Medical Genetics Commons^™

Effects Of Sars-Cov-2 Variants On Cd8+ T Cell Epitope Diversity: Estimating Clinical Severity In The United States, Grace Kim, Jacob Elnaggar, Maya Sevalia, Najah Nicholas, Mallory Varnado, Judy Crabtree, Lucio Miele

School of Medicine Faculty Publications

Association for Clinical and Translational Science 2024; April 3 - April 5, 2024; Las Vegas, NV

Social And Behavior Factors Of Alzheimer's Disease And Related Dementias: A National Study In The Us, David Ciciora, Elizabeth Vásquez, Edward Valachovic, Lifang Hou, Yinan Zheng, Hua Xu, Xiaoqian Jiang, Kun Huang, Kelley Pettee Gabriel, Hong-Wen Deng, Mary P Gallant, Kai Zhang

Faculty, Staff and Student Publications

Introduction: Considerable research has linked many risk factors to Alzheimer's Disease and Related Dementias (ADRD). Without a clear etiology of ADRD, it is advantageous to rank the known risk factors by their importance and determine if disparities exist. Statistical-based ranking can provide insight into which risk factors should be further evaluated.

Methods: This observational, population-based study assessed 50 county-level measures and estimates related to ADRD in 3,155 counties in the U.S. using data from 2010 to 2021. Statistical analysis was performed in 2022-2023. The machine learning method, eXtreme Gradient Boosting, was utilized to rank the importance of these variables by …

Label-Aware Distance Mitigates Temporal And Spatial Variability For Clustering And Visualization Of Single-Cell Gene Expression Data, Shaoheng Liang, Jinzhuang Dou, Ramiz Iqbal, Ken Chen

Faculty, Staff and Student Publications

Clustering and visualization are essential parts of single-cell gene expression data analysis. The Euclidean distance used in most distance-based methods is not optimal. The batch effect, i.e., the variability among samples gathered from different times, tissues, and patients, introduces large between-group distance and obscures the true identities of cells. To solve this problem, we introduce Label-Aware Distance (LAD), a metric using temporal/spatial locality of the batch effect to control for such factors. We validate LAD on simulated data as well as apply it to a mouse retina development dataset and a lung dataset. We also found the utility of our …

Sox On Tumors, A Comfort Or A Constraint?, Junqing Jiang, Yufei Wang, Mengyu Sun, Xiangyuan Luo, Zerui Zhang, Yijun Wang, Siwen Li, Dian Hu, Jiaqian Zhang, Zhangfan Wu, Xiaoping Chen, Bixiang Zhang, Xiao Xu, Shuai Wang, Shengjun Xu, Wenjie Huang, Limin Xia

Faculty, Staff and Student Publications

The sex-determining region Y (SRY)-related high-mobility group (HMG) box (SOX) family, composed of 20 transcription factors, is a conserved family with a highly homologous HMG domain. Due to their crucial role in determining cell fate, the dysregulation of SOX family members is closely associated with tumorigenesis, including tumor invasion, metastasis, proliferation, apoptosis, epithelial-mesenchymal transition, stemness and drug resistance. Despite considerable research to investigate the mechanisms and functions of the SOX family, confusion remains regarding aspects such as the role of the SOX family in tumor immune microenvironment (TIME) and contradictory impacts the SOX family exerts on tumors. This review summarizes …

Enabling The Clinical Application Of Artificial Intelligence In Genomics: A Perspective Of The Amia Genomics And Translational Bioinformatics Workgroup, Nephi A Walton, Radha Nagarajan, Chen Wang, Murat Sincan, Robert R Freimuth, David B Everman, Derek C Walton, Scott P Mcgrath, Dominick J Lemas, Panayiotis V Benos, Alexander V Alekseyenko, Qianqian Song, Ece Gamsiz Uzun, Casey Overby Taylor, Alper Uzun, Thomas Nate Person, Nadav Rappoport, Zhongming Zhao, Marc S Williams

Faculty, Staff and Student Publications

OBJECTIVE: Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space.

PROCESS: A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members.

CONCLUSIONS: Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of …

Fusionneoantigen: : A Resource Of Fusion Gene-Specific Neoantigens, Himansu Kumar, Ruihan Luo, Jianguo Wen, Chengyuan Yang, Xiaobo Zhou, Pora Kim

Faculty, Staff and Student Publications

Among the diverse sources of neoantigens (i.e. single-nucleotide variants (SNVs), insertions or deletions (Indels) and fusion genes), fusion gene-derived neoantigens are generally more immunogenic, have multiple targets per mutation and are more widely distributed across various cancer types. Therefore, fusion gene-derived neoantigens are a potential source of highly immunogenic neoantigens and hold great promise for cancer immunotherapy. However, the lack of fusion protein sequence resources and knowledge prevents this application. We introduce 'FusionNeoAntigen', a dedicated resource for fusion-specific neoantigens, accessible at https://compbio.uth.edu/FusionNeoAntigen. In this resource, we provide fusion gene breakpoint crossing neoantigens focused on ∼43K fusion proteins of ∼16K in-frame …

Cov2var, A Function Annotation Database Of Sars-Cov-2 Genetic Variation, Yuzhou Feng, Jiahao Yi, Lin Yang, Yanfei Wang, Jianguo Wen, Weiling Zhao, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species …

Combination Chemotherapy Optimization With Discrete Dosing, Temitayo Ajayi, Seyedmohammadhossein Hosseinian, Andrew J Schaefer, Clifton D Fuller

Faculty, Staff and Student Publications

Chemotherapy drug administration is a complex problem that often requires expensive clinical trials to evaluate potential regimens; one way to alleviate this burden and better inform future trials is to build reliable models for drug administration. This paper presents a mixed-integer program for combination chemotherapy (utilization of multiple drugs) optimization that incorporates various important operational constraints and, besides dose and concentration limits, controls treatment toxicity based on its effect on the count of white blood cells. To address the uncertainty of tumor heterogeneity, we also propose chance constraints that guarantee reaching an operable tumor size with a high probability in …

Statins Are Rarely Prescribed For Incidentally Discovered Covert Cerebrovascular Disease: A Retrospective Cohort In A Large Electronic Health Record (Ehr) Identified Using Natural Language Processing, Lester Y Leung, Eric Puttock, David F Kallmes, Patrick Luetmer, Sunyang Fu, Chengyi X Zheng, Hongfang Liu, Wansu Chen, David M Kent

Faculty, Staff and Student Publications

Introduction: While incidentally discovered covert cerebrovascular diseases (id-CCD) are associated with future stroke, it is not known if patients with id-CCD are prescribed statins.

Methods: Patients age ≥50 with id-CCD on neuroimaging from 2009 to 2019 with no prior ischaemic stroke, transient ischaemic attack or dementia were identified using natural language processing in a large real-world cohort. Robust Poisson multivariable regression was used to assess statin prescription among patients without prior statins.

Results: Among 2 41 050 patients, 74 975 patients (31.1%; 4.7% with covert brain infarcts (CBI); 29.0% with white matter disease (WMD)) had id-CCD. 53.5% (95% CI 53.2 …

Siglec15, Negatively Correlated With Pd-L1 In Hcc, Could Induce Cd8+ T Cell Apoptosis To Promote Immune Evasion, Zheng Chen, Mincheng Yu, Bo Zhang, Lei Jin, Qiang Yu, Shuang Liu, Binghai Zhou, Jiuliang Yan, Wentao Zhang, Xiaoqiang Li, Yongfeng Xu, Yongsheng Xiao, Jian Zhou, Jia Fan, Mien-Chie Hung, Qinghai Ye, Hui Li, Lei Guo

Faculty, Staff and Student Publications

Functional roles of SIGLEC15 in hepatocellular carcinoma (HCC) were not clear, which was recently found to be an immune inhibitor with similar structure of inhibitory B7 family members. SIGLEC15 expression in HCC was explored in public databases and further examined by PCR analysis. SIGLEC15 and PD-L1 expression patterns were examined in HCC samples through immunohistochemistry. SIGLEC15 expression was knocked-down or over-expressed in HCC cell lines, and CCK8 tests were used to examine cell proliferative ability in vitro. Influences of SIGLEC15 expression on tumor growth were examined in immune deficient and immunocompetent mice respectively. Co-culture system of HCC cell lines and …

Single-Cell Dna Methylome And 3d Multi-Omic Atlas Of The Adult Mouse Brain, Hanqing Liu, Qiurui Zeng, Jingtian Zhou, Anna Bartlett, Bang-An Wang, Peter Berube, Wei Tian, Mia Kenworthy, Jordan Altshul, Joseph R Nery, Huaming Chen, Rosa G Castanon, Songpeng Zu, Yang Eric Li, Jacinta Lucero, Julia K Osteen, Antonio Pinto-Duarte, Jasper Lee, Jon Rink, Silvia Cho, Nora Emerson, Michael Nunn, Carolyn O'Connor, Zhanghao Wu, Ion Stoica, Zizhen Yao, Kimberly A Smith, Bosiljka Tasic, Chongyuan Luo, Jesse R Dixon, Hongkui Zeng, Bing Ren, M Margarita Behrens, Joseph R Ecker

Faculty, Staff and Student Publications

Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation–methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 …

Ensuring Trust In Genomics Research, Erman Ayday, Jaideep Vaidya, Xiaoqian Jiang, Amalio Telenti

Faculty, Staff and Student Publications

Reproducibility, transparency, representation, and privacy underpin the trust on genomics research in general and genome-wide association studies (GWAS) in particular. Concerns about these issues can be mitigated by technologies that address privacy protection, quality control, and verifiability of GWAS. However, many of the existing technological solutions have been developed in isolation and may address one aspect of reproducibility, transparency, representation, and privacy of GWAS while unknowingly impacting other aspects. As a consequence, the current patchwork of technological tools only partially and in an overlapping manner address issues with GWAS, sometimes even creating more problems. This paper addresses the progress in …

Web-Grading-A Tool To Test Personal Grading Of Renal And Prostate Cancer, Glen Kristiansen, Matthias Schmid, Lars Egevad, Hemamali Samaratunga, Murali Varma, Kaan Inam, Hans-Jürgen Thiesen, Brett Delahunt, Yulin Dai

Faculty, Staff and Student Publications

Only a few pathologists have the opportunity to verify their personal grading through objective assessment. This study introduces a web-based grading platform to facilitate and validate the grading of renal cell carcinoma and prostate cancer. Two representative images of two clinically annotated cohorts of 100 cases each of prostate and renal cell carcinoma were used. Each participant was asked to grade a tumor series utilizing a three tiered grading system. Finally, a Kaplan-Meier curve was drawn, and the log-rank test was used for statistical testing of the p-value. The grading of 22 participants (68%) achieved prognostic significance. Further analysis highlighted …

Pathogen-Driven Crispr Screens Identify Trex1as A Regulator Of Dna Self-Sensing During Influenza Virus Infection, Cason R King, Yiping Liu, Katherine A Amato, Grace A Schaack, Clayton Mickelson, Autumn E Sanders, Tony Hu, Srishti Gupta, Ryan A Langlois, Judith A Smith, Andrew Mehle

Faculty, Staff and Student Publications

Host:pathogen interactions dictate the outcome of infection, yet the limitations of current approaches leave large regions of this interface unexplored. Here, we develop a novel fitness-based screen that queries factors important during the middle to late stages of infection. This is achieved by engineering influenza virus to direct the screen by programming dCas9 to modulate host gene expression. Our genome-wide screen for pro-viral factors identifies the cytoplasmic DNA exonuclease TREX1. TREX1 degrades cytoplasmic DNA to prevent inappropriate innate immune activation by self-DNA. We reveal that this same process aids influenza virus replication. Infection triggers release of mitochondrial DNA into the …

Collagene Enables Privacy-Aware Federated And Collaborative Genomic Data Analysis, Wentao Li, Miran Kim, Kai Zhang, Han Chen, Xiaoqian Jiang, Arif Harmanci

Faculty, Staff and Student Publications

Growing regulatory requirements set barriers around genetic data sharing and collaborations. Moreover, existing privacy-aware paradigms are challenging to deploy in collaborative settings. We present COLLAGENE, a tool base for building secure collaborative genomic data analysis methods. COLLAGENE protects data using shared-key homomorphic encryption and combines encryption with multiparty strategies for efficient privacy-aware collaborative method development. COLLAGENE provides ready-to-run tools for encryption/decryption, matrix processing, and network transfers, which can be immediately integrated into existing pipelines. We demonstrate the usage of COLLAGENE by building a practical federated GWAS protocol for binary phenotypes and a secure meta-analysis protocol. COLLAGENE is available at https://zenodo.org/record/8125935 …

Generative Pre-Trained Transformers (Gpt) And Space Health: A Potential Frontier In Astronaut Health During Exploration Missions, Ethan Waisberg, Joshua Ong, Mouayad Masalkhi, Nasif Zaman, Sharif Amit Kamran, Prithul Sarker, Andrew G Lee, Alireza Tavakkoli

Faculty, Staff and Student Publications

In anticipation of space exploration where astronauts are traveling away from Earth, and for longer durations with an increasing communication lag, artificial intelligence (AI) frameworks such as large language learning models (LLMs) that can be trained on Earth can provide real-time answers. This emerging technology may be helpful for acute medical emergencies, particularly in austere and distant space environments. In this manuscript, we provide an overview of generative pre-trained transformer (GPT) technology, a rapidly emerging AI technology, and implications, considerations, and limitations of such technology for space health.

Federated Generalized Linear Mixed Models For Collaborative Genome-Wide Association Studies, Wentao Li, Han Chen, Xiaoqian Jiang, Arif Harmanci

Faculty, Staff and Student Publications

Federated association testing is a powerful approach to conduct large-scale association studies where sites share intermediate statistics through a central server. There are, however, several standing challenges. Confounding factors like population stratification should be carefully modeled across sites. In addition, it is crucial to consider disease etiology using flexible models to prevent biases. Privacy protections for participants pose another significant challenge. Here, we propose distributed Mixed Effects Genome-wide Association study (dMEGA), a method that enables federated generalized linear mixed model-based association testing across multiple sites without explicitly sharing genotype and phenotype data. dMEGA employs a reference projection to …

Minimal Positional Substring Cover Is A Haplotype Threading Alternative To Li And Stephens Model, Ahsan Sanaullah, Degui Zhi, Shaojie Zhang

Faculty, Staff and Student Publications

The Li and Stephens (LS) hidden Markov model (HMM) models the process of reconstructing a haplotype as a mosaic copy of haplotypes in a reference panel. For small panels, the probabilistic parameterization of LS enables modeling the uncertainties of such mosaics. However, LS becomes inefficient when sample size is large, because of its linear time complexity. Recently the PBWT, an efficient data structure capturing the local haplotype matching among haplotypes, was proposed to offer a fast method for giving some optimal solution (Viterbi) to the LS HMM. Previously, we introduced the minimal positional substring cover (MPSC) problem as an alternative …

Fast Inference Of Genetic Recombination Rates In Biobank Scale Data, Ardalan Naseri, William Yue, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

Although rates of recombination events across the genome (genetic maps) are fundamental to genetic research, the majority of current studies only use one standard map. There is evidence suggesting population differences in genetic maps, and thus estimating population-specific maps, are of interest. Although the recent availability of biobank-scale data offers such opportunities, current methods are not efficient at leveraging very large sample sizes. The most accurate methods are still linkage disequilibrium (LD)-based methods that are only tractable for a few hundred samples. In this work, we propose a fast and memory-efficient method for estimating genetic maps from population genotyping data. …

Genome-Wide Association Study Of Lung Adenocarcinoma In East Asia And Comparison With A European Population, Jianxin Shi, Kouya Shiraishi, Jiyeon Choi, Keitaro Matsuo, Tzu-Yu Chen, Juncheng Dai, Rayjean J Hung, Kexin Chen, Xiao-Ou Shu, Young Tae Kim, Maria Teresa Landi, Dongxin Lin, Wei Zheng, Zhihua Yin, Baosen Zhou, Bao Song, Jiucun Wang, Wei Jie Seow, Lei Song, I-Shou Chang, Wei Hu, Li-Hsin Chien, Qiuyin Cai, Yun-Chul Hong, Hee Nam Kim, Yi-Long Wu, Maria Pik Wong, Brian Douglas Richardson, Karen M Funderburk, Shilan Li, Tongwu Zhang, Charles Breeze, Zhaoming Wang, Batel Blechter, Bryan A Bassig, Jin Hee Kim, Demetrius Albanes, Jason Y Y Wong, Min-Ho Shin, Lap Ping Chung, Yang Yang, She-Juan An, Hong Zheng, Yasushi Yatabe, Xu-Chao Zhang, Young-Chul Kim, Neil E Caporaso, Jiang Chang, James Chung Man Ho, Michiaki Kubo, Yataro Daigo, Minsun Song, Yukihide Momozawa, Yoichiro Kamatani, Masashi Kobayashi, Kenichi Okubo, Takayuki Honda, Dean H Hosgood, Hideo Kunitoh, Harsh Patel, Shun-Ichi Watanabe, Yohei Miyagi, Haruhiko Nakayama, Shingo Matsumoto, Hidehito Horinouchi, Masahiro Tsuboi, Ryuji Hamamoto, Koichi Goto, Yuichiro Ohe, Atsushi Takahashi, Akiteru Goto, Yoshihiro Minamiya, Megumi Hara, Yuichiro Nishida, Kenji Takeuchi, Kenji Wakai, Koichi Matsuda, Yoshinori Murakami, Kimihiro Shimizu, Hiroyuki Suzuki, Motonobu Saito, Yoichi Ohtaki, Kazumi Tanaka, Tangchun Wu, Fusheng Wei, Hongji Dai, Mitchell J Machiela, Jian Su, Yeul Hong Kim, In-Jae Oh, Victor Ho Fun Lee, Gee-Chen Chang, Ying-Huang Tsai, Kuan-Yu Chen, Ming-Shyan Huang, Wu-Chou Su, Yuh-Min Chen, Adeline Seow, Jae Yong Park, Sun-Seog Kweon, Kun-Chieh Chen, Yu-Tang Gao, Biyun Qian, Chen Wu, Daru Lu, Jianjun Liu, Ann G Schwartz, Richard Houlston, Margaret R Spitz, Ivan P Gorlov, Xifeng Wu, Ping Yang, Stephen Lam, Adonina Tardon, Chu Chen, Stig E Bojesen, Mattias Johansson, Angela Risch, Heike Bickeböller, Bu-Tian Ji, H-Erich Wichmann, David C Christiani, Gadi Rennert, Susanne Arnold, Paul Brennan, James Mckay, John K Field, Sanjay S Shete, Loic Le Marchand, Geoffrey Liu, Angeline Andrew, Lambertus A Kiemeney, Shan Zienolddiny-Narui, Kjell Grankvist, Mikael Johansson, Angela Cox, Fiona Taylor, Jian-Min Yuan, Philip Lazarus, Matthew B Schabath, Melinda C Aldrich, Hyo-Sung Jeon, Shih Sheng Jiang, Jae Sook Sung, Chung-Hsing Chen, Chin-Fu Hsiao, Yoo Jin Jung, Huan Guo, Zhibin Hu, Laurie Burdett, Meredith Yeager, Amy Hutchinson, Belynda Hicks, Jia Liu, Bin Zhu, Sonja I Berndt, Wei Wu, Junwen Wang, Yuqing Li, Jin Eun Choi, Kyong Hwa Park, Sook Whan Sung, Li Liu, Chang Hyun Kang, Wen-Chang Wang, Jun Xu, Peng Guan, Wen Tan, Chong-Jen Yu, Gong Yang, Alan Dart Loon Sihoe, Ying Chen, Yi Young Choi, Jun Suk Kim, Ho-Il Yoon, In Kyu Park, Ping Xu, Qincheng He, Chih-Liang Wang, Hsiao-Han Hung, Roel C H Vermeulen, Iona Cheng, Junjie Wu, Wei-Yen Lim, Fang-Yu Tsai, John K C Chan, Jihua Li, Hongyan Chen, Hsien-Chih Lin, Li Jin, Jie Liu, Norie Sawada, Taiki Yamaji, Kathleen Wyatt, Shengchao A Li, Hongxia Ma, Meng Zhu, Zhehai Wang, Sensen Cheng, Xuelian Li, Yangwu Ren, Ann Chao, Motoki Iwasaki, Junjie Zhu, Gening Jiang, Ke Fei, Guoping Wu, Chih-Yi Chen, Chien-Jen Chen, Pan-Chyr Yang, Jinming Yu, Victoria L Stevens, Joseph F Fraumeni, Nilanjan Chatterjee, Olga Y Gorlova, Chao Agnes Hsiung, Christopher I Amos, Hongbing Shen, Stephen J Chanock, Nathaniel Rothman, Takashi Kohno, Qing Lan

Faculty, Staff and Student Publications

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European …

Mesoporous Silica Nanoparticles As A Gene Delivery Platform For Cancer Therapy, Nisar Ul Khaliq, Juyeon Lee, Joohyeon Kim, Yejin Kim, Sohyeon Yu, Jisu Kim, Sangwoo Kim, Daekyung Sung, Hyungjun Kim

Faculty, Staff and Student Publications

Cancer remains a major global health challenge. Traditional chemotherapy often results in side effects and drug resistance, necessitating the development of alternative treatment strategies such as gene therapy. Mesoporous silica nanoparticles (MSNs) offer many advantages as a gene delivery carrier, including high loading capacity, controlled drug release, and easy surface functionalization. MSNs are biodegradable and biocompatible, making them promising candidates for drug delivery applications. Recent studies demonstrating the use of MSNs for the delivery of therapeutic nucleic acids to cancer cells have been reviewed, along with their potential as a tool for cancer therapy. The major challenges and future interventions …

The Potential Regulation Of A-To-I Rna Editing On Genes In Parkinson's Disease, Sijia Wu, Qiuping Xue, Xinyu Qin, Xiaoming Wu, Pora Kim, Jacqueline Chyr, Xiaobo Zhou, Liyu Huang

Faculty, Staff and Student Publications

Parkinson's disease (PD) is characterized by dopaminergic neurodegeneration and an abnormal accumulation of α-synuclein aggregates. A number of genetic factors have been shown to increase the risk of PD. Exploring the underlying molecular mechanisms that mediate PD's transcriptomic diversity can help us understand neurodegenerative pathogenesis. In this study, we identified 9897 A-to-I RNA editing events associated with 6286 genes across 372 PD patients. Of them, 72 RNA editing events altered miRNA binding sites and this may directly affect miRNA regulations of their host genes. However, RNA editing effects on the miRNA regulation of genes are more complex. They can (1) …

Physio-Psycho-Social Interaction Mechanism In Dyadic Health Of Young And Middle-Aged Stroke Survivors And Their Spousal Caregivers: A Longitudinal Observational Study Protocol, Dandan Xiang, Zhen-Xiang Zhang, Song Ge, Wen Na Wang, Bei-Lei Lin, Su-Yan Chen, Er-Feng Guo, Peng-Bo Zhang, Zhi-Wei Liu, Hui Li, Yong-Xia Mei

Faculty, Staff and Student Publications

Introduction: In recent years, stroke has become more common among young people. Stroke not only has a profound impact on patients' health but also incurs stress and health threats to their caregivers, especially spousal caregivers. Moreover, the health of stroke survivors and their caregivers is interdependent. To our knowledge, no study has explored dyadic health of young and middle-aged stroke survivors and their spousal caregivers from physiological, psychological and social perspectives. Therefore, this proposed study aims to explore the mechanism of how physiological, psychological and social factors affect dyadic health of young and middle-aged stroke survivors and their spousal caregivers. …

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 …

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 …

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 …

Automated Contouring And Planning In Radiation Therapy: What Is 'Clinically Acceptable'?, Hana Baroudi, Kristy K Brock, Wenhua Cao, Xinru Chen, Caroline Chung, Laurence E Court, Mohammad D El Basha, Maguy Farhat, Skylar Gay, Mary P Gronberg, Aashish Chandra Gupta, Soleil Hernandez, Kai Huang, David A Jaffray, Rebecca Lim, Barbara Marquez, Kelly Nealon, Tucker J Netherton, Callistus M Nguyen, Brandon Reber, Dong Joo Rhee, Ramon M Salazar, Mihir D Shanker, Carlos Sjogreen, Mckell Woodland, Jinzhong Yang, Cenji Yu, Yao Zhao

Faculty, Staff and Student Publications

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

E Pluribus Unum: Prospective Acceptability Benchmarking From The Contouring Collaborative For Consensus In Radiation Oncology Crowdsourced Initiative For Multiobserver Segmentation, Diana Lin, Kareem A Wahid, Benjamin E Nelms, Renjie He, Mohammed A Naser, Simon Duke, Michael V Sherer, John P Christodouleas, Abdallah S R Mohamed, Michael Cislo, James D Murphy, Clifton D Fuller, Erin F Gillespie

Faculty, Staff and Student Publications

Purpose: Contouring Collaborative for Consensus in Radiation Oncology (C3RO) is a crowdsourced challenge engaging radiation oncologists across various expertise levels in segmentation. An obstacle to artificial intelligence (AI) development is the paucity of multiexpert datasets; consequently, we sought to characterize whether aggregate segmentations generated from multiple nonexperts could meet or exceed recognized expert agreement.

Approach: Participants who contoured ≥1 region of interest (ROI) for the breast, sarcoma, head and neck (H&N), gynecologic (GYN), or gastrointestinal (GI) cases were identified as a nonexpert or recognized expert. Cohort-specific ROIs were combined into single simultaneous truth and performance level estimation (STAPLE) consensus segmentations. …

Detecting Overlapping Gene Regions Using The U-Net Attention Mechanism, Samuel Lemma

All Graduate Theses, Dissertations, and Other Capstone Projects

The current issue of locating, diagnosing, and treating cancer and other diseases linked to specific target genes necessitates the creation of a reliable system for precisely identifying target genes that are initially extracted from a human chromosome. Current methodologies often suffer from overlapping gene regions in the target gene that occurs during the analysis process, which can have a substantial impact on the accuracy of the results. Our recommended approach, which was the appropriate model to apply for this particular problem, is set to enhance the analytical process by utilizing neural networks' U-Net with an attention mechanism. We were able …

Development Of A Chemical Biology Approach To Uncover The Influence Of Sequence Variations On Ces1 Activity In Live Cells, Samuel James Knebel

Masters Theses

Drug metabolism is the biochemical process of modifying drugs to detoxify and remove them through enzymatic transformations. These biotransformation’s occur primarily in the liver and are critical to understanding how pharmaceutical compounds are chemically altered inside the human body. Human carboxylesterases (CESs) catalyze the hydrolysis of esters, amides, thioesters, and carbamates. CES-mediated hydrolysis plays an important role in the metabolism of many drugs including the first FDA approved antiviral treatment for COVID-19, remdesivir (Veklury), the seizure control medication rufinamide (Banzel), and the flu antiviral drug oseltamivir (Tamiflu). CES activity is known to be influenced by a variety of factors including …