Dissecting the Genetic Relationship Between Cardiovascular Risk Factors and Alzheimer's Disease
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A Clinicopathological and Molecular Genetic Analysis of Low-Grade Glioma in Adults
A CLINICOPATHOLOGICAL AND MOLECULAR GENETIC ANALYSIS OF LOW-GRADE GLIOMA IN ADULTS Presented by ANUSHREE SINGH MSc A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy Brain Tumour Research Centre Research Institute in Healthcare Sciences Faculty of Science and Engineering University of Wolverhampton November 2014 i DECLARATION This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of Anushree Singh to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature: Anushree Date: 30th November 2014 ii ABSTRACT The aim of the study was to identify molecular markers that can determine progression of low grade glioma. This was done using various approaches such as IDH1 and IDH2 mutation analysis, MGMT methylation analysis, copy number analysis using array comparative genomic hybridisation and identification of differentially expressed miRNAs using miRNA microarray analysis. IDH1 mutation was present at a frequency of 71% in low grade glioma and was identified as an independent marker for improved OS in a multivariate analysis, which confirms the previous findings in low grade glioma studies. -
Greg's Awesome Thesis
Analysis of alignment error and sitewise constraint in mammalian comparative genomics Gregory Jordan European Bioinformatics Institute University of Cambridge A dissertation submitted for the degree of Doctor of Philosophy November 30, 2011 To my parents, who kept us thinking and playing This dissertation is the result of my own work and includes nothing which is the out- come of work done in collaboration except where specifically indicated in the text and acknowledgements. This dissertation is not substantially the same as any I have submitted for a degree, diploma or other qualification at any other university, and no part has already been, or is currently being submitted for any degree, diploma or other qualification. This dissertation does not exceed the specified length limit of 60,000 words as defined by the Biology Degree Committee. November 30, 2011 Gregory Jordan ii Analysis of alignment error and sitewise constraint in mammalian comparative genomics Summary Gregory Jordan November 30, 2011 Darwin College Insight into the evolution of protein-coding genes can be gained from the use of phylogenetic codon models. Recently sequenced mammalian genomes and powerful analysis methods developed over the past decade provide the potential to globally measure the impact of natural selection on pro- tein sequences at a fine scale. The detection of positive selection in particular is of great interest, with relevance to the study of host-parasite conflicts, immune system evolution and adaptive dif- ferences between species. This thesis examines the performance of methods for detecting positive selection first with a series of simulation experiments, and then with two empirical studies in mammals and primates. -
Dissecting the Genetic Relationship Between
VU Research Portal Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer's disease Broce, Iris J; Tan, Chin Hong; Fan, Chun Chieh; Jansen, Iris; Savage, Jeanne E; Witoelar, Aree; Wen, Natalie; Hess, Christopher P; Dillon, William P; Glastonbury, Christine M; Glymour, Maria; Yokoyama, Jennifer S; Elahi, Fanny M; Rabinovici, Gil D; Miller, Bruce L; Mormino, Elizabeth C; Sperling, Reisa A; Bennett, David A; McEvoy, Linda K; Brewer, James B published in Acta Neuropathologica 2019 DOI (link to publisher) 10.1007/s00401-018-1928-6 document version Publisher's PDF, also known as Version of record document license Article 25fa Dutch Copyright Act Link to publication in VU Research Portal citation for published version (APA) Broce, I. J., Tan, C. H., Fan, C. C., Jansen, I., Savage, J. E., Witoelar, A., Wen, N., Hess, C. P., Dillon, W. P., Glastonbury, C. M., Glymour, M., Yokoyama, J. S., Elahi, F. M., Rabinovici, G. D., Miller, B. L., Mormino, E. C., Sperling, R. A., Bennett, D. A., McEvoy, L. K., ... Desikan, R. S. (2019). Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer's disease. Acta Neuropathologica, 137, 209-226. https://doi.org/10.1007/s00401-018-1928-6 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. -
Human Lectins, Their Carbohydrate Affinities and Where to Find Them
biomolecules Review Human Lectins, Their Carbohydrate Affinities and Where to Review HumanFind Them Lectins, Their Carbohydrate Affinities and Where to FindCláudia ThemD. Raposo 1,*, André B. Canelas 2 and M. Teresa Barros 1 1, 2 1 Cláudia D. Raposo * , Andr1 é LAQVB. Canelas‐Requimte,and Department M. Teresa of Chemistry, Barros NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829‐516 Caparica, Portugal; [email protected] 12 GlanbiaLAQV-Requimte,‐AgriChemWhey, Department Lisheen of Chemistry, Mine, Killoran, NOVA Moyne, School E41 of ScienceR622 Co. and Tipperary, Technology, Ireland; canelas‐ [email protected] NOVA de Lisboa, 2829-516 Caparica, Portugal; [email protected] 2* Correspondence:Glanbia-AgriChemWhey, [email protected]; Lisheen Mine, Tel.: Killoran, +351‐212948550 Moyne, E41 R622 Tipperary, Ireland; [email protected] * Correspondence: [email protected]; Tel.: +351-212948550 Abstract: Lectins are a class of proteins responsible for several biological roles such as cell‐cell in‐ Abstract:teractions,Lectins signaling are pathways, a class of and proteins several responsible innate immune for several responses biological against roles pathogens. such as Since cell-cell lec‐ interactions,tins are able signalingto bind to pathways, carbohydrates, and several they can innate be a immuneviable target responses for targeted against drug pathogens. delivery Since sys‐ lectinstems. In are fact, able several to bind lectins to carbohydrates, were approved they by canFood be and a viable Drug targetAdministration for targeted for drugthat purpose. delivery systems.Information In fact, about several specific lectins carbohydrate were approved recognition by Food by andlectin Drug receptors Administration was gathered for that herein, purpose. plus Informationthe specific organs about specific where those carbohydrate lectins can recognition be found by within lectin the receptors human was body. -
NIH Public Access Author Manuscript JAMA Neurol
NIH Public Access Author Manuscript JAMA Neurol. Author manuscript; available in PMC 2014 August 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: JAMA Neurol. 2014 February ; 71(2): 180–187. doi:10.1001/jamaneurol.2013.4560. The role of clusterin in amyloid-β associated neurodegeneration Rahul S. Desikan, MD, PhD1, Wesley K. Thompson, PhD2, Dominic Holland, PhD3, Christopher P. Hess, MD, PhD4, James B. Brewer, MD, PhD1,3, Henrik Zetterberg, MD, PhD5,6, Kaj Blennow, MD, PhD5, Ole A. Andreassen, MD, PhD2,7, Linda K. McEvoy, PhD1,#, Bradley T. Hyman, MD, PhD8,#, Anders M. Dale, PhD1,2,#, and for the Alzheimer's Disease Neuroimaging Initiative* 1Department of Radiology, University of California, San Diego, La Jolla, CA, USA 2Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA 3Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA 4Neuroradiology Section, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA 5Clinical Neurochemistry Laboratory, The Sahlgrenska Academy at Göteburg University, Mölndal, 40530, Gotheburg, Sweden 6UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom 7Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway 8Department of Neurology, Massachusetts General Hospital, Boston, MA, USA Abstract Importance—Converging evidence indicates that clusterin, a chaperone glycoprotein, influences Alzheimer's disease (AD) neurodegeneration. However, the precise role of clusterin in AD pathogenesis is still not well understood. Objective—To elucidate the relationship between clusterin, amyloid-β (Aβ), p-tau, and rate of brain atrophy over time among non-demented older individuals. -
Image Processing and Analysis Methods for the Adolescent Brain Cognitive Development Study
NeuroImage 202 (2019) 116091 Contents lists available at ScienceDirect NeuroImage journal homepage: www.elsevier.com/locate/neuroimage Image processing and analysis methods for the Adolescent Brain Cognitive Development Study Donald J. Hagler Jr. a,*, SeanN. Hatton a, M. Daniela Cornejo a, Carolina Makowski b, Damien A. Fair c, Anthony Steven Dick d, Matthew T. Sutherland d, B.J. Casey e, Deanna M. Barch f, Michael P. Harms f, Richard Watts e, James M. Bjork g, Hugh P. Garavan h, Laura Hilmer a, Christopher J. Pung a, Chelsea S. Sicat a, Joshua Kuperman a, Hauke Bartsch a, Feng Xue a, Mary M. Heitzeg i, Angela R. Laird d, Thanh T. Trinh a, Raul Gonzalez d, Susan F. Tapert a, Michael C. Riedel d, Lindsay M. Squeglia j, Luke W. Hyde i, Monica D. Rosenberg e, Eric A. Earl c, Katia D. Howlett k, Fiona C. Baker l, Mary Soules i, Jazmin Diaz a, Octavio Ruiz de Leon a, Wesley K. Thompson a, Michael C. Neale g, Megan Herting m,n, Elizabeth R. Sowell n, Ruben P. Alvarez o, Samuel W. Hawes d, Mariana Sanchez d, Jerzy Bodurka p, Florence J. Breslin p, Amanda Sheffield Morris p, Martin P. Paulus p, W. Kyle Simmons p, Jonathan R. Polimeni q,r, Andre van der Kouwe q,r, Andrew S. Nencka s, Kevin M. Gray j, Carlo Pierpaoli t, John A. Matochik u, Antonio Noronha u, Will M. Aklin k, Kevin Conway k, Meyer Glantz k, Elizabeth Hoffman k, Roger Little k, Marsha Lopez k, Vani Pariyadath k, Susan RB. Weiss k, Dana L. -
FBXO24 Rabbit Polyclonal Antibody – TA330492 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA330492 FBXO24 Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: WB Recommended Dilution: WB Reactivity: Human Host: Rabbit Isotype: IgG Clonality: Polyclonal Immunogen: The immunogen for anti-FBXO24 antibody: synthetic peptide directed towards the middle region of human FBXO24. Synthetic peptide located within the following region: LCATRECLYILSSHDIEQHAPYRHLPASRVVGTPEPSLGARAPQDPGGMA Formulation: Liquid. Purified antibody supplied in 1x PBS buffer with 0.09% (w/v) sodium azide and 2% sucrose. Note that this product is shipped as lyophilized powder to China customers. Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 65 kDa Gene Name: F-box protein 24 Database Link: NP_277041 Entrez Gene 26261 Human O75426 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 FBXO24 Rabbit Polyclonal Antibody – TA330492 Background: FBXO24 is a member of the F-box protein family which is characterized by an approximately 40 amino acid motif, the F-box. The F-box proteins constitute one of the four subunits of the ubiquitin protein ligase complex called SCFs (SKP1-cullin-F-box), which function in phosphorylation-dependent ubiquitination. The F-box proteins are divided into 3 classes: Fbws containing WD-40 domains, Fbls containing leucine-rich repeats, and Fbxs containing either different protein-protein interaction modules or no recognizable motifs. -
FBXO24 (Human) Recombinant Protein (P01)
FBXO24 (Human) Recombinant Storage Instruction: Store at -80°C. Aliquot to avoid Protein (P01) repeated freezing and thawing. Entrez GeneID: 26261 Catalog Number: H00026261-P01 Gene Symbol: FBXO24 Regulation Status: For research use only (RUO) Gene Alias: DKFZp434I1122, FBX24 Product Description: Human FBXO24 full-length ORF ( NP_277041.1, 1 a.a. - 580 a.a.) recombinant protein with Gene Summary: This gene encodes a member of the GST-tag at N-terminal. F-box protein family which is characterized by an approximately 40 amino acid motif, the F-box. The F-box Sequence: proteins constitute one of the four subunits of the MGEKAVPLLRRRRVKRSCPSCGSELGVEEKRGKGNPI ubiquitin protein ligase complex called SCFs SIQLFPPELVEHIISFLPVRDLVALGQTCRYFHEVCDGE (SKP1-cullin-F-box), which function in GVWRRICRRLSPRLQDQGSGVRPWKRAAILNYTKGLY phosphorylation-dependent ubiquitination. The F-box FQAFGGRRRCLSKSVAPLLAHGYRRFLPTKDHVFILDY proteins are divided into 3 classes: Fbws containing VGTLFFLKNALVSTLGQMQWKRACRYVVLCRGAKDF WD-40 domains, Fbls containing leucine-rich repeats, ASDPRCDTVYRKYLYVLATREPQEVVGTTSSRACDCV and Fbxs containing either different protein-protein EVYLQSSGQRVFKMTFHHSMTFKQIVLVGQETQRALL interaction modules or no recognizable motifs. The LLTEEGKIYSLVVNETQLDQPRSYTVQLALRKVSHYLP protein encoded by this gene belongs to the Fbxs class. HLRVACMTSNQSSTLYVTDQGGVYFEVHTPGVYRDLF Multiple transcript variants encoding different isoforms GTLQAFDPLDQQMPLALSLPAKILFCALGYNHLGLVDE have been found for this gene. [provided by RefSeq] FGRIFMQGNNRYGQLGTGDKMDRGEPTQVCYLQRPI TLWCGLNHSLVLSQSSEFSKELLGCGCGAGGRLPGW -
Supplementary Table 1. List of Genes Up-Regulated in Abiraterone-Resistant Vcap Xenograft Samples PIK3IP1 Phosphoinositide-3-Kin
Supplementary Table 1. List of genes up-regulated in abiraterone-resistant VCaP xenograft samples PIK3IP1 phosphoinositide-3-kinase interacting protein 1 TMEM45A transmembrane protein 45A THBS1 thrombospondin 1 C7orf63 chromosome 7 open reading frame 63 OPTN optineurin FAM49A family with sequence similarity 49, member A APOL4 apolipoprotein L, 4 C17orf108|LOC201229 chromosome 17 open reading frame 108 | hypothetical protein LOC201229 SNORD94 small nucleolar RNA, C/D box 94 PCDHB11 protocadherin beta 11 RBM11 RNA binding motif protein 11 C6orf225 chromosome 6 open reading frame 225 KIAA1984|C9orf86|TMEM14 1 KIAA1984 | chromosome 9 open reading frame 86 | transmembrane protein 141 KIAA1107 TLR3 toll-like receptor 3 LPAR6 lysophosphatidic acid receptor 6 KIAA1683 GRB10 growth factor receptor-bound protein 10 TIMP2 TIMP metallopeptidase inhibitor 2 CCDC28A coiled-coil domain containing 28A FBXL2 F-box and leucine-rich repeat protein 2 NOV nephroblastoma overexpressed gene TSPAN31 tetraspanin 31 NR3C2 nuclear receptor subfamily 3, group C, member 2 DYNC2LI1 dynein, cytoplasmic 2, light intermediate chain 1 C15orf51 dynamin 1 pseudogene SAMD13 sterile alpha motif domain containing 13 RASSF6 Ras association (RalGDS/AF-6) domain family member 6 ZNF167 zinc finger protein 167 GATA2 GATA binding protein 2 NUDT7 nudix (nucleoside diphosphate linked moiety X)-type motif 7 DNAJC18 DnaJ (Hsp40) homolog, subfamily C, member 18 SNORA57 small nucleolar RNA, H/ACA box 57 CALCOCO1 calcium binding and coiled-coil domain 1 RLN2 relaxin 2 ING4 inhibitor of -
Dissecting the Genetic Relationship Between
VU Research Portal Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer's disease Broce, Iris J; Tan, Chin Hong; Fan, Chun Chieh; Jansen, Iris; Savage, Jeanne E; Witoelar, Aree; Wen, Natalie; Hess, Christopher P; Dillon, William P; Glastonbury, Christine M; Glymour, Maria; Yokoyama, Jennifer S; Elahi, Fanny M; Rabinovici, Gil D; Miller, Bruce L; Mormino, Elizabeth C; Sperling, Reisa A; Bennett, David A; McEvoy, Linda K; Brewer, James B published in Acta Neuropathologica 2019 DOI (link to publisher) 10.1007/s00401-018-1928-6 document version Publisher's PDF, also known as Version of record document license Article 25fa Dutch Copyright Act Link to publication in VU Research Portal citation for published version (APA) Broce, I. J., Tan, C. H., Fan, C. C., Jansen, I., Savage, J. E., Witoelar, A., Wen, N., Hess, C. P., Dillon, W. P., Glastonbury, C. M., Glymour, M., Yokoyama, J. S., Elahi, F. M., Rabinovici, G. D., Miller, B. L., Mormino, E. C., Sperling, R. A., Bennett, D. A., McEvoy, L. K., ... Desikan, R. S. (2019). Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer's disease. Acta Neuropathologica, 137, 209-226. https://doi.org/10.1007/s00401-018-1928-6 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. -
ADGC) Collaboration and Data Sharing Summary
Alzheimer’s Disease Genetics Consortium (ADGC) Collaboration and Data Sharing Summary Alzheimer’s Disease Genetics Consortium (ADGC) NIA grant U01AG032984 Collaboration and Data Sharing Summary ADGC lead investigators Gerard D. Schellenberg, PI: University of Pennsylvania Lindsay Farrer: Boston University Jonathan Haines: Case Western Reserve University Richard Mayeux: Columbia University Margaret Pericak-Vance: University of Miami Li-San Wang: University of Pennsylvania The ADGC was formed to collaboratively use the collective resources of the AD research community to identify Alzheimer’s disease (AD) genes. These genes include those that cause AD, increase or decrease AD risk, and protect against AD. The ADGC includes investigators with the clinical, neuropathological, molecular and statistical expertise needed to analyze the complex phenotype of AD. The ADGC assembled genetic and phenotype data for a large number of AD cases and cognitively normal elderly controls. For non-Hispanic whites (NHW), subjects include 17,876 cases and 19,440 controls (Table 1A). For other ethnic groups (African Americans, Caribbean Hispanic, non-Caribbean Hispanics, and Asians), the subjects include 9,392 AD cases and 15,125 controls (Table 1B). Through a variety of approaches, the ADGC continues to add to this collection of cohorts. The following describes the collaborations established and the data sharing activities of the ADGC. I. ADGC collaborative network. The ADGC collaborates with 21 different cohorts in the US (Table 1A, B). The largest cohort is from the 31 NIA-funded Alzheimer’s Disease Centers (ADC’s) which have contributed 7,428 cases and 7,342 controls to ADGC studies. While the majority of subjects are non-Hispanic Caucasians (Table 1A), the ADGC also assembled and analyzed genetic and phenotype data for Hispanics, African Americans, and Asians (Table 1B). -
Polygenic Hazard Score: an Enrichment Marker for Alzheimer's Associated Amyloid and Tau Deposition
Acta Neuropathologica (2018) 135:85–93 https://doi.org/10.1007/s00401-017-1789-4 ORIGINAL PAPER Polygenic hazard score: an enrichment marker for Alzheimer’s associated amyloid and tau deposition Chin Hong Tan1 · Chun Chieh Fan2 · Elizabeth C. Mormino3 · Leo P. Sugrue1 · Iris J. Broce1 · Christopher P. Hess1 · William P. Dillon1 · Luke W. Bonham4 · Jennifer S. Yokoyama4 · Celeste M. Karch5 · James B. Brewer6,7,8 · Gil D. Rabinovici4 · Bruce L. Miller4 · Gerard D. Schellenberg9 · Karolina Kauppi7 · Howard A. Feldman6 · Dominic Holland6 · Linda K. McEvoy7 · Bradley T. Hyman10 · David A. Bennett11 · Ole A. Andreassen12,13 · Anders M. Dale2,6,7 · Rahul S. Desikan1,4 · For the Alzheimer’s Disease Neuroimaging Initiative Received: 20 September 2017 / Revised: 10 November 2017 / Accepted: 10 November 2017 / Published online: 24 November 2017 © Springer-Verlag GmbH Germany, part of Springer Nature 2017 Abstract There is an urgent need for identifying nondemented individuals at the highest risk of progressing to Alzheimer’s disease (AD) dementia. Here, we evaluated whether a recently validated polygenic hazard score (PHS) can be integrated with known in vivo cerebrospinal fuid (CSF) or positron emission tomography (PET) biomarkers of amyloid, and CSF tau pathology to prospectively predict cognitive and clinical decline in 347 cognitive normal (CN; baseline age range = 59.7–90.1, 98.85% white) and 599 mild cognitively impaired (MCI; baseline age range = 54.4–91.4, 98.83% white) individuals from the Alz- heimer’s Disease Neuroimaging Initiative 1, GO, and 2. We further investigated the association of PHS with post-mortem amyloid load and neurofbrillary tangles in the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort (N = 485, age at death range = 71.3–108.3).