University Of Southern California

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY Neuropsychiatric disorders are a leading cause of disability worldwide, with depressive disorders being the most disabling among them. Many patients are resistant to all current treatments. Invasive electrical brain stimulation for treatment-resistant depression showed early promise in open-label studies but has had variable efficacy in controlled clinical trials. To date, stimulation in neuropsychiatric disorders has been limited to an open-loop approach that applies a fixed pattern of continuous stimulation regardless of symptom levels. One limitation is that open-loop stimulation does not track the inter- and intra-subject variabilities in neuropsychiatric symptoms, which can change rapidly in an individual. Another limitation is the lack of an input-output model that can guide stimulation by predicting how ongoing stimulation input drives large-scale neural activity and the symptoms it underlies in an individual. We will address these limitations to enable precise invasive electrical brain stimulation for neuropsychiatric disorders by developing a novel real-time model-based neural control system. We will provide proof-of-concept demonstration for acute control of neural biomarkers of mood states related to depression symptoms in epilepsy patients with implanted intracranial electroencephalography (iEEG) electrodes, in whom we will obtain repeated mood self-reports and perform stimulation simultaneously with neural recording. The system will continuously adjust the stimulation parameters, for the first time, based on 2 elements: (i) Novel personalized input-output model learned on recorded brain network response while delivering a new stochastic stimulation waveform to excite network activity. (ii) Personalized decoder trained on multi-day continuous iEEG recordings and simultaneous mood self-reports to estimate mood state variations from neural activity as feedback. Combining these, we will build a real-time model-based closed-loop system to precisely drive the neurally-decoded mood state—the neural biomarker of mood—to a target level. Our system generalizes to any stimulation site. Here, we will demonstrate the system with orbitofrontal stimulation as we have shown it to acutely improve mood and modulate large-scale mood-relevant brain activity. We will run real-time closed-loop experiments in each patient. The system will estimate the neural biomarker from iEEG and adjust the stimulation amplitude and frequency in real-time based on the input-output model to drive the estimated biomarker to a target level. We will also develop model-free closed-loop on-off stimulation that turns stimulation on-off based on the neural biomarker. We will compare model-based, on-off and open-loop stimulations. Success of this program will enable precisely regulating a desired brain state by developing the first model-based closed- loop invasive brain stimulation system and advancing neuromodulation technology. It will also directly inform electrical stimulation therapy in future pivotal clinical trials of refractory depression. The developed system and gained knowledge will generalize across many neuropsychiatric disorders with broad public health impact.

NIH Research Projects · FY 2025 · 2021-03

Abstract ABSTRACT Approximately 70,000 adolescents and young adults are diagnosed with cancer between the ages of 15-39 in the U.S. every year. Due to their age and life stage, the experience of a cancer diagnosis as a young adult (YA) can lead to a cascade of emotional and physical challenges. A key obstacle faced by YA cancer patients is impaired social health, a complex construct that includes perceived social belonging, social support, and social network composition. YA patients report social health challenges such as maintaining existing and forming new social relationships after diagnosis, which may contribute to poor quality of life post-cancer. Diminished social health is a major risk factor for poorer health in the general population and has been found to reduce health-promoting behaviors such as physical activity, in part because of the lack of healthy opportunities and support that social contacts can provide. Cancer patients clearly benefit from greater levels of physical activity and lower levels of sedentary time as these are associated with improved quality of life, longer periods of disease-free survival, and lower mortality. Thus, understanding the relationships between social health, physical activity, and quality of life is critically important for YA cancer patients, as the impaired social health experienced by these patients may reduce their activity levels and endanger long-term health outcomes. The overall hypothesis is that social health in YA is negatively impacted following a cancer diagnosis, and that detriments in social health influence subsequent physical activity behaviors and survivorship quality of life (emotional well-being and physical function). In the proposed study, we will comprehensively prospectively assess social health over 12 months and examine its influence on activity behaviors and quality of life. Assessment will begin proximal to diagnosis when changes in social health are likely to initiate for YA cancer patients, with subsequent follow-ups at 3, 6, and 12 months. This longitudinal design will enable the examination of the dynamic changes in social health during and after therapy and its predictive influence on physical activity and quality of life. The Specific Aims are: Aim 1: we will characterize the trajectories of social health in YA cancer patients and assess their influences on quality of life in survivorship; Aim 2: we will investigate the longitudinal associations between social health and activity behaviors in YA cancer patients and test the mediational and reciprocal relationships between social health, activity behaviors, and quality of life; Aim 3: we will explore demographic and clinical moderators of the relationships between social health, activity behaviors, and quality of life. Understanding the mechanistic processes by which social health impacts activity behaviors and quality of life will inform the development of effective intervention strategies to foster social health and improve healthy survivorship for this at-risk and vulnerable population.

NIH Research Projects · FY 2025 · 2021-02

Abstract Prostate cancer (PC) afflicts more men in the U.S. than any other malignancy and is the second leading cause of cancer death in this population. Recently, new therapies have improved survival in some men but have offered little benefit to others. Tissue profiling has identified genes and pathways associated with resistance and progression to advanced disease, but little is known about the dynamics of when and how such changes arise during therapy. Such insights can only be gained through minimally invasive monitoring that allows repeated disease profiling over time. Our multidisciplinary team has developed and tested two such minimally invasive monitoring capabilities: The first is multi-parametric liquid biopsy: streamlined analysis of blood samples that simultaneously measures PC-relevant cellular and molecular features from single circulating tumor cells and matched plasma cell-free nucleic acids. The second is radiomic analysis: high-throughput extraction of quantitative metrics to identify PC-relevant phenomic imaging features. By synergizing the strengths of the two methods, our goal is to test the hypothesis that liquid biopsy and radiomic techniques can be applied jointly to monitor metastatic PC noninvasively over time, culminating in new prognostic and predictive tools to guide therapy. To maximize the impact of our findings, liquid biopsy profiling and radiomic analysis will be integrated into Southwest Oncology (SWOG) S1802, a phase 3 prospective therapeutic trial for over 1200 men with newly diagnosed metastatic castrate sensitive prostate cancer (mCSPC) treated with standard systemic therapy alone or in combination with definitive treatment of the primary tumor. Notably, SWOG and the other participating cooperative groups have reviewed and approved this proposal (see Letters of Support), and the requisite blood samples and CT scans already are being collected as part of the active protocol. In this unique setting, we will pursue three Specific Aims. We will: 1. Use multi-parametric liquid biopsies to monitor the evolving cellular and molecular landscape of mCSPC during treatment in S1802; 2. Use radiomic analysis of CT scans to monitor the evolving radiographic landscape of mCSPC during treatment in S1802; and 3. Integrate cellular, molecular, and radiomic data to develop composite disease monitoring models predictive of PFS and OS. Importantly, liquid biopsies and CT images will be matched within patients and analyzed at key inflection points over the course of the trial: at diagnosis, after initiation of systemic therapy, after definitive therapy, and at disease progression. In this way, the proposed work will illuminate when and how PC-relevant phenotypes arise during therapy, and how they relate to clinical outcomes. In particular, we will better understand which components of the liquid biopsy – circulating cells, plasma, or both – most accurately reflect the tumor's evolving molecular profile, which radiomic metrics most closely correlate with these molecular features and can serve as early cost-effective indicators of emerging resistance, and which composite models combining liquid biopsy and radiomic features best predict PFS and OS and can serve as powerful minimally-invasive tools to monitor and adjust therapy.

NIH Research Projects · FY 2025 · 2021-02

Project Summary/Abstract If no preventative measures are developed, the number of individuals suffering from Alzheimer’s Disease (AD) is expected to triple by 2050; many of whom will be members of a minority group. Ethnic and racial disparities in Alzheimer’s disease exist; however, these disparities are severely understudied, especially amongst African Americans. The consequent need for less invasive and more cost-effective tools to identify stages of AD at an earlier and perhaps more treatable time-point has fueled research into plasma biomarkers. Neural (NDEs) and astrocyte-derived exosomes (ADEs) have demonstrated biomarker potential for detecting stages of AD and predicting the conversion of MCI to AD. Although the field has been focused on NDEs and ADEs, there are surprisingly no published reports demonstrating the biomarker potential of microglial derived exosomes (MDEs). Any potential value of plasma exosome cargo to accurately identify stages of MCI and predict the conversion of MCI to AD, will require additional validation studies that specifically account for ethnic and racial differences amongst its patient cohorts. Understanding how ethnic and racial factors modify AD risk can yield new insights into race-dependent biological mechanisms, which in turn, can inform future diagnostic and therapeutic interventions. With the existing infrastructure at my home institution (UCSD), reagents and combined expertise of my mentor and collaborators, I will use a multidisciplinary approach to accomplish my research objectives. In the mentored phase of this proposal, I will be trained in unbiased, Mass spectrometry (MS)-based proteomic profiling for novel biomarker identification. My mentored studies will also involve the purification and characterization of MDEs. Lastly, I will also use these samples to study the diagnostic and prognostic utility of ADE and MDE cargo proteins (e.g. Aβ and p-tau) to predict conversion of MCI to AD. During the independent phase, I will apply the methods and perspectives learned in the mentored phase of this application to cross-validate the biomarker potential of plasma exosomes in a live cohort of African American patients who are at risk for developing AD. Successful completion of this study will significantly advance the field of exosome biology in neurodegeneration and may lead to the identification of novel biological targets for therapeutic development of AD. The training and mentorship that I will receive because of this funding award will undoubtedly contribute to my productivity as an independent scientist. Moreover, the K99/R00 mechanism will provide with the support necessary to advance of establishing an NIH- R01 funded, independent laboratory where I plan to continue my studies in racial disparities, exosome biology and biomarker discovery.

NIH Research Projects · FY 2025 · 2021-01

Project Summary: Noninvasive transcranial detection of intracranial hemorrhage using a tri-coil handheld portable eddy current damping imaging device Stroke and traumatic brain injury (TBI) are common causes of death and permanent disability worldwide, costing the U.S. health system more than $71 billion per year in lost productivity and medical expenses. Existing paradigms for stroke/TBI diagnosis require computed tomography (CT) or magnetic resonance (MR) imaging to classify ischemic versus hemorrhagic variants prior to intervention, as treatment for these conditions varies widely. Delays in diagnosis and issues related to transport of unstable patients associated with diagnostic imaging increase the likelihood of neurological injury and death. Translational medical devices that accelerate time-to-treatment in the field or hospital setting may help to reduce morbidity and mortality in stroke/TBI patients on a global level. Our team has developed a portable, rapid and noninvasive imaging and detection device based on eddy current damping (ECD) sensors that can detect brain hemorrhages associated with stroke and TBI, and have demonstrated feasibility in a benchtop, human cadaver and clinical patient setting. This device can potentially diagnose and classify hemorrhagic stroke/TBI subtypes with accurate spatial localization in minutes, rather than hours, thereby guiding early responders and medical providers in making time-sensitive medical decisions for clinical intervention, such as administration of tissue plasminogen activator for ischemic stroke. Our overall goal is to demonstrate the effectiveness of this novel stroke detection device in rapidly triaging stroke/TBI patients and achieving a level of diagnostic accuracy capable of guiding clinical intervention. We hypothesize that: 1) Regional conductivity changes in brain tissue can be imaged and detected using the portable ECD sensor; 2) Hemorrhagic stroke and TBI-related hemorrhages will increase regional conductivity, whereas ischemic stroke will decrease dependent brain conductivity in affected ischemic regions; and 3) Portable stroke imaging may reduce time-to-treatment and diagnosis associated with stroke/TBI. To test these hypotheses, we aim to: 1) Perform benchtop laboratory experiments to further elucidate how direction and magnitude of measured conductivity changes can differentiate stroke subtype and location, 2) Use validated human cadaver stroke simulation models to optimize ECD tri-coil array sensor detection of hemorrhage depth, volume, and location, 3) Utilize machine learning algorithms to quickly classify brain lesions with high accuracy, and 4) Implement early clinical stroke/TBI ECD sensor device testing to gauge effectiveness in live human patients, compared to CT/MR imaging. Development of methods for rapid bedside stroke/TBI diagnosis will provide practitioners with knowledge required to rapidly administer life-saving treatments, thereby improving patient quality of life and survival. Knowledge derived from this will help to reduce time-to-treatment and guide triage and intervention, which is likely to translate to improved morbidity and mortality associated with these common conditions.

NIH Research Projects · FY 2025 · 2021-01

ABSTRACT One in three seniors dies with Alzheimer’s disease (AD) or another dementia - diseases that cost the nation $259 billion, to rise to $1.1 trillion by 2050 (Alzheimer’s Association, 2017). Despite the vast personal and economic cost of these diseases, two major barriers stall efforts to discover key biological mechanisms that influence brain aging. First, the sheer cost of data collection means that most national initiatives have limited power to detect factors that affect brain aging. Even in datasets of N=1,000+ people (e.g., ADNI) – the power to discover modulators of brain aging is limited and may not generalize worldwide. Second, with the crisis of reproducibility, we do not always know if a finding will replicate; and if not, if this is due to true population heterogeneity or problems with methods. ENIGMA offers a coordinated global approach to solve these problems. ENIGMA’s World Aging Center is a global brain aging study that builds on our vast and highly productive ENIGMA consortium - a global network of 340 institutions in 45 countries. ENIGMA published the largest-ever genetic studies of the brain (Nature 2017; Science 2020), and the largest neuroimaging studies of 5 major psychiatric disorders. ENIGMA’s World Aging Center is a concerted global effort to pool all available data, methods, expertise and capital infrastructure to discover factors that affect brain aging. Our long-term goal is to identify personalized biological predictors of brain structural and functional decline and assess how they generalize globally. We have 4 aims: Aim 1: ENIGMA-Lifespan. Develop Lifespan Charts for Brain and Neural Tract Aging in 20,000 people. We will create charts showing how MRI brain measures change throughout life in 20,000 people, aged 1-92. We will compute a composite brain aging score, ‘Brain Age’, from available MRI, DTI, rsFMRI data, that measures how much the brain deviates from expected values, for a person’s age and sex. Aim 2: ENIGMA-Epigenetics. Relate genome-wide methylation levels to brain metrics in 10,000+ people, to discover epigenetic markers of accelerated brain aging. We discovered 2 epigenetic loci promoting brain aging in pilot studies. We will compute a “epigenetic clock” and test if it predicts brain metrics better than simple biological age. Aim 3: ENIGMA-Plasticity. Discover genomic loci that promote or mitigate brain tissue loss, in > 37 worldwide cohorts with longitudinal MRI. Aim 4: ENIGMA-Alzheimer’s Disease (New Aim). Meta-analyze the role of APOE, AD polygenic risk, and a new risk score for accelerated atrophy on neuroimaging biomarkers in aging and AD, including amyloid and FDG PET. These aims seek to analyze worldwide imaging, epigenetic, and clinical data with harmonized methods. We aim to create new aging “clocks” and reveal targetable risk factors and modifiers of brain aging in the genome and epigenome, test how and when they shift AD biomarkers, and test their generalizability worldwide.

NIH Research Projects · FY 2026 · 2021-01

PROJECT SUMMARY/ABSTRACT Nonalcoholic fatty liver disease (NAFLD) leading to nonalcoholic steatohepatitis (NASH) is a major cause of chronic liver disease that may progress to cirrhosis and hepatocellular carcinoma (HCC). Considering the prevalence, particularly among Hispanics, understanding the etiology and mechanisms of this disease by race/ethnicity is imperative. We have established a multidisciplinary team to comprehensively characterize the dynamic interplay of multiple factors (genetics, lifestyle, environmental and immune factors) in NAFLD/NASH and the underlying mechanisms driving incidence, severity and progression that result in health disparities in Hispanics. We will identify factors associated with NAFLD development and progression in Hispanics and non- Hispanic whites (NHW) in Los Angeles County (LAC). The large immigrant populations in LAC offer unique perspectives and opportunities to examine health disparities in Hispanics. We will enroll 2,000 patients (1,000 Hispanics and 1,000 NHW) with FibroScan-confirmed advanced (>F2) and mild (≤F1) hepatic fibrosis and 1,000 matched controls without ultrasonographic evidence of NAFLD recruited from the LAC and USC Keck Hospitals. We will collect biological specimens, clinical and detailed questionnaire data for sociodemographic and risk factors and use geospatial approaches to ascertain social and neighborhood-related factors. Case groups will be followed prospectively for disease progression. Our specific aims are 1) to determine the contribution of lifestyle, clinical, social/environmental factors and genetics (nuclear and mitochondrial) to ethnic disparities in NAFLD risk, disease severity (advanced/mild fibrosis) in Hispanics and NHW; 2) to examine how differential gene expression revealed by scRNA-transcriptomic profiling of circulating innate immune cells in NAFLD varies according to polygenic risk scores and dietary factors; utilize bioinformatics approach to identify plasma proteins with diagnostic and predictive accuracy for NAFLD severity and progression; 3) to identify high-risk groups for NAFLD risk and progression by integrating genetics, lifestyle, clinical, social and contextual factors in Hispanics and NHW using an innovative latent variable analysis. Our study will culminate in novel, comprehensive, and innovative characterization of multi-level factors associated with phenotypic spectrum of NAFLD and disease progression and contribute significantly to the understanding of the etiology and mechanisms that influence disparities in NAFLD in high-risk Hispanic population.

NIH Research Projects · FY 2025 · 2021-01

PROJECT SUMMARY/ABSTRACT We aim to reduce the limb-threatening and life-limiting burden of neuropathic diabetic foot ulcers (DFU) by advancing science in its most critical component: protective pressure offloading. We intend to do this via a randomized comparative effectiveness study of a first-ever smart removable offloading device (MOTUS Smart), which enables objective monitoring of adherence as well as adherence reinforcement (real-time notification of poor adherence via smartwatch + feedback via smartphone). Prescribed offloading, such as a removable cast walker (RCW), is used to reduce pressure on the bottom of the foot to protect the DFU. This allows it to heal while allowing the patient to be mobile. These devices can be a key component of healing and prevention of DFU. Unfortunately, patient adherence with these devices is poor. While irremovable offloading devices could address this challenge, they have other limitations including poor acceptability (because of its irremovability during sleep and shower), poor scalability (e.g., only 2% of U.S. clinics regularly prescribe this gold-standard therapy), poor patient-centered outcomes (e.g., poor sleep quality), and high likelihood of deconditioning (frailty/leg muscle atrophy) induced by offloading because of prolonged ankle joint immobilization leading to high recurrence rate of DFU. Another scientific gap in the field is poor understanding of the influence of weight-bearing activity on plantar wound healing. Some report that regular weight-bearing activity even while wearing protected offloading may delay healing. Others suggest that stable and appropriately dosed protected weight-bearing exercise is beneficial to accelerate healing. Given the debilitating nature of DFU and the high cost of treatment, there is a need for novel technological approaches to motivate neuropathic patients without normal painful feedback to adhere to prescribed offloading and to enable clinicians to monitor and counsel patients on physical activity and adherence. In this study, we will enroll 216 ambulatory patients with active DFU randomized to three groups (ratio: n=1:1:1). The first group includes the gold-standard treatment, an irremovable boot (which forces patients into adhering to protective offloading of pressure). The second group includes an otherwise identically equipped traditional removable device along with traditional counseling regarding the importance of adherence to offloading. The third group will include a “smart” removable cast walker that includes adherence reinforcement and remote patient monitoring. All three groups’ devices will be embedded with sensors that will allow monitoring of adherence and activity. This study enables us to examine the benefit of adherence reinforcement to speed up wound healing (Aim 1); the association between dosage of physical activity and wound healing (Aim 2); and patient-centered outcomes between the three treatment arms (Aim 3).

NIH Research Projects · FY 2025 · 2020-12

Project Summary Cardiovascular disease (CVD) accounts for the largest proportion of mortality and morbidity worldwide. While a strong body of evidence supports a role for long-term air pollution exposure in CVD among adults, relatively little is known about how air pollution exposures may affect the development of subclinical atherogenesis in younger populations. Early markers of these pathogenic processes, including carotid artery intima-media thickness (CIMT), arterial stiffening (CAS), and arterial wall composition as measured by echogenicity, may provide insight into different facets of the beginnings of disease. The lack of longitudinal studies with repeated characterization of measures of subclinical atherosclerosis in younger populations is a major gap in the field and it is unclear whether early life exposures to air pollutants may impact the progression of carotid atherosclerosis from childhood into adulthood. We hypothesize that ambient and traffic-related air pollutant exposures may influence the development of adverse subclinical cardiovascular phenotypes, indicated by carotid atherosclerosis progression, as children grow into early adulthood. We will test this hypothesis within the Southern California Children's Health Study (CHS), one of the largest and most comprehensive investigations of the long-term effects of air pollution on children's health. Carotid artery ultrasounds were performed on a subset of CHS children at age 10, providing an early measure of subclinical atherosclerosis. As these participants now approach early adulthood (~21-23 years), we are uniquely poised to address the question of whether lifetime air pollution exposures are associated with changes in atherosclerosis markers from childhood into early adulthood. Using childhood carotid artery ultrasound images as a baseline measure, we propose to leverage ongoing follow-up of CHS participants to obtain a repeat assessment of subclinical atherosclerosis measures (CIMT and CAS), and calculate carotid echogenicity (GSM), a novel metric of arterial wall composition, from baseline and follow-up ultrasound images. We will evaluate the effects of residential ambient and traffic-related air pollutants on changes in these measures of subclinical atherosclerosis over time, as well as attained level of atherosclerosis in early adulthood. We will also evaluate the relation between air pollution exposure and biomarkers of cardiometabolic dysfunction (glucose, lipids, HbA1c), to begin to investigate potential mechanisms underlying early atherosclerosis. This novel study will fill a critical gap in our knowledge of subclinical atherosclerosis in children over time and investigate the impact of lifetime air pollution exposure on early phases of disease progression.

NIH Research Projects · FY 2025 · 2020-12

PROJECT SUMMARY Obesity and diabetes are associated with the chronic overconsumption of high sugar foods and fluids, driven in large part by their palatable taste. A single heterodimeric G-protein coupled receptor (T1R2+3) found in mammalian taste cells is widely considered the principal means through which all simple sugars are detected and promote ingestion via the gustatory system. Yet, recent studies from our laboratory revealed that rodents come to respond more positively to the orosensory properties of glucose over fructose, when provided the opportunity to learn about their divergent metabolic consequences, and this phenomenon does not require the canonical T1R2+3 taste receptor. Collectively, these published studies point to the existence of a previously unknown taste receptor linked to glucose appetite. The preliminary findings included in this proposal now show that glucokinase, a phosphorylating enzyme involved in other glucosensing mechanisms, is expressed in murine taste cells. We further demonstrate that glucokinase levels in the taste tissue are regulated by energy state and dietary sugar exposure. Moreover, pharmacological activation of lingual glucokinase specifically bolsters licking behavior and neural responsiveness in the chorda tympani nerve for glucose, but not fructose or water. Our working hypothesis is that glucokinase is part of a T1R2+3-independent taste receptor that transduces glucose- specific signals in the gustatory system. The overall goal of this proposal is to further clarify the functional and molecular properties of this novel gustatory glucosensor. In Aim 1, we will combine genetic and pharmacological approaches to selectively disrupt and/or activate canonical “sweet” taste inputs and lingual glucokinase while measuring taste-driven licking for various “sweet” and “non-sweet” tastants in sugar-naïve and sugar-exposed mice. With immunoblot and qPCR, we will further quantify changes in glucokinase and other sensory mechanisms linked to glucokinase in taste tissue as a function of dietary sugar exposure. In Aim 2, we will combine genetic and pharmacological approaches to psychophysically assess the discriminability of glucose, fructose, and other tastants in a series of two response operant discrimination tasks in order to fully elucidate the behavioral outputs functionally linked to gustatory glucosensors. In Aim 3, we will combine genetic and pharmacological approaches with electrophysiology to determine how T1R2+3-independent, glucokinase-linked taste signals are neurally-transmitted from tongue to brain. The outcomes of these aims will identify novel and potentially critical aspects of nutrient sensing, with the ultimate goal of identifying potential new strategies to curb appetite.

NIH Research Projects · FY 2025 · 2020-12

PROJECT ABSTRACT Recent clinical trials, using checkpoint blockade, antigen-specific T cell receptor (TCR) or CD19-chimeric antigen receptor (CAR), have shown promising clinical results for patients with metastatic cancer. However, despite the impressive and durable clinical response in cancer patients treated with anti-PD-1 antibody, more than 50% of cancer patients fail to respond to this checkpoint blockade treatment. Immunotherapy based on vaccines and TCR in many solid tumors is still lacking due to lack of tumor-specific targets. Therefore, new targets and strategies are urgently needed for the development of immunotherapeutic approaches for solid tumors including melanoma. Whole exome sequencing approach in combination with computer-assisted prediction algorithms has provided an exceptional opportunity to identify new patient-specific antigen targets for cancer immunotherapy. By taking advantage of next-generation sequencing and tumor-reactive T cells, we recently identified many neoantigens recognized by tumor-reactive CD4+ T cells as well as CD8+ T cells. Importantly, we found that some of CD4+ T clones with a single TCR could recognize multiple neoantigens, but not the corresponding wild-type antigens. Recent clinical studies show that mutation-specific CD4+ T cells can mediate tumor growth inhibition in melanoma and epithelial cancers, suggesting that CD4+ T cells play a critical role in inhibiting tumor growth and orchestrating overall antitumor immunity. However, clinical responses of cancer patients are correlated with the trafficking, persistence and cytotoxic ability of T cells. We show that CD4+ T cells can be reprogrammed to increase their cytotoxicity activity against cancer cells. Based on these premises, we hypothesize that neoantigen-specific T cells, in particular CD4+ T cells, play an important role in recognizing neoantigens that drive tumor-specific antitumor immunity, leading to tumor regression. These neoantigens can be identified from melanoma and exploited as therapeutic targets for immunotherapy. We further hypothesize that neoantigen-specific CD4+ T cells can be engineered for improving their T cell persistence and cytolytic activity in combination with anti-PD-1 blockade. Based on these premises, we propose to identify novel neoantigens with emphasis on MHC class II neoantigens using genome-wide sequencing analysis and a genetic targeting expression system (Aim 1). We further plan to investigate whether potent therapeutic antitumor immunity can be generated by immunodominant neoantigen and a novel SAPNANO vaccine technology (Aim 2). Finally, we pursue our studies to determine whether SAPNANO vaccine-induced or T cell transfer immunity can be further enhanced by immune checkpoint blockade or reprogramming T cells to improve their cytotoxicity, (Aim 3). In all, the successful completion of our proposed studies will potentially shift the paradigm by the development of novel immunotherapies for many types of cancer including melanoma.

NIH Research Projects · FY 2024 · 2020-09

Project Abstract Outdoor air pollution, including fine particulate matter (PM2.5; and its constituents) and nitrogen dioxide (NO2), is ubiquitous in urban areas and is a neurotoxicant. Emerging toxicological and epidemiological evidence suggests that air pollution may contribute to increases in emotional behavioral problems and is linked to various mental health disorders in children, adolescents, and adults. These recent findings have elucidated the need to: 1) examine long-term effects of prenatal and childhood exposure; 2) identify pre-clinical neuroimaging biomarkers of neurotoxicological effects in neural circuitry implicated in mental health risk; and 3) investigate these effects in late-childhood and adolescence, as it is an opportune time to identify and intervene for those at risk for psychiatric disorders. We propose the first longitudinal study to examine how prenatal and childhood air pollution exposure impacts corticolimbic circuitry involved in emotion processing and regulation, and the onset of internalizing and externalizing psychopathology during the transition from late-childhood to early adolescence. Our hypothesis is that prenatal and childhood air pollution exposure contribute to increased risk for mental health disorders during adolescence through alterations in corticolimbic neural circuitry and emotional development. To test our hypothesis, the proposed project will create lifetime residential air pollution exposure estimates and leverage comprehensive neuroimaging of corticolimbic neural circuitry, emotion, and mental health data, from a multi-ethnic and geographically diverse cohort of 9- to 10-year-old children (N=11,873) enrolled in the nationwide longitudinal Adolescent Brain Cognitive Development (ABCD) study. Using multi-modal neuroimaging, we will elucidate the effects of prenatal and childhood air pollution exposure on changes in the structure (Aim 1) and function (Aim 2) of corticolimbic circuitry underlying emotional processing and regulation from late-childhood to early adolescence. In Aim 3, we will examine how prenatal and childhood air pollution exposure influences the development of emotional problems and subsequent risk for mental health disorders by using both: a) dimensional scales and b) mental health diagnostic criteria (based on Diagnostic and Statistical Manual of Mental Disorders). As an exploratory sub-aim, we will also examine a potential mediation of corticolimbic alterations at 9-10 yrs in the link between air pollution exposure during development and subsequent risk for internalizing and externalizing psychopathology at ages 11-12 yrs. This study is primarily focused on long-term prenatal and childhoodPM2.5 and NO2 exposure; however, we also plan to explore differential timing effects of these exposures as well as the potential neurotoxic effects of other ambient pollutants (i.e. ozone, PM components). The large, sociodemographic and geographic diverse sample of children from ABCD are at an opportune age to evaluate pre-clinical markers of psychopathology. This provides great promise for more robust and generalizable findings that have the potential to impact policy as well as identify early neuroimaging biomarkers as targets for early intervention.

NIH Research Projects · FY 2024 · 2020-09

ABSTRACT Alzheimer’s disease (AD) threatens to devastate society worldwide. For every 5 years of age over age 65, the prevalence of AD doubles, costing an estimated $277 billion in the U.S. in 2018, a $20 billion increase from the previous year. Here we propose a coordinated global study of brain aging and AD, that uses novel approaches to assess the white matter microstructure of the brain’s neural pathways - a crucial brain metric that breaks down on the pathway from molecular AD pathology to clinical decline. With a novel deep learning tool, called FiberNET, we extract and analyze the brain’s white matter fiber bundles obtained from diffusion MRI (dMRI) scans across the world, and answer 3 key questions: how do the brain’s tracts age worldwide? How does tract aging depend on sex, Alzheimer’s genetic risk, and brain amyloid load? Can tract metrics predict clinical decline better, when combined with standard, accepted biomarkers of AD? The proposal unites experts in AD, neuroimaging, machine learning, and large-scale genomics, to relate new aging metrics (tract microstructure) to protective and adverse factors. Novel mathematics include innovations in picking up crossing fibers and tissue properties from multi- shell diffusion MRI, and convolutional neural nets to learn patterns of aging in neural pathways worldwide. We aim to (1) use FiberNET, our deep learning method, to extract tracts from brain dMRI scans worldwide, and create normative charts for normal tract aging in 20,000 people across the lifespan; (2) ask how the tract aging trajectory depends on sex, the AD protective genotype APOE2, risk genotype APOE4, and brain amyloid load measured with amyloid-sensitive PET. The proposed study will create standardized charts of white matter tract integrity across the lifespan to serve as a guidepost for normative white matter aging. We build on our ENIGMA- Lifespan work - which analyzed brain MRI data from 10,144 people from 91 cohorts - to create lifespan charts for the brain’s major tracts from dMRI, yielding fundamental normative information for comparisons of AD groups worldwide. This lifespan approach will aid the discovery of personal factors that accelerate aging relative to population norms (e.g., sex, APOE genotype, and amyloid load). To ensure the impact of the developments, we created a team of beta-testers to help test and refine the methods, that is tightly integrated into our ENIGMA consortium, which is dedicated to cross-cohort data harmonization. This global approach to aging and AD will offer a new source of power to “break the logjam” in discovering factors that affect the brain as we age.

NIH Research Projects · FY 2026 · 2020-09

ABSTRACT Our U01 renewal application - Artificial Intelligence for Alzheimer's Disease (AI4AD) - expands on four productive themes from our prior funding period, supported by strong empirical results in our recent high impact publications. By developing cutting-edge Artificial Intelligence and Machine Learning (AIML) approaches, we address four key NIA mandates: (1) molecular subtyping for precision medicine, (2) improving Alzheimer’s Disease and Related Dementias (ADRD) clinical trial design, (3) adapting AI models to diverse cohorts for genetic target and treatment selection, and (4) genome-guided drug repositioning. Aim 1 develops a genomic extension of Large-Language Models to discover genomic markers associated with clinical AD onset and progression. We will adapt this breakthrough technology to process genomic sequences, to discover genomic targets associated with Alzheimer’s Disease (AD), AD biomarkers, and endophenotypes. We will compare the findings to those from our other AI-driven tools for gene discovery (SWAT-CNN, DeepBlock) and our whole genome tiling approach. In the Alzheimer’s Disease Sequencing Project (ADSP), over 60k people have 3-billion base-pair whole genome sequences–linked to imaging and deep phenotyping. Our AI-driven Genomic Discovery toolbox will reveal new AD-relevant genomic motifs that improve AD classification and predict disease progression more accurately than traditional AD GWAS-based models, such as polygenic risk. Aim 2 focuses on ADRD subtyping. Our AI tools will unravel the heterogeneity of dementia by deriving subtypes based on (1) clinical and cognitive data, (2) molecular neuropathology, and (3) neuroimaging. Subtyping across multiple dimensions will help more precisely define a patient’s diagnosis, and will eventually enhance treatment efficacy, re-stratify drug trial data to identify best responders, and allow gene discovery focused on subtypes. Our pilot work trained an AI method on ADSP and NACC datasets with post mortem neuropathology to infer scores for TDP-43, cerebral amyloid angiopathy, and Lewy body mixed-pathology subtypes. After validating this method on the large, diverse, incoming ADSP cohorts, we will run GWAS and whole-genome tiled association analyses to find genomic signatures linked to these subtypes. Aim 3 ensures our AI-based models are applicable across all ancestries, addressing the lack of validation for non-European groups. Our ancestry-informed models will leverage the new wave of ADSP data on local ancestry and social/environmental determinants of health. Aim 4 will enhance genome-guided treatment of ADRD by developing PreSiBo, an end-to-end drug discovery system matching treatments to specific subtypes. Focusing on molecular subtyping, we will validate subtype-specific targets and drugs using medication data from large cohorts, data from iPSC lines, and brain samples, based on the finding that ADRD drugs with genomic support are more likely to achieve FDA approval. Our renewal will advance precision medicine in ADRD through AI- driven approaches, creating robust. inclusive strategies for diverse populations.

NIH Research Projects · FY 2024 · 2020-09

Project Summary A fundamental question in developmental biology concerns the origin and control of patterns and shapes, also known as morphogenesis. Multicellular signaling networks, encoded in genetic networks, underlie the normal development of embryos and drive their morphogenesis. Paradigmatic example is the periodic segmentation of mesoderm into somites, the precursors of the vertebrae, during vertebrate development. Changes in genes, effector proteins, and cellular environments can lead to altered embryonic development as seen in congenital disorders. To cure diseases we need to understand how genes control cells at multiple scales and how groups of cells form coherent, functional tissues and organs. The last years have witnessed a boom in discoveries in developmental biology with single-cell sequencing, microfluidics, optics, increased computational power leading to unprecedented spatiotemporal resolution of the multiscale dynamics of morphogenetic systems, from molecules to cells to whole embryos. While these advancements have produced detailed roadmaps of the events orchestrated during develop- ment, we still lack a clear picture of which cellular networks drive collective morphogenetic programs. The classical forward and reverse genetic perturbative screenings, and even modern perturbative tools like optogenetics, still mainly focus at the level of the gene(s) or single signaling pathways. This makes it challenging to infer causal relationship between complex multicellular networks and developmental transitions. New perturbative tools are needed that could construct similar complexity as the ones observed in vivo. As these complex networks in vivo are based on cell-cell and cell-environment communication pathways, we need controllable versions of those pathways that we can (i) link in complex synthetic networks, (ii) use to control endogenous developmental pathways. Such a system would enable the introduction of precise and complex spatiotemporal perturbations at the level of the networks instead of the gene(s), ultimately delivering increased understanding of the relationship between complex networks and resulting developmental transitions. In our lab we develop synthetic cell-cell and cell-ECM pathways, connect them in networks, and use them to investigate developmental processes. Here we propose to (i) use these tools to investigate the mechanistic contribution of Notch signaling to the formation and propagation of signaling waves in the presomitic mesoderm and, (ii) develop new tools for cell-ECM communication, inspired by developmental signaling. We expect to enter a cycle of toolsàtestàanswersànew questionsànew tools. These studies will advance the field of developmental biology by shedding light on the behavior and logic of multicellular systems and how complex networks enable control across scales of space and time. Gaining insight and tools to direct developmental cell populations would have widespread relevance for the treatment of developmental defects and our capacity to control the growth of tissue and organs in a dish.

NIH Research Projects · FY 2024 · 2020-09

7. Project Summary/Abstract Discovering preclinical markers of cognitive and functional decline in mild cognitive impairment and dementia is fundamental for treatment development and to delay disease onset and progression. Subtle functional deficits on cognitively demanding activities often foreshadow dementia onset, but these early deficits are difficult to assess objectively with conventional methods. The proposed studies aspire to develop and validate performance-based indices for measuring functional deficits at older ages that are cost-effective, unobtrusive, and that could serve as early markers of subsequent cognitive decline and dementia. Specifically, we propose to develop indices of functional deficits that can be derived from participant response behaviors in existing population representative surveys. Completing a survey is a complex and cognitively demanding task that taxes a respondent's neuropsychological capacity. By focusing on how individuals complete surveys, we aim to derive a series of indices of functional deficits using two approaches: (1) The first approach consists of indices that are directly computed from participants' response patterns in questionnaires to capture invalid, incoherent, or erroneous responding on rating scales (examples include agreeing or disagreeing with statements regardless of content, skipping questions, or giving contradictory responses). (2) The second approach considers indices derived from individuals' computer use behavior in online surveys to measure the efficiency, speed, and consistency of behaviors during the completion of online surveys (examples include the proportion of corrected/changed answers, average response time, and response time variability). To evaluate the validity and clinical utility of the indices, we will systematically examine their associations with conceptually related constructs (concurrent cognitive test scores, instrumental activities of daily living, financial wellbeing, frailty), their sensitivity to change with age, their ability to predict subsequent cognitive decline, and their ability to predict the subsequent onset of mild cognitive impairment and dementia. Self-report surveys administered regularly in 16 existing longitudinal panel studies (>50,000 participants) will provide a rich basis for developing and testing indices derived from response patterns in questionnaires. An ongoing population representative Internet panel will provide the opportunity to test computer use behavior indices that are unobtrusively recorded “in the background” of online surveys. Marshalling multiple datasets and aggregating results across diverse samples and survey measures using identical data-analytic models will greatly enhance generalizability and test the breadth of applicability of each index. Examining the predictive accuracy of the indices alone and in concert will allow us to identify those indices that contribute substantial prognostic information and those that provide irrelevant or redundant information. This research has potential to broaden the repertoire of available tools that could signal cognitive and functional decline in older ages and allow for advanced study of dementia.

NIH Research Projects · FY 2024 · 2020-09

Project Summary Fine particulate matter (aerodynamic diameter<2.5 μm; PM2.5) is a novel and ubiquitous environmental neurotoxin affecting neurobehavioral development of millions of American children living in urban areas. However, our review points to several major methodological limitations and critical knowledge gaps in the extant literature, including: 1) the lack of studies with longitudinal brain and behavior assessments; 2) relatively small samples from localized geographical areas; 3) little to no information on long-term cumulative and/or differential timing of exposure across development; and 4) remaining questions regarding the neurotoxicity of PM2.5 exposure on critical neurobehavioral processes that continue to mature across adolescence. Although animal neurotoxicology studies have highlighted the importance of sex, there is only limited epidemiologic evidence for sex difference in PM2.5 neurotoxicity in children. Moreover, brain development is also shaped by family- and community-level social factors, but whether and how air pollution neurotoxicity interacts with the social context remains unclear. This application will leverage the nationwide longitudinal Development (ABCD) study of 9- and 10-year-olds (N=11,873) Adolescent Brain Cognitive to examine prenatal and childhood air pollution exposure effects on neurobehavioral development in boys and girls across 21 U.S. cities. ABCD outcome measures are anchored on the transition to early adolescence because neuromaturation continues from childhood through early adulthood, making such developmental transition periods potentially more vulnerable to environmental insults. Our primary exposure of interest is PM2.5, but advances in well-validated spatiotemporal modeling tools will also allow us to explore neurotoxicity of PM composition and other gaseous pollutants (i.e. NO2, O3). Given the reconstructed exposure histories from gestation to childhood to early-adolescence, we will: (a) determine long-term cumulative exposure effects; and (b) examine differential exposure effects across sensitive time windows to better define PM2.5 neurotoxicity on executive functioning (EF) and emotional behaviors from ages 9 to 12 years-old (Aim 1); and also understand how the resulting neurotoxicity influences structural and functional brain development, including brain morphology, white matter microstructure, brain activity at rest and during EF and emotion-focused tasks, and functional connectivity of large-scale networks (Aim 2). In Aim 3, we will evaluate if children are more susceptible to PM2.5 effects based on: a) sex and SES; and b) family- and neighborhood-level contextual risk and protective factors. This application will advance our understanding of air pollution neurotoxicity on adolescent brains, as well as how exposure effects may vary across sensitive time windows of development and/or differ by individual susceptibility. The resulting new knowledge will contribute to sciences-based air pollution regulations to protect public health, but also inform the development of preventions and interventions targeting sensitive time-windows and vulnerable populations.

NIH Research Projects · FY 2026 · 2020-09

Overall: Project Summary – 2P30AG066444-06 The Washington University Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) initiates, fosters, and supports the performance of innovative, cutting-edge research on Alzheimer disease (AD) and related dementias (ADRD) with regard to the etiology, pathogenesis, diagnosis, treatment, and prevention of disease. We provide well-characterized research participants (persons with symptomatic AD and age-matched controls), their clinical, cognitive, and imaging data, and their biospecimens (DNA, CSF, plasma, dermal fibroblasts, iPSCs, brain tissue) to research projects. We also provide intellectual and financial support to scientists at Washington University, other Alzheimer Disease Research Centers, and the research community nationally and internationally and engage in formal and informal collaborations, including multidisciplinary/multi-Center studies and the initiatives sponsored by the National Institute on Aging and the National Alzheimer Coordinating Center. Historically, our Center has focused on the earliest stages of dementia to identify the initial clinical and pathologic changes that distinguish AD from normal aging. Our approach is balanced between clinical and basic science domains with emphasis on interdisciplinary efforts. We will continue our training of students, fellows, and junior faculty in clinical and basic science research skills. We will continue to engage in outreach activities to transfer information on ADRD to lay and professional audiences. We are committed to assuring that our research cohort includes individuals at higher risk for dementia from the greater metropolitan St. Louis area. This renewal application includes eight Cores, plus the Research Education Component (REC): A: Administrative, B: Clinical, C: Data Management & Statistics, D: Neuropathology, E: Outreach, Recruitment, & Engagement, F: Biomarker, G: Genetics & High Throughput -Omics, and H: Health Disparities Engagement.

NIH Research Projects · FY 2024 · 2020-09

PROJECT SUMMARY There are now hundreds of thousands of people enrolled in biobank studies, with genome-wide genotypes and rich phenotype data recorded. These data are an unprecedented resource for learning about human genetic and phenotypic variation. At the same time, population geneticists are developing advanced tools for representing large genetic datasets as ancestral recombination graphs, which concisely encode the genealogical relationships among genomic segments from different people in the dataset. Combining biobank-scale data with these advanced computational tools presents a tremendous opportunity, but we need new statistical methods to realize the possible benefits. My research group will develop and apply such statistical methods to complex biomedical traits, drawing on expertise in population-genetic theory, statistical genetics, and computation. First, we will leverage our new methods and large public datasets to study the evolution of genetic variants associated with biomedically relevant traits, providing important clues about disease etiology. Ancestral recombination graphs can encode all historical information available in a sample of contemporary genomes, so they are a rich basis for evolutionary inference. Second, we will also develop methods for enhancing genome-wide association studies (GWAS) aimed at discovering trait-associated genetic variants. Many key GWAS goals that remain challenging today—adjustment for population stratification and assortative mating, fine mapping of causal variants, and others—hinge critically on parsing correlations among both neighboring and distant genetic loci. Ancestral recombination graphs represent such correlations naturally, and so emerging tools present a variety of novel possibilities for clarifying the genetic basis of trait variation, including heritable differences in disease susceptibility. Finally, a third leg of our research program will be aimed at protecting the privacy of participants in large genetic databases. The assembly of large genetic datasets is critical to biomedical research and also hinges on public trust that privacy can be ensured. We will consider a set of new privacy threats that will arise as genetic research advances, particularly as genotype–phenotype associations are better understood and as applications of genetic genealogy become more prevalent.

NIH Research Projects · FY 2025 · 2020-09

Abstract Hyperphosphorylated tau tangle is a defining hallmark of the Alzheimer’s disease (AD). Neuropathological and recent tau PET imaging studies suggest that tau deposition has a much stronger correlation with clinical symptoms than do amyloid plaques. The Braak staging suggests the neuron-to-neuron propagation of tau pathology through axonal pathways, which has been supported with increasing evidence from animal and post- mortem human studies. Limited research, however, has been conducted for the in vivo examination of connectivity changes of fiber pathways involved in tau pathology propagation. There is thus a clear knowledge gap regarding WHEN (specific tau pathology stage) and WHERE (specific fiber pathways) tau-induced connectivity changes occur during the disease course of AD. Building upon our extensive track record in connectome modeling and brain surface mapping, in this project we will develop novel computational tools for the systematic examination of different types of fiber pathways involved in the propagation of tau pathology: the short association fibers in the superficial white matter (SWM), the long association fibers within each hemisphere, and the commissural fibers connecting the two hemispheres. Our project will leverage existing tau PET and connectome imaging datasets that include: ADNI3 for late onset AD (LOAD) and the Estudio de la Enfermaded de Alzheimer en Jalisciences (EEAJ) study for autosomal dominant AD (ADAD). This provides us the unique opportunity to study ADAD and LOAD as being on an AD continuum and obtain a more complete characterization of the fiber pathways affected by the tau pathology from the early prodromal stage to the ultimate onset of AD. In addition, we will use an independent dataset (n=2000) from the Health & Aging Brain among Latino Elders (HABLE) study to validate the generalizability of our computational tools and connectome imaging makers to the Mexican American population. There are three specific aims in this project: 1. To develop novel computational tools for measuring superficial and deep white matter connectivity associated with tau propagation. 2. To map tau-induced connectivity changes of fiber pathways in AD. 3. To develop connectome-based prediction of tau- related cognitive changes in AD. Our project will for the first time provide the comprehensive and in vivo characterization of the fiber pathways affected by tau pathology in AD. This will help elucidate the role of different fiber pathways in the propagation of tau pathology at different disease stages, in particular the U-fibers in the SWM and the commissural fibers responsible for inter-hemispheric communications. The results from our study will provide more targeted connectome imaging makers for the early prediction of AD, especially in studies without tau PET imaging. All computational tools developed in this project will be freely distributed to the research community to enable other AD imaging researchers for more robust and thorough investigation of tau pathology networks.

NIH Research Projects · FY 2024 · 2020-09

Abstract Nicotine consumption in both combustible tobacco (cigarettes) and with electronic nicotine delivery systems (ENDS), or vaping, has become a serious health threat in the United States, particularly among adolescents. Decades of research have documented the many ways adolescent social networks, particularly friendship networks, influence the initiation, continued use, and brand choice of tobacco products. To date, however, there is no data or research on how friendship networks influence ENDS use. This study addresses this gap by proposing to add friendship network questions to two newly initiated cohorts of approximately 2,500 high school students each that are measuring ENDS use. Funding has already been acquired for the data collection for these cohorts and will start in November 2019 and October 2020. IRB approval to add the social network questions has been submitted to the IRB after consultation with the director of the USC office for the protection of human subjects. The friendship network questions to be added ask the students to name their closest friends in their grade at school. The names of all consented students are pre-entered into a roster so that the names auto-fill after a few letters are entered. This process has been implemented in other non-nicotine studies and works well. These data will then be used to test whether adolescents are influenced by their friends to initiate and continue ENDS use, as well as whether friends influence brand and flavor choices and marijuana uptake. In addition, network selection processes will be tested which occurs when people make network changes to be consistent with their behavior. Additional hypotheses to be tested include determining whether peer influence and selection: (1) are stronger among homophilous and/or stronger ties; (2) extends to dual- or poly-use; (3) occurs for brands and flavors choices; (4) occurs for dual ENDS and marijuana use. Given the longitudinal nature of the data we will construct ENDS and tobacco use trajectories and determine if network changes are associated with different trajectories. In sum, this proposal represents a timely opportunity to add a crucial piece of data to two newly initiated funded cohorts of school-based adolescent ENDS studies; namely, friendship network data. Preliminary data from a cross-sectional sample of 1,616 students in one school district in South Dakota showed a strong correlation between individual vaping and friend vaping. Longitudinal data are needed to determine the direction of this relationship and apply more sophisticated analytic techniques such as stochastic actor-oriented models.

NIH Research Projects · FY 2025 · 2020-09

This project proposes an integrated set of aims and analyses of existing social and epigenetic data from three national studies of aging in the family of Health and Retirement studies (the US Health and Retirement Study (HRS), the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA), and the Irish Longitudinal Study of Aging (TILDA)); assays of existing samples to produce longitudinal epigenetic data for the three countries are also proposed. Comparative analyses based on these data will address central questions about how life circumstances in both childhood and adulthood affect epigenetic change and how different historical and life-course exposures in these countries may result in differential patterns of associations. The project will also examine how epigenetic changes in turn are associated with health after age 50. The proposal is submitted in response to the US-Ireland Research and Development Partnership, a unique research initiative involving funding agencies from the United States (US), the Republic of Ireland (RofI), and Northern Ireland (NI). Proposals are submitted to each of the three countries with funding requested for each country's participation from their respective grant agency (e.g., US NIH); grant review is done only by NIH for all three projects based on this proposal. The project will examine the links between lifetime social, economic, psychological, environmental and behavioral circumstances, and epigenetic markers related to aging and health, and subsequent health. Epigenetic modification is one of the “hallmarks” of aging, i.e. an underlying physiological change that can speedup or delay aging-related health outcomes. Faster aging is characteristic of people in adverse social circumstances and epigenetic change, particularly DNA methylation (DNAm), appears to be especially influenced by adverse social circumstances, both at early ages and at later ages. This project will be unique in evaluating how a variety of social circumstances, i.e. low levels of education and income, minority group membership, adverse childhood experiences, adult traumas, risky health behaviors, psychological states, and chronic stress, are associated with epigenetic markers in three different countries, with somewhat different historical, social and behavioral characteristics which are operating in different health policy regimes – allowing for both replication where effects are hypothesized to be similar and differentiation where they are hypothesized to differ (e.g., where risk characteristics are differentially patterned by SES). The applicants are uniquely placed with their resources to explore how socioeconomic experiences across the life course alter epigenetic profiles to influence health outcomes such as biological dysregulation, frailty, disability, chronic disease, and premature mortality. The three data sets have been harmonized for information collection from the beginning of the studies and were designed to encourage comparative analysis. They have been harmonized in the survey information and the development of the epigenetic data in the three countries. Each country has strong independent research teams who bring unique expertise and resources and a history of collaboration to this collaborative proposal.

NIH Research Projects · FY 2025 · 2020-09

Project Summary Most sensory hearing loss is diagnosed and treated with little distinction. Indeed, ”sensorineural hearing loss” is a catch-all term. However, promising results over the last few years suggest that otoacoustic emissions (OAEs) can distinguish among sensory hearing losses that appear similar by audiogram. OAEs are non- invasive indicators of cochlear health and dysfunction that can be recorded in normal hearers and those with up to moderate degrees of hearing impairment. Though they offer a non-invasive, pre-neural window into the cochlea, their application in the audiology clinic has stagnated over the last two decades despite significant advances in the laboratory. Current clinical utility of OAEs includes only the detection of hearing loss; nothing is learned about the etiology of the hearing loss once detected. This project proposes to translate into the audiology clinic a rapid, research-proven technique to evoke OAEs with sweeping tones, allowing for the efficient, near-simultaneous recording of the two basic OAE classes: emissions produced by cochlear nonlinearities such as the distortion-product OAE (DPOAE), and those produced by cochlear reflections such as the stimulus-frequency OAE (SFOAE). These two types of emissions elucidate distinct cochlear properties, and each is uniquely sensitive to different auditory pathologies and etiologies. Analyzing combined OAE outcomes produces new relational metrics that exploit the unique diagnostic information offered by both, which initiates differential diagnosis of sensory hearing loss. Additionally, our advanced OAE system has incorporated innovative calibration techniques that mitigate the effects of ear-canal standing-wave interference, a known source of undesirable variability. These advanced calibrations improve the test-retest reliability of emissions, which allows for more accurate serial monitoring of hearing status and an expanded high-frequency test range. In this project, we will: 1) integrate existing software modules that calibrate, measure, and analyze swept-tone OAEs into a cohesive and user-friendly software program for the interleaved recording of DPOAEs and SFOAEs; 2) analyze DPOAE and SFOAE measures in a combined fashion to detect and monitor hearing loss and perform differential diagnosis for hearing impairments of confirmed etiology; and 3) strategically pare down the Combined-OAE Profile and validate its performance in an independent group of participants to produce an abbreviated clinical test for the diagnosis of sensory hearing loss. These steps will modernize and advance OAE assessment well beyond the rudimentary goal of detecting hearing loss and provide a degree of diagnostic specificity that will facilitate personalized intervention for individuals with hearing loss.

NIH Research Projects · FY 2025 · 2020-08

ABSTRACT HPV vaccination rates remain below target levels among adolescents in the United States, which is particularly concerning in safety-net populations with persistent disparities in HPV-associated cancer burden. There are numerous evidence-based strategies (EBS) designed to encourage HPV vaccination, but few programs are routinely used, much less sustained when research studies come to an end. The major research challenge we now face is not the lack of scientific knowledge about what works, but about how to integrate and sustain effective EBS for HPV vaccination within dynamic, real-world settings. Significant disruptions due to the COVID-19 pandemic further support the need to understand implementation context and processes for long- term sustainability and equity requirements of EBS for HPV vaccination in clinics serving safety-net populations (underinsured, low-income, marginalized communities). The R37 Parent Award consists of a four-year sequential mixed-methods study that identifies multilevel, community and clinic factors associated with implementation EBS for HPV vaccination within a multi-site Federally Qualified Health Care (FQHC) system. Guided by the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework and Rapid Assessment Procedure Informed Clinical Ethnography (RAPICE) process, our multidisciplinary team will evaluate longer-term sustainability, maintenance and equity requirements for use of EBS for HPV vaccination and identify factors that impact broader system-level adoption in this R37 Merit Extension Award. We also explore factors required for scaling-out and optimization for other settings and contexts. Specific aims include: Aim 1: Assess longer-term sustainability, maintenance and equity of HPV Vaccine EBS in demonstration clinics; and Aim 2: Identify factors and core strategies needed for broader FQHC system-wide adoption (scale-up) of EBS and inform requirements for spread to other safety-net settings (scale-out). There is a dearth of data on sustainability, adaptation, and scale-up/out within implementation science as it relates to integrating EBS for HPV vaccination in safety-net settings, as most intervention and hybrid trials have limited timeframes to rigorously examine these longer-term outcomes. This R37 MERIT Extension request will leverage two additional years of funding to carry out a logical extension of the four-year funded parent award to fill a critical research gap in longer-term sustainability and equity in EBS for HPV vaccination in safety-net settings. Data obtained will also inform a larger pragmatic trial to advance the science in adaptation and fit of EBS in diverse contexts and settings in future research.

NIH Research Projects · FY 2024 · 2020-08

PROJECT SUMMARY Interstitial Cystitis/Bladder Pain Syndrome (IC/BPS) is a common, chronic, and debilitating condition in women. The underlying cause of IC/BPS remains unknown. We recently published the first functional magnetic resonance imaging (fMRI) study comparing brain function in women with IC/BPS to healthy women. We found that women with IC/BPS have altered resting activity in supplementary motor area (SMA). Specifically, these changes appear in a part of SMA that we have shown to control pelvic floor muscle activity (“pelvic-SMA”). Our results provide the first explanation for extensive published reports of increased pelvic floor muscle activity in women with IC/BPS. We hypothesize that we are observing evidence of an important theory of chronic pain: motor cortical changes occur that are initially beneficial to increase protective muscle activity but are ultimately maladaptive and perpetuate pain. Our goal is to reduce pain by improving brain activity and pelvic muscle activity (making them more similar to healthy individuals). Using non-invasive repetitive transcranial magnetic stimulation (rTMS) directed at pelvic-SMA, we aim to determine if we can reduce pain (Aim 1), improve resting brain activity (fMRI) and resting pelvic floor muscle electromyographic (EMG) activity in IC/BPS (Aim 2), and to link the pain reductions to fMRI/EMG improvements to develop a causal mediation model of IC/BPS symptoms (Aim 3). We will recruit 75 women with IC/BPS to participate in the study, and participants will be randomized to 3 groups of 25 to test different rTMS paradigms: high-frequency (to increase excitability), low-frequency (to decrease excitability), and sham (as a control). Our preliminary data suggest that high-frequency stimulation is the best protocol since it improves resting pelvic-SMA activity while reducing pain and pelvic muscle activity. These results are convergent with an independently-published preliminary study that suggests that 5 consecutive days of high-frequency stimulation can reduce IC/BPS pain relative to sham, even measured 3 weeks after the cessation of stimulation. We will extend these preliminary findings in the proposed work: in the high-frequency and sham rTMS groups, we will study 5 consecutive days of stimulation with both shorter-term outcome measures (associated with the first day of stimulation) and longer-term outcome measures (3 weeks after the cessation of stimulation). In the low-frequency rTMS group, we will only examine shorter-term outcome measures associated with a single session, since our preliminary data suggest that low-frequency stimulation is active but perturbs pelvic-SMA and resting pelvic floor muscle activity away from values associated with healthy controls and does not reduce pain. Our preliminary results agree with a large body of literature suggesting that high-frequency rTMS applied to motor cortex is the best rTMS paradigm to reduce pain. However, our proposed work has the potential to greatly innovate the field of brain stimulation for pain by using sham and active comparison groups, as well as objective fMRI/EMG outcome measures, to define the mechanism by which high-frequency stimulation can improve deficiencies in motor function in chronic pain.