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1. Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Author: Kentistou, KA, Kaisinger, LR, Stankovic, S, Vaudel, M, Mendes de Oliveira, E, Messina, A, Walters, RG, Liu, X, Busch, AS, Helgason, H, Thompson, DJ, Santoni, F, Petricek, KM, Zouaghi, Y, Huang-Doran, I, Gudbjartsson, DF, Bratland, E, Lin, K, Gardner, EJ, Zhao, Y, Jia, RY, Terao, C, Riggan, MJ, Bolla, MK, Yazdanpanah, M, Yazdanpanah, N, Bradfield, JP, Broer, L, Campbell, A, Chasman, DI, Cousminer, DL, Franceschini, N, Franke, LH, Girotto, G, He, C, Järvelin, M-R, Joshi, PK, Kamatani, Y, Karlsson, R, Luan, J, Lunetta, KL, Mägi, R, Mangino, M, Medland, SE, Meisinger, C, Noordam, R, Nutile, T, Concas, MP, Polašek, O, Porcu, E, Ring, SM, Sala, C, Smith, AV, Tanaka, T, van der Most, PJ, Vitart, V, Wang, CA, Willemsen, G, Zygmunt, M, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Auer, PL, Barnes, CLK, Beckmann, MW, Berrington de Gonzalez, A, Bogdanova, NV, Bojesen, SE, Brenner, H, Buring, JE, Canzian, F, Chang-Claude, J, Couch, FJ, Cox, A, Crisponi, L, Czene, K, Daly, MB, Demerath, EW, Dennis, J, Devilee, P, De Vivo, I, Dörk, T, Dunning, AM, Dwek, M, Eriksson, JG, Fasching, PA, Fernandez-Rhodes, L, Ferreli, L, Fletcher, O, Gago-Dominguez, M, García-Closas, M, García-Sáenz, JA, González-Neira, A, Grallert, H, Guénel, P, Haiman, CA, Hall, P, Hamann, U, Hakonarson, H, Hart, RJ, Hickey, M, Hooning, MJ, Hoppe, R, Hopper, JL, Hottenga, J-J, Hu, FB, Huebner, H, Hunter, DJ, ABCTB Investigators, Jernström, H, John, EM, Karasik, D, Khusnutdinova, EK, Kristensen, VN, Lacey, JV, Lambrechts, D, Launer, LJ, Lind, PA, Lindblom, A, Magnusson, PKE, Mannermaa, A, McCarthy, MI, Meitinger, T, Menni, C, Michailidou, K, Millwood, IY, Milne, RL, Montgomery, GW, Nevanlinna, H, Nolte, IM, Nyholt, DR, Obi, N, O'Brien, KM, Offit, K, Oldehinkel, AJ, Ostrowski, SR, Palotie, A, Pedersen, OB, Peters, A, Pianigiani, G, Plaseska-Karanfilska, D, Pouta, A, Pozarickij, A, Radice, P, Rennert, G, Rosendaal, FR, Ruggiero, D, Saloustros, E, Sandler, DP, Schipf, S, Schmidt, CO, Schmidt, MK, Small, K, Spedicati, B, Stampfer, M, Stone, J, Tamimi, RM, Teras, LR, Tikkanen, E, Turman, C, Vachon, CM, Wang, Q, Winqvist, R, Wolk, A, Zemel, BS, Zheng, W, van Dijk, KW, Alizadeh, BZ, Bandinelli, S, Boerwinkle, E, Boomsma, DI, Ciullo, M, Chenevix-Trench, G, Cucca, F, Esko, T, Gieger, C, Grant, SFA, Gudnason, V, Hayward, C, Kolčić, I, Kraft, P, Lawlor, DA, Martin, NG, Nøhr, EA, Pedersen, NL, Pennell, CE, Ridker, PM, Robino, A, Snieder, H, Sovio, U, Spector, TD, Stöckl, D, Sudlow, C, Timpson, NJ, Toniolo, D, Uitterlinden, A, Ulivi, S, Völzke, H, Wareham, NJ, Widen, E, Wilson, JF, Lifelines Cohort Study, Danish Blood Donor Study, Ovarian Cancer Association Consortium, Breast Cancer Association Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, Pharoah, PDP, Li, L, Easton, DF, Njølstad, PR, Sulem, P, Murabito, JM, Murray, A, Manousaki, D, Juul, A, Erikstrup, C, Stefansson, K, Horikoshi, M, Chen, Z, Farooqi, IS, Pitteloud, N, Johansson, S, Day, FR, Perry, JRB, Ong, KK, Kentistou, KA, Kaisinger, LR, Stankovic, S, Vaudel, M, Mendes de Oliveira, E, Messina, A, Walters, RG, Liu, X, Busch, AS, Helgason, H, Thompson, DJ, Santoni, F, Petricek, KM, Zouaghi, Y, Huang-Doran, I, Gudbjartsson, DF, Bratland, E, Lin, K, Gardner, EJ, Zhao, Y, Jia, RY, Terao, C, Riggan, MJ, Bolla, MK, Yazdanpanah, M, Yazdanpanah, N, Bradfield, JP, Broer, L, Campbell, A, Chasman, DI, Cousminer, DL, Franceschini, N, Franke, LH, Girotto, G, He, C, Järvelin, M-R, Joshi, PK, Kamatani, Y, Karlsson, R, Luan, J, Lunetta, KL, Mägi, R, Mangino, M, Medland, SE, Meisinger, C, Noordam, R, Nutile, T, Concas, MP, Polašek, O, Porcu, E, Ring, SM, Sala, C, Smith, AV, Tanaka, T, van der Most, PJ, Vitart, V, Wang, CA, Willemsen, G, Zygmunt, M, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Auer, PL, Barnes, CLK, Beckmann, MW, Berrington de Gonzalez, A, Bogdanova, NV, Bojesen, SE, Brenner, H, Buring, JE, Canzian, F, Chang-Claude, J, Couch, FJ, Cox, A, Crisponi, L, Czene, K, Daly, MB, Demerath, EW, Dennis, J, Devilee, P, De Vivo, I, Dörk, T, Dunning, AM, Dwek, M, Eriksson, JG, Fasching, PA, Fernandez-Rhodes, L, Ferreli, L, Fletcher, O, Gago-Dominguez, M, García-Closas, M, García-Sáenz, JA, González-Neira, A, Grallert, H, Guénel, P, Haiman, CA, Hall, P, Hamann, U, Hakonarson, H, Hart, RJ, Hickey, M, Hooning, MJ, Hoppe, R, Hopper, JL, Hottenga, J-J, Hu, FB, Huebner, H, Hunter, DJ, ABCTB Investigators, Jernström, H, John, EM, Karasik, D, Khusnutdinova, EK, Kristensen, VN, Lacey, JV, Lambrechts, D, Launer, LJ, Lind, PA, Lindblom, A, Magnusson, PKE, Mannermaa, A, McCarthy, MI, Meitinger, T, Menni, C, Michailidou, K, Millwood, IY, Milne, RL, Montgomery, GW, Nevanlinna, H, Nolte, IM, Nyholt, DR, Obi, N, O'Brien, KM, Offit, K, Oldehinkel, AJ, Ostrowski, SR, Palotie, A, Pedersen, OB, Peters, A, Pianigiani, G, Plaseska-Karanfilska, D, Pouta, A, Pozarickij, A, Radice, P, Rennert, G, Rosendaal, FR, Ruggiero, D, Saloustros, E, Sandler, DP, Schipf, S, Schmidt, CO, Schmidt, MK, Small, K, Spedicati, B, Stampfer, M, Stone, J, Tamimi, RM, Teras, LR, Tikkanen, E, Turman, C, Vachon, CM, Wang, Q, Winqvist, R, Wolk, A, Zemel, BS, Zheng, W, van Dijk, KW, Alizadeh, BZ, Bandinelli, S, Boerwinkle, E, Boomsma, DI, Ciullo, M, Chenevix-Trench, G, Cucca, F, Esko, T, Gieger, C, Grant, SFA, Gudnason, V, Hayward, C, Kolčić, I, Kraft, P, Lawlor, DA, Martin, NG, Nøhr, EA, Pedersen, NL, Pennell, CE, Ridker, PM, Robino, A, Snieder, H, Sovio, U, Spector, TD, Stöckl, D, Sudlow, C, Timpson, NJ, Toniolo, D, Uitterlinden, A, Ulivi, S, Völzke, H, Wareham, NJ, Widen, E, Wilson, JF, Lifelines Cohort Study, Danish Blood Donor Study, Ovarian Cancer Association Consortium, Breast Cancer Association Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, Pharoah, PDP, Li, L, Easton, DF, Njølstad, PR, Sulem, P, Murabito, JM, Murray, A, Manousaki, D, Juul, A, Erikstrup, C, Stefansson, K, Horikoshi, M, Chen, Z, Farooqi, IS, Pitteloud, N, Johansson, S, Day, FR, Perry, JRB, and Ong, KK
Abstract: Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.
Published: 2024

2. A Likelihood Ratio Approach for Utilizing Case-Control Data in the Clinical Classification of Rare Sequence Variants: Application to BRCA1 and BRCA2

Author: Cutting, G, Zanti, M, O'Mahony, DG, Parsons, MT, Li, H, Dennis, J, Aittomakkiki, K, Andrulis, IL, Anton-Culver, H, Aronson, KJ, Augustinsson, A, Becher, H, Bojesen, SE, Bolla, MK, Brenner, H, Brown, MA, Buys, SS, Canzian, F, Caputo, SM, Castelao, JE, Chang-Claude, J, Czene, K, Daly, MB, De Nicolo, A, Devilee, P, Dork, T, Dunning, AM, Dwek, M, Eccles, DM, Engel, C, Evans, DG, Fasching, PA, Gago-Dominguez, M, Garcia-Closas, M, Garcia-Saenz, JA, Gentry-Maharaj, A, Geurts-Giele, WRR, Giles, GG, Glendon, G, Goldberg, MS, Garcia, EBG, Guendert, M, Guenel, P, Hahnen, E, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Hogervorst, FBL, Hollestelle, A, Hoppe, R, Hopper, JL, Houdayer, C, Houlston, RS, Howell, A, Investigators, A, Jakimovska, M, Jakubowska, A, Jernstrom, H, John, EM, Kaaks, R, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Lacey, J, Lambrechts, D, Leone, M, Lindblom, A, Lush, M, Mannermaa, A, Manoochehri, M, Manoukian, S, Margolin, S, Martinez, ME, Menon, U, Milne, RL, Monteiro, AN, Murphy, RA, Neuhausen, SL, Nevanlinna, H, Newman, WG, Offit, K, Park, SK, James, P, Peterlongo, P, Peto, J, Plaseska-Karanfilska, D, Punie, K, Radice, P, Rashid, MU, Rennert, G, Romero, A, Rosenberg, EH, Saloustros, E, Sandler, DP, Schmidt, MK, Schmutzler, RK, Shu, X-O, Simard, J, Southey, MC, Stone, J, Stoppa-Lyonnet, D, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Terry, MB, Thomassen, M, Troester, MA, Vachon, CM, Vega, A, Vreeswijk, MPG, Wang, Q, Wappenschmidt, B, Weinberg, CR, Wolk, A, Zheng, W, Feng, B, Couch, FJ, Spurdle, AB, Easton, DF, Goldgar, DE, Michailidou, K, Cutting, G, Zanti, M, O'Mahony, DG, Parsons, MT, Li, H, Dennis, J, Aittomakkiki, K, Andrulis, IL, Anton-Culver, H, Aronson, KJ, Augustinsson, A, Becher, H, Bojesen, SE, Bolla, MK, Brenner, H, Brown, MA, Buys, SS, Canzian, F, Caputo, SM, Castelao, JE, Chang-Claude, J, Czene, K, Daly, MB, De Nicolo, A, Devilee, P, Dork, T, Dunning, AM, Dwek, M, Eccles, DM, Engel, C, Evans, DG, Fasching, PA, Gago-Dominguez, M, Garcia-Closas, M, Garcia-Saenz, JA, Gentry-Maharaj, A, Geurts-Giele, WRR, Giles, GG, Glendon, G, Goldberg, MS, Garcia, EBG, Guendert, M, Guenel, P, Hahnen, E, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Hogervorst, FBL, Hollestelle, A, Hoppe, R, Hopper, JL, Houdayer, C, Houlston, RS, Howell, A, Investigators, A, Jakimovska, M, Jakubowska, A, Jernstrom, H, John, EM, Kaaks, R, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Lacey, J, Lambrechts, D, Leone, M, Lindblom, A, Lush, M, Mannermaa, A, Manoochehri, M, Manoukian, S, Margolin, S, Martinez, ME, Menon, U, Milne, RL, Monteiro, AN, Murphy, RA, Neuhausen, SL, Nevanlinna, H, Newman, WG, Offit, K, Park, SK, James, P, Peterlongo, P, Peto, J, Plaseska-Karanfilska, D, Punie, K, Radice, P, Rashid, MU, Rennert, G, Romero, A, Rosenberg, EH, Saloustros, E, Sandler, DP, Schmidt, MK, Schmutzler, RK, Shu, X-O, Simard, J, Southey, MC, Stone, J, Stoppa-Lyonnet, D, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Terry, MB, Thomassen, M, Troester, MA, Vachon, CM, Vega, A, Vreeswijk, MPG, Wang, Q, Wappenschmidt, B, Weinberg, CR, Wolk, A, Zheng, W, Feng, B, Couch, FJ, Spurdle, AB, Easton, DF, Goldgar, DE, and Michailidou, K
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.
Published: 2023

3. Genetically inferred birthweight, height, and puberty timing and risk of osteosarcoma.

Author: Gianferante, DM, Moore, A, Spector, LG, Wheeler, W, Yang, T, Hubbard, A, Gorlick, R, Patiño-Garcia, A, Lecanda, F, Flanagan, AM, Amary, F, Andrulis, IL, Wunder, JS, Thomas, DM, Ballinger, ML, Serra, M, Hattinger, C, Demerath, E, Johnson, W, Birmann, BM, De Vivo, I, Giles, G, Teras, LR, Arslan, A, Vermeulen, R, Sample, J, Freedman, ND, Huang, W-Y, Chanock, SJ, Savage, SA, Berndt, SI, Mirabello, L, Gianferante, DM, Moore, A, Spector, LG, Wheeler, W, Yang, T, Hubbard, A, Gorlick, R, Patiño-Garcia, A, Lecanda, F, Flanagan, AM, Amary, F, Andrulis, IL, Wunder, JS, Thomas, DM, Ballinger, ML, Serra, M, Hattinger, C, Demerath, E, Johnson, W, Birmann, BM, De Vivo, I, Giles, G, Teras, LR, Arslan, A, Vermeulen, R, Sample, J, Freedman, ND, Huang, W-Y, Chanock, SJ, Savage, SA, Berndt, SI, and Mirabello, L
Abstract: INTRODUCTION: Several studies have linked increased risk of osteosarcoma with tall stature, high birthweight, and early puberty, although evidence is inconsistent. We used genetic risk scores (GRS) based on established genetic loci for these traits and evaluated associations between genetically inferred birthweight, height, and puberty timing with osteosarcoma. METHODS: Using genotype data from two genome-wide association studies, totaling 1039 cases and 2923 controls of European ancestry, association analyses were conducted using logistic regression for each study and meta-analyzed to estimate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses were conducted by case diagnosis age, metastasis status, tumor location, tumor histology, and presence of a known pathogenic variant in a cancer susceptibility gene. RESULTS: Genetically inferred higher birthweight was associated with an increased risk of osteosarcoma (OR =1.59, 95% CI 1.07-2.38, P = 0.02). This association was strongest in cases without metastatic disease (OR =2.46, 95% CI 1.44-4.19, P = 9.5 ×10-04). Although there was no overall association between osteosarcoma and genetically inferred taller stature (OR=1.06, 95% CI 0.96-1.17, P = 0.28), the GRS for taller stature was associated with an increased risk of osteosarcoma in 154 cases with a known pathogenic cancer susceptibility gene variant (OR=1.29, 95% CI 1.03-1.63, P = 0.03). There were no significant associations between the GRS for puberty timing and osteosarcoma. CONCLUSION: A genetic propensity to higher birthweight was associated with increased osteosarcoma risk, suggesting that shared genetic factors or biological pathways that affect birthweight may contribute to osteosarcoma pathogenesis.
Published: 2023

4. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Author: Mueller, SH, Lai, AG, Valkovskaya, M, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Lush, M, Abu-Ful, Z, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baert, T, Freeman, LEB, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bogdanova, N, Bojesen, SE, Bonanni, B, Brenner, H, Brucker, SY, Buys, SS, Castelao, JE, Chan, TL, Chang-Claude, J, Chanock, SJ, Choi, J-Y, Chung, WK, Colonna, S, Cornelissen, S, Couch, FJ, Czene, K, Daly, MB, Devilee, P, Dork, T, Dossus, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Engel, C, Evans, DG, Fasching, PA, Fletcher, O, Flyger, H, Gago-Dominguez, M, Gao, Y-T, Garcia-Closas, M, Garcia-Saenz, JA, Genkinger, J, Gentry-Maharaj, A, Grassmann, F, Guenel, P, Gundert, M, Haeberle, L, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Harkness, EF, Harrington, PA, Hartikainen, JM, Hartman, M, Hein, A, Ho, W-K, Hooning, MJ, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Hunter, DJ, Huo, D, Investigators, A, Ito, H, Iwasaki, M, Jakubowska, A, Janni, W, John, EM, Jones, ME, Jung, A, Kaaks, R, Kang, D, Khusnutdinova, EK, Kim, S-W, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Kwong, A, Lacey, J, 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, RA, Nevanlinna, H, Newman, WG, Niederacher, D, O'Brien, KM, Obi, N, Offit, K, Olopade, O, Olshan, AF, Olsson, H, Park, SK, Patel, A, Perou, CM, Peto, J, Pharoah, PDP, Plaseska-Karanfilska, D, Presneau, N, Rack, B, Radice, P, Ramachandran, D, Rashid, MU, Rennert, G, Romero, A, Ruddy, KJ, Ruebner, M, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schneider, MO, Scott, C, Shah, M, Sharma, P, Shen, C-Y, Shu, X-O, Simard, J, Surowy, H, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Toland, AE, Tollenaar, RAEM, Torres, D, Torres-Mejia, G, Troester, MA, Truong, T, Vachon, CM, Vijai, J, Weinberg, CR, Wendt, C, Winqvist, R, Wolk, A, Wu, AH, Yamaji, T, Yang, XR, Yu, J-C, Zheng, W, Ziogas, A, Ziv, E, Dunning, AM, Easton, DF, Hemingway, H, Hamann, U, Kuchenbaecker, KB, Mueller, SH, Lai, AG, Valkovskaya, M, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Lush, M, Abu-Ful, Z, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baert, T, Freeman, LEB, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bogdanova, N, Bojesen, SE, Bonanni, B, Brenner, H, Brucker, SY, Buys, SS, Castelao, JE, Chan, TL, Chang-Claude, J, Chanock, SJ, Choi, J-Y, Chung, WK, Colonna, S, Cornelissen, S, Couch, FJ, Czene, K, Daly, MB, Devilee, P, Dork, T, Dossus, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Engel, C, Evans, DG, Fasching, PA, Fletcher, O, Flyger, H, Gago-Dominguez, M, Gao, Y-T, Garcia-Closas, M, Garcia-Saenz, JA, Genkinger, J, Gentry-Maharaj, A, Grassmann, F, Guenel, P, Gundert, M, Haeberle, L, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Harkness, EF, Harrington, PA, Hartikainen, JM, Hartman, M, Hein, A, Ho, W-K, Hooning, MJ, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Hunter, DJ, Huo, D, Investigators, A, Ito, H, Iwasaki, M, Jakubowska, A, Janni, W, John, EM, Jones, ME, Jung, A, Kaaks, R, Kang, D, Khusnutdinova, EK, Kim, S-W, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Kwong, A, Lacey, J, 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, RA, Nevanlinna, H, Newman, WG, Niederacher, D, O'Brien, KM, Obi, N, Offit, K, Olopade, O, Olshan, AF, Olsson, H, Park, SK, Patel, A, Perou, CM, Peto, J, Pharoah, PDP, Plaseska-Karanfilska, D, Presneau, N, Rack, B, Radice, P, Ramachandran, D, Rashid, MU, Rennert, G, Romero, A, Ruddy, KJ, Ruebner, M, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schneider, MO, Scott, C, Shah, M, Sharma, P, Shen, C-Y, Shu, X-O, Simard, J, Surowy, H, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Toland, AE, Tollenaar, RAEM, Torres, D, Torres-Mejia, G, Troester, MA, Truong, T, Vachon, CM, Vijai, J, Weinberg, CR, Wendt, C, Winqvist, R, Wolk, A, Wu, AH, Yamaji, T, Yang, XR, Yu, J-C, Zheng, W, Ziogas, A, Ziv, E, Dunning, AM, Easton, DF, Hemingway, H, Hamann, U, and Kuchenbaecker, KB
Abstract: BACKGROUND: 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. METHODS: 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. RESULTS: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10-6) and AC058822.1 (P = 1.47 × 10-4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. CONCLUSIONS: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10-5), demonstrating the importance of diversifying study cohorts.
Published: 2023

5. Association of the CHEK2 c.1100delC variant, radiotherapy, and systemic treatment with contralateral breast cancer risk and breast cancer-specific survival.

Author: Morra, A, Schreurs, MAC, Andrulis, IL, Anton-Culver, H, Augustinsson, A, Beckmann, MW, Behrens, S, Bojesen, SE, Bolla, MK, Brauch, H, Broeks, A, Buys, SS, Camp, NJ, Castelao, JE, Cessna, MH, Chang-Claude, J, Chung, WK, Collaborators, N, Colonna, SV, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Dennis, J, Devilee, P, Dörk, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Eriksson, M, Evans, DG, Fasching, PA, Fehm, TN, Figueroa, JD, Flyger, H, Gabrielson, M, Gago-Dominguez, M, García-Closas, M, García-Sáenz, JA, Genkinger, J, Grassmann, F, Gündert, M, Hahnen, E, Haiman, CA, Hamann, U, Harrington, PA, Hartikainen, JM, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Investigators, A, Investigators, K, Jakubowska, A, Janni, W, Jernström, H, John, EM, Johnson, N, Jones, ME, Kristensen, VN, Kurian, AW, Lambrechts, D, Marchand, LL, Lindblom, A, Lubiński, J, Lux, MP, Mannermaa, A, Mavroudis, D, Mulligan, AM, Muranen, TA, Nevanlinna, H, Nevelsteen, I, Neven, P, Newman, WG, Obi, N, Offit, K, Olshan, AF, Park-Simon, T-W, Patel, AV, Peterlongo, P, Phillips, K-A, Plaseska-Karanfilska, D, Polley, EC, Presneau, N, Pylkäs, K, Rack, B, Radice, P, Rashid, MU, Rhenius, V, Robson, M, Romero, A, Saloustros, E, Sawyer, EJ, Schmutzler, RK, Schuetze, S, Scott, C, Shah, M, Smichkoska, S, Southey, MC, Tapper, WJ, Teras, LR, Tollenaar, RAEM, Tomczyk, K, Tomlinson, I, Troester, MA, Vachon, CM, van Veen, EM, Wang, Q, Wendt, C, Wildiers, H, Winqvist, R, Ziogas, A, Hall, P, Pharoah, PDP, Adank, MA, Hollestelle, A, Schmidt, MK, Hooning, MJ, Morra, A, Schreurs, MAC, Andrulis, IL, Anton-Culver, H, Augustinsson, A, Beckmann, MW, Behrens, S, Bojesen, SE, Bolla, MK, Brauch, H, Broeks, A, Buys, SS, Camp, NJ, Castelao, JE, Cessna, MH, Chang-Claude, J, Chung, WK, Collaborators, N, Colonna, SV, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Dennis, J, Devilee, P, Dörk, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Eriksson, M, Evans, DG, Fasching, PA, Fehm, TN, Figueroa, JD, Flyger, H, Gabrielson, M, Gago-Dominguez, M, García-Closas, M, García-Sáenz, JA, Genkinger, J, Grassmann, F, Gündert, M, Hahnen, E, Haiman, CA, Hamann, U, Harrington, PA, Hartikainen, JM, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Investigators, A, Investigators, K, Jakubowska, A, Janni, W, Jernström, H, John, EM, Johnson, N, Jones, ME, Kristensen, VN, Kurian, AW, Lambrechts, D, Marchand, LL, Lindblom, A, Lubiński, J, Lux, MP, Mannermaa, A, Mavroudis, D, Mulligan, AM, Muranen, TA, Nevanlinna, H, Nevelsteen, I, Neven, P, Newman, WG, Obi, N, Offit, K, Olshan, AF, Park-Simon, T-W, Patel, AV, Peterlongo, P, Phillips, K-A, Plaseska-Karanfilska, D, Polley, EC, Presneau, N, Pylkäs, K, Rack, B, Radice, P, Rashid, MU, Rhenius, V, Robson, M, Romero, A, Saloustros, E, Sawyer, EJ, Schmutzler, RK, Schuetze, S, Scott, C, Shah, M, Smichkoska, S, Southey, MC, Tapper, WJ, Teras, LR, Tollenaar, RAEM, Tomczyk, K, Tomlinson, I, Troester, MA, Vachon, CM, van Veen, EM, Wang, Q, Wendt, C, Wildiers, H, Winqvist, R, Ziogas, A, Hall, P, Pharoah, PDP, Adank, MA, Hollestelle, A, Schmidt, MK, and Hooning, MJ
Abstract: Breast cancer (BC) patients with a germline CHEK2 c.1100delC variant have an increased risk of contralateral BC (CBC) and worse BC-specific survival (BCSS) compared to non-carriers. We aimed to assess the associations of CHEK2 c.1100delC, radiotherapy, and systemic treatment with CBC risk and BCSS. Analyses were based on 82,701 women diagnosed with invasive BC including 963 CHEK2 c.1100delC carriers; median follow-up was 9.1 years. Differential associations of treatment by CHEK2 c.1100delC status were tested by including interaction terms in a multivariable Cox regression model. A multi-state model was used for further insight into the relation between CHEK2 c.1100delC status, treatment, CBC risk and death. There was no evidence for differential associations of therapy with CBC risk by CHEK2 c.1100delC status The strongest association with reduced CBC risk was observed for the combination of chemotherapy and endocrine therapy [HR(95%CI): 0.66 (0.55-0.78)]. No association was observed with radiotherapy. Results from the multi-state model showed shorter BCSS for CHEK2 c.1100delC carriers versus non-carriers also after accounting for CBC occurrence [HR(95%CI) :1.30 (1.09-1.56)]. In conclusion, systemic therapy was associated with reduced CBC risk irrespective of CHEK2 c.1100delC status. Moreover, CHEK2 c.1100delC carriers had shorter BCSS, which appears not to be fully explained by their CBC risk. (Main MS: 3201 words).
Published: 2023

6. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author: Middha, PK, Wang, X, Behrens, S, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Auer, PL, Augustinsson, A, Baert, T, Freeman, LEB, Becher, H, Beckmann, MW, Benitez, J, Bojesen, SE, Brauch, H, Brenner, H, Brooks-Wilson, A, Campa, D, Canzian, F, Carracedo, A, Castelao, JE, Chanock, SJ, Chenevix-Trench, G, Cordina-Duverger, E, Couch, FJ, Cox, A, Cross, SS, Czene, K, Dossus, L, Dugue, P-A, Eliassen, AH, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Fletcher, O, Flyger, H, Gabrielson, M, Gago-Dominguez, M, Giles, GG, Gonzalez-Neira, A, Grassmann, F, Grundy, A, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hankinson, SE, Harkness, EF, Holleczek, B, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Hunter, DJ, Ingvar, C, Isaksson, K, Jernstroem, H, John, EM, Jones, ME, Kaaks, R, Keeman, R, Kitahara, CM, Ko, Y-D, Koutros, S, Kurian, AW, Lacey, JV, Lambrechts, D, Larson, NL, Larsson, S, Le Marchand, L, Lejbkowicz, F, Li, S, Linet, M, Lissowska, J, Martinez, ME, Maurer, T, Mulligan, AM, Mulot, C, Murphy, RA, Newman, WG, Nielsen, SF, Nordestgaard, BG, Norman, A, O'Brien, KM, Olson, JE, Patel, AV, Prentice, R, Rees-Punia, E, Rennert, G, Rhenius, V, Ruddy, KJ, Sandler, DP, Scott, CG, Shah, MT, Shu, X-O, Smeets, A, Southey, MC, Stone, J, Tamimi, RM, Taylor, JA, Teras, LR, Tomczyk, K, Troester, MA, Truong, T, Vachon, CM, Wang, SS, Weinberg, CR, Wildiers, H, Willett, W, Winham, SJ, Wolk, A, Yang, X, Zamora, MP, Zheng, W, Ziogas, A, Dunning, AM, Pharoah, PDP, Garcia-Closas, M, Schmidt, MK, Kraft, P, Milne, RL, Lindstroem, S, Easton, DF, Chang-Claude, J, Middha, PK, Wang, X, Behrens, S, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Auer, PL, Augustinsson, A, Baert, T, Freeman, LEB, Becher, H, Beckmann, MW, Benitez, J, Bojesen, SE, Brauch, H, Brenner, H, Brooks-Wilson, A, Campa, D, Canzian, F, Carracedo, A, Castelao, JE, Chanock, SJ, Chenevix-Trench, G, Cordina-Duverger, E, Couch, FJ, Cox, A, Cross, SS, Czene, K, Dossus, L, Dugue, P-A, Eliassen, AH, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Fletcher, O, Flyger, H, Gabrielson, M, Gago-Dominguez, M, Giles, GG, Gonzalez-Neira, A, Grassmann, F, Grundy, A, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hankinson, SE, Harkness, EF, Holleczek, B, Hoppe, R, Hopper, JL, Houlston, RS, Howell, A, Hunter, DJ, Ingvar, C, Isaksson, K, Jernstroem, H, John, EM, Jones, ME, Kaaks, R, Keeman, R, Kitahara, CM, Ko, Y-D, Koutros, S, Kurian, AW, Lacey, JV, Lambrechts, D, Larson, NL, Larsson, S, Le Marchand, L, Lejbkowicz, F, Li, S, Linet, M, Lissowska, J, Martinez, ME, Maurer, T, Mulligan, AM, Mulot, C, Murphy, RA, Newman, WG, Nielsen, SF, Nordestgaard, BG, Norman, A, O'Brien, KM, Olson, JE, Patel, AV, Prentice, R, Rees-Punia, E, Rennert, G, Rhenius, V, Ruddy, KJ, Sandler, DP, Scott, CG, Shah, MT, Shu, X-O, Smeets, A, Southey, MC, Stone, J, Tamimi, RM, Taylor, JA, Teras, LR, Tomczyk, K, Troester, MA, Truong, T, Vachon, CM, Wang, SS, Weinberg, CR, Wildiers, H, Willett, W, Winham, SJ, Wolk, A, Yang, X, Zamora, MP, Zheng, W, Ziogas, A, Dunning, AM, Pharoah, PDP, Garcia-Closas, M, Schmidt, MK, Kraft, P, Milne, RL, Lindstroem, S, Easton, DF, and Chang-Claude, J
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 < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). CONCLUSIONS: Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.
Published: 2023

7. A Genome-Wide Gene-Based Gene-Environment Interaction Study of Breast Cancer in More than 90,000 Women

Author: Wang, X, Chen, H, Kapoor, PM, Su, Y-R, Bolla, MK, Dennis, J, Dunning, AM, Lush, M, Wang, Q, Michailidou, K, Pharoah, PDP, Hopper, JL, Southey, MC, Koutros, S, Freeman, LEB, Stone, J, Rennert, G, Shibli, R, Murphy, RA, Aronson, K, Guenel, P, Truong, T, Teras, LR, Hodge, JM, Canzian, F, Kaaks, R, Brenner, H, Arndt, V, Hoppe, R, Lo, W-Y, Behrens, S, Mannermaa, A, Kosma, V-M, Jung, A, Becher, H, Glies, GG, Haiman, CA, Maskarinec, G, Scott, C, Winham, S, Simard, J, Goldberg, MS, Zheng, W, Long, J, Troester, MA, Love, MI, Peng, C, Tamimi, R, Eliassen, H, Garcia-Closas, M, Figueroa, J, Ahearn, T, Yang, R, Evans, DG, Howell, A, Hall, P, Czene, K, Wolk, A, Sandler, DP, Taylor, JA, Swerdlow, AJ, Orr, N, Lacey, JV, Wang, S, Olsson, H, Easton, DF, Milne, RL, Hsu, L, Kraft, P, Chang-Claude, J, Lindstroem, S, Wang, X, Chen, H, Kapoor, PM, Su, Y-R, Bolla, MK, Dennis, J, Dunning, AM, Lush, M, Wang, Q, Michailidou, K, Pharoah, PDP, Hopper, JL, Southey, MC, Koutros, S, Freeman, LEB, Stone, J, Rennert, G, Shibli, R, Murphy, RA, Aronson, K, Guenel, P, Truong, T, Teras, LR, Hodge, JM, Canzian, F, Kaaks, R, Brenner, H, Arndt, V, Hoppe, R, Lo, W-Y, Behrens, S, Mannermaa, A, Kosma, V-M, Jung, A, Becher, H, Glies, GG, Haiman, CA, Maskarinec, G, Scott, C, Winham, S, Simard, J, Goldberg, MS, Zheng, W, Long, J, Troester, MA, Love, MI, Peng, C, Tamimi, R, Eliassen, H, Garcia-Closas, M, Figueroa, J, Ahearn, T, Yang, R, Evans, DG, Howell, A, Hall, P, Czene, K, Wolk, A, Sandler, DP, Taylor, JA, Swerdlow, AJ, Orr, N, Lacey, JV, Wang, S, Olsson, H, Easton, DF, Milne, RL, Hsu, L, Kraft, P, Chang-Claude, J, and Lindstroem, S
Abstract: BACKGROUND: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. METHODS: We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. RESULTS: After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6). CONCLUSION: In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. IMPACT: Our study suggests a limited role of gene-environment interactions in breast cancer risk.
Published: 2022

8. Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Author: Wang, X, Kapoor, PM, Auer, PL, Dennis, J, Dunning, AM, Wang, Q, Lush, M, Michailidou, K, Bolla, MK, Aronson, KJ, Murphy, RA, Brooks-Wilson, A, Lee, DG, Guenel, P, Truong, T, Mulot, C, Teras, LR, Patel, A, Dossus, L, Kaaks, R, Hoppe, R, Bruening, T, Hamann, U, Czene, K, Gabrielson, M, Hall, P, Eriksson, M, Jung, A, Becher, H, Couch, FJ, Larson, NL, Olson, JE, Ruddy, KJ, Giles, GG, MacInnis, RJ, Southey, MC, Le Marchand, L, Wilkens, LR, Haiman, CA, Olsson, H, Augustinsson, A, Krueger, U, Wagner, P, Scott, C, Winham, SJ, Vachon, CM, Perou, CM, Olshan, AF, Troester, MA, Hunter, DJ, Eliassen, HA, Tamimi, RM, Brantley, K, Andrulis, IL, Figueroa, J, Chanock, SJ, Ahearn, TU, Evans, GD, Newman, WG, VanVeen, EM, Howell, A, Wolk, A, Hakansson, N, Ziogas, A, Jones, ME, Orr, N, Schoemaker, MJ, Swerdlow, AJ, Kitahara, CM, Linet, M, Prentice, RL, Easton, DF, Milne, RL, Kraft, P, Chang-Claude, J, Lindstrom, S, Wang, X, Kapoor, PM, Auer, PL, Dennis, J, Dunning, AM, Wang, Q, Lush, M, Michailidou, K, Bolla, MK, Aronson, KJ, Murphy, RA, Brooks-Wilson, A, Lee, DG, Guenel, P, Truong, T, Mulot, C, Teras, LR, Patel, A, Dossus, L, Kaaks, R, Hoppe, R, Bruening, T, Hamann, U, Czene, K, Gabrielson, M, Hall, P, Eriksson, M, Jung, A, Becher, H, Couch, FJ, Larson, NL, Olson, JE, Ruddy, KJ, Giles, GG, MacInnis, RJ, Southey, MC, Le Marchand, L, Wilkens, LR, Haiman, CA, Olsson, H, Augustinsson, A, Krueger, U, Wagner, P, Scott, C, Winham, SJ, Vachon, CM, Perou, CM, Olshan, AF, Troester, MA, Hunter, DJ, Eliassen, HA, Tamimi, RM, Brantley, K, Andrulis, IL, Figueroa, J, Chanock, SJ, Ahearn, TU, Evans, GD, Newman, WG, VanVeen, EM, Howell, A, Wolk, A, Hakansson, N, Ziogas, A, Jones, ME, Orr, N, Schoemaker, MJ, Swerdlow, AJ, Kitahara, CM, Linet, M, Prentice, RL, Easton, DF, Milne, RL, Kraft, P, Chang-Claude, J, and Lindstrom, S
Abstract: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.
Published: 2022

9. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author: Ahearn, TU, Zhang, H, Michailidou, K, Milne, RL, Bolla, MK, Dennis, J, Dunning, AM, Lush, M, Wang, Q, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Auer, PL, Augustinsson, A, Baten, A, Becher, H, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bojesen, SE, Bonanni, B, Borresen-Dale, A-L, Brauch, H, Brenner, H, Brooks-Wilson, A, Bruening, T, Burwinkel, B, Buys, SS, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Collee, JM, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Dork, T, Dwek, M, Eccles, DM, Evans, DG, Fasching, PA, Figueroa, J, Floris, G, Gago-Dominguez, M, Gapstur, SM, Garcia-Saenz, JA, Gaudet, MM, Giles, GG, Goldberg, MS, Gonzalez-Neira, A, Alnaes, GIG, Grip, M, Guenel, P, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Heemskerk-Gerritsen, BAM, Holleczek, B, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Howell, A, Jakimovska, M, Jakubowska, A, John, EM, Jones, ME, Jung, A, Kaaks, R, Kauppila, S, Keeman, R, Khusnutdinova, E, Kitahara, CM, Ko, Y-D, Koutros, S, Kristensen, VN, Kruger, U, Kubelka-Sabit, K, Kurian, AW, Kyriacou, K, Lambrechts, D, Lee, DG, Lindblom, A, Linet, M, Lissowska, J, Llaneza, A, Lo, W-Y, MacInnis, RJ, Mannermaa, A, Manoochehri, M, Margolin, S, Martinez, ME, McLean, C, Meindl, A, Menon, U, Nevanlinna, H, Newman, WG, Nodora, J, Offit, K, Olsson, H, Orr, N, Park-Simon, T-W, Patel, A, Peto, J, Pita, G, Plaseska-Karanfilska, D, Prentice, R, Punie, K, Pylkas, K, Radice, P, Rennert, G, Romero, A, Ruediger, T, Saloustros, E, Sampson, S, Sandler, DP, Sawyer, EJ, Schmutzler, RK, Schoemaker, MJ, Schottker, B, Sherman, ME, Shu, X-O, Smichkoska, S, Southey, MC, Spinelli, JJ, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Teras, LR, Terry, MB, Torres, D, Troester, MA, Vachon, CM, van Deurzen, CHM, van Veen, EM, Wagner, P, Weinberg, CR, Wendt, C, Wesseling, J, Winqvist, R, Wolk, A, Yang, XR, Zheng, W, Couch, FJ, Simard, J, Kraft, P, Easton, DF, Pharoah, PDP, Schmidt, MK, Garcia-Closas, M, Chatterjee, N, Ahearn, TU, Zhang, H, Michailidou, K, Milne, RL, Bolla, MK, Dennis, J, Dunning, AM, Lush, M, Wang, Q, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Auer, PL, Augustinsson, A, Baten, A, Becher, H, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bojesen, SE, Bonanni, B, Borresen-Dale, A-L, Brauch, H, Brenner, H, Brooks-Wilson, A, Bruening, T, Burwinkel, B, Buys, SS, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Collee, JM, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Dork, T, Dwek, M, Eccles, DM, Evans, DG, Fasching, PA, Figueroa, J, Floris, G, Gago-Dominguez, M, Gapstur, SM, Garcia-Saenz, JA, Gaudet, MM, Giles, GG, Goldberg, MS, Gonzalez-Neira, A, Alnaes, GIG, Grip, M, Guenel, P, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Heemskerk-Gerritsen, BAM, Holleczek, B, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Howell, A, Jakimovska, M, Jakubowska, A, John, EM, Jones, ME, Jung, A, Kaaks, R, Kauppila, S, Keeman, R, Khusnutdinova, E, Kitahara, CM, Ko, Y-D, Koutros, S, Kristensen, VN, Kruger, U, Kubelka-Sabit, K, Kurian, AW, Kyriacou, K, Lambrechts, D, Lee, DG, Lindblom, A, Linet, M, Lissowska, J, Llaneza, A, Lo, W-Y, MacInnis, RJ, Mannermaa, A, Manoochehri, M, Margolin, S, Martinez, ME, McLean, C, Meindl, A, Menon, U, Nevanlinna, H, Newman, WG, Nodora, J, Offit, K, Olsson, H, Orr, N, Park-Simon, T-W, Patel, A, Peto, J, Pita, G, Plaseska-Karanfilska, D, Prentice, R, Punie, K, Pylkas, K, Radice, P, Rennert, G, Romero, A, Ruediger, T, Saloustros, E, Sampson, S, Sandler, DP, Sawyer, EJ, Schmutzler, RK, Schoemaker, MJ, Schottker, B, Sherman, ME, Shu, X-O, Smichkoska, S, Southey, MC, Spinelli, JJ, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Teras, LR, Terry, MB, Torres, D, Troester, MA, Vachon, CM, van Deurzen, CHM, van Veen, EM, Wagner, P, Weinberg, CR, Wendt, C, Wesseling, J, Winqvist, R, Wolk, A, Yang, XR, Zheng, W, Couch, FJ, Simard, J, Kraft, P, Easton, DF, Pharoah, PDP, Schmidt, MK, Garcia-Closas, M, and Chatterjee, N
Abstract: BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
Published: 2022

10. Rare germline copy number variants (CNVs) and breast cancer risk

Author: Dennis, J, Tyrer, JP, Walker, LC, Michailidou, K, Dorling, L, Bolla, MK, Wang, Q, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Freeman, LEB, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bogdanova, N, Bojesen, SE, Brenner, H, Castelao, JE, Chang-Claude, J, Chenevix-Trench, G, Clarke, CL, Collee, JM, Couch, FJ, Cox, A, Cross, SS, Czene, K, Devilee, P, Dork, T, Dossus, L, Eliassen, AH, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Fletcher, O, Flyger, H, Fritschi, L, Gabrielson, M, Gago-Dominguez, M, Garcia-Closas, M, Giles, GG, Gonzalez-Neira, A, Guenel, P, Hahnen, E, Haiman, CA, Hall, P, Hollestelle, A, Hoppe, R, Hopper, JL, Howell, A, Jager, A, Jakubowska, A, John, EM, Johnson, N, Jones, ME, Jung, A, Kaaks, R, Keeman, R, Khusnutdinova, E, Kitahara, CM, Ko, Y-D, Kosma, V-M, Koutros, S, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Lacey, J, Lambrechts, D, Larson, NL, Linet, M, Ogrodniczak, A, Mannermaa, A, Manoukian, S, Margolin, S, Mavroudis, D, Milne, RL, Muranen, TA, Murphy, RA, Nevanlinna, H, Olson, JE, Olsson, H, Park-Simon, T-W, Perou, CM, Peterlongo, P, Plaseska-Karanfilska, D, Pylkas, K, Rennert, G, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Shibli, R, Smeets, A, Soucy, P, Southey, MC, Swerdlow, AJ, Tamimi, RM, Taylor, JA, Teras, LR, Terry, MB, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, Wendt, C, Winqvist, R, Wolk, A, Yang, XR, Zheng, W, Ziogas, A, Simard, J, Dunning, AM, Pharoah, PDP, Easton, DF, Dennis, J, Tyrer, JP, Walker, LC, Michailidou, K, Dorling, L, Bolla, MK, Wang, Q, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Freeman, LEB, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bogdanova, N, Bojesen, SE, Brenner, H, Castelao, JE, Chang-Claude, J, Chenevix-Trench, G, Clarke, CL, Collee, JM, Couch, FJ, Cox, A, Cross, SS, Czene, K, Devilee, P, Dork, T, Dossus, L, Eliassen, AH, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Fletcher, O, Flyger, H, Fritschi, L, Gabrielson, M, Gago-Dominguez, M, Garcia-Closas, M, Giles, GG, Gonzalez-Neira, A, Guenel, P, Hahnen, E, Haiman, CA, Hall, P, Hollestelle, A, Hoppe, R, Hopper, JL, Howell, A, Jager, A, Jakubowska, A, John, EM, Johnson, N, Jones, ME, Jung, A, Kaaks, R, Keeman, R, Khusnutdinova, E, Kitahara, CM, Ko, Y-D, Kosma, V-M, Koutros, S, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Lacey, J, Lambrechts, D, Larson, NL, Linet, M, Ogrodniczak, A, Mannermaa, A, Manoukian, S, Margolin, S, Mavroudis, D, Milne, RL, Muranen, TA, Murphy, RA, Nevanlinna, H, Olson, JE, Olsson, H, Park-Simon, T-W, Perou, CM, Peterlongo, P, Plaseska-Karanfilska, D, Pylkas, K, Rennert, G, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Shibli, R, Smeets, A, Soucy, P, Southey, MC, Swerdlow, AJ, Tamimi, RM, Taylor, JA, Teras, LR, Terry, MB, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, Wendt, C, Winqvist, R, Wolk, A, Yang, XR, Zheng, W, Ziogas, A, Simard, J, Dunning, AM, Pharoah, PDP, and Easton, DF
Abstract: Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.
Published: 2022

11. Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Author: Grootes, I, Keeman, R, Blows, FM, Milne, RL, Giles, GG, Swerdlow, AJ, Fasching, PA, Abubakar, M, Andrulis, IL, Anton-Culver, H, Beckmann, MW, Blomqvist, C, Bojesen, SE, Bolla, MK, Bonanni, B, Briceno, I, Burwinkel, B, Camp, NJ, Castelao, JE, Choi, J-Y, Clarke, CL, Couch, FJ, Cox, A, Cross, SS, Czene, K, Devilee, P, Dork, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Eriksson, M, Ernst, K, Evans, DG, Figueroa, JD, Fink, V, Floris, G, Fox, S, Gabrielson, M, Gago-Dominguez, M, Garcia-Saenz, JA, Gonzalez-Neira, A, Haeberle, L, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Hartman, M, Hein, A, Hooning, MJ, Hou, M-F, Howell, SJ, Ito, H, Jakubowska, A, Janni, W, John, EM, Jung, A, Kang, D, Kristensen, VN, Kwong, A, Lambrechts, D, Li, J, Manoochehri, M, Margolin, S, Matsuo, K, Taib, NAM, Mulligan, AM, Nevanlinna, H, Newman, WG, Offit, K, Osorio, A, Park, SK, Park-Simon, T-W, Patel, A, Presneau, N, Pylkas, K, Rack, B, Radice, P, Rennert, G, Romero, A, Saloustros, E, Sawyer, EJ, Schneeweiss, A, Schochter, F, Schoemaker, MJ, Shen, C-Y, Shibli, R, Sinn, P, Tapper, WJ, Tawfiq, E, Teo, SH, Teras, LR, Torres, D, Vachon, CM, van Deurzen, CHM, Wendt, C, Williams, JA, Winqvist, R, Elwood, M, Schmidt, MK, Pharoah, PDP, Grootes, I, Keeman, R, Blows, FM, Milne, RL, Giles, GG, Swerdlow, AJ, Fasching, PA, Abubakar, M, Andrulis, IL, Anton-Culver, H, Beckmann, MW, Blomqvist, C, Bojesen, SE, Bolla, MK, Bonanni, B, Briceno, I, Burwinkel, B, Camp, NJ, Castelao, JE, Choi, J-Y, Clarke, CL, Couch, FJ, Cox, A, Cross, SS, Czene, K, Devilee, P, Dork, T, Dunning, AM, Dwek, M, Easton, DF, Eccles, DM, Eriksson, M, Ernst, K, Evans, DG, Figueroa, JD, Fink, V, Floris, G, Fox, S, Gabrielson, M, Gago-Dominguez, M, Garcia-Saenz, JA, Gonzalez-Neira, A, Haeberle, L, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Hartman, M, Hein, A, Hooning, MJ, Hou, M-F, Howell, SJ, Ito, H, Jakubowska, A, Janni, W, John, EM, Jung, A, Kang, D, Kristensen, VN, Kwong, A, Lambrechts, D, Li, J, Manoochehri, M, Margolin, S, Matsuo, K, Taib, NAM, Mulligan, AM, Nevanlinna, H, Newman, WG, Offit, K, Osorio, A, Park, SK, Park-Simon, T-W, Patel, A, Presneau, N, Pylkas, K, Rack, B, Radice, P, Rennert, G, Romero, A, Saloustros, E, Sawyer, EJ, Schneeweiss, A, Schochter, F, Schoemaker, MJ, Shen, C-Y, Shibli, R, Sinn, P, Tapper, WJ, Tawfiq, E, Teo, SH, Teras, LR, Torres, D, Vachon, CM, van Deurzen, CHM, Wendt, C, Williams, JA, Winqvist, R, Elwood, M, Schmidt, MK, and Pharoah, PDP
Abstract: BACKGROUND: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2). METHOD: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance. RESULTS: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted. CONCLUSION: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.
Published: 2022

12. Distinct Reproductive Risk Profiles for Intrinsic-Like Breast Cancer Subtypes: Pooled Analysis of Population-Based Studies

Author: Jung, AY, Ahearn, TU, Behrens, S, Middha, P, Bolla, MK, Wang, Q, Arndt, V, Aronson, KJ, Augustinsson, A, Freeman, LEB, Becher, H, Brenner, H, Canzian, F, Carey, LA, Consortium, C, Czene, K, Eliassen, AH, Eriksson, M, Evans, DG, Figueroa, JD, Fritschi, L, Gabrielson, M, Giles, GG, Guenel, P, Hadjisavvas, A, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hoppe, R, Hopper, JL, Howell, A, Hunter, DJ, Huesing, A, Kaaks, R, Kosma, V-M, Koutros, S, Kraft, P, Lacey, J, Le Marchand, L, Lissowska, J, Loizidou, MA, Mannermaa, A, Maurer, T, Murphy, RA, Olshan, AF, Olsson, H, Patel, A, Perou, CM, Rennert, G, Shibli, R, Shu, X-O, Southey, MC, Stone, J, Tamimi, RM, Teras, LR, Troester, MA, Truong, T, Vachon, CM, Wang, SS, Wolk, A, Wu, AH, Yang, XR, Zheng, W, Dunning, AM, Pharoah, PDP, Easton, DF, Milne, RL, Chatterjee, N, Schmidt, MK, Garcia-Closas, M, Chang-Claude, J, Jung, AY, Ahearn, TU, Behrens, S, Middha, P, Bolla, MK, Wang, Q, Arndt, V, Aronson, KJ, Augustinsson, A, Freeman, LEB, Becher, H, Brenner, H, Canzian, F, Carey, LA, Consortium, C, Czene, K, Eliassen, AH, Eriksson, M, Evans, DG, Figueroa, JD, Fritschi, L, Gabrielson, M, Giles, GG, Guenel, P, Hadjisavvas, A, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hoppe, R, Hopper, JL, Howell, A, Hunter, DJ, Huesing, A, Kaaks, R, Kosma, V-M, Koutros, S, Kraft, P, Lacey, J, Le Marchand, L, Lissowska, J, Loizidou, MA, Mannermaa, A, Maurer, T, Murphy, RA, Olshan, AF, Olsson, H, Patel, A, Perou, CM, Rennert, G, Shibli, R, Shu, X-O, Southey, MC, Stone, J, Tamimi, RM, Teras, LR, Troester, MA, Truong, T, Vachon, CM, Wang, SS, Wolk, A, Wu, AH, Yang, XR, Zheng, W, Dunning, AM, Pharoah, PDP, Easton, DF, Milne, RL, Chatterjee, N, Schmidt, MK, Garcia-Closas, M, and Chang-Claude, J
Abstract: BACKGROUND: Reproductive 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. METHODS: Analyses 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. RESULTS: Compared 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
Published: 2022

13. Genetic insights into biological mechanisms governing human ovarian ageing

Author: Ruth, KS, Day, FR, Hussain, J, Martinez-Marchal, A, Aiken, CE, Azad, A, Thompson, DJ, Knoblochova, L, Abe, H, Tarry-Adkins, JL, Gonzalez, JM, Fontanillas, P, Claringbould, A, Bakker, OB, Sulem, P, Walters, RG, Terao, C, Turon, S, Horikoshi, M, Lin, K, Onland-Moret, NC, Sankar, A, Hertz, EPT, Timshel, PN, Shukla, V, Borup, R, Olsen, KW, Aguilera, P, Ferrer-Roda, M, Huang, Y, Stankovic, S, Timmers, PRHJ, Ahearn, TU, Alizadeh, BZ, Naderi, E, Andrulis, IL, Arnold, AM, Aronson, KJ, Augustinsson, A, Bandinelli, S, Barbieri, CM, Beaumont, RN, Becher, H, Beckmann, MW, Benonisdottir, S, Bergmann, S, Bochud, M, Boerwinkle, E, Bojesen, SE, Bolla, MK, Boomsma, DI, Bowker, N, Brody, JA, Broer, L, Buring, JE, Campbell, A, Campbell, H, Castelao, JE, Catamo, E, Chanock, SJ, Chenevix-Trench, G, Ciullo, M, Corre, T, Couch, FJ, Cox, A, Crisponi, L, Cross, SS, Cucca, F, Czene, K, Smith, GD, de Geus, EJCN, de Mutsert, R, De Vivo, I, Demerath, EW, Dennis, J, Dunning, AM, Dwek, M, Eriksson, M, Esko, T, Fasching, PA, Faul, JD, Ferrucci, L, Franceschini, N, Frayling, TM, Gago-Dominguez, M, Mezzavilla, M, Garcia-Closas, M, Gieger, C, Giles, GG, Grallert, H, Gudbjartsson, DF, Gudnason, V, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hayward, C, He, C, He, W, Heiss, G, Hoffding, MK, Hopper, JL, Hottenga, JJ, Hu, F, Hunter, D, Ikram, MA, Jackson, RD, Joaquim, MDR, John, EM, Joshi, PK, Karasik, D, Kardia, SLR, Kartsonaki, C, Karlsson, R, Kitahara, CM, Kolcic, I, Kooperberg, C, Kraft, P, Kurian, AW, Kutalik, Z, La Bianca, M, LaChance, G, Langenberg, C, Launer, LJ, Laven, JSE, Lawlor, DA, Le Marchand, L, Li, J, Lindblom, A, Lindstrom, S, Lindstrom, T, Linet, M, Liu, Y, Liu, S, Luan, J, Magi, R, Magnusson, PKE, Mangino, M, Mannermaa, A, Marco, B, Marten, J, Martin, NG, Mbarek, H, McKnight, B, Medland, SE, Meisinger, C, Meitinger, T, Menni, C, Metspalu, A, Milani, L, Milne, RL, Montgomery, GW, Mook-Kanamori, DO, Mulas, A, Mulligan, AM, Murray, A, Nalls, MA, Newman, A, Noordam, R, Nutile, T, Nyholt, DR, Olshan, AF, Olsson, H, Painter, JN, Patel, AV, Pedersen, NL, Perjakova, N, Peters, A, Peters, U, Pharoah, PDP, Polasek, O, Porcu, E, Psaty, BM, Rahman, I, Rennert, G, Rennert, HS, Ridker, PM, Ring, SM, Robino, A, Rose, LM, Rosendaal, FR, Rossouw, J, Rudan, I, Rueedi, R, Ruggiero, D, Sala, CF, Saloustros, E, Sandler, DP, Sanna, S, Sawyer, EJ, Sarnowski, C, Schlessinger, D, Schmidt, MK, Schoemaker, MJ, Schraut, KE, Scott, C, Shekari, S, Shrikhande, A, Smith, AV, Smith, BH, Smith, JA, Sorice, R, Southey, MC, Spector, TD, Spinelli, JJ, Stampfer, M, Stoeckl, D, van Meurs, JBJ, Strauch, K, Styrkarsdottir, U, Swerdlow, AJ, Tanaka, T, Teras, LR, Teumer, A, thorsteinsdottir, U, Timpson, NJ, Toniolo, D, Traglia, M, Troester, MA, Truong, T, Tyrrell, J, Uitterlinden, AG, Ulivi, S, Vachon, CM, Vitart, V, Voelker, U, Vollenweider, P, Voelzke, H, Wang, Q, Wareham, NJ, Weinberg, CR, Weir, DR, Wilcox, AN, van Dijk, KW, Willemsen, G, Wilson, JF, Wolffenbuttel, BHR, Wolk, A, Wood, AR, Zhao, W, Zygmunt, M, Chen, Z, Li, L, Franke, L, Burgess, S, Deelen, P, Pers, TH, Grondahl, ML, Andersen, CY, Pujol, A, Lopez-Contreras, AJ, Daniel, JA, Stefansson, K, Chang-Claude, J, van der Schouw, YT, Lunetta, KL, Chasman, DI, Easton, DF, Visser, JA, Ozanne, SE, Namekawa, SH, Solc, P, Murabito, JM, Ong, KK, Hoffmann, ER, Roig, I, Perry, JRB, Ruth, KS, Day, FR, Hussain, J, Martinez-Marchal, A, Aiken, CE, Azad, A, Thompson, DJ, Knoblochova, L, Abe, H, Tarry-Adkins, JL, Gonzalez, JM, Fontanillas, P, Claringbould, A, Bakker, OB, Sulem, P, Walters, RG, Terao, C, Turon, S, Horikoshi, M, Lin, K, Onland-Moret, NC, Sankar, A, Hertz, EPT, Timshel, PN, Shukla, V, Borup, R, Olsen, KW, Aguilera, P, Ferrer-Roda, M, Huang, Y, Stankovic, S, Timmers, PRHJ, Ahearn, TU, Alizadeh, BZ, Naderi, E, Andrulis, IL, Arnold, AM, Aronson, KJ, Augustinsson, A, Bandinelli, S, Barbieri, CM, Beaumont, RN, Becher, H, Beckmann, MW, Benonisdottir, S, Bergmann, S, Bochud, M, Boerwinkle, E, Bojesen, SE, Bolla, MK, Boomsma, DI, Bowker, N, Brody, JA, Broer, L, Buring, JE, Campbell, A, Campbell, H, Castelao, JE, Catamo, E, Chanock, SJ, Chenevix-Trench, G, Ciullo, M, Corre, T, Couch, FJ, Cox, A, Crisponi, L, Cross, SS, Cucca, F, Czene, K, Smith, GD, de Geus, EJCN, de Mutsert, R, De Vivo, I, Demerath, EW, Dennis, J, Dunning, AM, Dwek, M, Eriksson, M, Esko, T, Fasching, PA, Faul, JD, Ferrucci, L, Franceschini, N, Frayling, TM, Gago-Dominguez, M, Mezzavilla, M, Garcia-Closas, M, Gieger, C, Giles, GG, Grallert, H, Gudbjartsson, DF, Gudnason, V, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hayward, C, He, C, He, W, Heiss, G, Hoffding, MK, Hopper, JL, Hottenga, JJ, Hu, F, Hunter, D, Ikram, MA, Jackson, RD, Joaquim, MDR, John, EM, Joshi, PK, Karasik, D, Kardia, SLR, Kartsonaki, C, Karlsson, R, Kitahara, CM, Kolcic, I, Kooperberg, C, Kraft, P, Kurian, AW, Kutalik, Z, La Bianca, M, LaChance, G, Langenberg, C, Launer, LJ, Laven, JSE, Lawlor, DA, Le Marchand, L, Li, J, Lindblom, A, Lindstrom, S, Lindstrom, T, Linet, M, Liu, Y, Liu, S, Luan, J, Magi, R, Magnusson, PKE, Mangino, M, Mannermaa, A, Marco, B, Marten, J, Martin, NG, Mbarek, H, McKnight, B, Medland, SE, Meisinger, C, Meitinger, T, Menni, C, Metspalu, A, Milani, L, Milne, RL, Montgomery, GW, Mook-Kanamori, DO, Mulas, A, Mulligan, AM, Murray, A, Nalls, MA, Newman, A, Noordam, R, Nutile, T, Nyholt, DR, Olshan, AF, Olsson, H, Painter, JN, Patel, AV, Pedersen, NL, Perjakova, N, Peters, A, Peters, U, Pharoah, PDP, Polasek, O, Porcu, E, Psaty, BM, Rahman, I, Rennert, G, Rennert, HS, Ridker, PM, Ring, SM, Robino, A, Rose, LM, Rosendaal, FR, Rossouw, J, Rudan, I, Rueedi, R, Ruggiero, D, Sala, CF, Saloustros, E, Sandler, DP, Sanna, S, Sawyer, EJ, Sarnowski, C, Schlessinger, D, Schmidt, MK, Schoemaker, MJ, Schraut, KE, Scott, C, Shekari, S, Shrikhande, A, Smith, AV, Smith, BH, Smith, JA, Sorice, R, Southey, MC, Spector, TD, Spinelli, JJ, Stampfer, M, Stoeckl, D, van Meurs, JBJ, Strauch, K, Styrkarsdottir, U, Swerdlow, AJ, Tanaka, T, Teras, LR, Teumer, A, thorsteinsdottir, U, Timpson, NJ, Toniolo, D, Traglia, M, Troester, MA, Truong, T, Tyrrell, J, Uitterlinden, AG, Ulivi, S, Vachon, CM, Vitart, V, Voelker, U, Vollenweider, P, Voelzke, H, Wang, Q, Wareham, NJ, Weinberg, CR, Weir, DR, Wilcox, AN, van Dijk, KW, Willemsen, G, Wilson, JF, Wolffenbuttel, BHR, Wolk, A, Wood, AR, Zhao, W, Zygmunt, M, Chen, Z, Li, L, Franke, L, Burgess, S, Deelen, P, Pers, TH, Grondahl, ML, Andersen, CY, Pujol, A, Lopez-Contreras, AJ, Daniel, JA, Stefansson, K, Chang-Claude, J, van der Schouw, YT, Lunetta, KL, Chasman, DI, Easton, DF, Visser, JA, Ozanne, SE, Namekawa, SH, Solc, P, Murabito, JM, Ong, KK, Hoffmann, ER, Roig, I, and Perry, JRB
Abstract: Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
Published: 2021

14. Body size and weight change over adulthood and risk of breast cancer by menopausal and hormone receptor status: a pooled analysis of 20 prospective cohort studies

Author: van den Brandt, PA, Ziegler, RG, Wang, M, Hou, T, Li, R, Adami, H-O, Agnoli, C, Bernstein, L, Buring, JE, Chen, Y, Connor, AE, Eliassen, AH, Genkinger, JM, Gierach, G, Giles, GG, Goodman, GG, Hakansson, N, Krogh, V, Le Marchand, L, Lee, I-M, Liao, LM, Martinez, ME, Miller, AB, Milne, RL, Neuhouser, ML, Patel, AV, Prizment, A, Robien, K, Rohan, TE, Sawada, N, Schouten, LJ, Sinha, R, Stolzenberg-Solomon, RZ, Teras, LR, Tsugane, S, Visvanathan, K, Weiderpass, E, White, KK, Willett, WC, Wolk, A, Zeleniuch-Jacquotte, A, Smith-Warner, SA, van den Brandt, PA, Ziegler, RG, Wang, M, Hou, T, Li, R, Adami, H-O, Agnoli, C, Bernstein, L, Buring, JE, Chen, Y, Connor, AE, Eliassen, AH, Genkinger, JM, Gierach, G, Giles, GG, Goodman, GG, Hakansson, N, Krogh, V, Le Marchand, L, Lee, I-M, Liao, LM, Martinez, ME, Miller, AB, Milne, RL, Neuhouser, ML, Patel, AV, Prizment, A, Robien, K, Rohan, TE, Sawada, N, Schouten, LJ, Sinha, R, Stolzenberg-Solomon, RZ, Teras, LR, Tsugane, S, Visvanathan, K, Weiderpass, E, White, KK, Willett, WC, Wolk, A, Zeleniuch-Jacquotte, A, and Smith-Warner, SA
Abstract: Associations between anthropometric factors and breast cancer (BC) risk have varied inconsistently by estrogen and/or progesterone receptor (ER/PR) status. Associations between prediagnostic anthropometric factors and risk of premenopausal and postmenopausal BC overall and ER/PR status subtypes were investigated in a pooled analysis of 20 prospective cohorts, including 36,297 BC cases among 1,061,915 women, using multivariable Cox regression analyses, controlling for reproductive factors, diet and other risk factors. We estimated dose-response relationships and tested for nonlinear associations using restricted cubic splines. Height showed positive, linear associations for premenopausal and postmenopausal BC risk (6-7% RR increase per 5 cm increment), with stronger associations for receptor-positive subtypes. Body mass index (BMI) at cohort baseline was strongly inversely associated with premenopausal BC risk, and strongly positively-and nonlinearly-associated with postmenopausal BC (especially among women who never used hormone replacement therapy). This was primarily observed for receptor-positive subtypes. Early adult BMI (at 18-20 years) showed inverse, linear associations for premenopausal and postmenopausal BC risk (21% and 11% RR decrease per 5 kg/m2, respectively) with stronger associations for receptor-negative subtypes. Adult weight gain since 18-20 years was positively associated with postmenopausal BC risk, stronger for receptor-positive subtypes, and among women who were leaner in early adulthood. Women heavier in early adulthood generally had reduced premenopausal BC risk, independent of later weight gain. Positive associations between height, baseline (adult) BMI, adult weight gain and postmenopausal BC risk were substantially stronger for hormone receptor-positive versus negative subtypes. Premenopausal BC risk was positively associated with height, but inversely with baseline BMI and weight gain (mostly in receptor-positive subtypes). Inverse associ
Published: 2021

15. Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis

Author: Escala-Garcia, M, Canisius, S, Keeman, R, Beesley, J, Anton-Culver, H, Arndt, V, Augustinsson, A, Becher, H, Beckmann, MW, Behrens, S, Bermisheva, M, Bojesen, SE, Bolla, MK, Brenner, H, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Couch, FJ, Czene, K, Daly, MB, Dennis, J, Devilee, P, Dork, T, Dunning, AM, Easton, DF, Ekici, AB, Eliassen, AH, Fasching, PA, Flyger, H, Gago-Dominguez, M, Garcia-Closas, M, Garcia-Saenz, JA, Geisler, J, Giles, GG, Grip, M, Guendert, M, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hartikainen, JM, Heemskerk-Gerritsen, BAM, Hollestelle, A, Hoppe, R, Hopper, JL, Hunter, DJ, Jacot, W, Jakubowska, A, John, EM, Jung, AY, Kaaks, R, Khusnutdinova, E, Koppert, LB, Kraft, P, Kristensen, VN, Kurian, AW, Lambrechts, D, Le Marchand, L, Lindblom, A, Luben, RN, Lubinski, J, Mannermaa, A, Manoochehri, M, Margolin, S, Mavroudis, D, Muranen, TA, Nevanlinna, H, Olshan, AF, Olsson, H, Park-Simon, T-W, Patel, AV, Peterlongo, P, Pharoah, PDP, Punie, K, Radice, P, Rennert, G, Rennert, HS, Romero, A, Roylance, R, Ruediger, T, Ruebner, M, Saloustros, E, Sawyer, EJ, Schmutzler, RK, Schoemaker, MJ, Scott, C, Southey, MC, Surowy, H, Swerdlow, AJ, Tamimi, RM, Teras, LR, Thomas, E, Tomlinson, I, Troester, MA, Vachon, CM, Wang, Q, Winqvist, R, Wolk, A, Ziogas, A, Michailidou, K, Chenevix-Trench, G, Bachelot, T, Schmidt, MK, Escala-Garcia, M, Canisius, S, Keeman, R, Beesley, J, Anton-Culver, H, Arndt, V, Augustinsson, A, Becher, H, Beckmann, MW, Behrens, S, Bermisheva, M, Bojesen, SE, Bolla, MK, Brenner, H, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Couch, FJ, Czene, K, Daly, MB, Dennis, J, Devilee, P, Dork, T, Dunning, AM, Easton, DF, Ekici, AB, Eliassen, AH, Fasching, PA, Flyger, H, Gago-Dominguez, M, Garcia-Closas, M, Garcia-Saenz, JA, Geisler, J, Giles, GG, Grip, M, Guendert, M, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hartikainen, JM, Heemskerk-Gerritsen, BAM, Hollestelle, A, Hoppe, R, Hopper, JL, Hunter, DJ, Jacot, W, Jakubowska, A, John, EM, Jung, AY, Kaaks, R, Khusnutdinova, E, Koppert, LB, Kraft, P, Kristensen, VN, Kurian, AW, Lambrechts, D, Le Marchand, L, Lindblom, A, Luben, RN, Lubinski, J, Mannermaa, A, Manoochehri, M, Margolin, S, Mavroudis, D, Muranen, TA, Nevanlinna, H, Olshan, AF, Olsson, H, Park-Simon, T-W, Patel, AV, Peterlongo, P, Pharoah, PDP, Punie, K, Radice, P, Rennert, G, Rennert, HS, Romero, A, Roylance, R, Ruediger, T, Ruebner, M, Saloustros, E, Sawyer, EJ, Schmutzler, RK, Schoemaker, MJ, Scott, C, Southey, MC, Surowy, H, Swerdlow, AJ, Tamimi, RM, Teras, LR, Thomas, E, Tomlinson, I, Troester, MA, Vachon, CM, Wang, Q, Winqvist, R, Wolk, A, Ziogas, A, Michailidou, K, Chenevix-Trench, G, Bachelot, T, and Schmidt, MK
Abstract: Breast cancer metastasis accounts for most of the deaths from breast cancer. Identification of germline variants associated with survival in aggressive types of breast cancer may inform understanding of breast cancer progression and assist treatment. In this analysis, we studied the associations between germline variants and breast cancer survival for patients with distant metastases at primary breast cancer diagnosis. We used data from the Breast Cancer Association Consortium (BCAC) including 1062 women of European ancestry with metastatic breast cancer, 606 of whom died of breast cancer. We identified two germline variants on chromosome 1, rs138569520 and rs146023652, significantly associated with breast cancer-specific survival (P = 3.19 × 10-8 and 4.42 × 10-8). In silico analysis suggested a potential regulatory effect of the variants on the nearby target genes SDE2 and H3F3A. However, the variants showed no evidence of association in a smaller replication dataset. The validation dataset was obtained from the SNPs to Risk of Metastasis (StoRM) study and included 293 patients with metastatic primary breast cancer at diagnosis. Ultimately, larger replication studies are needed to confirm the identified associations.
Published: 2021

16. Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

Author: Morra, A, Escala-Garcia, M, Beesley, J, Keeman, R, Canisius, S, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Arndt, V, Auer, PL, Augustinsson, A, Freeman, LEB, Becher, H, Beckmann, MW, Behrens, S, Bojesen, SE, Bolla, MK, Brenner, H, Bruening, T, Buys, SS, Caan, B, Campa, D, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Cheng, T-YD, Clarke, CL, Colonna, S, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Dennis, J, Dork, T, Dossus, L, Dunning, AM, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Eriksson, M, Evans, DG, Fasching, PA, Flyger, H, Fritschi, L, Gago-Dominguez, M, Garcia-Saenz, JA, Giles, GG, Grip, M, Guenel, P, Guendert, M, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hart, SN, Hartikainen, JM, Hartmann, A, He, W, Hooning, MJ, Hoppe, R, Hopper, JL, Howell, A, Hunter, DJ, Jager, A, Jakubowska, A, Janni, W, John, EM, Jung, AY, Kaaks, R, Keupers, M, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kurian, AW, Lacey, J, Lambrechts, D, Le Marchand, L, Lindblom, A, Linet, M, Luben, RN, Lush, M, Mannermaa, A, Manoochehri, M, Margolin, S, Martens, JWM, Martinez, ME, Mavroudis, D, Michailidou, K, Milne, RL, Mulligan, AM, Muranen, TA, Nevanlinna, H, Newman, WG, Nielsen, SF, Nordestgaard, BG, Olshan, AF, Olsson, H, Orr, N, Park-Simon, T-W, Patel, A, Peissel, B, Peterlongo, P, Plaseska-Karanfilska, D, Prajzendanc, K, Prentice, R, Presneau, N, Rack, B, Rennert, G, Rennert, HS, Rhenius, V, Romero, A, Roylance, R, Lubinski, J, Ruebner, M, Saloustros, E, Sawyer, EJ, Schmutzler, RK, Schneeweiss, A, Scott, C, Shah, M, Smichkoska, S, Southey, MC, Stone, J, Surowy, H, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Teras, LR, Terry, MB, Tollenaar, RAEM, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, Wang, Q, Hurson, AN, Winqvist, R, Wolk, A, Ziogas, A, Brauch, H, Garcia-Closas, M, Pharoah, PDP, Easton, DF, Chenevix-Trench, G, Schmidt, MK, Morra, A, Escala-Garcia, M, Beesley, J, Keeman, R, Canisius, S, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Arndt, V, Auer, PL, Augustinsson, A, Freeman, LEB, Becher, H, Beckmann, MW, Behrens, S, Bojesen, SE, Bolla, MK, Brenner, H, Bruening, T, Buys, SS, Caan, B, Campa, D, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Cheng, T-YD, Clarke, CL, Colonna, S, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Dennis, J, Dork, T, Dossus, L, Dunning, AM, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Eriksson, M, Evans, DG, Fasching, PA, Flyger, H, Fritschi, L, Gago-Dominguez, M, Garcia-Saenz, JA, Giles, GG, Grip, M, Guenel, P, Guendert, M, Hahnen, E, Haiman, CA, Hakansson, N, Hall, P, Hamann, U, Hart, SN, Hartikainen, JM, Hartmann, A, He, W, Hooning, MJ, Hoppe, R, Hopper, JL, Howell, A, Hunter, DJ, Jager, A, Jakubowska, A, Janni, W, John, EM, Jung, AY, Kaaks, R, Keupers, M, Kitahara, CM, Koutros, S, Kraft, P, Kristensen, VN, Kurian, AW, Lacey, J, Lambrechts, D, Le Marchand, L, Lindblom, A, Linet, M, Luben, RN, Lush, M, Mannermaa, A, Manoochehri, M, Margolin, S, Martens, JWM, Martinez, ME, Mavroudis, D, Michailidou, K, Milne, RL, Mulligan, AM, Muranen, TA, Nevanlinna, H, Newman, WG, Nielsen, SF, Nordestgaard, BG, Olshan, AF, Olsson, H, Orr, N, Park-Simon, T-W, Patel, A, Peissel, B, Peterlongo, P, Plaseska-Karanfilska, D, Prajzendanc, K, Prentice, R, Presneau, N, Rack, B, Rennert, G, Rennert, HS, Rhenius, V, Romero, A, Roylance, R, Lubinski, J, Ruebner, M, Saloustros, E, Sawyer, EJ, Schmutzler, RK, Schneeweiss, A, Scott, C, Shah, M, Smichkoska, S, Southey, MC, Stone, J, Surowy, H, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Teras, LR, Terry, MB, Tollenaar, RAEM, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, Wang, Q, Hurson, AN, Winqvist, R, Wolk, A, Ziogas, A, Brauch, H, Garcia-Closas, M, Pharoah, PDP, Easton, DF, Chenevix-Trench, G, and Schmidt, MK
Abstract: BACKGROUND: Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients. METHODS: We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15). RESULTS: Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy. CONCLUSIONS: We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast
Published: 2021

17. Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element

Author: Baxter, JS, Johnson, N, Tomczyk, K, Gillespie, A, Maguire, S, Brough, R, Fachal, L, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Becher, H, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bogdanova, N, Bojesen, SE, Brenner, H, Brucker, SY, Cai, Q, Campa, D, Canzian, F, Castelao, JE, Chan, TL, Chang-Claude, J, Chanock, SJ, Chenevix-Trench, G, Choi, J-Y, Clarke, CL, Collaborators, N, Colonna, S, Conroy, DM, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Doerk, T, Dossus, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Engel, C, Fasching, PA, Figueroa, J, Flyger, H, Gago-Dominguez, M, Gao, C, Garcia-Closas, M, Garcia-Saenz, JA, Ghoussaini, M, Giles, GG, Goldberg, MS, Gonzalez-Neira, A, Guenel, P, Guendert, M, Haeberle, L, Hahnen, E, Haiman, CA, Hall, P, Hamann, U, Hartman, M, Hatse, S, Hauke, J, Hollestelle, A, Hoppe, R, Hopper, JL, Hou, M-F, Ito, H, Iwasaki, M, Jager, A, Jakubowska, A, Janni, W, John, EM, Joseph, V, Jung, A, Kaaks, R, Kang, D, Keeman, R, Khusnutdinova, E, Kim, S-W, Kosma, V-M, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Kwong, A, Lacey, J, Lambrechts, D, Larson, NL, Larsson, SC, Le Marchand, L, Lejbkowicz, F, Li, J, Long, J, Lophatananon, A, LubiNski, J, Mannermaa, A, Manoochehri, M, Manoukian, S, Margolin, S, Matsuo, K, Mavroudis, D, Mayes, R, Menon, U, Milne, RL, Taib, NAM, Muir, K, Muranen, TA, Murphy, RA, Nevanlinna, H, O'Brien, KM, Offit, K, Olson, JE, Olsson, H, Park, SK, Park-Simon, T-W, Patel, A, Peterlongo, P, Peto, J, Plaseska-Karanfilska, D, Presneau, N, Pylkas, K, Rack, B, Rennert, G, Romero, A, Ruebner, M, Ruediger, T, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schneeweiss, A, Schoemaker, MJ, Shah, M, Shen, C-Y, Shu, X-O, Simard, J, Southey, MC, Stone, J, Surowy, H, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Terry, MB, Toland, AE, Tomlinson, I, Truong, T, Tseng, C-C, Untch, M, Vachon, CM, van den Ouweland, AMW, Wang, SS, Weinberg, CR, Wendt, C, Winham, SJ, Winqvist, R, Wolk, A, Wu, AH, Yamaji, T, Zheng, W, Ziogas, A, Pharoah, PDP, Dunning, AM, Easton, DF, Pettitt, SJ, Lord, CJ, Haider, S, Orr, N, Fletcher, O, Baxter, JS, Johnson, N, Tomczyk, K, Gillespie, A, Maguire, S, Brough, R, Fachal, L, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Becher, H, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bogdanova, N, Bojesen, SE, Brenner, H, Brucker, SY, Cai, Q, Campa, D, Canzian, F, Castelao, JE, Chan, TL, Chang-Claude, J, Chanock, SJ, Chenevix-Trench, G, Choi, J-Y, Clarke, CL, Collaborators, N, Colonna, S, Conroy, DM, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Doerk, T, Dossus, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Engel, C, Fasching, PA, Figueroa, J, Flyger, H, Gago-Dominguez, M, Gao, C, Garcia-Closas, M, Garcia-Saenz, JA, Ghoussaini, M, Giles, GG, Goldberg, MS, Gonzalez-Neira, A, Guenel, P, Guendert, M, Haeberle, L, Hahnen, E, Haiman, CA, Hall, P, Hamann, U, Hartman, M, Hatse, S, Hauke, J, Hollestelle, A, Hoppe, R, Hopper, JL, Hou, M-F, Ito, H, Iwasaki, M, Jager, A, Jakubowska, A, Janni, W, John, EM, Joseph, V, Jung, A, Kaaks, R, Kang, D, Keeman, R, Khusnutdinova, E, Kim, S-W, Kosma, V-M, Kraft, P, Kristensen, VN, Kubelka-Sabit, K, Kurian, AW, Kwong, A, Lacey, J, Lambrechts, D, Larson, NL, Larsson, SC, Le Marchand, L, Lejbkowicz, F, Li, J, Long, J, Lophatananon, A, LubiNski, J, Mannermaa, A, Manoochehri, M, Manoukian, S, Margolin, S, Matsuo, K, Mavroudis, D, Mayes, R, Menon, U, Milne, RL, Taib, NAM, Muir, K, Muranen, TA, Murphy, RA, Nevanlinna, H, O'Brien, KM, Offit, K, Olson, JE, Olsson, H, Park, SK, Park-Simon, T-W, Patel, A, Peterlongo, P, Peto, J, Plaseska-Karanfilska, D, Presneau, N, Pylkas, K, Rack, B, Rennert, G, Romero, A, Ruebner, M, Ruediger, T, Saloustros, E, Sandler, DP, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schneeweiss, A, Schoemaker, MJ, Shah, M, Shen, C-Y, Shu, X-O, Simard, J, Southey, MC, Stone, J, Surowy, H, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Teo, SH, Teras, LR, Terry, MB, Toland, AE, Tomlinson, I, Truong, T, Tseng, C-C, Untch, M, Vachon, CM, van den Ouweland, AMW, Wang, SS, Weinberg, CR, Wendt, C, Winham, SJ, Winqvist, R, Wolk, A, Wu, AH, Yamaji, T, Zheng, W, Ziogas, A, Pharoah, PDP, Dunning, AM, Easton, DF, Pettitt, SJ, Lord, CJ, Haider, S, Orr, N, and Fletcher, O
Abstract: A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).
Published: 2021

18. Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

Author: Park, J, Choi, J-Y, Choi, J, Chung, S, Song, N, Park, SK, Han, W, Noh, D-Y, Ahn, S-H, Lee, JW, Kim, MK, Jee, SH, Wen, W, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Shah, M, Conroy, DM, Harrington, PA, Mayes, R, Czene, K, Hall, P, Teras, LR, Patel, AV, Couch, FJ, Olson, JE, Sawyer, EJ, Roylance, R, Bojesen, SE, Flyger, H, Lambrechts, D, Baten, A, Matsuo, K, Ito, H, Guenel, P, Truong, T, Keeman, R, Schmidt, MK, Wu, AH, Tseng, C-C, Cox, A, Cross, SS, Andrulis, IL, Hopper, JL, Southey, MC, Wu, P-E, Shen, C-Y, Fasching, PA, Ekici, AB, Muir, K, Lophatananon, A, Brenner, H, Arndt, V, Jones, ME, Swerdlow, AJ, Hoppe, R, Ko, Y-D, Hartman, M, Li, J, Mannermaa, A, Hartikainen, JM, Benitez, J, Gonzalez-Neira, A, Haiman, CA, Doerk, T, Bogdanova, NV, Teo, SH, Mohd Taib, NA, Fletcher, O, Johnson, N, Grip, M, Winqvist, R, Blomqvist, C, Nevanlinna, H, Lindblom, A, Wendt, C, Kristensen, VN, Tollenaar, RAEM, Heemskerk-Gerritsen, BAM, Radice, P, Bonanni, B, Hamann, U, Manoochehri, M, Lacey, JV, Martinez, ME, Dunning, AM, Pharoah, PDP, Easton, DF, Yoo, K-Y, Kang, D, Park, J, Choi, J-Y, Choi, J, Chung, S, Song, N, Park, SK, Han, W, Noh, D-Y, Ahn, S-H, Lee, JW, Kim, MK, Jee, SH, Wen, W, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Shah, M, Conroy, DM, Harrington, PA, Mayes, R, Czene, K, Hall, P, Teras, LR, Patel, AV, Couch, FJ, Olson, JE, Sawyer, EJ, Roylance, R, Bojesen, SE, Flyger, H, Lambrechts, D, Baten, A, Matsuo, K, Ito, H, Guenel, P, Truong, T, Keeman, R, Schmidt, MK, Wu, AH, Tseng, C-C, Cox, A, Cross, SS, Andrulis, IL, Hopper, JL, Southey, MC, Wu, P-E, Shen, C-Y, Fasching, PA, Ekici, AB, Muir, K, Lophatananon, A, Brenner, H, Arndt, V, Jones, ME, Swerdlow, AJ, Hoppe, R, Ko, Y-D, Hartman, M, Li, J, Mannermaa, A, Hartikainen, JM, Benitez, J, Gonzalez-Neira, A, Haiman, CA, Doerk, T, Bogdanova, NV, Teo, SH, Mohd Taib, NA, Fletcher, O, Johnson, N, Grip, M, Winqvist, R, Blomqvist, C, Nevanlinna, H, Lindblom, A, Wendt, C, Kristensen, VN, Tollenaar, RAEM, Heemskerk-Gerritsen, BAM, Radice, P, Bonanni, B, Hamann, U, Manoochehri, M, Lacey, JV, Martinez, ME, Dunning, AM, Pharoah, PDP, Easton, DF, Yoo, K-Y, and Kang, D
Abstract: In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10-3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10-4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.
Published: 2021

19. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author: Ahearn, TU, Zhang, H, Michailidou, K, Milne, RL, Bolla, MK, Dennis, J, Dunning, AM, Lush, M, Wang, Q, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Auer, PL, Augustinsson, A, Baten, A, Becher, H, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bojesen, SE, Bonanni, B, Børresen-Dale, A-L, Brauch, H, Brenner, H, Brooks-Wilson, A, Brüning, T, Burwinkel, B, Buys, SS, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Sahlberg, KK, Ottestad, L, Kåresen, R, Schlichting, E, Holmen, MM, Sauer, T, Haakensen, V, Engebråten, O, Naume, B, Fosså, A, Kiserud, CE, Reinertsen, KV, Helland, Å, Riis, M, Geisler, J, Collée, JM, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Dörk, T, Dwek, M, Eccles, DM, Evans, DG, Fasching, PA, Figueroa, J, Floris, G, Gago-Dominguez, M, Gapstur, SM, García-Sáenz, JA, Gaudet, MM, Giles, GG, Goldberg, MS, González-Neira, A, Alnæs, GIG, Grip, M, Guénel, P, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Heemskerk-Gerritsen, BAM, Holleczek, B, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Howell, A, Clarke, C, Balleine, R, Baxter, R, Braye, S, Carpenter, J, Dahlstrom, J, Forbes, J, Lee, C, Marsh, D, Morey, A, Pathmanathan, N, Scott, R, Simpson, P, Spigelman, A, Wilcken, N, Yip, D, Zeps, N, Fox, S, Campbell, I, Bowtell, D, Spurdle, A, Webb, P, de Fazio, A, Tassell, M, Kirk, J, Lindeman, G, Price, M, Southey, M, Milne, R, Deb, S, Jakimovska, M, Jakubowska, A, John, EM, Jones, ME, Jung, A, Kaaks, R, Kauppila, S, Keeman, R, Khusnutdinova, E, Kitahara, CM, Ko, Y-D, Koutros, S, Kristensen, VN, Krüger, U, Kubelka-Sabit, K, Kurian, AW, Kyriacou, K, Lambrechts, D, Lee, DG, Lindblom, A, Linet, M, Lissowska, J, Llaneza, A, Lo, W-Y, MacInnis, RJ, Mannermaa, A, Manoochehri, M, Margolin, S, Martinez, ME, McLean, C, Meindl, A, Menon, U, Nevanlinna, H, Newman, WG, Nodora, J, Offit, K, Olsson, H, Orr, N, Park-Simon, T-W, Patel, AV, Peto, J, Pita, G, Plaseska-Karanfilska, D, Prentice, R, Punie, K, Pylkäs, K, Radice, P, Rennert, G, Romero, A, Rüdiger, T, Saloustros, E, Sampson, S, Sandler, DP, Sawyer, EJ, Schmutzler, RK, Schoemaker, MJ, Schöttker, B, Sherman, ME, Shu, X-O, Smichkoska, S, Southey, MC, Spinelli, JJ, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Teras, LR, Terry, MB, Torres, D, Troester, MA, Vachon, CM, van Deurzen, CHM, van Veen, EM, Wagner, P, Weinberg, CR, Wendt, C, Wesseling, J, Winqvist, R, Wolk, A, Yang, XR, Zheng, W, Couch, FJ, Simard, J, Kraft, P, Easton, DF, Pharoah, PDP, Schmidt, MK, García-Closas, M, Chatterjee, N, Ahearn, Thomas U [0000-0003-0771-7752], Easton, Douglas [0000-0003-2444-3247], Pharoah, Paul [0000-0001-8494-732X], Apollo - University of Cambridge Repository, Medicum, HUS Comprehensive Cancer Center, Department of Oncology, Clinicum, Department of Obstetrics and Gynecology, Biosciences, HUS Gynecology and Obstetrics, Clinical Genetics, Medical Oncology, and Pathology
Subjects: False discovery rate, Oncology, Common breast cancer susceptibility variants, Receptor, ErbB-2, Estrogen receptor, PROGRESSION, Etiologic heterogeneity, Logistic regression, Basic medicine, Breast cancer, 0302 clinical medicine, PRIMARY THERAPY, HETEROGENEITY, RC254-282, HISTOLOGICAL GRADE, 0303 health sciences, Breast Neoplasms/epidemiology, Receptors, Estrogen/genetics, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, INTERNATIONAL EXPERT CONSENSUS, humanities, Receptor, ErbB-2/genetics, 3. Good health, Receptors, Estrogen, Receptors, Progesterone/genetics, 030220 oncology & carcinogenesis, Female, Biomarkers, Tumor/genetics, Receptors, Progesterone, Medical Genetics, Research Article, Risk, medicine.medical_specialty, SUSCEPTIBILITY LOCI, 3122 Cancers, Breast Neoplasms, Single-nucleotide polymorphism, Biology, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Internal medicine, Progesterone receptor, Biomarkers, Tumor, medicine, Genetic predisposition, Humans, ddc:610, GENOME-WIDE ASSOCIATION, Genetic association, Medicinsk genetik, 030304 developmental biology, Cancer och onkologi, medicine.disease, Cancer and Oncology, Clinical medicine, Genome-Wide Association Study
Abstract: Background Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. Methods Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. Results Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate p Conclusion This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
Published: 2020
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20. Genetically Determined Height and Risk of Non-hodgkin Lymphoma

Author: 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.
Published: 2020

21. Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes

Author: Din, L, Sheikh, M, Kosaraju, N, Smedby, KE, Bernatsky, S, Berndt, S, Skibola, CF, Nieters, A, Wang, S, McKay, JD, Cocco, P, Maynadie, M, Foretova, L, Staines, A, Mack, TM, de Sanjose, S, Vyse, TJ, Padyukov, L, Monnereau, A, Arslan, AA, Moore, A, Brooks-Wilson, AR, Novak, AJ, Glimelius, B, Birmann, BM, Link, BK, Stewart, C, Vajdic, CM, Haioun, C, Magnani, C, Conti, D, Cox, DG, Casabonne, D, Albanes, D, Kane, E, Roman, E, Muzi, G, Salles, G, Giles, GG, Adami, H-O, Ghesquieres, H, De Vivo, I, Clavel, J, Cerhan, JR, Spinelli, JJ, Hofmann, J, Vijai, J, Curtin, K, Costenbader, KH, Onel, K, Offit, K, Teras, LR, Morton, L, Conde, L, Miligi, L, Melbye, M, Ennas, MG, Liebow, M, Purdue, MP, Glenn, M, Southey, MC, Din, M, Rothman, N, Camp, NJ, Doo, NW, Becker, N, Pradhan, N, Bracci, PM, Boffetta, P, Vineis, P, Brennan, P, Kraft, P, Lan, Q, Severson, RK, Vermeulen, RCH, Milne, RL, Kaaks, R, Travis, RC, Weinstein, SJ, Chanock, SJ, Ansell, SM, Slager, SL, Zheng, T, Zhang, Y, Benavente, Y, Taub, Z, Madireddy, L, Gourraud, P-A, Oksenberg, JR, Cozen, W, Hjalgrim, H, Khankhanian, P, Din, L, Sheikh, M, Kosaraju, N, Smedby, KE, Bernatsky, S, Berndt, S, Skibola, CF, Nieters, A, Wang, S, McKay, JD, Cocco, P, Maynadie, M, Foretova, L, Staines, A, Mack, TM, de Sanjose, S, Vyse, TJ, Padyukov, L, Monnereau, A, Arslan, AA, Moore, A, Brooks-Wilson, AR, Novak, AJ, Glimelius, B, Birmann, BM, Link, BK, Stewart, C, Vajdic, CM, Haioun, C, Magnani, C, Conti, D, Cox, DG, Casabonne, D, Albanes, D, Kane, E, Roman, E, Muzi, G, Salles, G, Giles, GG, Adami, H-O, Ghesquieres, H, De Vivo, I, Clavel, J, Cerhan, JR, Spinelli, JJ, Hofmann, J, Vijai, J, Curtin, K, Costenbader, KH, Onel, K, Offit, K, Teras, LR, Morton, L, Conde, L, Miligi, L, Melbye, M, Ennas, MG, Liebow, M, Purdue, MP, Glenn, M, Southey, MC, Din, M, Rothman, N, Camp, NJ, Doo, NW, Becker, N, Pradhan, N, Bracci, PM, Boffetta, P, Vineis, P, Brennan, P, Kraft, P, Lan, Q, Severson, RK, Vermeulen, RCH, Milne, RL, Kaaks, R, Travis, RC, Weinstein, SJ, Chanock, SJ, Ansell, SM, Slager, SL, Zheng, T, Zhang, Y, Benavente, Y, Taub, Z, Madireddy, L, Gourraud, P-A, Oksenberg, JR, Cozen, W, Hjalgrim, H, and Khankhanian, P
Abstract: Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.
Published: 2019

22. Blood levels of cadmium and lead in relation to breast cancer risk in three prospective cohorts

Author: Gaudet, MM, Deubler, EL, Kelly, RS, Diver, WR, Teras, LR, Hodge, JM, Levine, KE, Haines, LG, Lundh, T, Lenner, P, Palli, D, Vineis, P, Bergdahl, IA, Gapstur, SM, Kyrtopoulos, SA, and Commission of the European Communities
Subjects: ENVIRONMENTAL CADMIUM, Breast Neoplasms, Article, breast cancer, Risk Factors, Humans, 1112 Oncology and Carcinogenesis, EXPOSURE, Oncology & Carcinogenesis, Prospective Studies, POPULATION, Aged, Aged, 80 and over, Sweden, Science & Technology, HERITABILITY, MORTALITY, WOMEN, Environmental Exposure, Middle Aged, PREVENTION, Oncology, Italy, Lead, Case-Control Studies, Carcinogens, SEX-HORMONES, Female, HEALTH, Life Sciences & Biomedicine, URINARY CADMIUM, Cadmium
Abstract: Cadmium and lead have been classified as carcinogens by the International Agency for Research on Cancer. However, their associations with breast cancer risk are unknown despite their persistence in the environment and ubiquitous human exposure. We examined associations of circulating levels of cadmium and lead with breast cancer risk in three case-control studies nested within the Cancer Prevention Study-II (CPS-II) LifeLink Cohort, European Prospective Investigation into Cancer and Nutrition - Italy (EPIC-Italy), and the Northern Sweden Health and Disease Study (NSHDS) cohorts. Metal levels were measured in stored erythrocytes from 1,435 cases and 1,433 controls using inductively coupled plasma-mass spectrometry. Summary relative risks (RR) and 95% confidence intervals (CI) were calculated using random-effects models with each study result weighted by the within- and between-study variances. I2 values were calculated to estimate proportion of between study variation. Using common cut-points, cadmium levels were not associated with breast cancer risk in the CPS-II cohort (continuous RR=1.01, 95% CI 0.76 - 1.34), but were inversely associated with risk in the EPIC- Italy (continuous RR=0.80, 95% CI 0.61 - 1.03) and NSHDS cohorts (continuous RR=0.73, 95% CI 0.54 - 0.97). The inverse association was also evident in the meta-analysis (continuous RR=0.84, 95% CI 0.69 - 1.01) with low between-study heterogeneity. Large differences in lead level distributions precluded a meta-analysis of their association with breast cancer risk; no associations were found in the three studies. Adult cadmium and lead levels were not associated with higher risk of breast cancer in our large meta-analysis.
Published: 2018

23. Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukemia

Author: Law, PJ, Berndt, SI, Speedy, HE, Camp, NJ, Sava, GP, Skibola, CF, Holroyd, A, Joseph, V, Sunter, NJ, Nieters, A, Bea, S, Monnereau, A, Martin-Garcia, D, Goldin, LR, Clot, G, Teras, LR, Quintela, I, Birmann, BM, Jayne, S, Cozen, W, Majid, A, Smedby, KE, Dearden, C, Brooks-Wilson, AR, Hall, AG, Purdue, MP, Mainou-Fowler, T, Vajdic, CM, Jackson, GH, Cocco, P, Marr, H, Zhang, Y, Zheng, T, Giles, GG, Lawrence, C, Call, TG, Liebow, M, Melbye, M, Glimelius, B, Mansouri, L, Glenn, M, Curtin, K, Diver, WR, Link, BK, Conde, L, Bracci, PM, Holly, EA, Jackson, RD, Tinker, LF, Benavente, Y, Boffetta, P, Brennan, P, Maynadie, M, McKay, J, Albanes, D, Weinstein, S, Wang, Z, Caporaso, NE, Morton, LM, Severson, RK, Riboli, E, Vineis, P, Vermeulen, RCH, Southey, MC, Milne, RL, Clavel, J, Topka, S, Spinelli, JJ, Kraft, P, Grazia Ennas, M, Summerfield, G, Ferri, GM, Harris, RJ, Miligi, L, Pettitt, AR, North, KE, Allsup, DJ, Fraumeni, JF, Bailey, JR, Offit, K, Pratt, G, Hjalgrim, H, Pepper, C, Chanock, SJ, Fegan, C, Rosenquist, R, De Sanjose, S, Carracedo, A, Dyer, MJS, Catovsky, D, Campo, E, Cerhan, JR, Allan, JM, Rothman, N, Houlston, R, and Slager, S
Subjects: RISK, CHROMATIN, Science & Technology, LOCI, VARIANTS, DISEASE, Multidisciplinary Sciences, TRANSCRIPTION FACTORS, MD Multidisciplinary, IMPUTATION, Science & Technology - Other Topics, BREAST-CANCER, COMMON VARIATION, METAANALYSIS
Abstract: Several chronic lymphocytic leukemia (CLL) susceptibility loci have been reported, however much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1000 Genomes and UK10K data, totaling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P = 5.04x10-13), 1q42.13 (rs41271473, P = 1.06x10-10), 4q24 (rs71597109, P = 1.37x10-10), 4q35.1 (rs57214277, P = 3.69x10-8), 6p21.31 (rs3800461, P = 1.97x10-8), 11q23.2 (rs61904987, P = 2.64x10-11), 18q21.1 (rs1036935, P = 3.27x10-8), 19p13.3 (rs7254272, P = 4.67x10-8) and 22q13.33 (rs140522, P = 2.70x10-9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for key determinants of B-cell development and immune response.
Published: 2016

24. Circulating resistin levels and risk of multiple myeloma in three prospective cohorts

Author: Santo, L, Teras, LR, Giles, GG, Weinstein, SJ, Albanes, D, Wang, Y, Pfeiffer, RM, Lan, Q, Rothman, N, Birmann, BM, Colditz, GA, Pollak, MN, Purdue, MP, Hofmann, JN, Santo, L, Teras, LR, Giles, GG, Weinstein, SJ, Albanes, D, Wang, Y, Pfeiffer, RM, Lan, Q, Rothman, N, Birmann, BM, Colditz, GA, Pollak, MN, Purdue, MP, and Hofmann, JN
Abstract: BACKGROUND: Resistin is a polypeptide hormone secreted by adipose tissue. A prior hospital-based case-control study reported serum resistin levels to be inversely associated with risk of multiple myeloma (MM). To date, this association has not been investigated prospectively. METHODS: We measured resistin concentrations for pre-diagnosis peripheral blood samples from 178 MM cases and 358 individually matched controls from three cohorts participating in the MM cohort consortium. RESULTS: In overall analyses, higher resistin levels were weakly associated with reduced MM risk. For men, we observed a statistically significant inverse association between resistin levels and MM (odds ratio, 0.44; 95% confidence interval (CI) 0.24-0.83 and 0.54; 95% CI 0.29-0.99, for the third and fourth quartiles, respectively, vs the lowest quartile; Ptrend=0.03). No association was observed for women. CONCLUSIONS: This study provides the first prospective evidence that low circulating resistin levels may be associated with an increased risk of MM, particularly for men.
Published: 2017

25. Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia

Author: Law, PJ, Berndt, SI, Speedy, HE, Camp, NJ, Sava, GP, Skibola, CF, Holroyd, A, Joseph, V, Sunter, NJ, Nieters, A, Bea, S, Monnereau, A, Martin-Garcia, D, Goldin, LR, Clot, G, Teras, LR, Quintela, I, Birmann, BM, Jayne, S, Cozen, W, Majid, A, Smedby, KE, Lan, Q, Dearden, C, Brooks-Wilson, AR, Hall, AG, Purdue, MP, Mainou-Fowler, T, Vajdic, CM, Jackson, GH, Cocco, P, Marr, H, Zhang, Y, Zheng, T, Giles, GG, Lawrence, C, Call, TG, Liebow, M, Melbye, M, Glimelius, B, Mansouri, L, Glenn, M, Curtin, K, Diver, WR, Link, BK, Conde, L, Bracci, PM, Holly, EA, Jackson, RD, Tinker, LF, Benavente, Y, Boffetta, P, Brennan, P, Maynadie, M, McKay, J, Albanes, D, Weinstein, S, Wang, Z, Caporaso, NE, Morton, LM, Severson, RK, Riboli, E, Vineis, P, Vermeulen, RCH, Southey, MC, Milne, RL, Clavel, J, Topka, S, Spinelli, JJ, Kraft, P, Ennas, MG, Summerfield, G, Ferri, GM, Harris, RJ, Miligi, L, Pettitt, AR, North, KE, Allsup, DJ, Fraumeni, JF, Bailey, JR, Offit, K, Pratt, G, Hjalgrim, H, Pepper, C, Chanock, SJ, Fegan, C, Rosenquist, R, de Sanjose, S, Carracedo, A, Dyer, MJS, Catovsky, D, Campo, E, Cerhan, JR, Allan, JM, Rothman, N, Houlston, R, Slager, SL, Law, PJ, Berndt, SI, Speedy, HE, Camp, NJ, Sava, GP, Skibola, CF, Holroyd, A, Joseph, V, Sunter, NJ, Nieters, A, Bea, S, Monnereau, A, Martin-Garcia, D, Goldin, LR, Clot, G, Teras, LR, Quintela, I, Birmann, BM, Jayne, S, Cozen, W, Majid, A, Smedby, KE, Lan, Q, Dearden, C, Brooks-Wilson, AR, Hall, AG, Purdue, MP, Mainou-Fowler, T, Vajdic, CM, Jackson, GH, Cocco, P, Marr, H, Zhang, Y, Zheng, T, Giles, GG, Lawrence, C, Call, TG, Liebow, M, Melbye, M, Glimelius, B, Mansouri, L, Glenn, M, Curtin, K, Diver, WR, Link, BK, Conde, L, Bracci, PM, Holly, EA, Jackson, RD, Tinker, LF, Benavente, Y, Boffetta, P, Brennan, P, Maynadie, M, McKay, J, Albanes, D, Weinstein, S, Wang, Z, Caporaso, NE, Morton, LM, Severson, RK, Riboli, E, Vineis, P, Vermeulen, RCH, Southey, MC, Milne, RL, Clavel, J, Topka, S, Spinelli, JJ, Kraft, P, Ennas, MG, Summerfield, G, Ferri, GM, Harris, RJ, Miligi, L, Pettitt, AR, North, KE, Allsup, DJ, Fraumeni, JF, Bailey, JR, Offit, K, Pratt, G, Hjalgrim, H, Pepper, C, Chanock, SJ, Fegan, C, Rosenquist, R, de Sanjose, S, Carracedo, A, Dyer, MJS, Catovsky, D, Campo, E, Cerhan, JR, Allan, JM, Rothman, N, Houlston, R, and Slager, SL
Abstract: Several chronic lymphocytic leukaemia (CLL) susceptibility loci have been reported; however, much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1,000 Genomes and UK10K data, totalling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P=5.04 × 10-13), 1q42.13 (rs41271473, P=1.06 × 10-10), 4q24 (rs71597109, P=1.37 × 10-10), 4q35.1 (rs57214277, P=3.69 × 10-8), 6p21.31 (rs3800461, P=1.97 × 10-8), 11q23.2 (rs61904987, P=2.64 × 10-11), 18q21.1 (rs1036935, P=3.27 × 10-8), 19p13.3 (rs7254272, P=4.67 × 10-8) and 22q13.33 (rs140522, P=2.70 × 10-9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for the key determinants of B-cell development and immune response.
Published: 2017

26. Lupus-related single nucleotide polymorphisms and risk of diffuse large B-cell lymphoma

Author: Bernatsky, S, Garcia, HAV, Spinelli, JJ, Gaffney, P, Smedby, KE, Ramsey-Goldman, R, Wang, SS, Adami, H-O, Albanes, D, Angelucci, E, Ansell, SM, Asmann, YW, Becker, N, Benavente, Y, Berndt, SI, Bertrand, KA, Birmann, BM, Boeing, H, Boffetta, P, Bracci, PM, Brennan, P, Brooks-Wilson, AR, Cerhan, JR, Chanock, SJ, Clavel, J, Conde, L, Cotenbader, KH, Cox, DG, Cozen, W, Crouch, S, De Roos, AJ, de Sanjose, S, Di Lollo, S, Diver, WR, Dogan, A, Foretova, L, Ghesquieres, H, Giles, GG, Glimelius, B, Habermann, TM, Haioun, C, Hartge, P, Hjalgrim, H, Holford, TR, Holly, EA, Jackson, RD, Kaaks, R, Kane, E, Kelly, RS, Klein, RJ, Kraft, P, Kricker, A, Lan, Q, Lawrence, C, Liebow, M, Lightfoot, T, Link, BK, Maynadie, M, Mckay, J, Melbye, M, Molina, TJ, Monnereau, A, Morton, LM, Nieters, A, North, KE, Novak, AJ, Offit, K, Purdue, MP, Rais, M, Riby, J, Roman, E, Rothman, N, Salles, G, Severi, G, Severson, RK, Skibola, CF, Slager, SL, Smith, A, Smith, MT, Southey, MC, Staines, A, Teras, LR, Thompson, CA, Tilly, H, Tinker, LF, Tjonneland, A, Turner, J, Vajdic, CM, Vermeulen, RCH, Vijai, J, Vineis, P, Virtamo, J, Wang, Z, Weinstein, S, Witzig, TE, Zelenetz, A, Zeleniuch-Jacquotte, A, Zhang, Y, Zheng, T, Zucca, M, Clarke, AE, Bernatsky, S, Garcia, HAV, Spinelli, JJ, Gaffney, P, Smedby, KE, Ramsey-Goldman, R, Wang, SS, Adami, H-O, Albanes, D, Angelucci, E, Ansell, SM, Asmann, YW, Becker, N, Benavente, Y, Berndt, SI, Bertrand, KA, Birmann, BM, Boeing, H, Boffetta, P, Bracci, PM, Brennan, P, Brooks-Wilson, AR, Cerhan, JR, Chanock, SJ, Clavel, J, Conde, L, Cotenbader, KH, Cox, DG, Cozen, W, Crouch, S, De Roos, AJ, de Sanjose, S, Di Lollo, S, Diver, WR, Dogan, A, Foretova, L, Ghesquieres, H, Giles, GG, Glimelius, B, Habermann, TM, Haioun, C, Hartge, P, Hjalgrim, H, Holford, TR, Holly, EA, Jackson, RD, Kaaks, R, Kane, E, Kelly, RS, Klein, RJ, Kraft, P, Kricker, A, Lan, Q, Lawrence, C, Liebow, M, Lightfoot, T, Link, BK, Maynadie, M, Mckay, J, Melbye, M, Molina, TJ, Monnereau, A, Morton, LM, Nieters, A, North, KE, Novak, AJ, Offit, K, Purdue, MP, Rais, M, Riby, J, Roman, E, Rothman, N, Salles, G, Severi, G, Severson, RK, Skibola, CF, Slager, SL, Smith, A, Smith, MT, Southey, MC, Staines, A, Teras, LR, Thompson, CA, Tilly, H, Tinker, LF, Tjonneland, A, Turner, J, Vajdic, CM, Vermeulen, RCH, Vijai, J, Vineis, P, Virtamo, J, Wang, Z, Weinstein, S, Witzig, TE, Zelenetz, A, Zeleniuch-Jacquotte, A, Zhang, Y, Zheng, T, Zucca, M, and Clarke, AE
Abstract: OBJECTIVE: Determinants of the increased risk of diffuse large B-cell lymphoma (DLBCL) in SLE are unclear. Using data from a recent lymphoma genome-wide association study (GWAS), we assessed whether certain lupus-related single nucleotide polymorphisms (SNPs) were also associated with DLBCL. METHODS: GWAS data on European Caucasians from the International Lymphoma Epidemiology Consortium (InterLymph) provided a total of 3857 DLBCL cases and 7666 general-population controls. Data were pooled in a random-effects meta-analysis. RESULTS: Among the 28 SLE-related SNPs investigated, the two most convincingly associated with risk of DLBCL included the CD40 SLE risk allele rs4810485 on chromosome 20q13 (OR per risk allele=1.09, 95% CI 1.02 to 1.16, p=0.0134), and the HLA SLE risk allele rs1270942 on chromosome 6p21.33 (OR per risk allele=1.17, 95% CI 1.01 to 1.36, p=0.0362). Of additional possible interest were rs2205960 and rs12537284. The rs2205960 SNP, related to a cytokine of the tumour necrosis factor superfamily TNFSF4, was associated with an OR per risk allele of 1.07, 95% CI 1.00 to 1.16, p=0.0549. The OR for the rs12537284 (chromosome 7q32, IRF5 gene) risk allele was 1.08, 95% CI 0.99 to 1.18, p=0.0765. CONCLUSIONS: These data suggest several plausible genetic links between DLBCL and SLE.
Published: 2017

27. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

Author: 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.
Published: 2016

28. Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia

Author: Berndt, SI, Camp, NJ, Skibola, CF, Vijai, J, Wang, Z, Gu, J, Nieters, A, Kelly, RS, Smedby, KE, Monnereau, A, Cozen, W, Cox, A, Wang, SS, Lan, Q, Teras, LR, Machado, M, Yeager, M, Brooks-Wilson, AR, Hartge, P, Purdue, MP, Birmann, BM, Vajdic, CM, Cocco, P, Zhang, Y, Giles, GG, Zeleniuch-Jacquotte, A, Lawrence, C, Montalvan, R, Burdett, L, Hutchinson, A, Ye, Y, Call, TG, Shanafelt, TD, Novak, AJ, Kay, NE, Liebow, M, Cunningham, JM, Allmer, C, Hjalgrim, H, Adami, H-O, Melbye, M, Glimelius, B, Chang, ET, Glenn, M, Curtin, K, Cannon-Albright, LA, Diver, WR, Link, BK, Weiner, GJ, Conde, L, Bracci, PM, Riby, J, Arnett, DK, Zhi, D, Leach, JM, Holly, EA, Jackson, RD, Tinker, LF, Benavente, Y, Sala, N, Casabonne, D, Becker, N, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, McKay, J, Staines, A, Chaffee, KG, Achenbach, SJ, Vachon, CM, Goldin, LR, Strom, SS, Leis, JF, Weinberg, JB, Caporaso, NE, Norman, AD, De Roos, AJ, Morton, LM, Severson, RK, Riboli, E, Vineis, P, Kaaks, R, Masala, G, Weiderpass, E, Chirlaque, M-D, Vermeulen, RCH, Travis, RC, Southey, MC, Milne, RL, Albanese, D, Virtamo, J, Weinstein, S, Clavel, J, Zheng, T, Holford, TR, Villano, DJ, Maria, A, Spinelli, JJ, Gascoyne, RD, Connors, JM, Bertrand, KA, Giovannucci, E, Kraft, P, Kricker, A, Turner, J, Ennas, MG, Ferri, GM, Miligi, L, Liang, L, Ma, B, Huang, J, Crouch, S, Park, J-H, Chatterjee, N, North, KE, Snowden, JA, Wright, J, Fraumeni, JF, Offit, K, Wu, X, de Sanjose, S, Cerhan, JR, Chanock, SJ, Rothman, N, Slager, SL, Berndt, SI, Camp, NJ, Skibola, CF, Vijai, J, Wang, Z, Gu, J, Nieters, A, Kelly, RS, Smedby, KE, Monnereau, A, Cozen, W, Cox, A, Wang, SS, Lan, Q, Teras, LR, Machado, M, Yeager, M, Brooks-Wilson, AR, Hartge, P, Purdue, MP, Birmann, BM, Vajdic, CM, Cocco, P, Zhang, Y, Giles, GG, Zeleniuch-Jacquotte, A, Lawrence, C, Montalvan, R, Burdett, L, Hutchinson, A, Ye, Y, Call, TG, Shanafelt, TD, Novak, AJ, Kay, NE, Liebow, M, Cunningham, JM, Allmer, C, Hjalgrim, H, Adami, H-O, Melbye, M, Glimelius, B, Chang, ET, Glenn, M, Curtin, K, Cannon-Albright, LA, Diver, WR, Link, BK, Weiner, GJ, Conde, L, Bracci, PM, Riby, J, Arnett, DK, Zhi, D, Leach, JM, Holly, EA, Jackson, RD, Tinker, LF, Benavente, Y, Sala, N, Casabonne, D, Becker, N, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, McKay, J, Staines, A, Chaffee, KG, Achenbach, SJ, Vachon, CM, Goldin, LR, Strom, SS, Leis, JF, Weinberg, JB, Caporaso, NE, Norman, AD, De Roos, AJ, Morton, LM, Severson, RK, Riboli, E, Vineis, P, Kaaks, R, Masala, G, Weiderpass, E, Chirlaque, M-D, Vermeulen, RCH, Travis, RC, Southey, MC, Milne, RL, Albanese, D, Virtamo, J, Weinstein, S, Clavel, J, Zheng, T, Holford, TR, Villano, DJ, Maria, A, Spinelli, JJ, Gascoyne, RD, Connors, JM, Bertrand, KA, Giovannucci, E, Kraft, P, Kricker, A, Turner, J, Ennas, MG, Ferri, GM, Miligi, L, Liang, L, Ma, B, Huang, J, Crouch, S, Park, J-H, Chatterjee, N, North, KE, Snowden, JA, Wright, J, Fraumeni, JF, Offit, K, Wu, X, de Sanjose, S, Cerhan, JR, Chanock, SJ, Rothman, N, and Slager, SL
Abstract: Chronic lymphocytic leukemia (CLL) is a common lymphoid malignancy with strong heritability. To further understand the genetic susceptibility for CLL and identify common loci associated with risk, we conducted a meta-analysis of four genome-wide association studies (GWAS) composed of 3,100 cases and 7,667 controls with follow-up replication in 1,958 cases and 5,530 controls. Here we report three new loci at 3p24.1 (rs9880772, EOMES, P=2.55 × 10(-11)), 6p25.2 (rs73718779, SERPINB6, P=1.97 × 10(-8)) and 3q28 (rs9815073, LPP, P=3.62 × 10(-8)), as well as a new independent SNP at the known 2q13 locus (rs9308731, BCL2L11, P=1.00 × 10(-11)) in the combined analysis. We find suggestive evidence (P<5 × 10(-7)) for two additional new loci at 4q24 (rs10028805, BANK1, P=7.19 × 10(-8)) and 3p22.2 (rs1274963, CSRNP1, P=2.12 × 10(-7)). Pathway analyses of new and known CLL loci consistently show a strong role for apoptosis, providing further evidence for the importance of this biological pathway in CLL susceptibility.
Published: 2016

29. A genome-wide association study of marginal zone lymphoma shows association to the HLA region

Author: Vijai, J, Wang, Z, Berndt, SI, Skibola, CF, Slager, SL, de Sanjose, S, Melbye, M, Glimelius, B, Bracci, PM, Conde, L, Birmann, BM, Wang, SS, Brooks-Wilson, AR, Lan, Q, de Bakker, PIW, Vermeulen, RCH, Portlock, C, Ansell, SM, Link, BK, Riby, J, North, KE, Gu, J, Hjalgrim, H, Cozen, W, Becker, N, Teras, LR, Spinelli, JJ, Turner, J, Zhang, Y, Purdue, MP, Giles, GG, Kelly, RS, Zeleniuch-Jacquotte, A, Ennas, MG, Monnereau, A, Bertrand, KA, Albanes, D, Lightfoot, T, Yeager, M, Chung, CC, Burdett, L, Hutchinson, A, Lawrence, C, Montalvan, R, Liang, L, Huang, J, Ma, B, Villano, DJ, Maria, A, Corines, M, Thomas, T, Novak, AJ, Dogan, A, Liebow, M, Thompson, CA, Witzig, TE, Habermann, TM, Weiner, GJ, Smith, MT, Holly, EA, Jackson, RD, Tinker, LF, Ye, Y, Adami, H-O, Smedby, KE, De Roos, AJ, Hartge, P, Morton, LM, Severson, RK, Benavente, Y, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, Mckay, J, Staines, A, Diver, WR, Vajdic, CM, Armstrong, BK, Kricker, A, Zheng, T, Holford, TR, Severi, G, Vineis, P, Ferri, GM, Ricco, R, Miligi, L, Clavel, J, Giovannucci, E, Kraft, P, Virtamo, J, Smith, A, Kane, E, Roman, E, Chiu, BCH, Fraumeni, JF, Wu, X, Cerhan, JR, Offit, K, Chanock, SJ, Rothman, N, Nieters, A, Vijai, J, Wang, Z, Berndt, SI, Skibola, CF, Slager, SL, de Sanjose, S, Melbye, M, Glimelius, B, Bracci, PM, Conde, L, Birmann, BM, Wang, SS, Brooks-Wilson, AR, Lan, Q, de Bakker, PIW, Vermeulen, RCH, Portlock, C, Ansell, SM, Link, BK, Riby, J, North, KE, Gu, J, Hjalgrim, H, Cozen, W, Becker, N, Teras, LR, Spinelli, JJ, Turner, J, Zhang, Y, Purdue, MP, Giles, GG, Kelly, RS, Zeleniuch-Jacquotte, A, Ennas, MG, Monnereau, A, Bertrand, KA, Albanes, D, Lightfoot, T, Yeager, M, Chung, CC, Burdett, L, Hutchinson, A, Lawrence, C, Montalvan, R, Liang, L, Huang, J, Ma, B, Villano, DJ, Maria, A, Corines, M, Thomas, T, Novak, AJ, Dogan, A, Liebow, M, Thompson, CA, Witzig, TE, Habermann, TM, Weiner, GJ, Smith, MT, Holly, EA, Jackson, RD, Tinker, LF, Ye, Y, Adami, H-O, Smedby, KE, De Roos, AJ, Hartge, P, Morton, LM, Severson, RK, Benavente, Y, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, Mckay, J, Staines, A, Diver, WR, Vajdic, CM, Armstrong, BK, Kricker, A, Zheng, T, Holford, TR, Severi, G, Vineis, P, Ferri, GM, Ricco, R, Miligi, L, Clavel, J, Giovannucci, E, Kraft, P, Virtamo, J, Smith, A, Kane, E, Roman, E, Chiu, BCH, Fraumeni, JF, Wu, X, Cerhan, JR, Offit, K, Chanock, SJ, Rothman, N, and Nieters, A
Abstract: Marginal zone lymphoma (MZL) is the third most common subtype of B-cell non-Hodgkin lymphoma. Here we perform a two-stage GWAS of 1,281 MZL cases and 7,127 controls of European ancestry and identify two independent loci near BTNL2 (rs9461741, P=3.95 × 10(-15)) and HLA-B (rs2922994, P=2.43 × 10(-9)) in the HLA region significantly associated with MZL risk. This is the first evidence that genetic variation in the major histocompatibility complex influences MZL susceptibility.
Published: 2015

30. Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma

Author: Cerhan, JR, Berndt, SI, Vijai, J, Ghesquieres, H, McKay, J, Wang, SS, Wang, Z, Yeager, M, Conde, L, de Bakker, PIW, Nieters, A, Cox, D, Burdett, L, Monnereau, A, Flowers, CR, De Roos, AJ, Brooks-Wilson, AR, Lan, Q, Severi, G, Melbye, M, Gu, J, Jackson, RD, Kane, E, Teras, LR, Purdue, MP, Vajdic, CM, Spinelli, JJ, Giles, GG, Albanes, D, Kelly, RS, Zucca, M, Bertrand, KA, Zeleniuch-Jacquotte, A, Lawrence, C, Hutchinson, A, Zhi, D, Habermann, TM, Link, BK, Novak, AJ, Dogan, A, Asmann, YW, Liebow, M, Thompson, CA, Ansell, SM, Witzig, TE, Weiner, GJ, Veron, AS, Zelenika, D, Tilly, H, Haioun, C, Molina, TJ, Hjalgrim, H, Glimelius, B, Adami, H-O, Bracci, PM, Riby, J, Smith, MT, Holly, EA, Cozen, W, Hartge, P, Morton, LM, Severson, RK, Tinker, LF, North, KE, Becker, N, Benavente, Y, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, Staines, A, Lightfoot, T, Crouch, S, Smith, A, Roman, E, Diver, WR, Offit, K, Zelenetz, A, Klein, RJ, Villano, DJ, Zheng, T, Zhang, Y, Holford, TR, Kricker, A, Turner, J, Southey, MC, Clavel, J, Virtamo, J, Weinstein, S, Riboli, E, Vineis, P, Kaaks, R, Trichopoulos, D, Vermeulen, RCH, Boeing, H, Tjonneland, A, Angelucci, E, Di Lollo, S, Rais, M, Birmann, BM, Laden, F, Giovannucci, E, Kraft, P, Huang, J, Ma, B, Ye, Y, Chiu, BCH, Sampson, J, Liang, L, Park, J-H, Chung, CC, Weisenburger, DD, Chatterjee, N, Fraumeni, JF, Slager, SL, Wu, X, de Sanjose, S, Smedby, KE, Salles, G, Skibola, CF, Rothman, N, Chanock, SJ, Cerhan, JR, Berndt, SI, Vijai, J, Ghesquieres, H, McKay, J, Wang, SS, Wang, Z, Yeager, M, Conde, L, de Bakker, PIW, Nieters, A, Cox, D, Burdett, L, Monnereau, A, Flowers, CR, De Roos, AJ, Brooks-Wilson, AR, Lan, Q, Severi, G, Melbye, M, Gu, J, Jackson, RD, Kane, E, Teras, LR, Purdue, MP, Vajdic, CM, Spinelli, JJ, Giles, GG, Albanes, D, Kelly, RS, Zucca, M, Bertrand, KA, Zeleniuch-Jacquotte, A, Lawrence, C, Hutchinson, A, Zhi, D, Habermann, TM, Link, BK, Novak, AJ, Dogan, A, Asmann, YW, Liebow, M, Thompson, CA, Ansell, SM, Witzig, TE, Weiner, GJ, Veron, AS, Zelenika, D, Tilly, H, Haioun, C, Molina, TJ, Hjalgrim, H, Glimelius, B, Adami, H-O, Bracci, PM, Riby, J, Smith, MT, Holly, EA, Cozen, W, Hartge, P, Morton, LM, Severson, RK, Tinker, LF, North, KE, Becker, N, Benavente, Y, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, Staines, A, Lightfoot, T, Crouch, S, Smith, A, Roman, E, Diver, WR, Offit, K, Zelenetz, A, Klein, RJ, Villano, DJ, Zheng, T, Zhang, Y, Holford, TR, Kricker, A, Turner, J, Southey, MC, Clavel, J, Virtamo, J, Weinstein, S, Riboli, E, Vineis, P, Kaaks, R, Trichopoulos, D, Vermeulen, RCH, Boeing, H, Tjonneland, A, Angelucci, E, Di Lollo, S, Rais, M, Birmann, BM, Laden, F, Giovannucci, E, Kraft, P, Huang, J, Ma, B, Ye, Y, Chiu, BCH, Sampson, J, Liang, L, Park, J-H, Chung, CC, Weisenburger, DD, Chatterjee, N, Fraumeni, JF, Slager, SL, Wu, X, de Sanjose, S, Smedby, KE, Salles, G, Skibola, CF, Rothman, N, and Chanock, SJ
Abstract: Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of 3 new genome-wide association studies (GWAS) and 1 previous scan, totaling 3,857 cases and 7,666 controls of European ancestry, with additional genotyping of 9 promising SNPs in 1,359 cases and 4,557 controls. In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; P = 2.33 × 10(-21)), rs2523607 at 6p21.33 (HLA-B; P = 2.40 × 10(-10)), rs79480871 at 2p23.3 (NCOA1; P = 4.23 × 10(-8)) and two independent SNPs, rs13255292 and rs4733601, at 8q24.21 (PVT1; P = 9.98 × 10(-13) and 3.63 × 10(-11), respectively). These data provide substantial new evidence for genetic susceptibility to this B cell malignancy and point to pathways involved in immune recognition and immune function in the pathogenesis of DLBCL.
Published: 2014

31. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author: Berndt, SI, Skibola, CF, Joseph, V, Camp, NJ, Nieters, A, Wang, Z, Cozen, W, Monnereau, A, Wang, SS, Kelly, RS, Lan, Q, Teras, LR, Chatterjee, N, Chung, CC, Yeager, M, Brooks-Wilson, AR, Hartge, P, Purdue, MP, Birmann, BM, Armstrong, BK, Cocco, P, Zhang, Y, Severi, G, Zeleniuch-Jacquotte, A, Lawrence, C, Burdette, L, Yuenger, J, Hutchinson, A, Jacobs, KB, Call, TG, Shanafelt, TD, Novak, AJ, Kay, NE, Liebow, M, Wang, AH, Smedby, KE, Adami, H-O, Melbye, M, Glimelius, B, Chang, ET, Glenn, M, Curtin, K, Cannon-Albright, LA, Jones, B, Diver, WR, Link, BK, Weiner, GJ, Conde, L, Bracci, PM, Riby, J, Holly, EA, Smith, MT, Jackson, RD, Tinker, LF, Benavente, Y, Becker, N, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, McKay, J, Staines, A, Rabe, KG, Achenbach, SJ, Vachon, CM, Goldin, LR, Strom, SS, Lanasa, MC, Spector, LG, Leis, JF, Cunningham, JM, Weinberg, JB, Morrison, VA, Caporaso, NE, Norman, AD, Linet, MS, De Roos, AJ, Morton, LM, Severson, RK, Riboli, E, Vineis, P, Kaaks, R, Trichopoulos, D, Masala, G, Weiderpass, E, Chirlaque, M-D, Vermeulen, RCH, Travis, RC, Giles, GG, Albanes, D, Virtamo, J, Weinstein, S, Clavel, J, Zheng, T, Holford, TR, Offit, K, Zelenetz, A, Klein, RJ, Spinelli, JJ, Bertrand, KA, Laden, F, Giovannucci, E, Kraft, P, Kricker, A, Turner, J, Vajdic, CM, Ennas, MG, Ferri, GM, Miligi, L, Liang, L, Sampson, J, Crouch, S, Park, J-H, North, KE, Cox, A, Snowden, JA, Wright, J, Carracedo, A, Lopez-Otin, C, Bea, S, Salaverria, I, Martin-Garcia, D, Campo, E, Fraumeni, JF, de Sanjose, S, Hjalgrim, H, Cerhan, JR, Chanock, SJ, Rothman, N, Slager, SL, Berndt, SI, Skibola, CF, Joseph, V, Camp, NJ, Nieters, A, Wang, Z, Cozen, W, Monnereau, A, Wang, SS, Kelly, RS, Lan, Q, Teras, LR, Chatterjee, N, Chung, CC, Yeager, M, Brooks-Wilson, AR, Hartge, P, Purdue, MP, Birmann, BM, Armstrong, BK, Cocco, P, Zhang, Y, Severi, G, Zeleniuch-Jacquotte, A, Lawrence, C, Burdette, L, Yuenger, J, Hutchinson, A, Jacobs, KB, Call, TG, Shanafelt, TD, Novak, AJ, Kay, NE, Liebow, M, Wang, AH, Smedby, KE, Adami, H-O, Melbye, M, Glimelius, B, Chang, ET, Glenn, M, Curtin, K, Cannon-Albright, LA, Jones, B, Diver, WR, Link, BK, Weiner, GJ, Conde, L, Bracci, PM, Riby, J, Holly, EA, Smith, MT, Jackson, RD, Tinker, LF, Benavente, Y, Becker, N, Boffetta, P, Brennan, P, Foretova, L, Maynadie, M, McKay, J, Staines, A, Rabe, KG, Achenbach, SJ, Vachon, CM, Goldin, LR, Strom, SS, Lanasa, MC, Spector, LG, Leis, JF, Cunningham, JM, Weinberg, JB, Morrison, VA, Caporaso, NE, Norman, AD, Linet, MS, De Roos, AJ, Morton, LM, Severson, RK, Riboli, E, Vineis, P, Kaaks, R, Trichopoulos, D, Masala, G, Weiderpass, E, Chirlaque, M-D, Vermeulen, RCH, Travis, RC, Giles, GG, Albanes, D, Virtamo, J, Weinstein, S, Clavel, J, Zheng, T, Holford, TR, Offit, K, Zelenetz, A, Klein, RJ, Spinelli, JJ, Bertrand, KA, Laden, F, Giovannucci, E, Kraft, P, Kricker, A, Turner, J, Vajdic, CM, Ennas, MG, Ferri, GM, Miligi, L, Liang, L, Sampson, J, Crouch, S, Park, J-H, North, KE, Cox, A, Snowden, JA, Wright, J, Carracedo, A, Lopez-Otin, C, Bea, S, Salaverria, I, Martin-Garcia, D, Campo, E, Fraumeni, JF, de Sanjose, S, Hjalgrim, H, Cerhan, JR, Chanock, SJ, Rothman, N, and Slager, SL
Abstract: Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P=1.22×10(-14)), 18q21.33 (BCL2, P=7.76×10(-11)), 11p15.5 (C11orf21, P=2.15×10(-10)), 4q25 (LEF1, P=4.24×10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P=2.50×10(-9)), 9p21.3 (CDKN2B-AS1, P=1.27×10(-8)), 18q21.32 (PMAIP1, P=2.51×10(-8)), 15q15.1 (BMF, P=2.71×10(-10)) and 2p22.2 (QPCT, P=1.68×10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P=2.08×10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P=5.40×10(-8)) and 5p15.33 (TERT, P=1.92×10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.
Published: 2013

32. Adiposity and physical activity as predictors of mortality.

Author: Calle EE, Teras LR, Thun MJ, Lauderdale DS, Hu FB, Willett WC, and Manson JE
Published: 2005

33. Obesity and mortality.

Author: Calle EE, Teras LR, and Thun MJ
Published: 2005

34. Pathogenic variants in cancer susceptibility genes predispose to Ductal Carcinoma In situ of the breast.

Author: Huang H, Couch RE, Karam R, Hu C, Boddicker N, Polley EC, Na J, Ambrosone CB, Yao S, Trentham-Dietz A, Eliassen AH, Penney K, Brantley K, Bodelon C, Teras LR, Hodge J, Patel A, Haiman CA, John EM, Neuhausen SL, Martinez E, Lacey JV, O'Brien KM, Sandler DP, Weinberg CR, Palmer JR, Bertrand KA, Vachon CM, Olson JE, Ruddy KE, Anton-Culver H, Ziogas A, Goldgar DE, Nathanson KL, Domchek SM, Weitzel JN, Kraft P, Dolinsky JS, Pesaran T, Richardson ME, Yadav S, and Couch FJ
Abstract: Purpose: To determine the relationship between germline pathogenic variants (PVs) in cancer predisposition genes and the risk of ductal carcinoma in situ (DCIS)., Methods: Germline PV frequencies in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, PALB2, RAD51C, and RAD51D) were compared between DCIS cases and unaffected controls, and between DCIS and infiltrating ductal carcinoma (IDC) cases from a clinical-testing cohort (n=9,887), a population-based cohort (n=3,876) and the UK Biobank (n=2421). The risk of contralateral breast cancer for DCIS cases with PVs was estimated in the population-based cohort., Results: Germline PVs were observed in 6.5% and 4.6% of women with DCIS in the clinical-testing and population-based cohorts, respectively. BRCA1, BRCA2, and PALB2 PVs frequencies were significantly lower among women with DCIS than IDC (clinical cohort: 2.8% vs. 5.7%; population-based cohort: 1.7% vs. 3.7%), whereas the PV frequencies for ATM and CHEK2 were similar. ATM, BRCA1, BRCA2, CHEK2, and PALB2 PVs were significantly associated with an increased risk of DCIS (OR>2.0), but only BRCA2 PVs were associated with high-risk (OR>4) in both cohorts. The cumulative incidence of contralateral breast cancer among carriers of PVs in high penetrance genes with DCIS was 23% over 15 years., Conclusions: The enrichment of PVs in ATM, BRCA1, BRCA2, CHEK2 and PALB2 among women with DCIS suggests that multigene panel testing may be appropriate for women with DCIS. Elevated risks of contralateral breast cancer in carriers of PVs in high penetrance genes with DCIS confirmed the utility of testing for surgical decision-making.
Published: 2024
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35. Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk.

Author: Kalia SS, Boddicker NJ, Yadav S, Huang H, Na J, Hu C, Ambrosone CB, Yao S, Haiman CA, Chen F, John EM, Kurian AW, Guo B, Lindstrӧm S, Auer P, Lacey JV Jr, Neuhausen SL, Martinez ME, Sandler DP, O'Brien KM, Taylor JA, Teras LR, Hodge JM, Lori A, Bodelon C, Trentham-Dietz A, Burnside ES, Vachon CM, Winham SJ, Goldgar DE, Domchek SM, Nathanson KL, Weitzel JN, Couch FJ, and Kraft P
Subjects: Humans, Female, Middle Aged, Case-Control Studies, Risk Factors, Risk Assessment methods, Multifactorial Inheritance, Adult, Aged, Prospective Studies, Polymorphism, Single Nucleotide, Breast Neoplasms genetics, Breast Neoplasms epidemiology, Genetic Predisposition to Disease
Abstract: Background: Breast cancer has been associated with monogenic, polygenic, and epidemiologic (clinical, reproductive, and lifestyle) risk factors, but studies evaluating the combined effects of these factors have been limited., Methods: We extended previous work in breast cancer risk modeling, incorporating pathogenic variants (PV) in six breast cancer predisposition genes and a 105-SNP polygenic risk score (PRS), to include an epidemiologic risk score (ERS) in a sample of non-Hispanic White women drawn from prospective cohorts and population-based case-control studies, with 23,518 cases and 22,832 controls, from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium., Results: The model predicts 4.4-fold higher risk of breast cancer for postmenopausal women with no predisposition PV and median PRS, but with the highest versus lowest ERS. Overall, women with CHEK2 PVs had >20% lifetime risk of breast cancer. However, 15.6% of women with CHEK2 PVs and a family history of breast cancer, and 45.1% of women with CHEK2 PVs but without a family history of breast cancer, had low (<20%) predicted lifetime risk and thus were below the threshold for MRI screening. CHEK2 PV carriers at the 10th percentile of the joint distribution of ERS and PRS, without a family history of breast cancer, had a predicted lifetime risk similar to the general population., Conclusions: These results illustrate that an ERS, alone and combined with the PRS, can contribute to clinically relevant risk stratification., Impact: Integrating monogenic, polygenic, and epidemiologic risk factors in breast cancer risk prediction models may inform personalized screening and prevention efforts., (©2024 American Association for Cancer Research.)
Published: 2024
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36. A case-cohort study of per- and polyfluoroalkyl substance concentrations and incident prostate cancer in the cancer prevention Study-II LifeLink cohort study.

Author: Troeschel AN, Teras LR, Hodge JM, Rodriguez J, Wang Y, Daniel J, Diver WR, and Winquist A
Subjects: Humans, Male, Middle Aged, Aged, Cohort Studies, Incidence, Environmental Pollutants blood, Environmental Exposure, United States epidemiology, Case-Control Studies, Adult, Alkanesulfonic Acids blood, Prostatic Neoplasms epidemiology, Prostatic Neoplasms blood, Prostatic Neoplasms chemically induced, Fluorocarbons blood
Abstract: Introduction: Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent, potentially carcinogenic chemicals. Previous studies investigating PFAS exposure and prostate cancer yielded mixed findings. We aimed to investigate associations between PFAS exposure and incident prostate cancer in a large cohort of U.S. men, overall and by selected demographic, lifestyle, and medical-related characteristics., Methods: We conducted a case-cohort study among Cancer Prevention Study-II LifeLink Cohort participants who, at baseline (1998-2001), had serum specimens collected and no prior cancer diagnosis. The study included all men diagnosed with prostate cancer (n = 1610) during follow-up (baseline-June 30, 2015) and a random sub-cohort of 500 men. PFAS concentrations [perfluorohexane sulfonic acid (PFHxS), perfluorooctane sulfonate (PFOS), perfluorononanoic acid (PFNA), and perfluorooctanoic acid (PFOA)] were measured in stored serum specimens. We used multivariable Cox proportional hazards models to estimate associations between PFAS concentrations and prostate cancer, overall and by selected characteristics (grade, stage, family history, age, education, smoking status, and alcohol consumption)., Results: Prostate cancer hazards were slightly higher among men with concentrations in the highest (Q4) vs lowest quartile (Q1) for PFHxS [hazard ratio (HR) (95% CI): 1.18 (0.88-1.59)] and PFOS [HR (95% CI): 1.18 (0.89-1.58)], but not for PFNA or PFOA. However, we observed heterogeneous associations by age, family history of prostate cancer (PFHxS), alcohol consumption (PFHxS), and education (PFNA). For example, no meaningful associations were observed among men aged <70 years at serum collection, but among men aged ≥70 years, HRs (95% CIs) comparing Q4 to Q1 were PFHxS 1.54 (1.02-2.31) and PFOS 1.62 (1.08-2.44). No meaningful heterogeneity in associations were observed by tumor grade or stage., Conclusions: Our findings do not clearly support an association between the PFAS considered and prostate cancer. However, positive associations observed in some subgroups, and consistently positive associations observed for PFHxS warrant further investigation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)
Published: 2024
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37. Association of Gene Variant Type and Location with Breast Cancer Risk in the General Population.

Author: Akamandisa MP, Boddicker NJ, Yadav S, Hu C, Hart SN, Ambrosone C, Anton-Culver H, Auer PL, Bodelon C, Burnside ES, Chen F, Eliassen HA, Goldgar DE, Haiman C, Hodge JM, Huang H, John EM, Karam R, Lacey JV, Lindstroem S, Martinez E, Na J, Neuhausen SL, O'Brien KM, Olson JE, Pal T, Palmer JR, Patel AV, Pesaran T, Polley EC, Richardson ME, Ruddy K, Sandler DP, Teras LR, Trentham-Dietz A, Vachon CM, Weinberg C, Winham SJ, Yao S, Zirpoli G, Kraft P, Weitzel JN, Domchek SM, Couch FJ, and Nathanson KL
Abstract: Importance: Pathogenic variants (PVs) in ATM, BRCA1, BRCA2, CHEK2 , and PALB2 are associated with increased breast cancer risk. However, it is unknown whether breast cancer risk differs by PV type or location in carriers ascertained from the general population., Objective: To evaluate breast cancer risks associated with PV type and location in ATM, BRCA1, BRCA2, CHEK2 , and PALB2 ., Design: Age adjusted case-control association analysis for all participants, subsets of PV carriers, and women with no breast cancer family history in population-based and clinical testing cohorts., Setting: Twelve US population-based studies within the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium, and breast cancer cases from the UK-Biobank and an Ambry Genetics clinical testing cohort., Participants: 32,247 women with and 32,544 age-matched women without a breast cancer diagnosis from CARRIERS; 237 and 1351 women with BRCA2 PVs and breast cancer from the UKBB and Ambry Genetics, respectively., Exposures: PVs in ATM, BRCA1, BRCA2, CHEK2, and PALB2., Main Outcomes and Measures: PVs were grouped by type and location within genes and assessed for risks of breast cancer (odds ratios (OR), 95% confidence intervals (CI), and p-values) using logistic regression. Mean ages at diagnosis were compared using linear regression., Results: Compared to women carrying BRCA2 exon 11 protein truncating variants (PTVs) in the CARRIERS population-based study, women with BRCA2 ex13-27 PTVs (OR=2.7, 95%CI 1.1-7.9) and ex1-10 PTVs (OR=1.6, 95%CI 0.8-3.5) had higher breast cancer risks, lower rates of ER-negative breast cancer (ex13-27 OR=0.5, 95%CI 0.2-0.9; ex1-10 OR=0.5, 95%CI 0.1-1.0), and earlier age of breast cancer diagnosis (ex13-27 5.5 years, p<0.001; ex1-10 2.4 years, p=0.17). These associations with ER-negative breast cancer and age replicated in a high-risk clinical cohort and the population-based UK Biobank cohort. No differences in risk or age at diagnosis by gene region were observed for PTVs in other predisposition genes., Conclusions and Relevance: Population-based and clinical high-risk cohorts establish that PTVs in exon 11 of BRCA2 are associated with reduced risk of breast cancer, later age at diagnosis, and greater risk of ER-negative disease. These differential risks may improve individualized risk prediction and clinical management for women carrying BRCA2 PTVs., Key Points: Question: Does ATM , BRCA1 , BRCA2 , CHEK2 and PALB2 pathogenic variant type and location influence breast cancer risk in population-based studies? Findings: Breast cancer risk and estrogen receptor status differ based on the type and location of pathogenic variants in BRCA2 . Women carrying protein truncating variants in exon 11 have a lower breast cancer risk in the population-based cohorts, older age at diagnosis and higher rates of estrogen receptor negative breast cancer than women with exon 1-10 or exon 13-27 truncation variants in population-based and clinical testing cohorts. Meaning: Incorporating pathogenic variant type and location in cancer risk models may improve individualized risk prediction.
Published: 2024
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38. Genetically inferred birthweight, height, and puberty timing and risk of osteosarcoma.

Author: Gianferante DM, Moore A, Spector LG, Wheeler W, Yang T, Hubbard A, Gorlick R, Patiño-Garcia A, Lecanda F, Flanagan AM, Amary F, Andrulis IL, Wunder JS, Thomas DM, Ballinger ML, Serra M, Hattinger C, Demerath E, Johnson W, Birmann BM, De Vivo I, Giles G, Teras LR, Arslan A, Vermeulen R, Sample J, Freedman ND, Huang WY, Chanock SJ, Savage SA, Berndt SI, and Mirabello L
Subjects: Humans, Female, Male, Case-Control Studies, Adolescent, Puberty genetics, Bone Neoplasms genetics, Bone Neoplasms epidemiology, Bone Neoplasms pathology, Genetic Predisposition to Disease, Risk Factors, Child, Adult, Polymorphism, Single Nucleotide, Young Adult, Osteosarcoma genetics, Osteosarcoma pathology, Osteosarcoma epidemiology, Body Height genetics, Birth Weight genetics, Genome-Wide Association Study
Abstract: Introduction: Several studies have linked increased risk of osteosarcoma with tall stature, high birthweight, and early puberty, although evidence is inconsistent. We used genetic risk scores (GRS) based on established genetic loci for these traits and evaluated associations between genetically inferred birthweight, height, and puberty timing with osteosarcoma., Methods: Using genotype data from two genome-wide association studies, totaling 1039 cases and 2923 controls of European ancestry, association analyses were conducted using logistic regression for each study and meta-analyzed to estimate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses were conducted by case diagnosis age, metastasis status, tumor location, tumor histology, and presence of a known pathogenic variant in a cancer susceptibility gene., Results: Genetically inferred higher birthweight was associated with an increased risk of osteosarcoma (OR =1.59, 95% CI 1.07-2.38, P = 0.02). This association was strongest in cases without metastatic disease (OR =2.46, 95% CI 1.44-4.19, P = 9.5 ×10 -04 ). Although there was no overall association between osteosarcoma and genetically inferred taller stature (OR=1.06, 95% CI 0.96-1.17, P = 0.28), the GRS for taller stature was associated with an increased risk of osteosarcoma in 154 cases with a known pathogenic cancer susceptibility gene variant (OR=1.29, 95% CI 1.03-1.63, P = 0.03). There were no significant associations between the GRS for puberty timing and osteosarcoma., Conclusion: A genetic propensity to higher birthweight was associated with increased osteosarcoma risk, suggesting that shared genetic factors or biological pathways that affect birthweight may contribute to osteosarcoma pathogenesis., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2023. Published by Elsevier Ltd.)
Published: 2024
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39. Alcohol intake and endogenous sex hormones in women: Meta-analysis of cohort studies and Mendelian randomization.

Author: Tin Tin S, Smith-Byrne K, Ferrari P, Rinaldi S, McCullough ML, Teras LR, Manjer J, Giles G, Le Marchand L, Haiman CA, Wilkens LR, Chen Y, Hankinson S, Tworoger S, Eliassen AH, Willett WC, Ziegler RG, Fuhrman BJ, Sieri S, Agnoli C, Cauley J, Menon U, Fourkala EO, Rohan TE, Kaaks R, Reeves GK, and Key TJ
Subjects: Adult, Female, Humans, Middle Aged, Alcohol Dehydrogenase genetics, Breast Neoplasms blood, Breast Neoplasms genetics, Breast Neoplasms metabolism, Cohort Studies, Cross-Sectional Studies, Estradiol blood, Estradiol metabolism, Postmenopause blood, Progesterone blood, Progesterone metabolism, Testosterone blood, Testosterone metabolism, Alcohol Drinking adverse effects, Alcohol Drinking blood, Alcohol Drinking metabolism, Gonadal Steroid Hormones blood, Gonadal Steroid Hormones metabolism, Mendelian Randomization Analysis, Premenopause blood, Sex Hormone-Binding Globulin metabolism, Sex Hormone-Binding Globulin analysis
Abstract: Background: The mechanisms underlying alcohol-induced breast carcinogenesis are not fully understood but may involve hormonal changes., Methods: Cross-sectional associations were investigated between self-reported alcohol intake and serum or plasma concentrations of estradiol, estrone, progesterone (in premenopausal women only), testosterone, androstenedione, dehydroepiandrosterone sulfate, and sex hormone binding globulin (SHBG) in 45 431 premenopausal and 173 476 postmenopausal women. Multivariable linear regression was performed separately for UK Biobank, European Prospective Investigation into Cancer and Nutrition, and Endogenous Hormones and Breast Cancer Collaborative Group, and meta-analyzed the results. For testosterone and SHBG, we also conducted Mendelian randomization and colocalization using the ADH1B (alcohol dehydrogenase 1B) variant (rs1229984)., Results: Alcohol intake was positively, though weakly, associated with all hormones (except progesterone in premenopausal women), with increments in concentrations per 10 g/day increment in alcohol intake ranging from 1.7% for luteal estradiol to 6.6% for postmenopausal dehydroepiandrosterone sulfate. There was an inverse association of alcohol with SHBG in postmenopausal women but a small positive association in premenopausal women. Two-sample randomization identified positive associations of alcohol intake with total testosterone (difference per 10 g/day increment: 4.1%; 95% CI, 0.6-7.6) and free testosterone (7.8%; 4.1-11.5), and an inverse association with SHBG (-8.1%; -11.3% to -4.9%). Colocalization suggested a shared causal locus at ADH1B between alcohol intake and higher free testosterone and lower SHBG (posterior probability for H4, 0.81 and 0.97, respectively)., Conclusions: Alcohol intake was associated with small increases in sex hormone concentrations, including bioavailable fractions, which may contribute to its effect on breast cancer risk., (© 2024 The Author(s). Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)
Published: 2024
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40. Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification.

Author: Zanti M, O'Mahony DG, Parsons MT, Dorling L, Dennis J, Boddicker NJ, Chen W, Hu C, Naven M, Yiangou K, Ahearn TU, Ambrosone CB, Andrulis IL, Antoniou AC, Auer PL, Baynes C, Bodelon C, Bogdanova NV, Bojesen SE, Bolla MK, Brantley KD, Camp NJ, Campbell A, Castelao JE, Cessna MH, Chang-Claude J, Chen F, Chenevix-Trench G, Conroy DM, Czene K, De Nicolo A, Domchek SM, Dörk T, Dunning AM, Eliassen AH, Evans DG, Fasching PA, Figueroa JD, Flyger H, Gago-Dominguez M, García-Closas M, Glendon G, González-Neira A, Grassmann F, Hadjisavvas A, Haiman CA, Hamann U, Hart SN, Hartman MBA, Ho WK, Hodge JM, Hoppe R, Howell SJ, Jakubowska A, Khusnutdinova EK, Ko YD, Kraft P, Kristensen VN, Lacey JV, Li J, Lim GH, Lindström S, Lophatananon A, Luccarini C, Mannermaa A, Martinez ME, Mavroudis D, Milne RL, Muir K, Nathanson KL, Nuñez-Torres R, Obi N, Olson JE, Palmer JR, Panayiotidis MI, Patel AV, Pharoah PDP, Polley EC, Rashid MU, Ruddy KJ, Saloustros E, Sawyer EJ, Schmidt MK, Southey MC, Tan VK, Teo SH, Teras LR, Torres D, Trentham-Dietz A, Truong T, Vachon CM, Wang Q, Weitzel JN, Yadav S, Yao S, Zirpoli GR, Cline MS, Devilee P, Tavtigian SV, Goldgar DE, Couch FJ, Easton DF, Spurdle AB, and Michailidou K
Abstract: Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS, and previous findings indicate that case-control likelihood ratios (LRs) outperform odds ratios for variant classification. As an initiative of the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Analytical Working Group we analyzed germline sequencing data of BRCA1 and BRCA2 from 96,691 female breast cancer cases and 303,925 unaffected controls from three studies: the BRIDGES study of the Breast Cancer Association Consortium, the Cancer Risk Estimates Related to Susceptibility consortium, and the UK Biobank. We observed 11,227 BRCA1 and BRCA2 variants, with 6,921 being coding, covering 23.4% of BRCA1 and BRCA2 VUS in ClinVar and 19.2% of ClinVar curated (likely) benign or pathogenic variants. Case-control LR evidence was highly consistent with ClinVar assertions for (likely) benign or pathogenic variants; exhibiting 99.1% sensitivity and 95.4% specificity for BRCA1 and 92.2% sensitivity and 86.6% specificity for BRCA2 . This approach provides case-control evidence for 785 unclassified variants, that can serve as a valuable element for clinical classification.
Published: 2024
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41. Excess Body Weight and the Risk of Second Primary Cancers Among Cancer Survivors.

Author: Bodelon C, Sung H, Mitchell EL, Deubler EL, Newton CC, Jemal A, Teras LR, and Patel AV
Subjects: Humans, Male, Female, Middle Aged, Aged, Prospective Studies, Risk Factors, Obesity epidemiology, Obesity complications, United States epidemiology, Adult, Cohort Studies, Neoplasms, Second Primary epidemiology, Neoplasms, Second Primary etiology, Cancer Survivors statistics & numerical data, Body Mass Index, Overweight epidemiology, Overweight complications
Abstract: Importance: Little is known about the causes of second primary cancers among individuals with a history of cancer. Descriptive studies have suggested that lifestyle factors, including excess body weight, may be important., Objective: To investigate whether excess body weight is associated with the risk of a second primary malignant neoplasm among cancer survivors., Design, Setting, and Participants: This cohort study of adults in 21 states in the US used data from the Cancer Prevention Study II Nutrition cohort, a large prospective study that invited participants to respond to a survey in 1992 and biennial surveys starting in 1997, and who were followed-up through 2017. Eligible participants included those who received a diagnosis of a first primary nonmetastatic invasive cancer between 1992 and 2015. Data analysis occurred from September 2023 to March 2024., Exposure: Body mass index (BMI), computed from self-reported height and weight at the time of the first primary cancer diagnosis (mean [SD] years to diagnosis, 1.7 [1.5] years)., Main Outcome and Measures: Main outcomes included a second primary cancer or an obesity-related second cancer. Cancer diagnoses were reported on biennial surveys and verified through medical record abstraction or linkage with state cancer registries., Results: This cohort included 26 894 participants who received a diagnosis of a first nonmetastatic primary cancer (mean [SD] age at first cancer diagnosis, 72.2 [6.5] years; 15 920 male [59.2%]). At the time of first diagnosis, 11 497 participants (42.8%) had overweight and 4684 (17.2%) had obesity. During a median (IQR) follow-up time of 7.9 (3.4-13.6) years, 3749 (13.9%) participants received a diagnosis of a second primary cancer, of which 1243 (33.2%) were obesity-related second primary cancers. Compared with cancer survivors whose BMI was in the normal range (18.5 to <25), there was 15% increased risk of any second primary cancer for those who had overweight (25 to <30; adjusted hazard ratio [aHR], 1.15; 95% CI, 1.07-1.25) and a 34% increased risk for those who had obesity (BMI ≥30; aHR, 1.34; 95% CI, 1.21-1.48), with greater risk for obesity-related second primary cancers, including a 40% increased risk for those with overweight (aHR, 1.40; 95% CI, 1.22,-1.61) and a 78% increased risk for those with obesity (aHR, 1.78; 95% CI, 1.51-2.11)., Conclusions and Relevance: In this cohort study of older survivors of nonmetastatic cancer, those who had overweight or obesity at the time of their first cancer diagnosis were at higher risk of developing a second cancer, especially an obesity-related second cancer. Given the high prevalence of overweight and obesity among cancer survivors, it is important to promote survivorship care guidelines recommending weight management and increase awareness of second cancers among physicians and cancer survivors.
Published: 2024
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42. Length of Overnight Fasting and 6-year Weight Change in the Cancer Prevention Study-3.

Author: McCullough ML, Masters M, Hartman TJ, Flanders WD, Playdon MC, Elahy V, Hodge RA, Teras LR, Wang Y, and Patel AV
Subjects: Humans, Female, Male, Middle Aged, Prospective Studies, Neoplasms prevention & control, Body Weight, Adult, Weight Gain, Time Factors, Cohort Studies, Aged, Fasting
Abstract: Background: Longer overnight fasting (ONF) is a potential strategy for weight control. Although promising, the evidence from large population-based studies is limited., Objectives: To examine the association of self-reported ONF duration with 3- and 6-y weight change in the American Cancer Society's Cancer Prevention Study-3 prospective cohort., Methods: United States adult Cancer Prevention Study-3 participants completed a 24-h validated meal and snack timing and frequency grid (weekday and weekend) in 2015, from which weighted ONF hours were calculated. Participants reported body weight in 2015, 2018, and 2021. Three- and 6-y weight change (kg, and % body weight) were assessed., Results: Among 104,420 mostly female (78.5%) participants aged 52.7 ± 9.5 (standard deviation) y followed for 6 y, a 1-h increase in ONF length was associated with a small but statistically significant reduction in weight gain over 3- and 6-y periods [multivariable-adjusted mean difference in % body weight = -0.02, 95% confidence interval (CI): -0.05, -0.00, P = 0.03 and -0.04, 95% CI: -0.07, -0.01, P < 0.01, respectively]. The mean difference of 6-y % reduction in weight gain was slightly greater among individuals with overweight (-0.05, 95% CI: -0.10, 0.00, P = 0.05) and obesity (-0.06, 95% CI: -0.12, 0.01, P = 0.08) compared with those with healthy body mass index (-0.03, 95% CI:-0.07, 0.01, P = 0.13) or underweight (0.16, 95% CI: -0.04, 0.36, P = 0.13, P interaction < 0.0001). Stronger associations were observed among those ≤55 y than 56+ (P < 0.001), and those with higher waist circumference (Pinteraction < 0.0001) but not by sex or earlier/later fasting period., Conclusions: Longer ONF was associated with slightly lower body weight in adult males and females over 6 y that was stronger among those with overweight or obesity, higher waist circumference, and those aged ≤55 y. The magnitude of weight change, although in the hypothesized direction, suggests that prolonged ONF may have modest impact on weight control over time., (Copyright © 2024 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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43. Publisher Correction: Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Author: Kentistou KA, Kaisinger LR, Stankovic S, Vaudel M, Mendes de Oliveira E, Messina A, Walters RG, Liu X, Busch AS, Helgason H, Thompson DJ, Santoni F, Petricek KM, Zouaghi Y, Huang-Doran I, Gudbjartsson DF, Bratland E, Lin K, Gardner EJ, Zhao Y, Jia RY, Terao C, Riggan MJ, Bolla MK, Yazdanpanah M, Yazdanpanah N, Bradfield JP, Broer L, Campbell A, Chasman DI, Cousminer DL, Franceschini N, Franke LH, Girotto G, He C, Järvelin MR, Joshi PK, Kamatani Y, Karlsson R, Luan J, Lunetta KL, Mägi R, Mangino M, Medland SE, Meisinger C, Noordam R, Nutile T, Concas MP, Polašek O, Porcu E, Ring SM, Sala C, Smith AV, Tanaka T, van der Most PJ, Vitart V, Wang CA, Willemsen G, Zygmunt M, Ahearn TU, Andrulis IL, Anton-Culver H, Antoniou AC, Auer PL, Barnes CLK, Beckmann MW, Berrington de Gonzalez A, Bogdanova NV, Bojesen SE, Brenner H, Buring JE, Canzian F, Chang-Claude J, Couch FJ, Cox A, Crisponi L, Czene K, Daly MB, Demerath EW, Dennis J, Devilee P, De Vivo I, Dörk T, Dunning AM, Dwek M, Eriksson JG, Fasching PA, Fernandez-Rhodes L, Ferreli L, Fletcher O, Gago-Dominguez M, García-Closas M, García-Sáenz JA, González-Neira A, Grallert H, Guénel P, Haiman CA, Hall P, Hamann U, Hakonarson H, Hart RJ, Hickey M, Hooning MJ, Hoppe R, Hopper JL, Hottenga JJ, Hu FB, Huebner H, Hunter DJ, Jernström H, John EM, Karasik D, Khusnutdinova EK, Kristensen VN, Lacey JV, Lambrechts D, Launer LJ, Lind PA, Lindblom A, Magnusson PKE, Mannermaa A, McCarthy MI, Meitinger T, Menni C, Michailidou K, Millwood IY, Milne RL, Montgomery GW, Nevanlinna H, Nolte IM, Nyholt DR, Obi N, O'Brien KM, Offit K, Oldehinkel AJ, Ostrowski SR, Palotie A, Pedersen OB, Peters A, Pianigiani G, Plaseska-Karanfilska D, Pouta A, Pozarickij A, Radice P, Rennert G, Rosendaal FR, Ruggiero D, Saloustros E, Sandler DP, Schipf S, Schmidt CO, Schmidt MK, Small K, Spedicati B, Stampfer M, Stone J, Tamimi RM, Teras LR, Tikkanen E, Turman C, Vachon CM, Wang Q, Winqvist R, Wolk A, Zemel BS, Zheng W, van Dijk KW, Alizadeh BZ, Bandinelli S, Boerwinkle E, Boomsma DI, Ciullo M, Chenevix-Trench G, Cucca F, Esko T, Gieger C, Grant SFA, Gudnason V, Hayward C, Kolčić I, Kraft P, Lawlor DA, Martin NG, Nøhr EA, Pedersen NL, Pennell CE, Ridker PM, Robino A, Snieder H, Sovio U, Spector TD, Stöckl D, Sudlow C, Timpson NJ, Toniolo D, Uitterlinden A, Ulivi S, Völzke H, Wareham NJ, Widen E, Wilson JF, Pharoah PDP, Li L, Easton DF, Njølstad PR, Sulem P, Murabito JM, Murray A, Manousaki D, Juul A, Erikstrup C, Stefansson K, Horikoshi M, Chen Z, Farooqi IS, Pitteloud N, Johansson S, Day FR, Perry JRB, and Ong KK
Published: 2024
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44. Outdoor air pollution and risk of incident adult haematologic cancer subtypes in a large US prospective cohort.

Author: Diver WR, Teras LR, Deubler EL, and Turner MC
Subjects: Humans, Male, Middle Aged, United States epidemiology, Female, Prospective Studies, Aged, Adult, Incidence, Environmental Exposure adverse effects, Nitrogen Dioxide adverse effects, Nitrogen Dioxide analysis, Risk Factors, Air Pollution adverse effects, Air Pollution analysis, Hematologic Neoplasms epidemiology, Hematologic Neoplasms etiology, Hematologic Neoplasms chemically induced, Particulate Matter adverse effects, Particulate Matter analysis, Air Pollutants adverse effects, Air Pollutants analysis
Abstract: Background: Outdoor air pollution and particulate matter (PM) are classified as Group 1 human carcinogens for lung cancer. Pollutant associations with haematologic cancers are suggestive, but these cancers are aetiologically heterogeneous and sub-type examinations are lacking., Methods: The American Cancer Society Cancer Prevention Study-II Nutrition Cohort was used to examine associations of outdoor air pollutants with adult haematologic cancers. Census block group level annual predictions of particulate matter (PM 2.5 , PM 10 , PM 10-2.5 ), nitrogen dioxide (NO 2 ), ozone (O 3 ), sulfur dioxide (SO 2 ), and carbon monoxide (CO) were assigned with residential addresses. Hazard ratios (HR) and 95% confidence intervals (CI) between time-varying pollutants and haematologic subtypes were estimated., Results: Among 108,002 participants, 2659 incident haematologic cancers were identified from 1992-2017. Higher PM 10-2.5 concentrations were associated with mantle cell lymphoma (HR per 4.1 μg/m 3 = 1.43, 95% CI 1.08-1.90). NO 2 was associated with Hodgkin lymphoma (HR per 7.2 ppb = 1.39; 95% CI 1.01-1.92) and marginal zone lymphoma (HR per 7.2 ppb = 1.30; 95% CI 1.01-1.67). CO was associated with marginal zone (HR per 0.21 ppm = 1.30; 95% CI 1.04-1.62) and T-cell (HR per 0.21 ppm = 1.27; 95% CI 1.00-1.61) lymphomas., Conclusions: The role of air pollutants on haematologic cancers may have been underestimated previously because of sub-type heterogeneity., (© 2024. The Author(s).)
Published: 2024
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45. Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Author: Kentistou KA, Kaisinger LR, Stankovic S, Vaudel M, Mendes de Oliveira E, Messina A, Walters RG, Liu X, Busch AS, Helgason H, Thompson DJ, Santoni F, Petricek KM, Zouaghi Y, Huang-Doran I, Gudbjartsson DF, Bratland E, Lin K, Gardner EJ, Zhao Y, Jia RY, Terao C, Riggan MJ, Bolla MK, Yazdanpanah M, Yazdanpanah N, Bradfield JP, Broer L, Campbell A, Chasman DI, Cousminer DL, Franceschini N, Franke LH, Girotto G, He C, Järvelin MR, Joshi PK, Kamatani Y, Karlsson R, Luan J, Lunetta KL, Mägi R, Mangino M, Medland SE, Meisinger C, Noordam R, Nutile T, Concas MP, Polašek O, Porcu E, Ring SM, Sala C, Smith AV, Tanaka T, van der Most PJ, Vitart V, Wang CA, Willemsen G, Zygmunt M, Ahearn TU, Andrulis IL, Anton-Culver H, Antoniou AC, Auer PL, Barnes CLK, Beckmann MW, Berrington de Gonzalez A, Bogdanova NV, Bojesen SE, Brenner H, Buring JE, Canzian F, Chang-Claude J, Couch FJ, Cox A, Crisponi L, Czene K, Daly MB, Demerath EW, Dennis J, Devilee P, De Vivo I, Dörk T, Dunning AM, Dwek M, Eriksson JG, Fasching PA, Fernandez-Rhodes L, Ferreli L, Fletcher O, Gago-Dominguez M, García-Closas M, García-Sáenz JA, González-Neira A, Grallert H, Guénel P, Haiman CA, Hall P, Hamann U, Hakonarson H, Hart RJ, Hickey M, Hooning MJ, Hoppe R, Hopper JL, Hottenga JJ, Hu FB, Huebner H, Hunter DJ, Jernström H, John EM, Karasik D, Khusnutdinova EK, Kristensen VN, Lacey JV, Lambrechts D, Launer LJ, Lind PA, Lindblom A, Magnusson PKE, Mannermaa A, McCarthy MI, Meitinger T, Menni C, Michailidou K, Millwood IY, Milne RL, Montgomery GW, Nevanlinna H, Nolte IM, Nyholt DR, Obi N, O'Brien KM, Offit K, Oldehinkel AJ, Ostrowski SR, Palotie A, Pedersen OB, Peters A, Pianigiani G, Plaseska-Karanfilska D, Pouta A, Pozarickij A, Radice P, Rennert G, Rosendaal FR, Ruggiero D, Saloustros E, Sandler DP, Schipf S, Schmidt CO, Schmidt MK, Small K, Spedicati B, Stampfer M, Stone J, Tamimi RM, Teras LR, Tikkanen E, Turman C, Vachon CM, Wang Q, Winqvist R, Wolk A, Zemel BS, Zheng W, van Dijk KW, Alizadeh BZ, Bandinelli S, Boerwinkle E, Boomsma DI, Ciullo M, Chenevix-Trench G, Cucca F, Esko T, Gieger C, Grant SFA, Gudnason V, Hayward C, Kolčić I, Kraft P, Lawlor DA, Martin NG, Nøhr EA, Pedersen NL, Pennell CE, Ridker PM, Robino A, Snieder H, Sovio U, Spector TD, Stöckl D, Sudlow C, Timpson NJ, Toniolo D, Uitterlinden A, Ulivi S, Völzke H, Wareham NJ, Widen E, Wilson JF, Pharoah PDP, Li L, Easton DF, Njølstad PR, Sulem P, Murabito JM, Murray A, Manousaki D, Juul A, Erikstrup C, Stefansson K, Horikoshi M, Chen Z, Farooqi IS, Pitteloud N, Johansson S, Day FR, Perry JRB, and Ong KK
Subjects: Humans, Female, Animals, Multifactorial Inheritance genetics, Mice, Genome-Wide Association Study, Adolescent, Puberty, Precocious genetics, Polymorphism, Single Nucleotide, Receptors, G-Protein-Coupled genetics, Puberty, Delayed genetics, Child, Menarche genetics, Puberty genetics, Gene Frequency
Abstract: Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease., (© 2024. The Author(s).)
Published: 2024
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46. Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction.

Author: Yiangou K, Mavaddat N, Dennis J, Zanti M, Wang Q, Bolla MK, Abubakar M, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Augustinsson A, Baten A, Behrens S, Bermisheva M, de Gonzalez AB, Białkowska K, Boddicker N, Bodelon C, Bogdanova NV, Bojesen SE, Brantley KD, Brauch H, Brenner H, Camp NJ, Canzian F, Castelao JE, Cessna MH, Chang-Claude J, Chenevix-Trench G, Chung WK, Colonna SV, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dunning AM, Eccles DM, Eliassen AH, Engel C, Eriksson M, Evans DG, Fasching PA, Fletcher O, Flyger H, Fritschi L, Gago-Dominguez M, Gentry-Maharaj A, González-Neira A, Guénel P, Hahnen E, Haiman CA, Hamann U, Hartikainen JM, Ho V, Hodge J, Hollestelle A, Honisch E, Hooning MJ, Hoppe R, Hopper JL, Howell S, Howell A, Jakovchevska S, Jakubowska A, Jernström H, Johnson N, Kaaks R, Khusnutdinova EK, Kitahara CM, Koutros S, Kristensen VN, Lacey JV, Lambrechts D, Lejbkowicz F, Lindblom A, Lush M, Mannermaa A, Mavroudis D, Menon U, Murphy RA, Nevanlinna H, Obi N, Offit K, Park-Simon TW, Patel AV, Peng C, Peterlongo P, Pita G, Plaseska-Karanfilska D, Pylkäs K, Radice P, Rashid MU, Rennert G, Roberts E, Rodriguez J, Romero A, Rosenberg EH, Saloustros E, Sandler DP, Sawyer EJ, Schmutzler RK, Scott CG, Shu XO, Southey MC, Stone J, Taylor JA, Teras LR, van de Beek I, Willett W, Winqvist R, Zheng W, Vachon CM, Schmidt MK, Hall P, MacInnis RJ, Milne RL, Pharoah PDP, Simard J, Antoniou AC, Easton DF, and Michailidou K
Abstract: The 313-variant polygenic risk score (PRS 313 ) provides a promising tool for breast cancer risk prediction. However, evaluation of the PRS 313 across different European populations which could influence risk estimation has not been performed. Here, we explored the distribution of PRS 313 across European populations using genotype data from 94,072 females without breast cancer, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 225,105 female participants from the UK Biobank. The mean PRS 313 differed markedly across European countries, being highest in south-eastern Europe and lowest in north-western Europe. Using the overall European PRS 313 distribution to categorise individuals leads to overestimation and underestimation of risk in some individuals from south-eastern and north-western countries, respectively. Adjustment for principal components explained most of the observed heterogeneity in mean PRS. Country-specific PRS distributions may be used to calibrate risk categories in individuals from different countries.
Published: 2024
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47. A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer.

Author: Amgad M, Hodge JM, Elsebaie MAT, Bodelon C, Puvanesarajah S, Gutman DA, Siziopikou KP, Goldstein JA, Gaudet MM, Teras LR, and Cooper LAD
Subjects: Female, Humans, Clinical Trials as Topic, Tumor Microenvironment genetics, Image Processing, Computer-Assisted, Deep Learning, Breast Neoplasms diagnostic imaging, Breast Neoplasms pathology
Abstract: Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists grade the microscopic appearance of breast tissue using the Nottingham criteria, which are qualitative and do not account for noncancerous elements within the tumor microenvironment. Here we present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast tumor microenvironment morphology. HiPS uses deep learning to accurately map cellular and tissue structures to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study-II and validated using data from three independent cohorts, including the Prostate, Lung, Colorectal, and Ovarian Cancer trial, Cancer Prevention Study-3, and The Cancer Genome Atlas. HiPS consistently outperformed pathologists in predicting survival outcomes, independent of tumor-node-metastasis stage and pertinent variables. This was largely driven by stromal and immune features. In conclusion, HiPS is a robustly validated biomarker to support pathologists and improve patient prognosis., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2024
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48. Long-term multimorbidity trajectories in older adults: The role of cancer, demographics, and health behaviors.

Author: Rees-Punia E, Masters M, Teras LR, Leach CR, Williams GR, Newton CC, Diver WR, Patel AV, and Parsons HM
Subjects: Humans, Female, Aged, United States epidemiology, Male, Medicare, Health Behavior, Obesity epidemiology, Demography, Multimorbidity, Neoplasms epidemiology
Abstract: Background: Multimorbidity is associated with premature mortality and excess health care costs. The burden of multimorbidity is highest among patients with cancer, yet trends and determinants of multimorbidity over time are poorly understood., Methods: Via Medicare claims linked to Cancer Prevention Study II data, group-based trajectory modeling was used to compare National Cancer Institute comorbidity index score trends for cancer survivors and older adults without a cancer history. Among cancer survivors, multinomial logistic regression analyses evaluated associations between demographics, health behaviors, and comorbidity trajectories., Results: In 82,754 participants (mean age, 71.6 years [SD, 5.1 years]; 56.9% female), cancer survivors (n = 11,265) were more likely than older adults without a cancer history to experience the riskiest comorbidity trajectories: (1) steady, high comorbidity scores (remain high; odds ratio [OR], 1.36; 95% CI, 1.29-1.45), and (2) high scores that increased over time (start high and increase; OR, 1.51; 95% CI, 1.38-1.65). Cancer survivors who were physically active postdiagnosis were less likely to fall into these two trajectories (OR, 0.73; 95% CI, 0.64-0.84, remain high; OR, 0.42; 95% CI, 0.33-0.53, start high and increase) compared to inactive survivors. Cancer survivors with obesity were more likely to have a trajectory that started high and increased (OR, 2.83; 95% CI, 2.32-3.45 vs. normal weight), although being physically active offset some obesity-related risk. Cancer survivors who smoked postdiagnosis were also six times more likely to have trajectories that started high and increased (OR, 6.86; 95% CI, 4.41-10.66 vs. never smokers)., Conclusions: Older cancer survivors are more likely to have multiple comorbidities accumulated at a faster pace than older adults without a history of cancer. Weight management, physical activity, and smoking avoidance postdiagnosis may attenuate that trend., (© 2023 American Cancer Society.)
Published: 2024
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49. Case-Cohort Study of the Association between PFAS and Selected Cancers among Participants in the American Cancer Society's Cancer Prevention Study II LifeLink Cohort.

Author: Winquist A, Hodge JM, Diver WR, Rodriguez JL, Troeschel AN, Daniel J, and Teras LR
Subjects: Male, Humans, Female, Cohort Studies, American Cancer Society, Carcinoma, Renal Cell, Leukemia, Lymphocytic, Chronic, B-Cell, Environmental Pollutants, Alkanesulfonic Acids, Fluorocarbons, Kidney Neoplasms chemically induced, Kidney Neoplasms epidemiology
Abstract: Background: Previous epidemiological studies found associations between exposure to per- and polyfluoroalkyl substances (PFAS) and some cancer types. Many studies considered highly exposed populations, so relevance to less-exposed populations can be uncertain. Additionally, many studies considered only cancer site, not histology., Objectives: We conducted a case-cohort study within the American Cancer Society's prospective Cancer Prevention Study II (CPS-II) LifeLink cohort to examine associations between PFAS exposure and risk of selected cancers, considering histologic subtypes., Methods: Serum specimens were collected from cohort participants during the period 1998-2001. This study included a subcohort (500 men, 499 women) randomly selected from participants without prior cancer diagnoses at serum collection, and all participants with incident (after serum collection) first cancers of the breast (females only, n = 786 ), bladder ( n = 401 ), kidney ( n = 158 ), pancreas ( n = 172 ), prostate (males only, n = 1,610 ) or hematologic system ( n = 635 ). PFAS concentrations [perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)] were measured in stored serum. We assessed associations between PFAS concentrations and incident cancers, by site and histologic subtype, using multivariable Cox proportional hazards models stratified by sex and controlling for age and year at blood draw, education, race/ethnicity, smoking, and alcohol use., Results: Serum PFOA concentrations were positively associated with renal cell carcinoma of the kidney among women [hazard ratio (HR) and 95% confidence interval (CI) per PFOA doubling: 1.54 (95% CI: 1.05, 2.26)] but not men. Among men, we observed a positive association between PFHxS concentrations and chronic lymphocytic leukemia/small lymphocytic lymphoma [CLL/SLL, HR and 95% CI per PFHxS doubling: 1.34 (95% CI: 1.02, 1.75)]. We observed some heterogeneity of associations by histologic subtype within sites., Discussion: This study supports the previously observed association between PFOA and renal cell carcinoma among women and suggests an association between PFHxS and CLL/SLL among men. Consideration of histologic subtypes might be important in future studies of PFAS-cancer associations. https://doi.org/10.1289/EHP13174.
Published: 2023
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50. Germline Mutations in 12 Genes and Risk of Ovarian Cancer in Three Population-Based Cohorts.

Author: Kotsopoulos J, Hathaway CA, Narod SA, Teras LR, Patel AV, Hu C, Yadav S, Couch FJ, and Tworoger SS
Subjects: Humans, Female, Germ-Line Mutation, Prospective Studies, BRCA1 Protein genetics, BRCA2 Protein genetics, Carcinoma, Ovarian Epithelial genetics, Genetic Testing, Genetic Predisposition to Disease, Ovarian Neoplasms epidemiology, Ovarian Neoplasms genetics, Ovarian Neoplasms pathology, Breast Neoplasms genetics
Abstract: Background: With the widespread use of multigene panel genetic testing, population-based studies are necessary to accurately assess penetrance in unselected individuals. We evaluated the prevalence of germline pathogenic or likely pathogenic variants (mutations) in 12 cancer-predisposition genes and associations with ovarian cancer risk in three population-based prospective studies [Nurses' Health Study (NHS), NHSII, Cancer Prevention Study II]., Methods: We included women with epithelial ovarian or peritoneal cancer (n = 776) and controls who were alive and had at least one intact ovary at the time of the matched case diagnosis (n = 1,509). Germline DNA was sequenced for mutations in 12 genes. Conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for ovarian cancer risk by mutation status., Results: The mutation frequency across all 12 genes was 11.2% in cases and 3.3% in controls (P < 0.0001). BRCA1 and BRCA2 were the most frequently mutated (3.5% and 3.8% of cases and 0.3% and 0.5% of controls, respectively) and were associated with increased ovarian cancer risk [OR, BRCA1 = 12.38; 95% confidence interval (CI) = 4.72-32.45; OR, BRCA2 = 9.18; 95% CI = 3.98-21.15]. Mutation frequencies for the other genes were ≤1.0% and only PALB2 was significantly associated with risk (OR = 5.79; 95% CI = 1.09-30.83). There was no difference in survival for women with a BRCA germline mutation versus no mutation., Conclusions: Further research is needed to better understand the role of other mutations in ovarian cancer among unselected populations., Impact: Our data support guidelines for germline genetic testing for BRCA1 and BRCA2 among women diagnosed with epithelial ovarian cancer; testing for PALB2 may be warranted., (©2023 American Association for Cancer Research.)
Published: 2023
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