Prof. Leena Peltonen, PI; Dr. Markus Perola, Prof. Jaakko Kaprio, Dr. Kari Kuulasmaa, Prof. Aarno Palotie, Finland
Prof. Kirsten Ohm Kyvik, Prof. Kaare Christensen, Denmark
Dr. Antonia Stazi, Italy
Prof. Dorret Boomsma, Prof. J. (Hans) C. van Houwelingen, The Netherlands
Dr. Jennifer Harris, Norway
Prof. Jan-Eric Litton, Prof. Nancy Pedersen, Prof. Ann-Christine Syvänen, Sweden
Prof. Alun Evans, Prof. Tim Spector, United Kingdom
Prof. Nick Martin, Australia

Twin cohorts provide a unique advantage for investigations of the role of genetics and environment in the etiology of complex traits. Co-twins share environment throughout critical fetal period and early years of life and twin design harmonizes this component of complex traits in a unique manner. The EU-funded GenomEUtwin consortium consists of 8 twin cohorts (Australian, Danish, Dutch, Finnish, Italian, Norwegian, UK and Swedish) with > 600000 twin pairs. Federated database with open source code has been created to share the data across the cohorts. This collaboration aims to create a solution for problems that arise when analyzing human study samples with inbuilt problems of poor epidemiological study design, ascertainment bias, lack of longitudinal follow up of the phenotypes studied and a tremendous amount of noise created by environmental variation throughout development, but particularly during foetal life and childhood.
The European twin data sets have advantages for genetic studies, unobtainable in regular family or case-control studies. First, members of twin pairs are perfectly correlated for age and many major environmental influences (in particular, intrauterine and childhood conditions), which are important factors in studying common traits. Second, members of twin cohorts participate actively in longitudinal studies, and their continued commitment to participating in twin cohorts reflects their favorable attitude towards research. Third, twins provide an easy access to collecting both information and biological samples from additional core family members. Fourth, paternity is generally more reliable than in other kinds of sibships. Fifth, concordant monozygotic (MZ) twin pairs are ideal for association studies and for determination of the genetic and environmental factors affecting disease development and also offer the unique opportunity to look for genes that influence trait variability (e.g. genes x environment interaction). Sixth, twin cohorts represent excellent population cohorts for which ascertainment-bias typically does not pose a problem because sample selection has not occurred with reference to any specific phenotype. Seventh, twin data are particularly valuable to conduct quantitative trait loci analyses.

Twin cohorts provide a unique advantage for investigations of the role of genetics and environment in the etiology of common traits. Co-twins share environment throughout critical fetal period and early years of life and twin design harmonizes this component of complex traits in a unique manner. The GenomEUtwin (www.genomeutwin.org) consortium consists of eight twin cohorts (Australian, Danish, Dutch, Finnish, Italian, Norwegian, UK and Swedish) with the total number of hundreds of thousands of twin pairs. We performed QTL analysis of stature (body height) using genome-wide scans performed for 7495 individuals with genome-wide microsatellite marker- and phenotype data: Australia (n=2609), Denmark (628), Finland (858), Netherlands (1086), Sweden (540) and United Kingdom (2212). The marker maps were combined and related to the sequence positions using computer program developed by us which uses DeCode genetic map markers as an anchoring set (www.bioinfo.helsinki.fi/cartographer). We used the program Merlin for variance components analysis with age, sex and country-of-origin as covariates. The covariate adjusted heritability was 90% for stature in the pooled data set. We found evidence for two major QTLs for human stature on 15q24 (LOD=3.75, 1-lod drop 11cm) and Xq25 (LOD=2.73, 15cM) and one for males only on chromosome 9. Especially the evidence for linkage for the X-chromosomal locus is contributed by most of the cohorts, thus suggesting an evolutionally old genetic variant having effect on the growth in European-based populations. The BMI of the cohorts is currently under analysis.

To understand the complex ways in which genes influence disease processes, such as cardiovascular disease development, we need large numbers of phenotyped and genotyped individuals. Such numbers can often only be obtained by collaboration of multiple research centres, sometimes even in different countries. The GenomEUtwin project entails a large-scale collaboration in eight countries with as one of its aims to understand the way genes influence cardiovascular disease risk. A first step in such an endeavour is to provide heritability estimates in the different countries for cardiovascular risk parameters, using the same method in each country. Such a procedure was used for body mass index (BMI) and blood pressure. Using the data of 37,000 complete twin pairs between ages 20-29 and 30-39 years we showed that heritability for BMI was mostly high (> 65%) and within the same range for the eight countries. Within one exception, there was no evidence for an influence of common environment on BMI. Data on opposite twins showed that there may be sex-specific genetic effects. Combining data of more than 4000 twins from seven countries we showed heritability for systolic blood pressure between 52% and 66% and for diastolic blood pressure between 44 and 66%. There was no evidence for an effect of common environment or sex-specific effects. These results lay the foundation for future gene hunting studies using linkage and association procedures.