8,097 results on '"Xiao, Ou"'
Search Results
2. Refining breast cancer genetic risk and biology through multi-ancestry fine-mapping analyses of 192 risk regions
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Jia, Guochong, Chen, Zhishan, Ping, Jie, Cai, Qiuyin, Tao, Ran, Li, Chao, Bauer, Joshua A., Xie, Yuhan, Ambs, Stefan, Barnard, Mollie E., Chen, Yu, Choi, Ji-Yeob, Gao, Yu-Tang, Garcia-Closas, Montserrat, Gu, Jian, Hu, Jennifer J., Iwasaki, Motoki, John, Esther M., Kweon, Sun-Seog, Li, Christopher I., Matsuda, Koichi, Matsuo, Keitaro, Nathanson, Katherine L., Nemesure, Barbara, Olopade, Olufunmilayo I., Pal, Tuya, Park, Sue K., Park, Boyoung, Press, Michael F., Sanderson, Maureen, Sandler, Dale P., Shen, Chen-Yang, Troester, Melissa A., Yao, Song, Zheng, Ying, Ahearn, Thomas, Brewster, Abenaa M., Falusi, Adeyinka, Hennis, Anselm J. M., Ito, Hidemi, Kubo, Michiaki, Lee, Eun-Sook, Makumbi, Timothy, Ndom, Paul, Noh, Dong-Young, O’Brien, Katie M., Ojengbede, Oladosu, Olshan, Andrew F., Park, Min-Ho, Reid, Sonya, Yamaji, Taiki, Zirpoli, Gary, Butler, Ebonee N., Huang, Maosheng, Low, Siew-Kee, Obafunwa, John, Weinberg, Clarice R., Zhang, Haoyu, Zhao, Hongyu, Cote, Michelle L., Ambrosone, Christine B., Huo, Dezheng, Li, Bingshan, Kang, Daehee, Palmer, Julie R., Shu, Xiao-Ou, Haiman, Christopher A., Guo, Xingyi, Long, Jirong, and Zheng, Wei
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- 2025
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3. Reproductive factors and risk of epithelial ovarian cancer: results from the Asia Cohort Consortium: Epidemiology
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Merritt, Melissa A., Abe, Sarah Krull, Islam, Md Rashedul, Rahman, Md Shafiur, Saito, Eiko, Katagiri, Ryoko, Shin, Aesun, Choi, Ji-Yeob, Le Marchand, Loïc, Killeen, Jeffrey L., Gao, Yu-Tang, Tamakoshi, Akiko, Koh, Woon-Puay, Sakata, Ritsu, Sawada, Norie, Tsuji, Ichiro, Sugawara, Yumi, Kim, Jeongseon, Park, Sue K., Kweon, Sun-Seog, Shu, Xiao-Ou, Kimura, Takashi, Yuan, Jian-Min, Tsugane, Shoichiro, Kanemura, Seiki, Lu, Yukai, Shin, Min-Ho, Wen, Wanqing, Ahsan, Habibul, Boffetta, Paolo, Chia, Kee Seng, Matsuo, Keitaro, Qiao, You-Lin, Rothman, Nathaniel, Zheng, Wei, Inoue, Manami, and Kang, Daehee
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- 2024
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4. Associations of Blood Lipid-Related Polygenic Scores, Lifestyle Factors and Their Combined Effects with Risk of Coronary Artery Disease in the UK Biobank Cohort
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Choi, Jungyoon, Wen, Wanqing, Jia, Guochong, Tao, Ran, Long, Jirong, Shu, Xiao-Ou, and Zheng, Wei
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- 2024
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5. A proteome-wide association study identifies putative causal proteins for breast cancer risk
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Zhao, Tianying, Xu, Shuai, Ping, Jie, Jia, Guochong, Dou, Yongchao, Henry, Jill E., Zhang, Bing, Guo, Xingyi, Cote, Michele L., Cai, Qiuyin, Shu, Xiao-Ou, Zheng, Wei, and Long, Jirong
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- 2024
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6. Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction
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Yiangou, Kristia, Mavaddat, Nasim, Dennis, Joe, Zanti, Maria, Wang, Qin, Bolla, Manjeet K., Abubakar, Mustapha, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antonenkova, Natalia N., Arndt, Volker, Aronson, Kristan J., Augustinsson, Annelie, Baten, Adinda, Behrens, Sabine, Bermisheva, Marina, de Gonzalez, Amy Berrington, Białkowska, Katarzyna, Boddicker, Nicholas, Bodelon, Clara, Bogdanova, Natalia V., Bojesen, Stig E., Brantley, Kristen D., Brauch, Hiltrud, Brenner, Hermann, Camp, Nicola J., Canzian, Federico, Castelao, Jose E., Cessna, Melissa H., Chang-Claude, Jenny, Chenevix-Trench, Georgia, Chung, Wendy K., Colonna, Sarah V., Couch, Fergus J., Cox, Angela, Cross, Simon S., Czene, Kamila, Daly, Mary B., Devilee, Peter, Dörk, Thilo, Dunning, Alison M., Eccles, Diana M., Eliassen, A. Heather, Engel, Christoph, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Fletcher, Olivia, Flyger, Henrik, Fritschi, Lin, Gago-Dominguez, Manuela, Gentry-Maharaj, Aleksandra, González-Neira, Anna, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A., Hamann, Ute, Hartikainen, Jaana M., Ho, Vikki, Hodge, James, Hollestelle, Antoinette, Honisch, Ellen, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Howell, Sacha, Howell, Anthony, Jakovchevska, Simona, Jakubowska, Anna, Jernström, Helena, Johnson, Nichola, Kaaks, Rudolf, Khusnutdinova, Elza K., Kitahara, Cari M., Koutros, Stella, Kristensen, Vessela N., Lacey, James V., Lambrechts, Diether, Lejbkowicz, Flavio, Lindblom, Annika, Lush, Michael, Mannermaa, Arto, Mavroudis, Dimitrios, Menon, Usha, Murphy, Rachel A., Nevanlinna, Heli, Obi, Nadia, Offit, Kenneth, Park-Simon, Tjoung-Won, Patel, Alpa V., Peng, Cheng, Peterlongo, Paolo, Pita, Guillermo, Plaseska-Karanfilska, Dijana, Pylkäs, Katri, Radice, Paolo, Rashid, Muhammad U., Rennert, Gad, Roberts, Eleanor, Rodriguez, Juan, Romero, Atocha, Rosenberg, Efraim H., Saloustros, Emmanouil, Sandler, Dale P., Sawyer, Elinor J., Schmutzler, Rita K., Scott, Christopher G., Shu, Xiao-Ou, Southey, Melissa C., Stone, Jennifer, Taylor, Jack A., Teras, Lauren R., van de Beek, Irma, Willett, Walter, Winqvist, Robert, Zheng, Wei, Vachon, Celine M., Schmidt, Marjanka K., Hall, Per, MacInnis, Robert J., Milne, Roger L., Pharoah, Paul D. P., Simard, Jacques, Antoniou, Antonis C., Easton, Douglas F., and Michailidou, Kyriaki
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- 2024
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7. Body mass index and breast cancer risk in premenopausal and postmenopausal East Asian women: a pooled analysis of 13 cohort studies
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Wada, Keiko, Kuboyama, Koshi, Abe, Sarah Krull, Rahman, Md. Shafiur, Islam, Md. Rashedul, Saito, Eiko, Nagata, Chisato, Sawada, Norie, Tamakoshi, Akiko, Shu, Xiao-Ou, Sakata, Ritsu, Hozawa, Atsushi, Kanemura, Seiki, Ito, Hidemi, Sugawara, Yumi, Park, Sue K., Kweon, Sun-Seog, Ono, Ayami, Kimura, Takashi, Wen, Wanqing, Oze, Isao, Shin, Min-Ho, Shin, Aesun, Kim, Jeongseon, Lee, Jung Eun, Matsuo, Keitaro, Rothman, Nathaniel, Qiao, You-Lin, Zheng, Wei, Boffetta, Paolo, and Inoue, Manami
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- 2024
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8. α-Synuclein disrupts microglial autophagy through STAT1-dependent suppression of Ulk1 transcription
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Pei, Chong-Shuang, Hou, Xiao-Ou, Ma, Zhen-Yuan, Tu, Hai-Yue, Qian, Hai-Chun, Li, Yang, Li, Kai, Liu, Chun-Feng, Ouyang, Liang, Liu, Jun-Yi, and Hu, Li-Fang
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- 2024
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9. Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes
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Chen, Zhishan, Guo, Xingyi, Tao, Ran, Huyghe, Jeroen R., Law, Philip J., Fernandez-Rozadilla, Ceres, Ping, Jie, Jia, Guochong, Long, Jirong, Li, Chao, Shen, Quanhu, Xie, Yuhan, Timofeeva, Maria N., Thomas, Minta, Schmit, Stephanie L., Díez-Obrero, Virginia, Devall, Matthew, Moratalla-Navarro, Ferran, Fernandez-Tajes, Juan, Palles, Claire, Sherwood, Kitty, Briggs, Sarah E. W., Svinti, Victoria, Donnelly, Kevin, Farrington, Susan M., Blackmur, James, Vaughan-Shaw, Peter G., Shu, Xiao-Ou, Lu, Yingchang, Broderick, Peter, Studd, James, Harrison, Tabitha A., Conti, David V., Schumacher, Fredrick R., Melas, Marilena, Rennert, Gad, Obón-Santacana, Mireia, Martín-Sánchez, Vicente, Oh, Jae Hwan, Kim, Jeongseon, Jee, Sun Ha, Jung, Keum Ji, Kweon, Sun-Seog, Shin, Min-Ho, Shin, Aesun, Ahn, Yoon-Ok, Kim, Dong-Hyun, Oze, Isao, Wen, Wanqing, Matsuo, Keitaro, Matsuda, Koichi, Tanikawa, Chizu, Ren, Zefang, Gao, Yu-Tang, Jia, Wei-Hua, Hopper, John L., Jenkins, Mark A., Win, Aung Ko, Pai, Rish K., Figueiredo, Jane C., Haile, Robert W., Gallinger, Steven, Woods, Michael O., Newcomb, Polly A., Duggan, David, Cheadle, Jeremy P., Kaplan, Richard, Kerr, Rachel, Kerr, David, Kirac, Iva, Böhm, Jan, Mecklin, Jukka-Pekka, Jousilahti, Pekka, Knekt, Paul, Aaltonen, Lauri A., Rissanen, Harri, Pukkala, Eero, Eriksson, Johan G., Cajuso, Tatiana, Hänninen, Ulrika, Kondelin, Johanna, Palin, Kimmo, Tanskanen, Tomas, Renkonen-Sinisalo, Laura, Männistö, Satu, Albanes, Demetrius, Weinstein, Stephanie J., Ruiz-Narvaez, Edward, Palmer, Julie R., Buchanan, Daniel D., Platz, Elizabeth A., Visvanathan, Kala, Ulrich, Cornelia M., Siegel, Erin, Brezina, Stefanie, Gsur, Andrea, Campbell, Peter T., Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Slattery, Martha L., Potter, John D., Tsilidis, Kostas K., Schulze, Matthias B., Gunter, Marc J., Murphy, Neil, Castells, Antoni, Castellví-Bel, Sergi, Moreira, Leticia, Arndt, Volker, Shcherbina, Anna, Bishop, D. Timothy, Giles, Graham G., Southey, Melissa C., Idos, Gregory E., McDonnell, Kevin J., Abu-Ful, Zomoroda, Greenson, Joel K., Shulman, Katerina, Lejbkowicz, Flavio, Offit, Kenneth, Su, Yu-Ru, Steinfelder, Robert, Keku, Temitope O., van Guelpen, Bethany, Hudson, Thomas J., Hampel, Heather, Pearlman, Rachel, Berndt, Sonja I., Hayes, Richard B., Martinez, Marie Elena, Thomas, Sushma S., Pharoah, Paul D. P., Larsson, Susanna C., Yen, Yun, Lenz, Heinz-Josef, White, Emily, Li, Li, Doheny, Kimberly F., Pugh, Elizabeth, Shelford, Tameka, Chan, Andrew T., Cruz-Correa, Marcia, Lindblom, Annika, Hunter, David J., Joshi, Amit D., Schafmayer, Clemens, Scacheri, Peter C., Kundaje, Anshul, Schoen, Robert E., Hampe, Jochen, Stadler, Zsofia K., Vodicka, Pavel, Vodickova, Ludmila, Vymetalkova, Veronika, Edlund, Christopher K., Gauderman, W. James, Shibata, David, Toland, Amanda, Markowitz, Sanford, Kim, Andre, Chanock, Stephen J., van Duijnhoven, Franzel, Feskens, Edith J. M., Sakoda, Lori C., Gago-Dominguez, Manuela, Wolk, Alicja, Pardini, Barbara, FitzGerald, Liesel M., Lee, Soo Chin, Ogino, Shuji, Bien, Stephanie A., Kooperberg, Charles, Li, Christopher I., Lin, Yi, Prentice, Ross, Qu, Conghui, Bézieau, Stéphane, Yamaji, Taiki, Sawada, Norie, Iwasaki, Motoki, Le Marchand, Loic, Wu, Anna H., Qu, Chenxu, McNeil, Caroline E., Coetzee, Gerhard, Hayward, Caroline, Deary, Ian J., Harris, Sarah E., Theodoratou, Evropi, Reid, Stuart, Walker, Marion, Ooi, Li Yin, Lau, Ken S., Zhao, Hongyu, Hsu, Li, Cai, Qiuyin, Dunlop, Malcolm G., Gruber, Stephen B., Houlston, Richard S., Moreno, Victor, Casey, Graham, Peters, Ulrike, Tomlinson, Ian, and Zheng, Wei
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- 2024
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10. Clinical associations with a polygenic predisposition to benign lower white blood cell counts
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Mosley, Jonathan D., Shelley, John P., Dickson, Alyson L., Zanussi, Jacy, Daniel, Laura L., Zheng, Neil S., Bastarache, Lisa, Wei, Wei-Qi, Shi, Mingjian, Jarvik, Gail P., Rosenthal, Elisabeth A., Khan, Atlas, Sherafati, Alborz, Kullo, Iftikhar J., Walunas, Theresa L., Glessner, Joseph, Hakonarson, Hakon, Cox, Nancy J., Roden, Dan M., Frangakis, Stephan G., Vanderwerff, Brett, Stein, C. Michael, Van Driest, Sara L., Borinstein, Scott C., Shu, Xiao-Ou, Zawistowski, Matthew, Chung, Cecilia P., and Kawai, Vivian K.
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- 2024
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11. Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea
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Nabila, Salma, Choi, Ji-Yeob, Abe, Sarah Krull, Islam, Md Rashedul, Rahman, Md Shafiur, Saito, Eiko, Shin, Aesun, Merritt, Melissa A., Katagiri, Ryoko, Shu, Xiao-Ou, Sawada, Norie, Tamakoshi, Akiko, Sakata, Ritsu, Hozawa, Atsushi, Kim, Jeongseon, Nagata, Chisato, Park, Sue K., Kweon, Sun-Seog, Cai, Hui, Tsugane, Shoichiro, Kimura, Takashi, Kanemura, Seiki, Sugawara, Yumi, Wada, Keiko, Shin, Min-Ho, Ahsan, Habibul, Boffetta, Paolo, Chia, Kee Seng, Matsuo, Keitaro, Qiao, You-Lin, Rothman, Nathaniel, Zheng, Wei, Inoue, Manami, and Kang, Daehee
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- 2024
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12. Family history and gastric cancer incidence and mortality in Asia: a pooled analysis of more than half a million participants
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Huang, Dan, Song, Minkyo, Abe, Sarah Krull, Rahman, Md. Shafiur, Islam, Md. Rashedul, Saito, Eiko, De la Torre, Katherine, Sawada, Norie, Tamakoshi, Akiko, Shu, Xiao-Ou, Cai, Hui, Hozawa, Atsushi, Kanemura, Seiki, Kim, Jeongseon, Chen, Yu, Ito, Hidemi, Sugawara, Yumi, Park, Sue K., Shin, Myung-Hee, Hirabayashi, Mayo, Kimura, Takashi, Gao, Yu-Tang, Wen, Wanqing, Oze, Isao, Shin, Aesun, Ahn, Yoon-Ok, Ahsan, Habibul, Boffetta, Paolo, Chia, Kee Seng, Matsuo, Keitaro, Qiao, You-Lin, Rothman, Nathaniel, Zheng, Wei, Inoue, Manami, and Kang, Daehee
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- 2024
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13. Genetic correlation and causal associations between circulating C-reactive protein levels and lung cancer risk
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Shi, Jiajun, Wen, Wanqing, Long, Jirong, Xue, Haoran, Yang, Yaohua, Tao, Ran, Pan, Wei, Shu, Xiao-Ou, and Cai, Qiuyin
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- 2024
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14. Age at lung cancer diagnosis in females versus males who never smoke by race and ethnicity
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Blechter, Batel, Wong, Jason Y. Y., Chien, Li-Hsin, Shiraishi, Kouya, Shu, Xiao-Ou, Cai, Qiuyin, Zheng, Wei, Ji, Bu-Tian, Hu, Wei, Rahman, Mohammad L., Jiang, Hsin-Fang, Tsai, Fang-Yu, Huang, Wen-Yi, Gao, Yu-Tang, Han, Xijing, Steinwandel, Mark D., Yang, Gong, Daida, Yihe G., Liang, Su-Ying, Gomez, Scarlett L., DeRouen, Mindy C., Diver, W. Ryan, Reddy, Ananya G., Patel, Alpa V., Le Marchand, Loïc, Haiman, Christopher, Kohno, Takashi, Cheng, Iona, Chang, I-Shou, Hsiung, Chao Agnes, Rothman, Nathaniel, and Lan, Qing
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- 2024
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15. Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction
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Jia, Guochong, Ping, Jie, Guo, Xingyi, Yang, Yaohua, Tao, Ran, Li, Bingshan, Ambs, Stefan, Barnard, Mollie E., Chen, Yu, Garcia-Closas, Montserrat, Gu, Jian, Hu, Jennifer J., Huo, Dezheng, John, Esther M., Li, Christopher I., Li, James L., Nathanson, Katherine L., Nemesure, Barbara, Olopade, Olufunmilayo I., Pal, Tuya, Press, Michael F., Sanderson, Maureen, Sandler, Dale P., Shu, Xiao-Ou, Troester, Melissa A., Yao, Song, Adejumo, Prisca O., Ahearn, Thomas, Brewster, Abenaa M., Hennis, Anselm J. M., Makumbi, Timothy, Ndom, Paul, O’Brien, Katie M., Olshan, Andrew F., Oluwasanu, Mojisola M., Reid, Sonya, Butler, Ebonee N., Huang, Maosheng, Ntekim, Atara, Qian, Huijun, Zhang, Haoyu, Ambrosone, Christine B., Cai, Qiuyin, Long, Jirong, Palmer, Julie R., Haiman, Christopher A., and Zheng, Wei
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- 2024
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16. A Likelihood Ratio Approach for Utilizing Case‐Control Data in the Clinical Classification of Rare Sequence Variants: Application to BRCA1 and BRCA2
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Zanti, Maria, O′Mahony, Denise G, Parsons, Michael T, Li, Hongyan, Dennis, Joe, Aittomäkkiki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Aronson, Kristan J, Augustinsson, Annelie, Becher, Heiko, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Brown, Melissa A, Buys, Saundra S, Canzian, Federico, Caputo, Sandrine M, Castelao, Jose E, Chang-Claude, Jenny, Collaborators, GC-HBOC study, Czene, Kamila, Daly, Mary B, De Nicolo, Arcangela, Devilee, Peter, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Engel, Christoph, Evans, D Gareth, Fasching, Peter A, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Gentry-Maharaj, Aleksandra, Giele, Willemina RR Geurts-, Giles, Graham G, Glendon, Gord, Goldberg, Mark S, Garcia, Encarna B Gómez, Güendert, Melanie, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Hall, Per, Hamann, Ute, Harkness, Elaine F, Hogervorst, Frans BL, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L, Houdayer, Claude, Houlston, Richard S, Howell, Anthony, Investigators, ABCTB, Jakimovska, Milena, Jakubowska, Anna, Jernström, Helena, John, Esther M, Kaaks, Rudolf, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Lacey, James V, Lambrechts, Diether, Léoné, Melanie, Lindblom, Annika, Lubiński, Jan, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Menon, Usha, Milne, Roger L, Monteiro, Alvaro N, Murphy, Rachel A, Neuhausen, Susan L, Nevanlinna, Heli, Newman, William G, Offit, Kenneth, Park, Sue K, James, Paul, Peterlongo, Paolo, Peto, Julian, Plaseska-Karanfilska, Dijana, Punie, Kevin, Radice, Paolo, Rashid, Muhammad U, Rennert, Gad, Romero, Atocha, Rosenberg, Efraim H, Saloustros, Emmanouil, Sandler, Dale P, Schmidt, Marjanka K, Schmutzler, Rita K, and Shu, Xiao-Ou
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Biological Sciences ,Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Genetics ,Human Genome ,Cancer ,Prevention ,Breast Cancer ,Genetic Testing ,Biotechnology ,Women's Health ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Humans ,Case-Control Studies ,BRCA2 Protein ,Genetic Predisposition to Disease ,Female ,BRCA1 Protein ,Breast Neoplasms ,Likelihood Functions ,Genetic Variation ,Penetrance ,GC-HBOC study Collaborators ,ABCTB Investigators ,ACMG/AMP ,BRCA ,PS4 ,VUS ,case-control ,likelihood ratio ,variant classification ,Clinical Sciences ,Genetics & Heredity ,Clinical sciences - Abstract
A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.
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- 2023
17. Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization.
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Canzian, Federico, Du, Mengmeng, Gallinger, Steven, Giles, Graham, Goodman, Phyllis, Haiman, Christopher, Kogevinas, Manolis, Kooperberg, Charles, LeMarchand, Loic, Neale, Rachel, Visvanathan, Kala, White, Emily, Albanes, Demetrius, Andreotti, Gabriella, Babic, Ana, Berndt, Sonja, Brais, Lauren, Brennan, Paul, Buring, Julie, Rabe, Kari, Bamlet, William, Chanock, Stephen, Fuchs, Charles, Gaziano, J, Giovannucci, Edward, Hackert, Thilo, Hassan, Manal, Katzke, Verena, Kurtz, Robert, Lee, I-Min, Malats, Núria, Murphy, Neil, Oberg, Ann, Orlow, Irene, Porta, Miquel, Real, Francisco, Rothman, Nathaniel, Sesso, Howard, Silverman, Debra, Thompson, Ian, Wactawski-Wende, Jean, Wang, Xiaoliang, Wentzensen, Nicolas, Yu, Herbert, Zeleniuch-Jacquotte, Anne, Yu, Kai, Wolpin, Brian, Duell, Eric, Li, Donghui, Hung, Rayjean, Perdomo, Sandra, McCullough, Marjorie, Freedman, Neal, Patel, Alpa, Peters, Ulrike, Riboli, Elio, Sund, Malin, Tjønneland, Anne, Zhong, Jun, Van Den Eeden, Stephen, Kraft, Peter, Risch, Harvey, Amundadottir, Laufey, Klein, Alison, Stolzenberg-Solomon, Rachael, Antwi, Samuel, King, Sontoria, Veliginti, Swathi, Brouwers, Martijn, Ren, Zhewen, Zheng, Wei, Setiawan, Veronica, Wilkens, Lynne, Shu, Xiao-Ou, Arslan, Alan, Beane Freeman, Laura, and Bracci, Paige
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Humans ,Non-alcoholic Fatty Liver Disease ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Mendelian Randomization Analysis ,Pancreatic Neoplasms ,Obesity ,Polymorphism ,Single Nucleotide - Abstract
BACKGROUND: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. METHODS: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. RESULTS: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. CONCLUSIONS: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. IMPACT: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.
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- 2023
18. Commensal microorganisms ameliorate the adverse effects of high wheat starch diet on the growth performance, glucose and lipid metabolisms in juvenile largemouth bass, Micropterus salmoides
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Bi-Yun Zhang, Hong-Ling Yang, Ze-Hui Yuan, Xiao-Ou Sun, Jia-Hao Yin, Jun-Ji Xu, Guo-He Cai, and Yun-Zhang Sun
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Micropterus salmoides ,High starch diet ,Autochthonous probiotics ,Glucose metabolism ,Lipid metabolism ,Aquaculture. Fisheries. Angling ,SH1-691 - Abstract
Largemouth bass (Micropterus salmoides) is poor at utilizing starch, and it is not clear whether commensal microorganisms can alleviate the adverse influences of high wheat starch in M. salmoides. Here, twelve autochthonous microorganisms with amylase producing abilities were isolated from the M. salmoides fed with diets containing 6 %, 12 %, or 18 % starch. Among them, Citrobacter freundii F1, Bacillus altitudinis F7, Enterococcus casseliflavus D12, Plesiomonas shigelloides D15, Bacillus cabrialesii D16, Citrobacter portucalensis K25 and Serratia oryzae K28 showed no hemolytic activity and were safety for M. salmoides. A 42-d feeding experiment was performed to study the functions of the seven microorganisms. A total of 810 fish (5.9 ± 0.01 g) were equally distributed into 9 groups. The control groups C6 and C18 were respectively fed with 6 % and 18 % wheat starch diets, the groups F1, F7, D12, D15, D16, K25 and K28 were fed with 18 % wheat starch diets respectively supplemented with 1.0×108 CFU/g C. freundii F1, B. altitudinis F7, E. casseliflavus D12, P. shigelloides D15, B. cabrialesii D16, C. portucalensis K25 and S. oryzae K28. The results indicated that compared with 6 % starch, 18 % level inhibited the growth performance, increased the hepatic glycogen and fat contents, improved the activities of glycolysis-related enzymes (hexokinase (HK), glucokinase (GK), phosphofructokinase (PFK), pyruvate kinase (PK)), decreased the activities of gluconeogenesis-related enzymes, pyruvate carboxylase (PC) and phosphoenolpyruvate carboxykinase (PEPCK), promoted the activity of lipid synthases-related enzyme carnitine palmitoyl transferaseⅠ (CPT1) and reduced the activity of lipolytic enzymes-related lipoprotein lipase (LPL). C. freundii F1, P. shigelloides D15, C. portucalensis K25 and S. oryzae K28 had relatively poor alleviating effects, while B. altitudinis F7, E. casseliflavus D12 and B. cabrialesii D16 significantly promoted the final body weight (FBW), weight gain rate (WGR), specific growth rate (SGR), protein efficiency ratio (PER), decreased feed conversion rate (FCR), significantly reduced the hepatic glycogen and fat contents, decreased the activities of glycolysis-related enzymes (HK, GK, PK), improved the activities of gluconeogenesis-related enzymes (PC, PEPCK), reduced the activity of lipid synthases-related enzyme CPT1 (P < 0.05), which proved that these three strains could effectively alleviate the negative effects of high starch in M. salmoides. In conclusion, among the seven autochthonous microorganisms, B. altitudinis F7, E. casseliflavus D12 and B. cabrialesii D16 presented better potential advantages in improving glucose and lipid metabolisms, thus promoting the growth performance of M. salmoides fed with high wheat starch diet.
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- 2024
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19. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
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Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J., Yin, Xianyong, Lorenz, Kim M., Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E. M., Kanoni, Stavroula, Rayner, Nigel W., Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S. K., Preuss, Michael H., Petty, Lauren E., Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A., Cook, James P., Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J., Chai, Jin-Fang, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj S., Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Brody, Jennifer A., Kabagambe, Edmond, An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Broadaway, K. Alaine, Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Thangam, Manonanthini, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Ahluwalia, Tarunveer S., Anand, Sonia S., Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas A., Burant, Charles F., Butterworth, Adam S., Canouil, Mickaël, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Danesh, John, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry I., Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, González-Villalpando, Clicerio, González-Villalpando, Maria Elena, Gordon-Larsen, Penny, Gross, Myron, Guare, Lindsay A., Hackinger, Sophie, Hakaste, Liisa, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Horikoshi, Momoko, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md. Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jørgensen, Torben, Kamanu, Frederick K., Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kronenberg, Florian, Kuusisto, Johanna, Läll, Kristi, Lange, Leslie A., Lee, Kyung Min, Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian’an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lynch, Julie A., Lyssenko, Valeriya, Maeda, Shiro, Mamakou, Vasiliki, Mansuri, Sohail Rafik, Matsuda, Koichi, Meitinger, Thomas, Melander, Olle, Metspalu, Andres, Mo, Huan, Morris, Andrew D., Moura, Filipe A., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Patil, Snehal, Pei, Pei, Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Polikowsky, Hannah G., Porneala, Bianca, Prasad, Gauri, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Katheryn, Sabanayagam, Charumathi, Sandow, Kevin, Sankareswaran, Alagu, Sattar, Naveed, Schönherr, Sebastian, Shahriar, Mohammad, Shen, Botong, Shi, Jinxiu, Shin, Dong Mun, Shojima, Nobuhiro, Smith, Jennifer A., So, Wing Yee, Stančáková, Alena, Steinthorsdottir, Valgerdur, Stilp, Adrienne M., Strauch, Konstantin, Taylor, Kent D., Thorand, Barbara, Thorsteinsdottir, Unnur, Tomlinson, Brian, Tran, Tam C., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Wacher-Rodarte, Niels, Wheeler, Eleanor, Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamamoto, Kenichi, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zawistowski, Matthew, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Fornage, Myriam, Hanis, Craig L., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Yokota, Mitsuhiro, Kardia, Sharon L. R., Peyser, Patricia A., Pankow, James S., Engert, James C., Bonnefond, Amélie, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Mook-Kanamori, Dennis O., Tuomi, Tiinamaija, Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Paré, Guillaume, Sale, Michèle M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, Chen, Yii-Der Ida, Rich, Stephen S., McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Ghanbari, Mohsen, Tai, E-Shyong, Dupuis, Josee, Kato, Norihiro, Laakso, Markku, Köttgen, Anna, Koh, Woon-Puay, Bowden, Donald W., Palmer, Colin N. A., Kooner, Jaspal S., Kooperberg, Charles, Liu, Simin, North, Kari E., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Wareham, Nicholas J., Lee, Juyoung, Kim, Bong-Jo, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Ahlqvist, Emma, Goodarzi, Mark O., Mohlke, Karen L., Langenberg, Claudia, Haiman, Christopher A., Loos, Ruth J. F., Florez, Jose C., Rader, Daniel J., Ritchie, Marylyn D., Zöllner, Sebastian, Mägi, Reedik, Marston, Nicholas A., Ruff, Christian T., van Heel, David A., Finer, Sarah, Denny, Joshua C., Yamauchi, Toshimasa, Kadowaki, Takashi, Chambers, John C., Ng, Maggie C. Y., Sim, Xueling, Below, Jennifer E., Tsao, Philip S., Chang, Kyong-Mi, McCarthy, Mark I., Meigs, James B., Mahajan, Anubha, Spracklen, Cassandra N., Mercader, Josep M., Boehnke, Michael, Rotter, Jerome I., Vujkovic, Marijana, Voight, Benjamin F., Morris, Andrew P., and Zeggini, Eleftheria
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- 2024
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20. Integrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk
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Yaohua Yang, Yaxin Chen, Shuai Xu, Xingyi Guo, Guochong Jia, Jie Ping, Xiang Shu, Tianying Zhao, Fangcheng Yuan, Gang Wang, Yufang Xie, Hang Ci, Hongmo Liu, Yawen Qi, Yongjun Liu, Dan Liu, Weimin Li, Fei Ye, Xiao-Ou Shu, Wei Zheng, Li Li, Qiuyin Cai, and Jirong Long
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Science - Abstract
Abstract The relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging resources from the Genotype-Tissue Expression consortium, here we develop genetic models to predict DNA methylation at CpG sites across the genome for seven tissues and apply these models to genome-wide association study data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P
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- 2024
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21. Circulating immune markers and risks of non-Hodgkin lymphoma subtypes: A pooled analysis.
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Rhee, Jongeun, Birmann, Brenda, De Roos, Anneclaire, Epstein, Mara, Martinez-Maza, Otoniel, Breen, Elizabeth, Magpantay, Larry, Levin, Lynn, Visvanathan, Kala, Hosgood, H, Rohan, Thomas, Smoller, Sylvia, Bassig, Bryan, Qi, Lihong, Shu, Xiao-Ou, Koh, Woon-Puay, Zheng, Wei, Yuan, Jian-Min, Weinstein, Stephanie, Albanes, Demetrius, Lan, Qing, Rothman, Nathaniel, and Purdue, Mark
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CXCL13 ,immune markers ,non-Hodgkin lymphoma ,sCD27 ,sCD30 ,Adult ,Humans ,Leukemia ,Lymphocytic ,Chronic ,B-Cell ,Lymphoma ,Non-Hodgkin ,Lymphoma ,Follicular ,Biomarkers ,Lymphoma ,Large B-Cell ,Diffuse ,Case-Control Studies ,Lymphoma ,Mantle-Cell - Abstract
Although prediagnostic circulating concentrations of the immune activation markers soluble CD27 (sCD27), sCD30 and chemokine ligand-13 (CXCL13) have been associated with non-Hodgkin lymphoma (NHL) risk, studies have been limited by sample size in associations with NHL subtypes. We pooled data from eight nested case-control studies to investigate subtype-specific relationships for these analytes. Using polytomous regression, we calculated odds ratios (ORs) with 95% confidence intervals (CIs) relating study-specific analyte tertiles to selected subtypes vs controls (n = 3310): chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL; n = 623), diffuse large B cell lymphoma (DLBCL; n = 621), follicular lymphoma (FL; n = 398), marginal zone lymphoma (MZL; n = 138), mantle cell lymphoma (MCL; n = 82) and T cell lymphoma (TCL; n = 92). We observed associations with DLBCL for elevated sCD27 [OR for third vs first tertile (ORT3 ) = 2.2, 95% CI = 1.6-3.1], sCD30 (ORT3 = 2.0, 95% CI = 1.6-2.5) and CXCL13 (ORT3 = 2.3, 95% CI = 1.8-3.0). We also observed associations with sCD27 for CLL/SLL (ORT3 = 3.3, 95% CI = 2.4-4.6), MZL (ORT3 = 7.7, 95% CI = 3.0-20.1) and TCL (ORT3 = 3.4, 95% CI = 1.5-7.7), and between sCD30 and FL (ORT3 = 2.7, 95% CI = 2.0-3.5). In analyses stratified by time from phlebotomy to case diagnosis, the sCD27-TCL and all three DLBCL associations were equivalent across both follow-up periods (
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- 2023
22. Associations of alcohol intake with gut microbiome: a prospective study in a predominantly low-income Black/African American population
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Liu, Lili, Nguyen, Sang M, Wang, Lei, Shi, Jiajun, Long, Jirong, Cai, Qiuyin, Shrubsole, Martha J, Shu, Xiao-Ou, Zheng, Wei, and Yu, Danxia
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- 2025
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23. Unveiling circRNA-mediated ceRNA networks in ischemic stroke by integrative analysis of multi-source gene expression profiling
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Ya Zhang and Xiao-Ou Zhang
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Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Background: Circular RNAs (circRNAs) are emerging as potential therapeutic targets for ischemic stroke (IS) due to their regulatory roles in inflammation and apoptosis. This study aimed to develop a comprehensive and robust IS-specific competing endogenous RNA (ceRNA) network to facilitate the identification of novel diagnostic and therapeutic targets. Methods: We integrated expression data from 15 IS studies using the Rank-In algorithm to minimize batch effects. Differentially expressed circRNAs, miRNAs, and mRNAs were identified by comparing IS and control samples. Functional enrichment analysis of differentially expressed circRNA host genes revealed significantly enriched pathways and Gene Ontology (GO) terms relevant to IS pathogenesis. We further predicted miRNA-circRNA and mRNA-miRNA interactions, enabling the construction of a comprehensive ceRNA network to identify circRNA-related genes with diagnostic potential for IS. Results: Integrated analysis revealed 199 differentially expressed circRNAs, 103 miRNAs, and 1736 mRNAs in IS patients. Functional enrichment analysis implicated these molecules in relevant pathways like the neurotrophin signaling pathway and p53 signaling pathway. The constructed circRNA-miRNA-mRNA regulatory network provided insights into potential mechanisms underlying IS. Three circRNA-related genes (RGS2, CDK5R1, and NSF) displayed promising diagnostic potential for IS when combined. Conclusions: We successfully constructed a robust and informative IS-specific ceRNA network by integrating data from diverse sources. This network identified differentially expressed RNAs and revealed enriched pathways potentially involved in IS pathogenesis. Notably, our analysis identified CDK5R1, RGS2, and NSF as potential diagnostic biomarkers for IS. This study sheds light on a circRNA-mediated regulatory network with potential diagnostic and therapeutic implications for ischemic stroke.
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- 2024
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24. A multi-scale attention mechanism for detecting defects in leather fabrics
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Hao Li, Yifan Liu, Huawei Xu, Ke Yang, Zhen Kang, Mengzhen Huang, Xiao Ou, Yuchen Zhao, and Tongzhen Xing
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Attention mechanism ,Multi-scale information ,Defect detection ,Convolutional Neural network ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Defect detection is critical to industrial quality control in leather production engineering. The various sizes and locations of defects in leather, as well as significant differences within the same class and indistinctive variations between different classes of defects, contribute to the complexity of the problem. To address this challenge, we propose a Multi-Layer Residual Convolutional Attention (MLRCA) approach. MLRCA enhances its ability to capture both intra-class and inter-class differences by enhancing the semantic feature representation in the backbone network. To improve multiscale fusion effects, we also incorporate the MLRCA module into the feature pyramid network (FPN) and propose a new multi-layer residual convolution attention feature pyramid network (ML-FPN). This approach enables more accurate identification of leather defects at a more detailed level by selectively capturing contextual information from different domains. We then implement the Side-Aware Boundary Localization (SABL) detection head, which accurately locates defects and helps the network distinguish between similar defect categories for more precise positioning. To validate the effectiveness of our approach, we conducted ablation experiments on the created leather dataset. Comparative experiments demonstrate the excellent capability of our model to detect minor defects. The model achieved 83.4, 89.7, and 85.6 for the AP, AP50, and AP75 evaluation metrics. In addition, the model achieves 71.3, 89.9, and 88.9 for APS, APM, and APL. Our approach has been confirmed feasible through experimentation and provides new insights for automated leather defect detection methods.
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- 2024
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25. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population
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Shi, Jianxin, Shiraishi, Kouya, Choi, Jiyeon, Matsuo, Keitaro, Chen, Tzu-Yu, Dai, Juncheng, Hung, Rayjean J, Chen, Kexin, Shu, Xiao-Ou, Kim, Young Tae, Landi, Maria Teresa, Lin, Dongxin, Zheng, Wei, Yin, Zhihua, Zhou, Baosen, Song, Bao, Wang, Jiucun, Seow, Wei Jie, Song, Lei, Chang, I-Shou, Hu, Wei, Chien, Li-Hsin, Cai, Qiuyin, Hong, Yun-Chul, Kim, Hee Nam, Wu, Yi-Long, Wong, Maria Pik, Richardson, Brian Douglas, Funderburk, Karen M, Li, Shilan, Zhang, Tongwu, Breeze, Charles, Wang, Zhaoming, Blechter, Batel, Bassig, Bryan A, Kim, Jin Hee, Albanes, Demetrius, Wong, Jason YY, Shin, Min-Ho, Chung, Lap Ping, Yang, Yang, An, She-Juan, Zheng, Hong, Yatabe, Yasushi, Zhang, Xu-Chao, Kim, Young-Chul, Caporaso, Neil E, Chang, Jiang, Ho, James Chung Man, Kubo, Michiaki, Daigo, Yataro, Song, Minsun, Momozawa, Yukihide, Kamatani, Yoichiro, Kobayashi, Masashi, Okubo, Kenichi, Honda, Takayuki, Hosgood, Dean H, Kunitoh, Hideo, Patel, Harsh, Watanabe, Shun-ichi, Miyagi, Yohei, Nakayama, Haruhiko, Matsumoto, Shingo, Horinouchi, Hidehito, Tsuboi, Masahiro, Hamamoto, Ryuji, Goto, Koichi, Ohe, Yuichiro, Takahashi, Atsushi, Goto, Akiteru, Minamiya, Yoshihiro, Hara, Megumi, Nishida, Yuichiro, Takeuchi, Kenji, Wakai, Kenji, Matsuda, Koichi, Murakami, Yoshinori, Shimizu, Kimihiro, Suzuki, Hiroyuki, Saito, Motonobu, Ohtaki, Yoichi, Tanaka, Kazumi, Wu, Tangchun, Wei, Fusheng, Dai, Hongji, Machiela, Mitchell J, Su, Jian, Kim, Yeul Hong, Oh, In-Jae, Lee, Victor Ho Fun, Chang, Gee-Chen, Tsai, Ying-Huang, Chen, Kuan-Yu, Huang, Ming-Shyan, Su, Wu-Chou, Chen, Yuh-Min, Seow, Adeline, Park, Jae Yong, and Kweon, Sun-Seog
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Genetics ,Cancer ,Clinical Research ,Human Genome ,Prevention ,Lung ,Lung Cancer ,Tobacco ,Tobacco Smoke and Health ,2.1 Biological and endogenous factors ,Aetiology ,Respiratory ,Humans ,Genome-Wide Association Study ,Genetic Predisposition to Disease ,Adenocarcinoma of Lung ,Asia ,Eastern ,Lung Neoplasms ,Polymorphism ,Single Nucleotide - 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 (Pinteraction = 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.
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- 2023
26. Distinct Reproductive Risk Profiles for Intrinsic-Like Breast Cancer Subtypes: Pooled Analysis of Population-Based Studies
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Jung, Audrey Y, Ahearn, Thomas U, Behrens, Sabine, Middha, Pooja, Bolla, Manjeet K, Wang, Qin, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Freeman, Laura E Beane, Becher, Heiko, Brenner, Hermann, Canzian, Federico, Carey, Lisa A, Consortium, CTS, Czene, Kamila, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Figueroa, Jonine D, Fritschi, Lin, Gabrielson, Marike, Giles, Graham G, Guénel, Pascal, Hadjisavvas, Andreas, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hoppe, Reiner, Hopper, John L, Howell, Anthony, Hunter, David J, Hüsing, Anika, Kaaks, Rudolf, Kosma, Veli-Matti, Koutros, Stella, Kraft, Peter, Lacey, James V, Le Marchand, Loic, Lissowska, Jolanta, Loizidou, Maria A, Mannermaa, Arto, Maurer, Tabea, Murphy, Rachel A, Olshan, Andrew F, Olsson, Håkan, Patel, Alpa V, Perou, Charles M, Rennert, Gad, Shibli, Rana, Shu, Xiao-Ou, Southey, Melissa C, Stone, Jennifer, Tamimi, Rulla M, Teras, Lauren R, Troester, Melissa A, Truong, Thérèse, Vachon, Celine M, Wang, Sophia S, Wolk, Alicja, Wu, Anna H, Yang, Xiaohong R, Zheng, Wei, Dunning, Alison M, Pharoah, Paul DP, Easton, Douglas F, Milne, Roger L, Chatterjee, Nilanjan, Schmidt, Marjanka K, García-Closas, Montserrat, and Chang-Claude, Jenny
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Aging ,Cancer ,Clinical Research ,Women's Health ,Breast Cancer ,4.1 Discovery and preclinical testing of markers and technologies ,Female ,Humans ,Breast Neoplasms ,Receptor ,ErbB-2 ,Receptors ,Progesterone ,Receptors ,Estrogen ,Triple Negative Breast Neoplasms ,Case-Control Studies ,Risk Factors ,Biomarkers ,Tumor ,CTS Consortium ,Receptor ,erbB-2 ,Oncology & Carcinogenesis ,Oncology and carcinogenesis - Abstract
BackgroundReproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear.MethodsAnalyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided.ResultsCompared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2-like, and HER2-enriched-like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like.ConclusionsThis large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.
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- 2022
27. Sludge-derived biostimulants promote glycosylation of tricin and luteolin in the flavone and flavonol biosynthesis to enhance anti-inflammatory activities of rice
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Yuan, Xin, Hua, Yu, Chen, Shu-xian, Song, Qi, Li, Xiao-ou, Zhang, Yue, and Dai, Xiao-hu
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- 2024
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28. Waveguide distribution system of the HEPS linac
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He, Xiang, Zhang, Jing-Ru, Shi, Hua, Xiao, Ou-Zheng, Liu, Jing-Dong, Gan, Nan, Zeng, Hao, Li, Xiao-Ping, Shu, Guan, Zhao, Feng-Li, Wang, Sheng-Chang, Ma, Xin-Peng, Meng, Cai, He, Da-Yong, Li, Fei, Dong, Dong, Zhou, Zu-Sheng, Li, Jing-Yi, Wang, Jian-Li, Deng, Bing-Lin, Tian, Pi-Long, Wang, Xu-Jian, Song, Hong, Yang, Qi, and Kong, Xiang-Cheng
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- 2023
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29. Diabetes and gastric cancer incidence and mortality in the Asia Cohort Consortium: A pooled analysis of more than a half million participants
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Katherine De la Torre, Minkyo Song, Sarah Krull Abe, Md. Shafiur Rahman, Md. Rashedul Islam, Eiko Saito, Sukhong Min, Dan Huang, Yu Chen, Prakash C. Gupta, Norie Sawada, Akiko Tamakoshi, Xiao‐Ou Shu, Wanqing Wen, Ritsu Sakata, Jeongseon Kim, Chisato Nagata, Hidemi Ito, Sue K. Park, Myung‐Hee Shin, Mangesh S. Pednekar, Shoichiro Tsugane, Takashi Kimura, Yu‐Tang Gao, Hui Cai, Keiko Wada, Isao Oze, Aesun Shin, Yoon‐Ok Ahn, Habibul Ahsan, Paolo Boffetta, Kee Seng Chia, Keitaro Matsuo, You‐Lin Qiao, Nathaniel Rothman, Wei Zheng, Manami Inoue, and Daehee Kang
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Asia ,diabetes ,gastric cancer ,incidence ,mortality ,prospective studies ,Diseases of the endocrine glands. Clinical endocrinology ,RC648-665 - Abstract
Abstract Background Evidence suggests a possible link between diabetes and gastric cancer risk, but the findings remain inconclusive, with limited studies in the Asian population. We aimed to assess the impact of diabetes and diabetes duration on the development of gastric cancer overall, by anatomical and histological subtypes. Methods A pooled analysis was conducted using 12 prospective studies included in the Asia Cohort Consortium. Among 558 981 participants (median age 52), after a median follow‐up of 14.9 years and 10.5 years, 8556 incident primary gastric cancers and 8058 gastric cancer deaths occurred, respectively. Cox proportional hazard regression models were used to estimate study‐specific hazard ratios (HRs) and 95% confidence intervals (CIs) and pooled using random‐effects meta‐analyses. Results Diabetes was associated with an increased incidence of overall gastric cancer (HR 1.15, 95% CI 1.06–1.25). The risk association did not differ significantly by sex (women vs men: HR 1.31, 95% CI 1.07–1.60 vs 1.12, 1.01–1.23), anatomical subsites (noncardia vs cardia: 1.14, 1.02–1.28 vs 1.17, 0.77–1.78) and histological subtypes (intestinal vs diffuse: 1.22, 1.02–1.46 vs 1.00, 0.62–1.61). Gastric cancer risk increased significantly during the first decade following diabetes diagnosis (HR 4.70, 95% CI 3.77–5.86), and decreased with time (nonlinear p
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- 2024
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30. Blood Lipids, Lipoproteins, and Apolipoproteins With Risk of Coronary Heart Disease: A Prospective Study Among Racially Diverse Populations
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Kui Deng, Xiong‐Fei Pan, Markus W. Voehler, Qiuyin Cai, Hui Cai, Xiao‐Ou Shu, Deepak K. Gupta, Loren Lipworth, Wei Zheng, and Danxia Yu
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apolipoprotein ,coronary heart disease ,lipid ,lipoprotein ,nuclear magnetic resonance ,racially diverse populations ,Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Abstract
Background Comprehensive blood lipoprotein profiles and their association with incident coronary heart disease (CHD) among racially and geographically diverse populations remain understudied. Methods and Results We conducted nested case–control studies of CHD among 3438 individuals (1719 pairs), including 1084 White Americans (542 pairs), 1244 Black Americans (622 pairs), and 1110 Chinese adults (555 pairs). We examined 36 plasma lipids, lipoproteins, and apolipoproteins, measured by nuclear magnetic resonance spectroscopy, with incident CHD among all participants and subgroups by demographics, lifestyle, and metabolic health status using conditional or unconditional logistic regression adjusted for potential confounders. Conventionally measured blood lipids, that is, total cholesterol, triglycerides, low‐density lipoprotein‐cholesterol, and high‐density lipoprotein‐cholesterol, were each associated with incident CHD, with odds ratios (ORs) being 1.33, 1.32, 1.24, and 0.79 per 1‐SD increase among all participants. Seventeen lipoprotein biomarkers showed numerically stronger associations than conventional lipids, with ORs per 1‐SD among all participants ranging from 1.35 to 1.57 and a negative OR of 0.78 (all false discovery rate
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- 2024
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31. Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes
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Moore, Jill E, Purcaro, Michael J, Pratt, Henry E, Epstein, Charles B, Shoresh, Noam, Adrian, Jessika, Kawli, Trupti, Davis, Carrie A, Dobin, Alexander, Kaul, Rajinder, Halow, Jessica, Van Nostrand, Eric L, Freese, Peter, Gorkin, David U, Shen, Yin, He, Yupeng, Mackiewicz, Mark, Pauli-Behn, Florencia, Williams, Brian A, Mortazavi, Ali, Keller, Cheryl A, Zhang, Xiao-Ou, Elhajjajy, Shaimae I, Huey, Jack, Dickel, Diane E, Snetkova, Valentina, Wei, Xintao, Wang, Xiaofeng, Rivera-Mulia, Juan Carlos, Rozowsky, Joel, Zhang, Jing, Chhetri, Surya B, Zhang, Jialing, Victorsen, Alec, White, Kevin P, Visel, Axel, Yeo, Gene W, Burge, Christopher B, Lécuyer, Eric, Gilbert, David M, Dekker, Job, Rinn, John, Mendenhall, Eric M, Ecker, Joseph R, Kellis, Manolis, Klein, Robert J, Noble, William S, Kundaje, Anshul, Guigó, Roderic, Farnham, Peggy J, Cherry, J Michael, Myers, Richard M, Ren, Bing, Graveley, Brenton R, Gerstein, Mark B, Pennacchio, Len A, Snyder, Michael P, Bernstein, Bradley E, Wold, Barbara, Hardison, Ross C, Gingeras, Thomas R, Stamatoyannopoulos, John A, and Weng, Zhiping
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ENCODE Project Consortium ,General Science & Technology - Abstract
In the version of this article initially published, two members of the ENCODE Project Consortium were missing from the author list. Rizi Ai (Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA) and Shantao Li (Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA) are now included in the author list. These errors have been corrected in the online version of the article.
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- 2022
32. Allele-specific binding (ASB) analyzer for annotation of allele-specific binding SNPs
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Ying Li, Xiao-Ou Zhang, Yan Liu, and Aiping Lu
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Allele-specific binding ,Single nucleotide polymorphism ,Motif analysis ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Allele-specific binding (ASB) events occur when transcription factors (TFs) bind more favorably to one of the two parental alleles at heterozygous single nucleotide polymorphisms (SNPs). Evidence suggests that ASB events could reveal the impact of sequence variations on TF binding and may have implications for the risk of diseases. Results Here we present ASB-analyzer, a software platform that enables the users to quickly and efficiently input raw sequencing data to generate individual reports containing the cytogenetic map of ASB SNPs and their associated phenotypes. This interactive tool thereby combines ASB SNP identification, biological annotation, motif analysis, phenotype associations and report summary in one pipeline. With this pipeline, we identified 3772 ASB SNPs from thirty GM12878 ChIP-seq datasets and demonstrated that the ASB SNPs were more likely to be enriched at important sites in TF-binding domains. Conclusions ASB-analyzer is a user-friendly tool that enables the detection, characterization and visualization of ASB SNPs. It is implemented in Python, R and bash shell and packaged in the Conda environment. It is available as an open-source tool on GitHub at https://github.com/Liying1996/ASBanalyzer .
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- 2023
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33. Inflammation-associated ectopic mineralization
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Jing-Han Song, Ming-Yi Liu, Yu-Xuan Ma, Qian-Qian Wan, Jing Li, Xiao-Ou Diao, and Li-Na Niu
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Immune cells ,Inflammatory mediators ,Osteogenic signaling pathways ,Ectopic mineralization ,Inflammatory conditions ,Anti-inflammatory treatments ,Science (General) ,Q1-390 - Abstract
Ectopic mineralization refers to the deposition of mineralized complexes in the extracellular matrix of soft tissues. Calcific aortic valve disease, vascular calcification, gallstones, kidney stones, and abnormal mineralization in arthritis are common examples of ectopic mineralization. They are debilitating diseases and exhibit excess mortality, disability, and morbidity, which impose on patients with limited social or financial resources. Recent recognition that inflammation plays an important role in ectopic mineralization has attracted the attention of scientists from different research fields. In the present review, we summarize the origin of inflammation in ectopic mineralization and different channels whereby inflammation drives the initiation and progression of ectopic mineralization. The current knowledge of inflammatory milieu in pathological mineralization is reviewed, including how immune cells, pro-inflammatory mediators, and osteogenic signaling pathways induce the osteogenic transition of connective tissue cells, providing nucleating sites and assembly of aberrant minerals. Advances in the understanding of the underlying mechanisms involved in inflammatory-mediated ectopic mineralization enable novel strategies to be developed that may lead to the resolution of these enervating conditions.
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- 2023
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34. Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants
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Yang, Yaohua, Xu, Shuai, Jia, Guochong, Yuan, Fangcheng, Ping, Jie, Guo, Xingyi, Tao, Ran, Shu, Xiao-Ou, Zheng, Wei, Long, Jirong, and Cai, Qiuyin
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- 2023
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35. Polymorphisms in genes of melatonin biosynthesis and signaling support the light-at-night hypothesis for breast cancer
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Wichert, Katharina, Hoppe, Reiner, Ickstadt, Katja, Behrens, Thomas, Winter, Stefan, Herold, Robert, Terschüren, Claudia, Lo, Wing-Yee, Guénel, Pascal, Truong, Thérèse, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Lush, Michael, Andrulis, Irene L., Brenner, Hermann, Chang-Claude, Jenny, Cox, Angela, Cross, Simon S., Czene, Kamila, Eriksson, Mikael, Figueroa, Jonine D., García-Closas, Montserrat, Goldberg, Mark S., Hamann, Ute, He, Wei, Holleczek, Bernd, Hopper, John L., Jakubowska, Anna, Ko, Yon-Dschun, Lubiński, Jan, Mulligan, Anna Marie, Obi, Nadia, Rhenius, Valerie, Shah, Mitul, Shu, Xiao-Ou, Simard, Jacques, Southey, Melissa C., Zheng, Wei, Dunning, Alison M., Pharoah, Paul D. P., Hall, Per, Easton, Douglas F., Brüning, Thomas, Brauch, Hiltrud, Harth, Volker, and Rabstein, Sylvia
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- 2023
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36. Association between chronic pain and quality of life in long-term breast cancer survivors: a prospective analysis
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Yin, Michelle, Gu, Kai, Cai, Hui, and Shu, Xiao-Ou
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- 2023
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37. Impacts of Poverty and Lifestyles on Mortality: A Cohort Study in Predominantly Low-Income Americans
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Liu, Lili, Wen, Wanqing, Shrubsole, Martha J., Lipworth, Loren E., Mumma, Michael T., Ackerly, Brooke A., Shu, Xiao-Ou, Blot, William J., and Zheng, Wei
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- 2024
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38. Integration of high-resolution promoter profiling assays reveals novel, cell type-specific transcription start sites across 115 human cell and tissue types
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Moore, Jill E, Zhang, Xiao-Ou, Elhajjajy, Shaimae I, Fan, Kaili, Pratt, Henry E, Reese, Fairlie, Mortazavi, Ali, and Weng, Zhiping
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Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Biotechnology ,Human Genome ,Generic health relevance ,Gene Expression Regulation ,Genome-Wide Association Study ,Humans ,Promoter Regions ,Genetic ,Transcription Initiation Site ,Medical and Health Sciences ,Bioinformatics - Abstract
Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type-specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks are primarily proximal to GENCODE-annotated TSSs and are concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3' ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations are supported by epigenomic and other transcriptomic data sets. To show the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI genome-wide association study (GWAS) catalog and identified new candidate GWAS genes. Overall, our work shows the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.
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- 2022
39. Multi-ancestry genome-wide gene–sleep interactions identify novel loci for blood pressure
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Wang, Heming, Noordam, Raymond, Cade, Brian E, Schwander, Karen, Winkler, Thomas W, Lee, Jiwon, Sung, Yun Ju, Bentley, Amy R, Manning, Alisa K, Aschard, Hugues, Kilpeläinen, Tuomas O, Ilkov, Marjan, Brown, Michael R, Horimoto, Andrea R, Richard, Melissa, Bartz, Traci M, Vojinovic, Dina, Lim, Elise, Nierenberg, Jovia L, Liu, Yongmei, Chitrala, Kumaraswamynaidu, Rankinen, Tuomo, Musani, Solomon K, Franceschini, Nora, Rauramaa, Rainer, Alver, Maris, Zee, Phyllis C, Harris, Sarah E, van der Most, Peter J, Nolte, Ilja M, Munroe, Patricia B, Palmer, Nicholette D, Kühnel, Brigitte, Weiss, Stefan, Wen, Wanqing, Hall, Kelly A, Lyytikäinen, Leo-Pekka, O’Connell, Jeff, Eiriksdottir, Gudny, Launer, Lenore J, de Vries, Paul S, Arking, Dan E, Chen, Han, Boerwinkle, Eric, Krieger, Jose E, Schreiner, Pamela J, Sidney, Stephen, Shikany, James M, Rice, Kenneth, Chen, Yii-Der Ida, Gharib, Sina A, Bis, Joshua C, Luik, Annemarie I, Ikram, M Arfan, Uitterlinden, André G, Amin, Najaf, Xu, Hanfei, Levy, Daniel, He, Jiang, Lohman, Kurt K, Zonderman, Alan B, Rice, Treva K, Sims, Mario, Wilson, Gregory, Sofer, Tamar, Rich, Stephen S, Palmas, Walter, Yao, Jie, Guo, Xiuqing, Rotter, Jerome I, Biermasz, Nienke R, Mook-Kanamori, Dennis O, Martin, Lisa W, Barac, Ana, Wallace, Robert B, Gottlieb, Daniel J, Komulainen, Pirjo, Heikkinen, Sami, Mägi, Reedik, Milani, Lili, Metspalu, Andres, Starr, John M, Milaneschi, Yuri, Waken, RJ, Gao, Chuan, Waldenberger, Melanie, Peters, Annette, Strauch, Konstantin, Meitinger, Thomas, Roenneberg, Till, Völker, Uwe, Dörr, Marcus, Shu, Xiao-Ou, Mukherjee, Sutapa, Hillman, David R, Kähönen, Mika, Wagenknecht, Lynne E, Gieger, Christian, Grabe, Hans J, and Zheng, Wei
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Human Genome ,Sleep Research ,Clinical Research ,Biotechnology ,Hypertension ,Genetics ,Aetiology ,2.1 Biological and endogenous factors ,Cardiovascular ,Blood Pressure ,Genetic Loci ,Genome-Wide Association Study ,Humans ,Polymorphism ,Single Nucleotide ,Sleep ,Biological Sciences ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Psychiatry - Abstract
Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 Pjoint
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- 2021
40. Lung Cancer Risk Prediction Models for Asian Ever-Smokers
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Yang, Jae Jeong, Wen, Wanqing, Zahed, Hana, Zheng, Wei, Lan, Qing, Abe, Sarah K., Rahman, Md. Shafiur, Islam, Md. Rashedul, Saito, Eiko, Gupta, Prakash C., Tamakoshi, Akiko, Koh, Woon-Puay, Gao, Yu-Tang, Sakata, Ritsu, Tsuji, Ichiro, Malekzadeh, Reza, Sugawara, Yumi, Kim, Jeongseon, Ito, Hidemi, Nagata, Chisato, You, San-Lin, Park, Sue K., Yuan, Jian-Min, Shin, Myung-Hee, Kweon, Sun-Seog, Yi, Sang-Wook, Pednekar, Mangesh S., Kimura, Takashi, Cai, Hui, Lu, Yukai, Etemadi, Arash, Kanemura, Seiki, Wada, Keiko, Chen, Chien-Jen, Shin, Aesun, Wang, Renwei, Ahn, Yoon-Ok, Shin, Min-Ho, Ohrr, Heechoul, Sheikh, Mahdi, Blechter, Batel, Ahsan, Habibul, Boffetta, Paolo, Chia, Kee Seng, Matsuo, Keitaro, Qiao, You-Lin, Rothman, Nathaniel, Inoue, Manami, Kang, Daehee, Robbins, Hilary A., and Shu, Xiao-Ou
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- 2024
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41. Lifestyle factors, genetic susceptibility to obesity and their interactions on coronary artery disease risk: A cohort study in the UK Biobank
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Choi, Jungyoon, Wen, Wanqing, Jia, Guochong, Tao, Ran, Long, Jirong, Shu, Xiao-Ou, and Zheng, Wei
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- 2024
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42. A prospective observation of influence of anti-VEGF on optic disc vasculature in nAMD patients
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Zhuang, Xuenan, Su, Yongyue, Li, Miaoling, Zhang, Liang, Mi, Lan, Ji, Yuying, Deng, Fei, Xiao, Ou, Zhang, Xiongze, Zhou, Lijun, Cao, Dan, He, Guiqin, Zeng, Yunkao, Pu, Jiaxin, Hao, Xinlei, Chen, Xuelin, Gan, Yuhong, Zhang, Yining, and Wen, Feng
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- 2024
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43. Association of glycaemic index and glycaemic load with type 2 diabetes, cardiovascular disease, cancer, and all-cause mortality: a meta-analysis of mega cohorts of more than 100 000 participants
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Balachandran, Bashyam, Zurbau, Andreea, Wang, Xunan, Liang, Fred, Yang, Wanning, Jenkins, David J A, Willett, Walter C, Yusuf, Salim, Hu, Frank B, Glenn, Andrea J, Liu, Simin, Mente, Andrew, Miller, Victoria, Bangdiwala, Shrikant I, Gerstein, Hertzel C, Sieri, Sabina, Ferrari, Pietro, Patel, Alpa V, McCullough, Marjorie L, Le Marchand, Loïc, Freedman, Neal D, Loftfield, Erikka, Sinha, Rashmi, Shu, Xiao-Ou, Touvier, Mathilde, Sawada, Norie, Tsugane, Shoichiro, van den Brandt, Piet A, Shuval, Kerem, Khan, Tauseef Ahmad, Paquette, Melanie, Sahye-Pudaruth, Sandhya, Patel, Darshna, Siu, Teenie Fei Yi, Srichaikul, Korbua, Kendall, Cyril W C, and Sievenpiper, John L
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- 2024
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44. Prevalence of metabolic syndrome among Vietnamese adult employees
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Ho, Nhan T., Tran, Mo T., Tran, Chi T.D., Vanderbloemen, Laura, Pham, Tung T., Hoang, Long B., Nguyen, Quyet V., Dorn, Joan, Trevisan, Maurizio, Shu, Xiao-Ou, and Le, Linh C.
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- 2024
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45. Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations
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Minta Thomas, Yu-Ru Su, Elisabeth A. Rosenthal, Lori C. Sakoda, Stephanie L. Schmit, Maria N. Timofeeva, Zhishan Chen, Ceres Fernandez-Rozadilla, Philip J. Law, Neil Murphy, Robert Carreras-Torres, Virginia Diez-Obrero, Franzel J. B. van Duijnhoven, Shangqing Jiang, Aesun Shin, Alicja Wolk, Amanda I. Phipps, Andrea Burnett-Hartman, Andrea Gsur, Andrew T. Chan, Ann G. Zauber, Anna H. Wu, Annika Lindblom, Caroline Y. Um, Catherine M. Tangen, Chris Gignoux, Christina Newton, Christopher A. Haiman, Conghui Qu, D. Timothy Bishop, Daniel D. Buchanan, David R. Crosslin, David V. Conti, Dong-Hyun Kim, Elizabeth Hauser, Emily White, Erin Siegel, Fredrick R. Schumacher, Gad Rennert, Graham G. Giles, Heather Hampel, Hermann Brenner, Isao Oze, Jae Hwan Oh, Jeffrey K. Lee, Jennifer L. Schneider, Jenny Chang-Claude, Jeongseon Kim, Jeroen R. Huyghe, Jiayin Zheng, Jochen Hampe, Joel Greenson, John L. Hopper, Julie R. Palmer, Kala Visvanathan, Keitaro Matsuo, Koichi Matsuda, Keum Ji Jung, Li Li, Loic Le Marchand, Ludmila Vodickova, Luis Bujanda, Marc J. Gunter, Marco Matejcic, Mark A. Jenkins, Martha L. Slattery, Mauro D’Amato, Meilin Wang, Michael Hoffmeister, Michael O. Woods, Michelle Kim, Mingyang Song, Motoki Iwasaki, Mulong Du, Natalia Udaltsova, Norie Sawada, Pavel Vodicka, Peter T. Campbell, Polly A. Newcomb, Qiuyin Cai, Rachel Pearlman, Rish K. Pai, Robert E. Schoen, Robert S. Steinfelder, Robert W. Haile, Rosita Vandenputtelaar, Ross L. Prentice, Sébastien Küry, Sergi Castellví-Bel, Shoichiro Tsugane, Sonja I. Berndt, Soo Chin Lee, Stefanie Brezina, Stephanie J. Weinstein, Stephen J. Chanock, Sun Ha Jee, Sun-Seog Kweon, Susan Vadaparampil, Tabitha A. Harrison, Taiki Yamaji, Temitope O. Keku, Veronika Vymetalkova, Volker Arndt, Wei-Hua Jia, Xiao-Ou Shu, Yi Lin, Yoon-Ok Ahn, Zsofia K. Stadler, Bethany Van Guelpen, Cornelia M. Ulrich, Elizabeth A. Platz, John D. Potter, Christopher I. Li, Reinier Meester, Victor Moreno, Jane C. Figueiredo, Graham Casey, Iris Lansdorp Vogelaar, Malcolm G. Dunlop, Stephen B. Gruber, Richard B. Hayes, Paul D. P. Pharoah, Richard S. Houlston, Gail P. Jarvik, Ian P. Tomlinson, Wei Zheng, Douglas A. Corley, Ulrike Peters, and Li Hsu
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Science - Abstract
Abstract Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values
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- 2023
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46. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
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Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K. Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J. Aronson, Paul L. Auer, Annelie Augustinsson, Thaïs Baert, Laura E. Beane Freeman, Heiko Becher, Matthias W. Beckmann, Javier Benitez, Stig E. Bojesen, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E. Castelao, Stephen J. Chanock, Georgia Chenevix-Trench, CTS Consortium, Emilie Cordina-Duverger, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A. Heather Eliassen, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Jonine D. Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G. Giles, Anna González-Neira, Felix Grassmann, Anne Grundy, Pascal Guénel, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Susan E. Hankinson, Elaine F. Harkness, Bernd Holleczek, Reiner Hoppe, John L. Hopper, Richard S. Houlston, Anthony Howell, David J. Hunter, Christian Ingvar, ABCTB Investigators, kConFab Investigators, Karolin Isaksson, Helena Jernström, Esther M. John, Michael E. Jones, Rudolf Kaaks, Renske Keeman, Cari M. Kitahara, Yon-Dschun Ko, Stella Koutros, Allison W. Kurian, James V. Lacey, Diether Lambrechts, Nicole L. Larson, Susanna Larsson, Loic Le Marchand, Flavio Lejbkowicz, Shuai Li, Martha Linet, Jolanta Lissowska, Maria Elena Martinez, Tabea Maurer, Anna Marie Mulligan, Claire Mulot, Rachel A. Murphy, William G. Newman, Sune F. Nielsen, Børge G. Nordestgaard, Aaron Norman, Katie M. O’Brien, Janet E. Olson, Alpa V. Patel, Ross Prentice, Erika Rees-Punia, Gad Rennert, Valerie Rhenius, Kathryn J. Ruddy, Dale P. Sandler, Christopher G. Scott, Mitul Shah, Xiao-Ou Shu, Ann Smeets, Melissa C. Southey, Jennifer Stone, Rulla M. Tamimi, Jack A. Taylor, Lauren R. Teras, Katarzyna Tomczyk, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Sophia S. Wang, Clarice R. Weinberg, Hans Wildiers, Walter Willett, Stacey J. Winham, Alicja Wolk, Xiaohong R. Yang, M. Pilar Zamora, Wei Zheng, Argyrios Ziogas, Alison M. Dunning, Paul D. P. Pharoah, Montserrat García-Closas, Marjanka K. Schmidt, Peter Kraft, Roger L. Milne, Sara Lindström, Douglas F. Easton, and Jenny Chang-Claude
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Breast cancer ,Gene-environment interactions ,Genetic epidemiology ,European ancestry ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Background Genome-wide studies of gene–environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. Methods Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene–environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. Results Assuming a 1 × 10–5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability
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- 2023
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47. Gut Microbiome of Patients With Breast Cancer in Vietnam
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Sang M. Nguyen, Huong T.T. Tran, Jirong Long, Martha J. Shrubsole, Hui Cai, Yaohua Yang, Lan M. Nguyen, Giang H. Nguyen, Chu V. Nguyen, To V. Ta, Jie Wu, Qiuyin Cai, Wei Zheng, Thuan V. Tran, and Xiao-Ou Shu
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
PURPOSEGut microbiota play an important role in human health, including cancer. Cancer and its treatment, in turn, may alter the gut microbiome. To understand this complex relationship, we profiled the gut microbiome of 356 Vietnamese patients with breast cancer.MATERIALS AND METHODSStool samples were collected before chemotherapy, with 162 pre- and 194 postsurgery. The gut microbiome was measured by shotgun metagenomic sequencing. Associations of gut microbial diversity, taxa abundance, and gut microbiome health index (GMHI) with sociodemographic, clinical factors, and tumor characteristics were evaluated.RESULTSPostsurgery samples were associated with significantly lower α- and β-diversities (P < .001) and showed significant differences in the abundance of 15% of 2,864 investigated taxa (false discovery rate [FDR]
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- 2024
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48. A cross-sectional study of inflammatory markers as determinants of circulating kynurenines in the Lung Cancer Cohort Consortium
- Author
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Midttun, Øivind, Ulvik, Arve, Meyer, Klaus, Zahed, Hana, Giles, Graham G., Manjer, Jonas, Sandsveden, Malte, Langhammer, Arnulf, Sørgjerd, Elin Pettersen, Behndig, Annelie F., Johansson, Mikael, Freedman, Neal D., Huang, Wen-Yi, Chen, Chu, Prentice, Ross, Stevens, Victoria L., Wang, Ying, Le Marchand, Loïc, Weinstein, Stephanie J., Cai, Qiuyin, Arslan, Alan A., Chen, Yu, Shu, Xiao-Ou, Zheng, Wei, Yuan, Jian-Min, Koh, Woon-Puay, Visvanathan, Kala, Sesso, Howard D., Zhang, Xuehong, Gaziano, J. Michael, Fanidi, Anouar, Robbins, Hilary A., Brennan, Paul, Johansson, Mattias, and Ueland, Per M.
- Published
- 2023
- Full Text
- View/download PDF
49. A novel capsule endoscopy for upper and mid-GI tract: the UMGI capsule
- Author
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Jiang, Bin, Qian, Yang-Yang, Wang, Yuan-Chen, Pan, Jun, Jiang, Xi, Zhu, Jia-Hui, Qiu, Xiao-Ou, Zhou, Wei, Li, Zhao-Shen, and Liao, Zhuan
- Published
- 2023
- Full Text
- View/download PDF
50. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry
- Author
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Mueller, Stefanie H., Lai, Alvina G., Valkovskaya, Maria, Michailidou, Kyriaki, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Lush, Michael, Abu-Ful, Zomoruda, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antonenkova, Natalia N., Arndt, Volker, Aronson, Kristan J., Augustinsson, Annelie, Baert, Thais, Freeman, Laura E. Beane, Beckmann, Matthias W., Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia V., Bojesen, Stig E., Bonanni, Bernardo, Brenner, Hermann, Brucker, Sara Y., Buys, Saundra S., Castelao, Jose E., Chan, Tsun L., Chang-Claude, Jenny, Chanock, Stephen J., Choi, Ji-Yeob, Chung, Wendy K., Colonna, Sarah V., Cornelissen, Sten, Couch, Fergus J., Czene, Kamila, Daly, Mary B., Devilee, Peter, Dörk, Thilo, Dossus, Laure, Dwek, Miriam, Eccles, Diana M., Ekici, Arif B., Eliassen, A. Heather, Engel, Christoph, Evans, D. Gareth, Fasching, Peter A., Fletcher, Olivia, Flyger, Henrik, Gago-Dominguez, Manuela, Gao, Yu-Tang, García-Closas, Montserrat, García-Sáenz, José A., Genkinger, Jeanine, Gentry-Maharaj, Aleksandra, Grassmann, Felix, Guénel, Pascal, Gündert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A., Håkansson, Niclas, Hall, Per, Harkness, Elaine F., Harrington, Patricia A., Hartikainen, Jaana M., Hartman, Mikael, Hein, Alexander, Ho, Weang-Kee, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Houlston, Richard S., Howell, Anthony, Hunter, David J., Huo, Dezheng, Ito, Hidemi, Iwasaki, Motoki, Jakubowska, Anna, Janni, Wolfgang, John, Esther M., Jones, Michael E., Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Khusnutdinova, Elza K., Kim, Sung-Won, Kitahara, Cari M., Koutros, Stella, Kraft, Peter, Kristensen, Vessela N., Kubelka-Sabit, Katerina, Kurian, Allison W., Kwong, Ava, Lacey, James V., Lambrechts, Diether, Le Marchand, Loic, Li, Jingmei, Linet, Martha, Lo, Wing-Yee, Long, Jirong, Lophatananon, Artitaya, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Matsuo, Keitaro, Mavroudis, Dimitrios, Menon, Usha, Muir, Kenneth, Murphy, Rachel A., Nevanlinna, Heli, Newman, William G., Niederacher, Dieter, O’Brien, Katie M., Obi, Nadia, Offit, Kenneth, Olopade, Olufunmilayo I., Olshan, Andrew F., Olsson, Håkan, Park, Sue K., Patel, Alpa V., Patel, Achal, Perou, Charles M., Peto, Julian, Pharoah, Paul D. P., Plaseska-Karanfilska, Dijana, Presneau, Nadege, Rack, Brigitte, Radice, Paolo, Ramachandran, Dhanya, Rashid, Muhammad U., Rennert, Gad, Romero, Atocha, Ruddy, Kathryn J., Ruebner, Matthias, Saloustros, Emmanouil, Sandler, Dale P., Sawyer, Elinor J., Schmidt, Marjanka K., Schmutzler, Rita K., Schneider, Michael O., Scott, Christopher, Shah, Mitul, Sharma, Priyanka, Shen, Chen-Yang, Shu, Xiao-Ou, Simard, Jacques, Surowy, Harald, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Toland, Amanda E., Tollenaar, Rob A. E. M., Torres, Diana, Torres-Mejía, Gabriela, Troester, Melissa A., Truong, Thérèse, Vachon, Celine M., Vijai, Joseph, Weinberg, Clarice R., Wendt, Camilla, Winqvist, Robert, Wolk, Alicja, Wu, Anna H., Yamaji, Taiki, Yang, Xiaohong R., Yu, Jyh-Cherng, Zheng, Wei, Ziogas, Argyrios, Ziv, Elad, Dunning, Alison M., Easton, Douglas F., Hemingway, Harry, Hamann, Ute, and Kuchenbaecker, Karoline B.
- Published
- 2023
- Full Text
- View/download PDF
Catalog
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