale network vulnerability contributing to a spectrum of clinically heterogeneous syndromes. It is critical to better understand the neuroanatomic and clinical features of gene expression in the current era of precision medicine in which there are antisense oligonucleotide (ASO) and adeno-associated vector (AAV) viral genetic therapies that aim to modify gene expression which have recently received FDA-approval for neuromuscular disorders and are underway for C9orf72 and GRN. While prior studies suggest that genetic and epigenetic variation contributes to the spectrum of heterogeneity in FTD and ALS, evaluations of the relationships between gene expression and disease phenotype are rare. This project aims to establish biological and genetic factors that influence regional anatomic disease burden which will provide regionally-specific biomarkers to track in emerging genetic therapies. We propose three Specific Aims: (1) Identify regional relationships between molecular gene expression and macroscale networks that bias risk for a specific clinical syndrome. We will interrogate publicly- available regional RNA microarray data and relate patterns of covariance from TDP-associated genes to structurally and functionally-derived networks that are associated with distinct bvFTD, PPA, and ALS syndromes; (2) Establish convergence between gene expression and in vivo neuroimaging networks of FTD and ALS patients. We will relate regional RNA microarray data of healthy individuals to in vivo cortical thickness and graph-theoretic network features (e.g., degree, path length) defined in Core E that are derived from FTD and/or ALS patients with inherited disease recruited from Core B and scanned using 3T MRI in Core C. We hypothesize that the regional distribution of gene covariance in typical adults will relate to the regional distribution of neurodegeneration in individuals with genetic mutations; and (3) Determine the manner in which modifiers of gene expression impact network structure in FTD & ALS. Using principles of network control theory we will leverage naturally-occurring heterogeneity in gene expression, including epigenetic (e.g., DNA methylation) and common genetic (e.g., allele dosage) factors, to determine whether these gene enhancing or silencing sources of heterogeneity are associated with altered network distributions of disease.