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2. Targeted sequencing to identify novel genetic risk factors for deep vein thrombosis: a study of 734 genes

Author

de Haan, H.G., van Hylckama Vlieg, A., Lotta, L.A., Gorski, M.M., Bucciarelli, P., Martinelli, I., Baglin, T.P., Peyvandi, F., Rosendaal, F.R., Amouyel, P., de Andrade, M., Basu, S., Berr, C., Brody, J.A., Chasman, D. I, Dartigues, J.‐F., Folsom, A.R., Germain, M., Heit, J., Houwing‐Duitermaat, J., Kabrhel, C., Kraft, P., Le Gal, G., Lindström, S., Monajemi, R., Morange, P.‐E., Psaty, B.M., Reitsma, P.H., Ridker, P.M., Rose, L.M., Saut, N., Slagboom, E., Smadja, D., Smith, N.L., Suchon, P., Tang, W., Taylor, K.D., Trégouët, D.‐A., Tzourio, C., de Visser, M.C.H., Weng, L.‐C., and Wiggins, K.L.

Published
2018
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4. 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

8. 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

17. Deep targeted sequencing of 12 breast cancer susceptibility regions in 4611 women across four different ethnicities

Author

Lindstroem, S, Ablorh, A, Chapman, B, Gusev, A, Chen, G, Turman, C, Eliassen, AH, Price, AL, Henderson, BE, Le Marchand, L, Hofmann, O, Haiman, CA, Kraft, P, Lindstroem, S, Ablorh, A, Chapman, B, Gusev, A, Chen, G, Turman, C, Eliassen, AH, Price, AL, Henderson, BE, Le Marchand, L, Hofmann, O, Haiman, CA, and Kraft, P

Abstract

BACKGROUND: Although genome-wide association studies (GWASs) have identified thousands of disease susceptibility regions, the underlying causal mechanism in these regions is not fully known. It is likely that the GWAS signal originates from one or many as yet unidentified causal variants. METHODS: Using next-generation sequencing, we characterized 12 breast cancer susceptibility regions identified by GWASs in 2288 breast cancer cases and 2323 controls across four populations of African American, European, Japanese, and Hispanic ancestry. RESULTS: After genotype calling and quality control, we identified 137,530 single-nucleotide variants (SNVs); of those, 87.2 % had a minor allele frequency (MAF) <0.005. For SNVs with MAF >0.005, we calculated the smallest number of SNVs needed to obtain a posterior probability set (PPS) such that there is 90 % probability that the causal SNV is included. We found that the PPS for two regions, 2q35 and 11q13, contained less than 5 % of the original SNVs, dramatically decreasing the number of potentially causal SNVs. However, we did not find strong evidence supporting a causal role for any individual SNV. In addition, there were no significant gene-based rare SNV associations after correcting for multiple testing. CONCLUSIONS: This study illustrates some of the challenges faced in fine-mapping studies in the post-GWAS era, most importantly the large sample sizes needed to identify rare-variant associations or to distinguish the effects of strongly correlated common SNVs.

Published
2016

18. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair

Author

Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, L, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, N, Corre, T, Hottenga, J-J, Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, A-L, Boutin, TS, Brauch, H, Brenner, H, Bruening, T, Burwinkel, B, Campbell, A, Campbell, H, Chanock, SJ, Chapman, JR, Chen, Y-DI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, De Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Doerk, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, X, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, A, Homuth, G, Hooning, MJ, Hopper, JL, Hu, FB, Huang, J, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, V-M, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, J, Li, X, Lindstroem, S, Liu, Y, Luan, J, Lubinski, J, Maegi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Mueller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, F, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK, Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, CM, Simard, J, Sorice, R, Southey, MC, Stoeckl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q, Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, van Duijn, CM, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, AG, Ulivi, S, Voelzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, JA, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, Murray, A, Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, L, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, N, Corre, T, Hottenga, J-J, Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, A-L, Boutin, TS, Brauch, H, Brenner, H, Bruening, T, Burwinkel, B, Campbell, A, Campbell, H, Chanock, SJ, Chapman, JR, Chen, Y-DI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, De Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Doerk, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, X, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, A, Homuth, G, Hooning, MJ, Hopper, JL, Hu, FB, Huang, J, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, V-M, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, J, Li, X, Lindstroem, S, Liu, Y, Luan, J, Lubinski, J, Maegi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Mueller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, F, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK, Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, CM, Simard, J, Sorice, R, Southey, MC, Stoeckl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q, Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, van Duijn, CM, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, AG, Ulivi, S, Voelzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, JA, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, and Murray, A

Abstract

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

Published
2015

19. Genetic determinants of telomere length and risk of common cancers: a Mendelian randomization study

Author

Zhang, C, Doherty, JA, Burgess, S, Hung, RJ, Lindstroem, S, Kraft, P, Gong, J, Amos, CI, Sellers, TA, Monteiro, ANA, Chenevix-Trench, G, Bickeboeller, H, Risch, A, Brennan, P, Mckay, JD, Houlston, RS, Landi, MT, Timofeeva, MN, Wang, Y, Heinrich, J, Kote-Jarai, Z, Eeles, RA, Muir, K, Wiklund, F, Gronberg, H, Berndt, SI, Chanock, SJ, Schumacher, F, Haiman, CA, Henderson, BE, Al Olama, AA, Andrulis, IL, Hopper, JL, Chang-Claude, J, John, EM, Malone, KE, Gammon, MD, Ursin, G, Whittemore, AS, Hunter, DJ, Gruber, SB, Knight, JA, Hou, L, Le Marchand, L, Newcomb, PA, Hudson, TJ, Chan, AT, Li, L, Woods, MO, Ahsan, H, Pierce, BL, Zhang, C, Doherty, JA, Burgess, S, Hung, RJ, Lindstroem, S, Kraft, P, Gong, J, Amos, CI, Sellers, TA, Monteiro, ANA, Chenevix-Trench, G, Bickeboeller, H, Risch, A, Brennan, P, Mckay, JD, Houlston, RS, Landi, MT, Timofeeva, MN, Wang, Y, Heinrich, J, Kote-Jarai, Z, Eeles, RA, Muir, K, Wiklund, F, Gronberg, H, Berndt, SI, Chanock, SJ, Schumacher, F, Haiman, CA, Henderson, BE, Al Olama, AA, Andrulis, IL, Hopper, JL, Chang-Claude, J, John, EM, Malone, KE, Gammon, MD, Ursin, G, Whittemore, AS, Hunter, DJ, Gruber, SB, Knight, JA, Hou, L, Le Marchand, L, Newcomb, PA, Hudson, TJ, Chan, AT, Li, L, Woods, MO, Ahsan, H, and Pierce, BL

Abstract

Epidemiological studies have reported inconsistent associations between telomere length (TL) and risk for various cancers. These inconsistencies are likely attributable, in part, to biases that arise due to post-diagnostic and post-treatment TL measurement. To avoid such biases, we used a Mendelian randomization approach and estimated associations between nine TL-associated SNPs and risk for five common cancer types (breast, lung, colorectal, ovarian and prostate cancer, including subtypes) using data on 51 725 cases and 62 035 controls. We then used an inverse-variance weighted average of the SNP-specific associations to estimate the association between a genetic score representing long TL and cancer risk. The long TL genetic score was significantly associated with increased risk of lung adenocarcinoma (P = 6.3 × 10(-15)), even after exclusion of a SNP residing in a known lung cancer susceptibility region (TERT-CLPTM1L) P = 6.6 × 10(-6)). Under Mendelian randomization assumptions, the association estimate [odds ratio (OR) = 2.78] is interpreted as the OR for lung adenocarcinoma corresponding to a 1000 bp increase in TL. The weighted TL SNP score was not associated with other cancer types or subtypes. Our finding that genetic determinants of long TL increase lung adenocarcinoma risk avoids issues with reverse causality and residual confounding that arise in observational studies of TL and disease risk. Under Mendelian randomization assumptions, our finding suggests that longer TL increases lung adenocarcinoma risk. However, caution regarding this causal interpretation is warranted in light of the potential issue of pleiotropy, and a more general interpretation is that SNPs influencing telomere biology are also implicated in lung adenocarcinoma risk.

Published
2015

21. A Genome-Wide 'Pleiotropy Scan' Does Not Identify New Susceptibility Loci for Estrogen Receptor Negative Breast Cancer

Author

Peterlongo, P, Campa, D, Barrdahl, M, Tsilidis, KK, Severi, G, Diver, WR, Siddiq, A, Chanock, S, Hoover, RN, Ziegler, RG, Berg, CD, Buys, SS, Haiman, CA, Henderson, BE, Schumacher, FR, Le Marchand, L, Flesch-Janys, D, Lindstroem, S, Hunter, DJ, Hankinson, SE, Willett, WC, Kraft, P, Cox, DG, Khaw, K-T, Tjonneland, A, Dossus, L, Trichopoulos, D, Panico, S, van Gils, CH, Weiderpass, E, Barricarte, A, Sund, M, Gaudet, MM, Giles, G, Southey, M, Baglietto, L, Chang-Claude, J, Kaaks, R, Canzian, F, Peterlongo, P, Campa, D, Barrdahl, M, Tsilidis, KK, Severi, G, Diver, WR, Siddiq, A, Chanock, S, Hoover, RN, Ziegler, RG, Berg, CD, Buys, SS, Haiman, CA, Henderson, BE, Schumacher, FR, Le Marchand, L, Flesch-Janys, D, Lindstroem, S, Hunter, DJ, Hankinson, SE, Willett, WC, Kraft, P, Cox, DG, Khaw, K-T, Tjonneland, A, Dossus, L, Trichopoulos, D, Panico, S, van Gils, CH, Weiderpass, E, Barricarte, A, Sund, M, Gaudet, MM, Giles, G, Southey, M, Baglietto, L, Chang-Claude, J, Kaaks, R, and Canzian, F

Abstract

Approximately 15-30% of all breast cancer tumors are estrogen receptor negative (ER-). Compared with ER-positive (ER+) disease they have an earlier age at onset and worse prognosis. Despite the vast number of risk variants identified for numerous cancer types, only seven loci have been unambiguously identified for ER-negative breast cancer. With the aim of identifying new susceptibility SNPs for this disease we performed a pleiotropic genome-wide association study (GWAS). We selected 3079 SNPs associated with a human complex trait or disease at genome-wide significance level (P<5 × 10(-8)) to perform a secondary analysis of an ER-negative GWAS from the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), including 1998 cases and 2305 controls from prospective studies. We then tested the top ten associations (i.e. with the lowest P-values) using three additional populations with a total sample size of 3509 ER+ cases, 2543 ER- cases and 7031 healthy controls. None of the 3079 selected variants in the BPC3 ER-GWAS were significant at the adjusted threshold. 186 variants were associated with ER- breast cancer risk at a conventional threshold of P<0.05, with P-values ranging from 0.049 to 2.3 × 10(-4). None of the variants reached statistical significance in the replication phase. In conclusion, this study did not identify any novel susceptibility loci for ER-breast cancer using a "pleiotropic approach".

Published
2014

22. Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk

Author

Lindstroem, S, Thompson, DJ, Paterson, AD, Li, J, Gierach, GL, Scott, C, Stone, J, Douglas, JA, dos-Santos-Silva, I, Fernandez-Navarro, P, Verghase, J, Smith, P, Brown, J, Luben, R, Wareham, NJ, Loos, RJF, Heit, JA, Pankratz, VS, Norman, A, Goode, EL, Cunningham, JM, Deandrade, M, Vierkant, RA, Czene, K, Fasching, PA, Baglietto, L, Southey, MC, Giles, GG, Shah, KP, Chan, H-P, Helvie, MA, Beck, AH, Knoblauch, NW, Hazra, A, Hunter, DJ, Kraft, P, Pollan, M, Figueroa, JD, Couch, FJ, Hopper, JL, Hall, P, Easton, DF, Boyd, NF, Vachon, CM, Tamimi, RM, Lindstroem, S, Thompson, DJ, Paterson, AD, Li, J, Gierach, GL, Scott, C, Stone, J, Douglas, JA, dos-Santos-Silva, I, Fernandez-Navarro, P, Verghase, J, Smith, P, Brown, J, Luben, R, Wareham, NJ, Loos, RJF, Heit, JA, Pankratz, VS, Norman, A, Goode, EL, Cunningham, JM, Deandrade, M, Vierkant, RA, Czene, K, Fasching, PA, Baglietto, L, Southey, MC, Giles, GG, Shah, KP, Chan, H-P, Helvie, MA, Beck, AH, Knoblauch, NW, Hazra, A, Hunter, DJ, Kraft, P, Pollan, M, Figueroa, JD, Couch, FJ, Hopper, JL, Hall, P, Easton, DF, Boyd, NF, Vachon, CM, and Tamimi, RM

Abstract

Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5 × 10(-8)) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B and SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23 and TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease-susceptibility loci.

Published
2014

23. Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: a genome-wide interaction study

Author

Rudolph, A, Hein, R, Lindstroem, S, Beckmann, L, Behrens, S, Liu, J, Aschard, H, Bolla, MK, Wang, J, Truong, T, Cordina-Duverger, E, Menegaux, F, Bruening, T, Harth, V, Severi, G, Baglietto, L, Southey, M, Chanock, SJ, Lissowska, J, Figueroa, JD, Eriksson, M, Humpreys, K, Darabi, H, Olson, JE, Stevens, KN, Vachon, CM, Knight, JA, Glendon, G, Mulligan, AM, Ashworth, A, Orr, N, Schoemaker, M, Webb, PM, Guenel, P, Brauch, H, Giles, G, Garcia-Closas, M, Czene, K, Chenevix-Trench, G, Couch, FJ, Andrulis, IL, Swerdlow, A, Hunter, DJ, Flesch-Janys, D, Easton, DF, Hall, P, Nevanlinna, H, Kraft, P, Chang-Claude, J, Rudolph, A, Hein, R, Lindstroem, S, Beckmann, L, Behrens, S, Liu, J, Aschard, H, Bolla, MK, Wang, J, Truong, T, Cordina-Duverger, E, Menegaux, F, Bruening, T, Harth, V, Severi, G, Baglietto, L, Southey, M, Chanock, SJ, Lissowska, J, Figueroa, JD, Eriksson, M, Humpreys, K, Darabi, H, Olson, JE, Stevens, KN, Vachon, CM, Knight, JA, Glendon, G, Mulligan, AM, Ashworth, A, Orr, N, Schoemaker, M, Webb, PM, Guenel, P, Brauch, H, Giles, G, Garcia-Closas, M, Czene, K, Chenevix-Trench, G, Couch, FJ, Andrulis, IL, Swerdlow, A, Hunter, DJ, Flesch-Janys, D, Easton, DF, Hall, P, Nevanlinna, H, Kraft, P, and Chang-Claude, J

Abstract

Women using menopausal hormone therapy (MHT) are at increased risk of developing breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in 11 case-control studies. We used a case-only design to assess interactions between single-nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2920 cases (541 lobular) from four genome-wide association studies. The top 1391 SNPs showing P values for interaction (Pint) <3.0 × 10(-3) were selected for replication using pooled case-control data from 11 studies of the Breast Cancer Association Consortium, including 7689 cases (676 lobular) and 9266 controls. Fixed-effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9 × 10(-6)), two SNPs in SLC25A21 (combined Pint≤4.8 × 10(-5)), and three SNPs in PLCG2 (combined Pint≤4.5 × 10(-5)). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7 × 10(-5)), one SNP in CD80 (combined Pint≤8.2 × 10(-6)), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10(-6)), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6 × 10(-5)). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling, and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.

Published
2013

24. Common Breast Cancer Susceptibility Variants in LSP1 and RAD51L1 Are Associated with Mammographic Density Measures that Predict Breast Cancer Risk

Author

Vachon, CM, Scott, CG, Fasching, PA, Hall, P, Tamimi, RM, Li, J, Stone, J, Apicella, C, Odefrey, F, Gierach, GL, Jud, SM, Heusinger, K, Beckmann, MW, Pollan, M, Fernandez-Navarro, P, Gonzalez-Neira, A, Benitez, J, van Gils, CH, Lokate, M, Onland-Moret, NC, Peeters, PHM, Brown, J, Leyland, J, Varghese, JS, Easton, DF, Thompson, DJ, Luben, RN, Warren, RML, Wareham, NJ, Loos, RJF, Khaw, K-T, Ursin, G, Lee, E, Gayther, SA, Ramus, SJ, Eeles, RA, Leach, MO, Kwan-Lim, G, Couch, FJ, Giles, GG, Baglietto, L, Krishnan, K, Southey, MC, Le Marchand, L, Kolonel, LN, Woolcott, C, Maskarinec, G, Haiman, CA, Walker, K, Johnson, N, McCormack, VA, Biong, M, Alnaes, GIG, Gram, IT, Kristensen, VN, Borresen-Dale, A-L, Lindstroem, S, Hankinson, SE, Hunter, DJ, Andrulis, IL, Knight, JA, Boyd, NF, Figuero, JD, Lissowska, J, Wesolowska, E, Peplonska, B, Bukowska, A, Reszka, E, Liu, J, Eriksson, L, Czene, K, Audley, T, Wu, AH, Pankratz, VS, Hopper, JL, dos-Santos-Silva, I, Vachon, CM, Scott, CG, Fasching, PA, Hall, P, Tamimi, RM, Li, J, Stone, J, Apicella, C, Odefrey, F, Gierach, GL, Jud, SM, Heusinger, K, Beckmann, MW, Pollan, M, Fernandez-Navarro, P, Gonzalez-Neira, A, Benitez, J, van Gils, CH, Lokate, M, Onland-Moret, NC, Peeters, PHM, Brown, J, Leyland, J, Varghese, JS, Easton, DF, Thompson, DJ, Luben, RN, Warren, RML, Wareham, NJ, Loos, RJF, Khaw, K-T, Ursin, G, Lee, E, Gayther, SA, Ramus, SJ, Eeles, RA, Leach, MO, Kwan-Lim, G, Couch, FJ, Giles, GG, Baglietto, L, Krishnan, K, Southey, MC, Le Marchand, L, Kolonel, LN, Woolcott, C, Maskarinec, G, Haiman, CA, Walker, K, Johnson, N, McCormack, VA, Biong, M, Alnaes, GIG, Gram, IT, Kristensen, VN, Borresen-Dale, A-L, Lindstroem, S, Hankinson, SE, Hunter, DJ, Andrulis, IL, Knight, JA, Boyd, NF, Figuero, JD, Lissowska, J, Wesolowska, E, Peplonska, B, Bukowska, A, Reszka, E, Liu, J, Eriksson, L, Czene, K, Audley, T, Wu, AH, Pankratz, VS, Hopper, JL, and dos-Santos-Silva, I

Abstract

BACKGROUND: Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures. METHODS: We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status. RESULTS: Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07). CONCLUSION: We identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland. IMPACT: We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.

Published
2012

25. Common variants in ZNF365 are associated with both mammographic density and breast cancer risk

Author

Lindstroem, S, Vachon, CM, Li, J, Varghese, J, Thompson, D, Warren, R, Brown, J, Leyland, J, Audley, T, Wareham, NJ, Loos, RJF, Paterson, AD, Rommens, J, Waggott, D, Martin, LJ, Scott, CG, Pankratz, VS, Hankinson, SE, Hazra, A, Hunter, DJ, Hopper, JL, Southey, MC, Chanock, SJ, Silva, IDS, Liu, J, Eriksson, L, Couch, FJ, Stone, J, Apicella, C, Czene, K, Kraft, P, Hall, P, Easton, DF, Boyd, NF, Tamimi, RM, Lindstroem, S, Vachon, CM, Li, J, Varghese, J, Thompson, D, Warren, R, Brown, J, Leyland, J, Audley, T, Wareham, NJ, Loos, RJF, Paterson, AD, Rommens, J, Waggott, D, Martin, LJ, Scott, CG, Pankratz, VS, Hankinson, SE, Hazra, A, Hunter, DJ, Hopper, JL, Southey, MC, Chanock, SJ, Silva, IDS, Liu, J, Eriksson, L, Couch, FJ, Stone, J, Apicella, C, Czene, K, Kraft, P, Hall, P, Easton, DF, Boyd, NF, and Tamimi, RM

Abstract

High-percent mammographic density adjusted for age and body mass index is one of the strongest risk factors for breast cancer. We conducted a meta analysis of five genome-wide association studies of percent mammographic density and report an association with rs10995190 in ZNF365 (combined P = 9.6 × 10(-10)). Common variants in ZNF365 have also recently been associated with susceptibility to breast cancer.

Published
2011

40. A Large Study of Androgen Receptor Germline Variants and Their Relation to Sex Hormone Levels and Prostate Cancer Risk. Results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium

Author

Peter Kraft, Loic Le Marchand, H. Bas Bueno-de-Mesquita, Pär Stattin, Stephen J. Chanock, Daniel O. Stram, Stephanie J. Weinstein, Alison M. Dunning, Jarmo Virtamo, Heather Spencer Feigelson, Richard B. Hayes, Rosario Tumino, Matthew L. Freedman, Kim Overvad, David Altshuler, Demetrius Albanes, Jing Ma, Meredith Yeager, Heiner Boeing, Carmen Martinez, Meir J. Stampfer, Rudolf Kaaks, David J. Hunter, Brian E. Henderson, Elio Riboli, Michael J. Thun, Afshan Siddiq, Edward Giovannucci, Christopher A. Haiman, Laurence N. Kolonel, Naomi E. Allen, Sara Lindström, J. Michael Gaziano, Sonja I. Berndt, Dimitrios Trichopoulos, [Lindstroem,S, Hunter,DJ, Kraft,P] Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. [Lindstroem,S, Stampfer,M, Trichopoulos,D, Kraft,P] Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. [Giovannucci,E, Stampfer,M] Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA. [Kraft,P] Department of Biostatisctics, Harvard School of Public Health, Boston, Massachusetts, USA. [Ma,J, Stampfer,M] Department of Medicine, Channing Laboratory, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA. [Altshuler,D] Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, Department of Genetics, Harvard Medical School, Boston, Massachusetts, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts. [Riboli,E, Siddiq,A] Department of Epidemiology and Public Health, Faculty of Medicine, Imperial College, London, United Kingdom. [Albanes,D, Berndt,SI, Chanock,SJ, Hayes,RB, Weinstein,SJ] Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland. [Allen,NE] Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom. [Boeing,H] German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany. [Bueno-de-Mesquita,HB] National Institute for Public Health and the Environment, Bilthoven, The Netherlands. [Dunning,AM] Department of Oncology, University of Cambridge, Cambridge, United Kingdom. [Feigelson,HS, Thun,MJ] Department of Epidemiology, American Cancer Society, Atlanta, Georgia. [Feigelson, HS] Kaiser Permanente, Denver, Colorado. [Gaziano,JM] Massachusetts Veterans Epidemiology and Research Information Center and Geriatric Research, Education, Clinical Center, Boston Veterans Affairs Healthcare System, Boston, Massachusetts, Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts. [Haiman,CA, Henderson,BE, Stram, DO] Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California. [Hayes,RB] Division of Epidemiology, New York University Langone Medical Center, New York, New York. [Kaaks,R] Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany. [Kolonel,LN, Le Marchand,L]Cancer Research Center, University of Hawaii, Honolulu, Hawaii. [Martinez,C] Andalusian School of Public Health. Centro de Investigación Biomédica en Red Epidemiología y Salud Pública, Granada, Spain. [Overvad,K] Clinical Epidemiology and Cardiology, Aalborg Hospital, Aarhus University Hospital, Aalborg, Denmark. [Stattin,P] Surgical and Perioperative Sciences, Urology and Andrology, Umeå University, Umeå, Sweden. [Tumino,R] Cancer Registry Azienda Ospedaliera 'Civile M.P.Arezzo', Ragusa, Italy. [Virtamo,J] Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland. [Yeager,M] Core Genotyping Facility, Advanced Technology Program, SAIC Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland. [Freedman,ML] Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts. The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, and This work was supported by National Cancer Institute cooperative agreements UO1-CA98233, UO1-CA98710, UO1-CA98216, and UO1-CA98758, and by the Intramural Research Program of National Institutes of Health/National Cancer Institute, Division of Cancer Epidemiology and Genetics. S.L. is supported by the Swedish Research Council (Vetenskapsrådet).

Subjects
Male, Oncology, Neoplasias de la próstata, Endocrinology, Diabetes and Metabolism, Clinical Biochemistry, urologic and male genital diseases, Biochemistry, Germline, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Genetic Techniques::Genetic Association Studies [Medical Subject Headings], Cohort Studies, Androgen deprivation therapy, Prostate cancer, Endocrinology, Sex hormone-binding globulin, Trinucleotide Repeats, Receptores androgénicos, Gonadal Steroid Hormones, Prostate cancer risk, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Case-Control Studies [Medical Subject Headings], General Medicine, Middle Aged, Receptors, Androgen, Cohort, Original Article, Female, Health Care::Health Care Economics and Organizations::Organizations::Government::Federal Government::United States Government Agencies::United States Dept. of Health and Human Services::National Institutes of Health (U.S.)::National Cancer Institute (U.S.) [Medical Subject Headings], Risk, medicine.medical_specialty, Estudios de cohortes, Breast Neoplasms, Biology, Diseases::Neoplasms::Neoplasms by Site::Urogenital Neoplasms::Genital Neoplasms, Male::Prostatic Neoplasms [Medical Subject Headings], Germline mutation, Translational Highlights from Jcem, Health Care::Environment and Public Health::Public Health::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Cohort Studies [Medical Subject Headings], Internal medicine, Carcinoma, medicine, Humans, Genetic Predisposition to Disease, Molecular Biology, Diseases::Neoplasms::Neoplasms by Site::Breast Neoplasms [Medical Subject Headings], Genetic Association Studies, Germ-Line Mutation, Aged, Hormonas esteroides gonadales, Estudios de asociación genética, Biochemistry (medical), Case-control study, Prostatic Neoplasms, Cancer, medicine.disease, National Cancer Institute (U.S.), United States, Androgen receptor, Chemicals and Drugs::Hormones, Hormone Substitutes, and Hormone Antagonists::Hormones::Gonadal Hormones::Gonadal Steroid Hormones [Medical Subject Headings], Case-Control Studies, Chemicals and Drugs::Amino Acids, Peptides, and Proteins::Proteins::Receptors, Cytoplasmic and Nuclear::Receptors, Steroid::Receptors, Androgen [Medical Subject Headings], biology.protein
Abstract

Background: Androgens are key regulators of prostate gland maintenance and prostate cancer growth, and androgen deprivation therapy has been the mainstay of treatment for advanced prostate cancer for many years. A long-standing hypothesis has been that inherited variation in the androgen receptor (AR) gene plays a role in prostate cancer initiation. However, studies to date have been inconclusive and often suffered from small sample sizes. Objective and Methods: We investigated the association of AR sequence variants with circulating sex hormone levels and prostate cancer risk in 6058 prostate cancer cases and 6725 controls of Caucasian origin within the Breast and Prostate Cancer Cohort Consortium. We genotyped a highly polymorphic CAG microsatellite in exon 1 and six haplotype tagging single nucleotide polymorphisms and tested each genetic variant for association with prostate cancer risk and with sex steroid levels. Results: We observed no association between AR genetic variants and prostate cancer risk. However, there was a strong association between longer CAG repeats and higher levels of testosterone (P = 4.73 × 10−5) and estradiol (P = 0.0002), although the amount of variance explained was small (0.4 and 0.7%, respectively). Conclusions: This study is the largest to date investigating AR sequence variants, sex steroid levels, and prostate cancer risk. Although we observed no association between AR sequence variants and prostate cancer risk, our results support earlier findings of a relation between the number of CAG repeats and circulating levels of testosterone and estradiol.

Published
2010

41. 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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42. Tobacco smoking and binge alcohol use are associated with incident venous thromboembolism in an HIV cohort.

Author

Luu B, Ruderman S, Nance R, Delaney JAC, Ma J, Hahn A, Heckbert SR, Budoff MJ, Crothers K, Mathews WC, Christopolous K, Hunt PW, Eron J, Moore R, Keruly J, Lober WB, Burkholder GA, Willig A, Chander G, McCaul ME, Cropsey K, O'Cleirigh C, Peter I, Feinstein M, Tsui JI, Lindstroem S, Saag M, Kitahata MM, Crane HM, Drumright LN, and Whitney BM

Subjects
Ethanol, Humans, Proportional Hazards Models, Prospective Studies, Risk Factors, Tobacco Smoking, Binge Drinking complications, Binge Drinking epidemiology, HIV Infections complications, Venous Thromboembolism epidemiology, Venous Thromboembolism etiology
Abstract

Background: People with HIV (PWH) are at increased risk of cardiovascular comorbidities and substance use is a potential predisposing factor. We evaluated associations of tobacco smoking and alcohol use with venous thromboembolism (VTE) in PWH., Methods: We assessed incident, centrally adjudicated VTE among 12 957 PWH within the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort between January 2009 and December 2018. Using separate Cox proportional hazards models, we evaluated associations of time-updated alcohol and cigarette use with VTE, adjusting for demographic and clinical characteristics. Smoking was evaluated as pack-years and never, former, or current use with current cigarettes per day. Alcohol use was parameterized using categorical and continuous alcohol use score, frequency of use, and binge frequency., Results: During a median of 3.6 years of follow-up, 213 PWH developed a VTE. One-third of PWH reported binge drinking and 40% reported currently smoking. In adjusted analyses, risk of VTE was increased among both current (HR: 1.44, 95% CI: 1.02-2.03) and former (HR: 1.44, 95% CI: 0.99-2.07) smokers compared to PWH who never smoked. Additionally, total pack-years among ever-smokers (HR: 1.10 per 5 pack-years; 95% CI: 1.03-1.18) was associated with incident VTE in a dose-dependent manner. Frequency of binge drinking was associated with incident VTE (HR: 1.30 per 7 days/month, 95% CI: 1.11-1.52); however, alcohol use frequency was not. Severity of alcohol use was not significantly associated with VTE., Conclusions: Current smoking and pack-year smoking history were dose-dependently associated with incident VTE among PWH in CNICS. Binge drinking was also associated with VTE. Interventions for smoking and binge drinking may decrease VTE risk among PWH., (© 2022 British HIV Association.)

Published
2022
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43. A Population-Based Study of Genes Previously Implicated in Breast Cancer.

Author

Hu C, Hart SN, Gnanaolivu R, Huang H, Lee KY, Na J, Gao C, Lilyquist J, Yadav S, Boddicker NJ, Samara R, Klebba J, Ambrosone CB, Anton-Culver H, Auer P, Bandera EV, Bernstein L, Bertrand KA, Burnside ES, Carter BD, Eliassen H, Gapstur SM, Gaudet M, Haiman C, Hodge JM, Hunter DJ, Jacobs EJ, John EM, Kooperberg C, Kurian AW, Le Marchand L, Lindstroem S, Lindstrom T, Ma H, Neuhausen S, Newcomb PA, O'Brien KM, Olson JE, Ong IM, Pal T, Palmer JR, Patel AV, Reid S, Rosenberg L, Sandler DP, Scott C, Tamimi R, Taylor JA, Trentham-Dietz A, Vachon CM, Weinberg C, Yao S, Ziogas A, Weitzel JN, Goldgar DE, Domchek SM, Nathanson KL, Kraft P, Polley EC, and Couch FJ

Subjects
Adult, Aged, Aged, 80 and over, Case-Control Studies, Female, Humans, Middle Aged, Mutation, Odds Ratio, Risk, Sequence Analysis, DNA, Young Adult, Breast Neoplasms genetics, Genetic Predisposition to Disease genetics, Genetic Variation
Abstract

Background: Population-based estimates of the risk of breast cancer associated with germline pathogenic variants in cancer-predisposition genes are critically needed for risk assessment and management in women with inherited pathogenic variants., Methods: In a population-based case-control study, we performed sequencing using a custom multigene amplicon-based panel to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer (case patients) and 32,544 unaffected women (controls) from population-based studies in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Associations between pathogenic variants in each gene and the risk of breast cancer were assessed., Results: Pathogenic variants in 12 established breast cancer-predisposition genes were detected in 5.03% of case patients and in 1.63% of controls. Pathogenic variants in BRCA1 and BRCA2 were associated with a high risk of breast cancer, with odds ratios of 7.62 (95% confidence interval [CI], 5.33 to 11.27) and 5.23 (95% CI, 4.09 to 6.77), respectively. Pathogenic variants in PALB2 were associated with a moderate risk (odds ratio, 3.83; 95% CI, 2.68 to 5.63). Pathogenic variants in BARD1 , RAD51C , and RAD51D were associated with increased risks of estrogen receptor-negative breast cancer and triple-negative breast cancer, whereas pathogenic variants in ATM , CDH1 , and CHEK2 were associated with an increased risk of estrogen receptor-positive breast cancer. Pathogenic variants in 16 candidate breast cancer-predisposition genes, including the c.657&#95;661del5 founder pathogenic variant in NBN , were not associated with an increased risk of breast cancer., Conclusions: This study provides estimates of the prevalence and risk of breast cancer associated with pathogenic variants in known breast cancer-predisposition genes in the U.S. population. These estimates can inform cancer testing and screening and improve clinical management strategies for women in the general population with inherited pathogenic variants in these genes. (Funded by the National Institutes of Health and the Breast Cancer Research Foundation.)., (Copyright © 2021 Massachusetts Medical Society.)

Published
2021
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44. Telomere Maintenance Variants and Survival after Colorectal Cancer: Smoking- and Sex-Specific Associations.

Author

Yin H, Hardikar S, Lindstroem S, Hsu L, Anderson KE, Banbury BL, Berndt SI, Chan AT, Giovanucci EL, Harrison TA, Joshi AD, Nan H, Potter JD, Sakoda LC, Slattery ML, Schoen RE, White E, Peters U, and Newcomb PA

Subjects
Aged, Colorectal Neoplasms mortality, Colorectal Neoplasms pathology, Female, Humans, Male, Prognosis, Sex Factors, Survival Analysis, Colorectal Neoplasms genetics, Smoking adverse effects, Telomere metabolism
Abstract

Background: Telomeres play an important role in colorectal cancer prognosis. Variation in telomere maintenance genes may be associated with survival after colorectal cancer diagnosis, but evidence is limited. In addition, possible interactions between telomere maintenance genes and prognostic factors, such as smoking and sex, also remain to be investigated., Methods: We conducted gene-wide analyses of colorectal cancer prognosis in 4,896 invasive colorectal cancer cases from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO); 1,871 common variants within 13 telomere maintenance genes were included. Cox models were fit to estimate associations of these variants individually with overall and colorectal cancer-specific survival. Likelihood ratio tests were used to test for interaction by smoking and sex. P values were adjusted using Bonferroni correction., Results: The association between minor allele of rs7200950 ( ACD ) with colorectal cancer-specific survival varied significantly by smoking pack-years (corrected P = 0.049), but no significant trend was observed. By sex, minor alleles for rs2975843 ( TERF1 ), rs75676021 ( POT1 ), and rs74429678 ( POT1 ) were associated with decreased overall and/or colorectal cancer-specific survival in women but not in men., Conclusions: Our study reported a gene-wide statistically significant interaction with sex ( TERF1, POT1 ). Although significant interaction by smoking pack-years ( ACD ) was observed, there was no evidence of a dose response. Validation of these findings in other large studies and further functional annotation on these SNPs are warranted., Impact: Our study found a gene-smoking and gene-sex interaction on survival after colorectal cancer diagnosis, providing new insights into the role of genetic polymorphisms in telomere maintenance on colorectal cancer prognosis., (©2020 American Association for Cancer Research.)

Published
2020
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45. Interaction of a genetic risk score with physical activity, physical inactivity, and body mass index in relation to venous thromboembolism risk.

Author

Kim J, Kraft P, Hagan KA, Harrington LB, Lindstroem S, and Kabrhel C

Subjects
Adult, Female, Follow-Up Studies, Genome-Wide Association Study, Humans, Logistic Models, Male, Middle Aged, Models, Genetic, Polymorphism, Single Nucleotide, Risk Factors, Body Mass Index, Exercise, Genetic Predisposition to Disease, Venous Thromboembolism genetics
Abstract

Introduction: Venous thromboembolism (VTE) is highly heritable. Physical activity, physical inactivity and body mass index (BMI) are also risk factors, but evidence of interaction between genetic and environmental risk factors is limited., Methods: Data on 2,134 VTE cases and 3,890 matched controls were obtained from the Nurses' Health Study (NHS), Nurses' Health Study II (NHS II), and Health Professionals Follow-up Study (HPFS). We calculated a weighted genetic risk score (wGRS) using 16 single nucleotide polymorphisms associated with VTE risk in published genome-wide association studies (GWAS). Data on three risk factors, physical activity (metabolic equivalent [MET] hours per week), physical inactivity (sitting hours per week) and BMI, were obtained from biennial questionnaires. VTE cases were incident since cohort inception; controls were matched to cases on age, cohort, and genotype array. Using conditional logistic regression, we assessed joint effects and interaction effects on both additive and multiplicative scales. We also ran models using continuous wGRS stratified by risk-factor categories., Results: We observed a supra-additive interaction between wGRS and BMI. Having both high wGRS and high BMI was associated with a 3.4-fold greater risk of VTE (relative excess risk due to interaction = 0.69, p = 0.046). However, we did not find evidence for a multiplicative interaction with BMI. No interactions were observed for physical activity or inactivity., Conclusion: We found a synergetic effect between a genetic risk score and high BMI on the risk of VTE. Intervention efforts lowering BMI to decrease VTE risk may have particularly large beneficial effects among individuals with high genetic risk., (© 2018 WILEY PERIODICALS, INC.)

Published
2018
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