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Sung H, Garcia-Closas M, Chang-Claude J, Blows FM, Ali HR, Figueroa J, Nevanlinna H, Fagerholm R, Heikkilä P, Blomqvist C, Giles GG, Milne RL, Southey MC, McLean C, Mannermaa A, Kosma VM, Kataja V, Sironen R, Couch FJ, Olson JE, Hallberg E, Olswold C, Cox A, Cross SS, Kraft P, Tamimi RM, Eliassen AH, Schmidt MK, Bolla MK, Wang Q, Easton D, Howat WJ, Coulson P, Pharoah PDP, Sherman ME, Yang XR. Heterogeneity of luminal breast cancer characterised by immunohistochemical expression of basal markers. Br J Cancer 2016; 114:298-304. [PMID: 26679376 PMCID: PMC4742579 DOI: 10.1038/bjc.2015.437] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 10/23/2015] [Accepted: 11/21/2015] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Luminal A breast cancer defined as hormone receptor positive and human epidermal growth factor receptor 2 (HER2) negative is known to be heterogeneous. Previous study showed that luminal A tumours with the expression of basal markers ((cytokeratin (CK) 5 or CK5/6) or epidermal growth factor receptor (EGFR)) were associated with poorer prognosis compared with those that stained negative for basal markers. Prompted by this study, we assessed whether tumour characteristics and risk factors differed by basal marker status within luminal A tumours. METHODS We pooled 5040 luminal A cases defined by immunohistochemistry (4490 basal-negative ((CK5 (or CK5/6))- and EGFR-) and 550 basal-positive ((CK5 (or CK5/6+)) or EGFR+)) from eight studies participating in the Breast Cancer Association Consortium. Case-case comparison was performed using unconditional logistic regression. RESULTS Tumour characteristics and risk factors did not vary significantly by the expression of basal markers, although results suggested that basal-positive luminal tumours tended to be smaller and node negative, and were more common in women with a positive family history and lower body mass index. CONCLUSIONS Most established breast cancer risk factors were similar in basal-positive and basal-negative luminal A tumours. The non-significant but suggestive differences in tumour features and family history warrant further investigations.
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MESH Headings
- Adult
- Age Factors
- Aged
- Biomarkers, Tumor/metabolism
- Body Mass Index
- Breast Neoplasms/metabolism
- Breast Neoplasms/pathology
- Carcinoma, Ductal, Breast/metabolism
- Carcinoma, Ductal, Breast/pathology
- Carcinoma, Lobular/metabolism
- Carcinoma, Lobular/pathology
- ErbB Receptors/metabolism
- Female
- Humans
- Immunohistochemistry
- Keratin-5/metabolism
- Keratin-6/metabolism
- Menarche
- Menopause
- Middle Aged
- Neoplasm Grading
- Neoplasm Staging
- Parity
- Prognosis
- Receptor, ErbB-2/metabolism
- Receptors, Estrogen/metabolism
- Receptors, Progesterone/metabolism
- Risk Factors
- Tumor Burden
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Meeks HD, Song H, Michailidou K, Bolla MK, Dennis J, Wang Q, Barrowdale D, Frost D, McGuffog L, Ellis S, Feng B, Buys SS, Hopper JL, Southey MC, Tesoriero A, James PA, Bruinsma F, Campbell IG, Broeks A, Schmidt MK, Hogervorst FBL, Beckman MW, Fasching PA, Fletcher O, Johnson N, Sawyer EJ, Riboli E, Banerjee S, Menon U, Tomlinson I, Burwinkel B, Hamann U, Marme F, Rudolph A, Janavicius R, Tihomirova L, Tung N, Garber J, Cramer D, Terry KL, Poole EM, Tworoger SS, Dorfling CM, van Rensburg EJ, Godwin AK, Guénel P, Truong T, Stoppa-Lyonnet D, Damiola F, Mazoyer S, Sinilnikova OM, Isaacs C, Maugard C, Bojesen SE, Flyger H, Gerdes AM, Hansen TVO, Jensen A, Kjaer SK, Hogdall C, Hogdall E, Pedersen IS, Thomassen M, Benitez J, González-Neira A, Osorio A, Hoya MDL, Segura PP, Diez O, Lazaro C, Brunet J, Anton-Culver H, Eunjung L, John EM, Neuhausen SL, Ding YC, Castillo D, Weitzel JN, Ganz PA, Nussbaum RL, Chan SB, Karlan BY, Lester J, Wu A, Gayther S, Ramus SJ, Sieh W, Whittermore AS, Monteiro ANA, Phelan CM, Terry MB, Piedmonte M, Offit K, Robson M, Levine D, Moysich KB, Cannioto R, Olson SH, Daly MB, Nathanson KL, Domchek SM, Lu KH, Liang D, Hildebrant MAT, Ness R, Modugno F, Pearce L, Goodman MT, Thompson PJ, Brenner H, Butterbach K, Meindl A, Hahnen E, Wappenschmidt B, Brauch H, Brüning T, Blomqvist C, Khan S, Nevanlinna H, Pelttari LM, Aittomäki K, Butzow R, Bogdanova NV, Dörk T, Lindblom A, Margolin S, Rantala J, Kosma VM, Mannermaa A, Lambrechts D, Neven P, Claes KBM, Maerken TV, Chang-Claude J, Flesch-Janys D, Heitz F, Varon-Mateeva R, Peterlongo P, Radice P, Viel A, Barile M, Peissel B, Manoukian S, Montagna M, Oliani C, Peixoto A, Teixeira MR, Collavoli A, Hallberg E, Olson JE, Goode EL, Hart SN, Shimelis H, Cunningham JM, Giles GG, Milne RL, Healey S, Tucker K, Haiman CA, Henderson BE, Goldberg MS, Tischkowitz M, Simard J, Soucy P, Eccles DM, Le N, Borresen-Dale AL, Kristensen V, Salvesen HB, Bjorge L, Bandera EV, Risch H, Zheng W, Beeghly-Fadiel A, Cai H, Pylkäs K, Tollenaar RAEM, Ouweland AMWVD, Andrulis IL, Knight JA, Narod S, Devilee P, Winqvist R, Figueroa J, Greene MH, Mai PL, Loud JT, García-Closas M, Schoemaker MJ, Czene K, Darabi H, McNeish I, Siddiquil N, Glasspool R, Kwong A, Park SK, Teo SH, Yoon SY, Matsuo K, Hosono S, Woo YL, Gao YT, Foretova L, Singer CF, Rappaport-Feurhauser C, Friedman E, Laitman Y, Rennert G, Imyanitov EN, Hulick PJ, Olopade OI, Senter L, Olah E, Doherty JA, Schildkraut J, Koppert LB, Kiemeney LA, Massuger LFAG, Cook LS, Pejovic T, Li J, Borg A, Öfverholm A, Rossing MA, Wentzensen N, Henriksson K, Cox A, Cross SS, Pasini BJ, Shah M, Kabisch M, Torres D, Jakubowska A, Lubinski J, Gronwald J, Agnarsson BA, Kupryjanczyk J, Moes-Sosnowska J, Fostira F, Konstantopoulou I, Slager S, Jones M, Antoniou AC, Berchuck A, Swerdlow A, Chenevix-Trench G, Dunning AM, Pharoah PDP, Hall P, Easton DF, Couch FJ, Spurdle AB, Goldgar DE. BRCA2 Polymorphic Stop Codon K3326X and the Risk of Breast, Prostate, and Ovarian Cancers. J Natl Cancer Inst 2016; 108:djv315. [PMID: 26586665 PMCID: PMC4907358 DOI: 10.1093/jnci/djv315] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 08/13/2015] [Accepted: 10/02/2015] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. METHODS Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. RESULTS The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10(-) (6)) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10(-3)). These associations were stronger for serous ovarian cancer and for estrogen receptor-negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10(-5) and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10(-5), respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. CONCLUSIONS Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations.
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Chen J, Ryu E, Hathcock M, Ballman K, Chia N, Olson JE, Nelson H. Impact of demographics on human gut microbial diversity in a US Midwest population. PeerJ 2016; 4:e1514. [PMID: 26839739 PMCID: PMC4734456 DOI: 10.7717/peerj.1514] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Accepted: 11/26/2015] [Indexed: 12/21/2022] Open
Abstract
The clinical utility of microbiome biomarkers depends on the reliable and reproducible nature of comparative results. Underappreciation of the variation associated with common demographic, health, and behavioral factors may confound associations of interest and generate false positives. Here, we present the Midwestern Reference Panel (MWRP), a resource for comparative gut microbiome studies conducted in the Midwestern United States. We analyzed the relationships between demographic and health behavior-related factors and the microbiota in this cohort, and estimated their effect sizes. Most variables investigated were associated with the gut microbiota. Specifically, body mass index (BMI), race, sex, and alcohol use were significantly associated with microbial β-diversity (P < 0.05, unweighted UniFrac). BMI, race and alcohol use were also significantly associated with microbial α-diversity (P < 0.05, species richness). Tobacco use showed a trend toward association with the microbiota (P < 0.1, unweighted UniFrac). The effect sizes of the associations, as quantified by adjusted R2 values based on unweighted UniFrac distances, were small (< 1% for all variables), indicating that these factors explain only a small percentage of overall microbiota variability. Nevertheless, the significant associations between these variables and the gut microbiota suggest that they could still be potential confounders in comparative studies and that controlling for these variables in study design, which is the main objective of the MWRP, is important for increasing reproducibility in comparative microbiome studies.
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Van Driest SL, Wells QS, Stallings S, Bush WS, Gordon A, Nickerson DA, Kim JH, Crosslin DR, Jarvik GP, Carrell DS, Ralston JD, Larson EB, Bielinski SJ, Olson JE, Ye Z, Kullo IJ, Abul-Husn NS, Scott SA, Bottinger E, Almoguera B, Connolly J, Chiavacci R, Hakonarson H, Rasmussen-Torvik LJ, Pan V, Persell SD, Smith M, Chisholm RL, Kitchner TE, He MM, Brilliant MH, Wallace JR, Doheny KF, Shoemaker MB, Li R, Manolio TA, Callis TE, Macaya D, Williams MS, Carey D, Kapplinger JD, Ackerman MJ, Ritchie MD, Denny JC, Roden DM. Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records. JAMA 2016; 315:47-57. [PMID: 26746457 PMCID: PMC4758131 DOI: 10.1001/jama.2015.17701] [Citation(s) in RCA: 131] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
IMPORTANCE Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants. OBJECTIVE To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014. EXPOSURES One or more variants designated as pathogenic in SCN5A or KCNH2. MAIN OUTCOMES AND MEASURES Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review. RESULTS Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, -10 milliseconds; 95% CI, -16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds. CONCLUSIONS AND RELEVANCE Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.
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Bardia A, Keenan TE, Ebbert JO, Lazovich D, Wang AH, Vierkant RA, Olson JE, Vachon CM, Limburg PJ, Anderson KE, Cerhan JR. Personalizing Aspirin Use for Targeted Breast Cancer Chemoprevention in Postmenopausal Women. Mayo Clin Proc 2016; 91:71-80. [PMID: 26678006 PMCID: PMC4807132 DOI: 10.1016/j.mayocp.2015.10.018] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Revised: 09/28/2015] [Accepted: 10/23/2015] [Indexed: 02/07/2023]
Abstract
OBJECTIVE To evaluate the association of aspirin and other nonsteroidal anti-inflammatory drugs with the incidence of postmenopausal breast cancer for risk subgroups defined by selected nonmodifiable or difficult to modify breast cancer risk factors in order to better understand the potential risk-benefit ratio for targeted chemoprevention. PATIENTS AND METHODS Postmenopausal women with no history of cancer on July 1, 1992 (N=26,580), were prospectively followed up through December 31, 2005, for breast cancer incidence (N=1581). Risk subgroups were defined on the basis of family history of breast cancer, age at menarche, age at menopause, parity/age at first live birth, personal history of benign breast disease, and body mass index. Hazard ratios (HRs) and 95% CIs adjusted for other breast cancer risk factors were estimated using Cox models. RESULTS Aspirin use was associated with a lower incidence of breast cancer for women with a family history of breast cancer (HR, 0.62 for 6 or more times per week vs never use; 95% CI, 0.41-0.93) and those with a personal history of benign breast disease (HR, 0.69; 95% CI, 0.50-0.95) but not for women in higher-risk subgroups for age at menarche, age at menopause, parity/age at first live birth, or body mass index. In contrast, inverse associations with aspirin use were observed in all lower-risk subgroups. Nonsteroidal anti-inflammatory drug use had no association with breast cancer incidence. CONCLUSION On the basis of their increased risk of breast cancer, postmenopausal women with a family history of breast cancer or a personal history of benign breast disease could potentially be targeted for aspirin chemoprevention studies. Future studies are needed to confirm these findings.
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Jamshidi M, Fagerholm R, Khan S, Aittomäki K, Czene K, Darabi H, Li J, Andrulis IL, Chang-Claude J, Devilee P, Fasching PA, Michailidou K, Bolla MK, Dennis J, Wang Q, Guo Q, Rhenius V, Cornelissen S, Rudolph A, Knight JA, Loehberg CR, Burwinkel B, Marme F, Hopper JL, Southey MC, Bojesen SE, Flyger H, Brenner H, Holleczek B, Margolin S, Mannermaa A, Kosma VM, Dyck LV, Nevelsteen I, Couch FJ, Olson JE, Giles GG, McLean C, Haiman CA, Henderson BE, Winqvist R, Pylkäs K, Tollenaar RA, García-Closas M, Figueroa J, Hooning MJ, Martens JW, Cox A, Cross SS, Simard J, Dunning AM, Easton DF, Pharoah PD, Hall P, Blomqvist C, Schmidt MK, Nevanlinna H. SNP-SNP interaction analysis of NF-κB signaling pathway on breast cancer survival. Oncotarget 2015; 6:37979-94. [PMID: 26317411 PMCID: PMC4741978 DOI: 10.18632/oncotarget.4991] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2015] [Accepted: 07/16/2015] [Indexed: 12/03/2022] Open
Abstract
In breast cancer, constitutive activation of NF-κB has been reported, however, the impact of genetic variation of the pathway on patient prognosis has been little studied. Furthermore, a combination of genetic variants, rather than single polymorphisms, may affect disease prognosis. Here, in an extensive dataset (n = 30,431) from the Breast Cancer Association Consortium, we investigated the association of 917 SNPs in 75 genes in the NF-κB pathway with breast cancer prognosis. We explored SNP-SNP interactions on survival using the likelihood-ratio test comparing multivariate Cox' regression models of SNP pairs without and with an interaction term. We found two interacting pairs associating with prognosis: patients simultaneously homozygous for the rare alleles of rs5996080 and rs7973914 had worse survival (HRinteraction 6.98, 95% CI=3.3-14.4, P=1.42E-07), and patients carrying at least one rare allele for rs17243893 and rs57890595 had better survival (HRinteraction 0.51, 95% CI=0.3-0.6, P = 2.19E-05). Based on in silico functional analyses and literature, we speculate that the rs5996080 and rs7973914 loci may affect the BAFFR and TNFR1/TNFR3 receptors and breast cancer survival, possibly by disturbing both the canonical and non-canonical NF-κB pathways or their dynamics, whereas, rs17243893-rs57890595 interaction on survival may be mediated through TRAF2-TRAIL-R4 interplay. These results warrant further validation and functional analyses.
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Zhang B, Shu XO, Delahanty RJ, Zeng C, Michailidou K, Bolla MK, Wang Q, Dennis J, Wen W, Long J, Li C, Dunning AM, Chang-Claude J, Shah M, Perkins BJ, Czene K, Darabi H, Eriksson M, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Lambrechts D, Neven P, Wildiers H, Floris G, Schmidt MK, Rookus MA, van den Hurk K, de Kort WLAM, Couch FJ, Olson JE, Hallberg E, Vachon C, Rudolph A, Seibold P, Flesch-Janys D, Peto J, Dos-Santos-Silva I, Fletcher O, Johnson N, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Li J, Humphreys K, Brand J, Guénel P, Truong T, Cordina-Duverger E, Menegaux F, Burwinkel B, Marme F, Yang R, Surowy H, Benitez J, Zamora MP, Perez JIA, Cox A, Cross SS, Reed MWR, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Chenevix-Trench G, Haiman CA, Henderson BE, Schumacher F, Marchand LL, Lindblom A, Margolin S, Hooning MJ, Martens JWM, Tilanus-Linthorst MMA, Collée JM, Hopper JL, Southey MC, Tsimiklis H, Apicella C, Slager S, Toland AE, Ambrosone CB, Yannoukakos D, Giles GG, Milne RL, McLean C, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Swerdlow AJ, Ashworth A, Orr N, Jones M, Figueroa J, Garcia-Closas M, Brinton L, Lissowska J, Dumont M, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Brauch H, Brüning T, Ko YD, Peterlongo P, Manoukian S, Bonanni B, Radice P, Bogdanova N, Antonenkova N, Dörk T, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Devilee P, Seynaeve C, Van Asperen CJ, Jakubowska A, Lubiński J, Jaworska-Bieniek K, Durda K, Hamann U, Torres D, Schmutzler RK, Neuhausen SL, Anton-Culver H, Kristensen VN, Grenaker Alnæs GI, Pierce BL, Kraft P, Peters U, Lindstrom S, Seminara D, Burgess S, Ahsan H, Whittemore AS, John EM, Gammon MD, Malone KE, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Ahmed S, Maranian M, Healey CS, González-Neira A, Pita G, Alonso MR, Álvarez N, Herrero D, Pharoah PDP, Simard J, Hall P, Hunter DJ, Easton DF, Zheng W. Height and Breast Cancer Risk: Evidence From Prospective Studies and Mendelian Randomization. J Natl Cancer Inst 2015; 107:djv219. [PMID: 26296642 PMCID: PMC4643630 DOI: 10.1093/jnci/djv219] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 02/03/2015] [Accepted: 07/15/2015] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear. METHODS We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients. RESULTS The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8). CONCLUSIONS Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer.
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Tolcher MC, Holbert MR, Weaver AL, McGree ME, Olson JE, El-Nashar SA, Famuyide AO, Brost BC. Predicting Cesarean Delivery After Induction of Labor Among Nulliparous Women at Term. Obstet Gynecol 2015; 126:1059-1068. [PMID: 26444107 PMCID: PMC4618703 DOI: 10.1097/aog.0000000000001083] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To identify independent risk factors for cesarean delivery after induction of labor and to develop a nomogram for predicting cesarean delivery among nulliparous women undergoing induction of labor at term. METHODS This is a retrospective cohort study including nulliparous women with singleton, term (37 0/7 weeks of gestation or greater), cephalic pregnancies undergoing induction of labor from July 1, 2006, through May 31, 2012, at a tertiary care academic center. Inductions were identified using International Classification of Diseases, 9th Revision codes. Demographic, delivery, and outcome data were abstracted manually from the medical record. Women with a contraindication to vaginal delivery (malpresentation, abnormal placentation, prior myomectomy) were excluded. Independent risk factors for cesarean delivery were identified using logistic regression. RESULTS During the study period, there were 785 nulliparous inductions that met study criteria; 231 (29.4%) underwent cesarean delivery. Independent risk factors associated with an increased risk of cesarean delivery included older maternal age, shorter maternal height, greater body mass index, greater weight gain during pregnancy, older gestational age, hypertension, diabetes mellitus, and initial cervical dilation less than 3 cm. A nomogram was constructed based on the final model with a bias-corrected c-index of 0.709 (95% confidence interval 0.671-0.750). CONCLUSION We identified independent risk factors that can be used to predict cesarean delivery among nulliparous women undergoing induction of labor at term. If validated in other populations, the nomogram could be useful for individualized counseling of women with a combination of identifiable antepartum risk factors. LEVEL OF EVIDENCE II.
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Guo X, Long J, Zeng C, Michailidou K, Ghoussaini M, Bolla MK, Wang Q, Milne RL, Shu XO, Cai Q, Beesley J, Kar SP, Andrulis IL, Anton-Culver H, Arndt V, Beckmann MW, Beeghly-Fadiel A, Benitez J, Blot W, Bogdanova N, Bojesen SE, Brauch H, Brenner H, Brinton L, Broeks A, Brüning T, Burwinkel B, Cai H, Canisius S, Chang-Claude J, Choi JY, Couch FJ, Cox A, Cross SS, Czene K, Darabi H, Devilee P, Droit A, Dörk T, Fasching PA, Fletcher O, Flyger H, Fostira F, Gaborieau V, García-Closas M, Giles GG, Grip M, Guénel P, Haiman CA, Hamann U, Hartman M, Hollestelle A, Hopper JL, Hsiung CN, Ito H, Jakubowska A, Johnson N, Kabisch M, Kang D, Khan S, Knight JA, Kosma VM, Lambrechts D, Le Marchand L, Li J, Lindblom A, Lophatananon A, Lubinski J, Mannermaa A, Manoukian S, Margolin S, Marme F, Matsuo K, McLean CA, Meindl A, Muir K, Neuhausen SL, Nevanlinna H, Nord S, Olson JE, Orr N, Peterlongo P, Putti TC, Rudolph A, Sangrajrang S, Sawyer EJ, Schmidt MK, Schmutzler RK, Shen CY, Shi J, Shrubsole MJ, Southey MC, Swerdlow A, Teo SH, Thienpont B, Toland AE, Tollenaar RAEM, Tomlinson IPM, Truong T, Tseng CC, van den Ouweland A, Wen W, Winqvist R, Wu A, Yip CH, Zamora MP, Zheng Y, Hall P, Pharoah PDP, Simard J, Chenevix-Trench G, Dunning AM, Easton DF, Zheng W. Fine-scale mapping of the 4q24 locus identifies two independent loci associated with breast cancer risk. Cancer Epidemiol Biomarkers Prev 2015; 24:1680-91. [PMID: 26354892 PMCID: PMC4633342 DOI: 10.1158/1055-9965.epi-15-0363] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2015] [Accepted: 07/20/2015] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. METHODS We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. RESULTS Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10(-4); OR, 1.04; 95% confidence interval (CI), 1.02-1.07] and rs77928427 (P = 1.86 × 10(-4); OR, 1.04; 95% CI, 1.02-1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r(2) ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. CONCLUSION Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. IMPACT Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk.
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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 JJ, Mangino M, Smith AV, Tanaka T, Abecasis G, 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 AL, Boutin TS, Brauch H, Brenner H, Brüning T, Burwinkel B, Campbell A, Campbell H, Chanock SJ, Chapman JR, Chen YDI, Chenevix-Trench G, Couch FJ, Coviello AD, Cox A, Czene K, Darabi H, De Vivo I, Demerath EW, Dennis J, Devilee P, Dörk T, dos-Santos-Silva I, Dunning AM, Eicher JD, Fasching PA, Faul JD, Figueroa J, Flesch-Janys D, Gandin I, Garcia ME, García-Closas M, Giles GG, Girotto GG, Goldberg MS, González-Neira A, Goodarzi MO, Grove ML, Gudbjartsson DF, Guénel 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 VM, Kriebel J, Kristensen V, Lambrechts D, Langenberg C, Li J, Li X, Lindström S, Liu Y, Luan J, Lubinski J, Mägi R, Mannermaa A, Manz J, Margolin S, Marten J, Martin NG, Masciullo C, Meindl A, Michailidou K, Mihailov E, Milani L, Milne RL, Müller-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 PD, Pirastu NN, Pirie A, Pistis G, Polasek O, Porteous D, Psaty BM, Pylkäs 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, Stöckl 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 BB, 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 SL, Kraft P, McKnight B, Metspalu A, Morrison AC, Reiner AP, Ridker PM, Rotter JI, Toniolo D, Uitterlinden AG, Ulivi S, Völzke H, Wareham NJ, Weir DR, Yerges-Armstrong LM, Price AL, Stefansson K, Visser JA, Ong KK, Chang-Claude J, Murabito JM, Perry JR, Murray A. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair. Nat Genet 2015; 47:1294-1303. [PMID: 26414677 PMCID: PMC4661791 DOI: 10.1038/ng.3412] [Citation(s) in RCA: 265] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Accepted: 09/02/2015] [Indexed: 02/02/2023]
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.
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Takahashi PY, Ryu E, Hathcock MA, Olson JE, Bielinski SJ, Cerhan JR, Rand-Weaver J, Juhn YJ. A novel housing-based socioeconomic measure predicts hospitalisation and multiple chronic conditions in a community population. J Epidemiol Community Health 2015; 70:286-91. [PMID: 26458399 DOI: 10.1136/jech-2015-205925] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2015] [Accepted: 09/27/2015] [Indexed: 11/04/2022]
Abstract
BACKGROUND Socioeconomic status (SES) is an important predictor for outcomes of chronic diseases. However, it is often unavailable in clinical data. We sought to determine whether an individual housing-based SES index termed HOUSES can influence the likelihood of multiple chronic conditions (MCC) and hospitalisation in a community population. METHODS Participants were residents of Olmsted County, Minnesota, aged >18 years, who were enrolled in Mayo Clinic Biobank on 31 December 2010, with follow-up until 31 December 2011. Primary outcome was all-cause hospitalisation over 1 calendar-year. Secondary outcome was MCC determined through a Minnesota Medical Tiering score. A logistic regression model was used to assess the association of HOUSES with the Minnesota tiering score. With adjustment for age, sex and MCC, the association of HOUSES with hospitalisation risk was tested using the Cox proportional hazards model. RESULTS Eligible patients totalled 6402 persons (median age, 57 years; 25th-75th quartiles, 45-68 years). The lowest quartile of HOUSES was associated with a higher Minnesota tiering score after adjustment for age and sex (OR (95% CI) 2.4 (2.0 to 3.1)) when compared with the highest HOUSES quartile. Patients in the lowest HOUSES quartile had higher risk of all-cause hospitalisation (age, sex, MCC-adjusted HR (95% CI) 1.53 (1.18 to 1.98)) compared with those in the highest quartile. CONCLUSIONS Low SES, as assessed by HOUSES, was associated with increased risk of hospitalisation and greater MCC health burden. HOUSES may be a clinically useful surrogate for SES to assess risk stratification for patient care and clinical research.
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Rudolph A, Fasching PA, Behrens S, Eilber U, Bolla MK, Wang Q, Thompson D, Czene K, Brand JS, Li J, Scott C, Pankratz VS, Brandt K, Hallberg E, Olson JE, Lee A, Beckmann MW, Ekici AB, Haeberle L, Maskarinec G, Le Marchand L, Schumacher F, Milne RL, Knight JA, Apicella C, Southey MC, Kapuscinski MK, Hopper JL, Andrulis IL, Giles GG, Haiman CA, Khaw KT, Luben R, Hall P, Pharoah PDP, Couch FJ, Easton DF, Dos-Santos-Silva I, Vachon C, Chang-Claude J. A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density. Breast Cancer Res 2015; 17:110. [PMID: 26275715 PMCID: PMC4537547 DOI: 10.1186/s13058-015-0625-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2015] [Accepted: 07/29/2015] [Indexed: 02/02/2023] Open
Abstract
INTRODUCTION Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. METHODS The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. RESULTS No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02). CONCLUSIONS The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.
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Kullo IJ, Jouni H, Olson JE, Montori VM, Bailey KR. Design of a randomized controlled trial of disclosing genomic risk of coronary heart disease: the Myocardial Infarction Genes (MI-GENES) study. BMC Med Genomics 2015; 8:51. [PMID: 26271327 PMCID: PMC4536729 DOI: 10.1186/s12920-015-0122-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2015] [Accepted: 07/15/2015] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Whether disclosure of a genetic risk score (GRS) for a common disease influences relevant clinical outcomes is unknown. We describe design of the Myocardial Infarction Genes (MI-GENES) Study, a randomized clinical trial to assess whether disclosing a GRS for coronary heart disease (CHD) leads to lowering of low-density lipoprotein cholesterol (LDL-C) levels. METHODS AND DESIGN We performed an initial screening genotyping of 28 CHD susceptibility single-nucleotide polymorphisms (SNPs) that are not associated with blood pressure or lipid levels, in 1000 individuals from Olmsted County, Minnesota who were participants in the Mayo Clinic BioBank and met eligibility criteria. We calculated GRS based on 28 SNPs and will enroll 110 patients each in two CHD genomic risk categories: high (GRS ≥1.1), and average/low (GRS <1.1). The study coordinator will obtain informed consent for the study that includes placing genetic testing results in the electronic health record. Participants will undergo a blood draw and return 6-10 weeks later (Visit 2) once genotyping is completed and a GRS calculated. At this visit, patients will be randomized (1:1) to receive CHD risk estimates from a genetic counselor based on a conventional risk score (CRS) vs. GRS, followed by shared decision making with a physician regarding statin use. Three and six months following the disclosure of CHD risk, participants will return for measurement of fasting lipid levels and assessment of changes in dietary fat intake and physical activity levels. Psychosocial measures will be assessed at baseline and after disclosure of CHD risk. DISCUSSION The proposed trial will provide insights into the clinical utility of genetic testing for CHD risk assessment. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov registration number: NCT01936675 .
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Takahashi PY, Ryu E, Olson JE, Winkler EM, Hathcock MA, Gupta R, Sloan JA, Pathak J, Bielinski SJ, Cerhan JR. Health behaviors and quality of life predictors for risk of hospitalization in an electronic health record-linked biobank. Int J Gen Med 2015; 8:247-54. [PMID: 26316799 PMCID: PMC4540136 DOI: 10.2147/ijgm.s85473] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background Hospital risk stratification models using electronic health records (EHRs) often use age and comorbid health burden. Our primary aim was to determine if quality of life or health behaviors captured in an EHR-linked biobank can predict future risk of hospitalization. Methods Participants in the Mayo Clinic Biobank completed self-administered questionnaires at enrollment that included quality of life and health behaviors. Participants enrolled as of December 31, 2010 were followed for one year to ascertain hospitalization. Data on comorbidities and hospitalization were derived from the Mayo Clinic EHR. Hazard ratios (HR) and 95% confidence interval (CI) were used, adjusted for age and sex. We used gradient boosting machines models to integrate multiple factors. Different models were compared using C-statistic. Results Of the 8,927 eligible Mayo Clinic Biobank participants, 834 (9.3%) were hospitalized. Self-perceived health status and alcohol use had the strongest associations with risk of hospitalization. Compared to participants with excellent self-perceived health, those reporting poor/fair health had higher risk of hospitalization (HR =3.66, 95% CI 2.74–4.88). Alcohol use was inversely associated with hospitalization (HR =0.57 95% CI 0.45–0.72). The gradient boosting machines model estimated self-perceived health as the most influential factor (relative influence =16%). The predictive ability of the model based on comorbidities was slightly higher than the one based on the self-perceived health (C-statistic =0.67 vs 0.65). Conclusion This study demonstrates that self-perceived health may be an important piece of information to add to the EHR. It may be another method to determine hospitalization risk.
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Middha S, Lindor NM, McDonnell SK, Olson JE, Johnson KJ, Wieben ED, Farrugia G, Cerhan JR, Thibodeau SN. How well do whole exome sequencing results correlate with medical findings? A study of 89 Mayo Clinic Biobank samples. Front Genet 2015; 6:244. [PMID: 26257771 PMCID: PMC4513238 DOI: 10.3389/fgene.2015.00244] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Accepted: 07/03/2015] [Indexed: 12/30/2022] Open
Abstract
Whole exome sequencing (WES) is increasingly being used for diagnosis without adequate information on predictive characteristics of reportable variants typically found on any given individual and correlation with clinical phenotype. In this study, we performed WES on 89 deceased individuals (mean age at death 74 years, range 28-93) from the Mayo Clinic Biobank. Significant clinical diagnoses were abstracted from electronic medical record via chart review. Variants [Single Nucleotide Variant (SNV) and insertion/deletion] were filtered based on quality (accuracy >99%, read-depth >20, alternate-allele read-depth >5, minor-allele-frequency <0.1) and available HGMD/OMIM phenotype information. Variants were defined as Tier-1 (nonsense, splice or frame-shifting) and Tier-2 (missense, predicted-damaging) and evaluated in 56 ACMG-reportable genes, 57 cancer-predisposition genes, along with examining overall genotype-phenotype correlations. Following variant filtering, 7046 total variants were identified (~79/person, 644 Tier-1, 6402 Tier-2), 161 among 56 ACMG-reportable genes (~1.8/person, 13 Tier-1, 148 Tier-2), and 115 among 57 cancer-predisposition genes (~1.3/person, 3 Tier-1, 112 Tier-2). The number of variants across 57 cancer-predisposition genes did not differentiate individuals with/without invasive cancer history (P > 0.19). Evaluating genotype-phenotype correlations across the exome, 202(3%) of 7046 filtered variants had some evidence for phenotypic correlation in medical records, while 3710(53%) variants had no phenotypic correlation. The phenotype associated with the remaining 44% could not be assessed from a typical medical record review. These data highlight significant continued challenges in the ability to extract medically meaningful predictive results from WES.
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Bielinski SJ, Pathak J, Carrell DS, Takahashi PY, Olson JE, Larson NB, Liu H, Sohn S, Wells QS, Denny JC, Rasmussen-Torvik LJ, Pacheco JA, Jackson KL, Lesnick TG, Gullerud RE, Decker PA, Pereira NL, Ryu E, Dart RA, Peissig P, Linneman JG, Jarvik GP, Larson EB, Bock JA, Tromp GC, de Andrade M, Roger VL. A Robust e-Epidemiology Tool in Phenotyping Heart Failure with Differentiation for Preserved and Reduced Ejection Fraction: the Electronic Medical Records and Genomics (eMERGE) Network. J Cardiovasc Transl Res 2015. [PMID: 26195183 DOI: 10.1007/s12265-015-9644-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Identifying populations of heart failure (HF) patients is paramount to research efforts aimed at developing strategies to effectively reduce the burden of this disease. The use of electronic medical record (EMR) data for this purpose is challenging given the syndromic nature of HF and the need to distinguish HF with preserved or reduced ejection fraction. Using a gold standard cohort of manually abstracted cases, an EMR-driven phenotype algorithm based on structured and unstructured data was developed to identify all the cases. The resulting algorithm was executed in two cohorts from the Electronic Medical Records and Genomics (eMERGE) Network with a positive predictive value of >95 %. The algorithm was expanded to include three hierarchical definitions of HF (i.e., definite, probable, possible) based on the degree of confidence of the classification to capture HF cases in a whole population whereby increasing the algorithm utility for use in e-Epidemiologic research.
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Sobral-Leite M, Wesseling J, Smit VTHBM, Nevanlinna H, van Miltenburg MH, Sanders J, Hofland I, Blows FM, Coulson P, Patrycja G, Schellens JHM, Fagerholm R, Heikkilä P, Aittomäki K, Blomqvist C, Provenzano E, Ali HR, Figueroa J, Sherman M, Lissowska J, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Phillips KA, Couch FJ, Olson JE, Vachon C, Visscher D, Brenner H, Butterbach K, Arndt V, Holleczek B, Hooning MJ, Hollestelle A, Martens JWM, van Deurzen CHM, van de Water B, Broeks A, Chang-Claude J, Chenevix-Trench G, Easton DF, Pharoah PDP, García-Closas M, de Graauw M, Schmidt MK. Annexin A1 expression in a pooled breast cancer series: association with tumor subtypes and prognosis. BMC Med 2015; 13:156. [PMID: 26137966 PMCID: PMC4489114 DOI: 10.1186/s12916-015-0392-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 06/04/2015] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Annexin A1 (ANXA1) is a protein related with the carcinogenesis process and metastasis formation in many tumors. However, little is known about the prognostic value of ANXA1 in breast cancer. The purpose of this study is to evaluate the association between ANXA1 expression, BRCA1/2 germline carriership, specific tumor subtypes and survival in breast cancer patients. METHODS Clinical-pathological information and follow-up data were collected from nine breast cancer studies from the Breast Cancer Association Consortium (BCAC) (n = 5,752) and from one study of familial breast cancer patients with BRCA1/2 mutations (n = 107). ANXA1 expression was scored based on the percentage of immunohistochemical staining in tumor cells. Survival analyses were performed using a multivariable Cox model. RESULTS The frequency of ANXA1 positive tumors was higher in familial breast cancer patients with BRCA1/2 mutations than in BCAC patients, with 48.6 % versus 12.4 %, respectively; P <0.0001. ANXA1 was also highly expressed in BCAC tumors that were poorly differentiated, triple negative, EGFR-CK5/6 positive or had developed in patients at a young age. In the first 5 years of follow-up, patients with ANXA1 positive tumors had a worse breast cancer-specific survival (BCSS) than ANXA1 negative (HRadj = 1.35; 95 % CI = 1.05-1.73), but the association weakened after 10 years (HRadj = 1.13; 95 % CI = 0.91-1.40). ANXA1 was a significant independent predictor of survival in HER2+ patients (10-years BCSS: HRadj = 1.70; 95 % CI = 1.17-2.45). CONCLUSIONS ANXA1 is overexpressed in familial breast cancer patients with BRCA1/2 mutations and correlated with poor prognosis features: triple negative and poorly differentiated tumors. ANXA1 might be a biomarker candidate for breast cancer survival prediction in high risk groups such as HER2+ cases.
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Stone J, Thompson DJ, Dos Santos Silva I, Scott C, Tamimi RM, Lindstrom S, Kraft P, Hazra A, Li J, Eriksson L, Czene K, Hall P, Jensen M, Cunningham J, Olson JE, Purrington K, Couch FJ, Brown J, Leyland J, Warren RML, Luben RN, Khaw KT, Smith P, Wareham NJ, Jud SM, Heusinger K, Beckmann MW, Douglas JA, Shah KP, Chan HP, Helvie MA, Le Marchand L, Kolonel LN, Woolcott C, Maskarinec G, Haiman C, Giles GG, Baglietto L, Krishnan K, Southey MC, Apicella C, Andrulis IL, Knight JA, Ursin G, Alnaes GIG, Kristensen VN, Borresen-Dale AL, Gram IT, Bolla MK, Wang Q, Michailidou K, Dennis J, Simard J, Pharoah P, Dunning AM, Easton DF, Fasching PA, Pankratz VS, Hopper JL, Vachon CM. Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures. Cancer Res 2015; 75:2457-67. [PMID: 25862352 PMCID: PMC4470785 DOI: 10.1158/0008-5472.can-14-2012] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2014] [Accepted: 03/10/2015] [Indexed: 12/30/2022]
Abstract
Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.
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Ferzoco RM, Hallberg EJ, Vivek S, Cogswell JA, Hinton JL, Marshman PJ, Olswold CL, Goetz MP, Slager SL, Olson JE, Couch FJ, Ruddy KJ. Real-world self-reported adherence to endocrine therapy in a large longitudinal cohort of breast cancer patients. J Clin Oncol 2015. [DOI: 10.1200/jco.2015.33.15_suppl.e20630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Orr N, Dudbridge F, Dryden N, Maguire S, Novo D, Perrakis E, Johnson N, Ghoussaini M, Hopper JL, Southey MC, Apicella C, Stone J, Schmidt MK, Broeks A, Van't Veer LJ, Hogervorst FB, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Gibson L, Aitken Z, Warren H, Sawyer E, Tomlinson I, Kerin MJ, Miller N, Burwinkel B, Marme F, Schneeweiss A, Sohn C, Guénel P, Truong T, Cordina-Duverger E, Sanchez M, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Benitez J, Zamora MP, Arias Perez JI, Menéndez P, Anton-Culver H, Neuhausen SL, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Hamann U, Brauch H, Justenhoven C, Brüning T, Ko YD, Nevanlinna H, Aittomäki K, Blomqvist C, Khan S, Bogdanova N, Dörk T, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Chenevix-Trench G, Beesley J, Lambrechts D, Moisse M, Floris G, Beuselinck B, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Radice P, Peterlongo P, Peissel B, Pensotti V, Couch FJ, Olson JE, Slettedahl S, Vachon C, Giles GG, Milne RL, McLean C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Kristensen V, Alnæs GG, Nord S, Borresen-Dale AL, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Devilee P, Tollenaar RAEM, Seynaeve CM, Van Asperen CJ, Garcia-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Darabi H, Eriksson M, Klevebring D, Hooning MJ, Hollestelle A, van Deurzen CHM, Kriege M, Hall P, Li J, Liu J, Humphreys K, Cox A, Cross SS, Reed MWR, Pharoah PDP, Dunning AM, Shah M, Perkins BJ, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Ashworth A, Swerdlow A, Jones M, Schoemaker MJ, Meindl A, Schmutzler RK, Olswold C, Slager S, Toland AE, Yannoukakos D, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Matsuo K, Ito H, Iwata H, Ishiguro J, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Teo SH, Yip CH, Kang P, Ikram MK, Shu XO, Lu W, Gao YT, Cai H, Kang D, Choi JY, Park SK, Noh DY, Hartman M, Miao H, Lim WY, Lee SC, Sangrajrang S, Gaborieau V, Brennan P, Mckay J, Wu PE, Hou MF, Yu JC, Shen CY, Blot W, Cai Q, Signorello LB, Luccarini C, Bayes C, Ahmed S, Maranian M, Healey CS, González-Neira A, Pita G, Alonso MR, Álvarez N, Herrero D, Tessier DC, Vincent D, Bacot F, Hunter DJ, Lindstrom S, Dennis J, Michailidou K, Bolla MK, Easton DF, dos Santos Silva I, Fletcher O, Peto J. Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2. Hum Mol Genet 2015; 24:2966-84. [PMID: 25652398 PMCID: PMC4406292 DOI: 10.1093/hmg/ddv035] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2014] [Accepted: 01/30/2015] [Indexed: 11/13/2022] Open
Abstract
We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.
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Couch FJ, Hart SN, Sharma P, Ewart Toland A, Miron P, Olson JE, Godwin A, Pankratz VS, Olswold C, Slettedahl S, Guidugli L, Beckmann MW, Rack B, Ekici AB, Konstantopoulou I, Fostira F, Fountzilas G, Pelttari LM, Yao S, Garber J, Cox A, Brauch H, Ambrosone C, Nevanlinna H, Yannoukakos D, Slager SL, Vachon CM, Eccles DM, Fasching PA. Abstract P4-12-03: Triple-negative breast cancer: Frequency of inherited mutations in breast cancer susceptibility genes. Cancer Res 2015. [DOI: 10.1158/1538-7445.sabcs14-p4-12-03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Guidelines recommend germline mutation testing of breast cancer predisposition genes in triple negative (TN) breast cancer cases with a family history of breast or ovarian cancer or when diagnosed under age 60. However, the prevalence of mutations in these genes among TN cases unselected for family history of breast or ovarian cancer is not known.
Methods: To assess the frequency of mutations in 16 predisposition genes in TN cases we screened a large cohort of TN patients (n=1824) unselected for family history of breast or ovarian cancer from 12 centers and 824 study matched unaffected controls for mutations using a panel-based sequencing approach.
Results: Deleterious mutations were identified in 15% of TN patients: 8.5% had BRCA1, 2.7% had BRCA2, and 3.6% had mutations in 12 other genes. Mutations in non-BRCA1/2 genes encoding proteins implicated in homologous recombination repair of DNA double strand breaks were detected at the same frequency as in breast cancer families. TN cases with mutations had high-grade tumors and were diagnosed at an earlier age than non-mutated cases. However, 10% of TN cases diagnosed at ≥60 years and 5% with no family history of cancer were also found to carry mutations. Inactivating mutations in non-BRCA1/2 predisposition genes were associated with moderate to high risks of TN breast cancer.
Conclusions: National Comprehensive Cancer Network (NCCN) guidelines support clinical genetic testing of breast cancer predisposition genes in 95% of TN breast cancer patients carrying mutations in susceptibility genes. In contrast, National Institute of Health and Care Excellence (NICE) guidelines in the U.K. do not support genetic testing of a substantial proportion of TN patients with predisposing alleles. Frequency tables for inherited mutations in known predisposition genes based on age of diagnosis and family history of cancer will allow for selection of TN patients most likely to carry mutations in the predisposition genes.
Citation Format: Fergus J Couch, Steven N Hart, Priyanka Sharma, Amanda Ewart Toland, Penelope Miron, Janet E Olson, Andrew Godwin, Vernon S Pankratz, Curtis Olswold, Seth Slettedahl, Lucia Guidugli, Matthias W Beckmann, Brigitte Rack, Arif B Ekici, Irene Konstantopoulou, Florentia Fostira, George Fountzilas, Liisa M Pelttari, Song Yao, Judy Garber, Angela Cox, Hiltrud Brauch, Christine Ambrosone, Heli Nevanlinna, Drakoulis Yannoukakos, Susan L Slager, Celine M Vachon, Diana M Eccles, Peter A Fasching. Triple-negative breast cancer: Frequency of inherited mutations in breast cancer susceptibility genes [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-12-03.
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Guo Q, Schmidt MK, Kraft P, Canisius S, Chen C, Khan S, Tyrer J, Bolla MK, Wang Q, Dennis J, Michailidou K, Lush M, Kar S, Beesley J, Dunning AM, Shah M, Czene K, Darabi H, Eriksson M, Lambrechts D, Weltens C, Leunen K, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Blomqvist C, Aittomäki K, Fagerholm R, Muranen TA, Couch FJ, Olson JE, Vachon C, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Broeks A, Hogervorst FB, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Hopper JL, Tsimiklis H, Apicella C, Southey MC, Cox A, Cross SS, Reed MWR, Giles GG, Milne RL, McLean C, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Hooning MJ, Hollestelle A, Martens JWM, van den Ouweland AMW, Marme F, Schneeweiss A, Yang R, Burwinkel B, Figueroa J, Chanock SJ, Lissowska J, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Brenner H, Dieffenbach AK, Arndt V, Holleczek B, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Li J, Brand JS, Humphreys K, Devilee P, Tollenaar RAEM, Seynaeve C, Radice P, Peterlongo P, Bonanni B, Mariani P, Fasching PA, Beckmann MW, Hein A, Ekici AB, Chenevix-Trench G, Balleine R, Phillips KA, Benitez J, Zamora MP, Arias Perez JI, Menéndez P, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Hamann U, Kabisch M, Ulmer HU, Rüdiger T, Margolin S, Kristensen V, Nord S, Evans DG, Abraham JE, Earl HM, Hiller L, Dunn JA, Bowden S, Berg C, Campa D, Diver WR, Gapstur SM, Gaudet MM, Hankinson SE, Hoover RN, Hüsing A, Kaaks R, Machiela MJ, Willett W, Barrdahl M, Canzian F, Chin SF, Caldas C, Hunter DJ, Lindstrom S, García-Closas M, Hall P, Easton DF, Eccles DM, Rahman N, Nevanlinna H, Pharoah PDP. Identification of novel genetic markers of breast cancer survival. J Natl Cancer Inst 2015; 107:djv081. [PMID: 25890600 PMCID: PMC4555642 DOI: 10.1093/jnci/djv081] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2014] [Revised: 12/20/2014] [Accepted: 02/26/2015] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival. METHODS We conducted a large meta-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided. RESULTS We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust. CONCLUSIONS This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.
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Vachon CM, Pankratz VS, Scott CG, Haeberle L, Ziv E, Jensen MR, Brandt KR, Whaley DH, Olson JE, Heusinger K, Hack CC, Jud SM, Beckmann MW, Schulz-Wendtland R, Tice JA, Norman AD, Cunningham JM, Purrington KS, Easton DF, Sellers TA, Kerlikowske K, Fasching PA, Couch FJ. The contributions of breast density and common genetic variation to breast cancer risk. J Natl Cancer Inst 2015; 107:dju397. [PMID: 25745020 PMCID: PMC4598340 DOI: 10.1093/jnci/dju397] [Citation(s) in RCA: 144] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2014] [Revised: 07/18/2014] [Accepted: 10/27/2014] [Indexed: 01/18/2023] Open
Abstract
We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population.
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Mavaddat N, Pharoah PDP, Michailidou K, Tyrer J, Brook MN, Bolla MK, Wang Q, Dennis J, Dunning AM, Shah M, Luben R, Brown J, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Czene K, Darabi H, Eriksson M, Peto J, Dos-Santos-Silva I, Dudbridge F, Johnson N, Schmidt MK, Broeks A, Verhoef S, Rutgers EJ, Swerdlow A, Ashworth A, Orr N, Schoemaker MJ, Figueroa J, Chanock SJ, Brinton L, Lissowska J, Couch FJ, Olson JE, Vachon C, Pankratz VS, Lambrechts D, Wildiers H, Van Ongeval C, van Limbergen E, Kristensen V, Grenaker Alnæs G, Nord S, Borresen-Dale AL, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Burwinkel B, Marme F, Schneeweiss A, Sohn C, Trentham-Dietz A, Newcomb P, Titus L, Egan KM, Hunter DJ, Lindstrom S, Tamimi RM, Kraft P, Rahman N, Turnbull C, Renwick A, Seal S, Li J, Liu J, Humphreys K, Benitez J, Pilar Zamora M, Arias Perez JI, Menéndez P, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Bogdanova NV, Antonenkova NN, Dörk T, Anton-Culver H, Neuhausen SL, Ziogas A, Bernstein L, Devilee P, Tollenaar RAEM, Seynaeve C, van Asperen CJ, Cox A, Cross SS, Reed MWR, Khusnutdinova E, Bermisheva M, Prokofyeva D, Takhirova Z, Meindl A, Schmutzler RK, Sutter C, Yang R, Schürmann P, Bremer M, Christiansen H, Park-Simon TW, Hillemanns P, Guénel P, Truong T, Menegaux F, Sanchez M, Radice P, Peterlongo P, Manoukian S, Pensotti V, Hopper JL, Tsimiklis H, Apicella C, Southey MC, Brauch H, Brüning T, Ko YD, Sigurdson AJ, Doody MM, Hamann U, Torres D, Ulmer HU, Försti A, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Andrulis IL, Knight JA, Glendon G, Marie Mulligan A, Chenevix-Trench G, Balleine R, Giles GG, Milne RL, McLean C, Lindblom A, Margolin S, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Eilber U, Wang-Gohrke S, Hooning MJ, Hollestelle A, van den Ouweland AMW, Koppert LB, Carpenter J, Clarke C, Scott R, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Brenner H, Arndt V, Stegmaier C, Karina Dieffenbach A, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Offit K, Vijai J, Robson M, Rau-Murthy R, Dwek M, Swann R, Annie Perkins K, Goldberg MS, Labrèche F, Dumont M, Eccles DM, Tapper WJ, Rafiq S, John EM, Whittemore AS, Slager S, Yannoukakos D, Toland AE, Yao S, Zheng W, Halverson SL, González-Neira A, Pita G, Rosario Alonso M, Álvarez N, Herrero D, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Ahmed S, Maranian M, Healey CS, Simard J, Hall P, Easton DF, Garcia-Closas M. Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 2015; 107:djv036. [PMID: 25855707 PMCID: PMC4754625 DOI: 10.1093/jnci/djv036] [Citation(s) in RCA: 361] [Impact Index Per Article: 40.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Revised: 12/01/2014] [Accepted: 01/26/2015] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
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Wolfe JW, Engelken EJ, Olson JE. Low-frequency harmonic acceleration in the evaluation of surgical treatment of Meniere's disease. Adv Otorhinolaryngol 2015; 25:192-6. [PMID: 484351 DOI: 10.1159/000402941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
23 patients with classical findings of Meniere's disease and so diagnosed by a neurotologist were tested with harmonic acceleration. 7 of these patients were selected to receive endolymphatic-mastoid shunts for intractable vertigo and/or highly progressive fluctuant hearing loss. All 7 patients showed an increase in the impairment in their phase relationships at the lowest frequency (0.01Hz) following surgery which was considered to be secondary to the procedure. Later this phase lag returned to a level approaching normal. They also showed a definite decrease in the asymmetry (labyrinthine preponderance) of their nystagmic responses to acceleration.
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