High throughput analysis of SNPs for the study of major complex traits and diseases.

It has become obvious that most common complex diseases and behavioural traits in humans are to a large extent heritable. Identification of the genes and relevant genetic variation involved, will reveal biological pathways determining these traits and diseases. Searching for these genes requires appropriate samples, innovative statistical methods, and state-of-the-art genotyping technology.Generally two approaches are combined to identify such genes. Systematic genome scans are performed to establish the smallest possible chromosomal region harbouring the gene. In the second approach candidate genes and genome regions are studied either by known, functional genetic variation or by unknown variants in an attempt to find the haplotype of the gene / chromosomal region carrying a functional variant. Fine mapping of loci identified in genome scans and candidate gene studies is performed by typing large numbers of di-allelic SNPs (Single Nucleotide Polymorphism) occurring at every 200-300 bases in the genome. A fast growing number of random SNPs, functional SNPs and SNPs that mark the haplotypes of genes in the population and LD blocks in the genome, is being identified and available in public and Celera databases.For several complex diseases, quantitative risk factors of disease and behavioural traits, VU/VUmc and LUMC study vast numbers of candidate genes and chromosomal regions resulting from genome scans in collaborative and separate projects. These include studies in rheumatoid- and osteoarthritis, cardiovascular disease, venous thrombosis, restenosis, migraine, depression, cognition, brain function, dementia and ageing/longevity. These studies are carried out in large cohorts/families of patients and healthy subjects and in mouse models. Both VU/VUmc and LUMC have put a major effort in establishing these lines of research. The ongoing studies aim to identify quantitative trait loci (QTLs) underlying these complex traits and diseases and also to test the clinical relevance of functional variants (associated e.g. with variations in gene expression, activity of gene product) such as establishing the percentage of patients that carry the gene variant, gene-environment interactions that influence disease risk, the pattern of disease progression of carriers of the variant, and the response to therapy.Many techniques are currently available for SNP typing; few however, allow cost effective typing of hundreds of SNPs in thousands of DNA samples, which is now required to make major progress. We apply for support for high throughput SNP typing by mass spectrometry, which is the most cost effective and flexible method that is currently automated for high throughput. This technology combines single base extension with mass-spectrometry (Mass ARRAY) and was successfully developed and applied by Sequenom Genetics in automated settings allowing for thousands of typings a day. Automation, accuracy and analysis are integrated into one of the cheapest operational systems available with the potential to perform typings even cheaper in the future. Especially attractive is the flexibility in handling both limited SNP numbers in large samples and large SNP numbers in limited sample sizes. We have developed the expertise for automated high throughput genome scanning and low to medium throughput SNP typing. Ample expertise in mass spectrometry for protein analysis and two mass spectrometers are available. We now apply for equipment to complete a fully functional facility for SNP typing up to 7.500 typings a day of a great diversity of SNPs in large groups of patients and in populations based samples using mass spec. Such cost effective SNP typing facility will allow synergistic typing projects in VU/VUmc and LUMC and the joint use of much of the equipment. The collaborative setting would be the first of its kind in The Netherlands and will be organised in an accessible fashion and facilitate many scientists at VU and LUMC as well as those at other collaborating universities.