Physical activity during adolescence and early adulthood and breast cancer risk before age 40 years.

BACKGROUND: Breast cancer (BC) incidence is increasing in women under age 40 years, underscoring the need for research on BC risk factors for younger women. METHODS: We used data from an international family cohort (n=26,348) to examine whether recreational physical activity (RPA) during adolescence and early adulthood are associated with BC risk before age 40. The cohort includes 2,502 women diagnosed with BC before age 40, including 2,408 diagnosed before study enrollment (68% within 5 years of enrollment). Women reported their average hours-per-week of moderate and strenuous RPA during adolescence (12-17 years) and early adulthood (25-34 years), which were converted to total age-adjusted metabolic equivalents-per-week and categorized into quartiles. We conducted attained age analyses until age 40 (follow-up time began at age 18) using Cox proportional hazards regression models adjusted for study center, race and ethnicity, and education. RESULTS: Being in the highest versus lowest quartile of RPA during adolescence and early adulthood were respectively associated with 12% [HR (95% CI): 0.88 (0.78, 0.98)] and 16% [HR (95% CI): 0.84 (0.74, 0.95) lower BC risks before age 40. Being in the highest quartile of RPA during both adolescence and early adulthood (Pearson correlation=0.52) versus neither timepoint was associated with a 22% lower risk [HR (95% CI): 0.78 (0.68, 0.89)]. CONCLUSIONS: Findings suggest that RPA during adolescence and early adulthood may lower BC risk before age 40. IMPACT: Policies promoting physical activity during adolescence and early adulthood may be important for reducing the growing burden of breast cancer in younger women.

Region-based analyses of existing genome-wide association studies identifies novel potential genetic susceptibility regions for glioma.

PURPOSE: Glioma is a rare and debilitating brain cancer with one of the lowest cancer survival rates. Genome-wide association studies have identified 34 genetic susceptibility regions. We sought to discover novel susceptibility regions using approaches which test groups of contiguous genetic markers simultaneously. PATIENTS AND METHODS: We analyzed data from three independent glioma studies of European ancestry, GliomaScan (1,316 cases/1,293 controls), AGOG (560 cases/2,237 controls), and GICC (4,000 cases/2,411 controls), using the machine-learning algorithm DEPTH and a region-based regression method based on the generalized Berk-Jones (GBJ) statistic, to assess the association of glioma with genomic regions by glioma type and sex. Summary statistics from the UCSF/Mayo Clinic study were used for independent validation. We conducted a meta-analysis using GliomaScan, AGOG, GICC and UCSF/Mayo. RESULTS: We identified 11 novel candidate genomic regions for glioma risk common to multiple studies. Two of the 11 regions, 16p13.3 containing RBFOX1 and 1p36.21 containing PRDM2, were significantly associated with female and male glioma risk respectively, based on results of the meta-analysis. Both regions have been previously linked to glioma tumor progression. Three of the 11 regions contain neurotransmitter receptor genes (7q31.33 GRM8, 5q35.2 DRD1, 15q13.3 CHRNA7). CONCLUSIONS: Our region-based approach identified 11 genomic regions that suggest association with glioma risk of which two regions, 16p13.3 and 1p36.21, warrant further investigation as genetic susceptibility regions for female and male risk respectively. Our analyses suggest that genetic susceptibility to glioma may differ by sex and highlights the possibility that synapse-related genes play a role in glioma susceptibility.

Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk.

BACKGROUND: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk, but variations in gene expression levels may also modify the effect of NSAID use. Therefore, we tested interactions between NSAID use and predicted gene expression levels in relation to colorectal cancer risk. METHODS: Genetically predicted gene expressions were tested for interaction with NSAID use on colorectal cancer risk among 19,258 colorectal cancer cases and 18,597 controls from 21 observational studies. A Mixed Score Test for Interactions (MiSTi) approach was used to jointly assess G × E effects which are modeled via fixed interaction effects of the weighted burden within each gene set (burden) and residual G × E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing. RESULTS: Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on colorectal cancer risk, including DPP10 (PG×E = 1.96 × 10-4), KRT16 (PG×E = 2.3 × 10-4), CD14 (PG×E = 9.38 × 10-4), and CYP27A1 (PG×E = 1.44 × 10-3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on colorectal cancer risk (PG×E = 3.23 × 10-5). No interactions were observed between predicted gene expression and nonaspirin NSAID use at FDR < 0.2. CONCLUSIONS: By incorporating functional information, we discovered several novel genes that interacted with NSAID use. IMPACT: These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on colorectal cancer.