15 research outputs found

    Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

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    Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice

    CYP2A6 activity and cigarette consumption interact in smoking-related lung cancer susceptibility.

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    Cigarette smoke, containing both nicotine and carcinogens, causes lung cancer. However, not all smokers develop lung cancer, highlighting the importance of the interaction between host susceptibility and environmental exposure in tumorigenesis. Here, we aimed to delineate the interaction between metabolizing ability of tobacco carcinogens and smoking intensity in mediating genetic susceptibility to smoking-related lung tumorigenesis. Single-variant and gene-based associations of 43 tobacco carcinogen-metabolizing genes with lung cancer were analyzed using summary statistics and individual-level genetic data, followed by causal inference of Mendelian randomization, mediation analysis, and structural equation modeling. Cigarette smoke-exposed cell models were used to detect gene expression patterns in relation to specific alleles. Data from the International Lung Cancer Consortium (29,266 cases and 56,450 controls) and UK Biobank (2,155 cases and 376,329 controls) indicated that the genetic variant rs56113850 C>T located in intron 4 of CYP2A6 was significantly associated with decreased lung cancer risk among smokers [odds ratio (OR) = 0.88, 95% confidence interval = 0.85-0.91, P = 2.18Ă—10-16], which might interact (Pinteraction = 0.028) with and partially be mediated (ORindirect = 0.987) by smoking status. Smoking intensity accounted for 82.3% of the effect of CYP2A6 activity on lung cancer risk but entirely mediated the genetic effect of rs56113850. Mechanistically, the rs56113850 T allele rescued the downregulation of CYP2A6 caused by cigarette smoke exposure, potentially through preferential recruitment of transcription factor HLTF. Together, this study provides additional insights into the interplay between host susceptibility and carcinogen exposure in smoking-related lung tumorigenesis

    Postdiagnosis BMI Change Is Associated with Non-Small Cell Lung Cancer Survival

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    Background: Body mass index (BMI) change after a lung cancer diagnosis has been associated with non-small cell lung cancer (NSCLC) survival. This study aimed to quantify the association based on a large-scale observational study. Methods: Included in the study were 7,547 patients with NSCLC with prospectively collected BMI data from Massachusetts General Hospital and Brigham and Women's Hospital/Dana-Farber Cancer Institute. Cox proportional hazards regression with time-dependent covariates was used to estimate effect of time-varying postdiagnosis BMI change rate (% per month) on overall survival (OS), stratified by clinical subgroups. Spline analysis was conducted to quantify the nonlinear association. A Mendelian Randomization (MR) analysis with a total of 3,495 patients further validated the association. Results: There was a J-shape association between postdiagnosis BMI change and OS among patients with NSCLC. Specifically, a moderate BMI decrease [0.5-2.0; HR = 2.45; 95% confidence interval (CI), 2.25-2.67] and large BMI decrease (≥2.0; HR = 4.65; 95% CI, 4.15-5.20) were strongly associated with worse OS, whereas moderate weight gain (0.5-2.0) reduced the risk for mortality (HR = 0.78; 95% CI, 0.68-0.89) and large weight gain (≥2.0) slightly increased the risk of mortality without reaching statistical significance (HR = 1.10; 95% CI, 0.86-1.42).MR analyses supported the potential causal roles of postdiagnosis BMI change in survival. Conclusions: This study indicates that BMI change after diagnosis was associated with mortality risk
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