BACKGROUND: Insulin-like growth factor I (IGF-I) appears to play a role in prostate development and carcinogenesis. We investigated whether genetic variation at the IGF1 locus is associated with prostate cancer risk. METHODS: We sequenced IGF1 exons in germline DNA from 95 men with advanced prostate cancer to identify missense variants. IGF1 linkage disequilibrium patterns and common haplotypes were characterized by genotyping 64 single-nucleotide polymorphisms (SNPs) spanning 156 kilobases in 349 control subjects. Associations between IGF1 haplotypes and genotypes were investigated among 2320 patients with prostate cancer and 2290 control subjects from the Multiethnic Cohort. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by unconditional logistic regression to determine the association between prostate cancer and IGF1 haplotypes and genotypes. We used permutation testing to correct for multiple hypothesis testing. All statistical tests were two-sided. RESULTS: No IGF1 missense variants were observed. We identified four blocks of strong linkage disequilibrium and selected a subset of 29 tagging SNPs that could accurately predict both the common IGF1 haplotypes and the remaining SNPs. Haplotype analysis revealed nominally statistically significant associations with prostate cancer risk in each of the four haplotype blocks: haplotype 1B (OR = 1.21, 95% CI = 1.04 to 1.40), haplotype 2C (OR = 1.24, 95% CI = 1.06 to 1.44), haplotype 3C (OR = 1.25, 95% CI = 1.03 to 1.50), and haplotype 4D (OR = 1.19, 95% CI = 1.02 to 1.39). Two SNPs--rs7978742 (Ptrend = .002) and rs7965399 (Ptrend = .002)--were perfectly correlated (correlation coefficient = 1.0) with one another and also associated with prostate cancer risk. These two SNPs were strong proxies for haplotypes 1B, 2C, 3C, and 4D and could account for the haplotype findings. Permutation testing revealed that a similarly strong result would be observed by chance only 5.6% of the time. CONCLUSION: Inherited variation in IGF1 may play a role in the risk of prostate cancer.
BACKGROUND:Insulin-like growth factor I (IGF-I) appears to play a role in prostate development and carcinogenesis. We investigated whether genetic variation at the IGF1 locus is associated with prostate cancer risk. METHODS: We sequenced IGF1 exons in germline DNA from 95 men with advanced prostate cancer to identify missense variants. IGF1 linkage disequilibrium patterns and common haplotypes were characterized by genotyping 64 single-nucleotide polymorphisms (SNPs) spanning 156 kilobases in 349 control subjects. Associations between IGF1 haplotypes and genotypes were investigated among 2320 patients with prostate cancer and 2290 control subjects from the Multiethnic Cohort. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by unconditional logistic regression to determine the association between prostate cancer and IGF1 haplotypes and genotypes. We used permutation testing to correct for multiple hypothesis testing. All statistical tests were two-sided. RESULTS: No IGF1 missense variants were observed. We identified four blocks of strong linkage disequilibrium and selected a subset of 29 tagging SNPs that could accurately predict both the common IGF1 haplotypes and the remaining SNPs. Haplotype analysis revealed nominally statistically significant associations with prostate cancer risk in each of the four haplotype blocks: haplotype 1B (OR = 1.21, 95% CI = 1.04 to 1.40), haplotype 2C (OR = 1.24, 95% CI = 1.06 to 1.44), haplotype 3C (OR = 1.25, 95% CI = 1.03 to 1.50), and haplotype 4D (OR = 1.19, 95% CI = 1.02 to 1.39). Two SNPs--rs7978742 (Ptrend = .002) and rs7965399 (Ptrend = .002)--were perfectly correlated (correlation coefficient = 1.0) with one another and also associated with prostate cancer risk. These two SNPs were strong proxies for haplotypes 1B, 2C, 3C, and 4D and could account for the haplotype findings. Permutation testing revealed that a similarly strong result would be observed by chance only 5.6% of the time. CONCLUSION: Inherited variation in IGF1 may play a role in the risk of prostate cancer.
Authors: Kimberly E Alexander; Suzanne Chambers; Amanda B Spurdle; Jyotsna Batra; Felicity Lose; Tracy A O'Mara; Robert A Gardiner; Joanne F Aitken; Judith A Clements; Mary-Anne Kedda; Monika Janda Journal: Qual Life Res Date: 2015-02-28 Impact factor: 4.147
Authors: Fredrick R Schumacher; Iona Cheng; Matthew L Freedman; Lorelei Mucci; Naomi E Allen; Michael N Pollak; Richard B Hayes; Daniel O Stram; Federico Canzian; Brian E Henderson; David J Hunter; Jarmo Virtamo; Jonas Manjer; J Michael Gaziano; Laurence N Kolonel; Anne Tjønneland; Demetrius Albanes; Eugenia E Calle; Edward Giovannucci; E David Crawford; Christopher A Haiman; Peter Kraft; Walter C Willett; Michael J Thun; Loïc Le Marchand; Rudolf Kaaks; Heather Spencer Feigelson; H Bas Bueno-de-Mesquita; Domenico Palli; Elio Riboli; Eiliv Lund; Pilar Amiano; Gerald Andriole; Alison M Dunning; Dimitrios Trichopoulos; Meir J Stampfer; Timothy J Key; Jing Ma Journal: Hum Mol Genet Date: 2010-05-19 Impact factor: 6.150
Authors: L C Macleod; L J Chery; E Y C Hu; S B Zeliadt; S K Holt; D W Lin; M P Porter; J L Gore; J L Wright Journal: Prostate Cancer Prostatic Dis Date: 2015-03-31 Impact factor: 5.554
Authors: Chung-Jung Chiu; Yvette P Conley; Michael B Gorin; Gary Gensler; Chao-Qiang Lai; Fu Shang; Allen Taylor Journal: Invest Ophthalmol Vis Sci Date: 2011-11-25 Impact factor: 4.799
Authors: Stefan Lönn; Nathaniel Rothman; William R Shapiro; Howard A Fine; Robert G Selker; Peter M Black; Jay S Loeffler; Amy A Hutchinson; Peter D Inskip Journal: Neuro Oncol Date: 2008-06-18 Impact factor: 12.300
Authors: Aruna V Sarma; Rodney L Dunn; Leslie A Lange; Anna Ray; Yunfei Wang; Ethan M Lange; Kathleen A Cooney Journal: Prostate Date: 2008-02-15 Impact factor: 4.104
Authors: Heather M Ochs-Balcom; Caila B Vaughn; Jing Nie; Zhengyi Chen; Cheryl L Thompson; Niyati Parekh; Russell Tracy; Li Li Journal: Cancer Causes Control Date: 2013-11-06 Impact factor: 2.506