Neurology Commons^™

Tead-Independent Mechanisms Of Yap Function In Cardiomyocyte Cell Cycle Reentry, Bing Xie, Jeffrey Steimle, Vaibhav Deshmukh, Lin Liu, Chang-Ru Tsai, Todd R Heallen, Wyatt Paltzer, Yuka Morikawa, Fansen Meng, Jun Wang, James F Martin

Faculty, Staff and Students Publications

Adult mammalian hearts exhibit limited regenerative capacity because of the restricted renewal of cardiomyocytes. Recent studies reveal that mammalian hearts exhibit transient regenerative potential within a short time frame after birth, suggesting a regulatory mechanism that prevents adult hearts from initiating a regenerative response to cardiac injury. Here, we discovered that an active form of YAP, named YAP6SA, which is not inhibited by the Hippo signaling pathway and does not interact with TEADs, induces cardiomyocyte cell cycle reentry. In addition, YAP6SA interacts with scaffold protein MPDZ to regulate Rho GTPases and promote cell cycle progression in cardiomyocytes (CMs). Importantly, YAP6SA …

Risk Of Major Depression In Partners Of People With Alzheimer's Disease: A National Cohort Study, Casey Crump, Jingkai Wei, Barbara G Vickrey, Alexis C Edwards, Paul E Schulz, Weiva Sieh, Jan Sundquist, Kristina Sundquist

Faculty, Staff and Student Publications

Background: Alzheimer's disease (AD) may cause significant psychosocial distress not only in the patient but also their partner. However, long-term risks of major depression in partners of AD patients are largely unknown.

Methods: A national cohort study was conducted of all 145 289 partners of people diagnosed with all-cause dementia, including 57 113 partners of people diagnosed with AD, in Sweden during 1998-2017, and 1 300 561 population-based controls. Cox regression was used to compute hazard ratios (HRs) for subsequent risk of major depression identified from nationwide outpatient and inpatient diagnoses through 2018, adjusting for sociodemographic factors and prior mental …

The Landscape Of Malignant Transition: Unraveling Cancer Cell-Of-Origin And Heterogeneous Tissue Microenvironment, Ruihan Luo, Jiajia Liu, Tiangang Wang, Weiling Zhao, Yanfei Wang, Jianguo Wen, Hongyu Wang, Shanli Ding, Xiaobo Zhou

Faculty, Staff and Student Publications

Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced …

Age-Associated Proteins Explain The Role Of Medial Temporal Lobe Networks In Alzheimer’S Disease, Adam Turnbull, Yejin Kim, Kai Zhang, Xiaoqian Jiang, Zihuai He, Victor W Henderson, F Vankee Lin

Faculty, Staff and Student Publications

The structural connectivity (SC) of the medial temporal lobe and its associated cortical anterior temporal and posterior medial networks (MTL-AT-PM) is linked to pathologies and memory decline in Alzheimer's disease (AD). However, neuroimaging analyses cannot tell us how SC changes occur in AD at the molecular level and do not provide a means of intervening to slow/prevent pathology-related changes in MTL-AT-PM SC. The current study aimed to understand how and where AD-related changes occur within MTL-AT-PM using proteomics. We used a 4-step approach in 101 older adults from a local sample, aiming to understand how proteins and SC in combination …

Staged Screening Identifies People With Biomarkers Related To Neuronal Alpha-Synuclein Disease, Ethan G Brown, Lana M Chahine, Andrew Siderowf, Caroline Gochanour, Ryan Kurth, Micah J Marshall, Chelsea Caspell-Garcia, Michael C Brumm, Craig E Stanley, Monica Korell, Bridget Mcmahon, Maggie Kuhl, Kimberly Fabrizio, Laura Heathers, Luis Concha-Marambio, Claudio Soto, Sohini Chowdhury, Christopher S Coffey, Tatiana M Foroud, Tanya Simuni, Kenneth Marek, Caroline M Tanner

Faculty, Staff and Student Publications

Objective: Remote identification of individuals with severe hyposmia may enable scalable recruitment of participants with underlying alpha-synuclein aggregation. We evaluated the performance of a staged screening paradigm using remote smell testing to enrich for abnormal dopamine transporter single-photon emission computed tomography imaging (DAT-SPECT) and alpha-synuclein aggregation.

Methods: The Parkinson's Progression Markers Initiative (PPMI) recruited participants for the prodromal cohort who were 60-years and older without a Parkinson's disease diagnosis. Participants were invited to complete a University of Pennsylvania Smell Identification Test (UPSIT) independently through an online portal. Hyposmic participants were invited to complete DAT-SPECT, which determined eligibility for enrollment in …

Protocol For Unlocking Alternative Polyadenylation Insights From Bulk Rna-Seq Data With Polyaminer-Bulk, Venkata Jonnakuti, Sriya Jonnakuti, Hari Krishna Yalamanchili

Duncan NRI Faculty and Staff Publications

PolyAMiner-Bulk, a deep-learning-based algorithm to decode alternative polyadenylation (APA) dynamics from bulk RNA sequencing (RNA-seq) data, enables scientists to identify and quantify APA events from processed bulk RNA-seq data. The protocol allows researchers to explore differential APA usage between two conditions and gain a better understanding of post-transcriptional regulatory mechanisms. The major steps involve input data preparation, executing PolyAMiner-Bulk, and interpreting the results. A basic familiarity with pre-processing bulk RNA-seq data and command-line tools is suggested.

For complete details on the use and execution of this protocol, please refer to Jonnakuti et al.¹

Diverse Ancestral Representation Improves Genetic Intolerance Metrics, Alexander L Han, Chloe F Sands, Dorota Matelska, Jessica C Butts, Vida Ravanmehr, Fengyuan Hu, Esmeralda Villavicencio Gonzalez, Nicholas Katsanis, Carlos D Bustamante, Quanli Wang, Slavé Petrovski, Dimitrios Vitsios, Ryan S Dhindsa

Duncan NRI Faculty and Staff Publications

The unprecedented scale of genomic databases has revolutionized our ability to identify regions in the human genome intolerant to variation—regions often implicated in disease. However, these datasets remain constrained by limited ancestral diversity. Here, we analyze whole-exome sequencing data from 460,551 UK Biobank and 125,748 Genome Aggregation Database (gnomAD) participants across multiple ancestries to test several key intolerance metrics, including the Residual Variance Intolerance Score (RVIS), Missense Tolerance Ratio (MTR), and Loss-of-Function Observed/Expected ratio (LOF O/E). We demonstrate that increasing ancestral representation, rather than sample size alone, critically drives their performance. Scores trained on variation observed in African and Admixed …

Longitudinal Multi-Omics In Alpha-Synuclein Drosophila Model Discriminates Disease- From Age-Associated Pathologies In Parkinson’S Disease, Justin Moore, Timothy Wu, Justin Dhindsa, Omar El Fadel, Anh Le, Alma Perez, Bismark Amoh, Akash Tarkunde, Katy F Zhu, Matthew Avalos, Eric B Dammer, Duc M Duong, Nicholas T Seyfried, Joshua M Shulman, Ismael Al-Ramahi, Juan Botas

Duncan NRI Faculty and Staff Publications

Parkinson's disease (PD) starts decades before symptoms appear, usually in the later decades of life, when age-related changes are occurring. To identify molecular changes early in the disease course and distinguish PD pathologies from aging, we generated Drosophila expressing alpha-synuclein (αSyn) in neurons and performed longitudinal bulk transcriptomics and proteomics on brains at six time points across the lifespan and compared the data to healthy control flies as well as human post-mortem brain datasets. We found that translational and energy metabolism pathways were downregulated in αSyn flies at the earliest timepoints; comparison with the aged control flies suggests that elevated …

Understanding Pediatric Bipolar Disorder Through The Investigation Of Clinical, Neuroanatomic, Neurophysiological And Neurocognitive Dimensions: A Pilot Study, Alessio Simonetti, Evelina Bernardi, Sherin Kurian, Antonio Restaino, Claudia Calderoni, Emanuela De Chiara, Francesca Bardi, Gabriele Sani, Jair C Soares, Kirti Saxena

Faculty, Staff and Student Publications

Background: Pathophysiological models of pediatric bipolar disorder (PBD) are lacking. Multimodal approaches may provide a comprehensive description of the complex relationship between the brain and behavior. Aim: To assess behavioral, neuropsychological, neurophysiological, and neuroanatomical alterations in youth with PBD.

Methods: Subjects with PBD (n = 23) and healthy controls (HCs, n = 23) underwent (a) clinical assessments encompassing the severity of psychiatric symptoms, (b) neuropsychological evaluation, (c) analyses of event-related potentials (related to the passive viewing of fearful, neutral, and happy faces during electroencephalography recording, and (d) cortical thickness and deep gray matter volume measurement using magnetic …

Optimizing Electrode Configurations For Eeg Mild Cognitive Impairment Detection, Yi Jiang, Xin Zhang, Zhiwei Guo, Xiaobo Zhou, Jiayuan He, Ning Jiang

Faculty, Staff and Student Publications

The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the optimization of electrode configuration for MCI detection. We used a 32-channel EEG device to record the data of 21 MCI patients and 20 cognitively normal elderly (NC) undergoing working memory (WM) tasks. Based on the differential value (MCI group vs. NC group) from the Power Spectral Density (PSD) value of each electrode in θ and α frequency band during WM …

Optimizing Decision-Making In A Cerebral Palsy Model Using Reinforcement Learning, Richard Ampah

Pitzer Senior Theses

This study presents an original interdisciplinary investigation into how reinforcement learning (RL) can model motor and cognitive defects and potentially improve motor and cognitive functions in individuals with cerebral palsy (CP), a non-progressive neurological disorder that impairs movement and adaptability. Integrating computational neuroscience and machine learning, the research applies policy gradient methods and Markov Decision Processes (MDPs) to simulate adaptive learning in agents with and without CP-related constraints.

The central aim is to compare the cumulative rewards of optimal policies, derived from value iteration, and human-like learning policies using the REINFORCE algorithm, both with and without the Bellman baseline. The …

Leveraging Snomed Ct For Patient Cohort Identification Over Heterogeneous Ehr Data, Xubing Hao, Yan Huang, Licong Cui, Xiaojin Li

Faculty, Staff and Student Publications

SNOMED CT is extensively employed to standardize data across diverse patient datasets and support cohort identification, with studies revealing its benefits and challenges. In this work, we developed a SNOMED CT-driven cohort query system over a heterogeneous Optum® de-identified COVID-19 Electronic Health Record dataset leveraging concept mappings between ICD-9-CM/ICD-10-CM and SNOMED CT. We evaluated the benefits and challenges of using SNOMED CT to perform cohort queries based on both query code sets and actual patients retrieved from the database, leveraging the original ICD-9-CM and ICD-10-CM as baselines. Manual review of 80 random cases revealed 65 cases containing 148 true positive …

Neurofilament Light Chain In Serum Of Cancer Patients With Acute Neurological Complications, Amulya Gottiparthy, Keng Lam, Suprateek Kundu, Zixi Yang, Ivo Tremont-Lukats, Sudhakar Tummala

Faculty, Staff and Student Publications

Aim: Neurofilament light chain (NfL) is a nonspecific sensitive biomarker of axonal damage.

Methods: This case series identified cancer patients with neurological complications who had serum NfL measurements and paired these results to outcomes.

Results: NfL serum levels were available in 15 patients with hematological malignancies or solid tumors. The neurological complications studied were immune effector cell-associated neurotoxicity syndrome, immune checkpoint inhibitor-related encephalopathy, anoxic brain injury, Guillain-Barre syndrome, hemophagocytic lymphohistiocytosis, transverse myelitis, paraneoplastic syndrome, central nervous system demyelinating disorder and chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids. All patients but one with serum NfL >900 pg/ml died …

Mortality Risks Associated With Depression In Men With Prostate Cancer, Casey Crump, Pär Stattin, James D Brooks, Jan Sundquist, Weiva Sieh, Kristina Sundquist

Faculty, Staff and Student Publications

Background: Men diagnosed with prostate cancer (PC) have an increased risk of depression; however, it is unclear to what extent depression affects long-term survival. A better understanding of such effects is needed to improve long-term care and outcomes for men with PC.

Objective: To determine the associations between major depression and mortality in a national cohort of men with PC.

Design, setting, and participants: A national cohort study was conducted of all 180 189 men diagnosed with PC in Sweden during 1998-2017. Subsequent diagnoses of major depression were ascertained from nationwide outpatient and inpatient records through 2018.

Outcome measurements and …

Neurocognitive Functioning Of Patients With Sinonasal And Nasopharyngeal Cancers Treated With Multimodality Therapy, Dan Yaniv, Lindsay M Niccolai, Jeffrey S Wefel, Catherine M Sullaway, Jack Phan, Clifton David Fuller, Kareem B Haroun, Ehab Y Hanna, Shirley Y Su

Faculty, Staff and Student Publications

Importance Few recent studies have examined neurocognitive functioning (NCF) in patients with sinonasal and nasopharyngeal cancers (NPCs) prior to and following multimodality therapy or the potential differences in NCF by disease variables such as disease site.

Objective The objective of this study is to determine rates of NCF impairments prior to and following multimodality therapy, declines in NCF following radiotherapy (RT), and possible differences in NCF by the disease site.

Design, Setting, and Participants We conducted a retrospective chart review of 39 patients with sinonasal and NPCs who underwent comprehensive neuropsychological evaluations. Twenty patients were evaluated prior to RT, of …

Durable Local Control With Hypofractionated Radiation Therapy For Unresectable Or Metastatic Melanoma, Sydney A Keatts, Aya F Salem, David M Swanson, Ahsan S Farooqi, Andrew J Bishop, Rodabe N Amaria, Jennifer L Mcquade, Isabella C Glitza Oliva, Adi Diab, Roi Weiser, Sarah B Fisher, Ryan P Goepfert, Merrick I Ross, B Ashleigh Guadagnolo, Devarati Mitra

Faculty, Staff and Student Publications

BACKGROUND AND PURPOSE: As patients with advanced melanoma live longer in the context of systemic therapy advancements, better strategies for durable control of bulky tumors are needed. In this study, we evaluated if dose-escalated hypofractionated radiation therapy (HFRT) can provide durable local control and improve tumor-associated symptoms in patients with unresectable or bulky metastatic melanoma for whom stereotactic ablative radiotherapy (RT) approaches are not feasible due to tumor size or location.

MATERIALS AND METHODS: We retrospectively reviewed 49 patients with unresectable or bulky metastatic melanoma who were treated to a total of 53 tumor targets with 12-17 fractions HFRT at …

Characterizing The Progression From Mild Cognitive Impairment To Dementia: A Network Analysis Of Longitudinal Clinical Visits, Muskan Garg, Sara Hejazi, Sunyang Fu, Maria Vassilaki, Ronald C Petersen, Jennifer St Sauver, Sunghwan Sohn

Faculty, Staff and Student Publications

Background: With the recent surge in the utilization of electronic health records for cognitive decline, the research community has turned its attention to conducting fine-grained analyses of dementia onset using advanced techniques. Previous works have mostly focused on machine learning-based prediction of dementia, lacking the analysis of dementia progression and its associations with risk factors over time. The black box nature of machine learning models has also raised concerns regarding their uncertainty and safety in decision making, particularly in sensitive domains like healthcare.

Objective: We aimed to characterize the progression of health conditions, such as chronic diseases and neuropsychiatric symptoms, …

Clinical Outcome-Guided Deep Temporal Clustering For Disease Progression Subtyping, Dulin Wang, Xiaotian Ma, Paul E Schulz, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Objective: Complex diseases exhibit heterogeneous progression patterns, necessitating effective capture and clustering of longitudinal changes to identify disease subtypes for personalized treatments. However, existing studies often fail to design clustering-specific representations or neglect clinical outcomes, thereby limiting the interpretability and clinical utility.

Method: We design a unified framework for subtyping longitudinal progressive diseases. We focus on effectively integrating all data from disease progressions and improving patient representation for downstream clustering. Specifically, we propose a clinical Outcome-Guided Deep Temporal Clustering (OG-DTC) that generates representations informed by clustering and clinical outcomes. A GRU-based seq2seq architecture captures the temporal dynamics, and the model …

Targeting Igf2 To Reprogram The Tumor Microenvironment For Enhanced Viro-Immunotherapy, Min Hye Noh, Jin Muk Kang, Alexandra A Miller, Grace Nguyen, Minxin Huang, Ji Seon Shim, Alberto J Bueso-Perez, Sara A Murphy, Kimberly A Rivera-Caraballo, Yoshihiro Otani, Eunju Kim, Seung-Hee Yoo, Yuanqing Yan, Yeshavanth Banasavadi-Siddegowda, Hiroshi Nakashima, E Antonio Chiocca, Balveen Kaur, Zhongming Zhao, Tae Jin Lee, Ji Young Yoo

Faculty, Staff and Student Publications

BACKGROUND: The FDA approval of oncolytic herpes simplex-1 virus (oHSV) therapy underscores its therapeutic promise and safety as a cancer immunotherapy. Despite this promise, the current efficacy of oHSV is significantly limited to a small subset of patients largely due to the resistance in tumor and tumor microenvironment (TME).

METHODS: RNA sequencing (RNA-Seq) was used to identify molecular targets of oHSV resistance. Intracranial human and murine glioma or breast cancer brain metastasis (BCBM) tumor-bearing mouse models were employed to elucidate the mechanism underlying oHSV therapy-induced resistance.

RESULTS: Transcriptome analysis identified IGF2 as one of the top-secreted proteins following oHSV treatment. …

The Oncolytic Adenovirus Delta-24-Rgd In Combination With Onc201 Induces A Potent Antitumor Response In Pediatric High-Grade And Diffuse Midline Glioma Models, Daniel De La Nava, Iker Ausejo-Mauleon, Virginia Laspidea, Marisol Gonzalez-Huarriz, Andrea Lacalle, Noelia Casares, Marta Zalacain, Lucía Marrodan, Marc García-Moure, Maria C Ochoa, Antonio Carlos Tallon-Cobos, Reyes Hernandez-Osuna, Javier Marco-Sanz, Laasya Dhandapani, Irati Hervás-Corpión, Oren J Becher, Javad Nazarian, Sabine Mueller, Timothy N Phoenix, Jasper Van Der Lugt, Mikel Hernaez, Elizabeth Guruceaga, Carl Koschmann, Sriram Venneti, Joshua E Allen, Matthew D Dun, Juan Fueyo, Candelaria Gomez-Manzano, Jaime Gallego Perez-Larraya, Ana Patiño-García, Sara Labiano, Marta M Alonso

Faculty, Staff and Student Publications

BACKGROUND: Pediatric high-grade gliomas (pHGGs), including diffuse midline gliomas (DMGs), are aggressive pediatric tumors with one of the poorest prognoses. Delta-24-RGD and ONC201 have shown promising efficacy as single agents for these tumors. However, the combination of both agents has not been evaluated.

METHODS: The production of functional viruses was assessed by immunoblotting and replication assays. The antitumor effect was evaluated in a panel of human and murine pHGG and DMG cell lines. RNAseq, the seahorse stress test, mitochondrial DNA content, and γH2A.X immunofluorescence were used to perform mechanistic studies. Mouse models of both diseases were used to assess the …

Antitumor Activity Of A Pyrrolobenzodiazepine Antibody-Drug Conjugate Targeting Lgr5 In Preclinical Models Of Neuroblastoma, Jianghua Tu, Yukimatsu Toh, Adela M Aldana, Jake J Wen, Ling Wu, Joan Jacob, Li Li, Sheng Pan, Kendra S Carmon, Qingyun J Liu

Faculty, Staff and Student Publications

Neuroblastoma (NB) is a cancer of the peripheral nervous system found in children under 15 years of age. It is the most frequently diagnosed cancer during infancy, accounting for ~12% of all cancer-related deaths in children. Leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5) is a membrane receptor that is associated with the primary tumor formation and metastasis of cancers in the gastrointestinal system. Remarkably, high levels of LGR5 are found in NB tumor cells, and high LGR5 expression is strongly correlated with poor survival. Antibody-drug conjugates (ADCs) are monoclonal antibodies that are covalently linked to cell-killing cytotoxins to deliver the payloads …

Reliable Detection Of Generalized Convulsive Seizures Using An Off-The-Shelf Digital Watch: A Multisite Phase 2 Study, Yash Shashank Vakilna, Xiaojin Li, Jaison S Hampson, Yan Huang, John C Mosher, Yuri Dabaghian, Xi Luo, Blanca Talavera, Sandipan Pati, Masel Todd, Ryan Hays, Charles Akos Szabo, Guo-Qiang Zhang, Samden D Lhatoo

Faculty, Staff and Student Publications

Objective: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy.

Methods: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors. Sixty-eight time and frequency domain features were extracted from the sensor data and were used to train a random forest algorithm. A testing framework was developed that would better reflect the EMU setting, consisting of …

Cholesterol-Dependent Lxr Transcription Factor Activity Represses Pronociceptive Effects Of Estrogen In Sensory Neurons And Pain Induced By Myelin Basic Protein Fragments, Swathi K Hullugundi, Jennifer Dolkas, Andrei V Chernov, Tony L Yaksh, Kelly A Eddinger, Mila Angert, Glaucilene Ferreira Catroli, Alex Y Strongin, Patrick M Dougherty, Yan Li, Oswal Quehenberger, Aaron Armando, Veronica I Shubayev

Faculty, Staff and Student Publications

BACKGROUND: A bioactive myelin basic protein (MBP) fragment, comprising MBP

METHODS: In male and female normal and post-CCI rat sciatic nerves, we assessed: (i) cholesterol precursor and metabolite levels by lipidomics; (ii) MBP

RESULTS: CCI regulated LXRα ligand and receptor levels in nerves of both sexes, with cholesterol precursors, desmosterol and 7-DHC, and oxysterol elevated in females relative to males. MBP

CONCLUSION: The injury-released bioactive MBP fragments induce pronociceptive changes by selective inactivation of nuclear transcription factors, including LXRα. By Ncoa1 sequestration, bioactive MBP fragments render LXRα function to counteract pronociceptive activity of estrogen/ESR1 in sensory neurons. This effect of …

Improved Liver Disease Prediction From Clinical Data Through An Evaluation Of Ensemble Learning Approaches, Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao

Faculty, Staff and Student Publications

PURPOSE: Liver disease causes two million deaths annually, accounting for 4% of all deaths globally. Prediction or early detection of the disease via machine learning algorithms on large clinical data have become promising and potentially powerful, but such methods often have some limitations due to the complexity of the data. In this regard, ensemble learning has shown promising results. There is an urgent need to evaluate different algorithms and then suggest a robust ensemble algorithm in liver disease prediction.

METHOD: Three ensemble approaches with nine algorithms are evaluated on a large dataset of liver patients comprising 30,691 samples with 11 …

Increased Incidence Of Vestibular Disorders In Patients With Sars-Cov-2, Lawrance Lee, Evan French, Daniel H Coelho, Nauman F Manzoor, Adam B Wilcox, Adam M Lee, Alexis Graves, Alfred Anzalone, Amin Manna, Amit Saha, Amy Olex, Andrea Zhou, Andrew E Williams, Andrew Southerland, Andrew T Girvin, Anita Walden, Anjali A Sharathkumar, Benjamin Amor, Benjamin Bates, Brian Hendricks, Brijesh Patel, Caleb Alexander, Carolyn Bramante, Cavin Ward-Caviness, Charisse Madlock-Brown, Christine Suver, Christopher Chute, Christopher Dillon, Chunlei Wu, Clare Schmitt, Cliff Takemoto, Dan Housman, Davera Gabriel, David A Eichmann, Diego Mazzotti, Don Brown, Eilis Boudreau, Elaine Hill, Elizabeth Zampino, Emily Carlson Marti, Emily R Pfaff, Evan French, Farrukh M Koraishy, Federico Mariona, Fred Prior, George Sokos, Greg Martin, Harold Lehmann, Heidi Spratt, Hemalkumar Mehta, Hongfang Liu, Hythem Sidky, J W Awori Hayanga, Jami Pincavitch, Jaylyn Clark, Jeremy Richard Harper, Jessica Islam, Jin Ge, Joel Gagnier, Joel H Saltz, Joel Saltz, Johanna Loomba, John Buse, Jomol Mathew, Joni L Rutter, Julie A Mcmurry, Justin Guinney, Justin Starren, Karen Crowley, Katie Rebecca Bradwell, Kellie M Walters, Ken Wilkins, Kenneth R Gersing, Kenrick Dwain Cato, Kimberly Murray, Kristin Kostka, Lavance Northington, Lee Allan Pyles, Leonie Misquitta, Lesley Cottrell, Lili Portilla, Mariam Deacy, Mark M Bissell, Marshall Clark, Mary Emmett, Mary Morrison Saltz, Matvey B Palchuk, Melissa A Haendel, Meredith Adams, Meredith Temple-O'Connor, Michael G Kurilla, Michele Morris, Nabeel Qureshi, Nasia Safdar, Nicole Garbarini, Noha Sharafeldin, Ofer Sadan, Patricia A Francis, Penny Wung Burgoon, Peter Robinson, Philip R O Payne, Rafael Fuentes, Randeep Jawa, Rebecca Erwin-Cohen, Rena Patel, Richard A Moffitt, Richard L Zhu, Rishi Kamaleswaran, Robert Hurley, Robert T Miller, Saiju Pyarajan, Sam G Michael, Samuel Bozzette, Sandeep Mallipattu, Satyanarayana Vedula, Scott Chapman, Shawn T O'Neil, Soko Setoguchi, Stephanie S Hong, Steve Johnson, Tellen D Bennett, Tiffany Callahan, Umit Topaloglu, Usman Sheikh, Valery Gordon, Vignesh Subbian, Warren A Kibbe, Wenndy Hernandez, Will Beasley, Will Cooper, William Hillegass, Xiaohan Tanner Zhang

Faculty, Staff and Student Publications

OBJECTIVE: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population.

STUDY DESIGN: Retrospective.

SETTING: Clinical data in the National COVID Cohort Collaborative database (N3C).

METHODS: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period.

RESULTS: Patients testing positive for COVID-19 were significantly more likely to have …

Brain Cell-Type Shifts In Alzheimer’S Disease, Autism, And Schizophrenia Interrogated Using Methylomics And Genetics, Chloe X Yap, Daniel D Vo, Matthew G Heffel, Arjun Bhattacharya, Cindy Wen, Yuanhao Yang, Kathryn E Kemper, Jian Zeng, Zhili Zheng, Zhihong Zhu, Eilis Hannon, Dorothea Seiler Vellame, Alice Franklin, Christa Caggiano, Brie Wamsley, Daniel H Geschwind, Noah Zaitlen, Alexander Gusev, Bogdan Pasaniuc, Jonathan Mill, Chongyuan Luo, Michael J Gandal

Faculty, Staff and Student Publications

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial …

Prediction Of Disease-Free Survival For Precision Medicine Using Cooperative Learning On Multi-Omic Data, Georg Hahn, Dmitry Prokopenko, Julian Hecker, Sharon M Lutz, Kristina Mullin, Leinal Sejour, Winston Hide, Ioannis Vlachos, Stacia Desantis, Rudolph E Tanzi, Christoph Lange

Faculty, Staff and Student Publications

In precision medicine, both predicting the disease susceptibility of an individual and forecasting its disease-free survival are areas of key research. Besides the classical epidemiological predictor variables, data from multiple (omic) platforms are increasingly available. To integrate this wealth of information, we propose new methodology to combine both cooperative learning, a recent approach to leverage the predictive power of several datasets, and polygenic hazard score models. Polygenic hazard score models provide a practitioner with a more differentiated view of the predicted disease-free survival than the one given by merely a point estimate, for instance computed with a polygenic risk score. …

Generalizing Parkinson’S Disease Detection Using Keystroke Dynamics: A Self-Supervised Approach, Shikha Tripathi, Alejandro Acien, Ashley A Holmes, Teresa Arroyo-Gallego, Luca Giancardo

Faculty, Staff and Student Publications

Objective: Passive monitoring of touchscreen interactions generates keystroke dynamic signals that can be used to detect and track neurological conditions such as Parkinson's disease (PD) and psychomotor impairment with minimal burden on the user. However, this typically requires datasets with clinically confirmed labels collected in standardized environments, which is challenging, especially for a large subject pool. This study validates the efficacy of a self-supervised learning method in reducing the reliance on labels and evaluates its generalizability.

Materials and methods: We propose a new type of self-supervised loss combining Barlow Twins loss, which attempts to create similar feature representations with reduced …

Montelukast As A Repurposable Additive Drug For Standard-Efficacy Multiple Sclerosis Treatment: Emulating Clinical Trials With Retrospective Administrative Health Claims Data, Astrid M Manuel, Assaf Gottlieb, Leorah Freeman, Zhongming Zhao

Faculty, Staff and Student Publications

BACKGROUND: Effective and safe treatment options for multiple sclerosis (MS) are still needed. Montelukast, a leukotriene receptor antagonist (LTRA) currently indicated for asthma or allergic rhinitis, may provide an additional therapeutic approach.

OBJECTIVE: The study aimed to evaluate the effects of montelukast on the relapses of people with MS (pwMS).

METHODS: In this retrospective case-control study, two independent longitudinal claims datasets were used to emulate randomized clinical trials (RCTs). We identified pwMS aged 18-65 years, on MS disease-modifying therapies concomitantly, in de-identified claims from Optum's Clinformatics

RESULTS: pwMS treated with montelukast demonstrated a statistically significant 23.6% reduction in relapses compared …

Alterations In Brain Morphometric Networks And Their Relationship With Memory Dysfunction In Patients With Type 2 Diabetes Mellitus, Rye Young Kim, Yoonji Joo, Eunji Ha, Haejin Hong, Chaewon Suh, Youngeun Shim, Hyeonji Lee, Yejin Kim, Jae-Hyoung Cho, Sujung Yoon, In Kyoon Lyoo

Faculty, Staff and Student Publications

Cognitive dysfunction, a significant complication of type 2 diabetes mellitus (T2DM), can potentially manifest even from the early stages of the disease. Despite evidence of global brain atrophy and related cognitive dysfunction in early-stage T2DM patients, specific regions vulnerable to these changes have not yet been identified. The study enrolled patients with T2DM of less than five years’ duration and without chronic complications (T2DM group, n=100) and demographically similar healthy controls (control group, n=50). High-resolution T1-weighted magnetic resonance imaging data were subjected to independent component analysis to identify structurally significant components indicative of morphometric networks. Within these networks, the groups’ …