A meta-analysis of Hodgkin lymphoma reveals 19p13.3 TCF3 as a novel susceptibility locus.

Recent genome-wide association studies (GWAS) of Hodgkin lymphoma (HL) have identified associations with genetic variation at both HLA and non-HLA loci; however, much of heritable HL susceptibility remains unexplained. Here we perform a meta-analysis of three HL GWAS totaling 1,816 cases and 7,877 controls followed by replication in an independent set of 1,281 cases and 3,218 controls to find novel risk loci. We identify a novel variant at 19p13.3 associated with HL (rs1860661; odds ratio (OR)=0.81, 95% confidence interval (95% CI) = 0.76-0.86, P(combined) = 3.5 × 10(-10)), located in intron 2 of TCF3 (also known as E2A), a regulator of B- and T-cell lineage commitment known to be involved in HL pathogenesis. This meta-analysis also notes associations between previously published loci at 2p16, 5q31, 6p31, 8q24 and 10p14 and HL subtypes. We conclude that our data suggest a link between the 19p13.3 locus, including TCF3, and HL risk.

Urinary tract infections and reduced risk of bladder cancer in Los Angeles.

We investigated the association between urinary tract infections (UTIs) and transitional cell carcinoma of the bladder in a population-based case-control study in Los Angeles covering 1586 cases and age-, gender-, and race-matched neighbourhood controls. A history of bladder infection was associated with a reduced risk of bladder cancer among women (odds ratio (OR), 0.66; 95% confidence interval (CI), 0.46-0.96). No effect was found in men, perhaps due to power limitations. A greater reduction in bladder cancer risk was observed among women with multiple infections (OR, 0.37; 95% CI, 0.18-0.78). Exclusion of subjects with a history of diabetes, kidney or bladder stones did not change the inverse association. A history of kidney infections was not associated with bladder cancer risk, but there was a weak association between a history of other UTIs and slightly increased risk among men. Our results suggest that a history of bladder infection is associated with a reduced risk of bladder cancer among women. Cytotoxicity from antibiotics commonly used to treat bladder infections is proposed as one possible explanation.

A linkage analysis of D17S74 (CMM86) in thirty-five families with premenopausal bilateral breast cancer.

We report here results of a linkage analysis of a marker in 35 families in which the proband had premenopausal bilateral breast cancer. This group is of particular interest given their high family risk and the question of etiological heterogeneity. Probands were ascertained from cancer registries in Los Angeles County and Connecticut and major hospitals in Montréal and Québec. Assuming no residual heterogeneity and summing lod scores over all families, we obtained strong evidence against tight linkage (e.g., lod score at theta = 0.000001 is -3.39). To address the issue of heterogeneity, we performed admixture and predivided sample analyses. Using an admixture model we were able to reject the hypothesis of no linkage versus that of linkage with homogeneity (P = 0.045). However, we were unable to reject the hypothesis of no linkage versus linkage with heterogeneity (P = 0.119) or to distinguish between linkage with homogeneity and linkage with heterogeneity (P = 0.500). Predivided sample analyses based upon age of onset, pathological characteristics, time between diagnoses of the breast cancers in each bilateral proband, and the span of ages at diagnoses within a family did not discriminate between apparently linked and unlinked families.

Correcting for variable age of onset in the estimation of familial relative risk when there is a secular trend in incidence of disease.

We discuss the effects that a secular trend in incidence would have on estimation of familial relative risk (ratio of observed to expected cumulative incidence among relatives of index cases). For example, when age-specific incidence rates of a condition have increased during the lifetimes of relatives among whom relative risk is to be estimated, familial relative risk will be biased downward if cross-sectional, age-specific incidence data are used to estimate expected cumulative incidence among relatives. The stronger the trend and the older the ages of unaffected relatives, the greater the bias will be. Incorporating different age-specific incidence curves for different birth cohorts into the analysis is an approach we suggest for correcting the bias.