Changes in Brain Transcripts Related to Alzheimer's Disease in a Model
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Genetic Mutations and Mechanisms in Dilated Cardiomyopathy
Genetic mutations and mechanisms in dilated cardiomyopathy Elizabeth M. McNally, … , Jessica R. Golbus, Megan J. Puckelwartz J Clin Invest. 2013;123(1):19-26. https://doi.org/10.1172/JCI62862. Review Series Genetic mutations account for a significant percentage of cardiomyopathies, which are a leading cause of congestive heart failure. In hypertrophic cardiomyopathy (HCM), cardiac output is limited by the thickened myocardium through impaired filling and outflow. Mutations in the genes encoding the thick filament components myosin heavy chain and myosin binding protein C (MYH7 and MYBPC3) together explain 75% of inherited HCMs, leading to the observation that HCM is a disease of the sarcomere. Many mutations are “private” or rare variants, often unique to families. In contrast, dilated cardiomyopathy (DCM) is far more genetically heterogeneous, with mutations in genes encoding cytoskeletal, nucleoskeletal, mitochondrial, and calcium-handling proteins. DCM is characterized by enlarged ventricular dimensions and impaired systolic and diastolic function. Private mutations account for most DCMs, with few hotspots or recurring mutations. More than 50 single genes are linked to inherited DCM, including many genes that also link to HCM. Relatively few clinical clues guide the diagnosis of inherited DCM, but emerging evidence supports the use of genetic testing to identify those patients at risk for faster disease progression, congestive heart failure, and arrhythmia. Find the latest version: https://jci.me/62862/pdf Review series Genetic mutations and mechanisms in dilated cardiomyopathy Elizabeth M. McNally, Jessica R. Golbus, and Megan J. Puckelwartz Department of Human Genetics, University of Chicago, Chicago, Illinois, USA. Genetic mutations account for a significant percentage of cardiomyopathies, which are a leading cause of conges- tive heart failure. -
343747488.Pdf
Washington University School of Medicine Digital Commons@Becker Open Access Publications 6-1-2020 Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 Simon Hsu Anna A Pimenova Kimberly Hayes Juan A Villa Matthew J Rosene See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Authors Simon Hsu, Anna A Pimenova, Kimberly Hayes, Juan A Villa, Matthew J Rosene, Madhavi Jere, Alison M Goate, and Celeste M Karch Neurobiology of Disease 139 (2020) 104817 Contents lists available at ScienceDirect Neurobiology of Disease journal homepage: www.elsevier.com/locate/ynbdi Systematic validation of variants of unknown significance in APP, PSEN1 T and PSEN2 Simon Hsua, Anna A. Pimenovab, Kimberly Hayesa, Juan A. Villaa, Matthew J. Rosenea, ⁎ Madhavi Jerea, Alison M. Goateb, Celeste M. Karcha, a Department of Psychiatry, Washington University School of Medicine, 425 S Euclid Avenue, St Louis, MO 63110, USA b Department of Neuroscience, Mount Sinai School of Medicine, New York, NY, USA ARTICLE INFO ABSTRACT Keywords: Alzheimer's disease (AD) is a neurodegenerative disease that is clinically characterized by progressive cognitive APP decline. More than 200 pathogenic mutations have been identified in amyloid-β precursor protein (APP), presenilin PSEN1 1 (PSEN1) and presenilin 2 (PSEN2). Additionally, common and rare variants occur within APP, PSEN1, and PSEN2 PSEN2 that may be risk factors, protective factors, or benign, non-pathogenic polymorphisms. Yet, to date, no Alzheimer's disease single study has carefully examined the effect of all of the variants of unknown significance reported in APP, Cell-based assays PSEN1 and PSEN2 on Aβ isoform levels in vitro. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Detecting and Tracking Early Neurodegeneration in Familial
University College London Institute of Neurology Detecting and tracking early neurodegeneration in familial Alzheimer’s disease A thesis submitted for the degree of Doctor of Philosophy Philip S.J. Weston 1 For Emma and Evie 2 Declaration of authorship and originality I, Philip S.J. Weston, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Philip S.J. Weston 3 Acknowledgements Above all I would like to thank the FAD family members who so kindly donated their time and energy to participate in research. Without their effort and dedication none of the studies reported in this thesis would have been possible. I am grateful to the Medical Research Council for funding my Clinical Research Training Fellowship, and to the National Institute of Health Research, which provided valuable funds for other aspects of the study. My primary supervisor, Nick Fox, has been a constant source of support, inspiration, and motivation. I am grateful to Nick for entrusting me with such a valuable cohort of special individuals, and for allowing me to oversee the conduct of the studies presented here. I also thank my secondary supervisor Jon Schott for providing additional useful advice and support throughout. Finally I would like to thank my co-workers, collaborators and colleagues. On the two imaging projects: Manja Lehman, Natalie Ryan, Marc Modat, Ivor Simpson, Nico Toussaint, and Seb Ourselin. On the serum neurofilament light project: Henrik Zetterberg, Kaj Blennow, Simon Mead, and Ron Druyeh. On the accelerated long-term forgetting study: Adam Zeman, Chris Butler, Yuying Liang, Seb Crutch, and Susie Henley. -
Genetic Testing for Familial Alzheimer's Disease
Corporate Medical Policy Genetic Testing for Familial Alzheimer’s Disease AHS – M2038 File Name: genetic_testing_for_familial_alzheimers_disease Origination: 1/2019 Last CAP Review: 10/2020 Next CAP Review: 10/2021 Last Review: 10/2020 Description of Procedure or Service Alzheimer disease (AD) is a neurodegenerative disease defined by a gradual decline in memory, cognitive functions, gross atrophy of the brain, and an accumulation of extracellular amyloid plaques and intracellular neurofibrillary tangles (Karch, Cruchaga, & Goate, 2014). Familial Alzheimer disease (FAD) is a rare, inherited form of AD. FAD has a much earlier onset than other forms of Alzheimer disease with symptoms developing in individuals in their thirties or forties. Related Policies General Genetic Testing, Germline Disorders AHS – M2145 General Genetic Testing, Somatic Disorders AHS – M2146 ***Note: This Medical Policy is complex and technical. For questions concerning the technical language and/or specific clinical indications for its use, please consult your physician. Policy BCBSNC will provide coverage for genetic testing for familial Alzheimer disease when it is determined the medical criteria or reimbursement guidelines below are met. Benefits Application This medical policy relates only to the services or supplies described herein. Please refer to the Member's Benefit Booklet for availability of benefits. Member's benefits may vary according to benefit design; therefore member benefit language should be reviewed before applying the terms of this medical policy. -
Methodology Report ENU Mutagenesis Screen to Establish Motor Phenotypes in Wild-Type Mice and Modifiers of a Pre-Existing Motor Phenotype in Tau Mutant Mice
Hindawi Publishing Corporation Journal of Biomedicine and Biotechnology Volume 2011, Article ID 130947, 11 pages doi:10.1155/2011/130947 Methodology Report ENU Mutagenesis Screen to Establish Motor Phenotypes in Wild-Type Mice and Modifiers of a Pre-Existing Motor Phenotype in Tau Mutant Mice Xin Liu,1 Michael Dobbie,2 Rob Tunningley,2 Belinda Whittle,2 Yafei Zhang, 2 Lars M. Ittner,1 and Jurgen¨ Gotz¨ 1 1 Alzheimer’s and Parkinson’s Disease Laboratory, Brain & Mind Research Institute, University of Sydney, 100 Mallett Street, Camperdown, NSW 2050, Australia 2 Australian Phenomics Facility, Australian National University, 117 Garran Road, Acton, ACT 0200, Australia Correspondence should be addressed to Jurgen¨ Gotz,¨ [email protected] Received 24 August 2011; Accepted 4 November 2011 Academic Editor: Kurt Burki¨ Copyright © 2011 Xin Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Modifier screening is a powerful genetic tool. While not widely used in the vertebrate system, we applied these tools to transgenic mouse strains that recapitulate key aspects of Alzheimer’s disease (AD), such as tau-expressing mice. These are characterized by a robust pathology including both motor and memory impairment. The phenotype can be modulated by ENU mutagenesis, which results in novel mutant mouse strains and allows identifying the underlying gene/mutation. Here we discuss -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Comparative Analysis of Alzheimer's Disease Knock-In Model Brain
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.16.431539; this version posted February 17, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Title: Comparative analysis of Alzheimer’s disease knock-in model brain transcriptomes implies changes to energy metabolism as a causative pathogenic stress Authors: Karissa Barthelson1*, Morgan Newman1, Michael Lardelli1 Affiliations: 1Alzheimer’s Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia Author list footnotes: *Corresponding author Corresponding author e-mail address: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.02.16.431539; this version posted February 17, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Summary Energy production is the most fundamentally important cellular activity supporting all other functions, particularly in highly active organs such as brains, Here we summarise transcriptome analyses of young adult (pre-disease) brains from a collection of eleven early onset familial Alzheimer’s disease (EOfAD)-like and non-EOfAD-like mutations in three zebrafish genes. The one cellular activity consistently predicted as affected by only the EOfAD-like mutations is oxidative phosphorylation that produces most of the brain’s energy. -
Insurance and Advance Pay Test Requisition
Insurance and Advance Pay Test Requisition (2021) For Specimen Collection Service, Please Fax this Test Requisition to 1.610.271.6085 Client Services is available Monday through Friday from 8:30 AM to 9:00 PM EST at 1.800.394.4493, option 2 Patient Information Patient Name Patient ID# (if available) Date of Birth Sex designated at birth: 9 Male 9 Female Street address City, State, Zip Mobile phone #1 Other Phone #2 Patient email Language spoken if other than English Test and Specimen Information Consult test list for test code and name Test Code: Test Name: Test Code: Test Name: 9 Check if more than 2 tests are ordered. Additional tests should be checked off within the test list ICD-10 Codes (required for billing insurance): Clinical diagnosis: Age at Initial Presentation: Ancestral Background (check all that apply): 9 African 9 Asian: East 9 Asian: Southeast 9 Central/South American 9 Hispanic 9 Native American 9 Ashkenazi Jewish 9 Asian: Indian 9 Caribbean 9 European 9 Middle Eastern 9 Pacific Islander Other: Indications for genetic testing (please check one): 9 Diagnostic (symptomatic) 9 Predictive (asymptomatic) 9 Prenatal* 9 Carrier 9 Family testing/single site Relationship to Proband: If performed at Athena, provide relative’s accession # . If performed at another lab, a copy of the relative’s report is required. Please attach detailed medical records and family history information Specimen Type: Date sample obtained: __________ /__________ /__________ 9 Whole Blood 9 Serum 9 CSF 9 Muscle 9 CVS: Cultured 9 Amniotic Fluid: Cultured 9 Saliva (Not available for all tests) 9 DNA** - tissue source: Concentration ug/ml Was DNA extracted at a CLIA-certified laboratory or a laboratory meeting equivalent requirements (as determined by CAP and/or CMS)? 9 Yes 9 No 9 Other*: If not collected same day as shipped, how was sample stored? 9 Room temp 9 Refrigerated 9 Frozen (-20) 9 Frozen (-80) History of blood transfusion? 9 Yes 9 No Most recent transfusion: __________ /__________ /__________ *Please contact us at 1.800.394.4493, option 2 prior to sending specimens. -
Supp Table 6.Pdf
Supplementary Table 6. Processes associated to the 2037 SCL candidate target genes ID Symbol Entrez Gene Name Process NM_178114 AMIGO2 adhesion molecule with Ig-like domain 2 adhesion NM_033474 ARVCF armadillo repeat gene deletes in velocardiofacial syndrome adhesion NM_027060 BTBD9 BTB (POZ) domain containing 9 adhesion NM_001039149 CD226 CD226 molecule adhesion NM_010581 CD47 CD47 molecule adhesion NM_023370 CDH23 cadherin-like 23 adhesion NM_207298 CERCAM cerebral endothelial cell adhesion molecule adhesion NM_021719 CLDN15 claudin 15 adhesion NM_009902 CLDN3 claudin 3 adhesion NM_008779 CNTN3 contactin 3 (plasmacytoma associated) adhesion NM_015734 COL5A1 collagen, type V, alpha 1 adhesion NM_007803 CTTN cortactin adhesion NM_009142 CX3CL1 chemokine (C-X3-C motif) ligand 1 adhesion NM_031174 DSCAM Down syndrome cell adhesion molecule adhesion NM_145158 EMILIN2 elastin microfibril interfacer 2 adhesion NM_001081286 FAT1 FAT tumor suppressor homolog 1 (Drosophila) adhesion NM_001080814 FAT3 FAT tumor suppressor homolog 3 (Drosophila) adhesion NM_153795 FERMT3 fermitin family homolog 3 (Drosophila) adhesion NM_010494 ICAM2 intercellular adhesion molecule 2 adhesion NM_023892 ICAM4 (includes EG:3386) intercellular adhesion molecule 4 (Landsteiner-Wiener blood group)adhesion NM_001001979 MEGF10 multiple EGF-like-domains 10 adhesion NM_172522 MEGF11 multiple EGF-like-domains 11 adhesion NM_010739 MUC13 mucin 13, cell surface associated adhesion NM_013610 NINJ1 ninjurin 1 adhesion NM_016718 NINJ2 ninjurin 2 adhesion NM_172932 NLGN3 neuroligin -
Nanomedicine for Neurodegenerative Disorders: Focus on Alzheimer's
International Journal of Molecular Sciences Review Nanomedicine for Neurodegenerative Disorders: Focus on Alzheimer’s and Parkinson’s Diseases Keelan Jagaran and Moganavelli Singh * Nano-Gene and Drug Delivery Group, Discipline of Biochemistry, University of KwaZulu-Natal, Private Bag X54001, Durban 4000, South Africa; [email protected] * Correspondence: [email protected]; Tel.: +27-31-260-7170 Abstract: Neurodegenerative disorders involve the slow and gradual degeneration of axons and neurons in the central nervous system (CNS), resulting in abnormalities in cellular function and eventual cellular demise. Patients with these disorders succumb to the high medical costs and the disruption of their normal lives. Current therapeutics employed for treating these diseases are deemed palliative. Hence, a treatment strategy that targets the disease’s cause, not just the symptoms exhibited, is desired. The synergistic use of nanomedicine and gene therapy to effectively target the causative mutated gene/s in the CNS disease progression could provide the much-needed impetus in this battle against these diseases. This review focuses on Parkinson’s and Alzheimer’s diseases, the gene/s and proteins responsible for the damage and death of neurons, and the importance of nanomedicine as a potential treatment strategy. Multiple genes were identified in this regard, each presenting with various mutations. Hence, genome-wide sequencing is essential for specific treatment in patients. While a cure is yet to be achieved, genomic studies form the basis for creating a highly efficacious nanotherapeutic that can eradicate these dreaded diseases. Thus, nanomedicine can lead the way in helping millions of people worldwide to eventually lead a better life. -
The Untold Stories of the Speech Gene, the FOXP2 Cancer Gene
www.Genes&Cancer.com Genes & Cancer, Vol. 9 (1-2), January 2018 The untold stories of the speech gene, the FOXP2 cancer gene Maria Jesus Herrero1,* and Yorick Gitton2,* 1 Center for Neuroscience Research, Children’s National Medical Center, NW, Washington, DC, USA 2 Sorbonne University, INSERM, CNRS, Vision Institute Research Center, Paris, France * Both authors contributed equally to this work Correspondence to: Yorick Gitton, email: [email protected] Keywords: FOXP2 factor, oncogene, cancer, prognosis, language Received: March 01, 2018 Accepted: April 02, 2018 Published: April 18, 2018 Copyright: Herrero and Gitton et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT FOXP2 encodes a transcription factor involved in speech and language acquisition. Growing evidence now suggests that dysregulated FOXP2 activity may also be instrumental in human oncogenesis, along the lines of other cardinal developmental transcription factors such as DLX5 and DLX6 [1–4]. Several FOXP family members are directly involved during cancer initiation, maintenance and progression in the adult [5–8]. This may comprise either a pro- oncogenic activity or a deficient tumor-suppressor role, depending upon cell types and associated signaling pathways. While FOXP2 is expressed in numerous cell types, its expression has been found to be down-regulated in breast cancer [9], hepatocellular carcinoma [8] and gastric cancer biopsies [10]. Conversely, overexpressed FOXP2 has been reported in multiple myelomas, MGUS (Monoclonal Gammopathy of Undetermined Significance), several subtypes of lymphomas [5,11], as well as in neuroblastomas [12] and ERG fusion-negative prostate cancers [13].