Sara Lindstrom

Publications (47) View all

• Article: Genetic Variation in the Vitamin D Pathway in Relation to Risk of Prostate Cancer - Results from Breast and Prostate Cancer Cohort Consortium (BPC3).

  Alison M Mondul, Irene M Shui, Kai Yu, Ruth C Travis, Victoria L Stevens, Daniele Campa, Frederick Schumacher, Regina G Ziegler, H Bas Bueno-de-Mesquita, Sonja I Berndt, [......], Mark P Purdue, Meir J Stampfer, Stephanie J Weinstein, Walter Willett, Meredith Yeager, Stephen J Chanock, Dimitrios Trichopoulos, Laurence N Kolonel, Peter Kraft, Demetrius Albanes
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  ABSTRACT: BACKGROUND: Studies suggest that vitamin D status may be associated with prostate cancer risk, although the direction and strength of this association differs between experimental and observational studies. Genome-wide association studies have identified genetic variants associated with 25-hydroxyvitamin D (25(OH)D) status. We examined SNPs in four genes shown to predict circulating levels of 25(OH)D in relation to prostate cancer risk. METHODS: SNP markers localized to each of four genes (GC, CYP24A1, CYP2R1, and DHCR7) previously associated with 25(OH)D were genotyped in 10,018 cases and 11,052 controls from the NCI Breast and Prostate Cancer Cohort Consortium. Logistic regression was used to estimate the individual and cumulative association between genetic variants and risk of overall and aggressive prostate cancer. RESULTS: We observed a decreased risk of aggressive prostate cancer among men with the allele in rs6013897 near CYP24A1 associated with lower serum 25(OH)D (per A allele, OR=0.86, 95%CI=0.80-0.93, p-trend=0.0002), but an increased risk for non-aggressive disease (per a allele: OR=1.10, 95%CI=1.04-1.17, p-trend=0.002). Examination of a polygenic score of the four SNPs revealed statistically significantly lower risk of aggressive prostate cancer among men with a greater number of low vitamin D alleles (OR for 6-8 vs. 0-1 alleles = 0.66, 95% CI = 0.44 - 0.98; p-trend=0.003). CONCLUSIONS: In this large, pooled analysis, genetic variants related to lower 25(OH)D were associated with a decreased risk of aggressive prostate cancer. Impact: Our genetic findings do not support a protective association between loci known to influence vitamin D levels and prostate cancer risk.
  Cancer Epidemiology Biomarkers &amp Prevention 02/2013; · 4.12 Impact Factor
• Article: Identification of a novel percent mammographic density locus at 12q24.

  Kristen N Stevens, Sara Lindstrom, Christopher G Scott, Deborah Thompson, Thomas A Sellers, Xianshu Wang, Alice Wang, Elizabeth Atkinson, David N Rider, Jeanette E Eckel-Passow, [......], Jennifer Stone, Carmel Apicella, Peter Kraft, Susan E Hankinson, Aditi Hazra, David J Hunter, Douglas F Easton, Fergus J Couch, Rulla M Tamimi, Celine M Vachon
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  ABSTRACT: Percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer and has a heritable component that remains largely unidentified. We performed a three-stage genome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci associated with this trait. In stage 1, we combined three GWASs of percent density comprised of 1241 women from studies at the Mayo Clinic and identified the top 48 loci (99 single nucleotide polymorphisms). We attempted replication of these loci in 7018 women from seven additional studies (stage 2). The meta-analysis of stage 1 and 2 data identified a novel locus, rs1265507 on 12q24, associated with percent density, adjusting for age and BMI (P = 4.43 × 10(-8)). We refined the 12q24 locus with 459 additional variants (stage 3) in a combined analysis of all three stages (n = 10 377) and confirmed that rs1265507 has the strongest association in the 12q24 region (P = 1.03 × 10(-8)). Rs1265507 is located between the genes TBX5 and TBX3, which are members of the phylogenetically conserved T-box gene family and encode transcription factors involved in developmental regulation. Understanding the mechanism underlying this association will provide insight into the genetics of breast tissue composition.
  Human Molecular Genetics 04/2012; 21(14):3299-305. · 7.64 Impact Factor
• Article: Interactions between genome-wide significant genetic variants and circulating concentrations of insulin-like growth factor 1, sex hormones, and binding proteins in relation to prostate cancer risk in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium.

  Konstantinos K Tsilidis, Ruth C Travis, Paul N Appleby, Naomi E Allen, Sara Lindstrom, Fredrick R Schumacher, David Cox, Ann W Hsing, Jing Ma, Gianluca Severi, [......], Edward Giovannucci, David J Hunter, Peter Kraft, Meir J Stampfer, Graham G Giles, Gerald L Andriole, Sonja I Berndt, Stephen J Chanock, Richard B Hayes, Timothy J Key
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  ABSTRACT: Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. There is limited information on the mechanistic basis of these associations, particularly about whether they interact with circulating concentrations of growth factors and sex hormones, which may be important in prostate cancer etiology. Using conditional logistic regression, the authors compared per-allele odds ratios for prostate cancer for 39 GWAS-identified SNPs across thirds (tertile groups) of circulating concentrations of insulin-like growth factor 1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3), testosterone, androstenedione, androstanediol glucuronide, estradiol, and sex hormone-binding globulin (SHBG) for 3,043 cases and 3,478 controls in the Breast and Prostate Cancer Cohort Consortium. After allowing for multiple testing, none of the SNPs examined were significantly associated with growth factor or hormone concentrations, and the SNP-prostate cancer associations did not differ by these concentrations, although 4 interactions were marginally significant (MSMB-rs10993994 with androstenedione (uncorrected P = 0.008); CTBP2-rs4962416 with IGFBP-3 (uncorrected P = 0.003); 11q13.2-rs12418451 with IGF-1 (uncorrected P = 0.006); and 11q13.2-rs10896449 with SHBG (uncorrected P = 0.005)). The authors found no strong evidence that associations between GWAS-identified SNPs and prostate cancer are modified by circulating concentrations of IGF-1, sex hormones, or their major binding proteins.
  American journal of epidemiology 03/2012; 175(9):926-35. · 5.59 Impact Factor
• Article: Common breast cancer susceptibility variants in LSP1 and RAD51L1 are associated with mammographic density measures that predict breast cancer risk.

  Celine M Vachon, Christopher G Scott, Peter A Fasching, Per Hall, Rulla M Tamimi, Jingmei Li, Jennifer Stone, Carmel Apicella, Fabrice Odefrey, Gretchen L Gierach, [......], Agnieszka Bukowska, Edyta Reszka, JianJun Liu, Louise Eriksson, Kamila Czene, Tina Audley, Anna H Wu, V Shane Pankratz, John L Hopper, Isabel dos-Santos-Silva
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  ABSTRACT: Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures. We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status. Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07). We identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland. We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.
  Cancer Epidemiology Biomarkers &amp Prevention 03/2012; 21(7):1156-66. · 4.12 Impact Factor
• Article: Common genetic variants in prostate cancer risk prediction--results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3).

  Sara Lindström, Fredrick R Schumacher, David Cox, Ruth C Travis, Demetrius Albanes, Naomi E Allen, Gerald Andriole, Sonja I Berndt, Heiner Boeing, H Bas Bueno-de-Mesquita, [......], Dimitrios Trichopoulos, Jarmo Virtamo, Stephanie J Weinstein, Walter C Willett, Meredith Yeager, Richard B Hayes, Gianluca Severi, Christopher A Haiman, Stephen J Chanock, Peter Kraft
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  ABSTRACT: One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent single-nucleotide polymorphism markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer, and age. We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data. The best risk model (C-statistic = 0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P = 0.009), with highest accuracy in men younger than 60 years (C-statistic = 0.679). The absolute ten-year risk for 50-year-old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile). Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from prostate-specific antigen screening. Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.
  Cancer Epidemiology Biomarkers &amp Prevention 03/2012; 21(3):437-44. · 4.12 Impact Factor