Life Sciences Commons^™

Transcriptomic-Assisted Immune And Neoantigen Profiling In Premalignancy, Kyle Chang, Florencia Mcallister, Eduardo Vilar

Faculty, Staff and Student Publications

Immune-based cancer therapies such as checkpoint inhibitors (CPI) and vaccines have been increasingly studied across different cancer types. Response to such therapies depends on a number of factors such as mutational burden, neoantigen load, presence of tumor infiltrating lymphocytes, among others. Next-generation sequencing (NGS) technologies are particularly attractive to interrogate the immune response compared to traditional assays such as qRT-PCR and immunohistochemistry (IHC) because they enable the discovery of neoantigens and simultaneous profiling of immune infiltration using gene expression on a large scale. Current approaches in immune profiling utilizes whole-exome sequencing (WES) for human leukocyte allele (HLA) typing and neoantigen …

Cancer Prevention Behaviors In Workers Of A Referral Cancer Center In Mexico City: A Pilot Study On Early Detection Awareness For Cancer, Nancy Reynoso-Noverón, Shine Chang, Luis Alonso Herrera-Montalvo, Abelardo Meneses-García

Faculty, Staff and Student Publications

Background: Prevention strategies for cancer are necessary. Health workers who often serve as role models bear responsibility for prevention counseling and programs. However, whether their habits and behaviors reflect prevention goals are unknown. We describe the prevalence of cancer risk factors and prevention behaviors in health workers of a referral cancer center in Mexico City.

Methods: Cross-sectional study in which workers of the National Cancer Institute were invited to participate in a prevention program, risk factor survey, and nutrition, psychological, and genetic counseling were included. The likelihood of cancer was calculated based on the presence of risk factors. Factors associated …

Emerging Current Trends And Research Focus Related To Pancreatic Cancer Metabolism: A Bibliometric And Visualized Analysis, Qian Shen, Chuanlong Zhang, Xiaochen Jiang, Junchen Li, Fudong Liu, Xiyuan Zhang, Ge'er En, Bo Pang

Faculty, Staff and Student Publications

BACKGROUND: As a malignant digestive system tumor, pancreatic cancer has unique metabolic characteristics. In recent years, the study of pancreatic cancer metabolism is in full swing, which provides a new direction for the treatment of pancreatic cancer patients. However, there is no systematic report of pancreatic cancer metabolism. In this paper, bibliometrics and visualization methods were used to analyze the number of publications, countries/regions, authors, institutions, journals, co-cited references, and keywords of pancreatic cancer metabolism articles, to summarize the research trends and predict research hotspots.

METHODS: We searched, screened and downloaded articles on pancreatic cancer metabolism through the Web of …

Meta-Analyses Identify Dna Methylation Associated With Kidney Function And Damage, Pascal Schlosser, Adrienne Tin, Pamela R Matias-Garcia, Chris H L Thio, Roby Joehanes, Hongbo Liu, Antoine Weihs, Zhi Yu, Anselm Hoppmann, Franziska Grundner-Culemann, Josine L Min, Adebowale A Adeyemo, Charles Agyemang, Johan Ärnlöv, Nasir A Aziz, Andrea Baccarelli, Murielle Bochud, Hermann Brenner, Monique M B Breteler, Cristian Carmeli, Layal Chaker, John C Chambers, Shelley A Cole, Josef Coresh, Tanguy Corre, Adolfo Correa, Simon R Cox, Niek De Klein, Graciela E Delgado, Arce Domingo-Relloso, Kai-Uwe Eckardt, Arif B Ekici, Karlhans Endlich, Kathryn L Evans, James S Floyd, Myriam Fornage, Lude Franke, Eliza Fraszczyk, Xu Gao, Xīn Gào, Mohsen Ghanbari, Sahar Ghasemi, Christian Gieger, Philip Greenland, Megan L Grove, Sarah E Harris, Gibran Hemani, Peter Henneman, Christian Herder, Steve Horvath, Lifang Hou, Mikko A Hurme, Shih-Jen Hwang, Marjo-Riitta Jarvelin, Sharon L R Kardia, Silva Kasela, Marcus E Kleber, Wolfgang Koenig, Jaspal S Kooner, Holly Kramer, Florian Kronenberg, Brigitte Kühnel, Terho Lehtimäki, Lars Lind, Dan Liu, Yongmei Liu, Donald M Lloyd-Jones, Kurt Lohman, Stefan Lorkowski, Ake T Lu, Riccardo E Marioni, Winfried März, Daniel L Mccartney, Karlijn A C Meeks, Lili Milani, Pashupati P Mishra, Matthias Nauck, Ana Navas-Acien, Christoph Nowak, Annette Peters, Holger Prokisch, Bruce M Psaty, Olli T Raitakari, Scott M Ratliff, Alex P Reiner, Sylvia E Rosas, Ben Schöttker, Joel Schwartz, Sanaz Sedaghat, Jennifer A Smith, Nona Sotoodehnia, Hannah R Stocker, Silvia Stringhini, Johan Sundström, Brenton R Swenson, Maria Tellez-Plaza, Joyce B J Van Meurs, Jana V Van Vliet-Ostaptchouk, Andrea Venema, Niek Verweij, Rosie M Walker, Matthias Wielscher, Juliane Winkelmann, Bruce H R Wolffenbuttel, Wei Zhao, Yinan Zheng, Marie Loh, Harold Snieder, Daniel Levy, Melanie Waldenberger, Katalin Susztak, Anna Köttgen, Alexander Teumer

Faculty, Staff and Student Publications

Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. to extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. …

Modeling Recurrence In Idiopathic Subglottic Stenosis With Mobile Peak Expiratory Flow, Kyle Kimura, Liping Du, Lynn D Berry, Li-Ching Huang, Sheau-Chiann Chen, David O Francis, Alexander Gelbard

Faculty, Staff and Student Publications

OBJECTIVES/HYPOTHESIS: We sought to establish normative peak expiratory flow (PEF) data for patients with idiopathic subglottic stenosis (iSGS), evaluate whether immediate changes in PEF after a procedure predict long-term treatment response, and test if a decline in longitudinal PEF is associated with disease recurrence.

STUDY DESIGN: International, prospective, 3-year multicenter cohort study of 810 patients with untreated, newly diagnosed, or previously treated iSGS.

METHODS: iSGS patients consented and enrolled in the North American Airway Collaborative (NoAAC) iSGS

RESULTS: Within the NoAAC iSGS1000 cohort, 810 patients participated in a 3-year, prospective study comparing surgical treatment efficacy and 385 had appropriate PEF …

Nrf1 Association With Auts2-Polycomb Mediates Specific Gene Activation In The Brain, Sanxiong Liu, Kimberly A Aldinger, Chi Vicky Cheng, Takae Kiyama, Mitali Dave, Hanna K Mcnamara, Wukui Zhao, James M Stafford, Nicolas Descostes, Pedro Lee, Stefano G Caraffi, Ivan Ivanovski, Edoardo Errichiello, Christiane Zweier, Orsetta Zuffardi, Michael Schneider, Antigone S Papavasiliou, M Scott Perry, Jennifer Humberson, Megan T Cho, Astrid Weber, Andrew Swale, Tudor C Badea, Chai-An Mao, Livia Garavelli, William B Dobyns, Danny Reinberg

Faculty, Staff and Student Publications

The heterogeneous family of complexes comprising Polycomb repressive complex 1 (PRC1) is instrumental for establishing facultative heterochromatin that is repressive to transcription. However, two PRC1 species, ncPRC1.3 and ncPRC1.5, are known to comprise novel components, AUTS2, P300, and CK2, that convert this repressive function to that of transcription activation. Here, we report that individuals harboring mutations in the HX repeat domain of AUTS2 exhibit defects in AUTS2 and P300 interaction as well as a developmental disorder reflective of Rubinstein-Taybi syndrome, which is mainly associated with a heterozygous pathogenic variant in CREBBP/EP300. Moreover, the absence of AUTS2 or mutation in its …

Comprehensive Characterization Of Covid-19 Patients With Repeatedly Positive Sars-Cov-2 Tests Using A Large Us Electronic Health Record Database, Xiao Dong, Yujia Zhou, Xiao-Ou Shu, Elmer V Bernstam, Rebecca Stern, David M Aronoff, Hua Xu, Loren Lipworth

Faculty, Staff and Student Publications

In the absence of genome sequencing, two positive molecular tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) separated by negative tests, prolonged time, and symptom resolution remain the best surrogate measure of possible reinfection. Using a large electronic health record database, we characterized clinical and testing data for 23 patients with repeatedly positive SARS-CoV-2 PCR test results ≥60 days apart, separated by ≥2 consecutive negative test results. The prevalence of chronic medical conditions, symptoms, and severe outcomes related to coronavirus disease 19 (COVID-19) illness were ascertained. The median age of patients was 64.5 years, 40% were Black, and 39% …

Exome Sequence Association Study Of Levels And Longitudinal Change Of Cardiovascular Risk Factor Phenotypes In European Americans And African Americans From The Atherosclerosis Risk In Communities Study, Elena V Feofanova, Elise Lim, Han Chen, Minjae Lee, Ching-Ti Liu, L Adrienne Cupples, Eric Boerwinkle

Faculty, Staff and Student Publications

Cardiovascular disease (CVD) is responsible for 31% of all deaths worldwide. Among CVD risk factors are age, race, increased systolic blood pressure (BP), and dyslipidemia. Both BP and blood lipids levels change with age, with a dose-dependent relationship between the cumulative exposure to hyperlipidemia and the risk of CVD. We performed an exome sequence association study using longitudinal data with up to 7805 European Americans (EAs) and 3171 African Americans (AAs) from the Atherosclerosis Risk in Communities (ARIC) study. We assessed associations of common (minor allele frequency > 5%) nonsynonymous and splice-site variants and gene-based sets of rare variants with levels …

Genome-Wide Association Study Of Serum Metabolites In The African American Study Of Kidney Disease And Hypertension, Shengyuan Luo, Elena V Feofanova, Adrienne Tin, Sarah Tung, Eugene P Rhee, Josef Coresh, Dan E Arking, Aditya Surapaneni, Pascal Schlosser, Yong Li, Anna Köttgen, Bing Yu, Morgan E Grams

Faculty, Staff and Student Publications

The genome-wide association study (GWAS) is a powerful means to study genetic determinants of disease traits and generate insights into disease pathophysiology. to date, few GWAS of circulating metabolite levels have been performed in African Americans with chronic kidney disease. Hypothesizing that novel genetic-metabolite associations may be identified in a unique population of African Americans with a lower glomerular filtration rate (GFR), we conducted a GWAS of 652 serum metabolites in 619 participants (mean measured glomerular filtration rate 45 mL/min/1.73m

Associations Between Physiological Biomarkers And Psychosocial Measures Of Pregnancy-Specific Anxiety And Depression With Support Intervention, Karen L Weis, Tony T Yuan, Katherine C Walker, Thomas F Gibbons, Wenyaw Chan

Faculty, Staff and Student Publications

Stress and anxiety significantly impact the hypothalamic-pituitary axis, and in pregnancy, the subsequent maternal-fetal response can lead to poor outcomes. The objective of this study was to assess the association between psychosocial measures of pregnancy-specific anxiety and physiologic inflammatory responses. Specifically, to determine the effectiveness of the Mentors Offering Maternal Support (M-O-M-S

Digital Technology Needs In Maternal Mental Health: A Qualitative Inquiry, Alexandra Zingg, Laura Carter, Deevakar Rogith, Amy Franklin, Sudhakar Selvaraj, Jerrie Refuerzo, Sahiti Myneni

Faculty, Staff and Student Publications

Digital technologies offer many opportunities to improve mental healthcare management for women seeking pre- and-postnatal care. They provide a discrete, practical medium that is well-suited for the sensitive nature of mental health. Women who are more prone to experiencing peripartum depression (PPD), such as those of low-socioeconomic background or in high-risk pregnancies, can benefit the most from such technologies. However, current digital interventions directed towards this population provide suboptimal support, and their responsiveness to end user needs is quite limited. Our objective is to understand the digital terrain of information needs for low-socioeconomic status women with high-risk pregnancies, specifically within …

Med-Bert: Pretrained Contextualized Embeddings On Large-Scale Structured Electronic Health Records For Disease Prediction, Laila Rasmy, Yang Xiang, Ziqian Xie, Cui Tao, Degui Zhi

Faculty, Staff and Student Publications

Deep learning (DL)-based predictive models from electronic health records (EHRs) deliver impressive performance in many clinical tasks. Large training cohorts, however, are often required by these models to achieve high accuracy, hindering the adoption of DL-based models in scenarios with limited training data. Recently, bidirectional encoder representations from transformers (BERT) and related models have achieved tremendous successes in the natural language processing domain. The pretraining of BERT on a very large training corpus generates contextualized embeddings that can boost the performance of models trained on smaller datasets. Inspired by BERT, we propose Med-BERT, which adapts the BERT framework originally developed …

Genetic And Non-Genetic Factors Affecting The Expression Of Covid-19-Relevant Genes In The Large Airway Epithelium, Silva Kasela, Victor E Ortega, Molly Martorella, Suresh Garudadri, Jenna Nguyen, Elizabeth Ampleford, Anu Pasanen, Srilaxmi Nerella, Kristina L Buschur, Igor Z Barjaktarevic, R Graham Barr, Eugene R Bleecker, Russell P Bowler, Alejandro P Comellas, Christopher B Cooper, David J Couper, Gerard J Criner, Jeffrey L Curtis, Meilan K Han, Nadia N Hansel, Eric A Hoffman, Robert J Kaner, Jerry A Krishnan, Fernando J Martinez, Merry-Lynn N Mcdonald, Deborah A Meyers, Robert Paine, Stephen P Peters, Mario Castro, Loren C Denlinger, Serpil C Erzurum, John V Fahy, Elliot Israel, Nizar N Jarjour, Bruce D Levy, Xingnan Li, Wendy C Moore, Sally E Wenzel, Charles Langelier, Prescott G Woodruff, Tuuli Lappalainen, Stephanie A Christenson

Faculty, Staff and Student Publications

BACKGROUND: The large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression.

METHODS: We analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with …

Genetic Discovery And Risk Characterization In Type 2 Diabetes Across Diverse Populations, Linda M Polfus, Burcu F Darst, Heather Highland, Xin Sheng, Maggie C Y Ng, Jennifer E Below, Lauren Petty, Stephanie Bien, Xueling Sim, Wei Wang, Pierre Fontanillas, Yesha Patel, Michael Preuss, Claudia Schurmann, Zhaohui Du, Yingchang Lu, Suhn K Rhie, Joseph M Mercader, Teresa Tusie-Luna, Clicerio González-Villalpando, Lorena Orozco, Cassandra N Spracklen, Brian E Cade, Richard A Jensen, Meng Sun, Yoonjung Yoonie Joo, Ping An, Lisa R Yanek, Lawrence F Bielak, Salman Tajuddin, Aude Nicolas, Guanjie Chen, Laura Raffield, Xiuqing Guo, Wei-Min Chen, Girish N Nadkarni, Mariaelisa Graff, Ran Tao, James S Pankow, Martha Daviglus, Qibin Qi, Eric A Boerwinkle, Simin Liu, Lawrence S Phillips, Ulrike Peters, Chris Carlson, Lynne R Wikens, Loic Le Marchand, Kari E North, Steven Buyske, Charles Kooperberg, Ruth J F Loos, Daniel O Stram, Christopher A Haiman

Faculty, Staff and Student Publications

Genomic discovery and characterization of risk loci for type 2 diabetes (T2D) have been conducted primarily in individuals of European ancestry. We conducted a multiethnic genome-wide association study of T2D among 53,102 cases and 193,679 control subjects from African, Hispanic, Asian, Native Hawaiian, and European population groups in the Population Architecture Genomics and Epidemiology (PAGE) and Diabetes Genetics Replication and Meta-analysis (DIAGRAM) Consortia. In individuals of African ancestry, we discovered a risk variant in the

Generalized And Transferable Patient Language Representation For Phenotyping With Limited Data, Yuqi Si, Elmer V Bernstam, Kirk Roberts

Faculty, Staff and Student Publications

The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing. In this work, we propose a multi-task pre-training and fine-tuning approach for learning generalized and transferable patient representations from medical language. The model is first pre-trained with different but related high-prevalence phenotypes and further fine-tuned on downstream target tasks. Our main contribution focuses on the impact this technique can have on low-prevalence phenotypes, a challenging task due to the dearth of data. We validate the representation from pre-training, and fine-tune the multi-task pre-trained models on low-prevalence phenotypes including 38 circulatory diseases, 23 …

Genome-Wide Meta-Analysis Of Muscle Weakness Identifies 15 Susceptibility Loci In Older Men And Women, Garan Jones, Katerina Trajanoska, Adam J Santanasto, Najada Stringa, Chia-Ling Kuo, Janice L Atkins, Joshua R Lewis, Thuyvy Duong, Shengjun Hong, Mary L Biggs, Jian'an Luan, Chloe Sarnowski, Kathryn L Lunetta, Toshiko Tanaka, Mary K Wojczynski, Ryan Cvejkus, Maria Nethander, Sahar Ghasemi, Jingyun Yang, M Carola Zillikens, Stefan Walter, Kamil Sicinski, Erika Kague, Cheryl L Ackert-Bicknell, Dan E Arking, B Gwen Windham, Eric Boerwinkle, Megan L Grove, Misa Graff, Dominik Spira, Ilja Demuth, Nathalie Van Der Velde, Lisette C P G M De Groot, Bruce M Psaty, Michelle C Odden, Alison E Fohner, Claudia Langenberg, Nicholas J Wareham, Stefania Bandinelli, Natasja M Van Schoor, Martijn Huisman, Qihua Tan, Joseph Zmuda, Dan Mellström, Magnus Karlsson, David A Bennett, Aron S Buchman, Philip L De Jager, Andre G Uitterlinden, Uwe Völker, Thomas Kocher, Alexander Teumer, Leocadio Rodriguéz-Mañas, Francisco J García, José A Carnicero, Pamela Herd, Lars Bertram, Claes Ohlsson, Joanne M Murabito, David Melzer, George A Kuchel, Luigi Ferrucci, David Karasik, Fernando Rivadeneira, Douglas P Kiel, Luke C Pilling

Faculty, Staff and Student Publications

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1 p = 4 × 10

Absent B Cells, Agammaglobulinemia, And Hypertrophic Cardiomyopathy In Folliculin-Interacting Protein 1 Deficiency, Francesco Saettini, Cecilia Poli, Jaime Vengoechea, Sonia Bonanomi, Julio C Orellana, Grazia Fazio, Fred H Rodriguez, Loreani P Noguera, Claire Booth, Valentina Jarur-Chamy, Marissa Shams, Maria Iascone, Maja Vukic, Serena Gasperini, Manuel Quadri, Amairelys Barroeta Seijas, Elizabeth Rivers, Mario Mauri, Raffaele Badolato, Gianni Cazzaniga, Cristina Bugarin, Giuseppe Gaipa, Wilma G M Kroes, Daniele Moratto, Monique M Van Oostaijen-Ten Dam, Frank Baas, Silvère Van Der Maarel, Rocco Piazza, Zeynep H Coban-Akdemir, James R Lupski, Bo Yuan, Ivan K Chinn, Lucia Daxinger, Andrea Biondi

Faculty, Staff and Student Publications

Agammaglobulinemia is the most profound primary antibody deficiency that can occur due to an early termination of B-cell development. We here investigated 3 novel patients, including the first known adult, from unrelated families with agammaglobulinemia, recurrent infections, and hypertrophic cardiomyopathy (HCM). Two of them also presented with intermittent or severe chronic neutropenia. We identified homozygous or compound-heterozygous variants in the gene for folliculin interacting protein 1 (FNIP1), leading to loss of the FNIP1 protein. B-cell metabolism, including mitochondrial numbers and activity and phosphatidylinositol 3-kinase/AKT pathway, was impaired. These defects recapitulated the Fnip1-/- animal model. Moreover, we identified either uniparental disomy …

Exchanges In A Virtual Environment For Diabetes Self-Management Education And Support: Social Network Analysis, Carlos A Pérez-Aldana, Allison A Lewinski, Constance M Johnson, Allison A Vorderstrasse, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities.

OBJECTIVE: The objective of this study was to …

Identifying Sleep-Related Factors Associated With Cognitive Function In A Hispanics/Latinos Cohort: A Dual Random Forest Approach, Li Xiaojin, Cui Licong, Wang Fei, Paul E Schulz, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Disordered sleep is associated with poor cognitive function and cognitive decline. However, little is known regarding the association of sleep-related factors with cognitive function in underrepresented cohorts such as the Hispanic/Latino population. Leveraging the National Sleep Research Resource, one of the most comprehensive collections of sleep studies, we identified a Hispanic/Latino cohort of 1,031 lower cognitive function cases and 2,062 normal controls. We developed a novel dual random forest (DRF) approach to discriminate cases against controls for estimating the potential impact of sleep-related variables related to the decline of cognitive function. Several important sleep-related factors were identified which may be …

Towards Digestible Digital Health Solutions: Application Of A Health Literacy Inclusive Development Framework For Peripartum Depression Management, Alexandra Zingg, Tavleen Singh, Sahiti Myneni

Faculty, Staff and Student Publications

Women of low income and education have lower levels of peripartum depression (PPD) literacy, limiting their ability to recognize symptoms and make informed healthcare decisions. Existing digital solutions and underlying development frameworks for PPD lack an integrative approach addressing health literacy and related disparities. Therefore, we develop an integrative framework for digital content engineering in PPD self-management consisting of (a) user needs analysis, (b) inclusion of eHealth literacy principles (science and health literacy), and (c) mapping user needs to the Behavioral Intervention Technology model. Results revealed that perinatal women seeking mental health care prefer information in multisensory formats, and knowledge …

A Comparison Of Exhaustive And Non-Lattice-Based Methods For Auditing Hierarchical Relations In Gene Ontology, Rashmie Abeysinghe, Fengbo Zheng, Licong Cui

Faculty, Staff and Student Publications

Uncovering and fixing errors in biomedical terminologies is essential so that they provide accurate knowledge to downstream applications that rely on them. Non-lattice-based methods have been applied to identify various kinds of inconsistencies in different biomedical terminologies. In previous work, we have introduced two inference-based approaches that were applied in an exhaustive manner to audit hierarchical relations in the Gene Ontology: (1) Lexical-based inference framework, and (2) Subsumption-based sub-term inference framework. However, it is unclear how effective these exhaustive approaches perform compared with their corresponding non-lattice-based approaches. Therefore, in this paper, we implement the non-lattice versions of these two exhaustive …

Utilization Of Target Lesion Heterogeneity For Treatment Efficacy Assessment In Late Stage Lung Cancer, Dung-Tsa Chen, Wenyaw Chan, Zachary J Thompson, Ram Thapa, Amer A Beg, Andreas N Saltos, Alberto A Chiappori, Jhanelle E Gray, Eric B Haura, Trevor A Rose, Ben Creelan

Faculty, Staff and Student Publications

RATIONALE: Recent studies have discovered several unique tumor response subgroups outside of response classification by Response Evaluation Criteria for Solid Tumors (RECIST), such as mixed response and oligometastasis. These subtypes have a distinctive property, lesion heterogeneity defined as diversity of tumor growth profiles in RECIST target lesions. Furthermore, many cancer clinical trials have been activated to evaluate various treatment options for heterogeneity-related subgroups (e.g., 29 trials so far listed in clinicaltrials.gov for cancer patients with oligometastasis). Some of the trials have shown survival benefit by tailored treatment strategies. This evidence presents the unmet need to incorporate lesion heterogeneity to improve …

Cross-Vendor Ct Image Data Harmonization Using Cvh-Ct, Md Selim, Jie Zhang, Baowei Fei, Guo-Qiang Zhang, Gary Yeeming Ge, Jin Chen

Faculty, Staff and Student Publications

While remarkable advances have been made in Computed Tomography (CT), most of the existing efforts focus on imaging enhancement while reducing radiation dose. How to harmonize CT image data captured using different scanners is vital in cross-center large-scale radiomics studies but remains the boundary to explore. Furthermore, the lack of paired training image problem makes it computationally challenging to adopt existing deep learning models. We propose a novel deep learning approach called CVH-CT for harmonizing CT images captured using scanners from different vendors. The generator of CVH-CT uses a self-attention mechanism to learn the scanner-related information. We also propose a …

Carving The Path To Allogeneic Car T Cell Therapy In Acute Myeloid Leukemia, Oren Pasvolsky, May Daher, Gheath Alatrash, David Marin, Naval Daver, Farhad Ravandi, Katy Rezvani, Elizabeth Shpall, Partow Kebriaei

Faculty, Staff and Student Publications

Despite advances in the understanding of the genetic landscape of acute myeloid leukemia (AML) and the addition of targeted biological and epigenetic therapies to the available armamentarium, achieving long-term disease-free survival remains an unmet need. Building on growing knowledge of the interactions between leukemic cells and their bone marrow microenvironment, strategies to battle AML by immunotherapy are under investigation. In the current review we describe the advances in immunotherapy for AML, with a focus on chimeric antigen receptor (CAR) T cell therapy. CARs constitute powerful immunologic modalities, with proven clinical success in B-Cell malignancies. We discuss the challenges and possible …

Deep Learning For Automated Analysis Of Cellular And Extracellular Components Of The Foreign Body Response In Multiphoton Microscopy Images, Mattia Sarti, Maria Parlani, Luis Diaz-Gomez, Antonios G Mikos, Pietro Cerveri, Stefano Casarin, Eleonora Dondossola

Faculty, Staff and Student Publications

The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, longitudinal investigation of the FBR evolution and interference strategies. However, follow-up analyses based on visual localization and manual segmentation are extremely time-consuming, subject to human error, and do not allow for automated parameter extraction. We developed an integrated computational pipeline based on an innovative and versatile variant of the U-Net neural network to segment and quantify cellular and extracellular structures of interest, which is …

Security And Privacy When Applying Fair Principles To Genomic Information, Jaime Delgado, Silvia Llorente

Faculty, Staff and Student Publications

Making data Findable, Accessible, Interoperable and Reusable (FAIR) is a good approach when data needs to be shared. However, security and privacy are still critical aspects. In the FAIRification process, there is a need both for de-identification of data and for license attribution. The paper analyses some of the issues related to this process when the objective is sharing genomic information. The main results are the identification of the already existing standards that could be used for this purpose and how to combine them. Nevertheless, the area is quickly evolving and more specific standards could be specified.

A Genome-Wide Association Study Discovers 46 Loci Of The Human Metabolome In The Hispanic Community Health Study/Study Of Latinos, Elena V Feofanova, Han Chen, Yulin Dai, Peilin Jia, Megan L Grove, Alanna C Morrison, Qibin Qi, Martha Daviglus, Jianwen Cai, Kari E North, Cathy C Laurie, Robert C Kaplan, Eric Boerwinkle, Bing Yu

Faculty, Staff and Student Publications

Variation in levels of the human metabolome reflect changes in homeostasis, providing a window into health and disease. The genetic impact on circulating metabolites in Hispanics, a population with high cardiometabolic disease burden, is largely unknown. We conducted genome-wide association analyses on 640 circulating metabolites in 3,926 Hispanic Community Health Study/Study of Latinos participants. The estimated heritability for 640 metabolites ranged between 0%-54% with a median at 2.5%. We discovered 46 variant-metabolite pairs (p value < 1.2 × 10

Representation Of Ehr Data For Predictive Modeling: A Comparison Between Umls And Other Terminologies, Laila Rasmy, Firat Tiryaki, Yujia Zhou, Yang Xiang, Cui Tao, Hua Xu, Degui Zhi

Faculty, Staff and Student Publications

OBJECTIVE: Predictive disease modeling using electronic health record data is a growing field. Although clinical data in their raw form can be used directly for predictive modeling, it is a common practice to map data to standard terminologies to facilitate data aggregation and reuse. There is, however, a lack of systematic investigation of how different representations could affect the performance of predictive models, especially in the context of machine learning and deep learning.

MATERIALS AND METHODS: We projected the input diagnoses data in the Cerner HealthFacts database to Unified Medical Language System (UMLS) and 5 other terminologies, including CCS, CCSR, …

Understanding Spatial Language In Radiology: Representation Framework, Annotation, And Spatial Relation Extraction From Chest X-Ray Reports Using Deep Learning, Surabhi Datta, Yuqi Si, Laritza Rodriguez, Sonya E Shooshan, Dina Demner-Fushman, Kirk Roberts

Faculty, Staff and Student Publications

Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Such spatial relationships are also linked to various differential diagnoses and often described through uncertainty phrases. Structured representation of this clinically significant spatial information has the potential to be used in a variety of downstream clinical informatics applications. Our focus is to extract these spatial representations from the reports. For this, we first define a representation framework based on the Spatial Role Labeling (SpRL) scheme, which we refer to as …

Covid-19 Testnorm: A Tool To Normalize Covid-19 Testing Names To Loinc Codes, Xiao Dong, Jianfu Li, Ekin Soysal, Jiang Bian, Scott L Duvall, Elizabeth Hanchrow, Hongfang Liu, Kristine E Lynch, Michael Matheny, Karthik Natarajan, Lucila Ohno-Machado, Serguei Pakhomov, Ruth Madeleine Reeves, Amy M Sitapati, Swapna Abhyankar, Theresa Cullen, Jami Deckard, Xiaoqian Jiang, Robert Murphy, Hua Xu

Faculty, Staff and Student Publications

Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) …