Huang, Yifan

Abstract Whole genome amplification (WGA) offers a means to enrich DNA quantities for epidemiologic studies. We used an ovarian cancer study of 1,536 single nucleotide polymorphisms (SNPs) and 2,368 samples to assess performance of multiple displacement amplification (MDA) WGA using an Illumina GoldenGate BeadArray. Initial screening revealed successful genotyping for 93.4% of WGA samples and 99.3% of genomic samples, and 93.2% of SNPs for WGA samples and 96.3% of SNPs for genomic samples. SNP failure was predicted by Illumina-provided designability rank, %GC (P ≤ 0.002), and for WGA only, distance to telomere and Illumina-provided SNP score (P ≤ 0.002). Distance to telomere and %GC were highly correlated; adjustment for %GC removed the association between distance to telomere and SNP failure. Although universally high, per-SNP call rates were related to designability rank, SNP score, %GC, minor allele frequency, distance to telomere (P ≤ 0.01), and, for WGA only, Illumina-provided validation class (P < 0.001). We found excellent concordance generally (>99.0%) among 124 WGA:genomic replicates, 15 WGA replicates, 88 replicate aliquots of the same WGA preparation, and 25 genomic replicates. Where there was discordance, it was across WGA:genomic replicates but limited to only a few samples among other replicates suggesting the introduction of error. Designability rank and SNP score correlated with WGA:genomic concordance (P < 0.001). In summary, use of MDA WGA DNA is feasible; however, caution is warranted regarding SNP selection and analysis. We recommend that biological SNP characteristics, notably distance to telomere and GC content (<50% GC recommended), as well as Illumina-provided metrics be considered in the creation of GoldenGate assays using MDA WGA DNA. (Cancer Epidemiol Biomarkers Prev 2008;17(7):1781–9)

Abstract Aim: To examine the use of complementary and alternative medicine (CAM) by women with varying levels of familial and perceived risk of breast cancer with the goal of preventing breast cancer. Methods: Cross-sectional data on CAM use were collected on 2,198 women (mean age, 63 years) personally unaffected by breast cancer in the Minnesota Breast Cancer Family Study. CAM use was compared across women at high, moderate, or average risk based on family history, as well as across categories of perceived risk of breast cancer. CAM use was also examined in relation to screening and general health behaviors, worry about breast cancer, and optimism. Results: Half (49.5%) of the women reported using at least one CAM modality with the intent of preventing breast cancer. Univariate analyses indicated that greater overall CAM use was related to greater perceived risk (P = 0.018), more general health behaviors (P < 0.0001), more breast cancer screening behaviors (P = 0.0002), greater optimism (P = 0.0002), and higher educational attainment (P < 0.0001). Multivariate analysis revealed that general health behaviors (P < 0.0001), education (P = 0.0027), and optimism (P = 0.037) were significant predictors of CAM use when in the same model with perceived risk and breast cancer screening behaviors. Conclusions: Many women use CAM with the goal of preventing breast cancer. General health-promoting behaviors, education, and optimism predict CAM use. Evidence-based guidance is needed for the public and health care providers on the potential and limitations of specific CAM approaches to affect cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(6):1527–34)

Abstract Studies suggest that underglycosylation of the cell membrane mucin MUC1 may be associated with epithelial ovarian cancer. We identified 26 genes involved in glycosylation and examined 93 single nucleotide polymorphisms (SNP) with a minor allele frequency of ≥0.05 in relation to incident ovarian cancer. Cases were ascertained at the Mayo Clinic, Rochester, MN (n = 396) or a 48-county region in North Carolina (Duke University; n = 534). Ovarian cancer–free controls (n = 1,037) were frequency matched to the cases on age, race, and residence. Subjects were interviewed to obtain data on risk factors and a sample of blood for DNA and genotyped using the Illumina GoldenGate assay. We excluded subjects and individual SNPs with genotype call rates of <90%. Data were analyzed using logistic regression, with adjustment for age and residence. We fitted dominant, log additive, and recessive genetic models. Among Caucasians, nine SNPs in eight genes were associated with risk at P < 0.05 under at least one genetic model before adjusting for multiple testing. A SNP in GALNT1 (rs17647532) was the only one that remained statistically significant after Bonferroni adjustment for multiple testing but was not statistically significant in Hardy-Weinberg equilibrium among controls. Haplotype analyses revealed a global association of GALNT1 with risk (P = 0.038, under a recessive genetic model), which largely reflected a decreased risk of one haplotype (0.10 frequency; odds ratio, 0.07; P = 0.01) compared with the most common haplotype (0.39 frequency). These results suggest that genetic polymorphisms in the glycoslyation process may be novel risk factors for ovarian cancer. (Cancer Epidemiol Biomarkers Prev 2008;17(2):397–404)