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Item Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations.(Springer Nature, 2023-10-02) 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; Küry S; Castellví-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 LPolygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.Item Bacterial lipopolysaccharide modulates immune response in the colorectal tumor microenvironment.(Nature Portfolio, 2023-08-23) Sulit AK; Daigneault M; Allen-Vercoe E; Silander OK; Hock B; McKenzie J; Pearson J; Frizelle FA; Schmeier S; Purcell RImmune responses can have opposing effects in colorectal cancer (CRC), the balance of which may determine whether a cancer regresses, progresses, or potentially metastasizes. These effects are evident in CRC consensus molecular subtypes (CMS) where both CMS1 and CMS4 contain immune infiltrates yet have opposing prognoses. The microbiome has previously been associated with CRC and immune response in CRC but has largely been ignored in the CRC subtype discussion. We used CMS subtyping on surgical resections from patients and aimed to determine the contributions of the microbiome to the pleiotropic effects evident in immune-infiltrated subtypes. We integrated host gene-expression and meta-transcriptomic data to determine the link between immune characteristics and microbiome contributions in these subtypes and identified lipopolysaccharide (LPS) binding as a potential functional mechanism. We identified candidate bacteria with LPS properties that could affect immune response, and tested the effects of their LPS on cytokine production of peripheral blood mononuclear cells (PBMCs). We focused on Fusobacterium periodonticum and Bacteroides fragilis in CMS1, and Porphyromonas asaccharolytica in CMS4. Treatment of PBMCs with LPS isolated from these bacteria showed that F. periodonticum stimulates cytokine production in PBMCs while both B. fragilis and P. asaccharolytica had an inhibitory effect. Furthermore, LPS from the latter two species can inhibit the immunogenic properties of F. periodonticum LPS when co-incubated with PBMCs. We propose that different microbes in the CRC tumor microenvironment can alter the local immune activity, with important implications for prognosis and treatment response.Item Probing the diabetes and colorectal cancer relationship using gene - environment interaction analyses.(Springer Nature, 2023-06-26) 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; Bézieau 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 UBACKGROUND: 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.Item Two genome-wide interaction loci modify the association of nonsteroidal anti-inflammatory drugs with colorectal cancer.(American Association for the Advancement of Science, 2024-05-29) Drew DA; Kim AE; Lin Y; Qu C; Morrison J; Lewinger JP; Kawaguchi E; Wang J; Fu Y; Zemlianskaia N; Díez-Obrero V; Bien SA; Dimou N; Albanes D; Baurley JW; Wu AH; Buchanan DD; Potter JD; Prentice RL; Harlid S; Arndt V; Barry EL; Berndt SI; Bouras E; Brenner H; Budiarto A; Burnett-Hartman A; Campbell PT; Carreras-Torres R; Casey G; Chang-Claude J; Conti DV; Devall MAM; Figueiredo JC; Gruber SB; Gsur A; Gunter MJ; Harrison TA; Hidaka A; Hoffmeister M; Huyghe JR; Jenkins MA; Jordahl KM; Kundaje A; Le Marchand L; Li L; Lynch BM; Murphy N; Nassir R; Newcomb PA; Newton CC; Obón-Santacana M; Ogino S; Ose J; Pai RK; Palmer JR; Papadimitriou N; Pardamean B; Pellatt AJ; Peoples AR; Platz EA; Rennert G; Ruiz-Narvaez E; Sakoda LC; Scacheri PC; Schmit SL; Schoen RE; Stern MC; Su Y-R; Thomas DC; Tian Y; Tsilidis KK; Ulrich CM; Um CY; van Duijnhoven FJB; Van Guelpen B; White E; Hsu L; Moreno V; Peters U; Chan AT; Gauderman WJRegular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.Item Identifying important microbial and genomic biomarkers for differentiating right- versus left-sided colorectal cancer using random forest models(BioMed Central Ltd, 2023-07-11) Kolisnik T; Sulit AK; Schmeier S; Frizelle F; Purcell R; Smith A; Silander OBACKGROUND: Colorectal cancer (CRC) is a heterogeneous disease, with subtypes that have different clinical behaviours and subsequent prognoses. There is a growing body of evidence suggesting that right-sided colorectal cancer (RCC) and left-sided colorectal cancer (LCC) also differ in treatment success and patient outcomes. Biomarkers that differentiate between RCC and LCC are not well-established. Here, we apply random forest (RF) machine learning methods to identify genomic or microbial biomarkers that differentiate RCC and LCC. METHODS: RNA-seq expression data for 58,677 coding and non-coding human genes and count data for 28,557 human unmapped reads were obtained from 308 patient CRC tumour samples. We created three RF models for datasets of human genes-only, microbes-only, and genes-and-microbes combined. We used a permutation test to identify features of significant importance. Finally, we used differential expression (DE) and paired Wilcoxon-rank sum tests to associate features with a particular side. RESULTS: RF model accuracy scores were 90%, 70%, and 87% with area under curve (AUC) of 0.9, 0.76, and 0.89 for the human genomic, microbial, and combined feature sets, respectively. 15 features were identified as significant in the model of genes-only, 54 microbes in the model of microbes-only, and 28 genes and 18 microbes in the model with genes-and-microbes combined. PRAC1 expression was the most important feature for differentiating RCC and LCC in the genes-only model, with HOXB13, SPAG16, HOXC4, and RNLS also playing a role. Ruminococcus gnavus and Clostridium acetireducens were the most important in the microbial-only model. MYOM3, HOXC4, Coprococcus eutactus, PRAC1, lncRNA AC012531.25, Ruminococcus gnavus, RNLS, HOXC6, SPAG16 and Fusobacterium nucleatum were most important in the combined model. CONCLUSIONS: Many of the identified genes and microbes among all models have previously established associations with CRC. However, the ability of RF models to account for inter-feature relationships within the underlying decision trees may yield a more sensitive and biologically interconnected set of genomic and microbial biomarkers.Item A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk.(American Association for Cancer Research, 2023-08-01) 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 FJ; 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 PTColorectal 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.Item Genome-wide interaction analysis of folate for colorectal cancer risk.(Elsevier B.V., 2023-11) Bouras E; Kim AE; Lin Y; Morrison J; Du M; Albanes D; Barry EL; Baurley JW; Berndt SI; Bien SA; Bishop TD; Brenner H; Budiarto A; Burnett-Hartman A; Campbell PT; Carreras-Torres R; Casey G; Cenggoro TW; Chan AT; Chang-Claude J; Conti DV; Cotterchio M; Devall M; Diez-Obrero V; Dimou N; Drew DA; Figueiredo JC; Giles GG; Gruber SB; Gunter MJ; Harrison TA; Hidaka A; Hoffmeister M; Huyghe JR; Joshi AD; Kawaguchi ES; Keku TO; Kundaje A; Le Marchand L; Lewinger JP; Li L; Lynch BM; Mahesworo B; Männistö S; Moreno V; Murphy N; Newcomb PA; Obón-Santacana M; Ose J; Palmer JR; Papadimitriou N; Pardamean B; Pellatt AJ; Peoples AR; Platz EA; Potter JD; Qi L; Qu C; Rennert G; Ruiz-Narvaez E; Sakoda LC; Schmit SL; Shcherbina A; Stern MC; Su Y-R; Tangen CM; Thomas DC; Tian Y; Um CY; van Duijnhoven FJ; Van Guelpen B; Visvanathan K; Wang J; White E; Wolk A; Woods MO; Ulrich CM; Hsu L; Gauderman WJ; Peters U; Tsilidis KKBackground Epidemiological and experimental evidence suggests that higher folate intake is associated with decreased colorectal cancer (CRC) risk; however, the mechanisms underlying this relationship are not fully understood. Genetic variation that may have a direct or indirect impact on folate metabolism can provide insights into folate’s role in CRC. Objectives Our aim was to perform a genome-wide interaction analysis to identify genetic variants that may modify the association of folate on CRC risk. Methods We applied traditional case-control logistic regression, joint 3-degree of freedom, and a 2-step weighted hypothesis approach to test the interactions of common variants (allele frequency >1%) across the genome and dietary folate, folic acid supplement use, and total folate in relation to risk of CRC in 30,550 cases and 42,336 controls from 51 studies from 3 genetic consortia (CCFR, CORECT, GECCO). Results Inverse associations of dietary, total folate, and folic acid supplement with CRC were found (odds ratio [OR]: 0.93; 95% confidence interval [CI]: 0.90, 0.96; and 0.91; 95% CI: 0.89, 0.94 per quartile higher intake, and 0.82 (95% CI: 0.78, 0.88) for users compared with nonusers, respectively). Interactions (P-interaction < 5×10-8) of folic acid supplement and variants in the 3p25.2 locus (in the region of Synapsin II [SYN2]/tissue inhibitor of metalloproteinase 4 [TIMP4]) were found using traditional interaction analysis, with variant rs150924902 (located upstream to SYN2) showing the strongest interaction. In stratified analyses by rs150924902 genotypes, folate supplementation was associated with decreased CRC risk among those carrying the TT genotype (OR: 0.82; 95% CI: 0.79, 0.86) but increased CRC risk among those carrying the TA genotype (OR: 1.63; 95% CI: 1.29, 2.05), suggesting a qualitative interaction (P-interaction = 1.4×10-8). No interactions were observed for dietary and total folate. Conclusions Variation in 3p25.2 locus may modify the association of folate supplement with CRC risk. Experimental studies and studies incorporating other relevant omics data are warranted to validate this finding.Item Prospective and Mendelian randomization analyses on the association of circulating fatty acid binding protein 4 (FABP-4) and risk of colorectal cancer.(BioMed Central, 2023-10-13) Nimptsch K; Aleksandrova K; Pham TT; Papadimitriou N; Janke J; Christakoudi S; Heath A; Olsen A; Tjønneland A; Schulze MB; Katzke V; Kaaks R; van Guelpen B; Harbs J; Palli D; Macciotta A; Pasanisi F; Yohar SMC; Guevara M; Amiano P; Grioni S; Jakszyn PG; Figueiredo JC; Samadder NJ; Li CI; Moreno V; Potter JD; Schoen RE; Um CY; Weiderpass E; Jenab M; Gunter MJ; Pischon TBACKGROUND: Fatty acid binding protein 4 (FABP-4) is a lipid-binding adipokine upregulated in obesity, which may facilitate fatty acid supply for tumor growth and promote insulin resistance and inflammation and may thus play a role in colorectal cancer (CRC) development. We aimed to investigate the association between circulating FABP-4 and CRC and to assess potential causality using a Mendelian randomization (MR) approach. METHODS: The association between pre-diagnostic plasma measurements of FABP-4 and CRC risk was investigated in a nested case-control study in 1324 CRC cases and the same number of matched controls within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. A two-sample Mendelian randomization study was conducted based on three genetic variants (1 cis, 2 trans) associated with circulating FABP-4 identified in a published genome-wide association study (discovery n = 20,436) and data from 58,131 CRC cases and 67,347 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry. RESULTS: In conditional logistic regression models adjusted for potential confounders including body size, the estimated relative risk, RR (95% confidence interval, CI) per one standard deviation, SD (8.9 ng/mL) higher FABP-4 concentration was 1.01 (0.92, 1.12) overall, 0.95 (0.80, 1.13) in men and 1.09 (0.95, 1.25) in women. Genetically determined higher FABP-4 was not associated with colorectal cancer risk (RR per FABP-4 SD was 1.10 (0.95, 1.27) overall, 1.03 (0.84, 1.26) in men and 1.21 (0.98, 1.48) in women). However, in a cis-MR approach, a statistically significant association was observed in women (RR 1.56, 1.09, 2.23) but not overall (RR 1.23, 0.97, 1.57) or in men (0.99, 0.71, 1.37). CONCLUSIONS: Taken together, these analyses provide no support for a causal role of circulating FABP-4 in the development of CRC, although the cis-MR provides some evidence for a positive association in women, which may deserve to be investigated further.Item Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes.(Springer Nature, 2024-04-26) Chen Z; Guo X; Tao R; Huyghe JR; Law PJ; Fernandez-Rozadilla C; Ping J; Jia G; Long J; Li C; Shen Q; Xie Y; Timofeeva MN; Thomas M; Schmit SL; Díez-Obrero V; Devall M; Moratalla-Navarro F; Fernandez-Tajes J; Palles C; Sherwood K; Briggs SEW; Svinti V; Donnelly K; Farrington SM; Blackmur J; Vaughan-Shaw PG; Shu X-O; Lu Y; Broderick P; Studd J; Harrison TA; Conti DV; Schumacher FR; Melas M; Rennert G; Obón-Santacana M; Martín-Sánchez V; Oh JH; Kim J; Jee SH; Jung KJ; Kweon S-S; Shin M-H; Shin A; Ahn Y-O; Kim D-H; Oze I; Wen W; Matsuo K; Matsuda K; Tanikawa C; Ren Z; Gao Y-T; Jia W-H; Hopper JL; Jenkins MA; Win AK; Pai RK; Figueiredo JC; Haile RW; Gallinger S; Woods MO; Newcomb PA; Duggan D; Cheadle JP; Kaplan R; Kerr R; Kerr D; Kirac I; Böhm J; Mecklin J-P; Jousilahti P; Knekt P; Aaltonen LA; Rissanen H; Pukkala E; Eriksson JG; Cajuso T; Hänninen U; Kondelin J; Palin K; Tanskanen T; Renkonen-Sinisalo L; Männistö S; Albanes D; Weinstein SJ; Ruiz-Narvaez E; Palmer JR; Buchanan DD; Platz EA; Visvanathan K; Ulrich CM; Siegel E; Brezina S; Gsur A; Campbell PT; Chang-Claude J; Hoffmeister M; Brenner H; Slattery ML; Potter JD; Tsilidis KK; Schulze MB; Gunter MJ; Murphy N; Castells A; Castellví-Bel S; Moreira L; Arndt V; Shcherbina A; Bishop DT; Giles GG; Southey MC; Idos GE; McDonnell KJ; Abu-Ful Z; Greenson JK; Shulman K; Lejbkowicz F; Offit K; Su Y-R; Steinfelder R; Keku TO; van Guelpen B; Hudson TJ; Hampel H; Pearlman R; Berndt SI; Hayes RB; Martinez ME; Thomas SS; Pharoah PDP; Larsson SC; Yen Y; Lenz H-J; White E; Li L; Doheny KF; Pugh E; Shelford T; Chan AT; Cruz-Correa M; Lindblom A; Hunter DJ; Joshi AD; Schafmayer C; Scacheri PC; Kundaje A; Schoen RE; Hampe J; Stadler ZK; Vodicka P; Vodickova L; Vymetalkova V; Edlund CK; Gauderman WJ; Shibata D; Toland A; Markowitz S; Kim A; Chanock SJ; van Duijnhoven F; Feskens EJM; Sakoda LC; Gago-Dominguez M; Wolk A; Pardini B; FitzGerald LM; Lee SC; Ogino S; Bien SA; Kooperberg C; Li CI; Lin Y; Prentice R; Qu C; Bézieau S; Yamaji T; Sawada N; Iwasaki M; Le Marchand L; Wu AH; Qu C; McNeil CE; Coetzee G; Hayward C; Deary IJ; Harris SE; Theodoratou E; Reid S; Walker M; Ooi LY; Lau KS; Zhao H; Hsu L; Cai Q; Dunlop MG; Gruber SB; Houlston RS; Moreno V; Casey G; Peters U; Tomlinson I; Zheng WGenome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.Item Barriers and facilitators to colorectal cancer diagnosis in New Zealand: a qualitative study(BioMed Central Ltd, 2020-10-01) Blackmore T; Norman K; Kidd J; Cassim S; Chepulis L; Keenan R; Firth M; Jackson C; Stokes T; Weller D; Emery J; Lawrenson RBackground New Zealand (NZ) has high rates of colorectal cancer but low rates of early diagnosis. Due to a lack of understanding of the pre-diagnostic experience from the patient’s perspective, it is necessary to investigate potential patient and health system factors that contribute to longer diagnostic intervals. Previous qualitative studies have discussed delays using The Model of Pathways to Treatment, but this has not been explored in the NZ context. This study aimed to understand the patient experience and perception of their general practitioner (GP) through the diagnostic process in the Waikato region of NZ. In particular, we sought to investigate potential barriers and facilitators that contribute to longer diagnostic intervals. Methods Ethical approval for this study was granted by the New Zealand Health and Disability Ethics Committee. Twenty-eight participants, diagnosed with colorectal cancer, were interviewed about their experience. Semi-structured interviews were audio recorded, transcribed verbatim and analysed thematically using The Model of Pathways to Treatment framework (intervals: appraisal, help-seeking, diagnostic). Results Participant appraisal of symptoms was a barrier to prompt diagnosis, particularly if symptoms were normalised, intermittent, or isolated in occurrence. Successful self-management techniques also resulted in delayed help-seeking. However if symptoms worsened, disruption to work and daily routines were important facilitators to seeking a GP consultation. Participants positively appraised GPs if they showed good technical competence and were proactive in investigating symptoms. Negative GP appraisals were associated with a lack of physical examinations and misdiagnosis, and left participants feeling dehumanised during the diagnostic process. However high levels of GP interpersonal competence could override poor technical competence, resulting in an overall positive experience, even if the cancer was diagnosed at an advanced stage. Māori participants often appraised symptoms inclusive of their sociocultural environment and considered the impact of their symptoms in relation to family. Conclusions The findings of this study highlight the importance of tailored colorectal cancer symptom communication in health campaigns, and indicate the significance of the interpersonal competence aspect of GP-patient interactions. These findings suggest that interpersonal competence be overtly displayed in all GP interactions to ensure a higher likelihood of a positive experience for the patient.