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Thomas CE, Georgeson P, Qu C, et al., 2024, Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature., Cancer Epidemiol Biomarkers Prev, Vol: 33, Pages: 534-546
BACKGROUND: The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors' association with colorectal cancer risk and survival differs by SBS88. METHODS: Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer-specific survival using Cox proportional hazards regression (N = 3,465 cases). RESULTS: 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66-0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer-specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47-7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78-1.21, Pheterogeneity = 0.066). CONCLUSIONS: Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer-specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available. IMPACT: This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.
Stern MC, Sanchez Mendez J, Kim AE, et al., 2024, Genome-Wide Gene-Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk., Cancer Epidemiol Biomarkers Prev, Vol: 33, Pages: 400-410
BACKGROUND: High red meat and/or processed meat consumption are established colorectal cancer risk factors. We conducted a genome-wide gene-environment (GxE) interaction analysis to identify genetic variants that may modify these associations. METHODS: A pooled sample of 29,842 colorectal cancer cases and 39,635 controls of European ancestry from 27 studies were included. Quantiles for red meat and processed meat intake were constructed from harmonized questionnaire data. Genotyping arrays were imputed to the Haplotype Reference Consortium. Two-step EDGE and joint tests of GxE interaction were utilized in our genome-wide scan. RESULTS: Meta-analyses confirmed positive associations between increased consumption of red meat and processed meat with colorectal cancer risk [per quartile red meat OR = 1.30; 95% confidence interval (CI) = 1.21-1.41; processed meat OR = 1.40; 95% CI = 1.20-1.63]. Two significant genome-wide GxE interactions for red meat consumption were found. Joint GxE tests revealed the rs4871179 SNP in chromosome 8 (downstream of HAS2); greater than median of consumption ORs = 1.38 (95% CI = 1.29-1.46), 1.20 (95% CI = 1.12-1.27), and 1.07 (95% CI = 0.95-1.19) for CC, CG, and GG, respectively. The two-step EDGE method identified the rs35352860 SNP in chromosome 18 (SMAD7 intron); greater than median of consumption ORs = 1.18 (95% CI = 1.11-1.24), 1.35 (95% CI = 1.26-1.44), and 1.46 (95% CI = 1.26-1.69) for CC, CT, and TT, respectively. CONCLUSIONS: We propose two novel biomarkers that support the role of meat consumption with an increased risk of colorectal cancer. IMPACT: The reported GxE interactions may explain the increased risk of colorectal cancer in certain population subgroups.
Albers FEM, Lou MWC, Dashti SG, et al., 2024, Sex-steroid hormones and risk of postmenopausal estrogen receptor-positive breast cancer: a case-cohort analysis., Cancer Causes Control
PURPOSE: Sex-steroid hormones are associated with postmenopausal breast cancer but potential confounding from other biological pathways is rarely considered. We estimated risk ratios for sex-steroid hormone biomarkers in relation to postmenopausal estrogen receptor (ER)-positive breast cancer, while accounting for biomarkers from insulin/insulin-like growth factor-signaling and inflammatory pathways. METHODS: This analysis included 1208 women from a case-cohort study of postmenopausal breast cancer within the Melbourne Collaborative Cohort Study. Weighted Poisson regression with a robust variance estimator was used to estimate risk ratios (RRs) and 95% confidence intervals (CIs) of postmenopausal ER-positive breast cancer, per doubling plasma concentration of progesterone, estrogens, androgens, and sex-hormone binding globulin (SHBG). Analyses included sociodemographic and lifestyle confounders, and other biomarkers identified as potential confounders. RESULTS: Increased risks of postmenopausal ER-positive breast cancer were observed per doubling plasma concentration of progesterone (RR: 1.22, 95% CI 1.03 to 1.44), androstenedione (RR 1.20, 95% CI 0.99 to 1.45), dehydroepiandrosterone (RR: 1.15, 95% CI 1.00 to 1.34), total testosterone (RR: 1.11, 95% CI 0.96 to 1.29), free testosterone (RR: 1.12, 95% CI 0.98 to 1.28), estrone (RR 1.21, 95% CI 0.99 to 1.48), total estradiol (RR 1.19, 95% CI 1.02 to 1.39) and free estradiol (RR 1.22, 95% CI 1.05 to 1.41). A possible decreased risk was observed for SHBG (RR 0.83, 95% CI 0.66 to 1.05). CONCLUSION: Progesterone, estrogens and androgens likely increase postmenopausal ER-positive breast cancer risk, whereas SHBG may decrease risk. These findings strengthen the causal evidence surrounding the sex-hormone-driven nature of postmenopausal breast cancer.
Georgeson P, Steinfelder RS, Harrison TA, et al., 2024, Genotoxic colibactin mutational signature in colorectal cancer is associated with clinicopathological features, specific genomic alterations and better survival., medRxiv
BACKGROUND AND AIMS: The microbiome has long been suspected of a role in colorectal cancer (CRC) tumorigenesis. The mutational signature SBS88 mechanistically links CRC development with the strain of Escherichia coli harboring the pks island that produces the genotoxin colibactin, but the genomic, pathological and survival characteristics associated with SBS88-positive tumors are unknown. METHODS: SBS88-positive CRCs were identified from targeted sequencing data from 5,292 CRCs from 17 studies and tested for their association with clinico-pathological features, oncogenic pathways, genomic characteristics and survival. RESULTS: In total, 7.5% (398/5,292) of the CRCs were SBS88-positive, of which 98.7% (392/398) were microsatellite stable/microsatellite instability low (MSS/MSI-L), compared with 80% (3916/4894) of SBS88 negative tumors (p=1.5x10-28). Analysis of MSS/MSI-L CRCs demonstrated that SBS88 positive CRCs were associated with the distal colon (OR=1.84, 95% CI=1.40-2.42, p=1x10-5) and rectum (OR=1.90, 95% CI=1.44-2.51, p=6x10-6) tumor sites compared with the proximal colon. The top seven recurrent somatic mutations associated with SBS88-positive CRCs demonstrated mutational contexts associated with colibactin-induced DNA damage, the strongest of which was the APC:c.835-8A>G mutation (OR=65.5, 95%CI=39.0-110.0, p=3x10-80). Large copy number alterations (CNAs) including CNA loss on 14q and gains on 13q, 16q and 20p were significantly enriched in SBS88-positive CRCs. SBS88-positive CRCs were associated with better CRC-specific survival (p=0.007; hazard ratio of 0.69, 95% CI=0.52-0.90) when stratified by age, sex, study, and by stage. CONCLUSION: SBS88-positivity, a biomarker of colibactin-induced DNA damage, can identify a novel subtype of CRC characterized by recurrent somatic mutations, copy number alterations and better survival. These findings provide new insights for treatment and prevention strategies for this subtype of CRC.
His M, Gunter MJ, Keski-Rahkonen P, et al., 2024, Application of Metabolomics to Epidemiologic Studies of Breast Cancer: New Perspectives for Etiology and Prevention., J Clin Oncol, Vol: 42, Pages: 103-115
PURPOSE: To provide an overview on how the application of metabolomics (high-throughput characterization of metabolites from cells, organs, tissues, or biofluids) to population-based studies may inform our understanding of breast cancer etiology. METHODS: We evaluated studies that applied metabolomic analyses to prediagnostic blood samples from prospective epidemiologic studies to identify circulating metabolites associated with breast cancer risk, overall and by breast cancer subtype and menopausal status. We provide some important considerations for the application and interpretation of metabolomics approaches in this context. RESULTS: Overall, specific lipids and amino acids were indicated as the most common metabolite classes associated with breast cancer development. However, comparison of results across studies is challenging because of heterogeneity in laboratory techniques, analytical methods, sample size, and applied statistical methods. CONCLUSION: Metabolomics is being increasingly applied to population-based studies for the identification of new etiologic hypotheses and/or mechanisms related to breast cancer development. Despite its success in applications to epidemiology, studies of larger sample size with detailed information on menopausal status, breast cancer subtypes, and repeated biologic samples collected over time are needed to improve comparison of results between studies and enhance validation of results, allowing potential clinical translation of findings.
Bull CJ, Hazelwood E, Bell JA, et al., 2023, Identifying metabolic features of colorectal cancer liability using Mendelian randomization., medRxiv
BACKGROUND: Recognizing the early signs of cancer risk is vital for informing prevention, early detection, and survival. METHODS: To investigate whether changes in circulating metabolites characterise the early stages of colorectal cancer (CRC) development, we examined associations between a genetic risk score (GRS) associated with CRC liability (72 single nucleotide polymorphisms) and 231 circulating metabolites measured by nuclear magnetic resonance spectroscopy in the Avon Longitudinal Study of Parents and Children (N=6,221). Linear regression models were applied to examine associations between genetic liability to colorectal cancer and circulating metabolites measured in the same individuals at age 8, 16, 18 and 25 years. RESULTS: The GRS for CRC was associated with up to 28% of the circulating metabolites at FDR-P<0.05 across all time points, particularly with higher fatty acids and very-low- and low-density lipoprotein subclass lipids. Two-sample reverse Mendelian randomization (MR) analyses investigating CRC liability (52,775 cases, 45,940 controls) and metabolites measured in a random subset of UK Biobank participants (N=118,466, median age 58y) revealed broadly consistent effect estimates with the GRS analysis. In conventional (forward) MR analyses, genetically predicted polyunsaturated fatty acid concentrations were most strongly associated with higher CRC risk. CONCLUSIONS: These analyses suggest that higher genetic liability to CRC can cause early alterations in systemic metabolism, and suggest that fatty acids may play an important role in CRC development. FUNDING: This work was supported by the Elizabeth Blackwell Institute for Health Research, University of Bristol, the Wellcome Trust, the Medical Research Council, Diabetes UK, the University of Bristol NIHR Biomedical Research Centre, and Cancer Research UK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work used
Stein MJ, Baurecht H, Sedlmeier AM, et al., 2023, Association between circadian physical activity patterns and mortality in the UK Biobank., Int J Behav Nutr Phys Act, Vol: 20
BACKGROUND: The benefit of physical activity (PA) for increasing longevity is well-established, however, the impact of diurnal timing of PA on mortality remains poorly understood. We aimed to derive circadian PA patterns and investigate their associations with all-cause mortality. METHODS: We used 24 h PA time series from 96,351 UK Biobank participants aged between 42 and 79 years at accelerometry in 2013-2015. Functional principal component analysis (fPCA) was applied to obtain circadian PA patterns. Using multivariable Cox proportional hazard models, we related the loading scores of these fPCs to estimate risk of mortality. RESULTS: During 6.9 years of follow-up, 2,850 deaths occurred. Four distinct fPCs accounted for 96% of the variation of the accelerometry data. Using a loading score of zero (i.e., average overall PA during the day) as the reference, a fPC1 score of + 2 (high overall PA) was inversely associated with mortality (Hazard ratio, HR = 0.91; 95% CI: 0.84-0.99), whereas a score of -2 (low overall PA) was associated with higher mortality (1.69; 95% CI: 1.57-1.81; p for non-linearity < 0.001). Significant inverse linear associations with mortality were observed for engaging in midday PA instead of early and late PA (fPC3) (HR for a 1-unit increase 0.88; 95% CI: 0.83-0.93). In contrast, midday and nocturnal PA instead of early and evening PA (fPC4) were positively associated with mortality (HR for a 1-unit increase 1.16; 95% CI: 1.08-1.25). CONCLUSION: Our results suggest that it is less important during which daytime hours one is active but rather, to engage in some level of elevated PA for longevity.
Dimou N, Kim AE, Flanagan O, et al., 2023, Probing the diabetes and colorectal cancer relationship using gene - environment interaction analyses, Annual Meeting of the American-Association-for-Cancer-Research (AACR), Publisher: SPRINGERNATURE, Pages: 511-520, ISSN: 0007-0920
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Pham TT, Nimptsch K, Papadimitriou N, et al., 2023, Genetically determined circulating resistin concentrations and risk of colorectal cancer: a two-sample Mendelian randomization study, JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, ISSN: 0171-5216
Constantinescu A-E, Bull CJ, Jones N, et al., 2023, Circulating white blood cell traits and colorectal cancer risk: A Mendelian randomisation study, INTERNATIONAL JOURNAL OF CANCER, ISSN: 0020-7136
Aglago EK, Kim A, Lin Y, et al., 2023, Table 1 from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><p>Selected characteristics of the participants.</p></jats:p>
Aglago EK, Kim A, Lin Y, et al., 2023, Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><div>Abstract<p>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 (<i>FMN1/GREM1</i>) 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 <i>FMN1/GREM1</i> 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.</p>Significance:<p>This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal
Aglago EK, Kim A, Lin Y, et al., 2023, Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><div>Abstract<p>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 (<i>FMN1/GREM1</i>) 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 <i>FMN1/GREM1</i> 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.</p>Significance:<p>This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal
Aglago EK, Kim A, Lin Y, et al., 2023, Supplementary Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><p>supplementary materials</p></jats:p>
Aglago EK, Kim A, Lin Y, et al., 2023, Table 1 from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><p>Selected characteristics of the participants.</p></jats:p>
Aglago EK, Kim A, Lin Y, et al., 2023, Table 2 from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><p>Summary of G × BMI analyses using 1DF, two-step, and 3DF analyses.</p></jats:p>
Aglago EK, Kim A, Lin Y, et al., 2023, Table 2 from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><p>Summary of G × BMI analyses using 1DF, two-step, and 3DF analyses.</p></jats:p>
Aglago EK, Kim A, Lin Y, et al., 2023, Supplementary Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
<jats:p><p>supplementary materials</p></jats:p>
Aglago EK, Kim A, Lin Y, et al., 2023, A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk, CANCER RESEARCH, Vol: 83, Pages: 2572-2583, ISSN: 0008-5472
Yarmolinsky J, Bouras E, Constantinescu A, et al., 2023, Genetically proxied glucose-lowering drug target perturbation and risk of cancer: a Mendelian randomisation analysis, DIABETOLOGIA, Vol: 66, Pages: 1481-1500, ISSN: 0012-186X
Kenkhuis M-F, Klingestijn M, Fanshawe A-M, et al., 2023, Longitudinal associations of sedentary behavior and physical activity with body composition in colorectal cancer survivors up to 2 years post treatment, JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, Vol: 149, Pages: 4063-4075, ISSN: 0171-5216
Clasen JL, Mabunda R, Heath AK, et al., 2023, Reproductive and hormonal factors and risk of renal cell carcinoma among women in the European Prospective Investigation into Cancer and Nutrition, Cancer Medicine, Vol: 12, Pages: 15588-15600, ISSN: 2045-7634
BackgroundRenal cell carcinoma (RCC) is twice as common among men compared with women, and hormonal factors have been suggested to partially explain this difference. There is currently little evidence on the roles of reproductive and hormonal risk factors in RCC aetiology.Materials & MethodsWe investigated associations of age at menarche and age at menopause, pregnancy-related factors, hysterectomy and ovariectomy and exogenous hormone use with RCC risk among 298,042 women in the European Prospective Investigation into Cancer and Nutrition (EPIC) study.ResultsDuring 15 years of follow-up, 438 RCC cases were identified. Parous women had higher rates of RCC compared with nulliparous women (HR = 1.71, 95% CI 1.18, 2.46), and women who were older at age of first pregnancy had lower rates of RCC (30 years + vs. <20 years HR = 0.53, 95% CI 0.34, 0.82). Additionally, we identified a positive association for hysterectomy (HR = 1.43 95% CI 1.09, 1.86) and bilateral ovariectomy (HR = 1.67, 95% CI 1.13, 2.47), but not unilateral ovariectomy (HR = 0.99, 95% CI 0.61, 1.62) with RCC risk. No clear associations were found for age at menarche, age at menopause or exogenous hormone use.ConclusionOur results suggest that parity and reproductive organ surgeries may play a role in RCC aetiology.
Watling CZ, Kelly RK, Murphy N, et al., 2023, Figure 4 from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk
<jats:p><p>Multivariable-adjusted hazard ratios (95% CI) for intake of fiber from breads and cereals from the touchscreen questionnaire and colorectal cancer risk by genetically predicted host short-chain fatty acid production for butyrate (<b>A</b>) and propionate (<i>n</i> = 343,621; <b>B</b>). Models stratified for sex and age at recruitment, and further adjusted for region, first 10 principal components, height, physical activity, Townsend deprivation index, education, employment, smoking, alcohol consumption measured at recruitment, diabetes status, nonsteroidal anti-inflammatory drug use, body mass index, processed and red meat intake, and female-specific covariates: menopausal hormone therapy use and menopausal status. Analyses are restricted to white British participants. χ<sup>2</sup> and <i>P</i> value represents improvement of fit obtained from likelihood ratio tests for including an interaction term between butyrate or propionate polygenic score and fiber from breads and cereals (modeled as a 5 gram/day increment) into the model. g/day, grams per day; <i>N</i>, number of participants; Q, quintile; ref, reference group.</p></jats:p>
Watling CZ, Kelly RK, Murphy N, et al., 2023, Supplementary Material from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk
<jats:p><p>Supplementary Material</p></jats:p>
Watling CZ, Kelly RK, Murphy N, et al., 2023, Figure 3 from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk
<jats:p><p>Multivariable-adjusted hazard ratios (95% CI) for intake of carbohydrates and fiber and colorectal cancer risk separated by genetically predicted host short-chain fatty acid production for butyrate (<b>A</b>) and propionate (<i>n</i> = 87,417; <b>B</b>). All models are stratified by sex, age at recruitment, adjusted for region of recruitment, first 10 genetic principal components, body mass index, height, physical activity, Townsend deprivation index, education, smoking, alcohol consumption, diabetes status, nonsteroidal anti-inflammatory drug use, red and processed meat intake, fruit and vegetable intake (except when fiber from vegetables and/or fruits, and non-free sugar intake was the exposure), energy intake, and female-specific covariates: menopausal hormone therapy use and menopausal status. Analyses are restricted to white British participants. χ<sup>2</sup> and <i>P</i> value represents improvement of fit obtained from likelihood ratio tests for including an interaction term between butyrate or propionate polygenic score and carbohydrate type/source (modeled as a 5% energy increment) or fiber source (modeled as a 5 gram/day increment) into the model.</p></jats:p>
Watling CZ, Kelly RK, Murphy N, et al., 2023, Figure 3 from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk
<jats:p><p>Multivariable-adjusted hazard ratios (95% CI) for intake of carbohydrates and fiber and colorectal cancer risk separated by genetically predicted host short-chain fatty acid production for butyrate (<b>A</b>) and propionate (<i>n</i> = 87,417; <b>B</b>). All models are stratified by sex, age at recruitment, adjusted for region of recruitment, first 10 genetic principal components, body mass index, height, physical activity, Townsend deprivation index, education, smoking, alcohol consumption, diabetes status, nonsteroidal anti-inflammatory drug use, red and processed meat intake, fruit and vegetable intake (except when fiber from vegetables and/or fruits, and non-free sugar intake was the exposure), energy intake, and female-specific covariates: menopausal hormone therapy use and menopausal status. Analyses are restricted to white British participants. χ<sup>2</sup> and <i>P</i> value represents improvement of fit obtained from likelihood ratio tests for including an interaction term between butyrate or propionate polygenic score and carbohydrate type/source (modeled as a 5% energy increment) or fiber source (modeled as a 5 gram/day increment) into the model.</p></jats:p>
Watling CZ, Kelly RK, Murphy N, et al., 2023, Table 1 from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk
<jats:p><p>Baseline characteristics by lowest and highest quartile of intake of whole grain starch, refined grain starch, and fiber in 114,217 UK Biobank participants.</p></jats:p>
Watling CZ, Kelly RK, Murphy N, et al., 2023, Supplementary Material from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk
<jats:p><p>Supplementary Material</p></jats:p>
Watling CZ, Kelly RK, Murphy N, et al., 2023, Table 1 from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk
<jats:p><p>Baseline characteristics by lowest and highest quartile of intake of whole grain starch, refined grain starch, and fiber in 114,217 UK Biobank participants.</p></jats:p>
Watling CZ, Kelly RK, Murphy N, et al., 2023, Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk, CANCER RESEARCH, Vol: 83, Pages: 2066-2076, ISSN: 0008-5472
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