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1.  Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: A genome-wide interaction study 
Endocrine-related cancer  2013;20(6):875-887.
Women using menopausal hormone therapy (MHT) are at increased risk to develop 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 eleven 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 2,920 cases (541 lobular) from four genome-wide association studies. The top 1,391 SNPs showing P-values for interaction (Pint) <3.0×10−03 were selected for replication using pooled case-control data from eleven studies of the Breast Cancer Association Consortium, including 7,689 cases (676 lobular) and 9,266 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≤8.9×10−06), two SNPs in SLC25A21 (combined Pint≤4.8×10−05), and three SNPs in PLCG2 (combined Pint≤4.5×10−05). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7×10−05), one SNP in CD80 (combined Pint≤8.2×10−06), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10−06), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6×10−05). 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.
doi:10.1530/ERC-13-0349
PMCID: PMC3863710  PMID: 24080446
breast cancer; genetic variation; menopausal hormone therapy; genome-wide
2.  MicroRNA Related Polymorphisms and Breast Cancer Risk 
Khan, Sofia | Greco, Dario | Michailidou, Kyriaki | Milne, Roger L. | Muranen, Taru A. | Heikkinen, Tuomas | Aaltonen, Kirsimari | Dennis, Joe | Bolla, Manjeet K. | Liu, Jianjun | Hall, Per | Irwanto, Astrid | Humphreys, Keith | Li, Jingmei | Czene, Kamila | Chang-Claude, Jenny | Hein, Rebecca | Rudolph, Anja | Seibold, Petra | Flesch-Janys, Dieter | Fletcher, Olivia | Peto, Julian | dos Santos Silva, Isabel | Johnson, Nichola | Gibson, Lorna | Aitken, Zoe | Hopper, John L. | Tsimiklis, Helen | Bui, Minh | Makalic, Enes | Schmidt, Daniel F. | Southey, Melissa C. | Apicella, Carmel | Stone, Jennifer | Waisfisz, Quinten | Meijers-Heijboer, Hanne | Adank, Muriel A. | van der Luijt, Rob B. | Meindl, Alfons | Schmutzler, Rita K. | Müller-Myhsok, Bertram | Lichtner, Peter | Turnbull, Clare | Rahman, Nazneen | Chanock, Stephen J. | Hunter, David J. | Cox, Angela | Cross, Simon S. | Reed, Malcolm W. R. | Schmidt, Marjanka K. | Broeks, Annegien | Veer, Laura J. V. a. n't. | Hogervorst, Frans B. | Fasching, Peter A. | Schrauder, Michael G. | Ekici, Arif B. | Beckmann, Matthias W. | Bojesen, Stig E. | Nordestgaard, Børge G. | Nielsen, Sune F. | Flyger, Henrik | Benitez, Javier | Zamora, Pilar M. | Perez, Jose I. A. | Haiman, Christopher A. | Henderson, Brian E. | Schumacher, Fredrick | Le Marchand, Loic | Pharoah, Paul D. P. | Dunning, Alison M. | Shah, Mitul | Luben, Robert | Brown, Judith | Couch, Fergus J. | Wang, Xianshu | Vachon, Celine | Olson, Janet E. | Lambrechts, Diether | Moisse, Matthieu | Paridaens, Robert | Christiaens, Marie-Rose | Guénel, Pascal | Truong, Thérèse | Laurent-Puig, Pierre | Mulot, Claire | Marme, Frederick | Burwinkel, Barbara | Schneeweiss, Andreas | Sohn, Christof | Sawyer, Elinor J. | Tomlinson, Ian | Kerin, Michael J. | Miller, Nicola | Andrulis, Irene L. | Knight, Julia A. | Tchatchou, Sandrine | Mulligan, Anna Marie | Dörk, Thilo | Bogdanova, Natalia V. | Antonenkova, Natalia N. | Anton-Culver, Hoda | Darabi, Hatef | Eriksson, Mikael | Garcia-Closas, Montserrat | Figueroa, Jonine | Lissowska, Jolanta | Brinton, Louise | Devilee, Peter | Tollenaar, Robert A. E. M. | Seynaeve, Caroline | van Asperen, Christi J. | Kristensen, Vessela N. | Slager, Susan | Toland, Amanda E. | Ambrosone, Christine B. | Yannoukakos, Drakoulis | Lindblom, Annika | Margolin, Sara | Radice, Paolo | Peterlongo, Paolo | Barile, Monica | Mariani, Paolo | Hooning, Maartje J. | Martens, John W. M. | Collée, J. Margriet | Jager, Agnes | Jakubowska, Anna | Lubinski, Jan | Jaworska-Bieniek, Katarzyna | Durda, Katarzyna | Giles, Graham G. | McLean, Catriona | Brauch, Hiltrud | Brüning, Thomas | Ko, Yon-Dschun | Brenner, Hermann | Dieffenbach, Aida Karina | Arndt, Volker | Stegmaier, Christa | Swerdlow, Anthony | Ashworth, Alan | Orr, Nick | Jones, Michael | Simard, Jacques | Goldberg, Mark S. | Labrèche, France | Dumont, Martine | Winqvist, Robert | Pylkäs, Katri | Jukkola-Vuorinen, Arja | Grip, Mervi | Kataja, Vesa | Kosma, Veli-Matti | Hartikainen, Jaana M. | Mannermaa, Arto | Hamann, Ute | Chenevix-Trench, Georgia | Blomqvist, Carl | Aittomäki, Kristiina | Easton, Douglas F. | Nevanlinna, Heli
PLoS ONE  2014;9(11):e109973.
Genetic variations, such as single nucleotide polymorphisms (SNPs) in microRNAs (miRNA) or in the miRNA binding sites may affect the miRNA dependent gene expression regulation, which has been implicated in various cancers, including breast cancer, and may alter individual susceptibility to cancer. We investigated associations between miRNA related SNPs and breast cancer risk. First we evaluated 2,196 SNPs in a case-control study combining nine genome wide association studies (GWAS). Second, we further investigated 42 SNPs with suggestive evidence for association using 41,785 cases and 41,880 controls from 41 studies included in the Breast Cancer Association Consortium (BCAC). Combining the GWAS and BCAC data within a meta-analysis, we estimated main effects on breast cancer risk as well as risks for estrogen receptor (ER) and age defined subgroups. Five miRNA binding site SNPs associated significantly with breast cancer risk: rs1045494 (odds ratio (OR) 0.92; 95% confidence interval (CI): 0.88–0.96), rs1052532 (OR 0.97; 95% CI: 0.95–0.99), rs10719 (OR 0.97; 95% CI: 0.94–0.99), rs4687554 (OR 0.97; 95% CI: 0.95–0.99, and rs3134615 (OR 1.03; 95% CI: 1.01–1.05) located in the 3′ UTR of CASP8, HDDC3, DROSHA, MUSTN1, and MYCL1, respectively. DROSHA belongs to miRNA machinery genes and has a central role in initial miRNA processing. The remaining genes are involved in different molecular functions, including apoptosis and gene expression regulation. Further studies are warranted to elucidate whether the miRNA binding site SNPs are the causative variants for the observed risk effects.
doi:10.1371/journal.pone.0109973
PMCID: PMC4229095  PMID: 25390939
3.  Common non-synonymous SNPs associated with breast cancer susceptibility: findings from the Breast Cancer Association Consortium 
Milne, Roger L. | Burwinkel, Barbara | Michailidou, Kyriaki | Arias-Perez, Jose-Ignacio | Zamora, M. Pilar | Menéndez-Rodríguez, Primitiva | Hardisson, David | Mendiola, Marta | González-Neira, Anna | Pita, Guillermo | Alonso, M. Rosario | Dennis, Joe | Wang, Qin | Bolla, Manjeet K. | Swerdlow, Anthony | Ashworth, Alan | Orr, Nick | Schoemaker, Minouk | Ko, Yon-Dschun | Brauch, Hiltrud | Hamann, Ute | Andrulis, Irene L. | Knight, Julia A. | Glendon, Gord | Tchatchou, Sandrine | Matsuo, Keitaro | Ito, Hidemi | Iwata, Hiroji | Tajima, Kazuo | Li, Jingmei | Brand, Judith S. | Brenner, Hermann | Dieffenbach, Aida Karina | Arndt, Volker | Stegmaier, Christa | Lambrechts, Diether | Peuteman, Gilian | Christiaens, Marie-Rose | Smeets, Ann | Jakubowska, Anna | Lubinski, Jan | Jaworska-Bieniek, Katarzyna | Durda, Katazyna | Hartman, Mikael | Hui, Miao | Yen Lim, Wei | Wan Chan, Ching | Marme, Federick | Yang, Rongxi | Bugert, Peter | Lindblom, Annika | Margolin, Sara | García-Closas, Montserrat | Chanock, Stephen J. | Lissowska, Jolanta | Figueroa, Jonine D. | Bojesen, Stig E. | Nordestgaard, Børge G. | Flyger, Henrik | Hooning, Maartje J. | Kriege, Mieke | van den Ouweland, Ans M.W. | Koppert, Linetta B. | Fletcher, Olivia | Johnson, Nichola | dos-Santos-Silva, Isabel | Peto, Julian | Zheng, Wei | Deming-Halverson, Sandra | Shrubsole, Martha J. | Long, Jirong | Chang-Claude, Jenny | Rudolph, Anja | Seibold, Petra | Flesch-Janys, Dieter | Winqvist, Robert | Pylkäs, Katri | Jukkola-Vuorinen, Arja | Grip, Mervi | Cox, Angela | Cross, Simon S. | Reed, Malcolm W.R. | Schmidt, Marjanka K. | Broeks, Annegien | Cornelissen, Sten | Braaf, Linde | Kang, Daehee | Choi, Ji-Yeob | Park, Sue K. | Noh, Dong-Young | Simard, Jacques | Dumont, Martine | Goldberg, Mark S. | Labrèche, France | Fasching, Peter A. | Hein, Alexander | Ekici, Arif B. | Beckmann, Matthias W. | Radice, Paolo | Peterlongo, Paolo | Azzollini, Jacopo | Barile, Monica | Sawyer, Elinor | Tomlinson, Ian | Kerin, Michael | Miller, Nicola | Hopper, John L. | Schmidt, Daniel F. | Makalic, Enes | Southey, Melissa C. | Hwang Teo, Soo | Har Yip, Cheng | Sivanandan, Kavitta | Tay, Wan-Ting | Shen, Chen-Yang | Hsiung, Chia-Ni | Yu, Jyh-Cherng | Hou, Ming-Feng | Guénel, Pascal | Truong, Therese | Sanchez, Marie | Mulot, Claire | Blot, William | Cai, Qiuyin | Nevanlinna, Heli | Muranen, Taru A. | Aittomäki, Kristiina | Blomqvist, Carl | Wu, Anna H. | Tseng, Chiu-Chen | Van Den Berg, David | Stram, Daniel O. | Bogdanova, Natalia | Dörk, Thilo | Muir, Kenneth | Lophatananon, Artitaya | Stewart-Brown, Sarah | Siriwanarangsan, Pornthep | Mannermaa, Arto | Kataja, Vesa | Kosma, Veli-Matti | Hartikainen, Jaana M. | Shu, Xiao-Ou | Lu, Wei | Gao, Yu-Tang | Zhang, Ben | Couch, Fergus J. | Toland, Amanda E. | Yannoukakos, Drakoulis | Sangrajrang, Suleeporn | McKay, James | Wang, Xianshu | Olson, Janet E. | Vachon, Celine | Purrington, Kristen | Severi, Gianluca | Baglietto, Laura | Haiman, Christopher A. | Henderson, Brian E. | Schumacher, Fredrick | Le Marchand, Loic | Devilee, Peter | Tollenaar, Robert A.E.M. | Seynaeve, Caroline | Czene, Kamila | Eriksson, Mikael | Humphreys, Keith | Darabi, Hatef | Ahmed, Shahana | Shah, Mitul | Pharoah, Paul D.P. | Hall, Per | Giles, Graham G. | Benítez, Javier | Dunning, Alison M. | Chenevix-Trench, Georgia | Easton, Douglas F. | Berchuck, Andrew | Eeles, Rosalind A. | Olama, Ali Amin Al | Kote-Jarai, Zsofia | Benlloch, Sara | Antoniou, Antonis | McGuffog, Lesley | Offit, Ken | Lee, Andrew | Dicks, Ed | Luccarini, Craig | Tessier, Daniel C. | Bacot, Francois | Vincent, Daniel | LaBoissière, Sylvie | Robidoux, Frederic | Nielsen, Sune F. | Cunningham, Julie M. | Windebank, Sharon A. | Hilker, Christopher A. | Meyer, Jeffrey | Angelakos, Maggie | Maskiell, Judi | van der Schoot, Ellen | Rutgers, Emiel | Verhoef, Senno | Hogervorst, Frans | Boonyawongviroj, Prat | Siriwanarungsan, Pornthep | Schrauder, Michael | Rübner, Matthias | Oeser, Sonja | Landrith, Silke | Williams, Eileen | Ryder-Mills, Elaine | Sargus, Kara | McInerney, Niall | Colleran, Gabrielle | Rowan, Andrew | Jones, Angela | Sohn, Christof | Schneeweiß, Andeas | Bugert, Peter | Álvarez, Núria | Lacey, James | Wang, Sophia | Ma, Huiyan | Lu, Yani | Deapen, Dennis | Pinder, Rich | Lee, Eunjung | Schumacher, Fred | Horn-Ross, Pam | Reynolds, Peggy | Nelson, David | Ziegler, Hartwig | Wolf, Sonja | Hermann, Volker | Lo, Wing-Yee | Justenhoven, Christina | Baisch, Christian | Fischer, Hans-Peter | Brüning, Thomas | Pesch, Beate | Rabstein, Sylvia | Lotz, Anne | Harth, Volker | Heikkinen, Tuomas | Erkkilä, Irja | Aaltonen, Kirsimari | von Smitten, Karl | Antonenkova, Natalia | Hillemanns, Peter | Christiansen, Hans | Myöhänen, Eija | Kemiläinen, Helena | Thorne, Heather | Niedermayr, Eveline | Bowtell, D | Chenevix-Trench, G | deFazio, A | Gertig, D | Green, A | Webb, P | Green, A. | Parsons, P. | Hayward, N. | Webb, P. | Whiteman, D. | Fung, Annie | Yashiki, June | Peuteman, Gilian | Smeets, Dominiek | Brussel, Thomas Van | Corthouts, Kathleen | Obi, Nadia | Heinz, Judith | Behrens, Sabine | Eilber, Ursula | Celik, Muhabbet | Olchers, Til | Manoukian, Siranoush | Peissel, Bernard | Scuvera, Giulietta | Zaffaroni, Daniela | Bonanni, Bernardo | Feroce, Irene | Maniscalco, Angela | Rossi, Alessandra | Bernard, Loris | Tranchant, Martine | Valois, Marie-France | Turgeon, Annie | Heguy, Lea | Sze Yee, Phuah | Kang, Peter | Nee, Kang In | Mariapun, Shivaani | Sook-Yee, Yoon | Lee, Daphne | Ching, Teh Yew | Taib, Nur Aishah Mohd | Otsukka, Meeri | Mononen, Kari | Selander, Teresa | Weerasooriya, Nayana | staff, OFBCR | Krol-Warmerdam, E. | Molenaar, J. | Blom, J. | Brinton, Louise | Szeszenia-Dabrowska, Neonila | Peplonska, Beata | Zatonski, Witold | Chao, Pei | Stagner, Michael | Bos, Petra | Blom, Jannet | Crepin, Ellen | Nieuwlaat, Anja | Heemskerk, Annette | Higham, Sue | Cross, Simon | Cramp, Helen | Connley, Dan | Balasubramanian, Sabapathy | Brock, Ian | Luccarini, Craig | Conroy, Don | Baynes, Caroline | Chua, Kimberley
Human Molecular Genetics  2014;23(22):6096-6111.
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04–1.10, P = 2.9 × 10−6], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03–1.07, P = 1.7 × 10−6) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07–1.12, P = 5.1 × 10−17). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05–1.10, P = 1.0 × 10−8); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04–1.07, P = 2.0 × 10−10). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.
doi:10.1093/hmg/ddu311
PMCID: PMC4204770  PMID: 24943594
4.  Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions 
Schoeps, Anja | Rudolph, Anja | Seibold, Petra | Dunning, Alison M. | Milne, Roger L. | Bojesen, Stig E. | Swerdlow, Anthony | Andrulis, Irene | Brenner, Hermann | Behrens, Sabine | Orr, Nicholas | Jones, Michael | Ashworth, Alan | Li, Jingmei | Cramp, Helen | Connley, Dan | Czene, Kamila | Darabi, Hatef | Chanock, Stephen J. | Lissowska, Jolanta | Figueroa, Jonine D. | Knight, Julia | Glendon, Gord | Mulligan, Anna M. | Dumont, Martine | Severi, Gianluca | Baglietto, Laura | Olson, Janet | Vachon, Celine | Purrington, Kristen | Moisse, Matthieu | Neven, Patrick | Wildiers, Hans | Spurdle, Amanda | Kosma, Veli-Matti | Kataja, Vesa | Hartikainen, Jaana M. | Hamann, Ute | Ko, Yon-Dschun | Dieffenbach, Aida K. | Arndt, Volker | Stegmaier, Christa | Malats, Núria | Arias Perez, JoséI. | Benítez, Javier | Flyger, Henrik | Nordestgaard, Børge G. | Truong, Théresè | Cordina-Duverger, Emilie | Menegaux, Florence | Silva, Isabel dos Santos | Fletcher, Olivia | Johnson, Nichola | Häberle, Lothar | Beckmann, Matthias W. | Ekici, Arif B. | Braaf, Linde | Atsma, Femke | van den Broek, Alexandra J. | Makalic, Enes | Schmidt, Daniel F. | Southey, Melissa C. | Cox, Angela | Simard, Jacques | Giles, Graham G. | Lambrechts, Diether | Mannermaa, Arto | Brauch, Hiltrud | Guénel, Pascal | Peto, Julian | Fasching, Peter A. | Hopper, John | Flesch-Janys, Dieter | Couch, Fergus | Chenevix-Trench, Georgia | Pharoah, Paul D. P. | Garcia-Closas, Montserrat | Schmidt, Marjanka K. | Hall, Per | Easton, Douglas F. | Chang-Claude, Jenny
Genetic epidemiology  2013;38(1):84-93.
Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.
doi:10.1002/gepi.21771
PMCID: PMC3995140  PMID: 24248812
breast cancer risk; gene-environment interaction; polymorphisms; body mass index; case-control study
5.  Smoking, variation in N-acetyltransferase 1 (NAT1) and 2 (NAT2), and risk of non-Hodgkin lymphoma: a pooled analysis within the InterLymph consortium 
Cancer causes & control : CCC  2012;24(1):125-134.
Purpose
Studies of smoking and risk of non-Hodgkin lymphoma (NHL) have yielded inconsistent results, possibly due to subtype heterogeneity and/or genetic variation impacting the metabolism of tobacco-derived carcinogens, including substrates of the N-acetyltransferase enzymes NAT1 and NAT2.
Methods
We conducted a pooled analysis of 5,026 NHL cases and 4,630 controls from seven case–control studies in the international lymphoma epidemiology consortium to examine associations between smoking, variation in the N-acetyltransferase genes NAT1 and NAT2, and risk of NHL subtypes. Smoking data were harmonized across studies, and genetic variants in NAT1 and NAT2 were used to infer acetylation phenotype of the NAT1 and NAT2 enzymes, respectively. Pooled odds ratios (ORs) and 95 % confidence intervals (95 % CIs) for risk of NHL and subtypes were calculated using joint fixed effects unconditional logistic regression models.
Results
Current smoking was associated with a significant 30 % increased risk of follicular lymphoma (n = 1,176) but not NHL overall or other NHL subtypes. The association was similar among NAT2 slow (OR 1.36; 95 % CI 1.07–1.75) and intermediate/rapid (OR 1.27; 95 % CI 0.95–1.69) acetylators (pinteraction = 0.82) and also did not differ by NAT1*10 allelotype. Neither NAT2 phenotype nor NAT1*10 allelotype was associated with risk of NHL overall or NHL subtypes.
Conclusion
The current findings provide further evidence for a modest association between current smoking and follicular lymphoma risk and suggest that this association may not be influenced by variation in the N-acetyltransferase enzymes.
doi:10.1007/s10552-012-0098-4
PMCID: PMC3529854  PMID: 23160945
Non-Hodgkin lymphoma; Gene environment interaction; Cigarette smoking; N-acetyltransferase; Follicular lymphoma
6.  A meta-analysis of genome-wide association studies of follicular lymphoma 
BMC Genomics  2012;13:516.
Background
B-cell non-Hodgkin lymphoma represents a diverse group of hematological malignancies, of which follicular lymphoma (FL) is one of the most common subtypes. Family and epidemiological studies suggest an important genetic role in the etiology of FL. In recent genome-wide association studies (GWAS) of FL, several genetic susceptibility loci have been identified on chromosome 6p21.33 (rs6457327) and 6p21.32 (rs10484561, rs2647012) in the human leukocyte antigen class I and class II regions. To identify new genetic variants and further elucidate the genetic basis of FL, a meta-analysis was performed of the top 1000 SNPs associated with FL risk from two GWAS in the US, Denmark and Sweden (592 cases, 1541 controls), with independent validation in 107 cases and 681 controls.
Results
rs9275517 and rs3117222 in the HLA class II region were validated and inversely associated with FL risk (rs9275517: OR = 0.63, 95% CI = 0.55-0.73, p = 4.03 × 10-11; rs3117222: OR = 0.66, 95% CI = 0.57-0.77, p = 1.45 × 10-7). rs9275517, which is in high linkage disequilibrium with rs2647012 (r2 = 0.9), was no longer associated with FL after conditioning on rs2647012. The rs3117222 association was independent of established FL SNPs, but not of the HLA-DPB1*0301 allele. Using publicly available gene expression profiles with matching genotype information, we found that rs3117222 also was significantly correlated with increased HLA-DPB1 expression.
Conclusions
By performing a meta-analysis of two GWAS of FL, we further validated the relevance of HLA-DPB1*0301 as a protective allele in the pathogenesis of FL. Moreover, the protective rs3117222 A allele correlated with increased levels of HLA-DPB1, suggesting a possible disease mechanism involving HLA-DPB1 expression regulation. Our results add further support to the major role of HLA genetic variation in the pathogenesis of FL.
doi:10.1186/1471-2164-13-516
PMCID: PMC3534234  PMID: 23025665
Follicular lymphoma (FL); Genome-wide association studies (GWAS); Human leukocyte antigen (HLA); Meta-analysis
7.  Genetic Variants in ER Cofactor Genes and Endometrial Cancer Risk 
PLoS ONE  2012;7(8):e42445.
Given that the transcriptional regulatory activity of estrogen receptor (ER) is modulated by its biochemical cofactors, genetic variation within the ER cofactor genes may alter cellular response to estrogen exposure and consequently modify the risk for endometrial cancer. We genotyped 685 tagging SNPs within 60 ER cofactor genes in 564 endometrial cancer cases and 1,510 controls from Sweden, and tested their associations with the risk of endometrial cancer. We investigated the associations of individual SNPs by using a trend test as well as multiple SNPs within a gene or gene complex by using multi-variant association analysis. No significant association was observed for any individual SNPs or genes, but a marginal association of the cumulative genetic variation of the NCOA2 complex as a whole (NCOA2, CARM1, CREBBP, PRMT1 and EP300) with endometrial cancer risk was observed (Padjusted = 0.033). However, the association failed to be replicated in an independent European dataset of 1265 cases and 5190 controls (P = 0.71). The results indicate that common genetic variants within ER cofactor genes are unlikely to play a significant role in endometrial cancer risk in European population.
doi:10.1371/journal.pone.0042445
PMCID: PMC3411617  PMID: 22876322
8.  Breast cancer risk prediction and individualised screening based on common genetic variation and breast density measurement 
Introduction
Over the last decade several breast cancer risk alleles have been identified which has led to an increased interest in individualised risk prediction for clinical purposes.
Methods
We investigate the performance of an up-to-date 18 breast cancer risk single-nucleotide polymorphisms (SNPs), together with mammographic percentage density (PD), body mass index (BMI) and clinical risk factors in predicting absolute risk of breast cancer, empirically, in a well characterised Swedish case-control study of postmenopausal women. We examined the efficiency of various prediction models at a population level for individualised screening by extending a recently proposed analytical approach for estimating number of cases captured.
Results
The performance of a risk prediction model based on an initial set of seven breast cancer risk SNPs is improved by additionally including eleven more recently established breast cancer risk SNPs (P = 4.69 × 10-4). Adding mammographic PD, BMI and all 18 SNPs to a Swedish Gail model improved the discriminatory accuracy (the AUC statistic) from 55% to 62%. The net reclassification improvement was used to assess improvement in classification of women into low, intermediate, and high categories of 5-year risk (P = 8.93 × 10-9). For scenarios we considered, we estimated that an individualised screening strategy based on risk models incorporating clinical risk factors, mammographic density and SNPs, captures 10% more cases than a screening strategy using the same resources, based on age alone. Estimates of numbers of cases captured by screening stratified by age provide insight into how individualised screening programs might appear in practice.
Conclusions
Taken together, genetic risk factors and mammographic density offer moderate improvements to clinical risk factor models for predicting breast cancer.
doi:10.1186/bcr3110
PMCID: PMC3496143  PMID: 22314178
9.  Associations of Breast Cancer Risk Factors With Tumor Subtypes: A Pooled Analysis From the Breast Cancer Association Consortium Studies 
Yang, Xiaohong R. | Chang-Claude, Jenny | Goode, Ellen L. | Couch, Fergus J. | Nevanlinna, Heli | Milne, Roger L. | Gaudet, Mia | Schmidt, Marjanka K. | Broeks, Annegien | Cox, Angela | Fasching, Peter A. | Hein, Rebecca | Spurdle, Amanda B. | Blows, Fiona | Driver, Kristy | Flesch-Janys, Dieter | Heinz, Judith | Sinn, Peter | Vrieling, Alina | Heikkinen, Tuomas | Aittomäki, Kristiina | Heikkilä, Päivi | Blomqvist, Carl | Lissowska, Jolanta | Peplonska, Beata | Chanock, Stephen | Figueroa, Jonine | Brinton, Louise | Hall, Per | Czene, Kamila | Humphreys, Keith | Darabi, Hatef | Liu, Jianjun | Van ‘t Veer, Laura J. | van Leeuwen, Flora E. | Andrulis, Irene L. | Glendon, Gord | Knight, Julia A. | Mulligan, Anna Marie | O’Malley, Frances P. | Weerasooriya, Nayana | John, Esther M. | Beckmann, Matthias W. | Hartmann, Arndt | Weihbrecht, Sebastian B. | Wachter, David L. | Jud, Sebastian M. | Loehberg, Christian R. | Baglietto, Laura | English, Dallas R. | Giles, Graham G. | McLean, Catriona A. | Severi, Gianluca | Lambrechts, Diether | Vandorpe, Thijs | Weltens, Caroline | Paridaens, Robert | Smeets, Ann | Neven, Patrick | Wildiers, Hans | Wang, Xianshu | Olson, Janet E. | Cafourek, Victoria | Fredericksen, Zachary | Kosel, Matthew | Vachon, Celine | Cramp, Helen E. | Connley, Daniel | Cross, Simon S. | Balasubramanian, Sabapathy P. | Reed, Malcolm W. R. | Dörk, Thilo | Bremer, Michael | Meyer, Andreas | Karstens, Johann H. | Ay, Aysun | Park-Simon, Tjoung-Won | Hillemanns, Peter | Arias Pérez, Jose Ignacio | Rodríguez, Primitiva Menéndez | Zamora, Pilar | Benítez, Javier | Ko, Yon-Dschun | Fischer, Hans-Peter | Hamann, Ute | Pesch, Beate | Brüning, Thomas | Justenhoven, Christina | Brauch, Hiltrud | Eccles, Diana M. | Tapper, William J. | Gerty, Sue M. | Sawyer, Elinor J. | Tomlinson, Ian P. | Jones, Angela | Kerin, Michael | Miller, Nicola | McInerney, Niall | Anton-Culver, Hoda | Ziogas, Argyrios | Shen, Chen-Yang | Hsiung, Chia-Ni | Wu, Pei-Ei | Yang, Show-Lin | Yu, Jyh-Cherng | Chen, Shou-Tung | Hsu, Giu-Cheng | Haiman, Christopher A. | Henderson, Brian E. | Le Marchand, Loic | Kolonel, Laurence N. | Lindblom, Annika | Margolin, Sara | Jakubowska, Anna | Lubiński, Jan | Huzarski, Tomasz | Byrski, Tomasz | Górski, Bohdan | Gronwald, Jacek | Hooning, Maartje J. | Hollestelle, Antoinette | van den Ouweland, Ans M. W. | Jager, Agnes | Kriege, Mieke | Tilanus-Linthorst, Madeleine M. A. | Collée, Margriet | Wang-Gohrke, Shan | Pylkäs, Katri | Jukkola-Vuorinen, Arja | Mononen, Kari | Grip, Mervi | Hirvikoski, Pasi | Winqvist, Robert | Mannermaa, Arto | Kosma, Veli-Matti | Kauppinen, Jaana | Kataja, Vesa | Auvinen, Päivi | Soini, Ylermi | Sironen, Reijo | Bojesen, Stig E. | Dynnes Ørsted, David | Kaur-Knudsen, Diljit | Flyger, Henrik | Nordestgaard, Børge G. | Holland, Helene | Chenevix-Trench, Georgia | Manoukian, Siranoush | Barile, Monica | Radice, Paolo | Hankinson, Susan E. | Hunter, David J. | Tamimi, Rulla | Sangrajrang, Suleeporn | Brennan, Paul | McKay, James | Odefrey, Fabrice | Gaborieau, Valerie | Devilee, Peter | Huijts, P.E.A. | Tollenaar, RAEM. | Seynaeve, C. | Dite, Gillian S. | Apicella, Carmel | Hopper, John L. | Hammet, Fleur | Tsimiklis, Helen | Smith, Letitia D. | Southey, Melissa C. | Humphreys, Manjeet K. | Easton, Douglas | Pharoah, Paul | Sherman, Mark E. | Garcia-Closas, Montserrat
Background
Previous studies have suggested that breast cancer risk factors are associated with estrogen receptor (ER) and progesterone receptor (PR) expression status of the tumors.
Methods
We pooled tumor marker and epidemiological risk factor data from 35 568 invasive breast cancer case patients from 34 studies participating in the Breast Cancer Association Consortium. Logistic regression models were used in case–case analyses to estimate associations between epidemiological risk factors and tumor subtypes, and case–control analyses to estimate associations between epidemiological risk factors and the risk of developing specific tumor subtypes in 12 population-based studies. All statistical tests were two-sided.
Results
In case–case analyses, of the epidemiological risk factors examined, early age at menarche (≤12 years) was less frequent in case patients with PR− than PR+ tumors (P = .001). Nulliparity (P = 3 × 10−6) and increasing age at first birth (P = 2 × 10−9) were less frequent in ER− than in ER+ tumors. Obesity (body mass index [BMI] ≥ 30 kg/m2) in younger women (≤50 years) was more frequent in ER−/PR− than in ER+/PR+ tumors (P = 1 × 10−7), whereas obesity in older women (>50 years) was less frequent in PR− than in PR+ tumors (P = 6 × 10−4). The triple-negative (ER−/PR−/HER2−) or core basal phenotype (CBP; triple-negative and cytokeratins [CK]5/6+ and/or epidermal growth factor receptor [EGFR]+) accounted for much of the heterogeneity in parity-related variables and BMI in younger women. Case–control analyses showed that nulliparity, increasing age at first birth, and obesity in younger women showed the expected associations with the risk of ER+ or PR+ tumors but not triple-negative (nulliparity vs parity, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.75 to 1.19, P = .61; 5-year increase in age at first full-term birth, OR = 0.95, 95% CI = 0.86 to 1.05, P = .34; obesity in younger women, OR = 1.36, 95% CI = 0.95 to 1.94, P = .09) or CBP tumors.
Conclusions
This study shows that reproductive factors and BMI are most clearly associated with hormone receptor–positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.
doi:10.1093/jnci/djq526
PMCID: PMC3107570  PMID: 21191117
10.  GWAS of Follicular Lymphoma Reveals Allelic Heterogeneity at 6p21.32 and Suggests Shared Genetic Susceptibility with Diffuse Large B-cell Lymphoma 
PLoS Genetics  2011;7(4):e1001378.
Non-Hodgkin lymphoma (NHL) represents a diverse group of hematological malignancies, of which follicular lymphoma (FL) is a prevalent subtype. A previous genome-wide association study has established a marker, rs10484561 in the human leukocyte antigen (HLA) class II region on 6p21.32 associated with increased FL risk. Here, in a three-stage genome-wide association study, starting with a genome-wide scan of 379 FL cases and 791 controls followed by validation in 1,049 cases and 5,790 controls, we identified a second independent FL–associated locus on 6p21.32, rs2647012 (ORcombined = 0.64, Pcombined = 2×10−21) located 962 bp away from rs10484561 (r2<0.1 in controls). After mutual adjustment, the associations at the two SNPs remained genome-wide significant (rs2647012:ORadjusted = 0.70, Padjusted = 4×10−12; rs10484561:ORadjusted = 1.64, Padjusted = 5×10−15). Haplotype and coalescence analyses indicated that rs2647012 arose on an evolutionarily distinct haplotype from that of rs10484561 and tags a novel allele with an opposite (protective) effect on FL risk. Moreover, in a follow-up analysis of the top 6 FL–associated SNPs in 4,449 cases of other NHL subtypes, rs10484561 was associated with risk of diffuse large B-cell lymphoma (ORcombined = 1.36, Pcombined = 1.4×10−7). Our results reveal the presence of allelic heterogeneity within the HLA class II region influencing FL susceptibility and indicate a possible shared genetic etiology with diffuse large B-cell lymphoma. These findings suggest that the HLA class II region plays a complex yet important role in NHL.
Author Summary
Earlier studies have established a marker rs10484561, in the HLA class II region on 6p21.32, associated with increased follicular lymphoma (FL) risk. Here, in a three-stage genome-wide association study of 1,428 FL cases and 6,581 controls, we identified a second independent FL–associated marker on 6p21.32, rs2647012, located 962 bp away from rs10484561. The associations at two SNPs remained genome-wide significant after mutual adjustment. Haplotype and coalescence analyses indicated that rs2647012 arose on an evolutionarily distinct lineage from that of rs10484561 and tags a novel allele with an opposite, protective effect on FL risk. Moreover, in an analysis of the top 6 FL–associated SNPs in 4,449 cases of other NHL subtypes, rs10484561 was associated with risk of diffuse large B-cell lymphoma. Our results reveal the presence of allelic heterogeneity at 6p21.32 in FL risk and suggest a shared genetic etiology with the common diffuse large B-cell lymphoma subtype.
doi:10.1371/journal.pgen.1001378
PMCID: PMC3080853  PMID: 21533074
11.  Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32 
Nature genetics  2010;42(8):661-664.
To identify susceptibility loci for non-Hodgkin lymphoma (NHL) subtypes, we conducted a three-stage genome-wide association study. We identified two variants associated with follicular lymphoma (FL) in 1,465 FL cases/6,958 controls at 6p21.32 (rs10484561, rs7755224, r2=1.0; combined p-values=1.12×10-29, 2.00×10-19), providing further support that MHC genetic variation influences FL susceptibility. Confirmatory evidence of a previously reported association was also found between chronic lymphocytic leukemia/small lymphocytic lymphoma and rs735665 (combined p-value=4.24×10-9).
doi:10.1038/ng.626
PMCID: PMC2913472  PMID: 20639881
12.  Genetic variation of ESR1 and its co-activator PPARGC1B is synergistic in augmenting the risk of estrogen receptor-positive breast cancer 
Introduction
Given the role of estrogen in breast carcinogenesis and the modification of estrogen receptor (ER) activity by its biochemical cofactors, we hypothesize that genetic variation within ER cofactor genes alters cellular response to estrogen exposure and consequently modifies the risk for ER-positive breast cancer.
Methods
We genotyped 790 tagging SNPs within 60 ER cofactor genes in 1,257 cases and 1,464 controls from Sweden and in 2,215 cases and 1,265 controls from Finland, and tested their associations with either ER-positive or ER-negative breast cancer.
Results
Seven SNPs showed consistent association with ER-positive breast cancer in the two independent samples, and six of them were located within PPARGC1B, encoding an ER co-activator, with the strongest association at rs741581 (odds ratio = 1.41, P = 4.84 × 10-5) that survived Bonferroni correction for multiple testing in the combined ER-positive breast cancer sample (Pcorrected = 0.03). Moreover, we also observed significant synergistic interaction (Pinteraction = 0.008) between the genetic polymorphisms within PPARGC1B and ESR1 in ER-positive breast cancer. By contrast, no consistent association was observed in ER-negative breast cancer. Furthermore, we found that administration of estrogen in the MCF-7 cell line induced PPARGC1B expression and enhanced occupancies of ER and RNA polymerase II within the region of SNP association, suggesting the upregulation of PPARGC1B expression by ESR1 activation.
Conclusions
Our study revealed that DNA polymorphisms of PPARGC1B, coding a bona fide ER co-activator, are associated with ER-positive breast cancer risk. The feed-forward transcriptional regulatory loop between PPARGC1B and ESR1 further augments their protein interaction, which provides a plausible mechanistic explanation for the synergistic genetic interaction between PPARGC1B and ESR1 in ER-positive breast cancer. Our study also highlights that biochemically and genomically informed candidate gene studies can enhance the discovery of interactive disease susceptibility genes.
doi:10.1186/bcr2817
PMCID: PMC3109578  PMID: 21269472
13.  A genome-wide association scan on estrogen receptor-negative breast cancer 
Introduction
Breast cancer is a heterogeneous disease and may be characterized on the basis of whether estrogen receptors (ER) are expressed in the tumour cells. ER status of breast cancer is important clinically, and is used both as a prognostic indicator and treatment predictor. In this study, we focused on identifying genetic markers associated with ER-negative breast cancer risk.
Methods
We conducted a genome-wide association analysis of 285,984 single nucleotide polymorphisms (SNPs) genotyped in 617 ER-negative breast cancer cases and 4,583 controls. We also conducted a genome-wide pathway analysis on the discovery dataset using permutation-based tests on pre-defined pathways. The extent of shared polygenic variation between ER-negative and ER-positive breast cancers was assessed by relating risk scores, derived using ER-positive breast cancer samples, to disease state in independent, ER-negative breast cancer cases.
Results
Association with ER-negative breast cancer was not validated for any of the five most strongly associated SNPs followed up in independent studies (1,011 ER-negative breast cancer cases, 7,604 controls). However, an excess of small P-values for SNPs with known regulatory functions in cancer-related pathways was found (global P = 0.052). We found no evidence to suggest that ER-negative breast cancer shares a polygenic basis to disease with ER-positive breast cancer.
Conclusions
ER-negative breast cancer is a distinct breast cancer subtype that merits independent analyses. Given the clinical importance of this phenotype and the likelihood that genetic effect sizes are small, greater sample sizes and further studies are required to understand the etiology of ER-negative breast cancers.
doi:10.1186/bcr2772
PMCID: PMC3046434  PMID: 21062454
14.  Multi-Variant Pathway Association Analysis Reveals the Importance of Genetic Determinants of Estrogen Metabolism in Breast and Endometrial Cancer Susceptibility 
PLoS Genetics  2010;6(7):e1001012.
Despite the central role of estrogen exposure in breast and endometrial cancer development and numerous studies of genes in the estrogen metabolic pathway, polymorphisms within the pathway have not been consistently associated with these cancers. We posit that this is due to the complexity of multiple weak genetic effects within the metabolic pathway that can only be effectively detected through multi-variant analysis. We conducted a comprehensive association analysis of the estrogen metabolic pathway by interrogating 239 tagSNPs within 35 genes of the pathway in three tumor samples. The discovery sample consisted of 1,596 breast cancer cases, 719 endometrial cancer cases, and 1,730 controls from Sweden; and the validation sample included 2,245 breast cancer cases and 1,287 controls from Finland. We performed admixture maximum likelihood (AML)–based global tests to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three sub-pathways for androgen synthesis, androgen-to-estrogen conversion, and estrogen removal. In the discovery sample, although no single polymorphism was significant after correction for multiple testing, the pathway-based AML global test suggested association with both breast (pglobal = 0.034) and endometrial (pglobal = 0.052) cancers. Further testing revealed the association to be focused on polymorphisms within the androgen-to-estrogen conversion sub-pathway, for both breast (pglobal = 0.008) and endometrial cancer (pglobal = 0.014). The sub-pathway association was validated in the Finnish sample of breast cancer (pglobal = 0.015). Further tumor subtype analysis demonstrated that the association of the androgen-to-estrogen conversion sub-pathway was confined to postmenopausal women with sporadic estrogen receptor positive tumors (pglobal = 0.0003). Gene-based AML analysis suggested CYP19A1 and UGT2B4 to be the major players within the sub-pathway. Our study indicates that the composite genetic determinants related to the androgen–estrogen conversion are important for the induction of two hormone-associated cancers, particularly for the hormone-driven breast tumour subtypes.
Author Summary
Estrogen exposure is the most important risk factor for breast and endometrial cancers. Genetic variation of the genes involved in estrogen metabolism has, however, not been consistently associated with these two cancers. We posited that the genetic risk associated with the estrogen metabolic genes is likely to be carried by multiple variants and is therefore most effectively detected by multi-variant analysis. We carried out a comprehensive association analysis of the estrogen metabolic pathway by interrogating SNPs within 35 genes of the pathway in three tumor samples from Sweden and Finland. Through pathway-based multi-variant association analysis, we showed that the genetic variation within the estrogen metabolic pathway is associated with risk for breast and endometrial cancers and that the genetic variation within the genes involved in androgen-to-estrogen conversion is particularly important for the development of ER–positive and sporadic breast tumors in postmenopausal women. Our study has demonstrated that the influence of genetic variation on hormone exposure has an impact on breast cancer development, especially on the development of hormone-driven breast tumor subtypes. Our study has also highlighted that future genetic studies of the estrogen metabolic genes should focus on the androgen-to-estrogen conversion process.
doi:10.1371/journal.pgen.1001012
PMCID: PMC2895650  PMID: 20617168
15.  ESR1 and EGF genetic variation in relation to breast cancer risk and survival 
Introduction
Oestrogen exposure is a central factor in the development of breast cancer. Oestrogen receptor alpha (ESR1) is the main mediator of oestrogen effect in breast epithelia and has also been shown to be activated by epidermal growth factor (EGF). We sought to determine if common genetic variation in the ESR1 and EGF genes affects breast cancer risk, tumour characteristics or breast cancer survival.
Methods
We genotyped 157 single nucleotide polymorphisms (SNPs) in ESR1 and 54 SNPs in EGF in 92 Swedish controls and selected haplotype tagging SNPs (tagSNPs) that could predict both single SNP and haplotype variation in the genes with an R2 of at least 0.8. The tagSNPs were genotyped in 1,590 breast cancer cases and 1,518 controls, and their association with breast cancer risk, tumour characteristics and survival were assessed using unconditional logistic regression models, Cox proportional hazard models and haplotype analysis.
Results
The single tagSNP analysis did not reveal association evidence for breast cancer risk, tumour characteristics, or survival. A multi-locus analysis of five adjacent tagSNPs suggested a region in ESR1 (between rs3003925 and rs2144025) for association with breast cancer risk (p = 0.001), but the result did not withstand adjustment for multiple comparisons (p = 0.086). A similar region was also implicated by haplotype analyses, but its significance needs to be verified by follow-up analysis.
Conclusion
Our results do not support a strong association between common variants in the ESR1 and EGF genes and breast cancer risk, tumour characteristics or survival.
doi:10.1186/bcr1861
PMCID: PMC2374971  PMID: 18271972

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