| 1. |
- Jacobs, Kevin B, et al.
(författare)
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Detectable clonal mosaicism and its relationship to aging and cancer.
- 2012
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Ingår i: Nature Genetics. - New York : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 44:6, s. 651-658
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Tidskriftsartikel (refereegranskat)abstract
- In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases.
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| 2. |
- Joshi, Amit D., et al.
(författare)
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Additive interactions between susceptibility single-nucleotide polymorphisms identified in genome-wide association studies and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium
- 2014
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Ingår i: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 180:10, s. 1018-1027
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Tidskriftsartikel (refereegranskat)abstract
- Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 x 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.
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| 3. |
- Lindstroem, Sara, et al.
(författare)
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Common genetic variants in prostate cancer risk prediction-results from the NCI breast and prostate cancer cohort consortium (BPC3)
- 2012
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:3, s. 437-444
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Tidskriftsartikel (refereegranskat)abstract
- Background: 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.Methods: 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.Results: 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).Conclusions: 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.Impact: Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.
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| 4. |
- Lindstrom, Sara, et al.
(författare)
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Characterizing Associations and SNP-Environment Interactions for GWAS-Identified Prostate Cancer Risk Markers-Results from BPC3
- 2011
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:2
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade) and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10(-28)). Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test), where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade,8) tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.
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| 5. |
- Sampson, Joshua N., et al.
(författare)
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Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
- 2015
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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| 6. |
- Wang, Zhaoming, et al.
(författare)
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Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33
- 2014
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:24, s. 6616-6633
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
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