Browsing by Author "Shcherbina A"

Now showing 1 - 5 of 5
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    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 PT
    Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. Significance: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.
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    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 W
    Genome-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.
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    Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk
    (Springer Nature Limited, 2024-04-01) 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 J
    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.
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    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 KK
    Background 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.
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    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 U
    BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.