Imperial College London

DrNeilMurphy

Faculty of MedicineSchool of Public Health

Honorary Senior Research Fellow
 
 
 
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neil.murphy

 
 
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Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
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198 results found

Thomas CE, Georgeson P, Qu C, Steinfelder RS, Buchanan DD, Song M, Harrison TA, Um CY, Hullar MA, Jenkins MA, Van Guelpen B, Lynch BM, Melaku YA, Huyghe JR, Aglago EK, Berndt SI, Boardman LA, Campbell PT, Cao Y, Chan AT, Drew DA, Figueiredo JC, French AJ, Giannakis M, Goode EL, Gruber SB, Gsur A, Gunter MJ, Hoffmeister M, Hsu L, Huang W-Y, Moreno V, Murphy N, Newcomb PA, Newton CC, Nowak JA, Obón-Santacana M, Ogino S, Sun W, Toland AE, Trinh QM, Ugai T, Zaidi SH, Peters U, Phipps AIet 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.

Journal article

Tian Y, Lin Y, Qu C, Arndt V, Baurley JW, Berndt SI, Bien SA, Bishop DT, Brenner H, Buchanan DD, Budiarto A, Campbell PT, Carreras-Torres R, Casey G, Chan AT, Chen R, Chen X, Conti DV, Díez-Obrero V, Dimou N, Drew DA, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gunter MJ, Harlid S, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl KM, Joshi AD, Keku TO, Kawaguchi E, Kim AE, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Moreno V, Morrison J, Murphy N, Nan H, Nassir R, Newcomb PA, Obón-Santacana M, Ogino S, Ose J, Pardamean B, Pellatt AJ, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez EA, Sakoda LC, Schoen RE, Shcherbina A, Stern MC, Su Y-R, Thibodeau SN, Thomas DC, Tsilidis KK, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, White E, Wolk A, Woods MO, Wu AH, Peters U, Gauderman WJ, Hsu L, Chang-Claude Jet al., 2024, Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk., Br J Cancer

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.

Journal article

Stern MC, Sanchez Mendez J, Kim AE, Obón-Santacana M, Moratalla-Navarro F, Martín V, Moreno V, Lin Y, Bien SA, Qu C, Su Y-R, White E, Harrison TA, Huyghe JR, Tangen CM, Newcomb PA, Phipps AI, Thomas CE, Kawaguchi ES, Lewinger JP, Morrison JL, Conti DV, Wang J, Thomas DC, Platz EA, Visvanathan K, Keku TO, Newton CC, Um CY, Kundaje A, Shcherbina A, Murphy N, Gunter MJ, Dimou N, Papadimitriou N, Bézieau S, van Duijnhoven FJB, Männistö S, Rennert G, Wolk A, Hoffmeister M, Brenner H, Chang-Claude J, Tian Y, Le Marchand L, Cotterchio M, Tsilidis KK, Bishop DT, Melaku YA, Lynch BM, Buchanan DD, Ulrich CM, Ose J, Peoples AR, Pellatt AJ, Li L, Devall MAM, Campbell PT, Albanes D, Weinstein SJ, Berndt SI, Gruber SB, Ruiz-Narvaez E, Song M, Joshi AD, Drew DA, Petrick JL, Chan AT, Giannakis M, Peters U, Hsu L, Gauderman WJet 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.

Journal article

Bull CJ, Hazelwood E, Bell JA, Tan VY, Constantinescu A-E, Borges MC, Legge DN, Burrows K, Huyghe JR, Brenner H, Castellví-Bel S, Chan AT, Kweon S-S, Marchand LL, Li L, Cheng I, Pai RK, Figueiredo JC, Murphy N, Gunter MJ, Timpson NJ, Vincent EEet 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

Journal article

Thomas M, Su Y-R, Rosenthal EA, Sakoda LC, Schmit SL, Timofeeva MN, Chen Z, Fernandez-Rozadilla C, Law PJ, Murphy N, Carreras-Torres R, Diez-Obrero V, van Duijnhoven FJB, Jiang S, Shin A, Wolk A, Phipps AI, Burnett-Hartman A, Gsur A, Chan AT, Zauber AG, Wu AH, Lindblom A, Um CY, Tangen CM, Gignoux C, Newton C, Haiman CA, Qu C, Bishop DT, Buchanan DD, Crosslin DR, Conti DV, Kim D-H, Hauser E, White E, Siegel E, Schumacher FR, Rennert G, Giles GG, Hampel H, Brenner H, Oze I, Oh JH, Lee JK, Schneider JL, Chang-Claude J, Kim J, Huyghe JR, Zheng J, Hampe J, Greenson J, Hopper JL, Palmer JR, Visvanathan K, Matsuo K, Matsuda K, Jung KJ, Li L, Le Marchand L, Vodickova L, Bujanda L, Gunter MJ, Matejcic M, Jenkins MA, Slattery ML, D'Amato M, Wang M, Hoffmeister M, Woods MO, Kim M, Song M, Iwasaki M, Du M, Udaltsova N, Sawada N, Vodicka P, Campbell PT, Newcomb PA, Cai Q, Pearlman R, Pai RK, Schoen RE, Steinfelder RS, Haile RW, Vandenputtelaar R, Prentice RL, Kuery S, Castellvi-Bel S, Tsugane S, Berndt SI, Lee SC, Brezina S, Weinstein SJ, Chanock SJ, Jee SH, Kweon S-S, Vadaparampil S, Harrison TA, Yamaji T, Keku TO, Vymetalkova V, Arndt V, Jia W-H, Shu X-O, Lin Y, Ahn Y-O, Stadler ZK, Van Guelpen B, Ulrich CM, Platz EA, Potter JD, Li CI, Meester R, Moreno V, Figueiredo JC, Casey G, Lansdorp Vogelaar I, Dunlop MG, Gruber SB, Hayes RB, Pharoah PDP, Houlston RS, Jarvik GP, Tomlinson IP, Zheng W, Corley DA, Peters U, Hsu Let al., 2023, Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations, NATURE COMMUNICATIONS, Vol: 14

Journal article

King SD, Veliginti S, Brouwers MCGJ, Ren Z, Zheng W, Setiawan VW, Wilkens LR, Shu X-O, Arslan AA, Freeman LEB, Bracci PM, Canzian F, Du M, Gallinger SJ, Giles GG, Goodman PJ, Haiman CA, Kogevinas M, Kooperberg C, LeMarchand L, Neale RE, Visvanathan K, White E, Albanes D, Andreotti G, Babic A, Berndt SI, Brais LK, Brennan P, Buring JE, Rabe KG, Bamlet WR, Chanock SJ, Fuchs CS, Gaziano JM, Giovannucci EL, Hackert T, Hassan MM, Katzke V, Kurtz RC, Lee I-M, Malats N, Murphy N, Oberg AL, Orlow I, Porta M, Real FX, Rothman N, Sesso HD, Silverman DT, Thompson Jr IM, Wactawski-Wende J, Wang X, Wentzensen N, Yu H, Zeleniuch-Jacquotte A, Yu K, Wolpin BM, Duell EJ, Li D, Hung RJ, Perdomo S, McCullough ML, Freedman ND, Patel A, Peters U, Riboli E, Sund M, Tjonneland A, Zhong J, Van den Eeden SK, Kraft P, Risch HA, Amundadottir LT, Klein AP, Stolzenberg-Solomon RZ, Antwi SOet al., 2023, Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization, CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, Vol: 32, ISSN: 1055-9965

Journal article

Dimou N, Kim AE, Flanagan O, Murphy N, Diez-Obrero V, Shcherbina A, Aglago EK, Bouras E, Campbell PT, Casey G, Gallinger S, Gruber SB, Jenkins MA, Lin Y, Moreno V, Ruiz-Narvaez E, Stern MC, Tian Y, Tsilidis KK, Arndt V, Barry EL, Baurley JW, Berndt SI, Bezieau S, Bien SA, Bishop DT, Brenner H, Budiarto A, Carreras-Torres R, Cenggoro TW, Chan AT, Chang-Claude J, Chanock SJ, Chen X, Conti DV, Dampier CH, Devall M, Drew DA, Figueiredo JC, Giles GG, Gsur A, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jordahl K, Kawaguchi E, Keku TO, Larsson SC, Le Marchand L, Lewinger JP, Li L, Mahesworo B, Morrison J, Newcomb PA, Newton CC, Obon-Santacana M, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Pharoah PDP, Platz EA, Potter JD, Rennert G, Scacheri PC, Schoen RE, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Ulrich CM, Um CY, van Duijnhoven FJB, Visvanathan K, Vodicka P, Vodickova L, White E, Wolk A, Woods MO, Qu C, Kundaje A, Hsu L, Gauderman WJ, Gunter MJ, Peters Uet 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

Conference paper

Constantinescu A-E, Bull CJ, Jones N, Mitchell R, Burrows K, Dimou N, Bezieau S, Brenner H, Buchanan DD, D'Amato M, Jenkins MA, Moreno V, Pai RK, Um CY, White E, Murphy N, Gunter M, Timpson NJ, Huyghe JR, Vincent EEet al., 2023, Circulating white blood cell traits and colorectal cancer risk: A Mendelian randomisation study, INTERNATIONAL JOURNAL OF CANCER, ISSN: 0020-7136

Journal article

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet al., 2023, Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

<jats:p>&lt;div&gt;Abstract&lt;p&gt;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 (&lt;i&gt;FMN1/GREM1&lt;/i&gt;) 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 &lt;i&gt;FMN1/GREM1&lt;/i&gt; 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.&lt;/p&gt;Significance:&lt;p&gt;This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal

Other

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet 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>&lt;p&gt;Summary of G × BMI analyses using 1DF, two-step, and 3DF analyses.&lt;/p&gt;</jats:p>

Other

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt S, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chen AT, Chang-Claude J, Chen X, Conti D, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Le Marchand L, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obon-Santacana M, Morento V, Murphy N, Men H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet 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

Journal article

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet 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>&lt;p&gt;supplementary materials&lt;/p&gt;</jats:p>

Other

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet al., 2023, Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

<jats:p>&lt;div&gt;Abstract&lt;p&gt;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 (&lt;i&gt;FMN1/GREM1&lt;/i&gt;) 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 &lt;i&gt;FMN1/GREM1&lt;/i&gt; 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.&lt;/p&gt;Significance:&lt;p&gt;This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal

Other

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet 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>&lt;p&gt;Summary of G × BMI analyses using 1DF, two-step, and 3DF analyses.&lt;/p&gt;</jats:p>

Other

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet 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>&lt;p&gt;supplementary materials&lt;/p&gt;</jats:p>

Other

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet 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>&lt;p&gt;Selected characteristics of the participants.&lt;/p&gt;</jats:p>

Other

Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su Y-R, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, Campbell PTet 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>&lt;p&gt;Selected characteristics of the participants.&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;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 (&lt;b&gt;A&lt;/b&gt;) and propionate (&lt;i&gt;n&lt;/i&gt; = 87,417; &lt;b&gt;B&lt;/b&gt;). 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&lt;sup&gt;2&lt;/sup&gt; and &lt;i&gt;P&lt;/i&gt; 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.&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;Baseline characteristics by lowest and highest quartile of intake of whole grain starch, refined grain starch, and fiber in 114,217 UK Biobank participants.&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;Supplementary Material&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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

Journal article

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;Supplementary Material&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;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 (&lt;b&gt;A&lt;/b&gt;) and propionate (&lt;i&gt;n&lt;/i&gt; = 343,621; &lt;b&gt;B&lt;/b&gt;). 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&lt;sup&gt;2&lt;/sup&gt; and &lt;i&gt;P&lt;/i&gt; 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; &lt;i&gt;N&lt;/i&gt;, number of participants; Q, quintile; ref, reference group.&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet al., 2023, Data from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk

<jats:p>&lt;div&gt;Abstract&lt;p&gt;Whole grain and fiber intakes may decrease the risk of colorectal cancer. The interplay between host genetic factors, colonization of specific bacteria, production of short-chain fatty acids (SCFA), and intake of whole grains and fiber could alter the protective role of carbohydrates against colorectal cancer. Here, we assessed intakes of types and sources of carbohydrates in 114,217 UK Biobank participants with detailed dietary data (2–5 24-hour dietary assessments), and a host polygenic score (PGS) was applied to categorize participants as high or low for intraluminal microbial SCFA production, namely, butyrate and propionate. Multivariable Cox proportional hazards models were used to determine the associations of carbohydrates and SCFA with colorectal cancer incidence. During a median follow-up of 9.4 years, 1,193 participants were diagnosed with colorectal cancer. Risk was inversely associated with intakes of non-free sugar and whole grain fiber. Evidence of heterogeneity was observed by the butyrate PGS; consuming higher amounts of whole grain starch was only associated with a lower risk of colorectal cancer in those with predicted high SCFA production. Similarly, in additional analyses utilizing the larger UK Biobank cohort (&lt;i&gt;N&lt;/i&gt; = 343,621) with less detailed dietary assessment, only individuals with a high genetically predicted butyrate production had a lower risk of colorectal cancer per 5 g/day intake of bread and cereal fiber. This study suggests that colorectal cancer risk varies by intake of carbohydrate types and sources, and the impact of whole grain intake may be modified by SCFA production.&lt;/p&gt;Significance:&lt;p&gt;Prospective population-level analyses provide evidence supporting the importance of butyrate production in reduction of colorectal cancer risk by whole grain consumption.&lt;/p&gt;&lt;/div&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;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 (&lt;b&gt;A&lt;/b&gt;) and propionate (&lt;i&gt;n&lt;/i&gt; = 343,621; &lt;b&gt;B&lt;/b&gt;). 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&lt;sup&gt;2&lt;/sup&gt; and &lt;i&gt;P&lt;/i&gt; 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; &lt;i&gt;N&lt;/i&gt;, number of participants; Q, quintile; ref, reference group.&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;Baseline characteristics by lowest and highest quartile of intake of whole grain starch, refined grain starch, and fiber in 114,217 UK Biobank participants.&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet al., 2023, Data from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk

<jats:p>&lt;div&gt;Abstract&lt;p&gt;Whole grain and fiber intakes may decrease the risk of colorectal cancer. The interplay between host genetic factors, colonization of specific bacteria, production of short-chain fatty acids (SCFA), and intake of whole grains and fiber could alter the protective role of carbohydrates against colorectal cancer. Here, we assessed intakes of types and sources of carbohydrates in 114,217 UK Biobank participants with detailed dietary data (2–5 24-hour dietary assessments), and a host polygenic score (PGS) was applied to categorize participants as high or low for intraluminal microbial SCFA production, namely, butyrate and propionate. Multivariable Cox proportional hazards models were used to determine the associations of carbohydrates and SCFA with colorectal cancer incidence. During a median follow-up of 9.4 years, 1,193 participants were diagnosed with colorectal cancer. Risk was inversely associated with intakes of non-free sugar and whole grain fiber. Evidence of heterogeneity was observed by the butyrate PGS; consuming higher amounts of whole grain starch was only associated with a lower risk of colorectal cancer in those with predicted high SCFA production. Similarly, in additional analyses utilizing the larger UK Biobank cohort (&lt;i&gt;N&lt;/i&gt; = 343,621) with less detailed dietary assessment, only individuals with a high genetically predicted butyrate production had a lower risk of colorectal cancer per 5 g/day intake of bread and cereal fiber. This study suggests that colorectal cancer risk varies by intake of carbohydrate types and sources, and the impact of whole grain intake may be modified by SCFA production.&lt;/p&gt;Significance:&lt;p&gt;Prospective population-level analyses provide evidence supporting the importance of butyrate production in reduction of colorectal cancer risk by whole grain consumption.&lt;/p&gt;&lt;/div&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;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 (&lt;b&gt;A&lt;/b&gt;) and propionate (&lt;i&gt;n&lt;/i&gt; = 87,417; &lt;b&gt;B&lt;/b&gt;). 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&lt;sup&gt;2&lt;/sup&gt; and &lt;i&gt;P&lt;/i&gt; 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.&lt;/p&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet al., 2023, Data from Prospective Analysis Reveals Associations between Carbohydrate Intakes, Genetic Predictors of Short-Chain Fatty Acid Synthesis, and Colorectal Cancer Risk

<jats:p>&lt;div&gt;Abstract&lt;p&gt;Whole grain and fiber intakes may decrease the risk of colorectal cancer. The interplay between host genetic factors, colonization of specific bacteria, production of short-chain fatty acids (SCFA), and intake of whole grains and fiber could alter the protective role of carbohydrates against colorectal cancer. Here, we assessed intakes of types and sources of carbohydrates in 114,217 UK Biobank participants with detailed dietary data (2–5 24-hour dietary assessments), and a host polygenic score (PGS) was applied to categorize participants as high or low for intraluminal microbial SCFA production, namely, butyrate and propionate. Multivariable Cox proportional hazards models were used to determine the associations of carbohydrates and SCFA with colorectal cancer incidence. During a median follow-up of 9.4 years, 1,193 participants were diagnosed with colorectal cancer. Risk was inversely associated with intakes of non-free sugar and whole grain fiber. Evidence of heterogeneity was observed by the butyrate PGS; consuming higher amounts of whole grain starch was only associated with a lower risk of colorectal cancer in those with predicted high SCFA production. Similarly, in additional analyses utilizing the larger UK Biobank cohort (&lt;i&gt;N&lt;/i&gt; = 343,621) with less detailed dietary assessment, only individuals with a high genetically predicted butyrate production had a lower risk of colorectal cancer per 5 g/day intake of bread and cereal fiber. This study suggests that colorectal cancer risk varies by intake of carbohydrate types and sources, and the impact of whole grain intake may be modified by SCFA production.&lt;/p&gt;Significance:&lt;p&gt;Prospective population-level analyses provide evidence supporting the importance of butyrate production in reduction of colorectal cancer risk by whole grain consumption.&lt;/p&gt;&lt;/div&gt;</jats:p>

Other

Watling CZ, Kelly RK, Murphy N, Gunter M, Piernas C, Bradbury KE, Schmidt JA, Key TJ, Perez-Cornago Aet 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>&lt;p&gt;Supplementary Material&lt;/p&gt;</jats:p>

Other

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