Sub theme 1.10
Population genomics of complex diseases

Goals of research: general outline
Scientific achievements
Future plans: special goals and approach
Running projects
Associated staff

Workgroup leaders   Department
PhD  J.B.J.  van  Meurs   Internal Medicine
Dr.  F.  Rivadeneira   Internal Medicine
Prof.Dr  A.G.  Uitterlinden   Internal Medicine

Goals of research: general outline

Complex diseases, such as diabetes, Alzheimer’s disease and osteoporosis, are major health problems in the world. They are common and chronic disorders, associated with substantial co-morbidity, and have vast implications for health care costs and economic viability of countries. Treatment and prevention options are usually very limited and there is urgent need for novel diagnostics and interventions. Genomic research can provide such opportunities through studies in large and deeply phenotyped cohorts applying high-throughput technology to analyse mainly DNA and RNA. The research of this programme is focusing on identification and characterization of genetic and genomic factors for common traits and diseases through large-scale population studies mostly organized in global consortia of collaborating investigators. Within this research programme we distinguish several research lines on specific diseases and phenotypes, with a particular focus on musculoskeletal diseases, while we also house a high-throughput genomics facility.

Scientific achievements

The Genetics Lab has a high-throughput human genotyping facility (DNA isolation, formatting, genotyping (Illumina SNP arrays, Sequenom, Taqman), and sequencing (3 Illumina GA2). The genetic lab is coordinating all molecular genetic analyses in the Rotterdam Study. Within this framework we are collaborating with many (large) epidemiological study populations at Erasmus MC, and abroad involved in several consortia on complex traits and diseases including ENGAGE, CHARGE, and GIANT. Prof. Uitterlinden is coordinator of the EU-sponsored GENOMOS/GEFOS consortium, involving >150.000 subjects to identify genetic risk factors for osteoporosis by prospective meta-analyses. He is also coordinator and PI of the NOW-Groot investments project that has allowed the creation of GWAS databases of the Rotterdam Study and the Generation R study with n=20,000 samples with data on >500,000 SNPs in each participant. He is also co-director (with Prof, Westendorp, LUMC) of the NGI sponsored “Netherlands Consortium for Healthy Ageing (NCHA)”.

Over the past 5 years our research in the area of locomotor diseases has been dominated by the work in the EU-sponsored consortia GENOMOS and GEFOS which we are both leading and coordinating. In these large data collections >45 groups from all over the world are collaborating on the genetics of osteoporosis. Similarly, we participate in the TREAT OA consortium -that has recently started- and which fulfils such a role for osteoarthritis genetic research. Also our role as founding cohort (with the GWAS data of the Rotterdam Study) of the so-called CHARGE consortium (with >45,000 GWAS samples from the Framingham Study, the AGES study, CHS and ARIC), allows us to lead in GWAS on many relevant phenotypes for OP and OA, such as age ate menopause and height. We were, for example, the first to report genetic loci for age at menopause by GWAS (Stolk et al., Nat Genetics, 2009).

Within the GEFOS, GENOMOS, and TREAT OA consortia we have been successful in providing robust evidence for the contribution of common variations to BMD and fracture risk, and more recently to OA features. Initially this was done by candidate gene testing (van Meurs et al., JAMA 2008), but more recently we have applied Genome Wide Association Studies (GWAS). GWAS has brought discoveries of 20 new genetic loci for BMD (Richards et al., Lancet 2008; Rivadeneira et al., Nat Genetics in press). For OA, we have recently identified the first genetic locus by GWAS (Kerkhof et al., Arth Rheum 2009, in press). Many of these loci form the start of research into the role of novel genes and proteins in BMD regulation, and perhaps also in other OP phenotypes. This will also involve testing such genes in the cell line models and animal models described under A. Although these are early days, these findings might bring new opportunities for therapeutic interventions for OP. On the other side we have also seen that the explained variance of these common variations for, e.g., BMD, is modest and therefore of no or very little clinical utility for predictive testing.

Our analysis of Homocysteine (Hcy) has demonstrated that increased Hcy levels predict future OP fractures (van Meurs et al., NEJM 2004), a finding that has been quickly replicated in several other studies such as the Framingham Study. Based on these relationships we are involved in a large intervention trial in the Netherlands (ZonMW sponsored; Prof. Lips, VU Amsterdam; Prof. de Groot, University of Wageningen), to investigate whether B vitamin supplementation can reduce fractures in an elderly population. This basic discovery has lead to clinical trials in a remarkable short period.

Future plans: special goals and approach

For genetic research, the near future will involve running GWAS in ever increasing larger sample sizes for more different phenotypes that are of interest for OP and OA, such as Hcy levels, vitamin D levels, ultrasound characteristics of bone, hip geometry, joint replacement, osteoporotic fractures etc. etc. While these efforts will surely identify novel genes of interest (which can be taken further for mechanistic research), they only concern identification of common genetic variants and then mostly single nucleotide polymorphisms (SNPs). However, SNPs are just one type of DNA variation, next to, e.g., Copy Number Variations (CNVs), Variable Number of Tandem Repeats (VNTRs), and methylation patterns. Therefore, we will also study these other types of genetic variations using the established GWAS datasets (for CNVs), or by de novo genotyping and array analysis. In addition, we have so fare focussed on common variations and have neglected rarer and very rare variants which are ill-detected by the current SNP arrays.

In addition, we are currently generating mRNA expression profiles of white blood cell mRNA of >1,000 Rotterdam Study participants. By combining this with the SNP array data, this will allow mapping of so-called eQTLs (SNPs explaining inter-individual differences in expression levels) and test the expression profiles for correlation with phenotypes.

Recently, we have obtained funding for acquisition of 3 Illumina Genome Analysers (GA2). This will allow us to start pilot projects in several hundred samples from the Rotterdam Study to start identify and analyse the role of rare variants in OP and OA. Within the setting of GENOMOS/GEFOS as well as, e.g., CHARGE application of this high throughput sequencing technology allows us to test new variants in large datasets. Finally, the ultimate goal is of course to generate full genome sequences of ALL participants of the Rotterdam Study (and Generation R). Given the very fast development of new sequencing technology, this goal might already be achieved in the next 5 years.

These newly discovered genetic variants will be tested in the cell line models and animal models described under A, for their role in bone biology, for example by combining these molecular profiles of mRNA and proteins in the cell-line models with GWAS data.

Most recent publications

1.     van Meurs JBJ, Dhonuske-Rutten RAM, Pluijn SMF, van der Klift M, de Jonge R, Lindemans J, de Groot LCPGM, Hofman A, Witteman JCM, van Leeuwen JPTM, Breteler MMB, Lips P, Pols HAP, Uitterlinden AG. Homocysteine levels and the risk of osteoporotic fracture. New Engl J Med 2004; 350: 2033-2041

2.      van Meurs JB, Trikalinos TA, Ralston SH, Balcells S, Brandi ML, Brixen K, Kiel DP, Langdahl BL, Lips P, Ljunggren O, Lorenc R, Obermayer-Pietsch B, Ohlsson C, Pettersson U, Reid DM, Rousseau F, Scollen S, Van Hul W, Agueda L, Akesson K, Benevolenskaya LI, Ferrari SL, Hallmans G, Hofman A, Husted LB, Kruk M, Kaptoge S, Karasik D, Karlsson MK, Lorentzon M, Masi L, McGuigan FE, Mellström D, Mosekilde L, Nogues X, Pols HA, Reeve J, Renner W, Rivadeneira F, van Schoor NM, Weber K, Ioannidis JP, Uitterlinden AG; GENOMOS Study. Large-scale analysis of association between LRP5 and LRP6 variants and osteoporosis. JAMA. 2008 Mar 19;299(11):1277-90.

3.      Richards JB, Rivadeneira F, Inouye M, Pastinen TM, Soranzo N, Wilson SG, Andrew T, Falchi M, Gwilliam R, Ahmadi KR, Valdes AM, Arp P, Whittaker P, Verlaan DJ, Jhamai M, Kumanduri V, Moorhouse M, van Meurs JB, Hofman A, Pols HA, Hart D, Zhai G, Kato BS, Mullin BH, Zhang F, Deloukas P, Uitterlinden AG, Spector TD. Bone mineral density, osteoporosis, and osteoporotic fractures: a genome-wide association study. Lancet. 2008 May 3;371(9623):1505-12.

4.  Stolk L, Zhai G, van Meurs JB, Verbiest MM, Visser JA, Estrada K, Rivadeneira F, Williams FM, Cherkas L, Deloukas P, Soranzo N, de Keyzer JJ, Pop VJ, Lips P, Lebrun CE, van der Schouw YT, Grobbee DE, Witteman J, Hofman A, Pols HA, Laven JS, Spector TD, Uitterlinden AG. Loci at chromosomes 13, 19 and 20 influence age at natural menopause. Nat Genet. 41, 645 - 647 (2009)

5.     Rivadeneira F, Styrkársdóttir U, Estrada K, Halldórsson BV,  Hsu Y-H, Richards JB, Zillikens MC, Kavvoura FK,  Amin N, Aulchenko YS, L. Cupples LA, Deloukas P, Demissie S, Grundberg E, Hofman A, Kong A, Karasik D, van Meurs JBJ, Oostra B, Pastinen T,  Pols HAP, Sigurdsson G, Soranzo N, Thorleifsson G, Thorsteinsdottir U, Williams FMK, Wilson SG, Zhou Y, Ralston SH, van Duijn CM, Spector T, Kiel DP, Stefansson K, Ioannidis JPA, Uitterlinden AG, for the GEnetic Factors For Osteoporosis (GEFOS) Consortium. Twenty bone mineral density loci identified by large-scale meta-analysis of genome-wide association studies. Nat Genet (2009), in press.