1.2 Autoimmune Disease Multiple Sclerosis (MS)
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Genetic factors in the autoimmune disease multiple sclerosis Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf vorgelegt von Robert Goertsches aus Leverkusen Januar 2006 Aus dem Institut für Genetik der Heinrich-Heine Universität Düsseldorf Gedruckt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf Referent: Prof. Dr. E. Knust Koreferent: PD Dr. M. Beye Tag der mündlichen Prüfung: 20.04.2006 "Founded on acquired knowledge, a satisfying accomplishment manifest itself almost effortlessly, . however; only whoever has endured in the dark suspecting search, year after year, constantly swaying between conficende and despair, followed by the final breakthrough to the truth, can fully empathize." **** A. Einstein **** “Im Lichte bereits erlangter Erkenntnis erscheint das glücklich Erreichte fast wie selbstverständlich, . aber das ahnungsvolle, Jahre währende Suchen im Dunkeln mit seiner Abwechslung von Zuversicht und Ermattung und seinem endlichen Durchbrechen zur Wahrheit, das kennt nur, wer es selber erlebt hat.” Acknowledgement I want to express my thanks to the following persons without whom this work would have been impossible to initiate, manage and complete. I thank very much the person without whom I never would have gotten into this adventure in the first place, Pablo Villoslada, former member of the UNIC, Barcelona, and now investigating neurologist in Pamplona, at the Neuroimmunology department of the University of Navarra, Spain. I shall furthermore express my deepest gratitude to Xavier Monatalban and his team of the UNIC, examplary stating close colleagues and friends such as the always good mooded technician Mireia, the mighty informative, multilingual and cohering manager Josep Graells and his colleague Dunja, the living football bibles Carlos and Hector, the capable blood-drawing nurses Rosalia and Maria Jesus, Hammad, Christina, Montse, Eva, and in particular, for scientific advices and vivid discussions extending basic research, Manolo Comabella. All further members of the department that have not been named here, are thanked as well. I thank Armand Sanchez from the Department of Animal and Food Science, University Autonoma of Barcelona, for providing me with appropriate tools for DNA quantitations, DNA pool construction and quality testing. Special thanks goes to the company deCODE in Reykjavik, who showed great hospitality scientificwise (providing with the in-house genetic map) and on the personal level (3 months of teaching genetics and still icelandic friendliness), particularly Aslaug Jonasdottir, Ragnaheidur Fossdal, Theodora Thorlacius, and Jeff Gulcher. Furthermore I would like to express profound thanks to Jaume Bertranpetit and Arcadi Navarro from the Evolutionary biology department of the University Pompeu Fabra, Barcelona, for regular invitations to genetic meetings and providing access to their high- throughput genotyping facilities (thank you as well, Roger and Anna). I thank Alastair Compston and Stephen Sawcer, Cambridge (UK), for creating GAMES and for being of scientific help long after. I thank Sergio Baranzini and Jorge Oksenberg from University of California San Francisco (USA), for poof-reading the dissertation and counselling on genetic questions. I thank very much my supervisor Elisabeth Knust for her patience and interest in my research field that does not overlap exceedingly well with cell polarity in Drosophila. I direct the same to Martin Beye who was so kind in accepting to be co-referee of this dissertation. I deeply thank my parents Elaine and Klaus for being a constant and sensitive support all through my scientific life, and before! Finally and above all, I thank my dearest wife Verena, who managed to perform a multitude of important deeds: encouraging throughout this devoted long time, counselling on dissertation design, and - most important – giving birth to our daughter Emily, who I also thank for cheering me up endlessly. Die hier vorgelegte Dissertation habe ich eigenständig und ohne unerlaubte Hilfe angefertigt. Die Dissertation wurde in der vorgelegten oder in ähnlicher Form noch bei keiner anderen Institution eingereicht. Ich habe bisher keine erfolglosen Promotionsversuche unternommen. Düsseldorf, den 19.01.2006 (Robert Goertsches) Content i 1 Introduction 1-22 1.1 Autoimmunity 2 1.1.1 Autoimmune disease (AID) 2 1.2 Autoimmune disease multiple sclerosis (MS) 3 1.2.1 Clinical aspects of MS 3 1.2.2 Pathological heterogeneity of MS 5 1.2.3 Immunological heterogeneity of MS 6 1.3 Genetic factors in autoimmune disease 8 1.3.1 Simple genetic traits associated with autoimmunity 8 1.3.2 Genetics of common autoimmune diseases 10 1.3.3 Genetic heterogeneity in autoimmune diseases 10 1.4 Epistatic interaction in complex traits 11 1.5 Model of inheritance of autoimmune disease susceptibility 12 1.6 Common genetic variation in the human genome and their genetic markers 13 1.7 Concept of “Linkage Disequilibrium” and “Haplotype” 14 1.8 Basic approaches toward disease gene identification 16 1.8.1 Identifying disease genes in MS 17 1.8.2 Linkage analysis in MS 18 1.8.3 Association analysis in MS 18 1.9 Genetic heterogeneity, inheritance model and susceptibility genes in MS 18 1.9.1 A model of inheritance for MS 18 1.9.2 The (genetic) epidemiology and etiology of MS 20 1.10 Aim and content of the dissertation 21 2 Material & Methods 23-62 2.1 Genomic DNA extraction from peripheral blood 24 2.2 Determination of DNA concentration and quality 26 2.3 DNA pool contruction based on fluorescence quantitation 26 2.3.1 Calibration of TKO 100 Mini-Fluorometer by means of calf thymus DNA 28 2.3.2 DNA sample preparation, quantification and appropriate dilution 29 2.3.3 DNA pool construction 29 ii Content iii 2.4 DNA pool genotyping by means of microsatellite markers 30 2.4.1 Storage and preparation of reagents for PCR assay 31 2.4.2 Polymerase amplification and thermal cycling 32 2.4.3 Gel electrophoresis of PCR products 33 2.5 Analysis of microsatellite marker genotyped DNA pools 34 2.5.1 Processing of data 34 2.5.2 Analysis of STR-genotyped DNA pools applying the Single Peak Approach 35 2.6 A sliding-window method for the detection of clusters of markers displaying evidence for association with MS 39 2.6.1 Processing of data 39 2.6.2 Analysis of STR-Genotyped DNA pool data by sliding windows 40 2.7 SNP-Genotyping principle: the 5' Nuclease assay 43 2.7.1 Concepts of 5’ Nuclease and Allelic Discrimination Assay 43 2.7.2 Preparation of DNA dilutions for PCR assays: 96- and 384-well plates 45 2.7.3 Preparation of reaction solution for PCR assay 47 2.7.4 Polymerase amplification and thermal cycling and end-point analysis 48 2.8 MS patients and controls 50 2.9 SNP selection for two genomic regions of interest 50 2.10 SNP-Genotyping data handling 53 2.10.1 Allelic discrimination 53 2.10.2 Real-time amplification data 54 2.11 Analytical tools for describing genomic structure and detecting disease association 57 2.11.1 Descriptive analyses 57 2.11.1.1 Establishing Hardy-Weinberg equilibrium (HWE) in population samples 57 2.11.1.2 Linkage Disequilibrium (LD) determination by software Haploview 58 ii Content iii 2.11.2 Case-control association analyses 58 2.11.2.1 Single SNP-disease association analyses 58 2.11.2.2 Haplotype-disease association analyses 59 2.12 Accounting for multiple testing 61 3 Results 63-102 3.1 Genotyping of DNA Pools with microsatellite markers 64 3.2 Application of sliding windows on DNA pool data 66 3.2.1 Descriptive part 66 3.2.2 Sieving MS candidate regions and genes 71 3.3 Genotyping of individual DNA by means of single nucleotide polymorphism marker 79 3.3.1 Yield of applied 5' Nuclease assay 79 3.3.2 Hardy-Weinberg equilibrium (HWE) in healthy control and multiple sclerosis population samples 81 3.3.3 Linkage Disequilibrium block formation at genomic regions of interest 3p25.3 and 10q22.1 81 3.3.4 Detection of statistical significance derived from allele and single genotype comparisons 84 3.3.5 Correction for multiple testing through Sequential Bonferroni 88 3.4 Single gene inspection: haplotype analysis 89 3.4.1 VGLL4 - Transcription cofactor vestigial-like protein 90 3.4.2 PRF1 – Perforin 91 3.4.3 ADAMTS14 - a disintegrin-like and metalloproteinase domain with thrombospondin type 1 modules 14 92 3.4.4 C10orf27 – Chromsome 10 open reading frame 27 96 3.5 Combined gene haplotypes based on ascertained data of ADAMTS14 and C10orf27 99 iv Content v 4 Discussion 103-122 4.1 A whole genome screen employing microsatellite markers and pooled DNA 104 4.2 284 candidate genes detected by “Sliding windows” 107 4.3 3p25.2: Apg7l and Vgll4 110 4.4 10q22.1: Perforin, ADAMTS14 and C10orf27 111 4.4.1 10q22.1: Intergenic haplotypes ADAMTS14 and C10orf27 115 4.5 Pros and Cons on association study design 116 4.5.1 Pros of association studies 116 4.5.2 Cons of association studies 117 4.6 Multiple testing and epistasis 119 4.7 Conclusion and outlook 120 5 Summary 123-124 6 Reference List 125-146 7 Appendix 147-280 Appendix A STR-Genotyping of individual DNA samples 148 Appendix B STR genotyping data from DNA pools 167 Appendix C Sliding window plots and synoptical tables 197 Appendix D Genes of interest derived from sliding windows 245 Appendix E Allele and genotype frequency distributions and corresponding statistics 249 Appendix F Haplotype and haplotype pair frequency distributions and corresponding statistics 259 iv Abbreviations v Abbreviations