Red and Processed Meat Intake, Polygenic Risk and the Prevalence of Colorectal Neoplasms: Results from a Screening Colonoscopy Population.

High red and processed meat intake and genetic predisposition are risk factors of colorectal cancer (CRC). However, evidence of their independent and joint associations on the risk of colorectal neoplasms is limited. We assessed these associations among 4774 men and women undergoing screening colonoscopy. Polygenic risk scores (PRSs) were calculated based on 140 loci related to CRC. We used multiple logistic regression models to evaluate the associations of red and processed meat intake and PRS with the risk of colorectal neoplasms. Adjusted odds ratios (aORs) were translated to genetic risk equivalents (GREs) to compare the strength of the associations with colorectal neoplasm risk of both factors. Compared to ≤1 time/week, processed meat intake >1 time/week was associated with a significantly increased risk of colorectal neoplasm [aOR (95% CI): 1.28 (1.12-1.46)]. This risk increase was equivalent to the risk increase associated with a 19 percentile higher PRS. The association of red meat intake with colorectal neoplasm was weaker and did not reach statistical significance. High processed meat intake and PRS contribute to colorectal neoplasm risk independently. Limiting processed meat intake may offset a substantial proportion of the genetically increased risk of colorectal neoplasms.

Excess Weight, Polygenic Risk Score, and Findings of Colorectal Neoplasms at Screening Colonoscopy.

INTRODUCTION: Excess weight is an established risk factor of colorectal cancer (CRC). However, evidence is lacking on how its impact varies by polygenic risk at different stages of colorectal carcinogenesis. METHODS: We assessed the individual and joint associations of body mass index (BMI) and polygenic risk scores (PRSs) with findings of colorectal neoplasms among 4,784 participants of screening colonoscopy. Adjusted odds ratios (aORs) for excess weight derived by multiple logistic regression were converted to genetic risk equivalents (GREs) to quantify the impact of excess weight compared with genetic predisposition. RESULTS: Overweight and obesity (BMI 25-<30 and ≥30 kg/m 2 ) were associated with increased risk of any colorectal neoplasm (aOR [95% confidence interval, CI] 1.26 [1.09-1.45] and 1.47 [1.24-1.75]). Obesity was associated with increased risk of advanced colorectal neoplasm (aOR [95% CI] 1.46 [1.16-1.84]). Dose-response relationships were seen for the PRS (stronger for advanced neoplasms than any neoplasms), with no interaction with BMI, suggesting multiplicative effects of both factors. Obese participants with a PRS in the highest tertile had a 2.3-fold (95% CI 1.7-3.1) and 2.9-fold (95% CI 1.9-4.3) increased risk of any colorectal neoplasm and advanced colorectal neoplasm, respectively. The aOR of obesity translated into a GRE of 38, meaning that its impact was estimated to be equivalent to the risk caused by 38 percentiles higher PRS for colorectal neoplasm. DISCUSSION: Excess weight and polygenic risk are associated with increased risk of colorectal neoplasms in a multiplicative manner. Maintaining normal weight is estimated to have an equivalent effect as having 38 percentiles lower PRS.

Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk.

BACKGROUND: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk. METHODS: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated. RESULTS: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10-8). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%-4.0%) vs 6.1% (5.7%-6.5%) (difference 2.4%, P-value = 1.83 × 10-14); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%-1.8%) vs 2.2% (1.9%-2.4%) (difference 0.6%, P-value = 1.01 × 10-3), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk. CONCLUSIONS: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use.

Hyperbolic graph convolutional neural network with contrastive learning for automated ICD coding.

The International Classification of Diseases (ICD) is a widely used criterion for disease classification, health monitoring, and medical data analysis. Deep learning-based automated ICD coding has gained attention due to the time-consuming and costly nature of manual coding. The main challenges of automated ICD coding include imbalanced label distribution, code hierarchy and noisy texts. Recent works have considered using code hierarchy or description for better label representation to solve the problem of imbalanced label distribution. However, these methods are still ineffective and redundant since they only interact with a constant label representation. In this work, we introduce a novel Hyperbolic Graph Convolutional Network with Contrastive Learning (HGCN-CL) to solve the above problems and the shortcomings of the previous methods. We adopt a Hyperbolic graph convolutional network on ICD coding to capture the hierarchical structure of codes, which can solve the problem of large distortions when embedding hierarchical structure with graph convolutional network. Besides, we introduce contrastive learning for automatic ICD coding by injecting code features into text encoder to generate hierarchical-aware positive samples to solve the problem of interacting with constant code features. We conduct experiments on the public MIMIC-III and MIMIC-II datasets. The results on MIMIC III show that HGCN-CL outperforms previous state-of-art methods for automatic ICD coding, which achieves a 2.7% and 3.6% improvement respectively compared to previous best results (Hypercore). We also provide ablation experiments and hierarchy visualization to verify the effectiveness of components in our model.

Personalized Initial Screening Age for Colorectal Cancer in Individuals at Average Risk.

Importance: Colorectal cancer (CRC) risk varies widely in the population at average risk without a family history, but there are no established routines for translating this variation into personalized starting ages of screening. Objective: To illustrate derivation of risk-adapted starting ages of CRC screening based on the concept of risk advancement period (RAP) using sex and a polygenic risk score (PRS) as an example. Design, Setting, and Participants: This cohort study included participants in the UK Biobank study recruited in England, Wales, and Scotland between March 13, 2006, and October 1, 2010. Participants were aged 40 to 69 years, with no previous bowel cancer screening and no family history of CRC. Follow-up of cancer data was completed February 29, 2020, for England and Wales and January 31, 2021, for Scotland. The censoring date for death data was September 30, 2021, for England and Wales and October 31, 2021, for Scotland. Exposures: Data on age, sex, and family history were collected at the baseline interview. A PRS was calculated based on 139 CRC-related risk loci. Main Outcomes and Measures: Hazard ratios (HRs) of sex and PRS with CRC risk and mortality were estimated using Cox proportional hazards regression models and were translated to RAPs to quantify how many years of age earlier or later men and individuals in higher or lower PRS deciles would reach risks comparable with those of the reference group (ie, women or those in the 5th and 6th PRS deciles). Results: Among 242 779 participants (median age, 55 [IQR, 48-61] years; 55.7% women), 2714 incident CRC cases were identified during a median follow-up of 11.2 (IQR, 10.5-11.8) years and 758 deaths during a median follow-up of 12.8 (IQR, 12.0-13.4) years. The HRs of CRC risk were 1.57 (95% CI, 1.46-1.70) for men vs women and ranged from 0.51 (95% CI, 0.41-0.62) to 2.29 (95% CI, 2.01-2.62) across PRS deciles compared with the reference. The RAPs were 5.6 (95% CI, 4.6-6.6) years for men vs women and ranged from -8.4 (95% CI, -11.0 to -5.9) to 10.3 (95% CI, 8.5-12.1) years across PRS deciles compared with the reference deciles. Risk-adapted starting ages of screening would vary by 24 years between men in the highest PRS decile and women in the lowest PRS decile. Similar results were obtained regarding CRC mortality. Conclusions and Relevance: In this large cohort study including women and men at average risk of CRC, risk-adapted starting ages of screening strongly varied by sex and a PRS. The RAP concept could easily accommodate additional factors for defining personalized starting ages of screening.

Probing the diabetes and colorectal cancer relationship using gene - environment interaction analyses.

BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.

A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk.

Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. SIGNIFICANCE: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.

Overall and age-specific risk advancement periods of colorectal cancer for men vs women: Implications for gender-sensitive screening offers?

Colorectal cancer (CRC) incidence and mortality are higher among men than among women. We aimed to estimate overall and age-specific risk advancement periods (RAPs) for men compared to women, which quantify how many years earlier comparable levels of risk are reached by men. RAPs were derived by Cox regression models among 331 224 participants aged 40 to 69 at baseline of the UK Biobank with no previous diagnosis of CRC and no previous CRC screening examination who were followed with respect to CRC incidence for up to 13 years. Men were at substantially higher risk of CRC than women in age groups 50 to 59 and 60 to 69, with RAPs (95% confidence intervals) as high as 8.7 (4.5-13.0) and 6.2 (4.5-7.9), respectively. These RAPs were higher than those for family history of CRC in these age groups. By contrast, no significant sex difference but a major impact of family history was seen in age group 40 to 49 (P-value for interaction between sex and age = .00079). The observed patterns suggest that consideration of gender-specific starting ages of screening might be warranted in countries in which screening offers start at ages above 50 years.

Associations of smoking with early- and late-onset colorectal cancer.

BACKGROUND: Incidence of colorectal cancer (CRC) in younger adults is increasing in many countries. Smoking is an established risk factor of CRC risk, but evidence on its impact on early-onset CRC (EOCRC) risk is limited. We aimed to evaluate the association of smoking exposure with EOCRC and compare it with late-onset CRC (LOCRC). METHODS: Smoking history and other known or suspected CRC risk factors were ascertained in detail in personal interviews among 6264 CRC patients and 6866 controls (frequency matched for age, sex, and county of residence) who were recruited in 2003-2020 in the DACHS study (Darmkrebs: Chancen der Verhütung durch Screening [German]; Colorectal Cancer: Chances for Prevention Through Screening [English]), a population-based case-control study from Germany. Associations of smoking with EOCRC (<55 years, 724 cases, 787 controls) and LOCRC (≥55years, 5540 cases, 6079 controls) were estimated using multiple logistic regression. RESULTS: Smoking exposure was much higher among EOCRC cases than among controls, and strong associations of smoking were observed for both EOCRC and LOCR. Adjusted odds ratios for EOCRC and LOCRC were as follows: current smoking: 1.57 (95% confidence interval [CI] = 1.20 to 2.04, P < .001) and 1.46 (95% CI = 1.28 to 1.67, P < .001); former smoking: 1.39 (95% CI = 1.07 to 1.81, P = .01) and 1.24 (95% CI = 1.13 to 1.36, P < .001); per 10 pack-years: 1.15 (95% CI = 1.05 to 1.27, P < .001) and 1.05 (95% CI = 1.03 to 1.08, P < .001). These patterns were similar for colon and rectum cancer and for early- and late-stage CRC. CONCLUSION: Smoking is a strong risk factor for both EOCRC and LOCRC.

Genome-wide Interaction Study with Smoking for Colorectal Cancer Risk Identifies Novel Genetic Loci Related to Tumor Suppression, Inflammation, and Immune Response.

BACKGROUND: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. METHODS: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. RESULTS: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10-8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20-1.30] compared with the other genotypes (OR <1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10-8) and 8q24.23 (rs7005722, P = 2.88 × 10-8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09-1.16) compared with the other genotypes (OR <1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07-1.28) compared with the other genotypes (OR <1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). CONCLUSIONS: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. IMPACT: These findings can guide potential prevention treatments.

Body mass index and molecular subtypes of colorectal cancer.

BACKGROUND: Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. METHODS: We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. RESULTS: Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). CONCLUSIONS: In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.

Physical activity, polygenic risk score, and colorectal cancer risk.

INTRODUCTION: Whether and to what extent the relationship between physical activity (PA) and colorectal cancer (CRC) differs according to CRC-related genetic risk remains to be determined, and no studies to date have quantified how much genetically determined risk could be compensated for with active exercise. METHODS: Genetic risk was quantified by a polygenic risk score (PRS) summarizing the estimated effect of 140 CRC-associated genetic variants. Associations of PA with CRC risk were estimated by multivariable logistic regression across PRS levels. We also compared the impact of PA and specific PA types to the PRS using "genetic risk equivalent (GRE)", a novel approach to enhance effective risk communication. RESULTS: Among 5058 CRC patients and 4134 controls, we observed no significant association between overall PA level in quartiles and CRC risk. However, the highest versus lowest lifetime leisure time physical activity (LTPA) was associated with a 13% lower CRC risk [odds ratio 0.87, 95% confidence interval (CI) 0.77-1.00] independent of PRS levels (adjusted p value for interaction = 0.18). This effect was equivalent to the effect of having 11 percentiles lower PRS (GRE -10.6, 95% CI -20.7 to -0.6). The GRE (95% CI) for the highest lifetime sports tertile was -23.0 (-33.9 to -12.0). CONCLUSIONS: LTPA was inversely associated with CRC risk irrespective of polygenic risk for CRC, which reinforces the importance of LTPA in CRC prevention among the general population. Adequate sports activity can compensate for a large share of polygenic risk for CRC.

Polygenic Risk Score for Defining Personalized Surveillance Intervals After Adenoma Detection and Removal at Colonoscopy.

BACKGROUND & AIMS: Polygenic risk scores (PRSs) could help to define personalized colorectal cancer (CRC) screening strategies. The aim of this study was to evaluate whether a PRS, along with adenoma characteristics, could help to define more personalized and risk-adapted surveillance intervals. METHODS: In a population-based, case-control study from Germany, detailed information on previous colonoscopies and a PRS based on 140 CRC-related, single-nucleotide polymorphisms was obtained from 4696 CRC cases and 3709 controls. Participants were classified as having low, medium, or high genetic risk according to tertiles of PRSs among controls. We calculated the absolute risk of CRC based on the PRS and colonoscopy history and findings. RESULTS: We observed major variations of CRC risk according to the PRS, including among individuals with detection and removal of adenomas at colonoscopy. For instance, the estimated 10-year absolute risk of CRC for 50-year-old men and women with no polyps, for whom repeat screening colonoscopy is recommended after 10 years only, was 0.2%. Equivalent absolute risks were estimated for people with low-risk adenomas and low PRS. However, the same levels of absolute risk were reached within 3 to 5 years by those with low-risk adenomas and high PRS and with high-risk adenomas irrespective of the PRS. CONCLUSIONS: Consideration of genetic predisposition to CRC risk, as determined by a PRS, could help to define personalized, risk-adapted surveillance intervals after detection and removal of adenomas at screening colonoscopy. However, whether the risk variation is strong enough to direct clinical risk stratification needs to be explored further.

Assessment of Body Mass Index, Polygenic Risk Score, and Development of Colorectal Cancer.

Importance: Excess weight, the prevalence of which is high and increasing in many countries, is linked to multiple adverse health outcomes, including increased colorectal cancer (CRC) risk. Better communication of health risks associated with excess weight might support efforts of prevention. Objective: To evaluate the individual and joint associations of body mass index (BMI) and polygenic risk with CRC, to assess potential interactions among them, and to quantify by how much increased polygenic risk for CRC can be offset by having a BMI within reference range. Design, Setting, and Participants: This population-based case-control study was conducted in the Rhine-Neckar region of southwest Germany, with recruitment from 2003 to 2017. Participants with both risk factor and genetic information were included for analysis. Data analysis was conducted from December 8, 2021, to February 17, 2022. Exposures: BMI was calculated as self-reported weight in kilograms approximately 10 years before diagnosis or interview and current height in meters squared. A polygenic risk score (PRS) was built based on 140 CRC-related risk loci. Main Outcomes and Measures: Individual and joint associations of BMI and PRS with CRC were estimated using multiple logistic regression. Associations of excess weight with CRC were quantified by adjusted odds ratios (aORs) and genetic risk equivalents (GREs), the equivalent outcomes conveyed by defined differences in PRS percentiles. Results: Among 9169 participants (median [IQR] age, 69 [62-76] years; 5589 [61.0%] male participants) included, 5053 had CRC and 4116 did not. BMI of 30 or greater was associated with higher odds of having CRC compared with BMI less than 25 (aOR, 1.71; 95% CI, 1.49-1.97), independent of PRS levels (P for interaction = .45). Participants with BMI of 30 or greater and a PRS in the highest tertile had higher odds of CRC compared with participants with BMI less than 25 and a PRS in the lowest tertile (aOR, 3.82; 95% CI, 3.03-4.82). The estimated association of BMI greater than 30 with CRC risk was equivalent to that of having a 41 (95% CI, 29-53)-percentile higher PRS. BMI of 30 or greater was particularly associated with stage IV CRC (aOR, 2.21; 95% CI, 1.71-2.84). Conclusions and Relevance: These findings suggest that excess weight was associated with CRC regardless of PRS levels. The association of having a BMI within reference range may be similar to that of having a substantially lower polygenic risk for CRC.

The power of a healthy lifestyle for cancer prevention: the example of colorectal cancer.

OBJECTIVE: We aimed to directly compare the estimated effects of adherence to a healthy lifestyle with those of risk predisposition according to known genetic variants affecting colorectal cancer (CRC) risk, to support effective risk communication for cancer prevention. METHODS: A healthy lifestyle score (HLS) was derived from 5 lifestyle factors: smoking, alcohol consumption, diet, physical activity, and body adiposity. The association of lifestyle and polygenic risk score (PRS) (based on 140 CRC-associated risk loci) with CRC risk was assessed with multiple logistic regression and compared through the genetic risk equivalent (GRE), a novel approach providing an estimate of the effects of adherence to a healthy lifestyle in terms of percentile differences in PRS. RESULTS: A higher HLS was associated with lower CRC risk (4,844 cases, 3,964 controls). Those adhering to all 5 healthy lifestyle factors had a 62% (95% CI 54%-68%) lower CRC risk than those adhering to ≤ 2 healthy lifestyle factors. The estimated effect of adherence to all 5 compared with ≤ 2 healthy lifestyle factors was as strong as the effect of having a 79 percentile (GRE 79, 95% CI 61-97) lower PRS. The association between a healthy lifestyle and CRC risk was independent of PRS level but was particularly pronounced among those with a family history of CRC in ≥ 1 first-degree relative (P-interaction = 0.0013). CONCLUSIONS: A healthy lifestyle was strongly inversely associated with CRC risk. The large GRE indicated that CRC risk determined by polygenic risk may be offset to a substantial extent by adherence to a healthy lifestyle.

Building resilient supply chains in uncertain times: a comparative study of EU and ASEAN approaches to supply chain resilience.

Amid rising uncertainty in the global economy and unprecedented economic disruption caused by the COVID-19 pandemic, the concept of supply chain resilience has gained increasing popularity in ASEAN and the EU. However, by comparing their paths to resilient supply chains, this article argues that while both organizations regard resilience as a departure from past doctrines of pure economic efficiency, each has a different understanding of and approach to supply chain resilience. While for ASEAN, supply chain resilience is meant to reconcile inward- and outward-looking dimensions to support ASEAN competitiveness, within the EU, resilience is associated with the search for strategic autonomy with an internal focus. Despite these differences, both groups regard sustainability and digital transformation as crucial components of supply chain resilience, which they see as a way to enhance their economic cooperation and strategic partnership.

Common variability in oestrogen-related genes and pancreatic ductal adenocarcinoma risk in women.

The incidence of pancreatic ductal adenocarcinoma (PDAC) is different among males and females. This disparity cannot be fully explained by the difference in terms of exposure to known risk factors; therefore, the lower incidence in women could be attributed to sex-specific hormones. A two-phase association study was conducted in 12,387 female subjects (5436 PDAC cases and 6951 controls) to assess the effect on risk of developing PDAC of single nucleotide polymorphisms (SNPs) in 208 genes involved in oestrogen and pregnenolone biosynthesis and oestrogen-mediated signalling. In the discovery phase 14 polymorphisms showed a statistically significant association (P < 0.05). In the replication none of the findings were validated. In addition, a gene-based analysis was performed on the 208 selected genes. Four genes (NR5A2, MED1, NCOA2 and RUNX1) were associated with PDAC risk, but only NR5A2 showed an association (P = 4.08 × 10-5) below the Bonferroni-corrected threshold of statistical significance. In conclusion, despite differences in incidence between males and females, our study did not identify an effect of common polymorphisms in the oestrogen and pregnenolone pathways in relation to PDAC susceptibility. However, we validated the previously reported association between NR5A2 gene variants and PDAC risk.