Digital Commons Network^™

Prediction Of Brain Metastases Development In Patients With Lung Cancer By Explainable Artificial Intelligence From Electronic Health Records, Zhao Li, Rongbin Li, Yujia Zhou, Laila Rasmy, Degui Zhi, Ping Zhu, Antonio Dono, Xiaoqian Jiang, Hua Xu, Yoshua Esquenazi, W Jim Zheng

Faculty, Staff and Student Publications

PURPOSE: Early detection of brain metastases (BMs) is critical for prompt treatment and optimal control of the disease. In this study, we seek to predict the risk of developing BM among patients diagnosed with lung cancer on the basis of electronic health record (EHR) data and to understand what factors are important for the model to predict BM development through explainable artificial intelligence approaches accurately.

MATERIALS AND METHODS: We trained a recurrent neural network model, REverse Time AttentIoN (RETAIN), to predict the risk of developing BM using structured EHR data. To interpret the model's decision process, we analyzed the attention …

Why Is Biomedical Informatics Hard? A Fundamental Framework, Todd R Johnson, Elmer V Bernstam

Faculty, Staff and Student Publications

Building on previous work to define the scientific discipline of biomedical informatics, we present a framework that categorizes fundamental challenges into groups based on data, information, and knowledge, along with the transitions between these levels. We define each level and argue that the framework provides a basis for separating informatics problems from non-informatics problems, identifying fundamental challenges in biomedical informatics, and provides guidance regarding the search for general, reusable solutions to informatics problems. We distinguish between processing data (symbols) and processing meaning. Computational systems, that are the basis for modern information technology (IT), process data. In contrast, many important challenges …

De Novo Mutations Disturb Early Brain Development More Frequently Than Common Variants In Schizophrenia, Toshiyuki Itai, Peilin Jia, Yulin Dai, Jingchun Chen, Xiangning Chen, Zhongming Zhao

Faculty, Staff and Student Publications

Investigating functional, temporal, and cell-type expression features of mutations is important for understanding a complex disease. Here, we collected and analyzed common variants and de novo mutations (DNMs) in schizophrenia (SCZ). We collected 2,636 missense and loss-of-function (LoF) DNMs in 2,263 genes across 3,477 SCZ patients (SCZ-DNMs). We curated three gene lists: (a) SCZ-neuroGenes (159 genes), which are intolerant to LoF and missense DNMs and are neurologically important, (b) SCZ-moduleGenes (52 genes), which were derived from network analyses of SCZ-DNMs, and (c) SCZ-commonGenes (120 genes) from a recent GWAS as reference. To compare temporal gene expression, we used the BrainSpan …

Genomic Analysis Of Two Phlebotomine Sand Fly Vectors Of Leishmania From The New And Old World, Frédéric Labbé, Maha Abdeladhim, Jenica Abrudan, Alejandra Saori Araki, Ricardo N Araujo, Peter Arensburger, Joshua B Benoit, Reginaldo Pecanha Brazil, Rafaela V Bruno, Gustavo Bueno Da Silva Rivas, Vinicius Carvalho De Abreu, Jason Charamis, Iliano V Coutinho-Abreu, Samara G Da Costa-Latgé, Alistair Darby, Viv M Dillon, Scott J Emrich, Daniela Fernandez-Medina, Nelder Figueiredo Gontijo, Catherine M Flanley, Derek Gatherer, Fernando A Genta, Sandra Gesing, Gloria I Giraldo-Calderón, Bruno Gomes, Eric Roberto Guimaraes Rocha Aguiar, James G C Hamilton, Omar Hamarsheh, Mallory Hawksworth, Jacob M Hendershot, Paul V Hickner, Jean-Luc Imler, Panagiotis Ioannidis, Emily C Jennings, Shaden Kamhawi, Charikleia Karageorgiou, Ryan C Kennedy, Andreas Krueger, José M Latorre-Estivalis, Petros Ligoxygakis, Antonio Carlos A Meireles-Filho, Patrick Minx, Jose Carlos Miranda, Michael J Montague, Ronald J Nowling, Fabiano Oliveira, João Ortigão-Farias, Marcio G Pavan, Marcos Horacio Pereira, Andre Nobrega Pitaluga, Roenick Proveti Olmo, Marcelo Ramalho-Ortigao, José M C Ribeiro, Andrew J Rosendale, Mauricio R V Sant'anna, Steven E Scherer, Nágila F C Secundino, Douglas A Shoue, Caroline Da Silva Moraes, João Silveira Moledo Gesto, Nataly Araujo Souza, Zainulabueddin Syed, Samuel Tadros, Rayane Teles-De-Freitas, Erich L Telleria, Chad Tomlinson, Yara M Traub-Csekö, João Trindade Marques, Zhijian Tu, Maria F Unger, Jesus Valenzuela, Flávia V Ferreira, Karla P V De Oliveira, Felipe M Vigoder, John Vontas, Lihui Wang, Gareth D Weedall, Elyes Zhioua, Stephen Richards, Wesley C Warren, Robert M Waterhouse, Rod J Dillon, Mary Ann Mcdowell

Faculty, Staff and Students Publications

Phlebotomine sand flies are of global significance as important vectors of human disease, transmitting bacterial, viral, and protozoan pathogens, including the kinetoplastid parasites of the genus Leishmania, the causative agents of devastating diseases collectively termed leishmaniasis. More than 40 pathogenic Leishmania species are transmitted to humans by approximately 35 sand fly species in 98 countries with hundreds of millions of people at risk around the world. No approved efficacious vaccine exists for leishmaniasis and available therapeutic drugs are either toxic and/or expensive, or the parasites are becoming resistant to the more recently developed drugs. Therefore, sand fly and/or reservoir control …

Letter To The Editor: Quality Criteria For Computational Models Predicting Individual Outcomes In Car-T Cell Therapy, Anna M Mc Laughlin, Cassian Yee

Faculty, Staff and Student Publications

No abstract provided.

Quality Assurance Assessment Of Intra-Acquisition Diffusion-Weighted And T2-Weighted Magnetic Resonance Imaging Registration And Contour Propagation For Head And Neck Cancer Radiotherapy, Mohamed A Naser, Kareem A Wahid, Sara Ahmed, Vivian Salama, Cem Dede, Benjamin W Edwards, Ruitao Lin, Brigid Mcdonald, Travis C Salzillo, Renjie He, Yao Ding, Moamen Abobakr Abdelaal, Daniel Thill, Nicolette O'Connell, Virgil Willcut, John P Christodouleas, Stephen Y Lai, Clifton D Fuller, Abdallah S R Mohamed

Faculty, Staff and Student Publications

BACKGROUND/PURPOSE: Adequate image registration of anatomical and functional magnetic resonance imaging (MRI) scans is necessary for MR-guided head and neck cancer (HNC) adaptive radiotherapy planning. Despite the quantitative capabilities of diffusion-weighted imaging (DWI) MRI for treatment plan adaptation, geometric distortion remains a considerable limitation. Therefore, we systematically investigated various deformable image registration (DIR) methods to co-register DWI and T2-weighted (T2W) images.

MATERIALS/METHODS: We compared three commercial (ADMIRE, Velocity, Raystation) and three open-source (Elastix with default settings [Elastix Default], Elastix with parameter set 23 [Elastix 23], Demons) post-acquisition DIR methods applied to T2W and DWI MRI images acquired during the same …

Evaluating The Causal Effect Of Tobacco Smoking On White Matter Brain Aging: A Two-Sample Mendelian Randomization Analysis In Uk Biobank, Chen Mo, Jingtao Wang, Zhenyao Ye, Hongjie Ke, Song Liu, Kathryn Hatch, Si Gao, Jessica Magidson, Chixiang Chen, Braxton D Mitchell, Peter Kochunov, L Elliot Hong, Tianzhou Ma, Shuo Chen

Faculty, Staff and Student Publications

BACKGROUND AND AIMS: Tobacco smoking is a risk factor for impaired brain function, but its causal effect on white matter brain aging remains unclear. This study aimed to measure the causal effect of tobacco smoking on white matter brain aging.

DESIGN: Mendelian randomization (MR) analysis using two non-overlapping data sets (with and without neuroimaging data) from UK Biobank (UKB). The group exposed to smoking and control group consisted of current smokers and never smokers, respectively. Our main method was generalized weighted linear regression with other methods also included as sensitivity analysis.

SETTING: United Kingdom.

PARTICIPANTS: The study cohort included 23 …

Inconsistent Partitioning And Unproductive Feature Associations Yield Idealized Radiomic Models, Mishka Gidwani, Ken Chang, Jay Biren Patel, Katharina Viktoria Hoebel, Syed Rakin Ahmed, Praveer Singh, Clifton David Fuller, Jayashree Kalpathy-Cramer

Faculty, Staff and Student Publications

Background Radiomics is the extraction of predefined mathematic features from medical images for the prediction of variables of clinical interest. While some studies report superlative accuracy of radiomic machine learning (ML) models, the published methodology is often incomplete, and the results are rarely validated in external testing data sets. Purpose To characterize the type, prevalence, and statistical impact of methodologic errors present in radiomic ML studies. Materials and Methods Radiomic ML publications were reviewed for the presence of performance-inflating methodologic flaws. Common flaws were subsequently reproduced with randomly generated features interpolated from publicly available radiomic data sets to demonstrate the …

Machine Learning And Health Care: Potential Benefits And Issues, J Graham Atkinson, Elizabeth G Atkinson

Faculty, Staff and Students Publications

We discuss the potential for machine learning (ML) and artificial intelligence (AI) to improve health care, while detailing caveats and important considerations to ensure unbiased and equitable implementation. If disparities exist in the data used to train ML algorithms, they must be recognized and accounted for, so they do not bias performance accuracy or are not interpreted by the algorithm as simply a lack of need. We pay particular attention to an area in which bias in data composition is particularly striking, that is in large-scale genetics databases, as people of European descent are vastly overrepresented in the existing resources.

Air Pollution And Acute Kidney Injury In The U.S. Medicare Population: A Longitudinal Cohort Study, Whanhee Lee, Ziyad Al-Aly, Et Al.

2020-Current year OA Pubs

BACKGROUND: Recent studies have reported the association between air pollution exposure and reduced kidney function. However, it is unclear whether air pollution is associated with an increased risk of acute kidney injury (AKI).

OBJECTIVES: To address this gap in knowledge, we investigated the effect estimates of long-term exposures to fine particulate matter [PM

METHODS: This nationwide population-based longitudinal cohort study included 61,300,754 beneficiaries enrolled in Medicare Part A fee-for-service (FFS) who were

RESULTS: Exposure to

DISCUSSION: This study found an association between exposures to air pollution and the risk of the first hospital admission with AKI, and this association persisted …

Genetic Correlations Between Alzheimer’S Disease And Gut Microbiome Genera, Davis Cammann, Yimei Lu, Melika J Cummings, Mark L Zhang, Joan Manuel Cue, Jenifer Do, Jeffrey Ebersole, Xiangning Chen, Edwin C Oh, Jeffrey L Cummings, Jingchun Chen

Faculty, Staff and Student Publications

A growing body of evidence suggests that dysbiosis of the human gut microbiota is associated with neurodegenerative diseases like Alzheimer's disease (AD) via neuroinflammatory processes across the microbiota-gut-brain axis. The gut microbiota affects brain health through the secretion of toxins and short-chain fatty acids, which modulates gut permeability and numerous immune functions. Observational studies indicate that AD patients have reduced microbiome diversity, which could contribute to the pathogenesis of the disease. Uncovering the genetic basis of microbial abundance and its effect on AD could suggest lifestyle changes that may reduce an individual's risk for the disease. Using the largest genome-wide …

Dear Pandemic: A Topic Modeling Analysis Of Covid-19 Information Needs Among Readers Of An Online Science Communication Campaign., Aleksandra M Golos, Sharath Chandra Guntuku, Rachael Piltch-Loeb, Lindsey J Leininger, Amanda M Simanek, Aparna Kumar, Sandra S Albrecht, Jennifer Beam Dowd, Malia Jones, Alison M Buttenheim

College of Nursing Faculty Papers & Presentations

BACKGROUND: The COVID-19 pandemic was accompanied by an "infodemic"-an overwhelming excess of accurate, inaccurate, and uncertain information. The social media-based science communication campaign Dear Pandemic was established to address the COVID-19 infodemic, in part by soliciting submissions from readers to an online question box. Our study characterized the information needs of Dear Pandemic's readers by identifying themes and longitudinal trends among question box submissions.

METHODS: We conducted a retrospective analysis of questions submitted from August 24, 2020, to August 24, 2021. We used Latent Dirichlet Allocation topic modeling to identify 25 topics among the submissions, then used thematic analysis to …

Covariate-Specific Evaluation Of Continuous Biomarker, Ziyi Li, Yijian Huang, Dattatraya Patil, Mark Rubin, Martin G Sanda

Faculty, Staff and Student Publications

Diagnostic tests usually need to operate at a high sensitivity or specificity level in practice. Accordingly, specificity at the controlled sensitivity, or vice versa, is a clinically sensible performance metric for evaluating continuous biomarkers. Meanwhile, the performance of a biomarker may vary across sub-populations as defined by covariates, and covariate-specific evaluation can be informative. In this article, we develop a novel modeling and estimation method for covariate-specific specificity at a controlled sensitivity level. Unlike existing methods which typically adopt elaborate models of covariate effects over the entire biomarker distribution, our approach models covariate effects locally at a specific sensitivity level …

The Emergence Of A Virus Variant: Dynamics Of A Competition Model With Cross-Immunity Time-Delay Validated By Wastewater Surveillance Data For Covid-19, Bruce Pell, Samantha Brozak, Tin Phan, Fuqing Wu, Yang Kuang

Faculty, Staff and Student Publications

We consider the dynamics of a virus spreading through a population that produces a mutant strain with the ability to infect individuals that were infected with the established strain. Temporary cross-immunity is included using a time delay, but is found to be a harmless delay. We provide some sufficient conditions that guarantee local and global asymptotic stability of the disease-free equilibrium and the two boundary equilibria when the two strains outcompete one another. It is shown that, due to the immune evasion of the emerging strain, the reproduction number of the emerging strain must be significantly lower than that of …

Large Scale Crowdsourced Radiotherapy Segmentations Across A Variety Of Cancer Anatomic Sites, Kareem A Wahid, Diana Lin, Onur Sahin, Michael Cislo, Benjamin E Nelms, Renjie He, Mohammed A Naser, Simon Duke, Michael V Sherer, John P Christodouleas, Abdallah S R Mohamed, James D Murphy, Clifton D Fuller, Erin F Gillespie

Faculty, Staff and Student Publications

Clinician generated segmentation of tumor and healthy tissue regions of interest (ROIs) on medical images is crucial for radiotherapy. However, interobserver segmentation variability has long been considered a significant detriment to the implementation of high-quality and consistent radiotherapy dose delivery. This has prompted the increasing development of automated segmentation approaches. However, extant segmentation datasets typically only provide segmentations generated by a limited number of annotators with varying, and often unspecified, levels of expertise. In this data descriptor, numerous clinician annotators manually generated segmentations for ROIs on computed tomography images across a variety of cancer sites (breast, sarcoma, head and neck, …

Catalyzing Next-Generation Artificial Intelligence Through Neuroai, Anthony Zador, Sean Escola, Blake Richards, Bence Ölveczky, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, Dmitri Chklovskii, Anne Churchland, Claudia Clopath, James Dicarlo, Surya Ganguli, Jeff Hawkins, Konrad Körding, Alexei Koulakov, Yann Lecun, Timothy Lillicrap, Adam Marblestone, Bruno Olshausen, Alexandre Pouget, Cristina Savin, Terrence Sejnowski, Eero Simoncelli, Sara Solla, David Sussillo, Andreas S Tolias, Doris Tsao

Faculty, Staff and Students Publications

Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which challenges AI animal models to interact with the sensorimotor world at skill levels akin to their living counterparts. The embodied Turing test shifts the focus from those capabilities like game playing and language that are especially well-developed or uniquely human to those capabilities - inherited from over 500 million years of evolution - that are shared with all animals. Building …

A Thematic Analysis Of Shared Experiences Of Essential Health And Support Personnel In The Covid-19 Pandemic., Linda Carman Copel, Suzanne C. Smeltzer, Christine D. Byrne, Mu-Hsun Chen, Donna S. Havens, Peter Kaufmann, Heather Brom, Jennifer Dean Durning, Linda Maldonado, Patricia K. Bradley, Janell Mensinger, Jennifer Yost

Faculty Articles

AIMS AND OBJECTIVES: Studies have shown that the COVID-19 pandemic has taken a toll on individuals who interact with patients with SARS-CoV-2 but focused largely on clinicians in acute care settings. This qualitative descriptive study aimed to understand the experiences and well-being of essential workers across settings during the pandemic.

BACKGROUND: Multiple studies of the well-being of individuals who have cared for patients during the pandemic have included interviews of clinicians from acute care settings and revealed high levels of stress. However, other essential workers have not been included in most of those studies, yet they may also experience stress. …

Genetic Control Of Rna Editing In Neurodegenerative Disease, Sijia Wu, Qiuping Xue, Mengyuan Yang, Yanfei Wang, Pora Kim, Xiaobo Zhou, Liyu Huang

Faculty, Staff and Student Publications

A-to-I RNA editing diversifies human transcriptome to confer its functional effects on the downstream genes or regulations, potentially involving in neurodegenerative pathogenesis. Its variabilities are attributed to multiple regulators, including the key factor of genetic variants. To comprehensively investigate the potentials of neurodegenerative disease-susceptibility variants from the view of A-to-I RNA editing, we analyzed matched genetic and transcriptomic data of 1596 samples across nine brain tissues and whole blood from two large consortiums, Accelerating Medicines Partnership-Alzheimer's Disease and Parkinson's Progression Markers Initiative. The large-scale and genome-wide identification of 95 198 RNA editing quantitative trait loci revealed the preferred genetic effects …

Allostatic Load In Opioid Use Disorder: A Scoping Review Protocol., Jaimie Qiuyun Fan, Hillary Miller, Amanda Adams, Rebecca Bryan, Matthew Salzman

Cooper Medical School of Rowan University Departmental Research

INTRODUCTION: Opioid use disorder affects 2.1 million individuals in the USA, causing more than 100 000 overdose-related deaths annually. While the neurobiological model of addiction is well described and accepted, there is a lack of morbidity and mortality prognosticators for patients struggling with opioid use disorder. Allostatic load index is a promising candidate for the basis of a prognostication tool. Previous studies show that allostatic load predicts both morbidity and mortality in a variety of cohorts. This scoping review protocol provides the rationale and steps for summarizing and presenting existing evidence surrounding allostatic load in the context of opioid use …

Global Scientific Trends On Healthy Eating From 2002 To 2021: A Bibliometric And Visualized Analysis, Te Fang, Hongyi Cao, Yue Wang, Yang Gong, Zhongqing Wang

Faculty, Staff and Student Publications

Diet has been recognized as a vital risk factor for non-communicable diseases (NCDs), climate changes, and increasing population, which has been reflected by a rapidly growing body of the literature related to healthy eating. To reveal a panorama of the topics related to healthy eating, this study aimed to characterize and visualize the knowledge structure, hotspots, and trends in this field over the past two decades through bibliometric analyses. Publications related to healthy eating between 1 January 2002 and 31 December 2021 were retrieved and extracted from the Web of Science database. The characteristics of articles including publication years, journals, …

A Scoping Review Of Digital Health Interventions For Combating Covid-19 Misinformation And Disinformation, Katarzyna Czerniak, Raji Pillai, Abhi Parmar, Kavita Ramnath, Joseph Krocker, Sahiti Myneni

Faculty, Staff and Student Publications

OBJECTIVE: We provide a scoping review of Digital Health Interventions (DHIs) that mitigate COVID-19 misinformation and disinformation seeding and spread.

MATERIALS AND METHODS: We applied our search protocol to PubMed, PsychINFO, and Web of Science to screen 1666 articles. The 17 articles included in this paper are experimental and interventional studies that developed and tested public consumer-facing DHIs. We examined these DHIs to understand digital features, incorporation of theory, the role of healthcare professionals, end-user experience, and implementation issues.

RESULTS: The majority of studies (n = 11) used social media in DHIs, but there was a lack of platform-agnostic generalizability. …

Sequential Targeting Of Retinoblastoma And Dna Synthesis Pathways Is A Therapeutic Strategy For Sarcomas That Can Be Monitored In Real Time, Tuyen Duong Thanh Nguyen, Yan Wang, Tuyen N Bui, Rossana Lazcano, Davis R Ingram, Min Yi, Varshini Vakulabharanam, Linjie Luo, Marc A Pina, Cansu Karakas, Mi Li, Nicole M Kettner, Neeta Somaiah, Peter J Hougton, Osama Mawlawi, Alexander J Lazar, Kelly K Hunt, Khandan Keyomarsi

Faculty, Staff and Student Publications

Treatment strategies with a strong scientific rationale based on specific biomarkers are needed to improve outcomes in patients with advanced sarcomas. Suppression of cell cycle progression through reactivation of the tumor suppressor retinoblastoma (Rb) using CDK4/6 inhibitors is a potential avenue for novel targeted therapies in sarcomas that harbor intact Rb signaling. Here, we evaluated combination treatment strategies (sequential and concomitant) with the CDK4/6 inhibitor abemacicib to identify optimal combination strategies. Expression of Rb was examined in 1043 sarcoma tumor specimens, and 50% were found to be Rb-positive. Using in vitro and in vivo models, an effective 2-step sequential combination …

Sequential Targeting Of Retinoblastoma And Dna Synthesis Pathways Is A Therapeutic Strategy For Sarcomas That Can Be Monitored In Real Time, Tuyen Duong Thanh Nguyen, Yan Wang, Tuyen N Bui, Rossana Lazcano, Davis R Ingram, Min Yi, Varshini Vakulabharanam, Linjie Luo, Marc A Pina, Cansu Karakas, Mi Li, Nicole M Kettner, Neeta Somaiah, Peter J Hougton, Osama Mawlawi, Alexander J Lazar, Kelly K Hunt, Khandan Keyomarsi

Faculty, Staff and Student Publications

Treatment strategies with a strong scientific rationale based on specific biomarkers are needed to improve outcomes in patients with advanced sarcomas. Suppression of cell-cycle progression through reactivation of the tumor suppressor retinoblastoma (Rb) using CDK4/6 inhibitors is a potential avenue for novel targeted therapies in sarcomas that harbor intact Rb signaling. Here, we evaluated combination treatment strategies (sequential and concomitant) with the CDK4/6 inhibitor abemacicib to identify optimal combination strategies. Expression of Rb was examined in 1,043 sarcoma tumor specimens, and 50% were found to be Rb-positive. Using in vitro and in vivo models, an effective two-step sequential combination strategy …

Noninvasive Electromyometrial Imaging Of Human Uterine Maturation During Term Labor, Hui Wang, Zichao Wen, Wenjie Wu, Zhexian Sun, Zulfia Kisrieva-Ware, Yiqi Lin, Sicheng Wang, Hansong Gao, Haonan Xu, Peinan Zhao, Qing Wang, Alan L Schwartz, Phillip Cuculich, Yong Wang, Et Al.

2020-Current year OA Pubs

Electromyometrial imaging (EMMI) was recently developed to image the three-dimensional (3D) uterine electrical activation during contractions noninvasively and accurately in sheep. Herein we describe the development and application of a human EMMI system to image and evaluate 3D uterine electrical activation patterns at high spatial and temporal resolution during human term labor. We demonstrate the successful integration of the human EMMI system during subjects' clinical visits to generate noninvasively the uterine surface electrical potential maps, electrograms, and activation sequence through an inverse solution using up to 192 electrodes distributed around the abdomen surface. Quantitative indices, including the uterine activation curve, …

Hypomorphic Brca2 And Rad51c Double Mutant Mice Display Fanconi Anemia, Cancer And Polygenic Replication Stress, Karl-Heinz Tomaszowski, Sunetra Roy, Carolina Guerrero, Poojan Shukla, Caezaan Keshvani, Yue Chen, Martina Ott, Xiaogang Wu, Jianhua Zhang, Courtney D Dinardo, Detlev Schindler, Katharina Schlacher

Faculty, Staff and Student Publications

The prototypic cancer-predisposition disease Fanconi Anemia (FA) is identified by biallelic mutations in any one of twenty-three FANC genes. Puzzlingly, inactivation of one Fanc gene alone in mice fails to faithfully model the pleiotropic human disease without additional external stress. Here we find that FA patients frequently display FANC co-mutations. Combining exemplary homozygous hypomorphic Brca2/Fancd1 and Rad51c/Fanco mutations in mice phenocopies human FA with bone marrow failure, rapid death by cancer, cellular cancer-drug hypersensitivity and severe replication instability. These grave phenotypes contrast the unremarkable phenotypes seen in mice with single gene-function inactivation, revealing an unexpected synergism between Fanc mutations. Beyond …

A Gene Regulatory Network Approach Harmonizes Genetic And Epigenetic Signals And Reveals Repurposable Drug Candidates For Multiple Sclerosis, Astrid M Manuel, Yulin Dai, Peilin Jia, Leorah A Freeman, Zhongming Zhao

Faculty, Staff and Student Publications

Multiple sclerosis (MS) is a complex dysimmune disorder of the central nervous system. Genome-wide association studies (GWAS) have identified 233 genetic variations associated with MS at the genome-wide significant level. Epigenetic studies have pinpointed differentially methylated CpG sites in MS patients. However, the interplay between genetic risk factors and epigenetic regulation remains elusive. Here, we employed a network model to integrate GWAS summary statistics of 14 802 MS cases and 26 703 controls with DNA methylation profiles from 140 MS cases and 139 controls and the human interactome. We identified differentially methylated genes by aggregating additive effects of differentially methylated …

Patient And Physician Factors Associated With First Diagnosis Of Non-Affective Psychotic Disorder In Primary Care, Joshua C. Wiener, Rebecca Rodrigues, Jennifer N S Reid, Suzanne Archie, Richard G Booth, Chiachen Cheng, Saadia Hameed Jan, Paul Kurdyak, Arlene G Macdougall, Lena Palaniyappan, Bridget L Ryan, Kelly K. Anderson

Epidemiology and Biostatistics Publications

Primary care physicians play a central role in pathways to care for first-episode psychosis, and their increased involvement in early detection could improve service-related outcomes. The aim of this study was to estimate the proportion of psychosis first diagnosed in primary care, and identify associated patient and physician factors. We used linked health administrative data to construct a retrospective cohort of people aged 14-35 years with a first diagnosis of non-affective psychosis in Ontario, Canada between 2005-2015. We restricted the sample to patients with help-seeking contacts for mental health reasons in primary care in the six months prior to first …

Evaluating The Feasibility And Potential Impacts Of A Recovery-Oriented Psychosocial Rehabilitation Toolkit In A Health Care Setting In Kenya: A Mixed-Methods Study, Regina Casey, Joshua C. Wiener, Terry Krupa, Rosemary Lysaght, Marlene Janzen Le Ber, Ruth Ruhara, Elizabeth Price, Romaisa Pervez, Sean Kidd, Victoria Mutiso, David M Ndetei, Arlene G Macdougall

Epidemiology and Biostatistics Publications

OBJECTIVES: This pilot study evaluated the feasibility and potential impacts of delivering the Psychosocial Rehabilitation (PSR) Toolkit for people with serious mental illness within a health care setting in Kenya.

METHOD: This study used a convergent mixed-methods design. Participants were people with serious mental illness (n = 23), each with an accompanying family member, who were outpatients of a hospital or satellite clinic in semirural Kenya. The intervention consisted of 14 weekly group sessions of PSR cofacilitated by health care professionals and peers with mental illness. Quantitative data were collected from patients and family members using validated outcome measures before …

Identifying A Clinical Informatics Or Electronic Health Record Expert Witness For Medical Professional Liability Cases, Dean F Sittig, Adam Wright

Faculty, Staff and Student Publications

BACKGROUND: The health care field is experiencing widespread electronic health record (EHR) adoption. New medical professional liability (i.e., malpractice) cases will likely involve the review of data extracted from EHRs as well as EHR workflows, audit logs, and even the potential role of the EHR in causing harm.

OBJECTIVES: Reviewing printed versions of a patient's EHRs can be difficult due to differences in printed versus on-screen presentations, redundancies, and the way printouts are often grouped by document or information type rather than chronologically. Simply recreating an accurate timeline often requires experts with training and experience in designing, developing, using, and …

Mining For Equitable Health: Assessing The Impact Of Missing Data In Electronic Health Records, Emily Getzen, Lyle Ungar, Danielle Mowery, Xiaoqian Jiang, Qi Long

Faculty, Staff and Student Publications

Electronic health records (EHR) are collected as a routine part of healthcare delivery, and have great potential to be utilized to improve patient health outcomes. They contain multiple years of health information to be leveraged for risk prediction, disease detection, and treatment evaluation. However, they do not have a consistent, standardized format across institutions, particularly in the United States, and can present significant analytical challenges- they contain multi-scale data from heterogeneous domains and include both structured and unstructured data. Data for individual patients are collected at irregular time intervals and with varying frequencies. In addition to the analytical challenges, EHR …