title: Identification of genetic variants that influence circulating IGF1 levels: a targeted search strategy.
abstract: 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, and 18 single-nucleotide polymorphisms (SNPs) were identified, including five novel variants. We analysed two large population-based series of healthy women to test the nine SNPs with minor allele frequency (MAF) >1% within ECRs. Three of the nine SNPs within ECRs (rs35455143, rs35765817 and rs3839984) were significantly associated with circulating IGF1 levels in a multivariate analysis (P <or= 0.02 for each SNP, overall significance P < 0.001). All three are uncommon SNPs (MAF <or= 10%) that lie >70 kb 5' of IGF1. 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.
authors.affiliation: Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, Fulham Road, London SW3 6JB, UK. claire.palles@icr.ac.uk
authors.forename: Claire
authors.initials: C
authors.lastname: Palles
authors.forename: Nichola
authors.initials: N
authors.lastname: Johnson
authors.forename: Ben
authors.initials: B
authors.lastname: Coupland
authors.forename: Claire
authors.initials: C
authors.lastname: Taylor
authors.forename: Jaime
authors.initials: J
authors.lastname: Carvajal
authors.forename: Jeff
authors.initials: J
authors.lastname: Holly
authors.forename: Ian S
authors.initials: IS
authors.lastname: Fentiman
authors.forename: Isabel dos Santos
authors.initials: Idos S
authors.lastname: Silva
authors.forename: Alan
authors.initials: A
authors.lastname: Ashworth
authors.forename: Julian
authors.initials: J
authors.lastname: Peto
authors.forename: Olivia
authors.initials: O
authors.lastname: Fletcher
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000818:Animals; D001483:Base Sequence; D017124:Conserved Sequence; D005260:Female; D005828:Genetics, Population; D015894:Genome, Human; D023281:Genomics; D005838:Genotype; D006801:Humans; D007334:Insulin-Like Growth Factor I / Q000032:analysis / Q000235:genetics* / Q000378:metabolism*; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D017422:Sequence Analysis, DNA
chemical_list: D007334:Insulin-Like Growth Factor I