DOCSLIB.ORG

Genome-Wide Analysis of DNA Methylation and Risk Of

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Genome-Wide Analysis of DNA Methylation and Risk Of Gao et al. BMC Cardiovasc Disord (2021) 21:240 https://doi.org/10.1186/s12872-021-02001-w RESEARCH Open Access Genome-wide analysis of DNA methylation and risk of cardiovascular disease in a Chinese population Yan Gao1†, Huifang Pang1†, Bowang Chen1, ChaoQun Wu1, Yanping Wang1, Libo Hou1, Siming Wang1, Dianjianyi Sun2 and Xin Zheng1* Abstract Background: Systemic studies of association of genome-wide DNA methylated sites with cardiovascular disease (CVD) in prospective cohorts are lacking. Our aim was to identify DNA methylation sites associated with the risk of CVD and further investigate their potential predictive value in CVD development for high-risk subjects. Methods: We performed an epigenome-wide association study (EWAS) to identify CpGs related to CVD develop- ment in a Chinese population.We adopted a nested case–control design based on data from China PEACE Million Persons Project. A total of 83 cases who developed CVD events during follow-up and 83 controls who were matched with cases by age, sex, BMI, ethnicity, medications treatment and behavior risk factors were included in the discovery stage. Genome-wide DNA methylation from whole blood was detected using Infnium Human Methylation EPIC Beadchip (850 K). For signifcant CpGs [FDR(false discovery rate) < 0.005], we further validated in an independent cohort including 38 cases and 38 controls. Results: In discovery set, we identifed 8 signifcant CpGs (FDR < 0.005) associated with the risk of CVD after adjust- ment for cell components, demographic and cardiac risk factors and the frst 5 principal components. Two of these identifed CpGs (cg06901278 and cg09306458 in UACA ) were replicated in another independent set (p < 0.05). Enrich- ment analysis in 787 individual genes from 1036 CpGs in discovery set revealed a signifcant enrichment for anatomi- cal structure homeostasis as well as regulation of vesicle-mediated transport. Receiver operating characteristic (ROC) analysis showed that the model combined 8 CVD-related CpGs with baseline characteristics showed much better predictive efect for CVD occurrence compared with the model with baseline characteristics only [AUC (area under the curve) 0.967, 95% CI (0.942 0.991); AUC 0.621, 95% CI (0.536 0.706); p 9.716E-15]. = − = − = Conclusions: Our study identifed the novel CpGs associated with CVD development and revealed their additional predictive power in the risk of CVD for high-risk subjects. Keywords: EWAS, DNA methylation, CVD Introduction *Correspondence: [email protected] Cardiovascular disease (CVD), a complex disease that † Yan Gao and Huifang Pang: Co-frst author is attributed to the interaction between environmental 1 National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Chinese Academy of Medical and genetic factors, is the leading cause of death in most Sciences and Peking Union Medical College, Fuwai Hospital, National countries [1, 2]. It is necessary to elucidate the underlying Center for Cardiovascular Diseases, 167 Beilishi Road, Beijing 100037, biological mechanisms of CVD to enable early diagnosis People’s Republic of China Full list of author information is available at the end of the article and treatment of the disease. © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Gao et al. BMC Cardiovasc Disord (2021) 21:240 Page 2 of 10 For the development of CVD, it is widely accepted that community population if they were 35–75 years old age, sex, high blood pressure, smoking, dyslipidemia, and and could confrm their residence in a selected region diabetes are the major risk factors. Furthermore, over the including 141 primary health care sites (88 rural coun- past few years, many genome-wide association studies ties and 53 urban districts) from all 31 provinces in the (GWAS) have identifed relevant genetic polymorphisms mainland of China from September 15, 2014 to June as risk factors, but the results that known risk loci only 20, 2017. Te participants were initially screened for account for a small proportion of risk are not encourag- high-risk of CVD by measurements of blood pressure, ing for personal risk prediction based on genotyping [3]. height, weight and blood lipid, and a questionnaire on Tis suggests other risk factors possibly afect the devel- cardiovascular-related health status. Te subjects at opment of CVD between genetics and environmental high-risk of CVD were identifed if they met at least one factors, such as epigenetics. of four criteria: 1. Medical history of myocardial infarc- Epigenetics is based on stable and heritable alterations tion (MI), percutaneous coronary intervention (PCI), in gene expression without changes in the DNA sequence coronary artery bypass grafting (CABG) treatment, or itself [4]. DNA methylation is a crucial type of epigenetic stroke; 2. High blood pressure defned as systolic blood modifcation, by which a methyl group covalent bonds pressure (SBP) ≥ 160 mmHg or diastolic blood pressure ′ ′ to the C5 position of cytosine in 5 -C-phosphate-G-3 (DBP) ≥ 100 mmHg; 3. Dyslipidemia defned as low- (CpG) dinucleotides, ultimately regulating the gene tran- density lipoprotein cholesterol (LDL-C) ≥ 160 mg/dL scription activity and alter biological functions [5]. Pre- (4.14 mmol/L) or high-density lipoprotein cholesterol vious studies have demonstrated associations of DNA (HDL-C) < 30 mg/dL (0.78 mmol/L); 4. Risk of CVD in methylation with atherosclerosis [6, 7], ischemic heart 10 years ≥ 20% based on WHO/ISH Cardiovascular Risk disease [8], coronary heart disease (CHD) [8], coronary Prediction Charts for the Western Pacifc Region B [13]. artery disease [9] and acute coronary syndrome (ACS) Te high-risk participants received further health assess- [10]. Besides, DNA methylation is suggested as a bio- ments, including electrocardiography, ultrasound scan, marker for CVD risk [11]. However, the previous evi- blood and urine analysis, and a questionnaire on lifestyle dences were based on cross-sectional studies, lack of the and medical history and were followed up every year to rationale of temperal causality. Systemic identifcation collect information on medication adherence, risk fac- of genome-wide DNA diferential CpGs and analysis of tor control, and any hospitalization. Te data were col- their association with CVD risk are lacking. lected from standardized in-person interviews by trained In the present study, our main objective is to identify medical staf. Te central ethics committee at the China CpGs associated with the risk of CVD and further inves- National Center for Cardiovascular Disease (NCCD) tigate their potential predictive value in CVD devel- approved this project. All participants had completed opment for high-risk subjects. We frst examined the a written informed consent before participation in the association of genome-wide DNA methylation patterns project. from whole blood samples in 83 pairs of case–control In the present study, we performed a nested case–con- participants at high-risk of CVD using Infnium Human trol study based on the high-risk participants from the Methylation EPIC Beadchip (850 K). For identifed sig- MPP cohort to examine and validate the association of nifcant CpGs, we further validated their association with genome-wide CpGs with the development of CVD. Te the development of CVD in another independent cohort. inclusion criteria: 1. Blood samples were collected after And enrichment analysis in Gene Ontology (GO) terms January 1, 2016; 2. Two years follow-up data was avail- was conducted to identify signifcantly enriched catego- able; 3. Te questionnaire for the high-risk participants ries. Finally, we performed the ROC analysis to assess the was available. Patients were excluded if they have self- predictive value of genome-wide signifcant CpGs for the reported any of medical history of cancer, chronic liver risk of CVD. and kidney disease, infectious diseases, or any CVD at baseline. Methods Among the above eligible population, case (subjects Study design and study samples who developed cardiovascular events) and control (sub- Te study samples were collected from the China jects who did not develop cardiovascular events) were 1:1 PEACE Million Persons Project (MPP) cohort. Te matched for age (within 1 year), sex, BMI, the month of design and conduct of the project pilot have been pre- blood collection (within 1 month), medications treatment viously described in detail [12]. In brief, the China- (antiplatelet medications and statins), ethnicity (han or PEACE MPP is a national, population-based screening non-han), current smoking status, and current alcohol project funded by the Chinese government to identify intake at baseline. Ten, 121 pairs were randomly sam- individuals at high-risk of CVD. Te project enrolled pled from the above eligible case–control pairs. Among Gao et al. BMC Cardiovasc Disord (2021) 21:240 Page 3 of 10 them, 83 pairs case–control and 38 pairs case–control meal or random blood glucose greater than 11.1 mmol/L, were randomly selected and regarded as the discovery set or any kind of hypoglycemic agents.
Load more

Recommended publications
  • Goat Anti-Ymer / CCDC50 Antibody Size: 100Μg Specific Antibody in 200Μl
    EB06551 - Goat Anti-Ymer / CCDC50 Antibody Size: 100µg specific antibody in 200µl Target Protein Principal Names: Ymer protein, coiled-coil domain containing 50, C3orf6, YMER, C3orf6, chromosome 3 open reading frame 6 UK Office Official Symbol: CCDC50 Accession Number(s): NP_848018.1; NP_777568.1 Everest Biotech Ltd Human GeneID(s): 152137 Cherwell Innovation Centre Important Comments: This antibody is expected to recognise both reported isoforms of 77 Heyford Park human Ymer protein. Upper Heyford Oxfordshire Immunogen OX25 5HD Peptide with sequence CFSKSESSHKGFHYK, from the internal region of the protein UK sequence according to NP_848018.1; NP_777568.1. Enquiries: Please note the peptide is available for sale. [email protected] Sales: Purification and Storage [email protected] Purified from goat serum by ammonium sulphate precipitation followed by antigen affinity Tech support: chromatography using the immunizing peptide. [email protected] Supplied at 0.5 mg/ml in Tris saline, 0.02% sodium azide, pH7.3 with 0.5% bovine serum albumin. Tel: +44 (0)1869 238326 Aliquot and store at -20°C. Minimize freezing and thawing. Fax: +44 (0)1869 238327 Applications Tested US Office Peptide ELISA: antibody detection limit dilution 1:32000. Everest Biotech c/o Abcore Western blot: Preliminary experiments gave an approx 18kDa band in Human Brain 405 Maple Street, Suite A106 lysates after 1µg/ml antibody staining. Please note that currently we cannot find an Ramona, explanation in the literature for the band we observe given the calculated size of 56.3kDa CA 92065 according to NP_848018.1 and 35.8kDa according to NP_777568.1. The 18kDa band was USA successfully blocked by incubation with the immunizing peptide.
    [Show full text]
  • Genome-Scale Single-Cell Mechanical Phenotyping Reveals Disease-Related Genes Involved in Mitotic Rounding
    ARTICLE DOI: 10.1038/s41467-017-01147-6 OPEN Genome-scale single-cell mechanical phenotyping reveals disease-related genes involved in mitotic rounding Yusuke Toyoda 1,2, Cedric J. Cattin3, Martin P. Stewart 3,4,5, Ina Poser1, Mirko Theis6, Teymuras V. Kurzchalia1, Frank Buchholz1,6, Anthony A. Hyman1 & Daniel J. Müller 3 To divide, most animal cells drastically change shape and round up against extracellular confinement. Mitotic cells facilitate this process by generating intracellular pressure, which the contractile actomyosin cortex directs into shape. Here, we introduce a genome-scale microcantilever- and RNAi-based approach to phenotype the contribution of > 1000 genes to the rounding of single mitotic cells against confinement. Our screen analyzes the rounding force, pressure and volume of mitotic cells and localizes selected proteins. We identify 49 genes relevant for mitotic rounding, a large portion of which have not previously been linked to mitosis or cell mechanics. Among these, depleting the endoplasmic reticulum-localized protein FAM134A impairs mitotic progression by affecting metaphase plate alignment and pressure generation by delocalizing cortical myosin II. Furthermore, silencing the DJ-1 gene uncovers a link between mitochondria-associated Parkinson’s disease and mitotic pressure. We conclude that mechanical phenotyping is a powerful approach to study the mechanisms governing cell shape. 1 Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany. 2 Division of Cell Biology, Life Science Institute, Kurume University, Hyakunen-Kohen 1-1, Kurume, Fukuoka 839-0864, Japan. 3 Department of Biosystems Science and Engineering (D-BSSE), Eidgenössische Technische Hochschule (ETH) Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
    [Show full text]
  • Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
    Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo
    [Show full text]
  • A Genome-Wide in Vitro Bacterial-Infection Screen Reveals Human Variation in the Host Response Associated with Inflammatory Disease
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector ARTICLE A Genome-wide In Vitro Bacterial-Infection Screen Reveals Human Variation in the Host Response Associated with Inflammatory Disease Dennis C. Ko,1 Kajal P. Shukla,1 Christine Fong,1 Michael Wasnick,1 Mitchell J. Brittnacher,1 Mark M. Wurfel,2 Tarah D. Holden,2 Grant E. O’Keefe,5 Brian Van Yserloo,2 Joshua M. Akey,3 and Samuel I. Miller1,2,3,4,* Recent progress in cataloguing common genetic variation has made possible genome-wide studies that are beginning to elucidate the causes and consequences of our genetic differences. Approaches that provide a mechanistic understanding of how genetic variants func- tion to alter disease susceptibility and why they were substrates of natural selection would complement other approaches to human- genome analysis. Here we use a novel cell-based screen of bacterial infection to identify human variation in Salmonella-induced cell death. A loss-of-function allele of CARD8, a reported inhibitor of the proinflammatory protease caspase-1, was associated with increased cell death in vitro (p ¼ 0.013). The validity of this association was demonstrated through overexpression of alternative alleles and RNA interference in cells of varying genotype. Comparison of mammalian CARD8 orthologs and examination of variation among different human populations suggest that the increase in infectious-disease burden associated with larger animal groups (i.e., herds and colonies), and possibly human population expansion, may have naturally selected for loss of CARD8. We also find that the loss-of-function CARD8 allele shows a modest association with an increased risk of systemic inflammatory response syndrome in a small study (p ¼ 0.05).
    [Show full text]
  • Supplementary Information – Postema Et Al., the Genetics of Situs Inversus Totalis Without Primary Ciliary Dyskinesia
    1 Supplementary information – Postema et al., The genetics of situs inversus totalis without primary ciliary dyskinesia Table of Contents: Supplementary Methods 2 Supplementary Results 5 Supplementary References 6 Supplementary Tables and Figures Table S1. Subject characteristics 9 Table S2. Inbreeding coefficients per subject 10 Figure S1. Multidimensional scaling to capture overall genomic diversity 11 among the 30 study samples Table S3. Significantly enriched gene-sets under a recessive mutation model 12 Table S4. Broader list of candidate genes, and the sources that led to their 13 inclusion Table S5. Potential recessive and X-linked mutations in the unsolved cases 15 Table S6. Potential mutations in the unsolved cases, dominant model 22 2 1.0 Supplementary Methods 1.1 Participants Fifteen people with radiologically documented SIT, including nine without PCD and six with Kartagener syndrome, and 15 healthy controls matched for age, sex, education and handedness, were recruited from Ghent University Hospital and Middelheim Hospital Antwerp. Details about the recruitment and selection procedure have been described elsewhere (1). Briefly, among the 15 people with radiologically documented SIT, those who had symptoms reminiscent of PCD, or who were formally diagnosed with PCD according to their medical record, were categorized as having Kartagener syndrome. Those who had no reported symptoms or formal diagnosis of PCD were assigned to the non-PCD SIT group. Handedness was assessed using the Edinburgh Handedness Inventory (EHI) (2). Tables 1 and S1 give overviews of the participants and their characteristics. Note that one non-PCD SIT subject reported being forced to switch from left- to right-handedness in childhood, in which case five out of nine of the non-PCD SIT cases are naturally left-handed (Table 1, Table S1).
    [Show full text]
  • Supplementary Tables S1-S3
    Supplementary Table S1: Real time RT-PCR primers COX-2 Forward 5’- CCACTTCAAGGGAGTCTGGA -3’ Reverse 5’- AAGGGCCCTGGTGTAGTAGG -3’ Wnt5a Forward 5’- TGAATAACCCTGTTCAGATGTCA -3’ Reverse 5’- TGTACTGCATGTGGTCCTGA -3’ Spp1 Forward 5'- GACCCATCTCAGAAGCAGAA -3' Reverse 5'- TTCGTCAGATTCATCCGAGT -3' CUGBP2 Forward 5’- ATGCAACAGCTCAACACTGC -3’ Reverse 5’- CAGCGTTGCCAGATTCTGTA -3’ Supplementary Table S2: Genes synergistically regulated by oncogenic Ras and TGF-β AU-rich probe_id Gene Name Gene Symbol element Fold change RasV12 + TGF-β RasV12 TGF-β 1368519_at serine (or cysteine) peptidase inhibitor, clade E, member 1 Serpine1 ARE 42.22 5.53 75.28 1373000_at sushi-repeat-containing protein, X-linked 2 (predicted) Srpx2 19.24 25.59 73.63 1383486_at Transcribed locus --- ARE 5.93 27.94 52.85 1367581_a_at secreted phosphoprotein 1 Spp1 2.46 19.28 49.76 1368359_a_at VGF nerve growth factor inducible Vgf 3.11 4.61 48.10 1392618_at Transcribed locus --- ARE 3.48 24.30 45.76 1398302_at prolactin-like protein F Prlpf ARE 1.39 3.29 45.23 1392264_s_at serine (or cysteine) peptidase inhibitor, clade E, member 1 Serpine1 ARE 24.92 3.67 40.09 1391022_at laminin, beta 3 Lamb3 2.13 3.31 38.15 1384605_at Transcribed locus --- 2.94 14.57 37.91 1367973_at chemokine (C-C motif) ligand 2 Ccl2 ARE 5.47 17.28 37.90 1369249_at progressive ankylosis homolog (mouse) Ank ARE 3.12 8.33 33.58 1398479_at ryanodine receptor 3 Ryr3 ARE 1.42 9.28 29.65 1371194_at tumor necrosis factor alpha induced protein 6 Tnfaip6 ARE 2.95 7.90 29.24 1386344_at Progressive ankylosis homolog (mouse)
    [Show full text]
  • Predicting Environmental Chemical Factors Associated with Disease-Related Gene Expression Data
    UCSF UC San Francisco Previously Published Works Title Predicting environmental chemical factors associated with disease-related gene expression data. Permalink https://escholarship.org/uc/item/1kj3j6m8 Journal BMC medical genomics, 3(1) ISSN 1755-8794 Authors Patel, Chirag J Butte, Atul J Publication Date 2010-05-06 DOI 10.1186/1755-8794-3-17 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Patel and Butte BMC Medical Genomics 2010, 3:17 http://www.biomedcentral.com/1755-8794/3/17 RESEARCH ARTICLE Open Access PredictingResearch article environmental chemical factors associated with disease-related gene expression data Chirag J Patel1,2,3 and Atul J Butte*1,2,3 Abstract Background: Many common diseases arise from an interaction between environmental and genetic factors. Our knowledge regarding environment and gene interactions is growing, but frameworks to build an association between gene-environment interactions and disease using preexisting, publicly available data has been lacking. Integrating freely-available environment-gene interaction and disease phenotype data would allow hypothesis generation for potential environmental associations to disease. Methods: We integrated publicly available disease-specific gene expression microarray data and curated chemical- gene interaction data to systematically predict environmental chemicals associated with disease. We derived chemical- gene signatures for 1,338 chemical/environmental chemicals from the Comparative Toxicogenomics Database (CTD). We associated these chemical-gene signatures with differentially expressed genes from datasets found in the Gene Expression Omnibus (GEO) through an enrichment test. Results: We were able to verify our analytic method by accurately identifying chemicals applied to samples and cell lines. Furthermore, we were able to predict known and novel environmental associations with prostate, lung, and breast cancers, such as estradiol and bisphenol A.
    [Show full text]
  • Download Ppis for Each Single Seed, Thus Obtaining Each Seed’S Interactome (Ferrari Et Al., 2018)
    bioRxiv preprint doi: https://doi.org/10.1101/2021.01.14.425874; this version posted January 16, 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 4.0 International license. Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias Nikoleta Vavouraki1,2, James E. Tomkins1, Eleanna Kara3, Henry Houlden3, John Hardy4, Marcus J. Tindall2,5, Patrick A. Lewis1,4,6, Claudia Manzoni1,7* Author Affiliations 1: Department of Pharmacy, University of Reading, Reading, RG6 6AH, United Kingdom 2: Department of Mathematics and Statistics, University of Reading, Reading, RG6 6AH, United Kingdom 3: Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, WC1N 3BG, United Kingdom 4: Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, United Kingdom 5: Institute of Cardiovascular and Metabolic Research, University of Reading, Reading, RG6 6AS, United Kingdom 6: Department of Comparative Biomedical Sciences, Royal Veterinary College, London, NW1 0TU, United Kingdom 7: School of Pharmacy, University College London, London, WC1N 1AX, United Kingdom *Corresponding author: [email protected] Abstract The Hereditary Spastic Paraplegias are a group of neurodegenerative diseases characterized by spasticity and weakness in the lower body. Despite the identification of causative mutations in over 70 genes, the molecular aetiology remains unclear. Due to the combination of genetic diversity and variable clinical presentation, the Hereditary Spastic Paraplegias are a strong candidate for protein- protein interaction network analysis as a tool to understand disease mechanism(s) and to aid functional stratification of phenotypes.
    [Show full text]
  • Full-Text.Pdf
    Systematic Evaluation of Genes and Genetic Variants Associated with Type 1 Diabetes Susceptibility This information is current as Ramesh Ram, Munish Mehta, Quang T. Nguyen, Irma of September 23, 2021. Larma, Bernhard O. Boehm, Flemming Pociot, Patrick Concannon and Grant Morahan J Immunol 2016; 196:3043-3053; Prepublished online 24 February 2016; doi: 10.4049/jimmunol.1502056 Downloaded from http://www.jimmunol.org/content/196/7/3043 Supplementary http://www.jimmunol.org/content/suppl/2016/02/19/jimmunol.150205 Material 6.DCSupplemental http://www.jimmunol.org/ References This article cites 44 articles, 5 of which you can access for free at: http://www.jimmunol.org/content/196/7/3043.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 23, 2021 • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Systematic Evaluation of Genes and Genetic Variants Associated with Type 1 Diabetes Susceptibility Ramesh Ram,*,† Munish Mehta,*,† Quang T.
    [Show full text]
  • Regulation of Gene Expression Dynamics During Developmental Transitions by the Ikaros Transcription Factor
    Downloaded from genesdev.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Regulation of gene expression dynamics during developmental transitions by the Ikaros transcription factor Teresita L. Arenzana,1 Hilde Schjerven,2 and Stephen T. Smale1 1Department of Microbiology, Immunology, and Molecular Genetics, University of California at Los Angeles, Los Angeles, California 90095, USA; 2Department of Laboratory Medicine, University of California at San Francisco, San Francisco, California 94143, USA The DNA-binding protein Ikaros is a potent tumor suppressor and hematopoietic regulator. However, the mecha- nisms by which Ikaros functions remain poorly understood, due in part to its atypical DNA-binding properties and partnership with the poorly understood Mi-2/NuRD complex. In this study, we analyzed five sequential stages of thymocyte development in a mouse strain containing a targeted deletion of Ikaros zinc finger 4, which exhibits a select subset of abnormalities observed in Ikaros-null mice. By examining thymopoiesis in vivo and in vitro, diverse abnormalities were observed at each developmental stage. RNA sequencing revealed that each stage is characterized by the misregulation of a limited number of genes, with a strong preference for stage-specific rather than lineage- specific genes. Strikingly, individual genes rarely exhibited Ikaros dependence at all stages. Instead, a consistent feature of the aberrantly expressed genes was a reduced magnitude of expression level change during developmental transitions. These results, combined with analyses of the interplay between Ikaros loss of function and Notch sig- naling, suggest that Ikaros may not be a conventional activator or repressor of defined sets of genes.
    [Show full text]
  • Meta-Analysis of Gene Expression in Individuals with Autism Spectrum Disorders
    Meta-analysis of Gene Expression in Individuals with Autism Spectrum Disorders by Carolyn Lin Wei Ch’ng BSc., University of Michigan Ann Arbor, 2011 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Bioinformatics) The University of British Columbia (Vancouver) August 2013 c Carolyn Lin Wei Ch’ng, 2013 Abstract Autism spectrum disorders (ASD) are clinically heterogeneous and biologically complex. State of the art genetics research has unveiled a large number of variants linked to ASD. But in general it remains unclear, what biological factors lead to changes in the brains of autistic individuals. We build on the premise that these heterogeneous genetic or genomic aberra- tions will converge towards a common impact downstream, which might be reflected in the transcriptomes of individuals with ASD. Similarly, a considerable number of transcriptome analyses have been performed in attempts to address this question, but their findings lack a clear consensus. As a result, each of these individual studies has not led to any significant advance in understanding the autistic phenotype as a whole. The goal of this research is to comprehensively re-evaluate these expression profiling studies by conducting a systematic meta-analysis. Here, we report a meta-analysis of over 1000 microarrays across twelve independent studies on expression changes in ASD compared to unaffected individuals, in blood and brain. We identified a number of genes that are consistently differentially expressed across studies of the brain, suggestive of effects on mitochondrial function. In blood, consistent changes were more difficult to identify, despite individual studies tending to exhibit larger effects than the brain studies.
    [Show full text]
  • Transdifferentiation of Human Mesenchymal Stem Cells
    Transdifferentiation of Human Mesenchymal Stem Cells Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Julius-Maximilians-Universität Würzburg vorgelegt von Tatjana Schilling aus San Miguel de Tucuman, Argentinien Würzburg, 2007 Eingereicht am: Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Martin J. Müller Gutachter: PD Dr. Norbert Schütze Gutachter: Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am: Hiermit erkläre ich ehrenwörtlich, dass ich die vorliegende Dissertation selbstständig angefertigt und keine anderen als die von mir angegebenen Hilfsmittel und Quellen verwendet habe. Des Weiteren erkläre ich, dass diese Arbeit weder in gleicher noch in ähnlicher Form in einem Prüfungsverfahren vorgelegen hat und ich noch keinen Promotionsversuch unternommen habe. Gerbrunn, 4. Mai 2007 Tatjana Schilling Table of contents i Table of contents 1 Summary ........................................................................................................................ 1 1.1 Summary.................................................................................................................... 1 1.2 Zusammenfassung..................................................................................................... 2 2 Introduction.................................................................................................................... 4 2.1 Osteoporosis and the fatty degeneration of the bone marrow..................................... 4 2.2 Adipose and bone
    [Show full text]