The Emerging Spectrum of Allelic Variation in Schizophrenia
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Concentrative Nucleoside Transporter 3 As a Prognostic Indicator for Favorable Outcome of T(8;21)-Positive Acute Myeloid Leukemi
488 ONCOLOGY REPORTS 34: 488-494, 2015 Concentrative nucleoside transporter 3 as a prognostic indicator for favorable outcome of t(8;21)-positive acute myeloid leukemia patients after cytarabine-based chemotherapy JU HAN SONG1, KYUNG-MIN CHO1, HYEOUNG-JOON KIM2, YEO-KYEOUNG KIM2, NAN YOUNG KIM2, HEE-JE KIM3, TAE-Hyang LEE3, SEUNG YONG Hwang4 and TAE SUNG KIM1 1Division of Life Sciences, School of Life Sciences and Biotechnology, Korea University, Seoul; 2Genome Research Center for Hematopoietic Diseases, Chonnam National University Hwasun Hospital, Hwasun; 3Catholic Blood and Marrow Transplantation Center, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul; 4Division of Molecular and Life Science and GenoCheck Co., Ltd., Hanyang University, Ansan, Republic of Korea Received January 20, 2015; Accepted March 18, 2015 DOI: 10.3892/or.2015.3959 Abstract. Although acute myeloid leukemia (AML) exhibits Introduction diverse responses to chemotherapy, patients harboring the t(8;21) translocation are part of a favorable risk group. Acute myeloid leukemia (AML) is a highly heterogeneous However, the reason why this subgroup is more responsive hematologic malignancy that displays diverse responses to cytarabine-based therapy has not been elucidated. In the to chemotherapy. Although a number of clinical factors present study, we analyzed expression levels of cytarabine affect treatment outcomes, the cytogenetic features of AML metabolism-related genes in patients diagnosed with AML are generally accepted as strong predictors of therapeutic with or without t(8;21) and investigated their correlation with response (1). Pediatric and adult patients carrying the t(8;21) clinical outcomes after cytarabine-based therapy. Among the chromosomal translocation, which is one of the most frequent 8 genes studied, expression of the concentrative nucleoside AML subtypes, are part of a favorable risk group (2). -
Imaging the Genetics of Brain Structure and Function Biological Psychology
Biological Psychology 79 (2008) 1–8 Contents lists available at ScienceDirect Biological Psychology journal homepage: www.elsevier.com/locate/biopsycho Editorial Imaging the genetics of brain structure and function ARTICLE INFO ABSTRACT Article history: Imaging genetics combines brain imaging and genetics to detect genetic variation in brain structure and Available online 11 April 2008 function related to behavioral traits, including psychiatric endpoints, cognition, and affective regulation. This special issue features extensive reviews of the current state-of-the-art of the field and adds new findings from twin and candidate gene studies on functional MRI. Here we present a brief overview and discuss a number of desirable future developments which include more specific a priori hypotheses, more standardization of MRI measurements within and across laboratories, and larger sample sizes that allows testing of multiple genes and their interactions up to a scale that allows genetic whole genome association studies. Based on the overall tenet of the contributions to this special issue we predict that imaging genetics will increasingly impact on the classification systems for psychiatric disorders and the early detection and treatment of vulnerable individuals. ß 2008 Elsevier B.V. All rights reserved. Biological Psychology, quite literally, deals with the connection 1. Imaging genetics between the body and the mind. In the past two decades two specific instances of body-mind connections have captured the What exactly is imaging genetics? In the -
Mammalian 5€²-Nucleotidases*
THE JOURNAL OF BIOLOGICAL CHEMISTRY Vol. 278, No. 47, Issue of November 21, pp. 46195–46198, 2003 Minireview © 2003 by The American Society for Biochemistry and Molecular Biology, Inc. Printed in U.S.A. -Mammalian 5-Nucleotidases* residues the best alignment was between the two deoxynucle otidases and cN-III (10). Two 5Ј-nucleotidases, cN-II and cN- III, exhibit phosphotransferase activity (for reviews see Refs. Published, JBC Papers in Press, August 28, 2003, DOI 10.1074/jbc.R300032200 14 and 15) possibly because of higher stability of the phos- phoenzyme intermediate or faster exchange of the nucleoside Vera Bianchi‡§ and Jozef Spychala¶ product with the nucleoside acceptor. From the ‡Department of Biology, University of Padova, The active site of E. coli 5Ј-nucleotidase, the paradigm for I-35131 Padova, Italy and the ¶Lineberger eN, contains two zinc ions and the catalytic dyad Asp-His (11). Comprehensive Cancer Center, University of North No phosphoenzyme intermediate is formed during catalysis, Carolina, Chapel Hill, North Carolina 27599-7295 but a water molecule performs the nucleophilic attack on the phosphate (16). Nucleoside monophosphate phosphohydrolases or 5Ј-nucle- otidases (members of EC 3.1.3.5 and EC 3.1.3.6) dephosphoryl- Properties, Detection, and Inhibition ate non-cyclic nucleoside monophosphates to nucleosides and of 5-Nucleotidases inorganic phosphate. Seven human 5Ј-nucleotidases with dif- All 5Ј-nucleotidases have relatively broad substrate specific- ferent subcellular localization have been cloned (Table I). Se- ities. In agreement with the structural information on the quence comparisons show high homology only between cytoso- active sites (10, 11), all family members except eN are abso- lic 5Ј-nucleotidase IA (cN-IA)1 and B and between cytosolic lutely dependent on magnesium for activity. -
Sparse Deep Neural Networks on Imaging Genetics for Schizophrenia Case-Control Classification
medRxiv preprint doi: https://doi.org/10.1101/2020.06.11.20128975; this version posted June 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Sparse Deep Neural Networks on Imaging Genetics for Schizophrenia Case-Control Classification Jiayu Chen1,*, Xiang Li2,*, Vince D. Calhoun1,2,3, Jessica A. Turner1,3, Theo G. M. van Erp4,5, Lei Wang6, Ole A. Andreassen7, Ingrid Agartz7,8,9, Lars T. Westlye7,10 , Erik Jönsson7,9, Judith M. Ford11,12, Daniel H. Mathalon11,12, Fabio Macciardi4, Daniel S. O’Leary13, Jingyu Liu1,2, †, Shihao Ji2, † 1Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA; 2Department of Computer Science, Georgia State University, Atlanta, GA, USA; 3Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA; 4Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, Irvine, CA, USA; 5Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA; 6Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, USA; 7Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, University -
Imaging Genetics Approach to Parkinson's Disease and Its
www.nature.com/scientificreports OPEN Imaging genetics approach to Parkinson’s disease and its correlation with clinical score Received: 07 November 2016 Mansu Kim1,2, Jonghoon Kim1,2, Seung-Hak Lee1,2 & Hyunjin Park2,3 Accepted: 24 March 2017 Parkinson’s disease (PD) is a progressive neurodegenerative disorder associated with both underlying Published: 21 April 2017 genetic factors and neuroimaging findings. Existing neuroimaging studies related to the genome in PD have mostly focused on certain candidate genes. The aim of our study was to construct a linear regression model using both genetic and neuroimaging features to better predict clinical scores compared to conventional approaches. We obtained neuroimaging and DNA genotyping data from a research database. Connectivity analysis was applied to identify neuroimaging features that could differentiate between healthy control (HC) and PD groups. A joint analysis of genetic and imaging information known as imaging genetics was applied to investigate genetic variants. We then compared the utility of combining different genetic variants and neuroimaging features for predicting the Movement Disorder Society-sponsored unified Parkinson’s disease rating scale (MDS-UPDRS) in a regression framework. The associative cortex, motor cortex, thalamus, and pallidum showed significantly different connectivity between the HC and PD groups. Imaging genetics analysis identified PARK2, PARK7, HtrA2, GIGYRF2, and SNCA as genetic variants that are significantly associated with imaging phenotypes. A linear regression model combining genetic and neuroimaging features predicted the MDS-UPDRS with lower error and higher correlation with the actual MDS-UPDRS compared to other models using only genetic or neuroimaging information alone. Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by bradykinesia, resting trem- ors, rigidity, and difficulty with voluntary movement1. -
Molecular Characterization of Acute Myeloid Leukemia by Next Generation Sequencing: Identification of Novel Biomarkers and Targets of Personalized Therapies
Alma Mater Studiorum – Università di Bologna Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale Dottorato di Ricerca in Oncologia, Ematologia e Patologia XXX Ciclo Settore Scientifico Disciplinare: MED/15 Settore Concorsuale:06/D3 Molecular characterization of acute myeloid leukemia by Next Generation Sequencing: identification of novel biomarkers and targets of personalized therapies Presentata da: Antonella Padella Coordinatore Prof. Pier-Luigi Lollini Supervisore: Prof. Giovanni Martinelli Esame finale anno 2018 Abstract Acute myeloid leukemia (AML) is a hematopoietic neoplasm that affects myeloid progenitor cells and it is one of the malignancies best studied by next generation sequencing (NGS), showing a highly heterogeneous genetic background. The aim of the study was to characterize the molecular landscape of 2 subgroups of AML patients carrying either chromosomal number alterations (i.e. aneuploidy) or rare fusion genes. We performed whole exome sequencing and we integrated the mutational data with transcriptomic and copy number analysis. We identified the cell cycle, the protein degradation, response to reactive oxygen species, energy metabolism and biosynthetic process as the pathways mostly targeted by alterations in aneuploid AML. Moreover, we identified a 3-gene expression signature including RAD50, PLK1 and CDC20 that characterize this subgroup. Taking advantage of RNA sequencing we aimed at the discovery of novel and rare gene fusions. We detected 9 rare chimeric transcripts, of which partner genes were transcription factors (ZEB2, BCL11B and MAFK) or tumor suppressors (SAV1 and PUF60) rarely translocated across cancer types. Moreover, we detected cryptic events hiding the loss of NF1 and WT1, two recurrently altered genes in AML. Finally, we explored the oncogenic potential of the ZEB2-BCL11B fusion, which revealed no transforming ability in vitro. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
CHIMGEN: a Chinese Imaging Genetics Cohort to Enhance Cross-Ethnic and Cross-Geographic Brain Research
Molecular Psychiatry (2020) 25:517–529 https://doi.org/10.1038/s41380-019-0627-6 PERSPECTIVE CHIMGEN: a Chinese imaging genetics cohort to enhance cross- ethnic and cross-geographic brain research 1 1 2 3,4 5 6 7 Qiang Xu ● Lining Guo ● Jingliang Cheng ● Meiyun Wang ● Zuojun Geng ● Wenzhen Zhu ● Bing Zhang ● 8,9 10 11 12 13 14 15,16 Weihua Liao ● Shijun Qiu ● Hui Zhang ● Xiaojun Xu ● Yongqiang Yu ● Bo Gao ● Tong Han ● 17 18 1 1 1 19 20 Zhenwei Yao ● Guangbin Cui ● Feng Liu ● Wen Qin ● Quan Zhang ● Mulin Jun Li ● Meng Liang ● 21 22 23 24 25,26 27 28 Feng Chen ● Junfang Xian ● Jiance Li ● Jing Zhang ● Xi-Nian Zuo ● Dawei Wang ● Wen Shen ● 29 30 31,32 33,34 35,36 37 38 Yanwei Miao ● Fei Yuan ● Su Lui ● Xiaochu Zhang ● Kai Xu ● Long Jiang Zhang ● Zhaoxiang Ye ● 1,39 Chunshui Yu ● for the CHIMGEN Consortium Received: 26 September 2018 / Revised: 21 November 2019 / Accepted: 27 November 2019 / Published online: 11 December 2019 © The Author(s) 2019. This article is published with open access Abstract The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral 1234567890();,: 1234567890();,: phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18–30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. -
Introduction to Imaging Genetics Half Day Morning Course / 8:00-12:00
Introduction to Imaging Genetics Half Day Morning Course / 8:00-12:00 Organizers: Jason Stein, PhD, University of North Carolina at Chapel Hill, United States This course will introduce the fundamentals of “Imaging Genetics,” the process of modeling and understanding how genetic variation influences the structure and function of the human brain as measured through brain imaging. The course begins with a brief history of imaging genetics, including discussion on replicability and significance thresholds. Then, we will review recent findings in neuropsychiatric disease risk, what neuroimaging genetics can learn from neuropsychiatric genetics, and how neuroimaging genetics can be used to explain missing mechanisms in neuropsychiatric genetics. We will cover datasets and methods for conducting common and rare variant associations, as well as bioinformatic tools to interpret findings in the context of gene regulation. Overall this course will provide the neuroimager who is not familiar with genetics techniques an understanding of the current state genetics field when exploring neuroimaging phenotypes. Course Schedule: 8:00-8:45 A brief history of imaging genetics Jason Stein, PhD, University of North Carolina at Chapel Hill, United States 8:45-9:30 The genetic influences on neuropsychiatric disease risk Sven Cichon, Dr. rer. nat., Universitat Basel, Switzerland 9:30-10:15 The effect of common genetic variation on human brain structure Paul Thompson, Imaging Genetics Center, Keck School of Medicine of University of Southern California, United States 10:15-10:30 Break 10:30-11:15 The effect of rare variation on human brain structure Carrie Bearden, University of California, Los Angeles, United States 11:15-12:00 Connecting genetic variation to gene regulation Bernard Ng, PhD, University of British Columbia, Canada . -
Functional Analogy in Human Metabolism: Enzymes with Different Biological Roles Or Functional Redundancy?
GBE Functional Analogy in Human Metabolism: Enzymes with Different Biological Roles or Functional Redundancy? Rafael Mina Piergiorge1, Antonio Basılio de Miranda2, Ana Carolina Guimaraes~ 1,*, and Marcos Catanho1 1Laboratorio de Genoˆ mica Funcional e Bioinformatica, Fiocruz, Instituto Oswaldo Cruz, Manguinhos, Rio de Janeiro, Brazil 2Laboratorio de Biologia Computacional e Sistemas, Fiocruz, Instituto Oswaldo Cruz, Manguinhos, Rio de Janeiro, Brazil *Corresponding author: E-mail: carolg@fiocruz.br. Accepted: July 4, 2017 Abstract Since enzymes catalyze almost all chemical reactions that occur in living organisms, it is crucial that genes encoding such activities are correctly identified and functionally characterized. Several studies suggest that the fraction of enzymatic activities in which multiple events of independent origin have taken place during evolution is substantial. However, this topic is still poorly explored, and a comprehensive investigation of the occurrence, distribution, and implications of these events has not been done so far. Fundamental questions, such as how analogous enzymes originate, why so many events of independent origin have apparently occurred during evolution, and what are the reasons for the coexistence in the same organism of distinct enzymatic forms catalyzing the same reaction, remain unanswered. Also, several isofunctional enzymes are still not recognized as nonhomologous, even with substantial evidence indicating different evolutionary histories. In this work, we begin to investigate the biological significance of the cooccur- rence of nonhomologous isofunctional enzymes in human metabolism, characterizing functional analogous enzymes identified in metabolic pathways annotated in the human genome. Our hypothesis is that the coexistence of multiple enzymatic forms might not be interpreted as functional redundancy. Instead, these enzymatic forms may be implicated in distinct (and probably relevant) biological roles. -
Effect of Tenofovir on Nucleotidases and Cytokines in HIV-1 Target Cells
Effect of Tenofovir on Nucleotidases and Cytokines in HIV-1 Target Cells Nabanita Biswas*, Marta Rodriguez-Garcia, Sarah G. Crist, Zheng Shen, Jack E. Bodwell, John V. Fahey, Charles R. Wira Department of Physiology and Neurobiology, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, United States of America Abstract Tenofovir (TFV) has been widely used for pre-exposure prophylaxis of HIV-1 infection with mixed results. While the use of TFV in uninfected individuals for prevention of HIV-1 acquisition is actively being investigated, the possible consequences of TFV exposure for the HIV-target cells and the mucosal microenvironment are unknown. In the current study, we evaluated the effects of TFV treatment on blood-derived CD4+ T cells, monocyte-derived macrophages and dendritic cells (DC). Purified HIV-target cells were treated with different concentrations of TFV (0.001-1.0 mg/ml) for 2 to 24hr. RNA was isolated and RT-PCR was performed to compare the levels of mRNA expression of nucleotidases and pro-inflammatory cytokine genes (MIP3α, IL-8 and TNFα) in the presence or absence of TFV. We found that TFV increases 5’-ecto-nucleotidase (NT5E) and inhibits mitochondrial nucleotidase (NT5M) gene expression and increases 5’ nucleotidase activity in macrophages. We also observed that TFV stimulates the expression and secretion of IL-8 by macrophages, DC, and activated CD4+ T cells and increases the expression and secretion of MIP3α by macrophages. In contrast, TFV had no effect on TNFα secretion from macrophages, DC and CD4+ T cells. Our results demonstrate that TFV alters innate immune responses in HIV-target cells with potential implications for increased inflammation at mucosal surfaces. -
The Use of Phosphoproteomic Data to Identify Altered Kinases and Signaling Pathways in Cancer
The use of phosphoproteomic data to identify altered kinases and signaling pathways in cancer By Sara Renee Savage Thesis Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE in Biomedical Informatics August 10, 2018 Nashville, Tennessee Approved: Bing Zhang, Ph.D. Carlos Lopez, Ph.D. Qi Liu, Ph.D. ACKNOWLEDGEMENTS The work presented in this thesis would not have been possible without the funding provided by the NLM training grant (T15-LM007450) and the support of the Biomedical Informatics department at Vanderbilt. I am particularly indebted to Rischelle Jenkins, who helped me solve all administrative issues. Furthermore, this work is the result of a collaboration between all members of the Zhang lab and the larger CPTAC consortium. I would like to thank the other CPTAC centers for processing the data, and Chen Huang and Suhas Vasaikar in the Zhang lab for analyzing the colon cancer copy number and proteomic data, respectively. All members of the Zhang lab have been extremely helpful in answering any questions I had and offering suggestions on my work. Finally, I would like to acknowledge my mentor, Bing Zhang. I am extremely grateful for his guidance and for giving me the opportunity to work on these projects. ii TABLE OF CONTENTS Page ACKNOWLEDGEMENTS ................................................................................................ ii LIST OF TABLES............................................................................................................