Human Molecular Genetics Advance Access published online on February 4, 2008
Human Molecular Genetics, doi:10.1093/hmg/ddn034
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Identification of genetic variants that influence circulating IGF1 levels: a targeted search strategy
1 Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, Fulham Road, London, SW3 6JB, UK 2 Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK 3 Mutation Detection Facility, Cancer Research UK, St James's University Hospital, Leeds, LS9 7TF, UK 4 Gene Function and Regulation, Institute of Cancer Research, Fulham Road, London, SW3 6JB, UK 5 University Department of Clinical Science at North Bristol, Southmead Hospital, Bristol, BS10 5NB, UK 6 Academic Oncology Unit, Guy's Hospital, London, SE1 9RT, UK 7 Cancer Research UK Epidemiology and Genetics Group, The Institute of Cancer Research, Sutton, Surrey, SM2 5NG, UK
* To whom correspondence should be addressed at: Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, Fulham Road, London SW3 6JB, UK. Tel: +44(0)207 1535332; Fax: +44(0)2078783858; Email: claire.palles{at}icr.ac.uk
Received December 11, 2007; Revised January 30, 2008; Accepted January 30, 2008
An important class of genetic variants that affect disease susceptibility may lie within regulatory elements that influence gene expression. Regulatory sequences are difficult to identify and may be distant from the genes they regulate, but many lie within evolutionarily conserved regions (ECRs). We used comparative genomics to identify 12 ECRs up to 75 kb 5' to and within introns of IGF1. These were screened by high resolution melting curve analysis (MCA), and 18 single nucleotide polymorphisms (SNPs) were identified, including 5 novel variants. We analysed two large population-based series of healthy women to test the 9 SNPs with MAF>1% within ECRs. Three of the 9 SNPs within ECRs (rs35455143, rs35765817 and rs3839984) were significantly associated with circulating IGF1 levels in a multivariate analysis (p= 0.02 for each SNP, overall significance p<0.001). All three are uncommon SNPs (MAF= 10%) that lie more than 70 kb 5'of IGF. Two (rs35455143 and rs35765817) are in strong LD with each other, and appear to have opposite effects on circulating IGF1. Our results on a subset of other SNPs in or near IGF1 were consistent with previously reported associations with IGF1 levels, although only one (rs35767: p=0.05) was statistically significant. We believe that this is the first systematic study of an association between a phenotype and SNPs within ECRs extending over a large region adjacent to a gene. Targeting ECRs appears to be a useful strategy for identifying a subset of potentially functional non-coding regulatory SNPs.