Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry. Genome medicine Mueller, S. H., Lai, A. G., Valkovskaya, M., Michailidou, K., Bolla, M. K., Wang, Q., Dennis, J., Lush, M., Abu-Ful, Z., Ahearn, T. U., Andrulis, I. L., Anton-Culver, H., Antonenkova, N. N., Arndt, V., Aronson, K. J., Augustinsson, A., Baert, T., Freeman, L. E., Beckmann, M. W., Behrens, S., Benitez, J., Bermisheva, M., Blomqvist, C., Bogdanova, N. V., Bojesen, S. E., Bonanni, B., Brenner, H., Brucker, S. Y., Buys, S. S., Castelao, J. E., Chan, T. L., Chang-Claude, J., Chanock, S. J., Choi, J. Y., Chung, W. K., Colonna, S. V., Cornelissen, S., Couch, F. J., Czene, K., Daly, M. B., Devilee, P., Dörk, T., Dossus, L., Dwek, M., Eccles, D. M., Ekici, A. B., Eliassen, A. H., Engel, C., Evans, D. G., Fasching, P. A., Fletcher, O., Flyger, H., Gago-Dominguez, M., Gao, Y. T., García-Closas, M., García-Sáenz, J. A., Genkinger, J., Gentry-Maharaj, A., Grassmann, F., Guénel, P., Gündert, M., Haeberle, L., Hahnen, E., Haiman, C. A., Håkansson, N., Hall, P., Harkness, E. F., Harrington, P. A., Hartikainen, J. M., Hartman, M., Hein, A., Ho, W. K., Hooning, M. J., Hoppe, R., Hopper, J. L., Houlston, R. S., Howell, A., Hunter, D. J., Huo, D., Ito, H., Iwasaki, M., Jakubowska, A., Janni, W., John, E. M., Jones, M. E., Jung, A., Kaaks, R., Kang, D., Khusnutdinova, E. K., Kim, S. W., Kitahara, C. M., Koutros, S., Kraft, P., Kristensen, V. N., Kubelka-Sabit, K., Kurian, A. W., Kwong, A., Lacey, J. V., Lambrechts, D., Le Marchand, L., Li, J., Linet, M., Lo, W. Y., Long, J., Lophatananon, A., Mannermaa, A., Manoochehri, M., Margolin, S., Matsuo, K., Mavroudis, D., Menon, U., Muir, K., Murphy, R. A., Nevanlinna, H., Newman, W. G., Niederacher, D., O'Brien, K. M., Obi, N., Offit, K., Olopade, O. I., Olshan, A. F., Olsson, H., Park, S. K., Patel, A. V., Patel, A., Perou, C. M., Peto, J., Pharoah, P. D., Plaseska-Karanfilska, D., Presneau, N., Rack, B., Radice, P., Ramachandran, D., Rashid, M. U., Rennert, G., Romero, A., Ruddy, K. J., Ruebner, M., Saloustros, E., Sandler, D. P., Sawyer, E. J., Schmidt, M. K., Schmutzler, R. K., Schneider, M. O., Scott, C., Shah, M., Sharma, P., Shen, C. Y., Shu, X. O., Simard, J., Surowy, H., Tamimi, R. M., Tapper, W. J., Taylor, J. A., Teo, S. H., Teras, L. R., Toland, A. E., Tollenaar, R. A., Torres, D., Torres-Mejía, G., Troester, M. A., Truong, T., Vachon, C. M., Vijai, J., Weinberg, C. R., Wendt, C., Winqvist, R., Wolk, A., Wu, A. H., Yamaji, T., Yang, X. R., Yu, J. C., Zheng, W., Ziogas, A., Ziv, E., Dunning, A. M., Easton, D. F., Hemingway, H., Hamann, U., Kuchenbaecker, K. B. 2023; 15 (1): 7

Abstract

Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.In European ancestry samples, 14 genes were significantly associated (q?

View details for DOI 10.1186/s13073-022-01152-5

View details for PubMedID 36703164