Integrating genomic approaches to understand ageing to understand genomic approaches Integrating ageing to understand genomic approaches Integrating IntegratingIntegrating genomicgenomic UitnodigingUitnodiging VoorVoor het het bijwonen bijwonen van van de de openbare openbare approachesapproaches toto verdedigingverdediging van van mijnmijn proefschrift proefschrift understandunderstand ageingageing “Integrating“Integrating genomicgenomic MarjoleinMarjolein J. J. Peters Peters approachesapproaches to to understandunderstand ageing” ageing” doordoor MarjoleinMarjolein J. J.Peters Peters [email protected]@hotmail.com ParanimfenParanimfen HannekeHanneke Kerkhof Kerkhof LisetteLisette Stolk Stolk WoensdagWoensdag 2323 maart maart 2016 2016 Marjolein J. Peters Marjolein J. Peters Marjolein J. omom 13.30 13.30 uur uur ErasmusErasmus Medisch Medisch Centrum Centrum ProfessorProfessor Andries Andries Queridozaal Queridozaal WytemawegWytemaweg 80 80 30153015 CN CN Rotterdam Rotterdam NaNa afloop afloop van van de de promotie promotie bentbent u uvan van harte harte uitgenodigd uitgenodigd voor voor dede receptie. receptie. Integrating Genomic Approaches to Understand Ageing Marjolein J. Peters 502007-L-bw-Peters ACKNOWLEDGEMENTS The work described in this thesis was conducted at the department of Internal Medicine at Erasmus University Medical Center Rotterdam. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University Rotterdam; the Netherlands Organization for Scientific Research (NWO); the Netherlands Organization for Health Research and Development (ZonMW); the Research Institute for Diseases in the Elderly (RIDE); the Dutch Ministry of Education, Culture and Science; the Dutch Ministry of Health, Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. Additional funding for the work described in this thesis was provided by the European Commission (HEALTH-F2-2008-201865, GEFOS; HEALTH-F2-2008 35627, TREAT-OA); Netherlands Organisation for Scientific Research (NWO) Investments (nr. 175.010.2005.011, 911-03-012); the Netherlands Consortium for Healthy Ageing (NCHA); the Netherlands Genomics Initiative (NGI) / Netherlands Organisation for Scientific Research (NWO) project nr. 050-060-810; and Vidi grant 917103521. The infrastructure for the CHARGE Consortium is supported in part by the National Heart, Lung, and Blood Institute grant R01HL105756. Financial support for the publication of this thesis was kindly provided by the Erasmus University Rotterdam, the Anna Foundation (Anna Fonds), Stichting Artrose Zorg, Pfizer, and Becton Dickinson (BD). Design and layout: Legatron Electronic Publishing, Rotterdam Printing: Ipskamp Printing, Enschede ISBN: 978-94-028-0061-6 © M.J. Peters, 2016 No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means, without permission from the author or, when appropriate, from the publisher of the publications. 502007-L-bw-Peters “Integrating Genomic Approaches to Understand Ageing” “Integratie van genomische onderzoeksmethodes om veroudering beter te begrijpen” Proefschrift ter verkrijging van de graad van doctor aan de Erasmus Universiteit Rotterdam op gezag van de rector magnificus Prof.dr. H.A.P. Pols en volgens besluit van het College voor Promoties. De openbare verdeding zal plaatsvinden op woensdag 23 maart 2016 om 13.30 uur door Maria Josephine (Marjolein) Peters geboren te Avereest 502007-L-bw-Peters PROMOTIECOMMISSIE Promotor: Prof.dr. A.G. Uitterlinden Overige leden: Prof.dr. J.H. Gribnau Prof.dr. O.H. Franco Prof.dr. L.H. Franke Copromotor: Dr. J.B.J. van Meurs Paranimfen: Dr. H.J.M. Kerkhof Dr. L. Stolk 502007-L-bw-Peters CONTENT Chapter 1 General Introduction 7 Chapter 2 Transcriptomic Studies 27 2.1 The transcriptional landscape of age in human peripheral blood 29 2.2 A meta-analysis of gene expression signatures of blood pressure 59 and hypertension 2.3 Meta-analysis of whole-blood gene expression associations 79 with circulating lipid levels 2.4 Gene transcripts associated with muscle strength: a CHARGE 105 meta-analysis of 7,781 persons Chapter 3 Combining genetic & genomic approaches 127 3.1 Systematic identification of trans-eQTLs as putative drivers of 129 known disease associations 3.2 Identification of non-coding RNA target genes through 151 trans-eQTL analysis Chapter 4 Genomic analysis integration for age-related musculoskeletal 175 comorbidities 4.1 Genome-wide association study meta-analysis of chronic 177 widespread pain: evidence for involvement of the 5p15.2 region 4.2 Genetics of the heat pain threshold in the general population 199 4.3 Associations between joint effusion in the knee and gene 215 expression levels in the circulation: a meta-analysis Chapter 5 General Discussion 233 Chapter 6 Summary 253 Samenvatting 259 Chapter 7 Bibliography 265 Authors and affiliations 277 About the author 301 Over de auteur 302 Dankwoord 303 502007-L-bw-Peters 502007-L-bw-Peters CHAPTER 1 General Introduction 502007-L-bw-Peters Chapter 1 Age is a major risk factor for many common diseases including cancer, cardiovascular disease, hypertension, osteoarthritis, and type 2 diabetes. The process of ageing is described as a decline in intrinsic physiological functioning over time, leading to an increased mortality rate [1]. All cells and tissues experience progressively decreased functioning over time, but it is not clear which of these changes are causal to age-related phenotypes and diseases. Although age is the most powerful risk factor for many common diseases, the underlying molecular mechanisms are still largely unknown. Biological theories of ageing are dived in two main groups: the programmed ageing theory and the theory of cellular ageing [2]. The programmed ageing theory suggests that ageing is regulated by biological clocks operating throughout lifespan. This regulation would depend on changes in gene expression that affect systems responsible for maintenance, repair, and defense responses. The second theory of cellular ageing is based on the concept that damage, either due to environmental impacts on living organisms, normal byproducts of metabolism, or inefficient repair systems accumulates throughout the lifespan, and causes ageing. Despite the recent advances in molecular biology and genetics, the mysteries that control human lifespan are yet to be unraveled [3]. AGEING RESEARCH IN ANIMAL MODELS The first studies into the regulation of lifespan were performed in animal models, such as yeast (Saccharomyces cerevisiae), round worms (Caenorhabditis elegans), fruit flies (Drosophila melanogaster), and mice (Mus musculus). Genetically engineered animals allow for better understanding of the molecular mechanisms of ageing. An example is a mouse model that expresses a proofreading deficient form of the mitochondrial DNA (mtDNA) polymerase [4]. The mutation resulted in randomly accumulated mtDNA mutations during the course of mitochondrial biosynthesis. The mice displayed a normal phenotype at birth and early adolescence, but subsequently acquired many features of premature ageing (such as weight loss, reduced subcutaneous fat, osteoporosis, anemia, reduced fertility, and heart enlargement) and had a reduced lifespan. These results demonstrate that the accumulation of mtDNA mutations leads to premature ageing in mice. In addition, a significant decrease in the mitochondrial energetic capacity with ageing has been identified in yeast, round worms, and fruit flies [5]. Finally, a study in human volunteers showed that the mtDNA content in muscle declined with ageing [6]. They found reduced levels of mitochondrial gene transcripts and proteins, and a declined capacity for mitochondrial energy production, resulting in lower physical function and higher insulin resistance, both more common in the elderly. Animal models are still instrumental in studying the molecular mechanisms of disease processes: the short life span of some model species enable longitudinal studies and experimental manipulations [7]. While these studies have been crucial for the identification of some ageing regulating genes and pathways, a limitation is that the findings can be difficult to translate to human ageing. The Ageing Gene Database (GenAge) provides a publically available manually curated collection of all genes related to longevity and ageing in model organisms [8]. Today, about 300 human genes and about 2,000 genes in animals have been related to longevity and/or ageing. 8 502007-L-bw-Peters General Introduction AGEING RESEARCH USING CELL LINES Next to animal studies, cell culture studies have been used to study ageing. In 1961, Hayflick et 1 al. [9] discovered that human fibroblasts derived from embryonic tissues could only divide a finite number of times in culture, a phenomena called “replicative senescence”. In 1990, Harley et al. found that telomeres (repetitive sequences at the end of your chromosomes) shorten at each passage. The telomere length contributes to the stabilization of the telomeres, and is the key in avoiding replicative senescence [10]. Recently, scientists in Japan were able to either accelerate the process of ageing within human fibroblast cell lines, or to reverse the process of ageing [11]. They targeted two genes (GCAT and SHMT2) that produce the amino acid glycine in the mitochondria, and by reprogramming the fibroblast cell lines the researchers restored age-associated respiration defects. Yet, the connection between the in vitro findings and the ageing