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2. Polymorphisms of an innate immune gene, toll-like receptor 4, and aggressive prostate cancer risk: A systematic review and meta-analysis

Author

Witte, John, Weng, PH, Huang, YL, Page, JH, Chen, JH, Xu, J, Koutros, S, Berndt, S, Chanock, S, Yeager, M, and Witte, JS

Abstract

© 2014 Weng et al.Background: Toll-like receptor 4 (TLR4) is one of the best known TLR members expressed on the surface of several leukocytes and tissue cells and has a key function in detecting pathogen and danger-associated molecular patterns. The role o

Published
2014

3. Voluntary math remediation for STEM and economics disciplines – who is attending at all? Evidence from Germany.

Author

Büchele, S., Berndt, S., and Felix, A.

Abstract

Most studies on remedial courses are based on their mandatory attendance. However, changes may have occurred in the attendance policy of developmental math courses since the state of Florida decided to overcome obligatory math remediation for unprepared students. Consequently, researchers have recently started focusing on voluntary math remedial courses. In general, literature that goes back to the 1980s suggests that developmental coursework should be mandatory for unprepared first-year students. Since most universities in the US have always followed these recommendations, hardly any empirical evidence exists for the participation of students in voluntary remediation. Conversely, the remedial education system in Europe and particularly Germany is primarily voluntary. Therefore, this study exploratively examines the participation of students in two optional developmental math courses: a so-called preparatory course and a so-called bridging course. The findings suggest that summer-school-like preparatory courses miss their target group of at-risk students, whereas semester-running bridging courses reach it. [ABSTRACT FROM AUTHOR]

Published
2024
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6. A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Author

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, PT, 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, and Campbell, PT

Abstract

UNLABELLED: 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.

Published
2023

7. Prognostic role of detailed colorectal location and tumor molecular features: analyses of 13,101 colorectal cancer patients including 2994 early-onset cases

Author

Ugai, T, Akimoto, N, Haruki, K, Harrison, TA, Cao, Y, Qu, C, Chan, AT, Campbell, PT, Berndt, S, Buchanan, DD, Cross, AJ, Diergaarde, B, Gallinger, SJ, Gunter, MJ, Harlid, S, Hidaka, A, Hoffmeister, M, Brenner, H, Chang-Claude, J, Hsu, L, Jenkins, MA, Lin, Y, Milne, RL, Moreno, V, Newcomb, PA, Nishihara, R, Obon-Santacana, M, Pai, RK, Sakoda, LC, Schoen, RE, Slattery, ML, Sun, W, Amitay, EL, Alwers, E, Thibodeau, SN, Toland, AE, Van Guelpen, B, Zaidi, SH, Potter, JD, Meyerhardt, JA, Giannakis, M, Song, M, Nowak, JA, Peters, U, Phipps, A, Ogino, S, Ugai, T, Akimoto, N, Haruki, K, Harrison, TA, Cao, Y, Qu, C, Chan, AT, Campbell, PT, Berndt, S, Buchanan, DD, Cross, AJ, Diergaarde, B, Gallinger, SJ, Gunter, MJ, Harlid, S, Hidaka, A, Hoffmeister, M, Brenner, H, Chang-Claude, J, Hsu, L, Jenkins, MA, Lin, Y, Milne, RL, Moreno, V, Newcomb, PA, Nishihara, R, Obon-Santacana, M, Pai, RK, Sakoda, LC, Schoen, RE, Slattery, ML, Sun, W, Amitay, EL, Alwers, E, Thibodeau, SN, Toland, AE, Van Guelpen, B, Zaidi, SH, Potter, JD, Meyerhardt, JA, Giannakis, M, Song, M, Nowak, JA, Peters, U, Phipps, A, and Ogino, S

Abstract

BACKGROUND: The pathogenic effect of colorectal tumor molecular features may be influenced by several factors, including those related to microbiota, inflammation, metabolism, and epigenetics, which may change along colorectal segments. We hypothesized that the prognostic association of colon cancer location might differ by tumor molecular characteristics. METHODS: Utilizing a consortium dataset of 13,101 colorectal cancer cases, including 2994 early-onset cases, we conducted survival analyses of detailed tumor location stratified by statuses of microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and KRAS and BRAF oncogenic mutation. RESULTS: There was a statistically significant trend for better colon cancer-specific survival in relation to tumor location from the cecum to sigmoid colon (Ptrend = 0.002), excluding the rectum. The prognostic association of colon location differed by MSI status (Pinteraction = 0.001). Non-MSI-high tumors exhibited the cecum-to-sigmoid trend for better colon cancer-specific survival [Ptrend < 0.001; multivariable hazard ratio (HR) for the sigmoid colon (vs. cecum), 0.80; 95% confidence interval (CI) 0.70-0.92], whereas MSI-high tumors demonstrated a suggestive cecum-to-sigmoid trend for worse survival (Ptrend = 0.020; the corresponding HR, 2.13; 95% CI 1.15-3.92). The prognostic association of colon tumor location also differed by CIMP status (Pinteraction = 0.003) but not significantly by age, stage, or other features. Furthermore, MSI-high status was a favorable prognostic indicator in all stages. CONCLUSIONS: Both detailed colonic location and tumor molecular features need to be accounted for colon cancer prognostication to advance precision medicine. Our study indicates the important role of large-scale studies to robustly examine detailed colonic subsites in molecular oncology research.

Published
2023

8. Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

Author

Fernandez-Rozadilla, C, Timofeeva, M, Chen, Z, Law, P, Thomas, M, Bien, S, Diez-Obrero, V, Li, L, Fernandez-Tajes, J, Palles, C, Sherwood, K, Harris, S, Svinti, V, McDonnell, K, Farrington, S, Studd, J, Vaughan-Shaw, P, Shu, X-O, Long, J, Cai, Q, Guo, X, Lu, Y, Scacheri, P, Huyghe, J, Harrison, T, Shibata, D, Haiman, C, Devall, M, Schumacher, F, Melas, M, Rennert, G, Obon-Santacana, M, Martin-Sanchez, V, Moratalla-Navarro, F, 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, Potter, J, Jenkins, M, Win, AK, Pai, R, Figueiredo, J, Haile, R, Gallinger, S, Woods, M, Newcomb, P, Cheadle, J, Kaplan, R, Maughan, T, Kerr, R, Kerr, D, Kirac, I, Boehm, J, Mecklin, L-P, Jousilahti, P, Knekt, P, Aaltonen, L, Rissanen, H, Pukkala, E, Eriksson, J, Cajuso, T, Hanninen, U, Kondelin, J, Palin, K, Tanskanen, T, Renkonen-Sinisalo, L, Zanke, B, Mannisto, S, Albanes, D, Weinstein, S, Ruiz-Narvaez, E, Palmer, J, Buchanan, D, Platz, E, Visvanathan, K, Ulrich, C, Siegel, E, Brezina, S, Gsur, A, Campbell, P, Chang-Claude, J, Hoffmeister, M, Brenner, H, Slattery, M, Tsilidis, K, Schulze, M, Gunter, M, Murphy, N, Castells, A, Castellvi-Bel, S, Moreira, L, Arndt, V, Shcherbina, A, Stern, M, Pardamean, B, Bishop, T, Giles, G, Southey, M, Idos, G, Abu-Ful, Z, Greenson, J, Shulman, K, Lejbkowicz, F, Offit, K, Su, Y-R, Steinfelder, R, Keku, T, van Guelpen, B, Hudson, T, Hampel, H, Pearlman, R, Berndt, S, Hayes, R, Martinez, ME, Thomas, S, Corley, D, Pharoah, P, Larsson, S, Yen, Y, Lenz, H-J, White, E, Doheny, K, Pugh, E, Shelford, T, Chan, A, Cruz-Correa, M, Lindblom, A, Joshi, A, Schafmayer, C, Kundaje, A, Nickerson, D, Schoen, R, Hampe, J, Stadler, Z, Vodicka, P, Vodickova, L, Vymetalkova, V, Papadopoulos, N, Edlund, C, Gauderman, W, Thomas, D, Toland, A, Markowitz, S, Kim, A, Gruber, S, van Duijnhoven, F, Feskens, E, Sakoda, L, Gago-Dominguez, M, Wolk, A, Naccarati, A, Pardini, B, FitzGerald, L, Lee, SC, Ogino, S, Kooperberg, C, Li, C, Lin, Y, Prentice, R, Qu, C, Bezieau, S, Tangen, C, Mardis, E, Yamaji, T, Sawada, N, Iwasaki, M, Le Marchand, L, Wu, A, McNeil, C, Coetzee, G, Hayward, C, Deary, I, Theodoratou, E, Reid, S, Walker, M, Ooi, LY, Moreno, V, Casey, G, Tomlinson, I, Zheng, W, Dunlop, M, Houlston, R, Peters, U, Fernandez-Rozadilla, C, Timofeeva, M, Chen, Z, Law, P, Thomas, M, Bien, S, Diez-Obrero, V, Li, L, Fernandez-Tajes, J, Palles, C, Sherwood, K, Harris, S, Svinti, V, McDonnell, K, Farrington, S, Studd, J, Vaughan-Shaw, P, Shu, X-O, Long, J, Cai, Q, Guo, X, Lu, Y, Scacheri, P, Huyghe, J, Harrison, T, Shibata, D, Haiman, C, Devall, M, Schumacher, F, Melas, M, Rennert, G, Obon-Santacana, M, Martin-Sanchez, V, Moratalla-Navarro, F, 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, Potter, J, Jenkins, M, Win, AK, Pai, R, Figueiredo, J, Haile, R, Gallinger, S, Woods, M, Newcomb, P, Cheadle, J, Kaplan, R, Maughan, T, Kerr, R, Kerr, D, Kirac, I, Boehm, J, Mecklin, L-P, Jousilahti, P, Knekt, P, Aaltonen, L, Rissanen, H, Pukkala, E, Eriksson, J, Cajuso, T, Hanninen, U, Kondelin, J, Palin, K, Tanskanen, T, Renkonen-Sinisalo, L, Zanke, B, Mannisto, S, Albanes, D, Weinstein, S, Ruiz-Narvaez, E, Palmer, J, Buchanan, D, Platz, E, Visvanathan, K, Ulrich, C, Siegel, E, Brezina, S, Gsur, A, Campbell, P, Chang-Claude, J, Hoffmeister, M, Brenner, H, Slattery, M, Tsilidis, K, Schulze, M, Gunter, M, Murphy, N, Castells, A, Castellvi-Bel, S, Moreira, L, Arndt, V, Shcherbina, A, Stern, M, Pardamean, B, Bishop, T, Giles, G, Southey, M, Idos, G, Abu-Ful, Z, Greenson, J, Shulman, K, Lejbkowicz, F, Offit, K, Su, Y-R, Steinfelder, R, Keku, T, van Guelpen, B, Hudson, T, Hampel, H, Pearlman, R, Berndt, S, Hayes, R, Martinez, ME, Thomas, S, Corley, D, Pharoah, P, Larsson, S, Yen, Y, Lenz, H-J, White, E, Doheny, K, Pugh, E, Shelford, T, Chan, A, Cruz-Correa, M, Lindblom, A, Joshi, A, Schafmayer, C, Kundaje, A, Nickerson, D, Schoen, R, Hampe, J, Stadler, Z, Vodicka, P, Vodickova, L, Vymetalkova, V, Papadopoulos, N, Edlund, C, Gauderman, W, Thomas, D, Toland, A, Markowitz, S, Kim, A, Gruber, S, van Duijnhoven, F, Feskens, E, Sakoda, L, Gago-Dominguez, M, Wolk, A, Naccarati, A, Pardini, B, FitzGerald, L, Lee, SC, Ogino, S, Kooperberg, C, Li, C, Lin, Y, Prentice, R, Qu, C, Bezieau, S, Tangen, C, Mardis, E, Yamaji, T, Sawada, N, Iwasaki, M, Le Marchand, L, Wu, A, McNeil, C, Coetzee, G, Hayward, C, Deary, I, Theodoratou, E, Reid, S, Walker, M, Ooi, LY, Moreno, V, Casey, G, Tomlinson, I, Zheng, W, Dunlop, M, Houlston, R, and Peters, U

Abstract

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

Published
2023

9. Body mass index and molecular subtypes of colorectal cancer

Author

Murphy, N, Newton, CC, Song, M, Papadimitriou, N, Hoffmeister, M, Phipps, A, Harrison, TA, Newcomb, PA, Aglago, EK, Berndt, S, Brenner, H, Buchanan, DD, Cao, Y, Chan, AT, Chen, X, Cheng, I, Chang-Claude, J, Dimou, N, Drew, D, Farris, AB, French, AJ, Gallinger, S, Georgeson, P, Giannakis, M, Giles, GG, Gruber, SB, Harlid, S, Hsu, L, Huang, W-Y, Jenkins, MA, Laskar, RS, Le Marchand, L, Limburg, P, Lin, Y, Mandic, M, Nowak, JA, Obon-Santacana, M, Ogino, S, Qu, C, Sakoda, LC, Schoen, RE, Southey, MC, Stadler, ZK, Steinfelder, RS, Sun, W, Thibodeau, SN, Toland, AE, Trinh, QM, Tsilidis, KK, Ugai, T, Van Guelpen, B, Wang, X, Woods, MO, Zaidi, SH, Gunter, MJ, Peters, U, Campbell, PT, Murphy, N, Newton, CC, Song, M, Papadimitriou, N, Hoffmeister, M, Phipps, A, Harrison, TA, Newcomb, PA, Aglago, EK, Berndt, S, Brenner, H, Buchanan, DD, Cao, Y, Chan, AT, Chen, X, Cheng, I, Chang-Claude, J, Dimou, N, Drew, D, Farris, AB, French, AJ, Gallinger, S, Georgeson, P, Giannakis, M, Giles, GG, Gruber, SB, Harlid, S, Hsu, L, Huang, W-Y, Jenkins, MA, Laskar, RS, Le Marchand, L, Limburg, P, Lin, Y, Mandic, M, Nowak, JA, Obon-Santacana, M, Ogino, S, Qu, C, Sakoda, LC, Schoen, RE, Southey, MC, Stadler, ZK, Steinfelder, RS, Sun, W, Thibodeau, SN, Toland, AE, Trinh, QM, Tsilidis, KK, Ugai, T, Van Guelpen, B, Wang, X, Woods, MO, Zaidi, SH, Gunter, MJ, Peters, U, and Campbell, PT

Abstract

BACKGROUND: Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. METHODS: We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. RESULTS: Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). CONCLUSIONS: In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.

Published
2023

10. TET2 binds the androgen receptor and loss is associated with prostate cancer

Author

Nickerson, M L, Das, S, Im, K M, Turan, S, Berndt, S I, Li, H, Lou, H, Brodie, S A, Billaud, J N, Zhang, T, Bouk, A J, Butcher, D, Wang, Z, Sun, L, Misner, K, Tan, W, Esnakula, A, Esposito, D, Huang, W Y, Hoover, R N, Tucker, M A, Keller, J R, Boland, J, Brown, K, Anderson, S K, Moore, L E, Isaacs, W B, Chanock, S J, Yeager, M, Dean, M, and Andresson, T

Published
2017
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19. Prostate cancer risk stratification improvement across multiple ancestries with new polygenic hazard score

Author

Minh-Phuong, H-L, Karunamuni, R, Fan, CC, Asona, L, Thompson, WK, Martinez, ME, Eeles, RA, Kote-Jarai, Z, Muir, KR, Lophatananon, A, Schleutker, J, Pashayan, N, Batra, J, Groenberg, H, Neal, DE, Nordestgaard, BG, Tangen, CM, MacInnis, RJ, Wolk, A, Albanes, D, Haiman, CA, Travis, RC, Blot, WJ, Stanford, JL, Mucci, LA, West, CML, Nielsen, SF, Kibel, AS, Cussenot, O, Berndt, S, Koutros, S, Sorensen, KD, Cybulski, C, Grindedal, EM, Menegaux, F, Park, JY, Ingles, SA, Maier, C, Hamilton, RJ, Rosenstein, BS, Lu, Y-J, Watya, S, Vega, A, Kogevinas, M, Wiklund, F, Penney, KL, Huff, CD, Teixeira, MR, Multigner, L, Leach, RJ, Brenner, H, John, EM, Kaneva, R, Logothetis, CJ, Neuhausen, SL, De Ruyck, K, Ost, P, Razack, A, Newcomb, LF, Fowke, JH, Gamulin, M, Abraham, A, Claessens, F, Castelao, JE, Townsend, PA, Crawford, DC, Petrovics, G, van Schaik, RHN, Parent, M-E, Hu, JJ, Zheng, W, Mills, IG, Andreassen, OA, Dale, AM, Seibert, TM, Minh-Phuong, H-L, Karunamuni, R, Fan, CC, Asona, L, Thompson, WK, Martinez, ME, Eeles, RA, Kote-Jarai, Z, Muir, KR, Lophatananon, A, Schleutker, J, Pashayan, N, Batra, J, Groenberg, H, Neal, DE, Nordestgaard, BG, Tangen, CM, MacInnis, RJ, Wolk, A, Albanes, D, Haiman, CA, Travis, RC, Blot, WJ, Stanford, JL, Mucci, LA, West, CML, Nielsen, SF, Kibel, AS, Cussenot, O, Berndt, S, Koutros, S, Sorensen, KD, Cybulski, C, Grindedal, EM, Menegaux, F, Park, JY, Ingles, SA, Maier, C, Hamilton, RJ, Rosenstein, BS, Lu, Y-J, Watya, S, Vega, A, Kogevinas, M, Wiklund, F, Penney, KL, Huff, CD, Teixeira, MR, Multigner, L, Leach, RJ, Brenner, H, John, EM, Kaneva, R, Logothetis, CJ, Neuhausen, SL, De Ruyck, K, Ost, P, Razack, A, Newcomb, LF, Fowke, JH, Gamulin, M, Abraham, A, Claessens, F, Castelao, JE, Townsend, PA, Crawford, DC, Petrovics, G, van Schaik, RHN, Parent, M-E, Hu, JJ, Zheng, W, Mills, IG, Andreassen, OA, Dale, AM, and Seibert, TM

Abstract

BACKGROUND: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively. CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry d

Published
2022

20. Validation and functional characterization of GWAS-identified variants for chronic lymphocytic leukemia: a CRuCIAL study

Author

García-Martín, P., Díez, A.M., Maldonado, J.M.S., Serrano, A.J.C., Horst, R. ter, Benavente, Y., Landi, S., Macauda, A., Clay-Gilmour, A., Hernández-Mohedo, F., Niazi, Y., González-Sierra, P., Espinet, B., Rodríguez-Sevilla, J.J., Maffei, R., Blanco, G., Giaccherini, M., Puiggros, A., Cerhan, J., Marasca, R., Cañadas-Garre, M., López-Nevot, M., Chen-Liang, T., Thomsen, H., Gámez, I., Moreno, V., Marcos-Gragera, R., García-Álvarez, M., Llorca, J., Jerez, A., Berndt, S., Butrym, A., Norman, A.D., Casabonne, D., Luppi, M., Slager, S.L., Hemminki, K., Li, Y., Alcoceba, M., Campa, D., Canzian, F., Sanjosé, S. de, Försti, A., Netea, M.G., Jurado, M., Sainz, J., García-Martín, P., Díez, A.M., Maldonado, J.M.S., Serrano, A.J.C., Horst, R. ter, Benavente, Y., Landi, S., Macauda, A., Clay-Gilmour, A., Hernández-Mohedo, F., Niazi, Y., González-Sierra, P., Espinet, B., Rodríguez-Sevilla, J.J., Maffei, R., Blanco, G., Giaccherini, M., Puiggros, A., Cerhan, J., Marasca, R., Cañadas-Garre, M., López-Nevot, M., Chen-Liang, T., Thomsen, H., Gámez, I., Moreno, V., Marcos-Gragera, R., García-Álvarez, M., Llorca, J., Jerez, A., Berndt, S., Butrym, A., Norman, A.D., Casabonne, D., Luppi, M., Slager, S.L., Hemminki, K., Li, Y., Alcoceba, M., Campa, D., Canzian, F., Sanjosé, S. de, Försti, A., Netea, M.G., Jurado, M., and Sainz, J.

Abstract

Contains fulltext : 251927.pdf (Publisher’s version ) (Open Access)

Published
2022

21. Identifying colorectal cancer caused by biallelic MUTYH pathogenic variants using tumor mutational signatures

Author

Georgeson, P, Harrison, TA, Pope, BJ, Zaidi, SH, Qu, C, Steinfelder, RS, Lin, Y, Joo, JE, Mahmood, K, Clendenning, M, Walker, R, Amitay, EL, Berndt, S, Brenner, H, Campbell, PT, Cao, Y, Chan, AT, Chang-Claude, J, Doheny, KF, Drew, DA, Figueiredo, JC, French, AJ, Gallinger, S, Giannakis, M, Giles, GG, Gsur, A, Gunter, MJ, Hoffmeister, M, Hsu, L, Huang, W-Y, Limburg, P, Manson, JE, Moreno, V, Nassir, R, Nowak, JA, Obon-Santacana, M, Ogino, S, Phipps, A, Potter, JD, Schoen, RE, Sun, W, Toland, AE, Trinh, QM, Ugai, T, Macrae, FA, Rosty, C, Hudson, TJ, Jenkins, MA, Thibodeau, SN, Winship, IM, Peters, U, Buchanan, DD, Georgeson, P, Harrison, TA, Pope, BJ, Zaidi, SH, Qu, C, Steinfelder, RS, Lin, Y, Joo, JE, Mahmood, K, Clendenning, M, Walker, R, Amitay, EL, Berndt, S, Brenner, H, Campbell, PT, Cao, Y, Chan, AT, Chang-Claude, J, Doheny, KF, Drew, DA, Figueiredo, JC, French, AJ, Gallinger, S, Giannakis, M, Giles, GG, Gsur, A, Gunter, MJ, Hoffmeister, M, Hsu, L, Huang, W-Y, Limburg, P, Manson, JE, Moreno, V, Nassir, R, Nowak, JA, Obon-Santacana, M, Ogino, S, Phipps, A, Potter, JD, Schoen, RE, Sun, W, Toland, AE, Trinh, QM, Ugai, T, Macrae, FA, Rosty, C, Hudson, TJ, Jenkins, MA, Thibodeau, SN, Winship, IM, Peters, U, and Buchanan, DD

Abstract

Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87-100%)). All monoallelic MUTYH carriers are classified with the non-MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers (p = 2 × 10-23 and p = 6 × 10-11, respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers.

Published
2022

22. A saturated map of common genetic variants associated with human height

Author

Yengo, L, Vedantam, S, Marouli, E, Sidorenko, J, Bartell, E, Sakaue, S, Graff, M, Eliasen, AU, Jiang, Y, Raghavan, S, Miao, J, Arias, JD, Graham, SE, Mukamel, RE, Spracklen, CN, Yin, X, Chen, S-H, Ferreira, T, Highland, HH, Ji, Y, Karaderi, T, Lin, K, Lull, K, Malden, DE, Medina-Gomez, C, Machado, M, Moore, A, Rueger, S, Sim, X, Vrieze, S, Ahluwalia, TS, Akiyama, M, Allison, MA, Alvarez, M, Andersen, MK, Ani, A, Appadurai, V, Arbeeva, L, Bhaskar, S, Bielak, LF, Bollepalli, S, Bonnycastle, LL, Bork-Jensen, J, Bradfield, JP, Bradford, Y, Braund, PS, Brody, JA, Burgdorf, KS, Cade, BE, Cai, H, Cai, Q, Campbell, A, Canadas-Garre, M, Catamo, E, Chai, J-F, Chai, X, Chang, L-C, Chang, Y-C, Chen, C-H, Chesi, A, Choi, SH, Chung, R-H, Cocca, M, Concas, MP, Couture, C, Cuellar-Partida, G, Danning, R, Daw, EW, Degenhard, F, Delgado, GE, Delitala, A, Demirkan, A, Deng, X, Devineni, P, Dietl, A, Dimitriou, M, Dimitrov, L, Dorajoo, R, Ekici, AB, Engmann, JE, Fairhurst-Hunter, Z, Farmaki, A-E, Faul, JD, Fernandez-Lopez, J-C, Forer, L, Francescatto, M, Freitag-Wolf, S, Fuchsberger, C, Galesloot, TE, Gao, Y, Gao, Z, Geller, F, Giannakopoulou, O, Giulianini, F, Gjesing, AP, Goel, A, Gordon, SD, Gorski, M, Grove, J, Guo, X, Gustafsson, S, Haessler, J, Hansen, TF, Havulinna, AS, Haworth, SJ, He, J, Heard-Costa, N, Hebbar, P, Hindy, G, Ho, Y-LA, Hofer, E, Holliday, E, Horn, K, Hornsby, WE, Hottenga, J-J, Huang, H, Huang, J, Huerta-Chagoya, A, Huffman, JE, Hung, Y-J, Huo, S, Hwang, MY, Iha, H, Ikeda, DD, Isono, M, Jackson, AU, Jager, S, Jansen, IE, Johansson, I, Jonas, JB, Jonsson, A, Jorgensen, T, Kalafati, I-P, Kanai, M, Kanoni, S, Karhus, LL, Kasturiratne, A, Katsuya, T, Kawaguchi, T, Kember, RL, Kentistou, KA, Kim, H-N, Kim, YJ, Kleber, ME, Knol, MJ, Kurbasic, A, Lauzon, M, Le, P, Lea, R, Lee, J-Y, Leonard, HL, Li, SA, Li, X, Liang, J, Lin, H, Lin, S-Y, Liu, J, Liu, X, Lo, KS, Long, J, Lores-Motta, L, Luan, J, Lyssenko, V, Lyytikainen, L-P, Mahajan, A, Mamakou, V, Mangino, M, Manichaikul, A, Marten, J, Mattheisen, M, Mavarani, L, McDaid, AF, Meidtner, K, Melendez, TL, Mercader, JM, Milaneschi, Y, Miller, JE, Millwood, IY, Mishra, PP, Mitchell, RE, Mollehave, LT, Morgan, A, Mucha, S, Munz, M, Nakatochi, M, Nelson, CP, Nethander, M, Nho, CW, Nielsen, AA, Nolte, IM, Nongmaithem, SS, Noordam, R, Ntalla, I, Nutile, T, Pandit, A, Christofidou, P, Parna, K, Pauper, M, Petersen, ERB, Petersen, L, Pitkanen, N, Polasek, O, Poveda, A, Preuss, MH, Pyarajan, S, Raffield, LM, Rakugi, H, Ramirez, J, Rasheed, A, Raven, D, Rayner, NW, Riveros, C, Rohde, R, Ruggiero, D, Ruotsalainen, SE, Ryan, KA, Sabater-Lleal, M, Saxena, R, Scholz, M, Sendamarai, A, Shen, B, Shi, J, Shin, JH, Sidore, C, Sitlani, CM, Slieker, RKC, Smit, RAJ, Smith, A, Smith, JA, Smyth, LJ, Southam, LE, Steinthorsdottir, V, Sun, L, Takeuchi, F, Tallapragada, D, Taylor, KD, Tayo, BO, Tcheandjieu, C, Terzikhan, N, Tesolin, P, Teumer, A, Theusch, E, Thompson, DJ, Thorleifsson, G, Timmers, PRHJ, Trompet, S, Turman, C, Vaccargiu, S, van der Laan, SW, van der Most, PJ, van Klinken, JB, van Setten, J, Verma, SS, Verweij, N, Veturi, Y, Wang, CA, Wang, C, Wang, L, Wang, Z, Warren, HR, Wei, WB, Wickremasinghe, AR, Wielscher, M, Wiggins, KL, Winsvold, BS, Wong, A, Wu, Y, Wuttke, M, Xia, R, Xie, T, Yamamoto, K, Yang, J, Yao, J, Young, H, Yousri, NA, Yu, L, Zeng, L, Zhang, W, Zhang, X, Zhao, J-H, Zhao, W, Zhou, W, Zimmermann, ME, Zoledziewska, M, Adair, LS, Adams, HHH, Aguilar-Salinas, CA, Al-Mulla, F, Arnett, DK, Asselbergs, FW, Asvold, BO, Attia, J, Banas, B, Bandinelli, S, Bennett, DA, Bergler, T, Bharadwaj, D, Biino, G, Bisgaard, H, Boerwinkle, E, Boger, CA, Bonnelykke, K, Boomsma, D, Borglum, AD, Borja, JB, Bouchard, C, Bowden, DW, Brandslund, I, Brumpton, B, Buring, JE, Caulfield, MJ, Chambers, JC, Chandak, GR, Chanock, SJ, Chaturvedi, N, Chen, Y-DI, Chen, Z, Cheng, C-Y, Christophersen, IE, Ciullo, M, Cole, JW, Collins, FS, Cooper, RS, Cruz, M, Cucca, F, Cupples, LA, Cutler, MJ, Damrauer, SM, Dantoft, TM, de Borst, GJ, de Groot, LCPGM, De Jager, PL, de Kleijn, DP, de Silva, HJ, Dedoussis, G, den Hollander, A, Du, S, Easton, DF, Elders, PJM, Eliassen, AH, Ellinor, PT, Elmstahl, S, Erdmann, J, Evans, MK, Fatkin, D, Feenstra, B, Feitosa, MF, Ferrucci, L, Ford, I, Fornage, M, Franke, A, Franks, PW, Freedman, B, Gasparini, P, Gieger, C, Girotto, G, Goddard, ME, Golightly, YM, Gonzalez-Villalpando, C, Gordon-Larsen, P, Grallert, H, Grant, SFA, Grarup, N, Griffiths, L, Gudnason, V, Haiman, C, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayward, C, Heckbert, SR, Heng, C-K, Hengstenberg, C, Hewitt, AW, Hishigaki, H, Hoyng, CB, Huang, PL, Huang, W, Hunt, SC, Hveem, K, Hypponen, E, Iacono, WG, Ichihara, S, Ikram, MA, Isasi, CR, Jackson, RD, Jarvelin, M-R, Jin, Z-B, Jockel, K-H, Joshi, PK, Jousilahti, P, Jukema, JW, Kahonen, M, Kamatani, Y, Kang, KD, Kaprio, J, Kardia, SLR, Karpe, F, Kato, N, Kee, F, Kessler, T, Khera, A, Khor, CC, Kiemeney, LALM, Kim, B-J, Kim, EK, Kim, H-L, Kirchhof, P, Kivimaki, M, Koh, W-P, Koistinen, HA, Kolovou, GD, Kooner, JS, Kooperberg, C, Kottgen, A, Kovacs, P, Kraaijeveld, A, Kraft, P, Krauss, RM, Kumari, M, Kutalik, Z, Laakso, M, Lange, LA, Langenberg, C, Launer, LJ, Le Marchand, L, Lee, H, Lee, NR, Lehtimaki, T, Li, H, Li, L, Lieb, W, Lin, X, Lind, L, Linneberg, A, Liu, C-T, Loeffler, M, London, B, Lubitz, SA, Lye, SJ, Mackey, DA, Magi, R, Magnusson, PKE, Marcus, GM, Vidal, PM, Martin, NG, Marz, W, Matsuda, F, McGarrah, RW, McGue, M, McKnight, AJ, Medland, SE, Mellstrom, D, Metspalu, A, Mitchell, BD, Mitchell, P, Mook-Kanamori, DO, Morris, AD, Mucci, LA, Munroe, PB, Nalls, MA, Nazarian, S, Nelson, AE, Neville, MJ, Newton-Cheh, C, Nielsen, CS, Nothen, MM, Ohlsson, C, Oldehinkel, AJ, Orozco, L, Pahkala, K, Pajukanta, P, Palmer, CNA, Parra, EJ, Pattaro, C, Pedersen, O, Pennell, CE, Penninx, BWJH, Perusse, L, Peters, A, Peyser, PA, Porteous, DJ, Posthuma, D, Power, C, Pramstaller, PP, Province, MA, Qi, Q, Qu, J, Rader, DJ, Raitakari, OT, Ralhan, S, Rallidis, LS, Rao, DC, Redline, S, Reilly, DF, Reiner, AP, Rhee, SY, Ridker, PM, Rienstra, M, Ripatti, S, Ritchie, MD, Roden, DM, Rosendaal, FR, Rotter, J, Rudan, I, Rutters, F, Sabanayagam, C, Saleheen, D, Salomaa, V, Samani, NJ, Sanghera, DK, Sattar, N, Schmidt, B, Schmidt, H, Schmidt, R, Schulze, MB, Schunkert, H, Scott, LJ, Scott, RJ, Sever, P, Shiroma, EJ, Shoemaker, MB, Shu, X-O, Simonsick, EM, Sims, M, Singh, JR, Singleton, AB, Sinner, MF, Smith, JG, Snieder, H, Spector, TD, Stampfer, MJ, Stark, KJ, Strachan, DP, t' Hart, LM, Tabara, Y, Tang, H, Tardif, J-C, Thanaraj, TA, Timpson, NJ, Tonjes, A, Tremblay, A, Tuomi, T, Tuomilehto, J, Tusie-Luna, M-T, Uitterlinden, AG, van Dam, RM, van der Harst, P, Van der Velde, N, van Duijn, CM, van Schoor, NM, Vitart, V, Volker, U, Vollenweider, P, Volzke, H, Wacher-Rodarte, NH, Walker, M, Wang, YX, Wareham, NJ, Watanabe, RM, Watkins, H, Weir, DR, Werge, TM, Widen, E, Wilkens, LR, Willemsen, G, Willett, WC, Wilson, JF, Wong, T-Y, Woo, J-T, Wright, AF, Wu, J-Y, Xu, H, Yajnik, CS, Yokota, M, Yuan, J-M, Zeggini, E, Zemel, BS, Zheng, W, Zhu, X, Zmuda, JM, Zonderman, AB, Zwart, J-A, Chasman, D, Cho, YS, Heid, IM, McCarthy, M, Ng, MCY, O'Donnell, CJ, Rivadeneira, F, Thorsteinsdottir, U, Sun, Y, Tai, ES, Boehnke, M, Deloukas, P, Justice, AE, Lindgren, CM, Loos, RJF, Mohlke, KL, North, KE, Stefansson, K, Walters, RG, Winkler, TW, Young, KL, Loh, P-R, Esko, T, Assimes, TL, Auton, A, Abecasis, GR, Willer, CJ, Locke, AE, Berndt, S, Lettre, G, Frayling, TM, Okada, Y, Wood, AR, Visscher, PM, Hirschhorn, JN, Yengo, L, Vedantam, S, Marouli, E, Sidorenko, J, Bartell, E, Sakaue, S, Graff, M, Eliasen, AU, Jiang, Y, Raghavan, S, Miao, J, Arias, JD, Graham, SE, Mukamel, RE, Spracklen, CN, Yin, X, Chen, S-H, Ferreira, T, Highland, HH, Ji, Y, Karaderi, T, Lin, K, Lull, K, Malden, DE, Medina-Gomez, C, Machado, M, Moore, A, Rueger, S, Sim, X, Vrieze, S, Ahluwalia, TS, Akiyama, M, Allison, MA, Alvarez, M, Andersen, MK, Ani, A, Appadurai, V, Arbeeva, L, Bhaskar, S, Bielak, LF, Bollepalli, S, Bonnycastle, LL, Bork-Jensen, J, Bradfield, JP, Bradford, Y, Braund, PS, Brody, JA, Burgdorf, KS, Cade, BE, Cai, H, Cai, Q, Campbell, A, Canadas-Garre, M, Catamo, E, Chai, J-F, Chai, X, Chang, L-C, Chang, Y-C, Chen, C-H, Chesi, A, Choi, SH, Chung, R-H, Cocca, M, Concas, MP, Couture, C, Cuellar-Partida, G, Danning, R, Daw, EW, Degenhard, F, Delgado, GE, Delitala, A, Demirkan, A, Deng, X, Devineni, P, Dietl, A, Dimitriou, M, Dimitrov, L, Dorajoo, R, Ekici, AB, Engmann, JE, Fairhurst-Hunter, Z, Farmaki, A-E, Faul, JD, Fernandez-Lopez, J-C, Forer, L, Francescatto, M, Freitag-Wolf, S, Fuchsberger, C, Galesloot, TE, Gao, Y, Gao, Z, Geller, F, Giannakopoulou, O, Giulianini, F, Gjesing, AP, Goel, A, Gordon, SD, Gorski, M, Grove, J, Guo, X, Gustafsson, S, Haessler, J, Hansen, TF, Havulinna, AS, Haworth, SJ, He, J, Heard-Costa, N, Hebbar, P, Hindy, G, Ho, Y-LA, Hofer, E, Holliday, E, Horn, K, Hornsby, WE, Hottenga, J-J, Huang, H, Huang, J, Huerta-Chagoya, A, Huffman, JE, Hung, Y-J, Huo, S, Hwang, MY, Iha, H, Ikeda, DD, Isono, M, Jackson, AU, Jager, S, Jansen, IE, Johansson, I, Jonas, JB, Jonsson, A, Jorgensen, T, Kalafati, I-P, Kanai, M, Kanoni, S, Karhus, LL, Kasturiratne, A, Katsuya, T, Kawaguchi, T, Kember, RL, Kentistou, KA, Kim, H-N, Kim, YJ, Kleber, ME, Knol, MJ, Kurbasic, A, Lauzon, M, Le, P, Lea, R, Lee, J-Y, Leonard, HL, Li, SA, Li, X, Liang, J, Lin, H, Lin, S-Y, Liu, J, Liu, X, Lo, KS, Long, J, Lores-Motta, L, Luan, J, Lyssenko, V, Lyytikainen, L-P, Mahajan, A, Mamakou, V, Mangino, M, Manichaikul, A, Marten, J, Mattheisen, M, Mavarani, L, McDaid, AF, Meidtner, K, Melendez, TL, Mercader, JM, Milaneschi, Y, Miller, JE, Millwood, IY, Mishra, PP, Mitchell, RE, Mollehave, LT, Morgan, A, Mucha, S, Munz, M, Nakatochi, M, Nelson, CP, Nethander, M, Nho, CW, Nielsen, AA, Nolte, IM, Nongmaithem, SS, Noordam, R, Ntalla, I, Nutile, T, Pandit, A, Christofidou, P, Parna, K, Pauper, M, Petersen, ERB, Petersen, L, Pitkanen, N, Polasek, O, Poveda, A, Preuss, MH, Pyarajan, S, Raffield, LM, Rakugi, H, Ramirez, J, Rasheed, A, Raven, D, Rayner, NW, Riveros, C, Rohde, R, Ruggiero, D, Ruotsalainen, SE, Ryan, KA, Sabater-Lleal, M, Saxena, R, Scholz, M, Sendamarai, A, Shen, B, Shi, J, Shin, JH, Sidore, C, Sitlani, CM, Slieker, RKC, Smit, RAJ, Smith, A, Smith, JA, Smyth, LJ, Southam, LE, Steinthorsdottir, V, Sun, L, Takeuchi, F, Tallapragada, D, Taylor, KD, Tayo, BO, Tcheandjieu, C, Terzikhan, N, Tesolin, P, Teumer, A, Theusch, E, Thompson, DJ, Thorleifsson, G, Timmers, PRHJ, Trompet, S, Turman, C, Vaccargiu, S, van der Laan, SW, van der Most, PJ, van Klinken, JB, van Setten, J, Verma, SS, Verweij, N, Veturi, Y, Wang, CA, Wang, C, Wang, L, Wang, Z, Warren, HR, Wei, WB, Wickremasinghe, AR, Wielscher, M, Wiggins, KL, Winsvold, BS, Wong, A, Wu, Y, Wuttke, M, Xia, R, Xie, T, Yamamoto, K, Yang, J, Yao, J, Young, H, Yousri, NA, Yu, L, Zeng, L, Zhang, W, Zhang, X, Zhao, J-H, Zhao, W, Zhou, W, Zimmermann, ME, Zoledziewska, M, Adair, LS, Adams, HHH, Aguilar-Salinas, CA, Al-Mulla, F, Arnett, DK, Asselbergs, FW, Asvold, BO, Attia, J, Banas, B, Bandinelli, S, Bennett, DA, Bergler, T, Bharadwaj, D, Biino, G, Bisgaard, H, Boerwinkle, E, Boger, CA, Bonnelykke, K, Boomsma, D, Borglum, AD, Borja, JB, Bouchard, C, Bowden, DW, Brandslund, I, Brumpton, B, Buring, JE, Caulfield, MJ, Chambers, JC, Chandak, GR, Chanock, SJ, Chaturvedi, N, Chen, Y-DI, Chen, Z, Cheng, C-Y, Christophersen, IE, Ciullo, M, Cole, JW, Collins, FS, Cooper, RS, Cruz, M, Cucca, F, Cupples, LA, Cutler, MJ, Damrauer, SM, Dantoft, TM, de Borst, GJ, de Groot, LCPGM, De Jager, PL, de Kleijn, DP, de Silva, HJ, Dedoussis, G, den Hollander, A, Du, S, Easton, DF, Elders, PJM, Eliassen, AH, Ellinor, PT, Elmstahl, S, Erdmann, J, Evans, MK, Fatkin, D, Feenstra, B, Feitosa, MF, Ferrucci, L, Ford, I, Fornage, M, Franke, A, Franks, PW, Freedman, B, Gasparini, P, Gieger, C, Girotto, G, Goddard, ME, Golightly, YM, Gonzalez-Villalpando, C, Gordon-Larsen, P, Grallert, H, Grant, SFA, Grarup, N, Griffiths, L, Gudnason, V, Haiman, C, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayward, C, Heckbert, SR, Heng, C-K, Hengstenberg, C, Hewitt, AW, Hishigaki, H, Hoyng, CB, Huang, PL, Huang, W, Hunt, SC, Hveem, K, Hypponen, E, Iacono, WG, Ichihara, S, Ikram, MA, Isasi, CR, Jackson, RD, Jarvelin, M-R, Jin, Z-B, Jockel, K-H, Joshi, PK, Jousilahti, P, Jukema, JW, Kahonen, M, Kamatani, Y, Kang, KD, Kaprio, J, Kardia, SLR, Karpe, F, Kato, N, Kee, F, Kessler, T, Khera, A, Khor, CC, Kiemeney, LALM, Kim, B-J, Kim, EK, Kim, H-L, Kirchhof, P, Kivimaki, M, Koh, W-P, Koistinen, HA, Kolovou, GD, Kooner, JS, Kooperberg, C, Kottgen, A, Kovacs, P, Kraaijeveld, A, Kraft, P, Krauss, RM, Kumari, M, Kutalik, Z, Laakso, M, Lange, LA, Langenberg, C, Launer, LJ, Le Marchand, L, Lee, H, Lee, NR, Lehtimaki, T, Li, H, Li, L, Lieb, W, Lin, X, Lind, L, Linneberg, A, Liu, C-T, Loeffler, M, London, B, Lubitz, SA, Lye, SJ, Mackey, DA, Magi, R, Magnusson, PKE, Marcus, GM, Vidal, PM, Martin, NG, Marz, W, Matsuda, F, McGarrah, RW, McGue, M, McKnight, AJ, Medland, SE, Mellstrom, D, Metspalu, A, Mitchell, BD, Mitchell, P, Mook-Kanamori, DO, Morris, AD, Mucci, LA, Munroe, PB, Nalls, MA, Nazarian, S, Nelson, AE, Neville, MJ, Newton-Cheh, C, Nielsen, CS, Nothen, MM, Ohlsson, C, Oldehinkel, AJ, Orozco, L, Pahkala, K, Pajukanta, P, Palmer, CNA, Parra, EJ, Pattaro, C, Pedersen, O, Pennell, CE, Penninx, BWJH, Perusse, L, Peters, A, Peyser, PA, Porteous, DJ, Posthuma, D, Power, C, Pramstaller, PP, Province, MA, Qi, Q, Qu, J, Rader, DJ, Raitakari, OT, Ralhan, S, Rallidis, LS, Rao, DC, Redline, S, Reilly, DF, Reiner, AP, Rhee, SY, Ridker, PM, Rienstra, M, Ripatti, S, Ritchie, MD, Roden, DM, Rosendaal, FR, Rotter, J, Rudan, I, Rutters, F, Sabanayagam, C, Saleheen, D, Salomaa, V, Samani, NJ, Sanghera, DK, Sattar, N, Schmidt, B, Schmidt, H, Schmidt, R, Schulze, MB, Schunkert, H, Scott, LJ, Scott, RJ, Sever, P, Shiroma, EJ, Shoemaker, MB, Shu, X-O, Simonsick, EM, Sims, M, Singh, JR, Singleton, AB, Sinner, MF, Smith, JG, Snieder, H, Spector, TD, Stampfer, MJ, Stark, KJ, Strachan, DP, t' Hart, LM, Tabara, Y, Tang, H, Tardif, J-C, Thanaraj, TA, Timpson, NJ, Tonjes, A, Tremblay, A, Tuomi, T, Tuomilehto, J, Tusie-Luna, M-T, Uitterlinden, AG, van Dam, RM, van der Harst, P, Van der Velde, N, van Duijn, CM, van Schoor, NM, Vitart, V, Volker, U, Vollenweider, P, Volzke, H, Wacher-Rodarte, NH, Walker, M, Wang, YX, Wareham, NJ, Watanabe, RM, Watkins, H, Weir, DR, Werge, TM, Widen, E, Wilkens, LR, Willemsen, G, Willett, WC, Wilson, JF, Wong, T-Y, Woo, J-T, Wright, AF, Wu, J-Y, Xu, H, Yajnik, CS, Yokota, M, Yuan, J-M, Zeggini, E, Zemel, BS, Zheng, W, Zhu, X, Zmuda, JM, Zonderman, AB, Zwart, J-A, Chasman, D, Cho, YS, Heid, IM, McCarthy, M, Ng, MCY, O'Donnell, CJ, Rivadeneira, F, Thorsteinsdottir, U, Sun, Y, Tai, ES, Boehnke, M, Deloukas, P, Justice, AE, Lindgren, CM, Loos, RJF, Mohlke, KL, North, KE, Stefansson, K, Walters, RG, Winkler, TW, Young, KL, Loh, P-R, Esko, T, Assimes, TL, Auton, A, Abecasis, GR, Willer, CJ, Locke, AE, Berndt, S, Lettre, G, Frayling, TM, Okada, Y, Wood, AR, Visscher, PM, and Hirschhorn, JN

Abstract

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Published
2022

23. Genetic variants associated with circulating C-reactive protein levels and colorectal cancer survival: Sex-specific and lifestyle factors specific associations

Author

Huang, Y, Hua, X, Labadie, JD, Harrison, TA, Dai, JY, Lindstrom, S, Lin, Y, Berndt, S, Buchanan, DD, Campbell, PT, Casey, G, Gallinger, SJ, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Sakoda, LC, Schoen, RE, Diergaarde, B, Slattery, ML, White, E, Giles, G, Brenner, H, Chang-Claude, J, Joshi, A, Ma, W, Pai, RK, Chan, AT, Peters, U, Newcomb, PA, Huang, Y, Hua, X, Labadie, JD, Harrison, TA, Dai, JY, Lindstrom, S, Lin, Y, Berndt, S, Buchanan, DD, Campbell, PT, Casey, G, Gallinger, SJ, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Sakoda, LC, Schoen, RE, Diergaarde, B, Slattery, ML, White, E, Giles, G, Brenner, H, Chang-Claude, J, Joshi, A, Ma, W, Pai, RK, Chan, AT, Peters, U, and Newcomb, PA

Abstract

Elevated blood levels of C-reactive protein (CRP) have been linked to colorectal cancer (CRC) survival. We evaluated genetic variants associated with CRP levels and their interactions with sex and lifestyle factors in association with CRC-specific mortality. Our study included 16 142 CRC cases from the International Survival Analysis in Colorectal Cancer Consortium. We identified 618 common single nucleotide polymorphisms (SNPs) associated with CRP levels from the NHGRI-EBI GWAS Catalog. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between SNPs and CRC-specific mortality adjusting for age, sex, genotyping platform/study and principal components. We investigated their interactions with sex and lifestyle factors using likelihood ratio tests. Of 5472 (33.9%) deaths accrued over up to 10 years of follow-up, 3547 (64.8%) were due to CRC. No variants were associated with CRC-specific mortality after multiple comparison correction. We observed strong evidence of interaction between variant rs1933736 at FRK gene and sex in relation to CRC-specific mortality (corrected Pinteraction = .0004); women had higher CRC-specific mortality associated with the minor allele (HR = 1.11, 95% CI = 1.04-1.19) whereas an inverse association was observed for men (HR = 0.88, 95% CI = 0.82-0.94). There was no evidence of interactions between CRP-associated SNPs and alcohol, obesity or smoking. Our study observed a significant interaction between sex and a CRP-associated variant in relation to CRC-specific mortality. Future replication of this association and functional annotation of the variant are needed.

Published
2022

24. Interactions between folate intake and genetic predictors of gene expression levels associated with colorectal cancer risk

Author

Haas, CB, Su, Y-R, Petersen, P, Wang, X, Bien, SA, Lin, Y, Albanes, D, Weinstein, SJ, Jenkins, MA, Figueiredo, JC, Newcomb, PA, Casey, G, Le Marchand, L, Campbell, PT, Moreno, V, Potter, JD, Sakoda, LC, Slattery, ML, Chan, AT, Li, L, Giles, GG, Milne, RL, Gruber, SB, Rennert, G, Woods, MO, Gallinger, SJ, Berndt, S, Hayes, RB, Huang, W-Y, Wolk, A, White, E, Nan, H, Nassir, R, Lindor, NM, Lewinger, JP, Kim, AE, Conti, D, Gauderman, WJ, Buchanan, DD, Peters, U, Hsu, L, Haas, CB, Su, Y-R, Petersen, P, Wang, X, Bien, SA, Lin, Y, Albanes, D, Weinstein, SJ, Jenkins, MA, Figueiredo, JC, Newcomb, PA, Casey, G, Le Marchand, L, Campbell, PT, Moreno, V, Potter, JD, Sakoda, LC, Slattery, ML, Chan, AT, Li, L, Giles, GG, Milne, RL, Gruber, SB, Rennert, G, Woods, MO, Gallinger, SJ, Berndt, S, Hayes, RB, Huang, W-Y, Wolk, A, White, E, Nan, H, Nassir, R, Lindor, NM, Lewinger, JP, Kim, AE, Conti, D, Gauderman, WJ, Buchanan, DD, Peters, U, and Hsu, L

Abstract

Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene-environment (G × E) interactions and may provide information on the underlying biological pathway. We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based G × E approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case-control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4839 genes with available genetically predicted expression. We pooled results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. We used a false discovery rate of 0.2 to identify genes with suggestive evidence of an interaction. We found suggestive evidence of interaction with folate intake on CRC risk for genes including glutathione S-Transferase Alpha 1 (GSTA1; p = 4.3E-4), Tonsuko Like, DNA Repair Protein (TONSL; p = 4.3E-4), and Aspartylglucosaminidase (AGA: p = 4.5E-4). We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk. Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein.

Published
2022

25. Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk

Author

Tian, Y, Kim, AE, Bien, SA, Lin, Y, Qu, C, Harrison, TA, Carreras-Torres, R, Diez-Obrero, V, Dimou, N, Drew, DA, Hidaka, A, Huyghe, JR, Jordahl, KM, Morrison, J, Murphy, N, Obon-Santacana, M, Ulrich, CM, Ose, J, Peoples, AR, Ruiz-Narvaez, EA, Shcherbina, A, Stern, MC, Su, Y-R, van Duijnhoven, FJB, Arndt, V, Baurley, JW, Berndt, S, Bishop, DT, Brenner, H, Buchanan, DD, Chan, AT, Figueiredo, JC, Gallinger, S, Gruber, SB, Harlid, S, Hoffmeister, M, Jenkins, MA, Joshi, AD, Keku, TO, Larsson, SC, Le Marchand, L, Li, L, Giles, GG, Milne, RL, Nan, H, Nassir, R, Ogino, S, Budiarto, A, Platz, EA, Potter, JD, Prentice, RL, Rennert, G, Sakoda, LC, Schoen, RE, Slattery, ML, Thibodeau, SN, Van Guelpen, B, Visvanathan, K, White, E, Wolk, A, Woods, MO, Wu, AH, Campbell, PT, Casey, G, Conti, D, Gunter, MJ, Kundaje, A, Lewinger, JP, Moreno, V, Newcomb, PA, Pardamean, B, Thomas, DC, Tsilidis, KK, Peters, U, Gauderman, WJ, Hsu, L, Chang-Claude, J, Tian, Y, Kim, AE, Bien, SA, Lin, Y, Qu, C, Harrison, TA, Carreras-Torres, R, Diez-Obrero, V, Dimou, N, Drew, DA, Hidaka, A, Huyghe, JR, Jordahl, KM, Morrison, J, Murphy, N, Obon-Santacana, M, Ulrich, CM, Ose, J, Peoples, AR, Ruiz-Narvaez, EA, Shcherbina, A, Stern, MC, Su, Y-R, van Duijnhoven, FJB, Arndt, V, Baurley, JW, Berndt, S, Bishop, DT, Brenner, H, Buchanan, DD, Chan, AT, Figueiredo, JC, Gallinger, S, Gruber, SB, Harlid, S, Hoffmeister, M, Jenkins, MA, Joshi, AD, Keku, TO, Larsson, SC, Le Marchand, L, Li, L, Giles, GG, Milne, RL, Nan, H, Nassir, R, Ogino, S, Budiarto, A, Platz, EA, Potter, JD, Prentice, RL, Rennert, G, Sakoda, LC, Schoen, RE, Slattery, ML, Thibodeau, SN, Van Guelpen, B, Visvanathan, K, White, E, Wolk, A, Woods, MO, Wu, AH, Campbell, PT, Casey, G, Conti, D, Gunter, MJ, Kundaje, A, Lewinger, JP, Moreno, V, Newcomb, PA, Pardamean, B, Thomas, DC, Tsilidis, KK, Peters, U, Gauderman, WJ, Hsu, L, and Chang-Claude, J

Abstract

BACKGROUND: The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. METHODS: We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2- or 3-degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. RESULTS: The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2-degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10-4). CONCLUSION: Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.

Published
2022

32. Holmium-166m measurements with AMS for the ECHo-project

Author

Rugel, G., Berndt, S., Düllmann, C. E., Dorrer, H., Forstner, O., Kieck, T., Kneip, N., Lachner, J., Merchel, S., Vivo Vilches, C., Wallner, A., and Wendt, K.

Abstract

The Electron Capture in ¹⁶³Ho experiment (ECHo) aims at measuring the mass of the electron neutrino by analysing the EC spectrum of the long-lived radionuclide ¹⁶³Ho (T_1/2 = 4570 a) with a metallic magnetic calorimeter (MMC). For the determination of a reasonable upper limit for the neutrino mass it is mandatory to keep the contamination with the long-lived radionuclide ¹⁶⁶mHo (T_1/2 = 1132.6 a) nine orders of magnitude below the ¹⁶³Ho content. The ion-implantation of ultra-pure ¹⁶³Ho into a MMC for the experiment is carried out by the RISIKO (Resonance Ionization Spectroscopy in KOllinear geometry) mass separator. The separation from ¹⁶⁶mHo, however, cannot be guaranteed to such low levels as needed in this project, it can only be estimated. Here we present our approach to determine the corresponding low isotopic ratio with accelerator mass spectrometry (AMS). Of course, this requires the formation of negative ions, where we find the highest negative ion yield for the anion HoO₂−. For first tests, stable ¹⁶⁵Ho was implanted by RISIKO into various different metal foils and we studied the overall Ho detection efficiency for our setup. We will present first results and estimates of the expected detection limit for the ¹⁶⁶mHo/¹⁶³Ho isotope ratio.

Published
2021

33. Low-level ¹⁶⁶mHo measurements with AMS for the ECHo-project

Author

Rugel, G., Berndt, S., Düllmann, C. E., Dorrer, H., Forstner, O., Kieck, T., Kneip, N., Lachner, J., Merchel, S., Vivo Vilches, C., Wallner, A., and Wendt, K.

Abstract

The Electron Capture in ¹⁶³Ho experiment (ECHo) aims at measuring the mass of νe by analysing the EC spectrum of the long-lived radionuclide ¹⁶³Ho (T1/2=4570 a) with a metallic magnetic calorimeter (MMC). For the determination of a reasonable upper limit for the neutrino mass it is mandatory to keep any contamination with the long-lived radionuclide 166mHo nine orders of magnitude below the ¹⁶³Ho content. The ion-implantation of ultra-pure ¹⁶³Ho into a MMC for the experiment is carried out by the RISIKO mass separator. The separation from ¹⁶⁶mHo, however, cannot be quantified to such low levels as needed. Here we present our approach to determine the corresponding low isotopic ratio with accelerator mass spectrometry (AMS). This requires the formation of negative ions, we find the highest negative ion yield for the anion HoO₂−. For first tests ¹⁶⁵Ho was implanted by RISIKO in various metal foils and we obtained results for the Ho detection efficieny. This allows for extrapolations for the expected measurement limit of the ¹⁶⁶mHo/¹⁶³Ho ratio.

Published
2021

38. A transcriptome-wide association study identifies novel candidate susceptibility genes for pancreatic cancer.

Author

Hasan M., Zhang T., Xiao W., Albanes D., Andreotti G., Arslan A.A., Babic A., Bamlet W.R., Beane-Freeman L., Berndt S., Borgida A., Bracci P.M., Brais L., Brennan P., Bueno-De-Mesquita B., Buring J., Canzian F., Childs E.J., Cotterchio M., Du M., Duell E.J., Fuchs C., Gallinger S., Michael Gaziano J., Giles G.G., Giovannucci E., Goggins M., Goodman G.E., Goodman P.J., Haiman C., Hartge P., Helzlsouer K.J., Holly E.A., Klein E.A., Kogevinas M., Kurtz R.J., LeMarchand L., Malats N., Mannisto S., Milne R., Neale R.E., Ng K., Obazee O., Oberg A.L., Orlow I., Patel A.V., Peters U., Porta M., Rothman N., Scelo G., Sesso H.D., Severi G., Sieri S., Silverman D., Sund M., Tjonneland A., Thornquist M.D., Tobias G.S., Trichopoulou A., van Den Eeden S.K., Visvanathan K., Wactawski-Wende J., Wentzensen N., White E., Yu H., Yuan C., Zeleniuch-Jacquotte A., Hoover R., Brown K., Kooperberg C., Risch H.A., Jacobs E.J., Li D., Yu K., Shu X.-O., Chanock S.J., Wolpin B.M., Stolzenberg-Solomon R.Z., Chatterjee N., Klein A.P., Smith J.P., Kraft P., Shi J., Petersen G.M., Zheng W., Amundadottir L.T., Zhong J., Jermusyk A., Wu L., Hoskins J.W., Collins I., Mocci E., Zhang M., Song L., Chung C.C., Hasan M., Zhang T., Xiao W., Albanes D., Andreotti G., Arslan A.A., Babic A., Bamlet W.R., Beane-Freeman L., Berndt S., Borgida A., Bracci P.M., Brais L., Brennan P., Bueno-De-Mesquita B., Buring J., Canzian F., Childs E.J., Cotterchio M., Du M., Duell E.J., Fuchs C., Gallinger S., Michael Gaziano J., Giles G.G., Giovannucci E., Goggins M., Goodman G.E., Goodman P.J., Haiman C., Hartge P., Helzlsouer K.J., Holly E.A., Klein E.A., Kogevinas M., Kurtz R.J., LeMarchand L., Malats N., Mannisto S., Milne R., Neale R.E., Ng K., Obazee O., Oberg A.L., Orlow I., Patel A.V., Peters U., Porta M., Rothman N., Scelo G., Sesso H.D., Severi G., Sieri S., Silverman D., Sund M., Tjonneland A., Thornquist M.D., Tobias G.S., Trichopoulou A., van Den Eeden S.K., Visvanathan K., Wactawski-Wende J., Wentzensen N., White E., Yu H., Yuan C., Zeleniuch-Jacquotte A., Hoover R., Brown K., Kooperberg C., Risch H.A., Jacobs E.J., Li D., Yu K., Shu X.-O., Chanock S.J., Wolpin B.M., Stolzenberg-Solomon R.Z., Chatterjee N., Klein A.P., Smith J.P., Kraft P., Shi J., Petersen G.M., Zheng W., Amundadottir L.T., Zhong J., Jermusyk A., Wu L., Hoskins J.W., Collins I., Mocci E., Zhang M., Song L., and Chung C.C.

Abstract

Background: Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Method(s): To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples). Result(s): We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate <.05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22:RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusion(s): By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.Copyright © 2020 Oxford University Press. All rights reserved.

Published
2021

39. Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients.

Author

Vachon C.M., Canzian F., Campa D., Watek M., Jurczyszyn A., Brown E.E., Berndt S., Butrym A., Norman A.D., Gemignani F., Slager S.L., Macauda A., Piredda C., Clay-Gilmour A.I., Sainz J., Buda G., Markiewicz M., Barington T., Ziv E., Hildebrandt M.A.T., Belachew A.A., Varkonyi J., Prejzner W., Druzd-Sitek A., Spinelli J., Andersen N.F., Hofmann J.N., Dudzinski M., Martinez-Lopez J., Iskierka-Jazdzewska E., Milne R.L., Mazur G., Giles G.G., Ebbesen L.H., Rymko M., Jamroziak K., Subocz E., Reis R.M., Garcia-Sanz R., Suska A., Haastrup E.K., Zawirska D., Grzasko N., Vangsted A.J., Dumontet C., Kruszewski M., Dutka M., Camp N.J., Waller R.G., Tomczak W., Pelosini M., Razny M., Marques H., Abildgaard N., Vachon C.M., Canzian F., Campa D., Watek M., Jurczyszyn A., Brown E.E., Berndt S., Butrym A., Norman A.D., Gemignani F., Slager S.L., Macauda A., Piredda C., Clay-Gilmour A.I., Sainz J., Buda G., Markiewicz M., Barington T., Ziv E., Hildebrandt M.A.T., Belachew A.A., Varkonyi J., Prejzner W., Druzd-Sitek A., Spinelli J., Andersen N.F., Hofmann J.N., Dudzinski M., Martinez-Lopez J., Iskierka-Jazdzewska E., Milne R.L., Mazur G., Giles G.G., Ebbesen L.H., Rymko M., Jamroziak K., Subocz E., Reis R.M., Garcia-Sanz R., Suska A., Haastrup E.K., Zawirska D., Grzasko N., Vangsted A.J., Dumontet C., Kruszewski M., Dutka M., Camp N.J., Waller R.G., Tomczak W., Pelosini M., Razny M., Marques H., and Abildgaard N.

Abstract

Gene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype-tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10-7 either in EBV-transformed B-lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression-free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4-rs1992292, TBRG4-rs2287535 and ENTPD1-rs2153913) showed associations with OS at P <.05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta-analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4-rs1992292 is associated with OS (hazard ratio = 1.14, 95% confidence interval 1.04-1.26, P =.007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.Copyright © 2021 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of Union for International Cancer Control.

Published
2021

40. Genetically Predicted Circulating C-Reactive Protein Concentration and Colorectal Cancer Survival: A Mendelian Randomization Consortium Study

Author

Hua, X, Dai, JY, Lindstrom, S, Harrison, TA, Lin, Y, Alberts, SR, Alwers, E, Berndt, S, Brenner, H, Buchanan, DD, Campbell, PT, Casey, G, Chang-Claude, J, Gallinger, S, Giles, GG, Goldberg, RM, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Joshi, AD, Ma, W, Milne, RL, Murphy, N, Pai, RK, Sakoda, LC, Schoen, RE, Shi, Q, Slattery, ML, Song, M, White, E, Le Marchand, L, Chan, AT, Peters, U, Newcomb, PA, Hua, X, Dai, JY, Lindstrom, S, Harrison, TA, Lin, Y, Alberts, SR, Alwers, E, Berndt, S, Brenner, H, Buchanan, DD, Campbell, PT, Casey, G, Chang-Claude, J, Gallinger, S, Giles, GG, Goldberg, RM, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Joshi, AD, Ma, W, Milne, RL, Murphy, N, Pai, RK, Sakoda, LC, Schoen, RE, Shi, Q, Slattery, ML, Song, M, White, E, Le Marchand, L, Chan, AT, Peters, U, and Newcomb, PA

Abstract

BACKGROUND: A positive association between circulating C-reactive protein (CRP) and colorectal cancer survival was reported in observational studies, which are susceptible to unmeasured confounding and reverse causality. We used a Mendelian randomization approach to evaluate the association between genetically predicted CRP concentrations and colorectal cancer-specific survival. METHODS: We used individual-level data for 16,918 eligible colorectal cancer cases of European ancestry from 15 studies within the International Survival Analysis of Colorectal Cancer Consortium. We calculated a genetic-risk score based on 52 CRP-associated genetic variants identified from genome-wide association studies. Because of the non-collapsibility of hazard ratios from Cox proportional hazards models, we used the additive hazards model to calculate hazard differences (HD) and 95% confidence intervals (CI) for the association between genetically predicted CRP concentrations and colorectal cancer-specific survival, overall and by stage at diagnosis and tumor location. Analyses were adjusted for age at diagnosis, sex, body mass index, genotyping platform, study, and principal components. RESULTS: Of the 5,395 (32%) deaths accrued over up to 10 years of follow-up, 3,808 (23%) were due to colorectal cancer. Genetically predicted CRP concentration was not associated with colorectal cancer-specific survival (HD, -1.15; 95% CI, -2.76 to 0.47 per 100,000 person-years; P = 0.16). Similarly, no associations were observed in subgroup analyses by stage at diagnosis or tumor location. CONCLUSIONS: Despite adequate power to detect moderate associations, our results did not support a causal effect of circulating CRP concentrations on colorectal cancer-specific survival. IMPACT: Future research evaluating genetically determined levels of other circulating inflammatory biomarkers (i.e., IL6) with colorectal cancer survival outcomes is needed.

Published
2021

41. Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3

Author

Mocci, E, Kundu, P, Wheeler, W, Arslan, AA, Beane-Freeman, LE, Bracci, PM, Brennan, P, Canzian, F, Du, M, Gallinger, S, Giles, GG, Goodman, PJ, Kooperberg, C, Le Marchand, L, Neale, RE, Shu, X-O, Visvanathan, K, White, E, Zheng, W, Albanes, D, Andreotti, G, Babic, A, Bamlet, WR, Berndt, S, Blackford, AL, Bueno-de-Mesquita, B, Buring, JE, Campa, D, Chanock, SJ, Childs, EJ, Duell, EJ, Fuchs, CS, Gaziano, JM, Giovannucci, EL, Goggins, MG, Hartge, P, Hassan, MM, Holly, EA, Hoover, RN, Hung, RJ, Kurtz, RC, Lee, I-M, Malats, N, Milne, RL, Ng, K, Oberg, AL, Panico, S, Peters, U, Porta, M, Rabe, KG, Riboli, E, Rothman, N, Scelo, G, Sesso, HD, Silverman, DT, Stevens, VL, Strobel, O, Thompson, IM, Tjonneland, A, Trichopoulou, A, Van den Eeden, SK, Wactawski-Wende, J, Wentzensen, N, Wilkens, LR, Yu, H, Yuan, F, Zeleniuch-Jacquotte, A, Amundadottir, LT, Li, D, Jacobs, EJ, Petersen, GM, Wolpin, BM, Risch, HA, Kraft, P, Chatterjee, N, Klein, AP, Stolzenberg-Solomon, R, Mocci, E, Kundu, P, Wheeler, W, Arslan, AA, Beane-Freeman, LE, Bracci, PM, Brennan, P, Canzian, F, Du, M, Gallinger, S, Giles, GG, Goodman, PJ, Kooperberg, C, Le Marchand, L, Neale, RE, Shu, X-O, Visvanathan, K, White, E, Zheng, W, Albanes, D, Andreotti, G, Babic, A, Bamlet, WR, Berndt, S, Blackford, AL, Bueno-de-Mesquita, B, Buring, JE, Campa, D, Chanock, SJ, Childs, EJ, Duell, EJ, Fuchs, CS, Gaziano, JM, Giovannucci, EL, Goggins, MG, Hartge, P, Hassan, MM, Holly, EA, Hoover, RN, Hung, RJ, Kurtz, RC, Lee, I-M, Malats, N, Milne, RL, Ng, K, Oberg, AL, Panico, S, Peters, U, Porta, M, Rabe, KG, Riboli, E, Rothman, N, Scelo, G, Sesso, HD, Silverman, DT, Stevens, VL, Strobel, O, Thompson, IM, Tjonneland, A, Trichopoulou, A, Van den Eeden, SK, Wactawski-Wende, J, Wentzensen, N, Wilkens, LR, Yu, H, Yuan, F, Zeleniuch-Jacquotte, A, Amundadottir, LT, Li, D, Jacobs, EJ, Petersen, GM, Wolpin, BM, Risch, HA, Kraft, P, Chatterjee, N, Klein, AP, and Stolzenberg-Solomon, R

Abstract

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

Published
2021

42. Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

Author

Conti, D, Darst, BF, Moss, LC, Saunders, EJ, Sheng, X, Chou, A, Schumacher, FR, Al Olama, AA, Benlloch, S, Dadaev, T, Brook, MN, Sahimi, A, Hoffmann, TJ, Takahashi, A, Matsuda, K, Momozawa, Y, Fujita, M, Muir, K, Lophatananon, A, Wan, P, Le Marchand, L, Wilkens, LR, Stevens, VL, Gapstur, SM, Carter, BD, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokolorczyk, D, Lubinski, J, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Roder, MA, Iversen, P, Batra, J, Chambers, S, Moya, L, Horvath, L, Clements, JA, Tilley, W, Risbridger, GP, Gronberg, H, Aly, M, Szulkin, R, Eklund, M, Nordstrom, T, Pashayan, N, Dunning, AM, Ghoussaini, M, Travis, RC, Key, TJ, Riboli, E, Park, JY, Sellers, TA, Lin, H-Y, Albanes, D, Weinstein, SJ, Mucci, LA, Giovannucci, E, Lindstrom, S, Kraft, P, Hunter, DJ, Penney, KL, Turman, C, Tangen, CM, Goodman, PJ, Thompson, IM, Hamilton, RJ, Fleshner, NE, Finelli, A, Parent, M-E, Stanford, JL, Ostrander, EA, Geybels, MS, Koutros, S, Freeman, LEB, Stampfer, M, Wolk, A, Hakansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sorensen, KD, Borre, M, Blot, WJ, Zheng, W, Yeboah, ED, Mensah, JE, Lu, Y-J, Zhang, H-W, Feng, N, Mao, X, Wu, Y, Zhao, S-C, Sun, Z, Thibodeau, SN, McDonnell, SK, Schaid, DJ, West, CML, Burnet, N, Barnett, G, Maier, C, Schnoeller, T, Luedeke, M, Kibel, AS, Drake, BF, Cussenot, O, Cancel-Tassin, G, Menegaux, F, Truong, T, Koudou, YA, John, EM, Grindedal, EM, Maehle, L, Khaw, K-T, Ingles, SA, Stern, MC, Vega, A, Gomez-Caamano, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandao, A, Watya, S, Lubwama, A, Bensen, JT, Fontham, ETH, Mohler, J, Taylor, JA, Kogevinas, M, Llorca, J, Castano-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Strom, SS, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Weaver, B, Brenner, H, Cuk, K, Holleczek, B, Saum, K-U, Klein, EA, Hsing, AW, Kittles, RA, Murphy, AB, Logothetis, CJ, Kim, J, Neuhausen, SL, Steele, L, Ding, YC, Isaacs, WB, Nemesure, B, Hennis, AJM, Carpten, J, Pandha, H, Michael, A, De Ruyck, K, De Meerleer, G, Ost, P, Xu, J, Razack, A, Lim, J, Teo, S-H, Newcomb, LF, Lin, DW, Fowke, JH, Neslund-Dudas, C, Rybicki, BA, Gamulin, M, Lessel, D, Kulis, T, Usmani, N, Singhal, S, Parliament, M, Claessens, F, Joniau, S, Van den Broeck, T, Gago-Dominguez, M, Castelao, JE, Martinez, ME, Larkin, S, Townsend, PA, Aukim-Hastie, C, Bush, WS, Aldrich, MC, Crawford, DC, Srivastava, S, Cullen, JC, Petrovics, G, Casey, G, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Varma, R, McKean-Cowdin, R, Torres, M, Mancuso, N, Berndt, S, Van den Eeden, SK, Easton, DF, Chanock, SJ, Cook, MB, Wiklund, F, Nakagawa, H, Witte, JS, Eeles, RA, Kote-Jarai, Z, Haiman, CA, Conti, D, Darst, BF, Moss, LC, Saunders, EJ, Sheng, X, Chou, A, Schumacher, FR, Al Olama, AA, Benlloch, S, Dadaev, T, Brook, MN, Sahimi, A, Hoffmann, TJ, Takahashi, A, Matsuda, K, Momozawa, Y, Fujita, M, Muir, K, Lophatananon, A, Wan, P, Le Marchand, L, Wilkens, LR, Stevens, VL, Gapstur, SM, Carter, BD, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokolorczyk, D, Lubinski, J, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Roder, MA, Iversen, P, Batra, J, Chambers, S, Moya, L, Horvath, L, Clements, JA, Tilley, W, Risbridger, GP, Gronberg, H, Aly, M, Szulkin, R, Eklund, M, Nordstrom, T, Pashayan, N, Dunning, AM, Ghoussaini, M, Travis, RC, Key, TJ, Riboli, E, Park, JY, Sellers, TA, Lin, H-Y, Albanes, D, Weinstein, SJ, Mucci, LA, Giovannucci, E, Lindstrom, S, Kraft, P, Hunter, DJ, Penney, KL, Turman, C, Tangen, CM, Goodman, PJ, Thompson, IM, Hamilton, RJ, Fleshner, NE, Finelli, A, Parent, M-E, Stanford, JL, Ostrander, EA, Geybels, MS, Koutros, S, Freeman, LEB, Stampfer, M, Wolk, A, Hakansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sorensen, KD, Borre, M, Blot, WJ, Zheng, W, Yeboah, ED, Mensah, JE, Lu, Y-J, Zhang, H-W, Feng, N, Mao, X, Wu, Y, Zhao, S-C, Sun, Z, Thibodeau, SN, McDonnell, SK, Schaid, DJ, West, CML, Burnet, N, Barnett, G, Maier, C, Schnoeller, T, Luedeke, M, Kibel, AS, Drake, BF, Cussenot, O, Cancel-Tassin, G, Menegaux, F, Truong, T, Koudou, YA, John, EM, Grindedal, EM, Maehle, L, Khaw, K-T, Ingles, SA, Stern, MC, Vega, A, Gomez-Caamano, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandao, A, Watya, S, Lubwama, A, Bensen, JT, Fontham, ETH, Mohler, J, Taylor, JA, Kogevinas, M, Llorca, J, Castano-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Strom, SS, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Weaver, B, Brenner, H, Cuk, K, Holleczek, B, Saum, K-U, Klein, EA, Hsing, AW, Kittles, RA, Murphy, AB, Logothetis, CJ, Kim, J, Neuhausen, SL, Steele, L, Ding, YC, Isaacs, WB, Nemesure, B, Hennis, AJM, Carpten, J, Pandha, H, Michael, A, De Ruyck, K, De Meerleer, G, Ost, P, Xu, J, Razack, A, Lim, J, Teo, S-H, Newcomb, LF, Lin, DW, Fowke, JH, Neslund-Dudas, C, Rybicki, BA, Gamulin, M, Lessel, D, Kulis, T, Usmani, N, Singhal, S, Parliament, M, Claessens, F, Joniau, S, Van den Broeck, T, Gago-Dominguez, M, Castelao, JE, Martinez, ME, Larkin, S, Townsend, PA, Aukim-Hastie, C, Bush, WS, Aldrich, MC, Crawford, DC, Srivastava, S, Cullen, JC, Petrovics, G, Casey, G, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Varma, R, McKean-Cowdin, R, Torres, M, Mancuso, N, Berndt, S, Van den Eeden, SK, Easton, DF, Chanock, SJ, Cook, MB, Wiklund, F, Nakagawa, H, Witte, JS, Eeles, RA, Kote-Jarai, Z, and Haiman, CA

Abstract

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

Published
2021

43. Association Between Smoking and Molecular Subtypes of Colorectal Cancer

Author

Wang, X, Amitay, E, Harrison, TA, Banbury, BL, Berndt, S, Brenner, H, Buchanan, DD, Campbell, PT, Cao, Y, Chan, AT, Chang-Claude, J, Gallinger, SJ, Giannakis, M, Giles, GG, Gunter, MJ, Hopper, JL, Jenkins, MA, Lin, Y, Moreno, V, Nishihara, R, Newcomb, PA, Ogino, S, Phipps, A, Sakoda, LC, Schoen, RE, Slattery, ML, Song, M, Sun, W, Thibodeau, SN, Toland, AE, Van Guelpen, B, Woods, MO, Hsu, L, Hoffmeister, M, Peters, U, Wang, X, Amitay, E, Harrison, TA, Banbury, BL, Berndt, S, Brenner, H, Buchanan, DD, Campbell, PT, Cao, Y, Chan, AT, Chang-Claude, J, Gallinger, SJ, Giannakis, M, Giles, GG, Gunter, MJ, Hopper, JL, Jenkins, MA, Lin, Y, Moreno, V, Nishihara, R, Newcomb, PA, Ogino, S, Phipps, A, Sakoda, LC, Schoen, RE, Slattery, ML, Song, M, Sun, W, Thibodeau, SN, Toland, AE, Van Guelpen, B, Woods, MO, Hsu, L, Hoffmeister, M, and Peters, U

Abstract

BACKGROUND: Smoking is associated with colorectal cancer (CRC) risk. Previous studies suggested this association may be restricted to certain molecular subtypes of CRC, but large-scale comprehensive analysis is lacking. METHODS: A total of 9789 CRC cases and 11 231 controls of European ancestry from 11 observational studies were included. We harmonized smoking variables across studies and derived sex study-specific quartiles of pack-years of smoking for analysis. Four somatic colorectal tumor markers were assessed individually and in combination, including BRAF mutation, KRAS mutation, CpG island methylator phenotype (CIMP), and microsatellite instability (MSI) status. A multinomial logistic regression analysis was used to assess the association between smoking and risk of CRC subtypes by molecular characteristics, adjusting for age, sex, and study. All statistical tests were 2-sided and adjusted for Bonferroni correction. RESULTS: Heavier smoking was associated with higher risk of CRC overall and stratified by individual markers (P trend < .001). The associations differed statistically significantly between all molecular subtypes, which was the most statistically significant for CIMP and BRAF. Compared with never-smokers, smokers in the fourth quartile of pack-years had a 90% higher risk of CIMP-positive CRC (odds ratio = 1.90, 95% confidence interval = 1.60 to 2.26) but only 35% higher risk for CIMP-negative CRC (odds ratio = 1.35, 95% confidence interval = 1.22 to 1.49; P difference = 2.1 x 10-6). The association was also stronger in tumors that were CIMP positive, MSI high, or KRAS wild type when combined (P difference < .001). CONCLUSION: Smoking was associated with differential risk of CRC subtypes defined by molecular characteristics. Heavier smokers had particularly higher risk of CRC subtypes that were CIMP positive and MSI high in combination, suggesting that smoking may be involved in the development of colorectal tumors via the serrated pathway.

Published
2021

44. Hepcidin-regulating iron metabolism genes and pancreatic ductal adenocarcinoma: a pathway analysis of genome-wide association studies

Author

Julian-Serrano, S, Yuan, F, Wheeler, W, Benyamin, B, Machiela, MJ, Arslan, AA, Beane-Freeman, LE, Bracci, PM, Duell, EJ, Du, M, Gallinger, S, Giles, GG, Goodman, PJ, Kooperberg, C, Le Marchand, L, Neale, RE, Shu, X-O, Van den Eeden, SK, Visvanathan, K, Zheng, W, Albanes, D, Andreotti, G, Ardanaz, E, Babic, A, Berndt, S, Brais, LK, Brennan, P, Bueno-de-Mesquita, B, Buring, JE, Chanock, SJ, Childs, EJ, Chung, CC, Fabianova, E, Foretova, L, Fuchs, CS, Gaziano, JM, Gentiluomo, M, Giovannucci, EL, Goggins, MG, Hackert, T, Hartge, P, Hassan, MM, Holcatova, I, Holly, EA, Hung, R, Janout, V, Kurtz, RC, Lee, I-M, Malats, N, McKean, D, Milne, RL, Newton, CC, Oberg, AL, Perdomo, S, Peters, U, Porta, M, Rothman, N, Schulze, MB, Sesso, HD, Silverman, DT, Thompson, IM, Wactawski-Wende, J, Weiderpass, E, Wenstzensen, N, White, E, Wilkens, LR, Yu, H, Zeleniuch-Jacquotte, A, Zhong, J, Kraft, P, Li, D, Campbell, PT, Petersen, GM, Wolpin, BM, Risch, HA, Amundadottir, LT, Klein, AP, Yu, K, Stolzenberg-Solomon, RZ, Julian-Serrano, S, Yuan, F, Wheeler, W, Benyamin, B, Machiela, MJ, Arslan, AA, Beane-Freeman, LE, Bracci, PM, Duell, EJ, Du, M, Gallinger, S, Giles, GG, Goodman, PJ, Kooperberg, C, Le Marchand, L, Neale, RE, Shu, X-O, Van den Eeden, SK, Visvanathan, K, Zheng, W, Albanes, D, Andreotti, G, Ardanaz, E, Babic, A, Berndt, S, Brais, LK, Brennan, P, Bueno-de-Mesquita, B, Buring, JE, Chanock, SJ, Childs, EJ, Chung, CC, Fabianova, E, Foretova, L, Fuchs, CS, Gaziano, JM, Gentiluomo, M, Giovannucci, EL, Goggins, MG, Hackert, T, Hartge, P, Hassan, MM, Holcatova, I, Holly, EA, Hung, R, Janout, V, Kurtz, RC, Lee, I-M, Malats, N, McKean, D, Milne, RL, Newton, CC, Oberg, AL, Perdomo, S, Peters, U, Porta, M, Rothman, N, Schulze, MB, Sesso, HD, Silverman, DT, Thompson, IM, Wactawski-Wende, J, Weiderpass, E, Wenstzensen, N, White, E, Wilkens, LR, Yu, H, Zeleniuch-Jacquotte, A, Zhong, J, Kraft, P, Li, D, Campbell, PT, Petersen, GM, Wolpin, BM, Risch, HA, Amundadottir, LT, Klein, AP, Yu, K, and Stolzenberg-Solomon, RZ

Abstract

BACKGROUND: Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVES: The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHODS: We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. RESULTS: The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSIONS: Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.

Published
2021

45. Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients

Author

Macauda, A, Piredda, C, Clay-Gilmour, A, Sainz, J, Buda, G, Markiewicz, M, Barington, T, Ziv, E, Hildebrandt, MAT, Belachew, AA, Varkonyi, J, Prejzner, W, Druzd-Sitek, A, Spinelli, J, Andersen, NF, Hofmann, JN, Dudzinski, M, Martinez-Lopez, J, Iskierka-Jazdzewska, E, Milne, RL, Mazur, G, Giles, GG, Ebbesen, LH, Rymko, M, Jamroziak, K, Subocz, E, Reis, RM, Garcia-Sanz, R, Suska, A, Haastrup, EK, Zawirska, D, Grzasko, N, Vangsted, AJ, Dumontet, C, Kruszewski, M, Dutka, M, Camp, NJ, Waller, RG, Tomczak, W, Pelosini, M, Razny, M, Marques, H, Abildgaard, N, Watek, M, Jurczyszyn, A, Brown, EE, Berndt, S, Butrym, A, Vachon, CM, Norman, AD, Slager, SL, Gemignani, F, Canzian, F, Campa, D, Macauda, A, Piredda, C, Clay-Gilmour, A, Sainz, J, Buda, G, Markiewicz, M, Barington, T, Ziv, E, Hildebrandt, MAT, Belachew, AA, Varkonyi, J, Prejzner, W, Druzd-Sitek, A, Spinelli, J, Andersen, NF, Hofmann, JN, Dudzinski, M, Martinez-Lopez, J, Iskierka-Jazdzewska, E, Milne, RL, Mazur, G, Giles, GG, Ebbesen, LH, Rymko, M, Jamroziak, K, Subocz, E, Reis, RM, Garcia-Sanz, R, Suska, A, Haastrup, EK, Zawirska, D, Grzasko, N, Vangsted, AJ, Dumontet, C, Kruszewski, M, Dutka, M, Camp, NJ, Waller, RG, Tomczak, W, Pelosini, M, Razny, M, Marques, H, Abildgaard, N, Watek, M, Jurczyszyn, A, Brown, EE, Berndt, S, Butrym, A, Vachon, CM, Norman, AD, Slager, SL, Gemignani, F, Canzian, F, and Campa, D

Abstract

Gene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype-tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10-7 either in EBV-transformed B-lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression-free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4-rs1992292, TBRG4-rs2287535 and ENTPD1-rs2153913) showed associations with OS at P < .05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta-analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4-rs1992292 is associated with OS (hazard ratio = 1.14, 95% confidence interval 1.04-1.26, P = .007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.

Published
2021

46. Genetic architectures of proximal and distal colorectal cancer are partly distinct

Author

Huyghe, JR, Harrison, TA, Bien, SA, Hampel, H, Figueiredo, JC, Schmit, SL, Conti, D, Chen, S, Qu, C, Lin, Y, Barfield, R, Baron, JA, Cross, AJ, Diergaarde, B, Duggan, D, Harlid, S, Imaz, L, Kang, HM, Levine, DM, Perduca, V, Perez-Cornago, A, Sakoda, LC, Schumacher, FR, Slattery, ML, Toland, AE, van Duijnhoven, FJB, Van Guelpen, B, Agudo, A, Albanes, D, Alonso, MH, Anderson, K, Arnau-Collell, C, Arndt, V, Banbury, BL, Bassik, MC, Berndt, S, Bezieau, S, Bishop, DT, Boehm, J, Boeing, H, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buch, S, Buchanan, DD, Burnett-Hartman, A, Caan, BJ, Campbell, PT, Carr, PR, Castells, A, Castellvi-Bel, S, Chan, AT, Chang-Claude, J, Chanock, SJ, Curtis, KR, de la Chapelle, A, Easton, DF, English, DR, Feskens, EJM, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Goodman, PJ, Grady, WM, Grove, JS, Gsur, A, Gunter, MJ, Haile, RW, Hampe, J, Hoffmeister, M, Hopper, JL, Hsu, W-L, Huang, W-Y, Hudson, TJ, Jenab, M, Jenkins, MA, Joshi, AD, Keku, TO, Kooperberg, C, Kuhn, T, Kury, S, Le Marchand, L, Lejbkowicz, F, Li, C, Li, L, Lieb, W, Lindblom, A, Lindor, NM, Mannisto, S, Markowitz, SD, Milne, RL, Moreno, L, Murphy, N, Nassir, R, Offit, K, Ogino, S, Panico, S, Parfrey, PS, Pearlman, R, Pharoah, PDP, Phipps, A, Platz, EA, Potter, JD, Prentice, RL, Qi, L, Raskin, L, Rennert, G, Rennert, HS, Riboli, E, Schafmayer, C, Schoen, RE, Seminara, D, Song, M, Su, Y-R, Tangen, CM, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Ulrich, CM, Visvanathan, K, Vodicka, P, Vodickova, L, Vymetalkova, V, Weigl, K, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Nickerson, DA, Scacheri, PC, Kundaje, A, Casey, G, Gruber, SB, Hsu, L, Moreno, V, Hayes, RB, Newcomb, PA, Peters, U, Huyghe, JR, Harrison, TA, Bien, SA, Hampel, H, Figueiredo, JC, Schmit, SL, Conti, D, Chen, S, Qu, C, Lin, Y, Barfield, R, Baron, JA, Cross, AJ, Diergaarde, B, Duggan, D, Harlid, S, Imaz, L, Kang, HM, Levine, DM, Perduca, V, Perez-Cornago, A, Sakoda, LC, Schumacher, FR, Slattery, ML, Toland, AE, van Duijnhoven, FJB, Van Guelpen, B, Agudo, A, Albanes, D, Alonso, MH, Anderson, K, Arnau-Collell, C, Arndt, V, Banbury, BL, Bassik, MC, Berndt, S, Bezieau, S, Bishop, DT, Boehm, J, Boeing, H, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buch, S, Buchanan, DD, Burnett-Hartman, A, Caan, BJ, Campbell, PT, Carr, PR, Castells, A, Castellvi-Bel, S, Chan, AT, Chang-Claude, J, Chanock, SJ, Curtis, KR, de la Chapelle, A, Easton, DF, English, DR, Feskens, EJM, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Goodman, PJ, Grady, WM, Grove, JS, Gsur, A, Gunter, MJ, Haile, RW, Hampe, J, Hoffmeister, M, Hopper, JL, Hsu, W-L, Huang, W-Y, Hudson, TJ, Jenab, M, Jenkins, MA, Joshi, AD, Keku, TO, Kooperberg, C, Kuhn, T, Kury, S, Le Marchand, L, Lejbkowicz, F, Li, C, Li, L, Lieb, W, Lindblom, A, Lindor, NM, Mannisto, S, Markowitz, SD, Milne, RL, Moreno, L, Murphy, N, Nassir, R, Offit, K, Ogino, S, Panico, S, Parfrey, PS, Pearlman, R, Pharoah, PDP, Phipps, A, Platz, EA, Potter, JD, Prentice, RL, Qi, L, Raskin, L, Rennert, G, Rennert, HS, Riboli, E, Schafmayer, C, Schoen, RE, Seminara, D, Song, M, Su, Y-R, Tangen, CM, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Ulrich, CM, Visvanathan, K, Vodicka, P, Vodickova, L, Vymetalkova, V, Weigl, K, Weinstein, SJ, White, E, Wolk, A, Woods, MO, Wu, AH, Abecasis, GR, Nickerson, DA, Scacheri, PC, Kundaje, A, Casey, G, Gruber, SB, Hsu, L, Moreno, V, Hayes, RB, Newcomb, PA, and Peters, U

Abstract

OBJECTIVE: An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. DESIGN: To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. RESULTS: We identified 13 loci that reached genome-wide significance (p<5×10-8) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. CONCLUSION: Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.

Published
2021

47. Holmium-166m measurements with AMS for the ECHo-project

Author

(0000-0002-0176-8842) Rugel, G., Berndt, S., Düllmann, C. E., Dorrer, H., Forstner, O., Kieck, T., Kneip, N., (0000-0002-2655-5800) Lachner, J., (0000-0002-8755-3980) Merchel, S., (0000-0002-4972-4072) Vivo Vilches, C., (0000-0003-2804-3670) Wallner, A., Wendt, K., (0000-0002-0176-8842) Rugel, G., Berndt, S., Düllmann, C. E., Dorrer, H., Forstner, O., Kieck, T., Kneip, N., (0000-0002-2655-5800) Lachner, J., (0000-0002-8755-3980) Merchel, S., (0000-0002-4972-4072) Vivo Vilches, C., (0000-0003-2804-3670) Wallner, A., and Wendt, K.

Abstract

The Electron Capture in ¹⁶³Ho experiment (ECHo) aims at measuring the mass of the electron neutrino by analysing the EC spectrum of the long-lived radionuclide ¹⁶³Ho (T_1/2 = 4570 a) with a metallic magnetic calorimeter (MMC). For the determination of a reasonable upper limit for the neutrino mass it is mandatory to keep the contamination with the long-lived radionuclide ¹⁶⁶mHo (T_1/2 = 1132.6 a) nine orders of magnitude below the ¹⁶³Ho content. The ion-implantation of ultra-pure ¹⁶³Ho into a MMC for the experiment is carried out by the RISIKO (Resonance Ionization Spectroscopy in KOllinear geometry) mass separator. The separation from ¹⁶⁶mHo, however, cannot be guaranteed to such low levels as needed in this project, it can only be estimated. Here we present our approach to determine the corresponding low isotopic ratio with accelerator mass spectrometry (AMS). Of course, this requires the formation of negative ions, where we find the highest negative ion yield for the anion HoO₂−. For first tests, stable ¹⁶⁵Ho was implanted by RISIKO into various different metal foils and we studied the overall Ho detection efficiency for our setup. We will present first results and estimates of the expected detection limit for the ¹⁶⁶mHo/¹⁶³Ho isotope ratio.

Published
2021

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