Objective To investigate the association between genus β human papillomaviruses and the incidence of nonmelanocytic skin cancer in the general population. Design Population based case-control study. Setting New Hampshire, USA. Participants 2366 skin cancer cases and controls from the general population aged 25 to 74 years (663 squamous cell carcinoma, 898 basal cell carcinoma, 805 controls), with plasma samples tested for L1 antibodies to 16 genus β human papillomaviruses by multiplex serology. Main outcome measures Odds ratios for squamous cell carcinoma and basal cell carcinoma associated with seropositivity to β human papillomaviruses. Results Squamous cell carcinoma, but not basal cell carcinoma, cases had a higher prevalence of each of the individual β human papillomaviruses assayed compared with controls. The odds ratios for squamous cell carcinoma increased with the number of β types positive (odds ratio for one type positive 0.99 (95% confidence interval 0.74 to 1.33); two to three types positive 1.44 (1.03 to 2.01); four to eight types positive 1.51 (1.03 to 2.20); more than eight types positive 1.71 (1.12 to 2.62); P for trend (categorical)<0.001; P for trend (continuous) =0.003). With limited statistical power, the association was stronger among long term users of systemic glucocorticoids (odds ratio 3.21, 1.22 to 8.44) than among non-users (1.23, 0.97 to 1.55). Conclusions These findings support a relation between genus β human papillomavirus infection and the incidence of squamous cell carcinoma of the skin in the general population, as well as potential enhancement of risk by immunosuppression.

IMPORTANCE COVID-19 is a life-threatening illness for many patients. Prior studies have established hematologic cancers as a risk factor associated with particularly poor outcomes from COVID-19. To our knowledge, no studies have established a beneficial role for anti-COVID-19 interventions in this at-risk population. Convalescent plasma therapy may benefit immunocompromised individuals with COVID-19, including those with hematologic cancers.OBJECTIVE To evaluate the association of convalescent plasma treatment with 30-day mortality in hospitalized adults with hematologic cancers and COVID-19 from a multi-institutional cohort. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study using data from the COVID-19 and Cancer Consortium registry with propensity score matching evaluated patients with hematologic cancers who were hospitalized for COVID-19. Data were collected between

Tobacco smoking is the most important and well-established bladder cancer risk factor and a rich source of chemical carcinogens and reactive oxygen species that can induce damage to DNA in urothelial cells. Therefore, common variation in DNA repair genes might modify bladder cancer risk. In this study, we present results from meta-analyses and pooled analyses conducted as part of the International Consortium of Bladder Cancer. We included data on 10 single nucleotide polymorphisms corresponding to seven DNA repair genes from 13 studies. Pooled analyses and meta-analyses included 5,282 cases and 5,954 controls of non-Latino white origin. We found evidence for weak but consistent associations with ERCC2 D312N [rs1799793; per-allele odds ratio (OR), 1.10; 95% confidence interval (95% CI), 1.01-1.19; P = 0.021], NBN E185Q (rs1805794; per-allele OR, 1.09; 95% CI, 1.01-1.18; P = 0.028), and XPC A499V (rs2228000; per-allele OR, 1.10; 95% CI, 1.00-1.21; P = 0.044). The association with NBN E185Q was limited to ever smokers (interaction P = 0.002) and was strongest for the highest levels of smoking dose and smoking duration. Overall, our study provides the strongest evidence to date for a role of common variants in DNA repair genes in bladder carcinogenesis. [Cancer Res 2009;69(17):6857-64]

Introduction

One goal of personal genomics is to use information about genomic variation to predict who is at risk for various common diseases. Technological advances in genotyping have spawned several personal genetic testing services that market genotyping services directly to the consumer. An important goal of consumer genetic testing is to provide health information along with the genotyping results. This has the potential to integrate detailed personal genetic and genomic information into healthcare decision making. Despite the potential importance of these advances, there are some important limitations. One concern is that much of the literature that is used to formulate personal genetics reports is based on genetic association studies that consider each genetic variant independently of the others. It is our working hypothesis that the true value of personal genomics will only be realized when the complexity of the genotype-to-phenotype mapping relationship is embraced, rather than ignored. We focus here on complexity in genetic architecture due to epistasis or nonlinear gene-gene interaction. We have previously developed a multifactor dimensionality reduction (MDR) algorithm and software package for detecting nonlinear interactions in genetic association studies. In most prior MDR analyses, the permutation testing strategy used to assess statistical significance was unable to differentiate MDR models that captured only interaction effects from those that also detected independent main effects. Statistical interpretation of MDR models required post-hoc analysis using entropy-based measures of interaction information. We introduce here a novel permutation test that allows the effects of nonlinear interactions between multiple genetic variants to be specifically tested in a manner that is not confounded by linear additive effects. We show using data simulated across 35 different NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript epistasis models with varying effect sizes (heritabilities = 0.01, 0.025, 0.05, 0.1, 0.2, 0.3, 0.4) and sample sizes (n = 400, 800, 1600) that the power to detect interactions using the explicit test of epistasis is no different than a standard permutation test. We also show that the test has the appropriate size or type I error rate of approximately 0.05. We then apply MDR with the new explicit test of epistasis to a large genetic study of bladder cancer (n=914) and show that a previously reported nonlinear interaction between two XPD gene polymorphisms is indeed significant (P = 0.005), even after considering the strong additive effect of smoking in the model. Finally, we evaluated the power of the explicit test of epistasis to detect the nonlinear interaction between two XPD gene polymorphisms by simulating data from the MDR model of bladder cancer susceptibility. We show that the power to detect the interaction alone was 1.00 while the power to detect the independent effect of smoking alone was 0.06 which is close to the expected type I error ...