169 results on '"Machiela MJ"'
Search Results
2. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.
- Author
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Wang, A, Shen, J, Rodriguez, AA, Saunders, EJ, Chen, F, Janivara, R, Darst, BF, Sheng, X, Xu, Y, Chou, AJ, Benlloch, S, Dadaev, T, Brook, MN, Plym, A, Sahimi, A, Hoffman, TJ, Takahashi, A, Matsuda, K, Momozawa, Y, Fujita, M, Laisk, T, Figuerêdo, J, Muir, K, Ito, S, Liu, X, Biobank Japan Project, Uchio, Y, Kubo, M, Kamatani, Y, Lophatananon, A, Wan, P, Andrews, C, Lori, A, Choudhury, PP, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokolorczyk, D, Lubinski, J, Rentsch, CT, Cho, K, Mcmahon, BH, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, A, Stroomberg, HV, Batra, J, Chambers, S, Horvath, L, Clements, JA, Tilly, 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, S, Cook, MB, 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-É, Stanford, JL, Ostrander, EA, Koutros, S, Beane Freeman, LE, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, 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, 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, Gómez-Caamaño, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Butler, EN, Mohler, JL, Taylor, JA, Kogevinas, M, Dierssen-Sotos, T, Castaño-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Pilie, P, Yu, Y, Bohlender, RJ, Gu, J, Strom, SS, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Brenner, H, Chen, X, Holleczek, B, Schöttker, B, 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, CM, Rybicki, BA, Gamulin, M, Lessel, D, Kulis, T, Usmani, N, Abraham, A, 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, J, Petrovics, G, Casey, G, Wang, Y, Tettey, Y, Lachance, J, Tang, W, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Yamoah, K, Govindasami, K, Chokkalingam, AP, Keaton, JM, Hellwege, JN, Clark, PE, Jalloh, M, Gueye, SM, Niang, L, Ogunbiyi, O, Shittu, O, Amodu, O, Adebiyi, AO, Aisuodionoe-Shadrach, OI, Ajibola, HO, Jamda, MA, Oluwole, OP, Nwegbu, M, Adusei, B, Mante, S, Darkwa-Abrahams, A, Diop, H, Gundell, SM, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Kachuri, L, Varma, R, McKean-Cowdin, R, Torres, M, Preuss, MH, Loos, RJF, Zawistowski, M, Zöllner, S, Lu, Z, Van Den Eeden, SK, Easton, DF, Ambs, S, Edwards, TL, Mägi, R, Rebbeck, TR, Fritsche, L, Chanock, SJ, Berndt, SI, Wiklund, F, Nakagawa, H, Witte, JS, Gaziano, JM, Justice, AC, Mancuso, N, Terao, C, Eeles, RA, Kote-Jarai, Z, Madduri, RK, Conti, DV, Haiman, CA, Wang, A, Shen, J, Rodriguez, AA, Saunders, EJ, Chen, F, Janivara, R, Darst, BF, Sheng, X, Xu, Y, Chou, AJ, Benlloch, S, Dadaev, T, Brook, MN, Plym, A, Sahimi, A, Hoffman, TJ, Takahashi, A, Matsuda, K, Momozawa, Y, Fujita, M, Laisk, T, Figuerêdo, J, Muir, K, Ito, S, Liu, X, Biobank Japan Project, Uchio, Y, Kubo, M, Kamatani, Y, Lophatananon, A, Wan, P, Andrews, C, Lori, A, Choudhury, PP, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokolorczyk, D, Lubinski, J, Rentsch, CT, Cho, K, Mcmahon, BH, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, A, Stroomberg, HV, Batra, J, Chambers, S, Horvath, L, Clements, JA, Tilly, 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, S, Cook, MB, 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-É, Stanford, JL, Ostrander, EA, Koutros, S, Beane Freeman, LE, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, 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, 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, Gómez-Caamaño, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Butler, EN, Mohler, JL, Taylor, JA, Kogevinas, M, Dierssen-Sotos, T, Castaño-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Pilie, P, Yu, Y, Bohlender, RJ, Gu, J, Strom, SS, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Brenner, H, Chen, X, Holleczek, B, Schöttker, B, 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, CM, Rybicki, BA, Gamulin, M, Lessel, D, Kulis, T, Usmani, N, Abraham, A, 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, J, Petrovics, G, Casey, G, Wang, Y, Tettey, Y, Lachance, J, Tang, W, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Yamoah, K, Govindasami, K, Chokkalingam, AP, Keaton, JM, Hellwege, JN, Clark, PE, Jalloh, M, Gueye, SM, Niang, L, Ogunbiyi, O, Shittu, O, Amodu, O, Adebiyi, AO, Aisuodionoe-Shadrach, OI, Ajibola, HO, Jamda, MA, Oluwole, OP, Nwegbu, M, Adusei, B, Mante, S, Darkwa-Abrahams, A, Diop, H, Gundell, SM, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Kachuri, L, Varma, R, McKean-Cowdin, R, Torres, M, Preuss, MH, Loos, RJF, Zawistowski, M, Zöllner, S, Lu, Z, Van Den Eeden, SK, Easton, DF, Ambs, S, Edwards, TL, Mägi, R, Rebbeck, TR, Fritsche, L, Chanock, SJ, Berndt, SI, Wiklund, F, Nakagawa, H, Witte, JS, Gaziano, JM, Justice, AC, Mancuso, N, Terao, C, Eeles, RA, Kote-Jarai, Z, Madduri, RK, Conti, DV, and Haiman, CA
- Abstract
The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
- Published
- 2023
3. Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- Author
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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
4. Hepcidin-regulating iron metabolism genes and pancreatic ductal adenocarcinoma: a pathway analysis of genome-wide association studies
- Author
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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
5. Publisher Correction: Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- Author
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Conti, DV, Darst, BF, Moss, LC, Saunders, EJ, Sheng, X, Chou, A, Schumacher, FR, Olama, AAA, 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, Wokołorczyk, D, Lubiński, J, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, 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, Nordström, 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-É, Stanford, JL, Ostrander, EA, Geybels, MS, Koutros, S, Freeman, LEB, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, 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, Gómez-Caamaño, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Fontham, ETH, Mohler, J, Taylor, JA, Kogevinas, M, Llorca, J, Castaño-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, SI, Van Den Eeden, SK, Easton, DF, Chanock, SJ, Cook, MB, Wiklund, F, Nakagawa, H, Witte, JS, Eeles, RA, Kote-Jarai, Z, Haiman, CA, Conti, DV, Darst, BF, Moss, LC, Saunders, EJ, Sheng, X, Chou, A, Schumacher, FR, Olama, AAA, 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, Wokołorczyk, D, Lubiński, J, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, 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, Nordström, 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-É, Stanford, JL, Ostrander, EA, Geybels, MS, Koutros, S, Freeman, LEB, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, 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, Gómez-Caamaño, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Fontham, ETH, Mohler, J, Taylor, JA, Kogevinas, M, Llorca, J, Castaño-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, SI, 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
In the version of this article originally published, the names of the equally contributing authors and jointly supervising authors were switched. The correct affiliations are: “These authors contributed equally: David V. Conti, Burcu F. Darst. These authors jointly supervised this work: David V. Conti, Rosalind A. Eeles, Zsofia Kote-Jarai, Christopher A. Haiman.” The error has been corrected in the HTML and PDF versions of the article.
- Published
- 2021
6. Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.
- Author
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Conti, DV, Darst, BF, Moss, LC, Saunders, EJ, Sheng, X, Chou, A, Schumacher, FR, Olama, AAA, Benlloch, S, Dadaev, T, Brook, MN, Zhang, H-W, Feng, N, Mao, X, Wu, Y, Zhao, S-C, Sun, Z, Thibodeau, SN, McDonnell, SK, Schaid, DJ, West, CML, Sahimi, A, Burnet, N, Barnett, G, Maier, C, Schnoeller, T, Luedeke, M, Kibel, AS, Drake, BF, Cussenot, O, Cancel-Tassin, G, Menegaux, F, Hoffmann, TJ, Truong, T, Koudou, YA, John, EM, Grindedal, EM, Maehle, L, Khaw, K-T, Ingles, SA, Stern, MC, Vega, A, Gómez-Caamaño, A, Takahashi, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Matsuda, K, Fontham, ETH, Mohler, J, Taylor, JA, Kogevinas, M, Llorca, J, Castaño-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Strom, SS, Momozawa, Y, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Weaver, B, Brenner, H, Cuk, K, Fujita, M, Holleczek, B, Saum, K-U, Klein, EA, Hsing, AW, Kittles, RA, Murphy, AB, Logothetis, CJ, Kim, J, Neuhausen, SL, Steele, L, Muir, K, Ding, YC, Isaacs, WB, Nemesure, B, Hennis, AJM, Carpten, J, Pandha, H, Michael, A, De Ruyck, K, De Meerleer, G, Ost, P, Lophatananon, A, Xu, J, Razack, A, Lim, J, Teo, S-H, Newcomb, LF, Lin, DW, Fowke, JH, Neslund-Dudas, C, Rybicki, BA, Gamulin, M, Wan, P, Lessel, D, Kulis, T, Usmani, N, Singhal, S, Parliament, M, Claessens, F, Joniau, S, Van den Broeck, T, Gago-Dominguez, M, Castelao, JE, Le Marchand, L, Martinez, ME, Larkin, S, Townsend, PA, Aukim-Hastie, C, Bush, WS, Aldrich, MC, Crawford, DC, Srivastava, S, Cullen, JC, Petrovics, G, Wilkens, LR, Casey, G, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Varma, R, McKean-Cowdin, R, Torres, M, Mancuso, N, Stevens, VL, Berndt, SI, Van Den Eeden, SK, Easton, DF, Chanock, SJ, Cook, MB, Wiklund, F, Nakagawa, H, Witte, JS, Eeles, RA, Kote-Jarai, Z, Gapstur, SM, Haiman, CA, Carter, BD, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokołorczyk, D, Lubiński, J, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, 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, Nordström, 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-É, Stanford, JL, Ostrander, EA, Geybels, MS, Koutros, S, Freeman, LEB, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, KD, Borre, M, Blot, WJ, Zheng, W, Yeboah, ED, Mensah, JE, Lu, Y-J, Conti, DV, Darst, BF, Moss, LC, Saunders, EJ, Sheng, X, Chou, A, Schumacher, FR, Olama, AAA, Benlloch, S, Dadaev, T, Brook, MN, Zhang, H-W, Feng, N, Mao, X, Wu, Y, Zhao, S-C, Sun, Z, Thibodeau, SN, McDonnell, SK, Schaid, DJ, West, CML, Sahimi, A, Burnet, N, Barnett, G, Maier, C, Schnoeller, T, Luedeke, M, Kibel, AS, Drake, BF, Cussenot, O, Cancel-Tassin, G, Menegaux, F, Hoffmann, TJ, Truong, T, Koudou, YA, John, EM, Grindedal, EM, Maehle, L, Khaw, K-T, Ingles, SA, Stern, MC, Vega, A, Gómez-Caamaño, A, Takahashi, A, Fachal, L, Rosenstein, BS, Kerns, SL, Ostrer, H, Teixeira, MR, Paulo, P, Brandão, A, Watya, S, Lubwama, A, Bensen, JT, Matsuda, K, Fontham, ETH, Mohler, J, Taylor, JA, Kogevinas, M, Llorca, J, Castaño-Vinyals, G, Cannon-Albright, L, Teerlink, CC, Huff, CD, Strom, SS, Momozawa, Y, Multigner, L, Blanchet, P, Brureau, L, Kaneva, R, Slavov, C, Mitev, V, Leach, RJ, Weaver, B, Brenner, H, Cuk, K, Fujita, M, Holleczek, B, Saum, K-U, Klein, EA, Hsing, AW, Kittles, RA, Murphy, AB, Logothetis, CJ, Kim, J, Neuhausen, SL, Steele, L, Muir, K, Ding, YC, Isaacs, WB, Nemesure, B, Hennis, AJM, Carpten, J, Pandha, H, Michael, A, De Ruyck, K, De Meerleer, G, Ost, P, Lophatananon, A, Xu, J, Razack, A, Lim, J, Teo, S-H, Newcomb, LF, Lin, DW, Fowke, JH, Neslund-Dudas, C, Rybicki, BA, Gamulin, M, Wan, P, Lessel, D, Kulis, T, Usmani, N, Singhal, S, Parliament, M, Claessens, F, Joniau, S, Van den Broeck, T, Gago-Dominguez, M, Castelao, JE, Le Marchand, L, Martinez, ME, Larkin, S, Townsend, PA, Aukim-Hastie, C, Bush, WS, Aldrich, MC, Crawford, DC, Srivastava, S, Cullen, JC, Petrovics, G, Wilkens, LR, Casey, G, Roobol, MJ, Jenster, G, van Schaik, RHN, Hu, JJ, Sanderson, M, Varma, R, McKean-Cowdin, R, Torres, M, Mancuso, N, Stevens, VL, Berndt, SI, Van Den Eeden, SK, Easton, DF, Chanock, SJ, Cook, MB, Wiklund, F, Nakagawa, H, Witte, JS, Eeles, RA, Kote-Jarai, Z, Gapstur, SM, Haiman, CA, Carter, BD, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Giles, GG, Southey, MC, MacInnis, RJ, Cybulski, C, Wokołorczyk, D, Lubiński, J, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Nordestgaard, BG, Nielsen, SF, Weischer, M, Bojesen, SE, Røder, 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, Nordström, 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-É, Stanford, JL, Ostrander, EA, Geybels, MS, Koutros, S, Freeman, LEB, Stampfer, M, Wolk, A, Håkansson, N, Andriole, GL, Hoover, RN, Machiela, MJ, Sørensen, KD, Borre, M, Blot, WJ, Zheng, W, Yeboah, ED, Mensah, JE, and Lu, Y-J
- 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.
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- 2021
7. Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility
- Author
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Landi MT, Bishop DT, MacGregor S, Machiela MJ, Stratigos AJ, Ghiorzo P, Brossard M, Calista D, Choi J, Fargnoli MC, Zhang T, Rodolfo M, Trower AJ, Menin C, Martinez J, Hadjisavvas A, Song L, Stefanaki I, Scolyer R, Yang R, Goldstein AM, Potrony M, Kypreou KP, Pastorino L, Queirolo P, Pellegrini C, Cattaneo L, Zawistowski M, Gimenez-Xavier P, Rodriguez A, Elefanti L, Manoukian S, Rivoltini L, Smith BH, Loizidou MA, Del Regno L, Massi D, Mandala M, Khosrotehrani K, Akslen LA, Amos CI, Andresen PA, Avril MF, Azizi E, Soyer HP, Bataille V, Dalmasso B, Bowdler LM, Burdon KP, Chen WV, Codd V, Craig JE, Debniak T, Falchi M, Fang S, Friedman E, Simi S, Galan P, Garcia-Casado Z, Gillanders EM, Gordon S, Green A, Gruis NA, Hansson J, Harland M, Harris J, Helsing P, Henders A, Hocevar M, Höiom V, Hunter D, Ingvar C, Kumar R, Lang J, Lathrop GM, Lee JE, Li X, Lubinski J, Mackie RM, Malt M, Malvehy J, McAloney K, Mohamdi H, Molven A, Moses EK, Neale RE, Novakovic S, Nyholt DR, Olsson H, Orr N, Fritsche LG, Puig-Butille JA, Qureshi AA, Radford-Smith GL, Randerson-Moor J, Requena C, Rowe C, Samani NJ, Sanna M, Schadendorf D, Schulze HJ, Simms LA, Smithers M, Song F, Swerdlow AJ, van der Stoep N, Kukutsch NA, Visconti A, Wallace L, Ward SV, Wheeler L, Sturm RA, Hutchinson A, Jones K, Malasky M, Vogt A, Zhou W, Pooley KA, Elder DE, Han J, Hicks B, Hayward NK, Kanetsky PA, Brummett C, Montgomery GW, Olsen CM, Hayward C, Dunning AM, Martin NG, Evangelou E, Mann GJ, Long G, Pharoah PDP, Easton DF, Barrett JH, Cust AE, Abecasis G, Duffy DL, Whiteman DC, Gogas H, De Nicolo A, Tucker MA, Newton-Bishop JA, GenoMEL Consortium, Q-MEGA and QTWIN Investigators, ATHENS Melanoma Study Group, 23andMe, SDH Study Group, IBD Investigators, Essen-Heidelberg Investigators, AMFS Investigators, MelaNostrum Consortium, Peris K, Chanock SJ, Demenais F, Brown KM, Puig S, Nagore E, Shi J, Iles MM, and Law MH
- Abstract
Meta-analysis of 36,760 cases and 375,188 controls identifies 54 loci associated with susceptibility to cutaneous melanoma. Further analysis combining nevus count and hair color GWAS results provide insights into the genetic architecture of melanoma. Most genetic susceptibility to cutaneous melanoma remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 cases of melanoma (67% newly genotyped) and 375,188 controls identified 54 significant (P < 5 x 10(-8)) loci with 68 independent single nucleotide polymorphisms. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with GWAS of nevus count and hair color, and transcriptome association approaches, uncovered 31 potential secondary loci for a total of 85 cutaneous melanoma susceptibility loci. These findings provide insights into cutaneous melanoma genetic architecture, reinforcing the importance of nevogenesis, pigmentation and telomere maintenance, together with identifying potential new pathways for cutaneous melanoma pathogenesis.
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- 2020
8. Genetically Determined Height and Risk of Non-hodgkin Lymphoma
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Moore, A, Kane, E, Wang, Z, Panagiotou, OA, Teras, LR, Monnereau, A, Wong Doo, N, Machiela, MJ, Skibola, CF, Slager, SL, Salles, G, Camp, NJ, Bracci, PM, Nieters, A, Vermeulen, RCH, Vijai, J, Smedby, KE, Zhang, Y, Vajdic, CM, Cozen, W, Spinelli, JJ, Hjalgrim, H, Giles, GG, Link, BK, Clavel, J, Arslan, AA, Purdue, MP, Tinker, LF, Albanes, D, Ferri, GM, Habermann, TM, Adami, H-O, Becker, N, Benavente, Y, Bisanzi, S, Boffetta, P, Brennan, P, Brooks-Wilson, AR, Canzian, F, Conde, L, Cox, DG, Curtin, K, Foretova, L, Gapstur, SM, Ghesquieres, H, Glenn, M, Glimelius, B, Jackson, RD, Lan, Q, Liebow, M, Maynadie, M, McKay, J, Melbye, M, Miligi, L, Milne, RL, Molina, TJ, Morton, LM, North, KE, Offit, K, Padoan, M, Patel, AV, Piro, S, Ravichandran, V, Riboli, E, de Sanjose, S, Severson, RK, Southey, MC, Staines, A, Stewart, C, Travis, RC, Weiderpass, E, Weinstein, S, Zheng, T, Chanock, SJ, Chatterjee, N, Rothman, N, Birmann, BM, Cerhan, JR, Berndt, SI, Moore, A, Kane, E, Wang, Z, Panagiotou, OA, Teras, LR, Monnereau, A, Wong Doo, N, Machiela, MJ, Skibola, CF, Slager, SL, Salles, G, Camp, NJ, Bracci, PM, Nieters, A, Vermeulen, RCH, Vijai, J, Smedby, KE, Zhang, Y, Vajdic, CM, Cozen, W, Spinelli, JJ, Hjalgrim, H, Giles, GG, Link, BK, Clavel, J, Arslan, AA, Purdue, MP, Tinker, LF, Albanes, D, Ferri, GM, Habermann, TM, Adami, H-O, Becker, N, Benavente, Y, Bisanzi, S, Boffetta, P, Brennan, P, Brooks-Wilson, AR, Canzian, F, Conde, L, Cox, DG, Curtin, K, Foretova, L, Gapstur, SM, Ghesquieres, H, Glenn, M, Glimelius, B, Jackson, RD, Lan, Q, Liebow, M, Maynadie, M, McKay, J, Melbye, M, Miligi, L, Milne, RL, Molina, TJ, Morton, LM, North, KE, Offit, K, Padoan, M, Patel, AV, Piro, S, Ravichandran, V, Riboli, E, de Sanjose, S, Severson, RK, Southey, MC, Staines, A, Stewart, C, Travis, RC, Weiderpass, E, Weinstein, S, Zheng, T, Chanock, SJ, Chatterjee, N, Rothman, N, Birmann, BM, Cerhan, JR, and Berndt, SI
- Abstract
Although the evidence is not consistent, epidemiologic studies have suggested that taller adult height may be associated with an increased risk of some non-Hodgkin lymphoma (NHL) subtypes. Height is largely determined by genetic factors, but how these genetic factors may contribute to NHL risk is unknown. We investigated the relationship between genetic determinants of height and NHL risk using data from eight genome-wide association studies (GWAS) comprising 10,629 NHL cases, including 3,857 diffuse large B-cell lymphoma (DLBCL), 2,847 follicular lymphoma (FL), 3,100 chronic lymphocytic leukemia (CLL), and 825 marginal zone lymphoma (MZL) cases, and 9,505 controls of European ancestry. We evaluated genetically predicted height by constructing polygenic risk scores using 833 height-associated SNPs. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for association between genetically determined height and the risk of four NHL subtypes in each GWAS and then used fixed-effect meta-analysis to combine subtype results across studies. We found suggestive evidence between taller genetically determined height and increased CLL risk (OR = 1.08, 95% CI = 1.00-1.17, p = 0.049), which was slightly stronger among women (OR = 1.15, 95% CI: 1.01-1.31, p = 0.036). No significant associations were observed with DLBCL, FL, or MZL. Our findings suggest that there may be some shared genetic factors between CLL and height, but other endogenous or environmental factors may underlie reported epidemiologic height associations with other subtypes.
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- 2020
9. Coinherited genetics of multiple myeloma and its precursor, monoclonal gammopathy of undetermined significance
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Clay-Gilmour, A, Hildebrandt, MAT, Brown, EE, Hofmann, JN, Spinelli, JJ, Giles, GG, Cozen, W, Bhatti, P, Wu, X, Waller, RG, Belachew, AA, Robinson, DP, Norman, AD, Sinnwell, JP, Berndt, S, Rajkumar, SV, Kumar, SK, Chanock, SJ, Machiela, MJ, Milne, RL, Slager, SL, Camp, NJ, Ziv, E, Vachon, CM, Clay-Gilmour, A, Hildebrandt, MAT, Brown, EE, Hofmann, JN, Spinelli, JJ, Giles, GG, Cozen, W, Bhatti, P, Wu, X, Waller, RG, Belachew, AA, Robinson, DP, Norman, AD, Sinnwell, JP, Berndt, S, Rajkumar, SV, Kumar, SK, Chanock, SJ, Machiela, MJ, Milne, RL, Slager, SL, Camp, NJ, Ziv, E, and Vachon, CM
- Abstract
So far, 23 germline susceptibility loci have been associated with multiple myeloma (MM) risk. It is unclear whether the genetic variation associated with MM susceptibility also predisposes to its precursor, monoclonal gammopathy of undetermined significance (MGUS). Leveraging 2434 MM cases, 754 MGUS cases, and 2 independent sets of controls (2567/879), we investigated potential shared genetic susceptibility of MM and MGUS by (1) performing MM and MGUS genome-wide association studies (GWAS); (2) validating the association of a polygenic risk score (PRS) based on 23 established MM loci (MM-PRS) with risk of MM, and for the first time with MGUS; and (3) examining genetic correlation of MM and MGUS. Heritability and genetic estimates yielded 17% (standard error [SE] ±0.04) and 15% (SE ±0.11) for MM and MGUS risk, respectively, and a 55% (SE ±0.30) genetic correlation. The MM-PRS was associated with risk of MM when assessed continuously (odds ratio [OR], 1.17 per SD; 95% confidence interval [CI], 1.13-1.21) or categorically (OR, 1.70; 95% CI, 1.38-2.09 for highest; OR, 0.71; 95% CI, 0.55-0.90 for lowest compared with middle quintile). The MM-PRS was similarly associated with MGUS (OR, 1.19 per SD; 95% CI, 1.14-1.26 as a continuous measure, OR, 1.77, 95%CI: 1.29-2.43 for highest and OR, 0.70, 95%CI: 0.50-0.98 for lowest compared with middle quintile). MM and MGUS associations did not differ by age, sex, or MM immunoglobulin isotype. We validated a 23-SNP MM-PRS in an independent series of MM cases and provide evidence for its association with MGUS. Our results suggest shared common genetic susceptibility to MM and MGUS.
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- 2020
10. Erratum to: Germline variation at 8q24 and prostate cancer risk in men of European ancestry (Nature Communications, (2018), 9, 1, (4616), 10.1038/s41467-018-06863-1)
- Author
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Matejcic, M, Saunders, EJ, Dadaev, T, Brook, MN, Wang, K, Sheng, X, Olama, AAA, Schumacher, FR, Ingles, SA, Govindasami, K, Benlloch, S, Berndt, SI, Albanes, D, Koutros, S, Muir, K, Stevens, VL, Gapstur, SM, Tangen, CM, Batra, J, Clements, J, Gronberg, H, Pashayan, N, Schleutker, J, Wolk, A, West, C, Mucci, L, Kraft, P, Cancel-Tassin, G, Sorensen, KD, Maehle, L, Grindedal, EM, Strom, SS, Neal, DE, Hamdy, FC, Donovan, JL, Travis, RC, Hamilton, RJ, Rosenstein, B, Lu, YJ, Giles, GG, Kibel, AS, Vega, A, Bensen, JT, Kogevinas, M, Penney, KL, Park, JY, Stanford, JL, Cybulski, C, Nordestgaard, BG, Brenner, H, Maier, C, Kim, J, Teixeira, MR, Neuhausen, SL, De Ruyck, K, Razack, A, Newcomb, LF, Lessel, D, Kaneva, R, Usmani, N, Claessens, F, Townsend, PA, Gago-Dominguez, M, Roobol, MJ, Menegaux, F, Khaw, KT, Cannon-Albright, LA, Pandha, H, Thibodeau, SN, Schaid, DJ, Henderson, BE, Stern, MC, Thwaites, A, Guy, M, Whitmore, I, Morgan, A, Fisher, C, Hazel, S, Livni, N, Cook, M, Fachal, L, Weinstein, S, Beane Freeman, LE, Hoover, RN, Machiela, MJ, Lophatananon, A, Carter, BD, Goodman, P, Moya, L, Srinivasan, S, Kedda, MA, Yeadon, T, Eckert, A, Eklund, M, Cavalli-Bjoerkman, C, Dunning, AM, Sipeky, C, Hakansson, N, Elliott, R, and Ranu, H
- Abstract
© 2019, The Author(s). The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.
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- 2019
11. Germline variation at 8q24 and prostate cancer risk in men of European ancestry (vol 9, 4616, 2018)
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Matejcic, M, Saunders, EJ, Dadaev, T, Brook, MN, Wang, K, Sheng, X, Al Olama, AA, Schumacher, FR, Ingles, SA, Govindasami, K, Benlloch, S, Berndt, SI, Albanes, D, Koutros, S, Muir, K, Stevens, VL, Gapstur, SM, Tangen, CM, Batra, J, Clements, J, Gronberg, H, Pashayan, N, Schleutker, J, Wolk, A, West, C, Mucci, L, Kraft, P, Cancel-Tassin, G, Sorensen, KD, Maehle, L, Grindedal, EM, Strom, SS, Neal, DE, Hamdy, FC, Donovan, JL, Travis, RC, Hamilton, RJ, Rosenstein, B, Lu, Y-J, Giles, GG, Kibel, AS, Vega, A, Bensen, JT, Kogevinas, M, Penney, KL, Park, JY, Stanford, JL, Cybulski, C, Nordestgaard, BG, Brenner, H, Maier, C, Kim, J, Teixeira, MR, Neuhausen, SL, De Ruyck, K, Razack, A, Newcomb, LF, Lessel, D, Kaneva, R, Usmani, N, Claessens, F, Townsend, PA, Gago-Dominguez, M, Roobol, MJ, Menegaux, F, Khaw, K-T, Cannon-Albright, LA, Pandha, H, Thibodeau, SN, Schaid, DJ, Wiklund, F, Chanock, SJ, Easton, DF, Eeles, RA, Kote-Jarai, Z, Conti, DV, Haiman, CA, Henderson, BE, Stern, MC, Thwaites, A, Guy, M, Whitmore, I, Morgan, A, Fisher, C, Hazel, S, Livni, N, Cook, M, Fachal, L, Weinstein, S, Freeman, LEB, Hoover, RN, Machiela, MJ, Lophatananon, A, Carter, BD, Goodman, P, Moya, L, Srinivasan, S, Kedda, M-A, Yeadon, T, Eckert, A, Eklund, M, Cavalli-Bjoerkman, C, Dunning, AM, Sipeky, C, Hakansson, N, Elliott, R, Ranu, H, Giovannucci, E, Turman, C, Hunter, DJ, Cussenot, O, Orntoft, TF, Lane, A, Lewis, SJ, Davis, M, Key, TJ, Brown, P, Kulkarni, GS, Zlotta, AR, Fleshner, NE, Finelli, A, Mao, X, Marzec, J, MacInnis, RJ, Milne, R, Hopper, JL, Aguado, M, Bustamante, M, Castano-Vinyals, G, Gracia-Lavedan, E, Cecchini, L, Stampfer, M, Ma, J, Sellers, TA, Geybels, MS, Park, H, Zachariah, B, Kolb, S, Wokolorczyk, D, Lubinski, J, Kluzniak, W, Nielsen, SF, Weisher, M, Cuk, K, Vogel, W, Luedeke, M, Logothetis, CJ, Paulo, P, Cardoso, M, Maia, S, Silva, MP, Steele, L, Ding, YC, De Meerleer, G, De Langhe, S, Thierens, H, Lim, J, Tan, MH, Ong, AT, Lin, DW, Kachakova, D, Mitkova, A, Mitev, V, Parliament, M, Jenster, G, Bangma, C, Schroder, FH, Truong, T, Koudou, YA, Michael, A, Kierzek, A, Karlsson, A, Broms, M, Wu, H, Aukim-Hastie, C, Tillmans, L, Riska, S, McDonnell, SK, Dearnaley, D, Spurdle, A, Gardiner, R, Hayes, V, Butler, L, Taylor, R, Papargiris, M, Saunders, P, Kujala, P, Talala, K, Taari, K, Bentzen, S, Hicks, B, Vogt, A, Hutchinson, A, Cox, A, George, A, Toi, A, Evans, A, Van der Kwast, TH, Imai, T, Saito, S, Zhao, S-C, Ren, G, Zhang, Y, Yu, Y, Wu, Y, Wu, J, Zhou, B, Pedersen, J, Lobato-Busto, R, Manuel Ruiz-Dominguez, J, Mengual, L, Alcaraz, A, Pow-Sang, J, Herkommer, K, Vlahova, A, Dikov, T, Christova, S, Carracedo, A, Tretarre, B, Rebillard, X, Mulot, C, Adolfsson, J, Stattin, P, Johansson, J-E, Martin, RM, Thompson, IM, Chambers, S, Aitken, J, Horvath, L, Haynes, A-M, Tilley, W, Risbridger, G, Aly, M, Nordstrom, T, Pharoah, P, Tammela, TLJ, Murtola, T, Auvinen, A, Burnet, N, Barnett, G, Andriole, G, Klim, A, Drake, BF, Borre, M, Kerns, S, Ostrer, H, Zhang, H-W, Cao, G, Lin, J, Ling, J, Li, M, Feng, N, Li, J, He, W, Guo, X, Sun, Z, Wang, G, Guo, J, Southey, MC, FitzGerald, LM, Marsden, G, Gomez-Caamano, A, Carballo, A, Peleteiro, P, Calvo, P, Szulkin, R, Llorca, J, Dierssen-Sotos, T, Gomez-Acebo, I, Lin, H-Y, Ostrander, EA, Bisbjerg, R, Klarskov, P, Roder, MA, Iversen, P, Holleczek, B, Stegmaier, C, Schnoeller, T, Bohnert, P, John, EM, Ost, P, Teo, S-H, Gamulin, M, Kulis, T, Kastelan, Z, Slavov, C, Popov, E, Van den Broeck, T, Joniau, S, Larkin, S, Esteban Castelao, J, Martinez, ME, Van Schaik, RHN, Xu, J, Lindstrom, S, Riboli, E, Berry, C, Siddiq, A, Canzian, F, Kolonel, LN, Le Marchand, L, Freedman, M, Cenee, S, Sanchez, M, and Commission of the European Communities
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Multidisciplinary Sciences ,Science & Technology ,MD Multidisciplinary ,Science & Technology - Other Topics ,PRACTICAL Consortium - Abstract
Correction to: Nature Communications; https://doi.org/10.1038/s41467-018-06863-1, published online 5 November 2018.
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- 2019
12. Germline variation at 8q24 and prostate cancer risk in men of European ancestry
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Matejcic, M, Saunders, EJ, Dadaev, T, Brook, MN, Wang, K, Sheng, X, Olama, AAA, Schumacher, FR, Ingles, SA, Govindasami, K, Benlloch, S, Berndt, SI, Albanes, D, Koutros, S, Muir, K, Stevens, VL, Gapstur, SM, Tangen, CM, Batra, J, Clements, J, Gronberg, H, Pashayan, N, Schleutker, J, Wolk, A, West, C, Mucci, L, Kraft, P, Cancel-Tassin, G, Sorensen, KD, Maehle, L, Grindedal, EM, Strom, SS, Neal, DE, Hamdy, FC, Donovan, JL, Travis, RC, Hamilton, RJ, Rosenstein, B, Lu, YJ, Giles, GG, Kibel, AS, Vega, A, Bensen, JT, Kogevinas, M, Penney, KL, Park, JY, Stanford, JL, Cybulski, C, Nordestgaard, BG, Brenner, H, Maier, C, Kim, J, Teixeira, MR, Neuhausen, SL, De Ruyck, K, Razack, A, Newcomb, LF, Lessel, D, Kaneva, R, Usmani, N, Claessens, F, Townsend, PA, Dominguez, MG, Roobol, MJ, Menegaux, F, Khaw, KT, Cannon-Albright, LA, Pandha, H, Thibodeau, SN, Schaid, DJ, Henderson, BE, Stern, MC, Thwaites, A, Guy, M, Whitmore, I, Morgan, A, Fisher, C, Hazel, S, Livni, N, Cook, M, Fachal, L, Weinstein, S, Beane Freeman, LE, Hoover, RN, Machiela, MJ, Lophatananon, A, Carter, BD, Goodman, P, Moya, L, Srinivasan, S, Kedda, MA, Yeadon, T, Eckert, A, Eklund, M, Cavalli-Bjoerkman, C, Dunning, AM, Sipeky, C, Hakansson, N, Elliott, R, and Ranu, H
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Genetic Markers ,Male ,Genotype ,European Continental Ancestry Group ,Prostatic Neoplasms ,Chromosome Mapping ,Risk Assessment ,Haplotypes ,Risk Factors ,Case-Control Studies ,Humans ,Genetic Predisposition to Disease ,Disease Susceptibility ,Chromosomes, Human, Pair 8 - Abstract
© 2018, The Author(s). Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.
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- 2018
13. Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
- Author
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Dadaev, T, Saunders, EJ, Newcombe, PJ, Anokian, E, Leongamornlert, DA, Brook, MN, Cieza-Borrella, C, Mijuskovic, M, Wakerell, S, Olama, AAA, Schumacher, FR, Berndt, SI, Benlloch, S, Ahmed, M, Goh, C, Sheng, X, Zhang, Z, Muir, K, Govindasami, K, Lophatananon, A, Stevens, VL, Gapstur, SM, Carter, BD, Tangen, CM, Goodman, P, Thompson, IM, Batra, J, Chambers, S, Moya, L, Clements, J, Horvath, L, Tilley, W, Risbridger, G, Gronberg, H, Aly, M, Nordström, T, Pharoah, P, Pashayan, N, Schleutker, J, Tammela, TLJ, Sipeky, C, Auvinen, A, Albanes, D, Weinstein, S, Wolk, A, Hakansson, N, West, C, Dunning, AM, Burnet, N, Mucci, L, Giovannucci, E, Andriole, G, Cussenot, O, Cancel-Tassin, G, Koutros, S, Freeman, LEB, Sorensen, KD, Orntoft, TF, Borre, M, Maehle, L, Grindedal, EM, Neal, DE, Donovan, JL, Hamdy, FC, Martin, RM, Travis, RC, Key, TJ, Hamilton, RJ, Fleshner, NE, Finelli, A, Ingles, SA, Stern, MC, Rosenstein, B, Kerns, S, Ostrer, H, Lu, Y-J, Zhang, H-W, Feng, N, Mao, X, Guo, X, Wang, G, Sun, Z, Giles, GG, Southey, MC, Macinnis, RJ, Fitzgerald, LM, Kibel, AS, Drake, BF, Vega, A, Gómez-Caamaño, A, Fachal, L, Szulkin, R, Eklund, M, Kogevinas, M, Llorca, J, Castaño-Vinyals, G, Penney, KL, Stampfer, M, Park, JY, Sellers, TA, Lin, H-Y, Stanford, JL, Cybulski, C, Wokolorczyk, D, Lubinski, J, Ostrander, EA, Geybels, MS, Nordestgaard, BG, Nielsen, SF, Weisher, M, Bisbjerg, R, Røder, MA, Iversen, P, Brenner, H, Cuk, K, Holleczek, B, Maier, C, Luedeke, M, Schnoeller, T, Kim, J, Logothetis, CJ, John, EM, Teixeira, MR, Paulo, P, Cardoso, M, Neuhausen, SL, Steele, L, Ding, YC, De Ruyck, K, De Meerleer, G, Ost, P, Razack, A, Lim, J, Teo, S-H, Lin, DW, Newcomb, LF, Lessel, D, Gamulin, M, Kulis, T, Kaneva, R, Usmani, N, Slavov, C, Mitev, V, Parliament, M, Singhal, S, Claessens, F, Joniau, S, Van Den Broeck, T, Larkin, S, Townsend, PA, Aukim-Hastie, C, Gago-Dominguez, M, Castelao, JE, Martinez, ME, Roobol, MJ, Jenster, G, Van Schaik, RHN, Menegaux, F, Truong, T, Koudou, YA, Xu, J, Khaw, K-T, Cannon-Albright, L, Pandha, H, Michael, A, Kierzek, A, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Lindstrom, S, Turman, C, Ma, J, Hunter, DJ, Riboli, E, Siddiq, A, Canzian, F, Kolonel, LN, Le Marchand, L, Hoover, RN, Machiela, MJ, Kraft, P, Consortium, Practical (Prostate Cancer Association Group To Investigate Cancer-Associated Alterations In The Genome), Freedman, M, Wiklund, F, Chanock, S, Henderson, BE, Easton, DF, Haiman, CA, Eeles, RA, Conti, DV, Kote-Jarai, Z, Dadaev, Tokhir [0000-0002-8268-0438], Leongamornlert, Daniel A [0000-0002-3486-3168], Brook, Mark N [0000-0002-8969-2378], Olama, Ali Amin Al [0000-0002-7178-3431], Schumacher, Fredrick R [0000-0002-3073-7463], Muir, Kenneth [0000-0001-6429-988X], Batra, Jyotsna [0000-0003-4646-6247], Nordström, Tobias [0000-0003-4915-7546], Pharoah, Paul [0000-0001-8494-732X], Pashayan, Nora [0000-0003-0843-2468], Schleutker, Johanna [0000-0002-1863-0305], Sipeky, Csilla [0000-0002-8853-4722], Wolk, Alicja [0000-0001-7387-6845], Cancel-Tassin, Géraldine [0000-0002-9583-6382], Sorensen, Karina Dalsgaard [0000-0002-4902-5490], Kerns, Sarah [0000-0002-6503-0011], Ostrer, Harry [0000-0002-2209-5376], Fachal, Laura [0000-0002-7256-9752], Kogevinas, Manolis [0000-0002-9605-0461], Nordestgaard, Børge G [0000-0002-1954-7220], Lim, Jasmine [0000-0002-7501-1834], Truong, Thérèse [0000-0002-2943-6786], Xu, Jianfeng [0000-0002-1343-8752], Easton, Douglas F [0000-0003-2444-3247], Eeles, Rosalind A [0000-0002-3698-6241], Apollo - University of Cambridge Repository, National Institutes of Health, Urology, and Clinical Chemistry
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Male ,Risk ,Science ,GENETIC ,Quantitative Trait Loci ,Black People ,PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium ,urologic and male genital diseases ,ANNOTATION ,Polymorphism, Single Nucleotide ,Article ,White People ,REGION ,GENETIC ASSOCIATION ,SDG 3 - Good Health and Well-being ,MD Multidisciplinary ,Medicine and Health Sciences ,ELEMENTS ,Humans ,Genetic Predisposition to Disease ,GENOME-WIDE ASSOCIATION ,lcsh:Science ,Medicinsk genetik ,MODEL SELECTION ,BAYESIAN FRAMEWORK ,Cancer och onkologi ,Science & Technology ,Chromosome Mapping ,Prostatic Neoplasms ,Bayes Theorem ,Molecular Sequence Annotation ,ASSOCIATION ,JOINT ANALYSIS ,RISK LOCI ,STATISTICS ,Multidisciplinary Sciences ,Cancer and Oncology ,Multivariate Analysis ,Science & Technology - Other Topics ,lcsh:Q ,Medical Genetics ,Algorithms ,VARIABLE-SELECTION ,Genome-Wide Association Study - Abstract
Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling., Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.
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- 2018
14. Genome-wide association study identifies multiple risk loci for renal cell carcinoma
- Author
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Scelo, G, Purdue, MP, Brown, KM, Johansson, M, Wang, Z, Eckel-Passow, JE, Ye, Y, Hoffman, JN, Choi, J, Foll, M, Gaborieau, V, Machiela, MJ, Colli, LM, Li, P, Sampson, JN, Abedi-Ardekani, B, Besse, C, Blanche, H, Boland, A, Burdette, L, Charbrier, A, Durand, G, Le Calvez-Kelm, F, Prokhortchouk, E, Robinot, N, Skyrabin, KG, Wozniak, MB, Yeager, M, Basta-Jovanovich, G, Dzamic, Z, Foretova, L, Holcatova, I, Janout, V, Mates, D, Mukeriya, A, Rascu, S, Zaridze, D, Bencko, V, Cybulski, C, Fabianova, E, Jinga, V, Lissowska, J, Lubinski, J, Navratilova, M, Rudnai, P, Szeszenia-Dabrowska, N, Benhamou, S, Cancel-Tassin, G, Cussenot, O, Baglietto, L, Boeing, H, Khaw, K-T, Weiderpass, E, Ljungberg, B, Sitaram, RT, Bruinsma, F, Jordan, SJ, Severi, G, Winship, I, Hveem, K, Vatten, LJ, Fletcher, T, Koppova, K, Larsson, SC, Wolk, A, Banks, RE, Selby, PJ, Easton, DF, Pharoah, P, Andreotti, G, Beane Freeman, LE, Koutros, S, Albanes, D, Mannisto, S, Weinstein, S, Clark, PE, Edwards, TL, Lipworth, L, Gapstur, SM, Stevens, VL, Carol, H, Freedman, ML, Pomerantz, MM, Cho, E, Kraft, P, Preston, MA, Wilson, KM, Gaziano, JM, Sesso, HD, Black, A, Freedman, ND, Huang, WY, Anema, JG, Kahnoski, RJ, Lane, BR, Noyes, SL, Petillo, D, Teh, BT, Peters, U, White, E, Anderson, GL, Johnson, L, Luo, J, Buring, J, Lee, I-M, Chow, W-H, Moore, LE, Wood, C, Eisen, T, Henrion, M, Larkin, J, Barman, P, Leibovich, BC, Choueiri, TK, Lathrop, GM, Rothman, N, Deleuze, J-F, McKay, JD, Parker, AS, Wu, X, Houlston, RS, Brennan, P, and Chanock, SJ
- Abstract
Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10−10), 3p22.1 (rs67311347, P=2.5 × 10−8), 3q26.2 (rs10936602, P=8.8 × 10−9), 8p21.3 (rs2241261, P=5.8 × 10−9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10−8), 11q22.3 (rs74911261, P=2.1 × 10−10) and 14q24.2 (rs4903064, P=2.2 × 10−24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility.
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- 2017
15. Body mass index and breast cancer survival: a Mendelian randomization analysis
- Author
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Guo, Q, Burgess, S, Turman, C, Bolla, MK, Wang, Q, Lush, M, Abraham, J, Aittomäki, K, Andrulis, IL, Apicella, C, Arndt, V, Barrdahl, M, Benitez, J, Berg, CD, Blomqvist, C, Bojesen, SE, Bonanni, B, Brand, JS, Brenner, H, Broeks, A, Burwinkel, B, Caldas, C, Campa, D, Canzian, F, Chang-Claude, J, Chanock, SJ, Chin, S-F, Couch, FJ, Cox, A, Cross, SS, Cybulski, C, Czene, K, Darabi, H, Devilee, P, Diver, WR, Dunning, AM, Earl, HM, Eccles, DM, Ekici, AB, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Flesch-Janys, D, Flyger, H, Gapstur, SM, Gaudet, MM, Giles, GG, Glendon, G, Grip, M, Gronwald, J, Haeberle, L, Haiman, CA, Hall, P, Hamann, U, Hankinson, S, Hartikainen, JM, Hein, A, Hiller, L, Hogervorst, FB, Holleczek, B, Hooning, MJ, Hoover, RN, Humphreys, K, Hunter, DJ, Hüsing, A, Jakubowska, A, Jukkola-Vuorinen, A, Kaaks, R, Kabisch, M, Kataja, V, Investigators, Kconfab/Aocs, Knight, JA, Koppert, LB, Kosma, V-M, Kristensen, VN, Lambrechts, D, Le Marchand, L, Li, J, Lindblom, A, Lindström, S, Lissowska, J, Lubinski, J, Machiela, MJ, Mannermaa, A, Manoukian, S, Margolin, S, Marme, F, Martens, JWM, McLean, C, Menéndez, P, Milne, RL, Mulligan, A, Muranen, TA, Nevanlinna, H, Neven, P, Nielsen, SF, Nordestgaard, BG, Olson, JE, Perez, JIA, Peterlongo, P, Phillips, K-A, Poole, CJ, Pylkäs, K, Radice, P, Rahman, N, Rüdiger, T, Rudolph, A, Sawyer, EJ, Schumacher, F, Seibold, P, Seynaeve, C, Shah, M, Smeets, A, Southey, MC, Tollenaar, RAEM, Tomlinson, I, Tsimiklis, H, Ulmer, H-U, Vachon, C, Van Den Ouweland, AMW, Veer, LJ, Wildiers, H, Willett, W, Winqvist, R, Zamora, MP, Chenevix-Trench, G, Dörk, T, Easton, DF, García-Closas, M, Kraft, P, Hopper, JL, Zheng, W, Schmidt, MK, Pharoah, PDP, Medical Oncology, and Surgery
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Genetic Variation ,Breast Neoplasms ,Mendelian Randomization Analysis ,Body mass index ,Breast cancer survival ,Epidemiology ,Genetics ,Mendelian randomization ,Polymorphism, Single Nucleotide ,Risk Assessment ,Survival Analysis ,White People ,Causality ,Europe ,RC0254 ,Meta-Analysis as Topic ,Receptors, Estrogen ,SDG 3 - Good Health and Well-being ,Risk Factors ,breast cancer survival ,Humans ,Female ,epidemiology ,genetics ,Cancer - Abstract
Background There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01–1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89–1.13, P = 0.95). Conclusions Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.
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- 2017
16. Two susceptibility loci identified for prostate cancer aggressiveness
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Berndt, Si, Wang, Z, Yeager, M, Alavanja, Mc, Albanes, D, Amundadottir, L, Andriole, G, Beane Freeman, L, Campa, D, Cancel-Tassin, G, Canzian, F, Cornu, Jn, Cussenot, O, Diver, Wr, Gapstur, Sm, Grönberg, H, Haiman, Ca, Henderson, B, Hutchinson, A, Hunter, Dj, Key, Tj, Kolb, S, Koutros, S, Kraft, P, Le Marchand, L, Lindström, S, Machiela, Mj, Ostrander, Ea, Riboli, E, Schumacher, F, Siddiq, A, Stanford, Jl, Stevens, Vl, Travis, Rc, Tsilidis, Kk, Virtamo, J, Weinstein, S, Wilkund, F, Xu, J, Lilly Zheng, S, Yu, K, Wheeler, W, Zhang, H, African, Ancestry Prostate Cancer GWAS Consortium, Sampson, J, Black, A, Jacobs, K, Hoover, Rn, Tucker, M, Chanock, Sj. Ingles SA, Kittles, Ra, Strom, Ss, Rybicki, Ba, Nemesure, B, Isaacs, Wb, Zheng, W, Pettaway, Ca, Yeboah, Ed, Tettey, Y, Biritwum, Rb, Adjei, Aa, Tay, E, Truelove, A, Niwa, S, Chokkalingam, Ap, John, Em, Murphy, Ab, Signorello, Lb, Carpten, J, Leske, Mc, Wu, Sy, Hennis, Aj, Neslund-Dudas, C, Hsing, Aw, Chu, L, Goodman, Pj, Klein, Ea, Witte, Js, Casey, G, Kaggwa, S, Cook, Mb, Stram, Do, and Blot, Wj.
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Oncology ,Male ,Aging ,GLEASON SCORE ,LINKAGE SCAN ,General Physics and Astronomy ,Genome-wide association study ,Disease ,Bioinformatics ,Prostate cancer ,SEQUENCE VARIANTS ,Medicine ,2.1 Biological and endogenous factors ,GTPASE-ACTIVATING PROTEIN ,Aetiology ,POPULATION ,Cancer ,RISK ,education.field_of_study ,African Ancestry Prostate Cancer GWAS Consortium ,Multidisciplinary ,Prostate Cancer ,3. Good health ,Multidisciplinary Sciences ,Science & Technology - Other Topics ,Urologic Diseases ,medicine.medical_specialty ,Population ,Article ,General Biochemistry, Genetics and Molecular Biology ,GENOME-WIDE ASSOCIATION ,BASE-LINE CHARACTERISTICS ,COHORT ,METAANALYSIS ,Internal medicine ,Genetics ,SNP ,Humans ,Neoplasm Invasiveness ,Genetic Predisposition to Disease ,education ,Pathological ,Science & Technology ,business.industry ,Vascular disease ,Prevention ,Human Genome ,Case-control study ,Prostatic Neoplasms ,General Chemistry ,medicine.disease ,Genetic Loci ,Case-Control Studies ,Neoplasm Grading ,business - Abstract
Most men diagnosed with prostate cancer will experience indolent disease; hence, discovering genetic variants that distinguish aggressive from nonaggressive prostate cancer is of critical clinical importance for disease prevention and treatment. In a multistage, case-only genome-wide association study of 12,518 prostate cancer cases, we identify two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49 × 10(-9)) and rs78943174 at 3q26.31 (NAALADL2, P=4.18 × 10(-8)). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85 × 10(-5)) with no association for nonaggressive prostate cancer compared with controls (P=0.57). The proximity of these loci to genes involved in vascular disease suggests potential biological mechanisms worthy of further investigation.
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- 2015
17. Identification of novel genetic markers of breast cancer survival
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Guo, Q, Schmidt, Mk, Kraft, P, Canisius, S, Chen, C, Khan, S, Tyrer, J, Bolla, Mk, Wang, Q, Dennis, J, Michailidou, K, Lush, M, Kar, S, Beesley, J, Dunning, Am, Shah, M, Czene, K, Darabi, H, Eriksson, M, Lambrechts, D, Weltens, C, Leunen, K, Bojesen, Se, Nordestgaard, Bg, Nielsen, Sf, Flyger, H, Chang Claude, J, Rudolph, A, Seibold, P, Flesch Janys, D, Blomqvist, C, Aittomäki, K, Fagerholm, R, Muranen, Ta, Couch, Fj, Olson, Je, Vachon, C, Andrulis, Il, Knight, Ja, Glendon, G, Mulligan, Am, Broeks, A, Hogervorst, Fb, Haiman, Ca, Henderson, Be, Schumacher, F, Le Marchand, L, Hopper, Jl, Tsimiklis, H, Apicella, C, Southey, Mc, Cox, A, Cross, Ss, Reed, Mw, Giles, Gg, Milne, Rl, Mclean, C, Winqvist, R, Pylkäs, K, Jukkola Vuorinen, A, Grip, M, Hooning, Mj, Hollestelle, A, Martens, Jw, van den Ouweland, Am, Marme, F, Schneeweiss, A, Yang, R, Burwinkel, B, Figueroa, J, Chanock, Sj, Lissowska, J, Sawyer, Ej, Tomlinson, I, Kerin, Mj, Miller, N, Brenner, H, Dieffenbach, Ak, Arndt, V, Holleczek, B, Mannermaa, A, Kataja, V, Kosma, Vm, Hartikainen, Jm, Li, J, Brand, Js, Humphreys, K, Devilee, P, Tollenaar, Ra, Seynaeve, C, Radice, P, Peterlongo, P, Bonanni, B, Mariani, P, Fasching, Beckmann, Mw, Hein, A, Ekici, Ab, Chenevix Trench, G, Balleine, R, Kconfab, Investigators, Phillips, Ka, Benitez, J, Zamora, Mp, Arias Perez, Ji, Menéndez, P, Jakubowska, A, Lubinski, J, Jaworska Bieniek, K, Durda, K, Hamann, U, Kabisch, M, Ulmer, Hu, Rüdiger, T, Margolin, S, Kristensen, V, Nord, S, Evans, Dg, Abraham, Je, Earl, Hm, Hiller, L, Dunn, Ja, Bowden, S, Berg, C, Campa, Daniele, Diver, Wr, Gapstur, Sm, Gaudet, Mm, Hankinson, Se, Hoover, Rn, Hüsing, A, Kaaks, R, Machiela, Mj, Willett, W, Barrdahl, M, Canzian, F, Chin, Sf, Caldas, C, Hunter, Dj, Lindstrom, S, García Closas, M, Hall, P, Easton, Df, Eccles, Dm, Rahman, N, Nevanlinna, H, and Pharoah, P. d.
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GENOME-WIDE ASSOCIATION ,SINGLE-NUCLEOTIDE POLYMORPHISMS ,GENOTYPE IMPUTATION ,PROGNOSIS ,RISK ,LOCI ,CYCLOPHOSPHAMIDE ,METAANALYSIS ,PROGRESSION ,EPIRUBICIN - Published
- 2015
18. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome
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Machiela, MJ, Zhou, W, Karlins, E, Sampson, JN, Freedman, ND, Yang, Q, Hicks, B, Dagnall, C, Hautman, C, Jacobs, KB, Abnet, CC, Aldrich, MC, Amos, C, Amundadottir, LT, Arslan, AA, Beane-Freeman, LE, Berndt, SI, Black, A, Blot, WJ, Bock, CH, Bracci, PM, Brinton, LA, Bueno-de-Mesquita, HB, Burdett, L, Buring, JE, Butler, MA, Canzian, F, Carreon, T, Chaffee, KG, Chang, I-S, Chatterjee, N, Chen, C, Chen, K, Chung, CC, Cook, LS, Bou, MC, Cullen, M, Davis, FG, De Vivo, I, Ding, T, Doherty, J, Duell, EJ, Epstein, CG, Fan, J-H, Figueroa, JD, Fraumeni, JF, Friedenreich, CM, Fuchs, CS, Gallinger, S, Gao, Y-T, Gapstur, SM, Garcia-Closas, M, Gaudet, MM, Gaziano, JM, Giles, GG, Gillanders, EM, Giovannucci, EL, Goldin, L, Goldstein, AM, Haiman, CA, Hallmans, G, Hankinson, SE, Harris, CC, Henriksson, R, Holly, EA, Hong, Y-C, Hoover, RN, Hsiung, CA, Hu, N, Hu, W, Hunter, DJ, Hutchinson, A, Jenab, M, Johansen, C, Khaw, K-T, Kim, HN, Kim, YH, Kim, YT, Klein, AP, Klein, R, Koh, W-P, Kolonel, LN, Kooperberg, C, Kraft, P, Krogh, V, Kurtz, RC, LaCroix, A, Lan, Q, Landi, MT, Le Marchand, L, Li, D, Liang, X, Liao, LM, Lin, D, Liu, J, Lissowska, J, Lu, L, Magliocco, AM, Malats, N, Matsuo, K, McNeill, LH, McWilliams, RR, Melin, BS, Mirabello, L, Moore, L, Olson, SH, Orlow, I, Park, JY, Patino-Garcia, A, Peplonska, B, Peters, U, Petersen, GM, Pooler, L, Prescott, J, Prokunina-Olsson, L, Purdue, MP, Qiao, Y-L, Rajaraman, P, Real, FX, Riboli, E, Risch, HA, Rodriguez-Santiago, B, Ruder, AM, Savage, SA, Schumacher, F, Schwartz, AG, Schwartz, KL, Seow, A, Setiawan, VW, Severi, G, Shen, H, Sheng, X, Shin, M-H, Shu, X-O, Silverman, DT, Spitz, MR, Stevens, VL, Stolzenberg-Solomon, R, Stram, D, Tang, Z-Z, Taylor, PR, Teras, LR, Tobias, GS, Van den Berg, D, Visvanathan, K, Wacholder, S, Wang, J-C, Wang, Z, Wentzensen, N, Wheeler, W, White, E, Wiencke, JK, Wolpin, BM, Wong, MP, Wu, C, Wu, T, Wu, X, Wu, Y-L, Wunder, JS, Xia, L, Yang, HP, Yang, P-C, Yu, K, Zanetti, KA, Zeleniuch-Jacquotte, A, Zheng, W, Zhou, B, Ziegler, RG, Perez-Jurado, LA, Caporaso, NE, Rothman, N, Tucker, M, Dean, MC, Yeager, M, Chanock, SJ, Machiela, MJ, Zhou, W, Karlins, E, Sampson, JN, Freedman, ND, Yang, Q, Hicks, B, Dagnall, C, Hautman, C, Jacobs, KB, Abnet, CC, Aldrich, MC, Amos, C, Amundadottir, LT, Arslan, AA, Beane-Freeman, LE, Berndt, SI, Black, A, Blot, WJ, Bock, CH, Bracci, PM, Brinton, LA, Bueno-de-Mesquita, HB, Burdett, L, Buring, JE, Butler, MA, Canzian, F, Carreon, T, Chaffee, KG, Chang, I-S, Chatterjee, N, Chen, C, Chen, K, Chung, CC, Cook, LS, Bou, MC, Cullen, M, Davis, FG, De Vivo, I, Ding, T, Doherty, J, Duell, EJ, Epstein, CG, Fan, J-H, Figueroa, JD, Fraumeni, JF, Friedenreich, CM, Fuchs, CS, Gallinger, S, Gao, Y-T, Gapstur, SM, Garcia-Closas, M, Gaudet, MM, Gaziano, JM, Giles, GG, Gillanders, EM, Giovannucci, EL, Goldin, L, Goldstein, AM, Haiman, CA, Hallmans, G, Hankinson, SE, Harris, CC, Henriksson, R, Holly, EA, Hong, Y-C, Hoover, RN, Hsiung, CA, Hu, N, Hu, W, Hunter, DJ, Hutchinson, A, Jenab, M, Johansen, C, Khaw, K-T, Kim, HN, Kim, YH, Kim, YT, Klein, AP, Klein, R, Koh, W-P, Kolonel, LN, Kooperberg, C, Kraft, P, Krogh, V, Kurtz, RC, LaCroix, A, Lan, Q, Landi, MT, Le Marchand, L, Li, D, Liang, X, Liao, LM, Lin, D, Liu, J, Lissowska, J, Lu, L, Magliocco, AM, Malats, N, Matsuo, K, McNeill, LH, McWilliams, RR, Melin, BS, Mirabello, L, Moore, L, Olson, SH, Orlow, I, Park, JY, Patino-Garcia, A, Peplonska, B, Peters, U, Petersen, GM, Pooler, L, Prescott, J, Prokunina-Olsson, L, Purdue, MP, Qiao, Y-L, Rajaraman, P, Real, FX, Riboli, E, Risch, HA, Rodriguez-Santiago, B, Ruder, AM, Savage, SA, Schumacher, F, Schwartz, AG, Schwartz, KL, Seow, A, Setiawan, VW, Severi, G, Shen, H, Sheng, X, Shin, M-H, Shu, X-O, Silverman, DT, Spitz, MR, Stevens, VL, Stolzenberg-Solomon, R, Stram, D, Tang, Z-Z, Taylor, PR, Teras, LR, Tobias, GS, Van den Berg, D, Visvanathan, K, Wacholder, S, Wang, J-C, Wang, Z, Wentzensen, N, Wheeler, W, White, E, Wiencke, JK, Wolpin, BM, Wong, MP, Wu, C, Wu, T, Wu, X, Wu, Y-L, Wunder, JS, Xia, L, Yang, HP, Yang, P-C, Yu, K, Zanetti, KA, Zeleniuch-Jacquotte, A, Zheng, W, Zhou, B, Ziegler, RG, Perez-Jurado, LA, Caporaso, NE, Rothman, N, Tucker, M, Dean, MC, Yeager, M, and Chanock, SJ
- Abstract
To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.
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- 2016
19. Common germline polymorphisms associated with breast cancer-specific survival
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Pirie, A, Guo, Q, Kraft, P, Canisius, S, Eccles, DM, Rahman, N, Nevanlinna, H, Chen, C, Khan, S, Tyrer, J, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Lush, M, Dunning, AM, Shah, M, Czene, K, Darabi, H, Eriksson, M, Lambrechts, D, Weltens, C, Leunen, K, van Ongeval, C, Nordestgaard, BG, Nielsen, SF, Flyger, H, Rudolph, A, Seibold, P, Flesch-Janys, D, Blomqvist, C, Aittomaki, K, Fagerholm, R, Muranen, TA, Olsen, JE, Hallberg, E, Vachon, C, Knight, JA, Glendon, G, Mulligan, AM, Broeks, A, Cornelissen, S, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Hopper, JL, Tsimiklis, H, Apicella, C, Southey, MC, Cross, SS, Reed, MWR, Giles, GG, Milne, RL, McLean, C, Winqvist, R, Pylkas, K, Jukkola-Vuorinen, A, Grip, M, Hooning, MJ, Hollestelle, A, Martens, JWM, van den Ouweland, AMW, Marme, F, Schneeweiss, A, Yang, R, Burwinkel, B, Figueroa, J, Chanock, SJ, Lissowska, J, Sawyer, EJ, Tomlinson, I, Kerin, MJ, Miller, N, Brenner, H, Butterbach, K, Holleczek, B, Kataja, V, Kosma, V-M, Hartikainen, JM, Li, J, Brand, JS, Humphreys, K, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Radice, P, Peterlongo, P, Manoukian, S, Ficarazzi, F, Beckmann, MW, Hein, A, Ekici, AB, Balleine, R, Phillips, K-A, Benitez, J, Zamora, MP, Perez, JIA, Menendez, P, Jakubowska, A, Lubinski, J, Gronwald, J, Durda, K, Hamann, U, Kabisch, M, Ulmer, HU, Ruediger, T, Margolin, S, Kristensen, V, Nord, S, Evans, DG, Abraham, J, Earl, H, Poole, CJ, Hiller, L, Dunn, JA, Bowden, S, Campa, D, Diver, WR, Gapstur, SM, Gaudet, MM, Hankinson, S, Hoover, RN, Husing, A, Kaaks, R, Machiela, MJ, Willett, W, Barrdahl, M, Canzian, F, Chin, S-F, Caldas, C, Hunter, DJ, Lindstrom, S, Garcia-Closas, M, Couch, FJ, Chenevix-Trench, G, Mannermaa, A, Andrulis, IL, Hall, P, Chang-Claude, J, Easton, DF, Bojesen, SE, Cox, A, Fasching, PA, Pharoah, PDP, Schmidt, MK, Pirie, A, Guo, Q, Kraft, P, Canisius, S, Eccles, DM, Rahman, N, Nevanlinna, H, Chen, C, Khan, S, Tyrer, J, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Lush, M, Dunning, AM, Shah, M, Czene, K, Darabi, H, Eriksson, M, Lambrechts, D, Weltens, C, Leunen, K, van Ongeval, C, Nordestgaard, BG, Nielsen, SF, Flyger, H, Rudolph, A, Seibold, P, Flesch-Janys, D, Blomqvist, C, Aittomaki, K, Fagerholm, R, Muranen, TA, Olsen, JE, Hallberg, E, Vachon, C, Knight, JA, Glendon, G, Mulligan, AM, Broeks, A, Cornelissen, S, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Hopper, JL, Tsimiklis, H, Apicella, C, Southey, MC, Cross, SS, Reed, MWR, Giles, GG, Milne, RL, McLean, C, Winqvist, R, Pylkas, K, Jukkola-Vuorinen, A, Grip, M, Hooning, MJ, Hollestelle, A, Martens, JWM, van den Ouweland, AMW, Marme, F, Schneeweiss, A, Yang, R, Burwinkel, B, Figueroa, J, Chanock, SJ, Lissowska, J, Sawyer, EJ, Tomlinson, I, Kerin, MJ, Miller, N, Brenner, H, Butterbach, K, Holleczek, B, Kataja, V, Kosma, V-M, Hartikainen, JM, Li, J, Brand, JS, Humphreys, K, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Radice, P, Peterlongo, P, Manoukian, S, Ficarazzi, F, Beckmann, MW, Hein, A, Ekici, AB, Balleine, R, Phillips, K-A, Benitez, J, Zamora, MP, Perez, JIA, Menendez, P, Jakubowska, A, Lubinski, J, Gronwald, J, Durda, K, Hamann, U, Kabisch, M, Ulmer, HU, Ruediger, T, Margolin, S, Kristensen, V, Nord, S, Evans, DG, Abraham, J, Earl, H, Poole, CJ, Hiller, L, Dunn, JA, Bowden, S, Campa, D, Diver, WR, Gapstur, SM, Gaudet, MM, Hankinson, S, Hoover, RN, Husing, A, Kaaks, R, Machiela, MJ, Willett, W, Barrdahl, M, Canzian, F, Chin, S-F, Caldas, C, Hunter, DJ, Lindstrom, S, Garcia-Closas, M, Couch, FJ, Chenevix-Trench, G, Mannermaa, A, Andrulis, IL, Hall, P, Chang-Claude, J, Easton, DF, Bojesen, SE, Cox, A, Fasching, PA, Pharoah, PDP, and Schmidt, MK
- Abstract
INTRODUCTION: Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium. METHODS: A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect. RESULTS: Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease. CONCLUSIONS: Although no variants reached genome-wide significance (P <5 x 10(-8)), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the
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- 2015
20. A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer
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Al Olama, AA, Kote-Jarai, Z, Berndt, SI, Conti, DV, Schumacher, F, Han, Y, Benlloch, S, Hazelett, DJ, Wang, Z, Saunders, E, Leongamornlert, D, Lindstrom, S, Jugurnauth-Little, S, Dadaev, T, Tymrakiewicz, M, Stram, DO, Rand, K, Wan, P, Stram, A, Sheng, X, Pooler, LC, Park, K, Xia, L, Tyrer, J, Kolonel, LN, Le Marchand, L, Hoover, RN, Machiela, MJ, Yeager, M, Burdette, L, Chung, CC, Hutchinson, A, Yu, K, Goh, C, Ahmed, M, Govindasami, K, Guy, M, Tammela, TLJ, Auvinen, A, Wahlfors, T, Schleutker, J, Visakorpi, T, Leinonen, KA, Xu, J, Aly, M, Donovan, J, Travis, RC, Key, TJ, Siddiq, A, Canzian, F, Khaw, K-T, Takahashi, A, Kubo, M, Pharoah, P, Pashayan, N, Weischer, M, Nordestgaard, BG, Nielsen, SF, Klarskov, P, Roder, MA, Iversen, P, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Stanford, JL, Kolb, S, Holt, S, Knudsen, B, Coll, AH, Gapstur, SM, Diver, WR, Stevens, VL, Maier, C, Luedeke, M, Herkommer, K, Rinckleb, AE, Strom, SS, Pettaway, C, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Choklcalingam, AP, Cannon-Albright, L, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Park, J, Sellers, T, Lin, H-Y, Isaacs, WB, Partin, AW, Brenner, H, Dieffenbach, AK, Stegmaier, C, Chen, C, Giovannucci, EL, Ma, J, Stampfer, M, Penney, KL, Mucci, L, John, EM, Ingles, SA, Kittles, RA, Murphy, AB, Pandha, H, Michael, A, Kierzek, AM, Blot, W, Signorello, LB, Zheng, W, Albanes, D, Virtamo, J, Weinstein, S, Nemesure, B, Carpten, J, Leske, C, Wu, S-Y, Hennis, A, Kibel, AS, Rybicki, BA, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Zheng, SL, Batra, J, Clements, J, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Slavov, C, Kaneva, R, Mitev, V, Witte, JS, Casey, G, Gillanders, EM, Seminara, D, Riboli, E, Hamdy, FC, Coetzee, GA, Li, Q, Freedman, ML, Hunter, DJ, Muir, K, Gronberg, H, Nea, DE, Southey, M, Giles, GG, Severi, G, Cook, MB, Nakagawa, H, Wiklund, F, Kraft, P, Chanock, SJ, Henderson, BE, Easton, DF, Eeles, RA, Haiman, CA, Al Olama, AA, Kote-Jarai, Z, Berndt, SI, Conti, DV, Schumacher, F, Han, Y, Benlloch, S, Hazelett, DJ, Wang, Z, Saunders, E, Leongamornlert, D, Lindstrom, S, Jugurnauth-Little, S, Dadaev, T, Tymrakiewicz, M, Stram, DO, Rand, K, Wan, P, Stram, A, Sheng, X, Pooler, LC, Park, K, Xia, L, Tyrer, J, Kolonel, LN, Le Marchand, L, Hoover, RN, Machiela, MJ, Yeager, M, Burdette, L, Chung, CC, Hutchinson, A, Yu, K, Goh, C, Ahmed, M, Govindasami, K, Guy, M, Tammela, TLJ, Auvinen, A, Wahlfors, T, Schleutker, J, Visakorpi, T, Leinonen, KA, Xu, J, Aly, M, Donovan, J, Travis, RC, Key, TJ, Siddiq, A, Canzian, F, Khaw, K-T, Takahashi, A, Kubo, M, Pharoah, P, Pashayan, N, Weischer, M, Nordestgaard, BG, Nielsen, SF, Klarskov, P, Roder, MA, Iversen, P, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Stanford, JL, Kolb, S, Holt, S, Knudsen, B, Coll, AH, Gapstur, SM, Diver, WR, Stevens, VL, Maier, C, Luedeke, M, Herkommer, K, Rinckleb, AE, Strom, SS, Pettaway, C, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Choklcalingam, AP, Cannon-Albright, L, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Park, J, Sellers, T, Lin, H-Y, Isaacs, WB, Partin, AW, Brenner, H, Dieffenbach, AK, Stegmaier, C, Chen, C, Giovannucci, EL, Ma, J, Stampfer, M, Penney, KL, Mucci, L, John, EM, Ingles, SA, Kittles, RA, Murphy, AB, Pandha, H, Michael, A, Kierzek, AM, Blot, W, Signorello, LB, Zheng, W, Albanes, D, Virtamo, J, Weinstein, S, Nemesure, B, Carpten, J, Leske, C, Wu, S-Y, Hennis, A, Kibel, AS, Rybicki, BA, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Zheng, SL, Batra, J, Clements, J, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Slavov, C, Kaneva, R, Mitev, V, Witte, JS, Casey, G, Gillanders, EM, Seminara, D, Riboli, E, Hamdy, FC, Coetzee, GA, Li, Q, Freedman, ML, Hunter, DJ, Muir, K, Gronberg, H, Nea, DE, Southey, M, Giles, GG, Severi, G, Cook, MB, Nakagawa, H, Wiklund, F, Kraft, P, Chanock, SJ, Henderson, BE, Easton, DF, Eeles, RA, and Haiman, CA
- Abstract
Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.
- Published
- 2014
21. Associations Between Mosaic Loss of Sex Chromosomes and Incident Hospitalization for Atrial Fibrillation in the United Kingdom.
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Lim J, Hubbard AK, Blechter B, Shi J, Zhou W, Loftfield E, Machiela MJ, and Wong JYY
- Subjects
- Humans, Male, Female, United Kingdom epidemiology, Middle Aged, Incidence, Aged, Chromosomes, Human, Y genetics, Mendelian Randomization Analysis, Chromosomes, Human, X genetics, Risk Factors, Risk Assessment, Sex Factors, Chromosome Deletion, Genetic Predisposition to Disease, Atrial Fibrillation genetics, Atrial Fibrillation epidemiology, Hospitalization statistics & numerical data, Mosaicism
- Abstract
Background: Mosaic loss of chromosome Y (mLOY) in leukocytes of men reflects genomic instability from aging, smoking, and environmental exposures. A similar mosaic loss of chromosome X (mLOX) occurs among women. However, the associations between mLOY, mLOX, and risk of incident heart diseases are unclear., Methods and Results: We estimated associations between mLOY, mLOX, and risk of incident heart diseases requiring hospitalization, including atrial fibrillation, myocardial infarction, ischemic heart disease, cardiomyopathy, and heart failure. We analyzed 190 613 men and 224 853 women with genotyping data from the UK Biobank. Among these participants, there were 37 037 men with mLOY and 13 978 women with mLOX detected using the Mosaic Chromosomal Alterations caller. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% CIs of each incident heart disease in relation to mLOY in men and mLOX in women. Additionally, Mendelian randomization was conducted to estimate causal associations. Among men, detectable mLOY was associated with elevated risk of atrial fibrillation (HR, 1.06 [95% CI, 1.03-1.11]). The associations were apparent in both never smokers (HR, 1.07 [95% CI, 1.01-1.14]) and ever smokers (HR, 1.05 [95% CI, 1.01-1.11]) as well as men aged >60 and ≤60 years. Mendelian randomization analyses supported causal associations between mLOY and atrial fibrillation (HR
MR-PRESSO , 1.15 [95% CI, 1.13-1.18]). Among postmenopausal women, we found a suggestive inverse association between detectable mLOX and atrial fibrillation risk (HR, 0.90 [95% CI, 0.83-0.98]). However, associations with mLOY and mLOX were not found for other heart diseases., Conclusions: Our findings suggest that mLOY and mLOX reflect sex-specific biological processes or exposure profiles related to incident atrial fibrillation requiring hospitalization.- Published
- 2024
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22. Genetically determined telomere length in monoclonal gammopathy of undetermined significance, multiple myeloma risk and outcome.
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Giaccherini M, Clay-Gilmour AI, Liotti R, Macauda A, Gentiluomo M, Brown EE, Machiela MJ, Chanock SJ, Hildebrandt MAT, Norman AD, Manasanch E, Rajkumar SV, Hofmann JN, Berndt SI, Bhatti P, Giles GG, Ziv E, Kumar SK, Camp NJ, Cozen W, Slager SL, Canzian F, Gemignani F, Vachon CM, and Campa D
- Abstract
Competing Interests: Competing interests The authors declare no competing interests.
- Published
- 2024
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23. Stratifying Lung Adenocarcinoma Risk with Multi-ancestry Polygenic Risk Scores in East Asian Never-Smokers.
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Blechter B, Wang X, Shi J, Shiraishi K, Choi J, Matsuo K, Chen TY, Dai J, Hung RJ, Chen K, Shu XO, Kim YT, Choudhury PP, Williams J, Landi MT, Lin D, Zheng W, Yin Z, Zhou B, Wang J, Seow WJ, Song L, Chang IS, Hu W, Chien LH, Cai Q, Hong YC, Kim HN, Wu YL, Wong MP, Richardson BD, Li S, Zhang T, Breeze C, Wang Z, Bassig BA, Kim JH, Albanes D, Wong JY, Shin MH, Chung LP, Yang Y, An SJ, Zheng H, Yatabe Y, Zhang XC, Kim YC, Caporaso NE, Chang J, Man Ho JC, Kubo M, Daigo Y, Song M, Momozawa Y, Kamatani Y, Kobayashi M, Okubo K, Honda T, Hosgood HD, Kunitoh H, Watanabe SI, Miyagi Y, Nakayama H, Matsumoto S, Horinouchi H, Tsuboi M, Hamamoto R, Goto K, Ohe Y, Takahashi A, Goto A, Minamiya Y, Hara M, Nishida Y, Takeuchi K, Wakai K, Matsuda K, Murakami Y, Shimizu K, Suzuki H, Saito M, Ohtaki Y, Tanaka K, Wu T, Wei F, Dai H, Machiela MJ, Su J, Kim YH, Oh IJ, Fun Lee VH, Chang GC, Tsai YH, Che KY, Huang MS, Su WC, Chen YM, Seow A, Park JY, Kweon SS, Chen KC, Gao YT, Qian B, Wu C, Lu D, Liu J, Schwartz AG, Houlston R, Spitz MR, Gorlov IP, Wu X, Yang P, Lam S, Tardon A, Chen C, Bojesen SE, Johansson M, Risch A, Bickeböller H, Ji BT, Wichmann HE, Christiani DC, Rennert G, Arnold S, Brennan P, McKay J, Field JK, Davies MPA, Shete SS, Le Marchand L, Liu G, Andrew A, Kiemeney LA, Zienolddiny-Narui S, Grankvist K, Johansson M, Cox A, Taylor F, Yuan JM, Lazarus P, Schabath MB, Aldrich MC, Jeon HS, Jiang SS, Sung JS, Chen CH, Hsiao CF, Jung YJ, Guo H, Hu Z, Burdett L, Yeager M, Hutchinson A, Hicks B, Liu J, Zhu B, Berndt SI, Wu W, Wang J, Li Y, Choi JE, Park KH, Sung SW, Liu L, Kang CH, Wang WC, Xu J, Guan P, Tan W, Yu CJ, Yang G, Loon Sihoe AD, Chen Y, Choi YY, Kim JS, Yoon HI, Park IK, Xu P, He Q, Wang CL, Hung HH, Vermeulen RCH, Cheng I, Wu J, Lim WY, Tsai FY, Chan JKC, Li J, Chen H, Lin HC, Jin L, Liu J, Sawada N, Yamaji T, Wyatt K, Li SA, Ma H, Zhu M, Wang Z, Cheng S, Li X, Ren Y, Chao A, Iwasaki M, Zhu J, Jiang G, Fei K, Wu G, Chen CY, Chen CJ, Yang PC, Yu J, Stevens VL, Fraumeni JF, Chatterjee N, Gorlova OY, Amos CI, Shen H, Hsiung CA, Chanock SJ, Rothman N, Kohno T, Lan Q, and Zhang H
- Abstract
Polygenic risk scores (PRSs) are promising for risk stratification but have mainly been developed in European populations. This study developed single- and multi-ancestry PRSs for lung adenocarcinoma (LUAD) in East Asian (EAS) never-smokers using genome-wide association study summary statistics from EAS (8,002 cases; 20,782 controls) and European (2,058 cases; 5,575 controls) populations. A multi-ancestry PRS, developed using CT-SLEB, was strongly associated with LUAD risk (odds ratio=1.71, 95% confidence interval (CI):1.61,1.82), with an area under the receiver operating curve value of 0.640 (95% CI:0.629,0.653). Individuals in the highest 20% of the PRS had nearly four times the risk compared to the lowest 20%. Individuals in the 95
th percentile of the PRS had an estimated 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year LUAD risk at age 50 (0.42%) by age 41. Our study underscores the potential of multi-ancestry PRS approaches to enhance LUAD risk stratification in EAS never-smokers.- Published
- 2024
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24. Social, Behavioral, and Clinical Risk Factors Are Associated with Clonal Hematopoiesis.
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Young CD, Hubbard AK, Saint-Maurice PF, Chan ICC, Cao Y, Tran D, Bolton KL, Chanock SJ, Matthews CE, Moore SC, Loftfield E, and Machiela MJ
- Subjects
- Humans, Male, Female, Risk Factors, Cross-Sectional Studies, Middle Aged, Aged, Alcohol Drinking adverse effects, Alcohol Drinking epidemiology, Adult, Smoking adverse effects, Smoking epidemiology, Life Style, Clonal Hematopoiesis genetics
- Abstract
Background: Risk factors including smoking, alcohol intake, physical activity (PA), and sleep patterns have been associated with cancer risk. Clonal hematopoiesis (CH), including mosaic chromosomal alterations and clonal hematopoiesis of indeterminate potential, is linked to increased hematopoietic cancer risk and could be used as common preclinical intermediates for the better understanding of associations of risk factors with rare hematologic malignancies., Methods: We analyzed cross-sectional data from 478,513 UK Biobank participants without hematologic malignancies using multivariable-adjusted analyses to assess the associations between lifestyle factors and CH types., Results: Smoking was reinforced as a potent modifiable risk factor for multiple CH types, with dose-dependent relationships persisting after cessation. Males in socially deprived areas of England had a lower risk of mosaic loss of chromosome Y (mLOY), females with moderate/high alcohol consumption (2-3 drinks/day) had increased mosaic loss of the X chromosome risk [OR = 1.17; 95% confidence interval (CI), 1.09-1.25; P = 8.31 × 10-6] compared with light drinkers, active males (moderate-high PA) had elevated risks of mLOY (PA category 3: OR = 1.06; 95% CI, 1.03-1.08; P = 7.57 × 10-6), and men with high body mass index (≥40) had reduced risk of mLOY (OR = 0.57; 95% CI, 0.51-0.65; P = 3.30 × 10-20). Sensitivity analyses with body mass index adjustment attenuated the effect in the mLOY-PA associations (IPAQ2: OR = 1.03; 95% CI, 1.00-1.06; P = 2.13 × 10-2 and IPAQ3: OR = 1.03; 95% CI, 1.01-1.06; P = 7.77 × 10-3)., Conclusions: Our study reveals associations between social deprivation, smoking, and alcohol consumption and CH risk, suggesting that these exposures could contribute to common types of CH and potentially rare hematologic cancers., Impact: This study underscores the impact of lifestyle factors on CH frequency, emphasizing social, behavioral, and clinical influences and the importance of sociobehavioral contexts when investigating CH risk factors., (©2024 American Association for Cancer Research.)
- Published
- 2024
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25. Transcriptome- and proteome-wide association studies identify genes associated with renal cell carcinoma.
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Dutta D, Guo X, Winter TD, Jahagirdar O, Ha E, Susztak K, Machiela MJ, Chanock SJ, and Purdue MP
- Subjects
- Humans, Genetic Predisposition to Disease, Gene Expression Regulation, Neoplastic, Polymorphism, Single Nucleotide, Gene Expression Profiling, Carcinoma, Renal Cell genetics, Genome-Wide Association Study, Kidney Neoplasms genetics, Transcriptome, Proteome genetics
- Abstract
We performed a series of integrative analyses including transcriptome-wide association studies (TWASs) and proteome-wide association studies (PWASs) of renal cell carcinoma (RCC) to nominate and prioritize molecular targets for laboratory investigation. On the basis of a genome-wide association study (GWAS) of 29,020 affected individuals and 835,670 control individuals and prediction models trained in transcriptomic reference models, our TWAS across four kidney transcriptomes (GTEx kidney cortex, kidney tubules, TCGA-KIRC [The Cancer Genome Atlas kidney renal clear-cell carcinoma], and TCGA-KIRP [TCGA kidney renal papillary cell carcinoma]) identified 38 gene associations (false-discovery rate <5%) in at least two of four transcriptomic panels and identified 12 genes that were independent of GWAS susceptibility regions. Analyses combining TWAS associations across 48 tissues from GTEx identified associations that were replicable in tumor transcriptomes for 23 additional genes. Analyses by the two major histologic types (clear-cell RCC and papillary RCC) revealed subtype-specific associations, although at least three gene associations were common to both subtypes. PWAS identified 13 associated proteins, all mapping to GWAS-significant loci. TWAS-identified genes were enriched for active enhancer or promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines. Using gene expression correlation, common cancers (breast and prostate) and RCC risk factors (e.g., hypertension and BMI) display genetic contributions shared with RCC. Our work identifies potential molecular targets for RCC susceptibility for downstream functional investigation., Competing Interests: Declaration of interests K.S. receives research support from Gilead, GSK, Novo Nordisk, Bayer, Regeneron, Calico, and Novartis. K.S. is on the advisory board of Jnana Therapeutics and has received consulting fees from Pfizer and Jnana. Declaration of interests for the Renal Cancer Genetics Consortium, which contributed toward acquisition of the individual-level data, can be referred to as a part of Purdue et al.(10) The other named authors in the manuscript have no competing interests to declare. It is to be noted that the individual-level data contributed by The Renal Cancer Genetics Consortium is now publicly available, and the current analyses were conducted with summary-level data only., (Published by Elsevier Inc.)
- Published
- 2024
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26. Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction.
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Hoffmann TJ, Graff RE, Madduri RK, Rodriguez AA, Cario CL, Feng K, Jiang Y, Wang A, Klein RJ, Pierce BL, Eggener S, Tong L, Blot W, Long J, Goss LB, Darst BF, Rebbeck T, Lachance J, Andrews C, Adebiyi AO, Adusei B, Aisuodionoe-Shadrach OI, Fernandez PW, Jalloh M, Janivara R, Chen WC, Mensah JE, Agalliu I, Berndt SI, Shelley JP, Schaffer K, Machiela MJ, Freedman ND, Huang WY, Li SA, Goodman PJ, Till C, Thompson I, Lilja H, Ranatunga DK, Presti J, Van Den Eeden SK, Chanock SJ, Mosley JD, Conti DV, Haiman CA, Justice AC, Kachuri L, and Witte JS
- Abstract
We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our genome-wide polygenic risk scores ranged from 11.6%-16.6% in European ancestry, 5.5%-9.5% in African ancestry, 13.5%-18.2% in Hispanic/Latino, and 8.6%-15.3% in Asian ancestry, and decreased with increasing age. Mid-life genetically-adjusted PSA levels were more strongly associated with overall and aggressive prostate cancer than unadjusted PSA. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, offering potential to personalize prostate cancer screening.
- Published
- 2024
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27. Transcriptome-wide association analysis identifies candidate susceptibility genes for prostate-specific antigen levels in men without prostate cancer.
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Chen DM, Dong R, Kachuri L, Hoffmann TJ, Jiang Y, Berndt SI, Shelley JP, Schaffer KR, Machiela MJ, Freedman ND, Huang WY, Li SA, Lilja H, Justice AC, Madduri RK, Rodriguez AA, Van Den Eeden SK, Chanock SJ, Haiman CA, Conti DV, Klein RJ, Mosley JD, Witte JS, and Graff RE
- Subjects
- Humans, Male, Gene Expression Profiling, Polymorphism, Single Nucleotide, Prostate-Specific Antigen blood, Genome-Wide Association Study, Prostatic Neoplasms genetics, Prostatic Neoplasms blood, Genetic Predisposition to Disease, Transcriptome
- Abstract
Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10 × 10
-6 ) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61 × 10-6 ) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25 × 10-6 ) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in a TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a GWAS. Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability of >0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels., Competing Interests: Declaration of interests J.S.W. is a non-employee and cofounder of Avail Bio. H.L. is named on a patent for assays to measure intact PSA and a patent for a statistical method to detect prostate cancer commercialized by OPKO Health (4KScore). H.L. receives royalties from sales of the assay and has stock in OPKO Health. H.L. serves on the Scientific Advisory Board for Fujirebio Diagnostics Inc and owns stock in Diaprost AB and Acousort AB. R.E.G. consults for Hunton Andrews Kurth LLC on subject matter unrelated to this study., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)- Published
- 2024
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28. Genetic drivers and cellular selection of female mosaic X chromosome loss.
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Liu A, Genovese G, Zhao Y, Pirinen M, Zekavat SM, Kentistou KA, Yang Z, Yu K, Vlasschaert C, Liu X, Brown DW, Hudjashov G, Gorman BR, Dennis J, Zhou W, Momozawa Y, Pyarajan S, Tuzov V, Pajuste FD, Aavikko M, Sipilä TP, Ghazal A, Huang WY, Freedman ND, Song L, Gardner EJ, Sankaran VG, Palotie A, Ollila HM, Tukiainen T, Chanock SJ, Mägi R, Natarajan P, Daly MJ, Bick A, McCarroll SA, Terao C, Loh PR, Ganna A, Perry JRB, and Machiela MJ
- Subjects
- Adult, Female, Humans, Male, Middle Aged, Alleles, Autoimmune Diseases genetics, Biological Specimen Banks, Chromosome Segregation genetics, Chromosomes, Human, Y genetics, Exome genetics, F-Box Proteins genetics, Genetic Predisposition to Disease genetics, Germ-Line Mutation, Leukemia genetics, Models, Genetic, Multifactorial Inheritance genetics, Mutation, Missense genetics, Aneuploidy, Chromosomes, Human, X genetics, Clone Cells metabolism, Clone Cells pathology, Leukocytes metabolism, Mosaicism
- Abstract
Mosaic loss of the X chromosome (mLOX) is the most common clonal somatic alteration in leukocytes of female individuals
1,2 , but little is known about its genetic determinants or phenotypic consequences. Here, to address this, we used data from 883,574 female participants across 8 biobanks; 12% of participants exhibited detectable mLOX in approximately 2% of leukocytes. Female participants with mLOX had an increased risk of myeloid and lymphoid leukaemias. Genetic analyses identified 56 common variants associated with mLOX, implicating genes with roles in chromosomal missegregation, cancer predisposition and autoimmune diseases. Exome-sequence analyses identified rare missense variants in FBXO10 that confer a twofold increased risk of mLOX. Only a small fraction of associations was shared with mosaic Y chromosome loss, suggesting that distinct biological processes drive formation and clonal expansion of sex chromosome missegregation. Allelic shift analyses identified X chromosome alleles that are preferentially retained in mLOX, demonstrating variation at many loci under cellular selection. A polygenic score including 44 allelic shift loci correctly inferred the retained X chromosomes in 80.7% of mLOX cases in the top decile. Our results support a model in which germline variants predispose female individuals to acquiring mLOX, with the allelic content of the X chromosome possibly shaping the magnitude of clonal expansion., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)- Published
- 2024
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29. Genomic characterization of cervical lymph node metastases in papillary thyroid carcinoma following the Chornobyl accident.
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Morton LM, Lee OW, Karyadi DM, Bogdanova TI, Stewart C, Hartley SW, Breeze CE, Schonfeld SJ, Cahoon EK, Drozdovitch V, Masiuk S, Chepurny M, Zurnadzhy LY, Dai J, Krznaric M, Yeager M, Hutchinson A, Hicks BD, Dagnall CL, Steinberg MK, Jones K, Jain K, Jordan B, Machiela MJ, Dawson ET, Vij V, Gastier-Foster JM, Bowen J, Mabuchi K, Hatch M, Berrington de Gonzalez A, Getz G, Tronko MD, Thomas GA, and Chanock SJ
- Subjects
- Humans, Male, Adult, Female, Adolescent, Proto-Oncogene Proteins B-raf genetics, Young Adult, Lymph Nodes pathology, Proto-Oncogene Proteins c-ret genetics, Child, Genomics, Middle Aged, Homeodomain Proteins genetics, Homeodomain Proteins metabolism, Gene Expression Profiling, MicroRNAs genetics, MicroRNAs metabolism, Neoplasms, Radiation-Induced genetics, Neoplasms, Radiation-Induced pathology, Neck pathology, Gene Expression Regulation, Neoplastic, Thyroid Cancer, Papillary genetics, Thyroid Cancer, Papillary pathology, Chernobyl Nuclear Accident, Lymphatic Metastasis genetics, Thyroid Neoplasms genetics, Thyroid Neoplasms pathology, Mutation, Iodine Radioisotopes
- Abstract
Childhood radioactive iodine exposure from the Chornobyl accident increased papillary thyroid carcinoma (PTC) risk. While cervical lymph node metastases (cLNM) are well-recognized in pediatric PTC, the PTC metastatic process and potential radiation association are poorly understood. Here, we analyze cLNM occurrence among 428 PTC with genomic landscape analyses and known drivers (
131 I-exposed = 349, unexposed = 79; mean age = 27.9 years). We show that cLNM are more frequent in PTC with fusion (55%) versus mutation (30%) drivers, although the proportion varies by specific driver gene (RET-fusion = 71%, BRAF-mutation = 38%, RAS-mutation = 5%). cLNM frequency is not associated with other characteristics, including radiation dose. cLNM molecular profiling (N = 47) demonstrates 100% driver concordance with matched primary PTCs and highly concordant mutational spectra. Transcriptome analysis reveals 17 differentially expressed genes, particularly in the HOXC cluster and BRINP3; the strongest differentially expressed microRNA also is near HOXC10. Our findings underscore the critical role of driver alterations and provide promising candidates for elucidating the biological underpinnings of PTC cLNM., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)- Published
- 2024
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30. Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions.
- Author
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Purdue MP, Dutta D, Machiela MJ, Gorman BR, Winter T, Okuhara D, Cleland S, Ferreiro-Iglesias A, Scheet P, Liu A, Wu C, Antwi SO, Larkin J, Zequi SC, Sun M, Hikino K, Hajiran A, Lawson KA, Cárcano F, Blanchet O, Shuch B, Nepple KG, Margue G, Sundi D, Diver WR, Folgueira MAAK, van Bokhoven A, Neffa F, Brown KM, Hofmann JN, Rhee J, Yeager M, Cole NR, Hicks BD, Manning MR, Hutchinson AA, Rothman N, Huang WY, Linehan WM, Lori A, Ferragu M, Zidane-Marinnes M, Serrano SV, Magnabosco WJ, Vilas A, Decia R, Carusso F, Graham LS, Anderson K, Bilen MA, Arciero C, Pellegrin I, Ricard S, Scelo G, Banks RE, Vasudev NS, Soomro N, Stewart GD, Adeyoju A, Bromage S, Hrouda D, Gibbons N, Patel P, Sullivan M, Protheroe A, Nugent FI, Fournier MJ, Zhang X, Martin LJ, Komisarenko M, Eisen T, Cunningham SA, Connolly DC, Uzzo RG, Zaridze D, Mukeria A, Holcatova I, Hornakova A, Foretova L, Janout V, Mates D, Jinga V, Rascu S, Mijuskovic M, Savic S, Milosavljevic S, Gaborieau V, Abedi-Ardekani B, McKay J, Johansson M, Phouthavongsy L, Hayman L, Li J, Lungu I, Bezerra SM, Souza AG, Sares CTG, Reis RB, Gallucci FP, Cordeiro MD, Pomerantz M, Lee GM, Freedman ML, Jeong A, Greenberg SE, Sanchez A, Thompson RH, Sharma V, Thiel DD, Ball CT, Abreu D, Lam ET, Nahas WC, Master VA, Patel AV, Bernhard JC, Freedman ND, Bigot P, Reis RM, Colli LM, Finelli A, Manley BJ, Terao C, Choueiri TK, Carraro DM, Houlston R, Eckel-Passow JE, Abbosh PH, Ganna A, Brennan P, Gu J, and Chanock SJ
- Subjects
- Humans, Case-Control Studies, Von Hippel-Lindau Tumor Suppressor Protein genetics, White People genetics, Black People, Carcinoma, Renal Cell genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Kidney Neoplasms genetics, Polymorphism, Single Nucleotide, Quantitative Trait Loci
- Abstract
Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.72, 95% confidence interval 2.23-3.30). In cis-expression quantitative trait locus analyses, 48 variants from 34 regions point toward 83 candidate genes. Enrichment of hypoxia-inducible factor-binding sites underscores the importance of hypoxia-related mechanisms in kidney cancer. Our results advance understanding of the genetic architecture of kidney cancer, provide clues for functional investigation and enable generation of a validated polygenic risk score with an estimated area under the curve of 0.65 (0.74 including risk factors) among European ancestry individuals., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
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- 2024
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31. Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood.
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Jakubek YA, Ma X, Stilp AM, Yu F, Bacon J, Wong JW, Aguet F, Ardlie K, Arnett D, Barnes K, Bis JC, Blackwell T, Becker LC, Boerwinkle E, Bowler RP, Budoff MJ, Carson AP, Chen J, Cho MH, Coresh J, Cox N, de Vries PS, DeMeo DL, Fardo DW, Fornage M, Guo X, Hall ME, Heard-Costa N, Hidalgo B, Irvin MR, Johnson AD, Kenny EE, Levy D, Li Y, Lima JA, Liu Y, Loos RJF, Machiela MJ, Mathias RA, Mitchell BD, Murabito J, Mychaleckyj JC, North K, Orchard P, Parker SC, Pershad Y, Peyser PA, Pratte KA, Psaty BM, Raffield LM, Redline S, Rich SS, Rotter JI, Shah SJ, Smith JA, Smith AP, Smith A, Taub M, Tiwari HK, Tracy R, Tuftin B, Bick AG, Sankaran VG, Reiner AP, Scheet P, and Auer PL
- Abstract
Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes ( CFHR1 and LRP6 ) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.
- Published
- 2024
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32. ArCH: improving the performance of clonal hematopoiesis variant calling and interpretation.
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Chan ICC, Panchot A, Schmidt E, McNulty S, Wiley BJ, Liu J, Turner K, Moukarzel L, Wong WSW, Tran D, Beeler JS, Batchi-Bouyou AL, Machiela MJ, Karyadi DM, Krajacich BJ, Zhao J, Kruglyak S, Lajoie B, Levy S, Patel M, Kantoff PW, Mason CE, Link DC, Druley TE, Stopsack KH, and Bolton KL
- Subjects
- Adult, Humans, High-Throughput Nucleotide Sequencing, Software, Reproducibility of Results, Mutation, Hematopoiesis genetics, Clonal Hematopoiesis, Hematologic Neoplasms
- Abstract
Motivation: The acquisition of somatic mutations in hematopoietic stem and progenitor stem cells with resultant clonal expansion, termed clonal hematopoiesis (CH), is associated with increased risk of hematologic malignancies and other adverse outcomes. CH is generally present at low allelic fractions, but clonal expansion and acquisition of additional mutations leads to hematologic cancers in a small proportion of individuals. With high depth and high sensitivity sequencing, CH can be detected in most adults and its clonal trajectory mapped over time. However, accurate CH variant calling is challenging due to the difficulty in distinguishing low frequency CH mutations from sequencing artifacts. The lack of well-validated bioinformatic pipelines for CH calling may contribute to lack of reproducibility in studies of CH., Results: Here, we developed ArCH, an Artifact filtering Clonal Hematopoiesis variant calling pipeline for detecting single nucleotide variants and short insertions/deletions by combining the output of four variant calling tools and filtering based on variant characteristics and sequencing error rate estimation. ArCH is an end-to-end cloud-based pipeline optimized to accept a variety of inputs with customizable parameters adaptable to multiple sequencing technologies, research questions, and datasets. Using deep targeted sequencing data generated from six acute myeloid leukemia patient tumor: normal dilutions, 31 blood samples with orthogonal validation, and 26 blood samples with technical replicates, we show that ArCH improves the sensitivity and positive predictive value of CH variant detection at low allele frequencies compared to standard application of commonly used variant calling approaches., Availability and Implementation: The code for this workflow is available at: https://github.com/kbolton-lab/ArCH., (© The Author(s) 2024. Published by Oxford University Press.)
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- 2024
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33. Phenotypic and genetically predicted leucocyte telomere length and lung cancer risk in the prospective UK Biobank.
- Author
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Wong JY, Blechter B, Hubbard AK, Machiela MJ, Shi J, Gadalla SM, Hu W, Rahman ML, Rothman N, and Lan Q
- Subjects
- Humans, Biological Specimen Banks, Prospective Studies, UK Biobank, Telomere Homeostasis genetics, Leukocytes, Telomere genetics, Lung Neoplasms epidemiology, Lung Neoplasms genetics, Adenocarcinoma
- Abstract
We investigated phenotypic leucocyte telomere length (LTL), genetically predicted LTL (gTL), and lung cancer risk among 371 890 participants, including 2829 incident cases, from the UK Biobank. Using multivariable Cox regression, we found dose-response relationships between longer phenotypic LTL (p-trend
continuous =2.6×10-5 ), longer gTL predicted using a polygenic score with 130 genetic instruments (p-trendcontinuous =4.2×10-10 ), and overall lung cancer risk, particularly for adenocarcinoma. The associations were prominent among never smokers. Mendelian Randomization analyses supported causal associations between longer telomere length and lung cancer (HRper 1 SD gTL =1.87, 95% CI: 1.49 to 2.36, p=4.0×10-7 ), particularly adenocarcinoma (HRper 1 SD gTL =2.45, 95%CI: 1.69 to 3.57, p=6.5×10-6 )., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)- Published
- 2024
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34. Genetic analyses identify evidence for a causal relationship between Ewing sarcoma and hernias.
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Yang T, Mills LJ, Hubbard AK, Cao R, Raduski A, Machiela MJ, and Spector LG
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- Humans, Genome-Wide Association Study, Sarcoma, Ewing epidemiology, Hernia, Inguinal epidemiology
- Abstract
Knowledge of Ewing sarcoma (EWS) risk factors is exceedingly limited; however, multiple small, independent studies have suggested a possible connection between hernia and EWS. By leveraging hernia summary statistics from the UK Biobank and a recently published genome-wide association study of EWS (733 EWS cases and 1,346 controls), we conducted a genetic investigation of the relationship of 5 hernia types (diaphragmatic, inguinal, umbilical, femoral, and ventral) and EWS. We discovered a positive causal relationship between inguinal hernia and EWS (OR 1.27, 95% confidence interval [CI] 1.01-1.59, and p = 0.041) through Mendelian randomization analysis. Further analyses suggested shared pathways through three genes: HMGA2, LOX, and FBXW7. Diaphragmatic hernia showed a stronger causal relationship with EWS among all of the hernia types (OR 2.26, 95% CI 1.30-3.95, p = 0.004), but no statistically significant local correlation pattern was observed. No evidence of a causal or genetic relationship was observed between EWS and the other three hernia types, including umbilical hernia, despite a previous report indicating an OR as high as 3.3. The finding of our genetic analysis provided additional support to the hypothesis that EWS and hernias may share a common origin., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Inc.)
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- 2024
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35. FORGEdb: a tool for identifying candidate functional variants and uncovering target genes and mechanisms for complex diseases.
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Breeze CE, Haugen E, Gutierrez-Arcelus M, Yao X, Teschendorff A, Beck S, Dunham I, Stamatoyannopoulos J, Franceschini N, Machiela MJ, and Berndt SI
- Subjects
- Protein Binding, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Regulatory Sequences, Nucleic Acid
- Abstract
The majority of disease-associated variants identified through genome-wide association studies are located outside of protein-coding regions. Prioritizing candidate regulatory variants and gene targets to identify potential biological mechanisms for further functional experiments can be challenging. To address this challenge, we developed FORGEdb ( https://forgedb.cancer.gov/ ; https://forge2.altiusinstitute.org/files/forgedb.html ; and https://doi.org/10.5281/zenodo.10067458 ), a standalone and web-based tool that integrates multiple datasets, delivering information on associated regulatory elements, transcription factor binding sites, and target genes for over 37 million variants. FORGEdb scores provide researchers with a quantitative assessment of the relative importance of each variant for targeted functional experiments., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
- Published
- 2024
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36. JAK2 V617F mutation and associated chromosomal alterations in primary and secondary myelofibrosis and post-HCT outcomes.
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Rafati M, Brown DW, Zhou W, Jones K, Luo W, St Martin A, Wang Y, He M, Spellman SR, Wang T, Deeg HJ, Gupta V, Lee SJ, Bolon YT, Chanock SJ, Machiela MJ, Saber W, and Gadalla SM
- Subjects
- Humans, Prognosis, Mutation, Disease Progression, Chromosome Aberrations, Recurrence, Janus Kinase 2 genetics, Primary Myelofibrosis diagnosis, Primary Myelofibrosis genetics, Primary Myelofibrosis therapy
- Abstract
JAK2 V617F is the most common driver mutation in primary or secondary myelofibrosis for which allogeneic hematopoietic cell transplantation (HCT) is the only curative treatment. Knowledge of the prognostic utility of JAK2 alterations in the HCT setting is limited. We identified all patients with MF who received HCT between 2000 and 2016 and had a pre-HCT blood sample (N = 973) available at the Center of International Blood and Marrow Transplant Research biorepository. PacBio sequencing and single nucleotide polymorphism-array genotyping were used to identify JAK2V617F mutation and associated mosaic chromosomal alterations (mCAs), respectively. Cox proportional hazard models were used for HCT outcome analyses. Genomic testing was complete for 924 patients with MF (634 primary MF [PMF], 135 postpolycythemia vera [PPV-MF], and 155 postessential thrombocytopenia [PET-MF]). JAK2V617F affected 562 patients (57.6% of PMF, 97% of PPV-MF, and 42.6% of PET-MF). Almost all patients with mCAs involving the JAK2 region (97.9%) were JAK2V617-positive. In PMF, JAK2V617F mutation status, allele burden, or identified mCAs were not associated with disease progression/relapse, nonrelapse mortality (NRM), or overall survival. Almost all PPV-MF were JAK2V617F-positive (97%), with no association between HCT outcomes and mutation allele burden or mCAs. In PET-MF, JAK2V617F high mutation allele burden (≥60%) was associated with excess risk of NRM, restricted to transplants received in the era of JAK inhibitors (2013-2016; hazard ratio = 7.65; 95% confidence interval = 2.10-27.82; P = .002). However, allele burden was not associated with post-HCT disease progression/relapse or survival. Our findings support the concept that HCT can mitigate the known negative effect of JAK2V617F in patients with MF, particularly for PMF and PPV-MF., (Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution.)
- Published
- 2023
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37. Mosaic chromosomal alterations in peripheral blood leukocytes of children in sub-Saharan Africa.
- Author
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Zhou W, Fischer A, Ogwang MD, Luo W, Kerchan P, Reynolds SJ, Tenge CN, Were PA, Kuremu RT, Wekesa WN, Masalu N, Kawira E, Kinyera T, Otim I, Legason ID, Nabalende H, Ayers LW, Bhatia K, Goedert JJ, Gouveia MH, Cole N, Hicks B, Jones K, Hummel M, Schlesner M, Chagaluka G, Mutalima N, Borgstein E, Liomba GN, Kamiza S, Mkandawire N, Mitambo C, Molyneux EM, Newton R, Glaser S, Kretzmer H, Manning M, Hutchinson A, Hsing AW, Tettey Y, Adjei AA, Chanock SJ, Siebert R, Yeager M, Prokunina-Olsson L, Machiela MJ, and Mbulaiteye SM
- Subjects
- Male, Child, Humans, Ghana, Chromosome Aberrations, Leukocytes pathology, Immunoglobulins genetics, Translocation, Genetic, Burkitt Lymphoma genetics, Burkitt Lymphoma pathology
- Abstract
In high-income countries, mosaic chromosomal alterations in peripheral blood leukocytes are associated with an elevated risk of adverse health outcomes, including hematologic malignancies. We investigate mosaic chromosomal alterations in sub-Saharan Africa among 931 children with Burkitt lymphoma, an aggressive lymphoma commonly characterized by immunoglobulin-MYC chromosomal rearrangements, 3822 Burkitt lymphoma-free children, and 674 cancer-free men from Ghana. We find autosomal and X chromosome mosaic chromosomal alterations in 3.4% and 1.7% of Burkitt lymphoma-free children, and 8.4% and 3.7% of children with Burkitt lymphoma (P-values = 5.7×10
-11 and 3.74×10-2 , respectively). Autosomal mosaic chromosomal alterations are detected in 14.0% of Ghanaian men and increase with age. Mosaic chromosomal alterations in Burkitt lymphoma cases include gains on chromosomes 1q and 8, the latter spanning MYC, while mosaic chromosomal alterations in Burkitt lymphoma-free children include copy-neutral loss of heterozygosity on chromosomes 10, 14, and 16. Our results highlight mosaic chromosomal alterations in sub-Saharan African populations as a promising area of research., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)- Published
- 2023
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38. Glyphosate Use and Mosaic Loss of Chromosome Y among Male Farmers in the Agricultural Health Study.
- Author
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Chang VC, Zhou W, Berndt SI, Andreotti G, Yeager M, Parks CG, Sandler DP, Rothman N, Beane Freeman LE, Machiela MJ, and Hofmann JN
- Subjects
- Animals, Humans, Male, Mosaicism, Agriculture, Glyphosate, Chromosomes, Human, Y, Farmers
- Abstract
Background: Glyphosate is the most commonly used herbicide worldwide and has been implicated in the development of certain hematologic cancers. Although mechanistic studies in human cells and animals support the genotoxic effects of glyphosate, evidence in human populations is scarce., Objectives: We evaluated the association between lifetime occupational glyphosate use and mosaic loss of chromosome Y (mLOY) as a marker of genotoxicity among male farmers., Methods: We analyzed blood-derived DNA from 1,606 farmers ≥ 50 years of age in the Biomarkers of Exposure and Effect in Agriculture study, a subcohort of the Agricultural Health Study. mLOY was detected using genotyping array intensity data in the pseudoautosomal region of the sex chromosomes. Cumulative lifetime glyphosate use was assessed using self-reported pesticide exposure histories. Using multivariable logistic regression, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between glyphosate use and any detectable mLOY (overall mLOY) or mLOY affecting ≥ 10 % of cells (expanded mLOY)., Results: Overall, mLOY was detected in 21.4% of farmers, and 9.8% of all farmers had expanded mLOY. Increasing total lifetime days of glyphosate use was associated with expanded mLOY [highest vs. lowest quartile; OR = 1.75 (95% CI: 1.00, 3.07), p trend = 0.03 ] but not with overall mLOY; the associations with expanded mLOY were most apparent among older ( ≥ 70 years of age) men [ OR = 2.30 (95% CI: 1.13, 4.67), p trend = 0.01 ], never smokers [ OR = 2.32 (95% CI: 1.04, 5.21), p trend = 0.04 ], and nonobese men [ OR = 2.04 (95% CI: 0.99, 4.19), p trend = 0.03 ]. Similar patterns of associations were observed for intensity-weighted lifetime days of glyphosate use., Discussion: High lifetime glyphosate use could be associated with mLOY affecting a larger fraction of cells, suggesting glyphosate could confer genotoxic or selective effects relevant for clonal expansion. As the first study to investigate this association, our findings contribute novel evidence regarding the carcinogenic potential of glyphosate and require replication in future studies. https://doi.org/10.1289/EHP12834.
- Published
- 2023
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39. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.
- Author
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Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, Darst BF, Sheng X, Xu Y, Chou AJ, Benlloch S, Dadaev T, Brook MN, Plym A, Sahimi A, Hoffman TJ, Takahashi A, Matsuda K, Momozawa Y, Fujita M, Laisk T, Figuerêdo J, Muir K, Ito S, Liu X, Uchio Y, Kubo M, Kamatani Y, Lophatananon A, Wan P, Andrews C, Lori A, Choudhury PP, Schleutker J, Tammela TLJ, Sipeky C, Auvinen A, Giles GG, Southey MC, MacInnis RJ, Cybulski C, Wokolorczyk D, Lubinski J, Rentsch CT, Cho K, Mcmahon BH, Neal DE, Donovan JL, Hamdy FC, Martin RM, Nordestgaard BG, Nielsen SF, Weischer M, Bojesen SE, Røder A, Stroomberg HV, Batra J, Chambers S, Horvath L, Clements JA, Tilly 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 HY, Albanes D, Weinstein S, Cook MB, Mucci LA, Giovannucci E, Lindstrom S, Kraft P, Hunter DJ, Penney KL, Turman C, Tangen CM, Goodman PJ, Thompson IM Jr, Hamilton RJ, Fleshner NE, Finelli A, Parent MÉ, Stanford JL, Ostrander EA, Koutros S, Beane Freeman LE, Stampfer M, Wolk A, Håkansson N, Andriole GL, Hoover RN, Machiela MJ, Sørensen KD, Borre M, Blot WJ, Zheng W, Yeboah ED, Mensah JE, Lu YJ, Zhang HW, Feng N, Mao X, Wu Y, Zhao SC, Sun Z, Thibodeau SN, McDonnell SK, Schaid DJ, West CML, 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 KT, Ingles SA, Stern MC, Vega A, Gómez-Caamaño A, Fachal L, Rosenstein BS, Kerns SL, Ostrer H, Teixeira MR, Paulo P, Brandão A, Watya S, Lubwama A, Bensen JT, Butler EN, Mohler JL, Taylor JA, Kogevinas M, Dierssen-Sotos T, Castaño-Vinyals G, Cannon-Albright L, Teerlink CC, Huff CD, Pilie P, Yu Y, Bohlender RJ, Gu J, Strom SS, Multigner L, Blanchet P, Brureau L, Kaneva R, Slavov C, Mitev V, Leach RJ, Brenner H, Chen X, Holleczek B, Schöttker B, 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 SH, Newcomb LF, Lin DW, Fowke JH, Neslund-Dudas CM, Rybicki BA, Gamulin M, Lessel D, Kulis T, Usmani N, Abraham A, 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 J, Petrovics G, Casey G, Wang Y, Tettey Y, Lachance J, Tang W, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Yamoah K, Govindasami K, Chokkalingam AP, Keaton JM, Hellwege JN, Clark PE, Jalloh M, Gueye SM, Niang L, Ogunbiyi O, Shittu O, Amodu O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Diop H, Gundell SM, Roobol MJ, Jenster G, van Schaik RHN, Hu JJ, Sanderson M, Kachuri L, Varma R, McKean-Cowdin R, Torres M, Preuss MH, Loos RJF, Zawistowski M, Zöllner S, Lu Z, Van Den Eeden SK, Easton DF, Ambs S, Edwards TL, Mägi R, Rebbeck TR, Fritsche L, Chanock SJ, Berndt SI, Wiklund F, Nakagawa H, Witte JS, Gaziano JM, Justice AC, Mancuso N, Terao C, Eeles RA, Kote-Jarai Z, Madduri RK, Conti DV, and Haiman CA
- Subjects
- Humans, Male, Black People genetics, Genome-Wide Association Study, Hispanic or Latino genetics, Polymorphism, Single Nucleotide, Risk Factors, White People genetics, Asian People genetics, Genetic Predisposition to Disease, Prostatic Neoplasms genetics
- Abstract
The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)
- Published
- 2023
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40. Serum biomarkers are altered in UK Biobank participants with mosaic chromosomal alterations.
- Author
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Hubbard AK, Brown DW, Zhou W, Lin SH, Genovese G, Chanock SJ, and Machiela MJ
- Subjects
- Humans, Male, Biological Specimen Banks, Cross-Sectional Studies, Biomarkers, United Kingdom, Mosaicism, Chromosomes, Human, Y
- Abstract
Age-related clonal expansion of cells harbouring mosaic chromosomal alterations (mCAs) is one manifestation of clonal haematopoiesis. Identifying factors that influence the generation and promotion of clonal expansion of mCAs are key to investigate the role of mCAs in health and disease. Herein, we report on widely measured serum biomarkers and their possible association with mCAs, which could provide new insights into molecular alterations that promote acquisition and clonal expansion. We performed a cross-sectional investigation of the association of 32 widely measured serum biomarkers with autosomal mCAs, mosaic loss of the Y chromosome, and mosaic loss of the X chromosome in 436 784 cancer-free participants from the UK Biobank. mCAs were associated with a range of commonly measured serum biomarkers such as lipid levels, circulating sex hormones, blood sugar homeostasis, inflammation and immune function, vitamins and minerals, kidney function, and liver function. Biomarker levels in participants with mCAs were estimated to differ by up to 5% relative to mCA-free participants, and individuals with higher cell fraction mCAs had greater deviation in mean biomarker values. Polygenic scores associated with sex hormone binding globulin, vitamin D, and total cholesterol were also associated with mCAs. Overall, we observed commonly used clinical serum biomarkers related to disease risk are associated with mCAs, suggesting mechanisms involved in these diseases could be related to mCA proliferation and clonal expansion., (Published by Oxford University Press 2023.)
- Published
- 2023
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41. Identification of novel genetic loci for risk of multiple myeloma by functional annotation.
- Author
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Macauda A, Briem K, Clay-Gilmour A, Cozen W, Försti A, Giaccherini M, Corradi C, Sainz J, Niazi Y, Ter Horst R, Li Y, Netea MG, Vogel U, Hemminki K, Slager SL, Varkonyi J, Andersen V, Iskierka-Jazdzewska E, Mártinez-Lopez J, Zaucha J, Camp NJ, Rajkumar SV, Druzd-Sitek A, Bhatti P, Chanock SJ, Kumar SK, Subocz E, Mazur G, Landi S, Machiela MJ, Jerez A, Norman AD, Hildebrandt MAT, Kadar K, Berndt SI, Ziv E, Buda G, Nagler A, Dumontet C, Raźny M, Watek M, Butrym A, Grzasko N, Dudzinski M, Rybicka-Ramos M, Matera EL, García-Sanz R, Goldschmidt H, Jamroziak K, Jurczyszyn A, Clavero E, Giles GG, Pelosini M, Zawirska D, Kruszewski M, Marques H, Haastrup E, Sánchez-Maldonado JM, Bertsch U, Rymko M, Raab MS, Brown EE, Hofmann JN, Vachon C, Campa D, and Canzian F
- Subjects
- Humans, Genetic Loci, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Multiple Myeloma genetics
- Published
- 2023
- Full Text
- View/download PDF
42. Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.
- Author
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Jakubek YA, Zhou Y, Stilp A, Bacon J, Wong JW, Ozcan Z, Arnett D, Barnes K, Bis JC, Boerwinkle E, Brody JA, Carson AP, Chasman DI, Chen J, Cho M, Conomos MP, Cox N, Doyle MF, Fornage M, Guo X, Kardia SLR, Lewis JP, Loos RJF, Ma X, Machiela MJ, Mack TM, Mathias RA, Mitchell BD, Mychaleckyj JC, North K, Pankratz N, Peyser PA, Preuss MH, Psaty B, Raffield LM, Vasan RS, Redline S, Rich SS, Rotter JI, Silverman EK, Smith JA, Smith AP, Taub M, Taylor KD, Yun J, Li Y, Desai P, Bick AG, Reiner AP, Scheet P, and Auer PL
- Subjects
- Humans, Black People genetics, Hispanic or Latino genetics, Precision Medicine, Genome-Wide Association Study, Mosaicism, Genome, Human
- Abstract
Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis., (© 2023. The Author(s).)
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- 2023
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43. Shared and distinct genetic etiologies for different types of clonal hematopoiesis.
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Brown DW, Cato LD, Zhao Y, Nandakumar SK, Bao EL, Gardner EJ, Hubbard AK, DePaulis A, Rehling T, Song L, Yu K, Chanock SJ, Perry JRB, Sankaran VG, and Machiela MJ
- Subjects
- Humans, Genotype, Clone Cells, DNA Modification Methylases, Clonal Hematopoiesis genetics, Biological Evolution
- Abstract
Clonal hematopoiesis (CH)-age-related expansion of mutated hematopoietic clones-can differ in frequency and cellular fitness by CH type (e.g., mutations in driver genes (CHIP), gains/losses and copy-neutral loss of chromosomal segments (mCAs), and loss of sex chromosomes). Co-occurring CH raises questions as to their origin, selection, and impact. We integrate sequence and genotype array data in up to 482,378 UK Biobank participants to demonstrate shared genetic architecture across CH types. Our analysis suggests a cellular evolutionary trade-off between different types of CH, with LOY occurring at lower rates in individuals carrying mutations in established CHIP genes. We observed co-occurrence of CHIP and mCAs with overlap at TET2, DNMT3A, and JAK2, in which CHIP precedes mCA acquisition. Furthermore, individuals carrying overlapping CH had high risk of future lymphoid and myeloid malignancies. Finally, we leverage shared genetic architecture of CH traits to identify 15 novel loci associated with leukemia risk., (© 2023. Springer Nature Limited.)
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- 2023
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44. Mosaic chromosomal alterations detected in men living with HIV and the relationship to non-Hodgkin lymphoma.
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Lin SH, Khan SM, Zhou W, Brown DW, Vergara C, Wolinsky SM, Martínez-Maza O, Margolick JB, Martinson JJ, Hussain SK, Engels EA, and Machiela MJ
- Subjects
- Humans, Male, Cohort Studies, Chromosomes, Human, Y, Mosaicism, HIV Infections complications, Lymphoma, Non-Hodgkin epidemiology, Lymphoma, Non-Hodgkin genetics
- Abstract
Objectives: People with HIV (PWH) have an elevated risk of non-Hodgkin lymphoma (NHL) and other diseases. Studying clonal hematopoiesis (CH), the clonal expansion of mutated hematopoietic stem cells, could provide insights regarding elevated NHL risk., Design: Cohort analysis of participants in the Multicenter AIDS Cohort Study ( N = 5979)., Methods: Mosaic chromosomal alterations (mCAs), a type of CH, were detected from genotyping array data using MoChA. We compared CH prevalence in men with HIV (MWH) to HIV-uninfected men using logistic regression, and among MWH, assessed the associations of CH with NHL incidence and overall mortality using Poisson regression., Results: Comparing MWH to HIV-uninfected men, we observed no difference in the frequency of autosomal mCAs (3.9% vs. 3.6%, P -value = 0.09) or mosaic loss of the Y chromosome (mLOY) (1.4% vs. 2.9%, P -value = 0.13). Autosomal mCAs involving copy-neutral loss of heterozygosity (CN-LOH) of chromosome 14q were more common in MWH. Among MWH, mCAs were not associated with subsequent NHL incidence (autosomal mCA P -value = 0.65, mLOY P -value = 0.48). However, two MWH with diffuse large B-cell lymphoma had overlapping CN-LOH mCAs on chromosome 19 spanning U2AF2 (involved in RNA splicing), and one MWH with Burkitt lymphoma had high-frequency mCAs involving chromosome 1 gain and chromosome 17 CN-LOH (cell fractions 22.1% and 25.0%, respectively). mCAs were not associated with mortality among MWH (autosomal mCA P -value = 0.52, mLOY P -value = 0.93)., Conclusions: We found limited evidence for a relationship between HIV infection and mCAs. Although mCAs were not significantly associated with NHL, mCAs detected in several NHL cases indicate a need for further investigation., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)
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- 2023
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45. Increase in power by obtaining 10 or more controls per case when type-1 error is small in large-scale association studies.
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Katki HA, Berndt SI, Machiela MJ, Stewart DR, Garcia-Closas M, Kim J, Shi J, Yu K, and Rothman N
- Subjects
- Humans, Odds Ratio, Control Groups, Research Design
- Abstract
Background: The rule of thumb that there is little gain in statistical power by obtaining more than 4 controls per case, is based on type-1 error α = 0.05. However, association studies that evaluate thousands or millions of associations use smaller α and may have access to plentiful controls. We investigate power gains, and reductions in p-values, when increasing well beyond 4 controls per case, for small α., Methods: We calculate the power, the median expected p-value, and the minimum detectable odds-ratio (OR), as a function of the number of controls/case, as α decreases., Results: As α decreases, at each ratio of controls per case, the increase in power is larger than for α = 0.05. For α between 10
-6 and 10-9 (typical for thousands or millions of associations), increasing from 4 controls per case to 10-50 controls per case increases power. For example, a study with power = 0.2 (α = 5 × 10-8 ) with 1 control/case has power = 0.65 with 4 controls/case, but with 10 controls/case has power = 0.78, and with 50 controls/case has power = 0.84. For situations where obtaining more than 4 controls per case provides small increases in power beyond 0.9 (at small α), the expected p-value can decrease by orders-of-magnitude below α. Increasing from 1 to 4 controls/case reduces the minimum detectable OR toward the null by 20.9%, and from 4 to 50 controls/case reduces by an additional 9.7%, a result which applies regardless of α and hence also applies to "regular" α = 0.05 epidemiology., Conclusions: At small α, versus 4 controls/case, recruiting 10 or more controls/cases can increase power, reduce the expected p-value by 1-2 orders of magnitude, and meaningfully reduce the minimum detectable OR. These benefits of increasing the controls/case ratio increase as the number of cases increases, although the amount of benefit depends on exposure frequencies and true OR. Provided that controls are comparable to cases, our findings suggest greater sharing of comparable controls in large-scale association studies., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)- Published
- 2023
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46. Genetically adjusted PSA levels for prostate cancer screening.
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Kachuri L, Hoffmann TJ, Jiang Y, Berndt SI, Shelley JP, Schaffer KR, Machiela MJ, Freedman ND, Huang WY, Li SA, Easterlin R, Goodman PJ, Till C, Thompson I, Lilja H, Van Den Eeden SK, Chanock SJ, Haiman CA, Conti DV, Klein RJ, Mosley JD, Graff RE, and Witte JS
- Subjects
- Male, Humans, Prostate-Specific Antigen genetics, Early Detection of Cancer, Neoplasm Grading, Biopsy, Prostatic Neoplasms diagnosis, Prostatic Neoplasms genetics, Prostatic Neoplasms pathology
- Abstract
Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10
-8 ) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA ) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14 , area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12 , AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4 ). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening., (© 2023. The Author(s).)- Published
- 2023
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47. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population.
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Shi J, Shiraishi K, Choi J, Matsuo K, Chen TY, Dai J, Hung RJ, Chen K, Shu XO, Kim YT, Landi MT, Lin D, Zheng W, Yin Z, Zhou B, Song B, Wang J, Seow WJ, Song L, Chang IS, Hu W, Chien LH, Cai Q, Hong YC, Kim HN, Wu YL, Wong MP, Richardson BD, Funderburk KM, Li S, Zhang T, Breeze C, Wang Z, Blechter B, Bassig BA, Kim JH, Albanes D, Wong JYY, Shin MH, Chung LP, Yang Y, An SJ, Zheng H, Yatabe Y, Zhang XC, Kim YC, Caporaso NE, Chang J, Ho JCM, Kubo M, Daigo Y, Song M, Momozawa Y, Kamatani Y, Kobayashi M, Okubo K, Honda T, Hosgood DH, Kunitoh H, Patel H, Watanabe SI, Miyagi Y, Nakayama H, Matsumoto S, Horinouchi H, Tsuboi M, Hamamoto R, Goto K, Ohe Y, Takahashi A, Goto A, Minamiya Y, Hara M, Nishida Y, Takeuchi K, Wakai K, Matsuda K, Murakami Y, Shimizu K, Suzuki H, Saito M, Ohtaki Y, Tanaka K, Wu T, Wei F, Dai H, Machiela MJ, Su J, Kim YH, Oh IJ, Lee VHF, Chang GC, Tsai YH, Chen KY, Huang MS, Su WC, Chen YM, Seow A, Park JY, Kweon SS, Chen KC, Gao YT, Qian B, Wu C, Lu D, Liu J, Schwartz AG, Houlston R, Spitz MR, Gorlov IP, Wu X, Yang P, Lam S, Tardon A, Chen C, Bojesen SE, Johansson M, Risch A, Bickeböller H, Ji BT, Wichmann HE, Christiani DC, Rennert G, Arnold S, Brennan P, McKay J, Field JK, Shete SS, Le Marchand L, Liu G, Andrew A, Kiemeney LA, Zienolddiny-Narui S, Grankvist K, Johansson M, Cox A, Taylor F, Yuan JM, Lazarus P, Schabath MB, Aldrich MC, Jeon HS, Jiang SS, Sung JS, Chen CH, Hsiao CF, Jung YJ, Guo H, Hu Z, Burdett L, Yeager M, Hutchinson A, Hicks B, Liu J, Zhu B, Berndt SI, Wu W, Wang J, Li Y, Choi JE, Park KH, Sung SW, Liu L, Kang CH, Wang WC, Xu J, Guan P, Tan W, Yu CJ, Yang G, Sihoe ADL, Chen Y, Choi YY, Kim JS, Yoon HI, Park IK, Xu P, He Q, Wang CL, Hung HH, Vermeulen RCH, Cheng I, Wu J, Lim WY, Tsai FY, Chan JKC, Li J, Chen H, Lin HC, Jin L, Liu J, Sawada N, Yamaji T, Wyatt K, Li SA, Ma H, Zhu M, Wang Z, Cheng S, Li X, Ren Y, Chao A, Iwasaki M, Zhu J, Jiang G, Fei K, Wu G, Chen CY, Chen CJ, Yang PC, Yu J, Stevens VL, Fraumeni JF Jr, Chatterjee N, Gorlova OY, Hsiung CA, Amos CI, Shen H, Chanock SJ, Rothman N, Kohno T, and Lan Q
- Subjects
- Humans, Genome-Wide Association Study, Genetic Predisposition to Disease, Asia, Eastern epidemiology, Polymorphism, Single Nucleotide, Adenocarcinoma of Lung genetics, Lung Neoplasms epidemiology, Lung Neoplasms genetics
- Abstract
Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P
interaction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)- Published
- 2023
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48. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization.
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Clavero E, Sanchez-Maldonado JM, Macauda A, Ter Horst R, Sampaio-Marques B, Jurczyszyn A, Clay-Gilmour A, Stein A, Hildebrandt MAT, Weinhold N, Buda G, García-Sanz R, Tomczak W, Vogel U, Jerez A, Zawirska D, Wątek M, Hofmann JN, Landi S, Spinelli JJ, Butrym A, Kumar A, Martínez-López J, Galimberti S, Sarasquete ME, Subocz E, Iskierka-Jażdżewska E, Giles GG, Rybicka-Ramos M, Kruszewski M, Abildgaard N, Verdejo FG, Sánchez Rovira P, da Silva Filho MI, Kadar K, Razny M, Cozen W, Pelosini M, Jurado M, Bhatti P, Dudzinski M, Druzd-Sitek A, Orciuolo E, Li Y, Norman AD, Zaucha JM, Reis RM, Markiewicz M, Rodríguez Sevilla JJ, Andersen V, Jamroziak K, Hemminki K, Berndt SI, Rajkumar V, Mazur G, Kumar SK, Ludovico P, Nagler A, Chanock SJ, Dumontet C, Machiela MJ, Varkonyi J, Camp NJ, Ziv E, Vangsted AJ, Brown EE, Campa D, Vachon CM, Netea MG, Canzian F, Försti A, and Sainz J
- Subjects
- Humans, Leukocytes, Mononuclear pathology, Biomarkers, Immunoglobulin M, Autophagy, Multiple Myeloma genetics, Multiple Myeloma pathology
- Abstract
Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10
-9 ) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46 , IKBKE , PARK2 , ULK4 , ATG5 , and CDKN2A associated with MM risk ( p = 4.47 × 10-4 -5.79 × 10-14 ). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 ( p = 4.0 × 10-4 ), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+ CD38+ B cells ( p = 4.8 × 10-4 ) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 ( p = 3.6 × 10-4 ). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+ CD3- B cells, CD5+ IgD- cells, IgM- cells, IgD- IgM- cells, and CD4- CD8- PBMCs ( p = 4.9 × 10-4 -8.6 × 10-4 ) and circulating concentrations of interleukin (IL)-20 ( p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+ EMCD45RO+ CD27- cells ( p = 9.3 × 10-4 ). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3- , MCP-2- , and IL20-dependent pathways.- Published
- 2023
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49. Transcriptome-Wide Association Analysis Identifies Novel Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer.
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Chen DM, Dong R, Kachuri L, Hoffmann T, Jiang Y, Berndt SI, Shelley JP, Schaffer KR, Machiela MJ, Freedman ND, Huang WY, Li SA, Lilja H, Van Den Eeden SK, Chanock S, Haiman CA, Conti DV, Klein RJ, Mosley JD, Witte JS, and Graff RE
- Abstract
Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility to screen for prostate cancer (PCa). We thus conducted a transcriptome-wide association study (TWAS) of PSA levels using genome-wide summary statistics from 95,768 PCa-free men, the MetaXcan framework, and gene prediction models trained in Genotype-Tissue Expression (GTEx) project data. Tissue-specific analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10e-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61e-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses that combined associations across 45 tissues identified 155 genes that were statistically significantly (p < 0.05/22,249 = 2.25e-6) associated with PSA levels. Based on conditional analyses that assessed whether TWAS associations were attributable to a lead GWAS variant, we found 20 novel genes (11 single-tissue, 9 cross-tissue) that were associated with PSA levels in the TWAS. Of these novel genes, five showed evidence of colocalization (colocalization probability > 0.5): EXOSC9, CCNA2, HIST1H2BN, RP11-182L21.6, and RP11-327J17.2. Six of the 20 novel genes are not known to impact PCa risk. These findings yield new hypotheses for genetic factors underlying PSA levels that should be further explored toward improving our understanding of PSA biology., Competing Interests: Declaration of Interests: JSW is a non-employee, cofounder of Avail Bio. HL is named on a patent for assays to measure intact prostate-specific antigen and a patent for a statistical method to detect prostate cancer commercialized by OPKO Health (4KScore). HL receives royalties from sales of the assay and has stock in OPKO Health. HL serves on the Scientific Advisory Board for Fujirebio Diagnostics Inc and owns stock in Diaprost AB and Acousort AB.
- Published
- 2023
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50. Targeted long-read sequencing of the Ewing sarcoma 6p25.1 susceptibility locus identifies germline-somatic interactions with EWSR1-FLI1 binding.
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Lee OW, Rodrigues C, Lin SH, Luo W, Jones K, Brown DW, Zhou W, Karlins E, Khan SM, Baulande S, Raynal V, Surdez D, Reynaud S, Rubio RA, Zaidi S, Grossetête S, Ballet S, Lapouble E, Laurence V, Pierron G, Gaspar N, Corradini N, Marec-Bérard P, Rothman N, Dagnall CL, Burdett L, Manning M, Wyatt K, Yeager M, Chari R, Leisenring WM, Kulozik AE, Kriebel J, Meitinger T, Strauch K, Kirchner T, Dirksen U, Mirabello L, Tucker MA, Tirode F, Armstrong GT, Bhatia S, Robison LL, Yasui Y, Romero-Pérez L, Hartmann W, Metzler M, Diver WR, Lori A, Freedman ND, Hoover RN, Morton LM, Chanock SJ, Grünewald TGP, Delattre O, and Machiela MJ
- Subjects
- Humans, Alleles, Cell Line, Tumor, Gene Expression Regulation, Neoplastic, Oncogene Proteins, Fusion genetics, Oncogene Proteins, Fusion metabolism, Proto-Oncogene Protein c-fli-1 genetics, Proto-Oncogene Protein c-fli-1 metabolism, RNA-Binding Protein EWS genetics, RNA-Binding Protein EWS metabolism, Bone Neoplasms genetics, Bone Neoplasms pathology, Sarcoma, Ewing genetics, Sarcoma, Ewing metabolism, Sarcoma, Ewing pathology
- Abstract
Ewing sarcoma (EwS) is a rare bone and soft tissue malignancy driven by chromosomal translocations encoding chimeric transcription factors, such as EWSR1-FLI1, that bind GGAA motifs forming novel enhancers that alter nearby expression. We propose that germline microsatellite variation at the 6p25.1 EwS susceptibility locus could impact downstream gene expression and EwS biology. We performed targeted long-read sequencing of EwS blood DNA to characterize variation and genomic features important for EWSR1-FLI1 binding. We identified 50 microsatellite alleles at 6p25.1 and observed that EwS-affected individuals had longer alleles (>135 bp) with more GGAA repeats. The 6p25.1 GGAA microsatellite showed chromatin features of an EWSR1-FLI1 enhancer and regulated expression of RREB1, a transcription factor associated with RAS/MAPK signaling. RREB1 knockdown reduced proliferation and clonogenic potential and reduced expression of cell cycle and DNA replication genes. Our integrative analysis at 6p25.1 details increased binding of longer GGAA microsatellite alleles with acquired EWSR-FLI1 to promote Ewing sarcomagenesis by RREB1-mediated proliferation., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)
- Published
- 2023
- Full Text
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