Browsing by Author "Hampel H"

Now showing 1 - 4 of 4
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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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    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 L
    Polygenic 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.
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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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    Subjective cognitive decline and rates of incident Alzheimer's disease and non–Alzheimer's disease dementia.
    (John Wiley and Sons Inc on behalf of The Alzheimer's Association, 2019-03) Slot RER; Sikkes SAM; Berkhof J; Brodaty H; Buckley R; Cavedo E; Dardiotis E; Guillo-Benarous F; Hampel H; Kochan NA; Lista S; Luck T; Maruff P; Molinuevo JL; Kornhuber J; Reisberg B; Riedel-Heller SG; Risacher SL; Roehr S; Sachdev PS; Scarmeas N; Scheltens P; Shulman MB; Saykin AJ; Verfaillie SCJ; Visser PJ; Vos SJB; Wagner M; Wolfsgruber S; Jessen F; Alzheimer's Disease Neuroimaging Initiative; DESCRIPA working group; INSIGHT-preAD study group; SCD-I working group; van der Flier WM
    Introduction In this multicenter study on subjective cognitive decline (SCD) in community-based and memory clinic settings, we assessed the (1) incidence of Alzheimer's disease (AD) and non-AD dementia and (2) determinants of progression to dementia. Methods Eleven cohorts provided 2978 participants with SCD and 1391 controls. We estimated dementia incidence and identified risk factors using Cox proportional hazards models. Results In SCD, incidence of dementia was 17.7 (95% Poisson confidence interval 15.2-20.3)/1000 person-years (AD: 11.5 [9.6-13.7], non-AD: 6.1 [4.7-7.7]), compared with 14.2 (11.3-17.6) in controls (AD: 10.1 [7.7-13.0], non-AD: 4.1 [2.6-6.0]). The risk of dementia was strongly increased in SCD in a memory clinic setting but less so in a community-based setting. In addition, higher age (hazard ratio 1.1 [95% confidence interval 1.1-1.1]), lower Mini–Mental State Examination (0.7 [0.66-0.8]), and apolipoprotein E ε4 (1.8 [1.3-2.5]) increased the risk of dementia. Discussion SCD can precede both AD and non-AD dementia. Despite their younger age, individuals with SCD in a memory clinic setting have a higher risk of dementia than those in community-based cohorts.