A case-control study of peripheral blood mitochondrial DNA copy number and risk of renal cell carcinoma

ackground Low mitochondrial DNA (mtDNA) copy number is a common feature of renal cell carcinoma (RCC), and may influence tumor development. Results from a recent case-control study suggest that low mtDNA copy number in peripheral blood may be a marker for increased RCC risk. In an attempt to replicate that finding, we measured mtDNA copy number in peripheral blood DNA from a U.S. population-based case-control study of RCC. Methodology/Principal Findings Relative mtDNA copy number was measured in triplicate by a quantitative real-time PCR assay using DNA extracted from peripheral whole blood. Cases (n = 603) had significantly lower mtDNA copy number than controls (n = 603; medians 0.85, 0.91 respectively; P = 0.0001). In multiple logistic regression analyses, the lowest quartile of mtDNA copy number was associated with a 60% increase in RCC risk relative to the highest quartile (OR = 1.6, 95% CI = 1.1\u20132.2; Ptrend = 0.009). This association remained in analyses restricted to cases treated by surgery alone (OR Q1 = 1.4, 95% CI = 1.0\u20132.1) and to localized tumors (2.0, 1.3\u20132.8). Conclusions/Significance Our findings from this investigation, to our knowledge the largest of its kind, offer important confirmatory evidence that low mtDNA copy number is associated with increased RCC risk. Additional research is needed to assess whether the association is replicable in prospective studies

An analysis of growth, differentiation and apoptosis genes with risk of renal cancer

We conducted a case-control study of renal cancer (987 cases and 1298 controls) in Central and Eastern Europe and analyzed genomic DNA for 319 tagging single-nucleotide polymorphisms (SNPs) in 21 genes involved in cellular growth, differentiation and apoptosis using an Illumina Oligo Pool All (OPA). A haplotype-based method (sliding window analysis of consecutive SNPs) was used to identify chromosome regions of interest that remained significant at a false discovery rate of 10%. Subsequently, risk estimates were generated for regions with a high level of signal and individual SNPs by unconditional logistic regression adjusting for age, gender and study center. Three regions containing genes associated with renal cancer were identified: caspase 1/5/4/ 12(CASP 1/5/4/12), epidermal growth factor receptor (EGFR), and insulin-like growth factor binding protein-3 (IGFBP3). We observed that individuals with CASP1/5/4/12 haplotype (spanning area upstream of CASP1 through exon 2 of CASP5) GGGCTCAGT were at higher risk of renal cancer compared to individuals with the most common haplotype (OR:1.40, 95% CI:1.10-1.78, p-value = 0.007). Analysis of EGFR revealed three strong signals within intron 1, particularly a region centered around rs759158 with a global p = 0.006 (GGG: OR:1.26, 95% CI:1.04-1.53 and ATG: OR:1.55, 95% CI:1.14-2.11). A region in IGFBP3 was also associated with increased risk (global p = 0.04). In addition, the number of statistically significant (p-value 0.05) SNP associations observed within these three genes was higher than would be expected by chance on a gene level. To our knowledge, this is the first study to evaluate these genes in relation to renal cancer and there is need to replicate and extend our findings. The specific regions associated with risk may have particular relevance for gene function and/or carcinogenesis. In conclusion, our evaluation has identified common genetic variants in CASP1, CASP5, EGFR, and IGFBP3 that could be associated with renal cancer risk

Polycyclic aromatic hydrocarbons in residential dust and risk of childhood acute lymphoblastic leukemia

Several polycyclic aromatic hydrocarbons (PAHs) are known or probable human carcinogens. We evaluated the relationship between PAH exposure and risk of childhood acute lymphoblastic leukemia (ALL) using concentrations in residential dust as an exposure indicator. We conducted a population-based case-control study (251 ALL cases, 306 birth-certificate controls) in Northern and Central California from 2001–2007. We collected residential dust using a high volume small surface sampler (HVS3) (n=185 cases, 212 controls) or by sampling from participants’ household vacuum cleaners (n=66 cases, 94 controls). We evaluated log-transformed concentrations of 9 individual PAHs, the summed PAHs, and the summed PAHs weighted by their carcinogenic potency (the toxic equivalence). We calculated odds ratios (ORs) and 95% confidence intervals (CI) using logistic regression adjusting for demographic characteristics and duration between diagnosis/reference date and dust collection. Among participants with HVS3 dust, risk of ALL was not associated with increasing concentration of any PAHs (based on OR per ln(ng/g). Among participants with vacuum dust, we observed positive associations between ALL risk and increasing concentrations of benzo[a]pyrene (OR per ln[ng/g]=1.42, 95% CI=0.95, 2.12), dibenzo[a,h]anthracene (OR=1.98, 95% CI=1.11, 3.55), benzo[k]fluoranthene (OR=1.71, 95% CI= 0.91, 3.22), indeno[1,2,3-cd]pyrene (OR=1.81, 95% CI=1.04, 3.16), and the toxic equivalence (OR=2.35, 95% CI=1.18, 4.69). The increased ALL risk among participants with vacuum dust suggests that PAH exposure may increase the risk of childhood ALL; however, reasons for the different results based on HVS3 dust samples deserve further study

Risk of renal cell carcinoma in relation to blood telomere length in a population-based case-control study

BACKGROUND: There are few known risk factors for renal cell carcinoma (RCC). Two small hospital-based case-control studies suggested an association between short blood telomere length (TL) and increased RCC risk. METHODS: We conducted a large population-based case-control study in two metropolitan regions of the United States comparing relative TL in DNA derived from peripheral blood samples from 891 RCC cases and 894 controls. Odds ratios and 95% confidence intervals were estimated using unconditional logistic regression in both unadjusted and adjusted models. RESULTS: Median TL was 0.85 for both cases and controls (P=0.40), and no differences in RCC risk by quartiles of TL were observed. Results of analyses stratified by age, sex, race, tumour stage, and time from RCC diagnosis to blood collection were similarly null. In multivariate analyses among controls, increasing age and history of hypertension were associated with shorter TL (P<0.001 and P=0.07, respectively), and African Americans had longer TL than Caucasians (P<0.001). CONCLUSION: These data do not support the hypothesis that blood TL is associated with RCC. This population-based case-control study is, to our knowledge, the largest investigation to date of TL and RC

Inside the black box: Starting to uncover the underlying decision rules used in a one-by-one expert assessment of occupational exposure in case-control studies

Objectives Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participant's reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review and future use of these expert-based exposure decisions. Methods Classification and regression trees (CART, predictions from a single tree) and random forests ( predictions from many trees) were used to identify the underlying rules from the questionnaire responses, and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity and frequency. Data were split into training (n=10 488 jobs), testing (n=2247) and validation (n=2248) datasets. Results The CART and random forest models' predictions agreed with 92-94% of the expert's binary probability assignments. For ordinal probability, intensity and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86-90% and 57-85%, respectively) than for low or medium exposed jobs (7-71%). Conclusions CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs, and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent, and creates a mechanism to efficiently replicate exposure decisions in future studies

Comparison of algorithm-based estimates of occupational diesel exhaust exposure to those of multiple independent raters in a population-based case-control study

Objectives: Algorithm-based exposure assessments based on patterns in questionnaire responses and professional judgment can readily apply transparent exposure decision rules to thousands of jobs quickly. However, we need to better understand how algorithms compare to a one-by-one job review by an exposure assessor. We compared algorithm-based estimates of diesel exhaust exposure to those of three independent raters within the New England Bladder Cancer Study, a population-based case-control study, and identified conditions under which disparities occurred in the assessments of the algorithm and the raters.Methods: Occupational diesel exhaust exposure was assessed previously using an algorithm and a single rater for all 14 983 jobs reported by 2631 study participants during personal interviews conducted from 2001 to 2004. Two additional raters independently assessed a random subset of 324 jobs that were selected based on strata defined by the cross-tabulations of the algorithm and the first rater's probability assessments for each job, oversampling their disagreements. The algorithm and each rater assessed the probability, intensity and frequency of occupational diesel exhaust exposure, as well as a confidence rating for each metric. Agreement among the raters, their aggregate rating (average of the three raters' ratings) and the algorithm were evaluated using proportion of agreement, kappa and weighted kappa (κw). Agreement analyses on the subset used inverse probability weighting to extrapolate the subset to estimate agreement for all jobs. Classification and Regression Tree (CART) models were used to identify patterns in questionnaire responses that predicted disparities in exposure status (i.e., unexposed versus exposed) between the first rater and the algorithm-based estimates.Results: For the probability, intensity and frequency exposure metrics, moderate to moderately high agreement was observed among raters (κw = 0.50-0.76) and between the algorithm and the individual raters (κw = 0.58-0.81). For these metrics, the algorithm estimates had consistently higher agreement with the aggregate rating (κw = 0.82) than with the individual raters. For all metrics, the agreement between the algorithm and the aggregate ratings was highest for the unexposed category (90-93%) and was poor to moderate for the exposed categories (9-64%). Lower agreement was observed for jobs with a start year <1965 versus ≥1965. For the confidence metrics, the agreement was poor to moderate among raters (κw = 0.17-0.45) and between the algorithm and the individual raters (κw = 0.24-0.61). CART models identified patterns in the questionnaire responses that predicted a fair-to-moderate (33-89%) proportion of the disagreements between the raters' and the algorithm estimates.Discussion: The agreement between any two raters was similar to the agreement between an algorithm-based approach and individual raters, providing additional support for using the more efficient and transparent algorithm-based approach. CART models identified some patterns in disagreements between the first rater and the algorithm. Given the absence of a gold standard for estimating exposure, these patterns can be reviewed by a team of exposure assessors to determine whether the algorithm should be revised for future studies. © 2012 The Author