Melbourne School of Population and Global Health - Research Publications

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Author: English, Dallas × Author: Southey, Melissa × End date: 2009 × Start date: 2008 ×

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    Heterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics
    Garcia-Closas, M ; Hall, P ; Nevanlinna, H ; Pooley, K ; Morrison, J ; Richesson, DA ; Bojesen, SE ; Nordestgaard, BG ; Axelsson, CK ; Arias, JI ; Milne, RL ; Ribas, G ; Gonzalez-Neira, A ; Benitez, J ; Zamora, P ; Brauch, H ; Justenhoven, C ; Hamann, U ; Ko, Y-D ; Bruening, T ; Haas, S ; Doerk, T ; Schuermann, P ; Hillemanns, P ; Bogdanova, N ; Bremer, M ; Karstens, JH ; Fagerholm, R ; Aaltonen, K ; Aittomaki, K ; Von Smitten, K ; Blomqvist, C ; Mannermaa, A ; Uusitupa, M ; Eskelinen, M ; Tengstrom, M ; Kosma, V-M ; Kataja, V ; Chenevix-Trench, G ; Spurdle, AB ; Beesley, J ; Chen, X ; Devilee, P ; Van Asperen, CJ ; Jacobi, CE ; Tollenaar, RAEM ; Huijts, PEA ; Klijn, JGM ; Chang-Claude, J ; Kropp, S ; Slanger, T ; Flesch-Janys, D ; Mutschelknauss, E ; Salazar, R ; Wang-Gohrke, S ; Couch, F ; Goode, EL ; Olson, JE ; Vachon, C ; Fredericksen, ZS ; Giles, GG ; Baglietto, L ; Severi, G ; Hopper, JL ; English, DR ; Southey, MC ; Haiman, CA ; Henderson, BE ; Kolonel, LN ; Le Marchand, L ; Stram, DO ; Hunter, DJ ; Hankinson, SE ; Cox, DG ; Tamimi, R ; Kraft, P ; Sherman, ME ; Chanock, SJ ; Lissowska, J ; Brinton, LA ; Peplonska, B ; Klijn, JGM ; Hooning, MJ ; Meijers-Heijboer, H ; Collee, JM ; Van den Ouweland, A ; Uitterlinden, AG ; Liu, J ; Lin, LY ; Yuqing, L ; Humphreys, K ; Czene, K ; Cox, A ; Balasubramanian, SP ; Cross, SS ; Reed, MWR ; Blows, F ; Driver, K ; Dunning, A ; Tyrer, J ; Ponder, BAJ ; Sangrajrang, S ; Brennan, P ; Mckay, J ; Odefrey, F ; Gabrieau, V ; Sigurdson, A ; Doody, M ; Struewing, JP ; Alexander, B ; Easton, DF ; Pharoah, PD ; Leal, SM (PUBLIC LIBRARY SCIENCE, 2008-04)
    A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding the etiologic heterogeneity of breast cancer may ultimately result in improvements in prevention, early detection, and treatment.
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    SNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis
    Constantine, CC ; Gurrin, LC ; McLaren, CE ; Bahlo, M ; Anderson, GJ ; Vulpe, CD ; Forrest, SM ; Allen, KJ ; Gertig, DM (BMC, 2008-03-20)
    BACKGROUND: We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis. METHODS: We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform. RESULTS: Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r2 from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays. CONCLUSION: A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.