Medical Genetics Commons^™

Proton Image-Guided Radiation Assignment For Therapeutic Escalation Via Selection Of Locally Advanced Head And Neck Cancer Patients [Pirates]: A Phase I Safety And Feasibility Trial Of Mri-Guided Adaptive Particle Radiotherapy, Lisanne V Van Dijk, Steven J Frank, Ying Yuan, Brandon Gunn, Amy C Moreno, Abdallah S R Mohamed, Kathryn E Preston, Yun Qing, Michael T Spiotto, William H Morrison, Anna Lee, Jack Phan, Adam S Garden, David I Rosenthal, Johannes A Langendijk, Clifton D Fuller

Faculty, Staff and Student Publications

Introduction: Radiation dose-escalation for head and neck cancer (HNC) patients aiming to improve cure rates is challenging due to the increased risk of unacceptable treatment-induced toxicities. With "Proton Image-guided Radiation Assignment for Therapeutic Escalation via Selection of locally advanced head and neck cancer patients" (PIRATES), we present a novel treatment approach that is designed to facilitate dose-escalation while minimizing the risk of dose-limiting toxicities for locally advanced HPV-negative HNC patients. The aim of this Phase I trial is to assess the safety & feasibility of PIRATES approach.

Methods: The PIRATES protocol employs a multi-faceted dose-escalation approach to minimize the risk …

Progression Free Survival Prediction For Head And Neck Cancer Using Deep Learning Based On Clinical And Pet/Ct Imaging Data, Mohamed A Naser, Kareem A Wahid, Abdallah S R Mohamed, Moamen Abobakr Abdelaal, Renjie He, Cem Dede, Lisanne V Van Dijk, Clifton D Fuller

Faculty, Staff and Student Publications

Determining progression-free survival (PFS) for head and neck squamous cell carcinoma (HNSCC) patients is a challenging but pertinent task that could help stratify patients for improved overall outcomes. PET/CT images provide a rich source of anatomical and metabolic data for potential clinical biomarkers that would inform treatment decisions and could help improve PFS. In this study, we participate in the 2021 HECKTOR Challenge to predict PFS in a large dataset of HNSCC PET/CT images using deep learning approaches. We develop a series of deep learning models based on the DenseNet architecture using a negative log-likelihood loss function that utilizes PET/CT …

Combining Tumor Segmentation Masks With Pet/Ct Images And Clinical Data In A Deep Learning Framework For Improved Prognostic Prediction In Head And Neck Squamous Cell Carcinoma, Kareem A Wahid, Renjie He, Cem Dede, Abdallah S R Mohamed, Moamen Abobakr Abdelaal, Lisanne V Van Dijk, Clifton D Fuller, Mohamed A Naser

Faculty, Staff and Student Publications

PET/CT images provide a rich data source for clinical prediction models in head and neck squamous cell carcinoma (HNSCC). Deep learning models often use images in an end-to-end fashion with clinical data or no additional input for predictions. However, in the context of HNSCC, the tumor region of interest may be an informative prior in the generation of improved prediction performance. In this study, we utilize a deep learning framework based on a DenseNet architecture to combine PET images, CT images, primary tumor segmentation masks, and clinical data as separate channels to predict progression-free survival (PFS) in days for HNSCC …

Establishment And Validation Of Pre-Therapy Cervical Vertebrae Muscle Quantification As A Prognostic Marker Of Sarcopenia In Patients With Head And Neck Cancer, Brennan Olson, Jared Edwards, Catherine Degnin, Nicole Santucci, Michelle Buncke, Jeffrey Hu, Yiyi Chen, Clifton D Fuller, Mathew Geltzeiler, Aaron J Grossberg, Daniel Clayburgh

Faculty, Staff and Student Publications

Background: Sarcopenia is prognostic for survival in patients with head and neck cancer (HNC). However, identification of this high-risk feature remains challenging without computed tomography (CT) imaging of the abdomen or thorax. Herein, we establish sarcopenia thresholds at the C3 level and determine if C3 sarcopenia is associated with survival in patients with HNC.

Methods: This retrospective cohort study was conducted in consecutive patients with a squamous cell carcinoma of the head and neck with cross-sectional abdominal or neck imaging within 60 days prior to treatment. Measurement of cross-sectional muscle area at L3 and C3 levels was performed from CT …

Anatomy And Function Of Ventral Tegmental Area Glutamate Neurons, Jing Cai, Qingchun Tong

Faculty, Staff and Student Publications

The ventral tegmental area (VTA) is well known for regulating reward consumption, learning, memory, and addiction behaviors through mediating dopamine (DA) release in downstream regions. Other than DA neurons, the VTA is known to be heterogeneous and contains other types of neurons, including glutamate neurons. In contrast to the well-studied and established functions of DA neurons, the role of VTA glutamate neurons is understudied, presumably due to their relatively small quantity and a lack of effective means to study them. Yet, emerging studies have begun to reveal the importance of glutamate release from VTA neurons in regulating diverse behavioral repertoire …

Causal Inference Of Genetic Variants And Genes In Amyotrophic Lateral Sclerosis, Siyu Pan, Xinxuan Liu, Tianzi Liu, Zhongming Zhao, Yulin Dai, Yin-Ying Wang, Peilin Jia, Fan Liu

Faculty, Staff and Student Publications

Amyotrophic lateral sclerosis (ALS) is a fatal progressive multisystem disorder with limited therapeutic options. Although genome-wide association studies (GWASs) have revealed multiple ALS susceptibility loci, the exact identities of causal variants, genes, cell types, tissues, and their functional roles in the development of ALS remain largely unknown. Here, we reported a comprehensive post-GWAS analysis of the recent large ALS GWAS (n = 80,610), including functional mapping and annotation (FUMA), transcriptome-wide association study (TWAS), colocalization (COLOC), and summary data-based Mendelian randomization analyses (SMR) in extensive multi-omics datasets. Gene property analysis highlighted inhibitory neuron 6, oligodendrocytes, and GABAergic neurons (Gad1/Gad2) as …

Facilitating Federated Genomic Data Analysis By Identifying Record Correlations While Ensuring Privacy, Leonard Dervishi, Xinyue Wang, Wentao Li, Anisa Halimi, Jaideep Vaidya, Xiaoqian Jiang, Erman Ayday

Faculty, Staff and Student Publications

With the reduction of sequencing costs and the pervasiveness of computing devices, genomic data collection is continually growing. However, data collection is highly fragmented and the data is still siloed across different repositories. Analyzing all of this data would be transformative for genomics research. However, the data is sensitive, and therefore cannot be easily centralized. Furthermore, there may be correlations in the data, which if not detected, can impact the analysis. In this paper, we take the first step towards identifying correlated records across multiple data repositories in a privacy-preserving manner. The proposed framework, based on random shuffling, synthetic record …

A Novel Group Of Genes That Cause Endocrine Resistance In Breast Cancer Identified By Dynamic Gene Expression Analysis, Arvand Asghari, Katherine Wall, Michael Gill, Natascha Del Vecchio, Farnaz Allahbakhsh, Jacky Wu, Nan Deng, W Jim Zheng, Hulin Wu, Michihisa Umetani, Vahed Maroufy

Faculty, Staff and Student Publications

Breast cancer (BC) is the most common type of cancer diagnosed in women. Among female cancer deaths, BC is the second leading cause of death worldwide. For estrogen receptor-positive (ER-positive) breast cancers, endocrine therapy is an effective therapeutic approach. However, in many cases, an ER-positive tumor becomes unresponsive to endocrine therapy, and tumor regrowth occurs after treatment. While some genetic mutations contribute to resistance in some patients, the underlying causes of resistance to endocrine therapy are mostly undetermined. In this study, we utilized a recently developed statistical approach to investigate the dynamic behavior of gene expression during the development of …

An Ensemble-Based Deep Convolutional Neural Network For Computer-Aided Polyps Identification From Colonoscopy, Pallabi Sharma, Bunil Kumar Balabantaray, Kangkana Bora, Saurav Mallik, Kunio Kasugai, Zhongming Zhao

Faculty, Staff and Student Publications

Colorectal cancer (CRC) is the third leading cause of cancer death globally. Early detection and removal of precancerous polyps can significantly reduce the chance of CRC patient death. Currently, the polyp detection rate mainly depends on the skill and expertise of gastroenterologists. Over time, unidentified polyps can develop into cancer. Machine learning has recently emerged as a powerful method in assisting clinical diagnosis. Several classification models have been proposed to identify polyps, but their performance has not been comparable to an expert endoscopist yet. Here, we propose a multiple classifier consultation strategy to create an effective and powerful classifier for …

A Deep Learning-Based Framework For Supporting Clinical Diagnosis Of Glioblastoma Subtypes, Sana Munquad, Tapas Si, Saurav Mallik, Asim Bikas Das, Zhongming Zhao

Faculty, Staff and Student Publications

Understanding molecular features that facilitate aggressive phenotypes in glioblastoma multiforme (GBM) remains a major clinical challenge. Accurate diagnosis of GBM subtypes, namely classical, proneural, and mesenchymal, and identification of specific molecular features are crucial for clinicians for systematic treatment. We develop a biologically interpretable and highly efficient deep learning framework based on a convolutional neural network for subtype identification. The classifiers were generated from high-throughput data of different molecular levels, i.e., transcriptome and methylome. Furthermore, an integrated subsystem of transcriptome and methylome data was also used to build the biologically relevant model. Our results show that deep learning model outperforms …

Dimensionality Reduction And Louvain Agglomerative Hierarchical Clustering For Cluster-Specified Frequent Biomarker Discovery In Single-Cell Sequencing Data, Soumita Seth, Saurav Mallik, Tapas Bhadra, Zhongming Zhao

Faculty, Staff and Student Publications

The major interest domains of single-cell RNA sequential analysis are identification of existing and novel types of cells, depiction of cells, cell fate prediction, classification of several types of tumor, and investigation of heterogeneity in different cells. Single-cell clustering plays an important role to solve the aforementioned questions of interest. Cluster identification in high dimensional single-cell sequencing data faces some challenges due to its nature. Dimensionality reduction models can solve the problem. Here, we introduce a potential cluster specified frequent biomarkers discovery framework using dimensionality reduction and hierarchical agglomerative clustering Louvain for single-cell RNA sequencing data analysis. First, we pre-filtered …

Explanation-Driven Deep Learning Model For Prediction Of Brain Tumour Status Using Mri Image Data, Loveleen Gaur, Mohan Bhandari, Tanvi Razdan, Saurav Mallik, Zhongming Zhao

Faculty, Staff and Student Publications

Cancer research has seen explosive development exploring deep learning (DL) techniques for analysing magnetic resonance imaging (MRI) images for predicting brain tumours. We have observed a substantial gap in explanation, interpretability, and high accuracy for DL models. Consequently, we propose an explanation-driven DL model by utilising a convolutional neural network (CNN), local interpretable model-agnostic explanation (LIME), and Shapley additive explanation (SHAP) for the prediction of discrete subtypes of brain tumours (meningioma, glioma, and pituitary) using an MRI image dataset. Unlike previous models, our model used a dual-input CNN approach to prevail over the classification challenge with images of inferior quality …

Breast Cancer Detection: Shallow Convolutional Neural Network Against Deep Convolutional Neural Networks Based Approach, Himanish Shekhar Das, Akalpita Das, Anupal Neog, Saurav Mallik, Kangkana Bora, Zhongming Zhao

Faculty, Staff and Student Publications

Introduction: Of all the cancers that afflict women, breast cancer (BC) has the second-highest mortality rate, and it is also believed to be the primary cause of the high death rate. Breast cancer is the most common cancer that affects women globally. There are two types of breast tumors: benign (less harmful and unlikely to become breast cancer) and malignant (which are very dangerous and might result in aberrant cells that could result in cancer).

Methods: To find breast abnormalities like masses and micro-calcifications, competent and educated radiologists often examine mammographic images. This study focuses on computer-aided diagnosis to help …

Apaview: A Web-Based Platform For Alternative Polyadenylation Analyses In Hematological Cancers, Xi Hu, Jialin Song, Jacqueline Chyr, Jinping Wan, Xiaoyan Wang, Jianqiang Du, Junbo Duan, Huqin Zhang, Xiaobo Zhou, Xiaoming Wu

Faculty, Staff and Student Publications

Background: Hematologic malignancies, such as acute promyelocytic leukemia (APL) and acute myeloid leukemia (AML), are cancers that start in blood-forming tissues and can affect the blood, bone marrow, and lymph nodes. They are often caused by genetic and molecular alterations such as mutations and gene expression changes. Alternative polyadenylation (APA) is a post-transcriptional process that regulates gene expression, and dysregulation of APA contributes to hematological malignancies. RNA-sequencing-based bioinformatic methods can identify APA sites and quantify APA usages as molecular indexes to study APA roles in disease development, diagnosis, and treatment. Unfortunately, APA data pre-processing, analysis, and visualization are time-consuming, inconsistent, …

Effects Of Tamoxifen Inducible Mercremer On Gene Expression In Cardiac Myocytes In Mice, Leila Rouhi, Siyang Fan, Sirisha M Cheedipudi, Melis Olcum, Hyun-Hwan Jeong, Zhongming Zhao, Priyatansh Gurha, Ali J Marian

Faculty, Staff and Student Publications

The Cre-LoxP technology, including the tamoxifen (TAM) inducible MerCreMer (MCM), is increasingly used to delineate gene function, understand the disease mechanisms, and test therapeutic interventions. We set to determine the effects of TAM-MCM on cardiac myocyte transcriptome. Expression of the MCM was induced specifically in cardiac myocytes upon injection of TAM to myosin heavy chain 6-MCM (Myh6-Mcm) mice for 5 consecutive days. Cardiac function, myocardial histology, and gene expression (RNA-sequencing) were analyzed 2 weeks after TAM injection. A total of 346 protein coding genes (168 up- and 178 down-regulated) were differentially expressed. Transcript levels of 85 genes, analyzed …

Identification Of Micrornas And Gene Regulatory Networks In Cleft Lip Common In Humans And Mice, Hiroki Yoshioka, Aimin Li, Akiko Suzuki, Sai Shankar Ramakrishnan, Zhongming Zhao, Junichi Iwata

Faculty, Staff and Student Publications

The etiology of cleft lip with/without cleft palate (CL/P), one of the most frequent craniofacial birth defects worldwide, is complicated by contributions of both genetic and environmental factors. Understanding the etiology of these conditions is essential for developing preventive strategies. This study thus aims to identify regulatory networks of microRNAs (miRNAs), transcriptional factors (TFs) and non-TF genes associated with cleft lip (CL) that are conserved in humans and mice. Notably, we found that miR-27b, miR-133b, miR-205, miR-376b and miR-376c were involved in the regulation of CL-associated gene expression in both humans and mice. Among the candidate miRNAs, the overexpression of …

Primary Ciliary Dyskinesia: Ancestral Haplotypes Analysis Of The Rsph4a Founder Mutation In Puerto Rico, Wilfredo De Jesús-Rojas, Dalilah Reyes De Jesús, Angélica M Nieves, Ricardo A Mosquera, Juan C Martinez-Cruzado

Faculty, Staff and Student Publications

Genetic mutations in >50 genes, including RSPH4A, can lead to primary ciliary dyskinesia (PCD). RSPH4A mutations affect radial spokes, which alter the configuration of the ciliary ultrastructure and lead to chronic oto-sinopulmonary disease. The RSPH4A [c.921+3_6delAAGT] founder mutation was described as one cause of PCD without laterality defects in Puerto Rico. The average Puerto Rican genetic composition includes 64% European, 21% African ancestral, and 15% Native-American or Taino, a native tribe in the Caribbean at the start of the European colonization, genes. Due to the relatively elevated Taino ancestry on the island, it might have contributed to the endemicity of …

The Design And Rationale Of A Multicenter Real-World Trial: The Southeastern Collaboration To Improve Blood Pressure Control In The Us Black Belt – Addressing The Triple Threat, Tina O Findley, Hope Northrup

Faculty, Staff and Student Publications

The incidence of congenital heart defect (CHD) has increased over the past fifty years, partly attributed to routine fetal anatomical examination by sonography during obstetric care and improvements in ultrasound technology and technique. Fetal findings on ultrasound in addition to maternal biomarkers are the backbone of first- and second-trimester screening for common genetic conditions, namely aneuploidy. Since the introduction of non-invasive prenatal testing (NIPT) using next-generation sequencing to sequence cell-free fetal DNA, the detection rate of common trisomies as well as sex chromosomal aneuploidies have markedly increased. As the use of NIPT continues to broaden, the best means of incorporating …

Overexpression Of Mir-1306-5p, Mir-3195, And Mir-3914 Inhibits Ameloblast Differentiation Through Suppression Of Genes Associated With Human Amelogenesis Imperfecta, Hiroki Yoshioka, Yin-Ying Wang, Akiko Suzuki, Meysam Shayegh, Mona V Gajera, Zhongming Zhao, Junichi Iwata

Faculty, Staff and Student Publications

Amelogenesis imperfecta is a congenital form of enamel hypoplasia. Although a number of genetic mutations have been reported in humans, the regulatory network of these genes remains mostly unclear. To identify signatures of biological pathways in amelogenesis imperfecta, we conducted bioinformatic analyses on genes associated with the condition in humans. Through an extensive search of the main biomedical databases, we found 56 genes in which mutations and/or association/linkage were reported in individuals with amelogenesis imperfecta. These candidate genes were further grouped by function, pathway, protein-protein interaction, and tissue-specific expression patterns using various bioinformatic tools. The bioinformatic analyses highlighted a group …

Phenytoin Inhibits Cell Proliferation Through Microrna-196a-5p In Mouse Lip Mesenchymal Cells, Hiroki Yoshioka, Sai Shankar Ramakrishnan, Akiko Suzuki, Junichi Iwata

Faculty, Staff and Student Publications

Cleft lip (CL) is one of the most common birth defects. It is caused by either genetic mutations or environmental factors. Recent studies suggest that environmental factors influence the expression of noncoding RNAs [e.g., microRNA (miRNA)], which can regulate the expression of genes crucial for cellular functions. In this study, we examined which miRNAs are associated with CL. Among 10 candidate miRNAs (miR-98-3p, miR-101a-3p, miR-101b-3p, miR-141-3p, miR-144-3p, miR-181a-5p, miR-196a-5p, miR-196b-5p, miR-200a-3p, and miR-710) identified through our bioinformatic analysis of CL-associated genes, overexpression of miR-181a-5p, miR-196a-5p, miR-196b-5p, and miR-710 inhibited cell proliferation through suppression of genes associated with CL in cultured …

Cost Efficacy Of Rapid Whole Genome Sequencing In The Pediatric Intensive Care Unit, Erica Sanford Kobayashi, Bryce Waldman, Branden M Engorn, Katherine Perofsky, Erika Allred, Benjamin Briggs, Chelsea Gatcliffe, Nanda Ramchandar, Jeffrey J Gold, Ami Doshi, Elizabeth G Ingulli, Courtney D Thornburg, Wendy Benson, Lauge Farnaes, Shimul Chowdhury, Seema Rego, Charlotte Hobbs, Stephen F Kingsmore, David P Dimmock, Nicole G Coufal

Faculty, Staff and Student Publications

The diagnostic and clinical utility of rapid whole genome sequencing (rWGS) for critically ill children in the intensive care unit (ICU) has been substantiated by multiple studies, but comprehensive cost-effectiveness evaluation of rWGS in the ICU outside of the neonatal age group is lacking. In this study, we examined cost data retrospectively for a cohort of 38 children in a regional pediatric ICU (PICU) who received rWGS. We identified seven of 17 patients who received molecular diagnoses by rWGS and had resultant changes in clinical management with sufficient clarity to permit cost and quality adjusted life years (QALY) modeling. Cost …

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 …

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 …

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 …

Epilepsy Risk Prediction Model For Patients With Tuberous Sclerosis Complex, Laura S Farach, Melissa A Richard, Philip J Lupo, Mustafa Sahin, Darcy A Krueger, Joyce Y Wu, Elizabeth M Bebin, Kit Sing Au, Hope Northrup, Tacern Study Group

Faculty, Staff and Student Publications

BACKGROUND: Individuals with tuberous sclerosis complex are at increased risk of epilepsy. Early seizure control improves developmental outcomes, making identifying at-risk patients critically important. Despite several identified risk factors, it remains difficult to predict. The purpose of the study was to evaluate the combined risk prediction of previously identified risk factors for epilepsy in individuals with tuberous sclerosis complex.

METHODS: The study group (n = 333) consisted of individuals with tuberous sclerosis complex who were enrolled in the Tuberous Sclerosis Complex Autism Center of Excellence Research Network and UT TSC Biobank. The outcome was defined as having an epilepsy diagnosis. …

Social And Leisure Activities Predict Transitions In Cognitive Functioning In Older Mexican Adults: A Latent Transition Analysis Of The Mexican Health And Aging Study, Heather Mary Brown, Stephen A Murray, Hope Northrup, Kit Sing Au, Lee A Niswander

Faculty, Staff and Student Publications

Disruptions in neural tube (NT) closure result in neural tube defects (NTDs). To understand the molecular processes required for mammalian NT closure, we investigated the role of Snx3, a sorting nexin gene. Snx3−/− mutant mouse embryos display a fully-penetrant cranial NTD. In vivo, we observed decreased canonical WNT target gene expression in the cranial neural epithelium of the Snx3−/− embryos and a defect in convergent extension of the neural epithelium. Snx3−/− cells show decreased WNT secretion, and live cell imaging reveals aberrant recycling of the WNT ligand-binding protein WLS and mis-trafficking to the lysosome for degradation. The importance …

Identification Of Novel Candidate Risk Genes For Myelomeningocele Within The Glucose Homeostasis/Oxidative Stress And Folate/One-Carbon Metabolism Networks, Paul Hillman, Craig Baker, Luke Hebert, Michael Brown, James Hixson, Allison Ashley-Koch, Alanna C Morrison, Hope Northrup, Kit Sing Au

Faculty, Staff and Student Publications

BACKGROUND: Neural tube defects (NTDs) are the second most common complex birth defect, yet, our understanding of the genetic contribution to their development remains incomplete. Two environmental factors associated with NTDs are Folate and One Carbon Metabolism (FOCM) and Glucose Homeostasis and Oxidative Stress (GHOS). Utilizing next-generation sequencing of a large patient cohort, we identify novel candidate genes in these two networks to provide insights into NTD mechanisms.

METHODS: Exome sequencing (ES) was performed in 511 patients, born with myelomeningocele, divided between European American and Mexican American ethnicities. Healthy control data from the Genome Aggregation database were ethnically matched and …

Evidence For Craniofacial Enhancer Variation Underlying Nonsyndromic Cleft Lip And Palate, Vershanna E Morris, S Shahrukh Hashmi, Lisha Zhu, Lorena Maili, Christian Urbina, Steven Blackwell, Matthew R Greives, Edward P Buchanan, John B Mulliken, Susan H Blanton, W Jim Zheng, Jacqueline T Hecht, Ariadne Letra

Faculty, Staff and Student Publications

Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect for which only ~ 20% of the underlying genetic variation has been identified. Variants in noncoding regions have been increasingly suggested to contribute to the missing heritability. In this study, we investigated whether variation in craniofacial enhancers contributes to NSCLP. Candidate enhancers were identified using VISTA Enhancer Browser and previous publications. Prioritization was based on patterning defects in knockout mice, deletion/duplication of craniofacial genes in animal models and results of whole exome/whole genome sequencing studies. This resulted in 20 craniofacial enhancers to be investigated. Custom amplicon-based …

Critical Micrornas And Regulatory Motifs In Cleft Palate Identified By A Conserved Mirna-Tf-Gene Network Approach In Humans And Mice, Aimin Li, Peilin Jia, Saurav Mallik, Rong Fei, Hiroki Yoshioka, Akiko Suzuki, Junichi Iwata, Zhongming Zhao

Faculty, Staff and Student Publications

Cleft palate (CP) is the second most common congenital birth defect. The etiology of CP is complicated, with involvement of various genetic and environmental factors. To investigate the gene regulatory mechanisms, we designed a powerful regulatory analytical approach to identify the conserved regulatory networks in humans and mice, from which we identified critical microRNAs (miRNAs), target genes and regulatory motifs (miRNA-TF-gene) related to CP. Using our manually curated genes and miRNAs with evidence in CP in humans and mice, we constructed miRNA and transcription factor (TF) co-regulation networks for both humans and mice. A consensus regulatory loop (miR17/miR20a-FOXE1-PDGFRA) and eight …

Wolff-Parkinson-White Syndrome: De Novo Variants And Evidence For Mutational Burden In Genes Associated With Atrial Fibrillation, Zeynep H Coban-Akdemir, Wu-Lin Charng, Mahshid Azamian, Ingrid S Paine, Jaya Punetha, Christopher M Grochowski, Tomasz Gambin, Santiago O Valdes, Bryan Cannon, Gladys Zapata, Patricia P Hernandez, Shalini Jhangiani, Harsha Doddapaneni, Jianhong Hu, Fatima Boricha, Donna M Muzny, Eric Boerwinkle, Yaping Yang, Richard A Gibbs, Jennifer E Posey, Xander H T Wehrens, John W Belmont, Jeffrey J Kim, Christina Y Miyake, James R Lupski, Seema R Lalani

Faculty, Staff and Student Publications

BACKGROUND: Wolff-Parkinson-White (WPW) syndrome is a relatively common arrhythmia affecting ~1-3/1,000 individuals. Mutations in PRKAG2 have been described in rare patients in association with cardiomyopathy. However, the genetic basis of WPW in individuals with a structurally normal heart remains poorly understood. Sudden death due to atrial fibrillation (AF) can also occur in these individuals. Several studies have indicated that despite ablation of an accessory pathway, the risk of AF remains high in patients compared to general population.

METHODS: We applied exome sequencing in 305 subjects, including 65 trios, 80 singletons, and 6 multiple affected families. We used de novo analysis, …