224 results on '"Coetzee, GA"'
Search Results
2. Novel Common Genetic Susceptibility Loci for Colorectal Cancer
- Author
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Schmit, SL, Edlund, CK, Schumacher, FR, Gong, J, Harrison, TA, Huyghe, JR, Qu, C, Melas, M, Van den Berg, DJ, Wang, H, Tring, S, Plummer, SJ, Albanes, D, Alonso, MH, Amos, CI, Anton, K, Aragaki, AK, Arndt, V, Barry, EL, Berndt, SI, Bezieau, S, Bien, S, Bloomer, A, Boehm, J, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buchanan, DD, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castelao, JE, Chan, AT, Chang-Claude, J, Chanock, SJ, Cheng, I, Cheng, Y-W, Chin, LS, Church, JM, Church, T, Coetzee, GA, Cotterchio, M, Correa, MC, Curtis, KR, Duggan, D, Easton, DF, English, D, Feskens, EJM, Fischer, R, FitzGerald, LM, Fortini, BK, Fritsche, LG, Fuchs, CS, Gago-Dominguez, M, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Giovannucci, EL, Gogarten, SM, Gonzalez-Villalpando, C, Gonzalez-Villalpando, EM, Grady, WM, Greenson, JK, Gsur, A, Gunter, M, Haiman, CA, Hampe, J, Harlid, S, Harju, JF, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Huang, S-C, Huerta, JM, Hudson, TJ, Hunter, DJ, Idos, GE, Iwasaki, M, Jackson, RD, Jacobs, EJ, Jee, SH, Jenkins, MA, Jia, W-H, Jiao, S, Joshi, AD, Kolonel, LN, Kono, S, Kooperberg, C, Krogh, V, Kuehn, T, Kury, S, LaCroix, A, Laurie, CA, Lejbkowicz, F, Lemire, M, Lenz, H-J, Levine, D, Li, CI, Li, L, Lieb, W, Lin, Y, Lindor, NM, Liu, Y-R, Loupakis, F, Lu, Y, Luh, F, Ma, J, Mancao, C, Manion, FJ, Markowitz, SD, Martin, V, Matsuda, K, Matsuo, K, McDonnell, KJ, McNeil, CE, Milne, R, Molina, AJ, Mukherjee, B, Murphy, N, Newcomb, PA, Offit, K, Omichessan, H, Palli, D, Cotore, JPP, Perez-Mayoral, J, Pharoah, PD, Potter, JD, Raskin, L, Rennert, G, Rennert, HS, Riggs, BM, Schafmayer, C, Schoen, RE, Sellers, TA, Seminara, D, Severi, G, Shi, W, Shibata, D, Shu, X-O, Siegel, EM, Slattery, ML, Southey, M, Stadler, ZK, Stern, MC, Stintzing, S, Taverna, D, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Tsugane, S, Ulrich, CM, van Duijnhoven, FJB, van Guelpan, B, Vijai, J, Virtamo, J, Weinstein, SJ, White, E, Win, AK, Wolk, A, Woods, M, Wu, AH, Wu, K, Xiang, Y-B, Yen, Y, Zanke, BW, Zeng, Y-X, Zhang, B, Zubair, N, Kweon, S-S, Figueiredo, JC, Zheng, W, Le Marchand, L, Lindblom, A, Moreno, V, Peters, U, Casey, G, Hsu, L, Conti, DV, Gruber, SB, Schmit, SL, Edlund, CK, Schumacher, FR, Gong, J, Harrison, TA, Huyghe, JR, Qu, C, Melas, M, Van den Berg, DJ, Wang, H, Tring, S, Plummer, SJ, Albanes, D, Alonso, MH, Amos, CI, Anton, K, Aragaki, AK, Arndt, V, Barry, EL, Berndt, SI, Bezieau, S, Bien, S, Bloomer, A, Boehm, J, Boutron-Ruault, M-C, Brenner, H, Brezina, S, Buchanan, DD, Butterbach, K, Caan, BJ, Campbell, PT, Carlson, CS, Castelao, JE, Chan, AT, Chang-Claude, J, Chanock, SJ, Cheng, I, Cheng, Y-W, Chin, LS, Church, JM, Church, T, Coetzee, GA, Cotterchio, M, Correa, MC, Curtis, KR, Duggan, D, Easton, DF, English, D, Feskens, EJM, Fischer, R, FitzGerald, LM, Fortini, BK, Fritsche, LG, Fuchs, CS, Gago-Dominguez, M, Gala, M, Gallinger, SJ, Gauderman, WJ, Giles, GG, Giovannucci, EL, Gogarten, SM, Gonzalez-Villalpando, C, Gonzalez-Villalpando, EM, Grady, WM, Greenson, JK, Gsur, A, Gunter, M, Haiman, CA, Hampe, J, Harlid, S, Harju, JF, Hayes, RB, Hofer, P, Hoffmeister, M, Hopper, JL, Huang, S-C, Huerta, JM, Hudson, TJ, Hunter, DJ, Idos, GE, Iwasaki, M, Jackson, RD, Jacobs, EJ, Jee, SH, Jenkins, MA, Jia, W-H, Jiao, S, Joshi, AD, Kolonel, LN, Kono, S, Kooperberg, C, Krogh, V, Kuehn, T, Kury, S, LaCroix, A, Laurie, CA, Lejbkowicz, F, Lemire, M, Lenz, H-J, Levine, D, Li, CI, Li, L, Lieb, W, Lin, Y, Lindor, NM, Liu, Y-R, Loupakis, F, Lu, Y, Luh, F, Ma, J, Mancao, C, Manion, FJ, Markowitz, SD, Martin, V, Matsuda, K, Matsuo, K, McDonnell, KJ, McNeil, CE, Milne, R, Molina, AJ, Mukherjee, B, Murphy, N, Newcomb, PA, Offit, K, Omichessan, H, Palli, D, Cotore, JPP, Perez-Mayoral, J, Pharoah, PD, Potter, JD, Raskin, L, Rennert, G, Rennert, HS, Riggs, BM, Schafmayer, C, Schoen, RE, Sellers, TA, Seminara, D, Severi, G, Shi, W, Shibata, D, Shu, X-O, Siegel, EM, Slattery, ML, Southey, M, Stadler, ZK, Stern, MC, Stintzing, S, Taverna, D, Thibodeau, SN, Thomas, DC, Trichopoulou, A, Tsugane, S, Ulrich, CM, van Duijnhoven, FJB, van Guelpan, B, Vijai, J, Virtamo, J, Weinstein, SJ, White, E, Win, AK, Wolk, A, Woods, M, Wu, AH, Wu, K, Xiang, Y-B, Yen, Y, Zanke, BW, Zeng, Y-X, Zhang, B, Zubair, N, Kweon, S-S, Figueiredo, JC, Zheng, W, Le Marchand, L, Lindblom, A, Moreno, V, Peters, U, Casey, G, Hsu, L, Conti, DV, and Gruber, SB
- Abstract
BACKGROUND: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. METHODS: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. RESULTS: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. CONCLUSIONS: T
- Published
- 2019
3. Interleukin-6 Related Genotypes, Body Mass Index and Risk of Multiple Myeloma
- Author
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Cozen, W, Gebregziabher, M, Conti, D, ven den Berg, DJ, Coetzee, GA, Wang, SS, Rothman, N, Bernstein, L, Hartge, P, Morbacher, A, Coetzee, SG, Salam, MT, Wang, W, Zadnick, J, and Ingles, SA
- Published
- 2006
4. Cell-type-specific enrichment of risk-associated regulatory elements at ovarian cancer susceptibility loci
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Coetzee, SG, Shen, HC, Hazelett, DJ, Lawrenson, K, Kuchenbaecker, K, Tyrer, J, Rhie, SK, Levanon, K, Karst, A, Drapkin, R, Ramus, SJ, Couch, FJ, Offit, K, Chenevix-Trench, G, Monteiro, ANA, Antoniou, A, Freedman, M, Coetzee, GA, Pharoah, PDP, Noushmehr, H, Gayther, SA, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Berchuck, A, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chen, A, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Dörk, T, Bois, AD, Dürst, M, Eccles, D, Easton, DF, Edwards, RP, Eilber, U, Ekici, AB, Fasching, PA, Fridley, BL, Gao, YT, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, James, P, Jensen, A, Ji, BT, Karlan, BY, Kjaer, SK, Kelemen, LE, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lele, S, Leminen, A, and Lester, J
- Abstract
© The Author 2015. Published by Oxford University Press. All rights reserved. Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most singlenucleotide polymorphisms (SNPs) associated with cancer risk lie in non-protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs) and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared with normal human mammary epithelial cells and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissue-specific regulatory signatures compared to nongynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P = 3.8 × 10-30), OSECs (P = 2.4 × 10-23) and HMECs (P = 6.7 × 10-15) but not for EECs (P = 0.45) or LNCaP cells (P = 0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) suggesting both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets of germline genetic susceptibility variants for ovarian cancer.
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- 2015
5. Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans
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Al Olama, AA, Dadaev, T, Hazelett, DJ, Li, Q, Leongamornlert, D, Saunders, EJ, Stephens, S, Cieza-Borrella, C, Whitmore, I, Garcia, SB, Giles, GG, Southey, MC, Fitzgerald, L, Gronberg, H, Wiklund, F, Aly, M, Henderson, BE, Schumacher, F, Haiman, CA, Schleutker, J, Wahlfors, T, Tammela, TL, Nordestgaard, BG, Key, TJ, Travis, RC, Neal, DE, Donovan, JL, Hamdy, FC, Pharoah, P, Pashayan, N, Khaw, K-T, Stanford, JL, Thibodeau, SN, Mcdonnell, SK, Schaid, DJ, Maier, C, Vogel, W, Luedeke, M, Herkommer, K, Kibel, AS, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Cannon-Albright, L, Brenner, H, Butterbach, K, Arndt, V, Park, JY, Sellers, T, Lin, H-Y, Slavov, C, Kaneva, R, Mitev, V, Batra, J, Clements, JA, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Pandha, H, Michael, A, Kierzek, A, Govindasami, K, Guy, M, Lophatonanon, A, Muir, K, Vinuela, A, Brown, AA, Freedman, M, Conti, DV, Easton, D, Coetzee, GA, Eeles, RA, Kote-Jarai, Z, Al Olama, AA, Dadaev, T, Hazelett, DJ, Li, Q, Leongamornlert, D, Saunders, EJ, Stephens, S, Cieza-Borrella, C, Whitmore, I, Garcia, SB, Giles, GG, Southey, MC, Fitzgerald, L, Gronberg, H, Wiklund, F, Aly, M, Henderson, BE, Schumacher, F, Haiman, CA, Schleutker, J, Wahlfors, T, Tammela, TL, Nordestgaard, BG, Key, TJ, Travis, RC, Neal, DE, Donovan, JL, Hamdy, FC, Pharoah, P, Pashayan, N, Khaw, K-T, Stanford, JL, Thibodeau, SN, Mcdonnell, SK, Schaid, DJ, Maier, C, Vogel, W, Luedeke, M, Herkommer, K, Kibel, AS, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Cannon-Albright, L, Brenner, H, Butterbach, K, Arndt, V, Park, JY, Sellers, T, Lin, H-Y, Slavov, C, Kaneva, R, Mitev, V, Batra, J, Clements, JA, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Pandha, H, Michael, A, Kierzek, A, Govindasami, K, Guy, M, Lophatonanon, A, Muir, K, Vinuela, A, Brown, AA, Freedman, M, Conti, DV, Easton, D, Coetzee, GA, Eeles, RA, and Kote-Jarai, Z
- Abstract
Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region
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- 2015
6. Genome-wide association study of colorectal cancer identifies six new susceptibility loci
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Schumacher, FR, Schmit, SL, Jiao, S, Edlund, CK, Wang, H, Zhang, B, Hsu, L, Huang, S-C, Fischer, CP, Harju, JF, Idos, GE, Lejbkowicz, F, Manion, FJ, McDonnell, K, McNeil, CE, Melas, M, Rennert, HS, Shi, W, Thomas, DC, Van Den Berg, DJ, Hutter, CM, Aragaki, AK, Butterbach, K, Caan, BJ, Carlson, CS, Chanock, SJ, Curtis, KR, Fuchs, CS, Gala, M, Giocannucci, EL, Gogarten, SM, Hayes, RB, Henderson, B, Hunter, DJ, Jackson, RD, Kolonel, LN, Kooperberg, C, Kury, S, LaCroix, A, Laurie, CC, Laurie, CA, Lemire, M, Levine, D, Ma, J, Makar, KW, Qu, C, Taverna, D, Ulrich, CM, Wu, K, Kono, S, West, DW, Berndt, SI, Bezieau, S, Brenner, H, Campbell, PT, Chan, AT, Chang-Claude, J, Coetzee, GA, Conti, DV, Duggan, D, Figueiredo, JC, Fortini, BK, Gallinger, SJ, Gauderman, WJ, Giles, G, Green, R, Haile, R, Harrison, TA, Hoffmeister, M, Hopper, JL, Hudson, TJ, Jacobs, E, Iwasaki, M, Jee, SH, Jenkins, M, Jia, W-H, Joshi, A, Li, L, Lindor, NM, Matsuo, K, Moreno, V, Mukherjee, B, Newcomb, PA, Potter, JD, Raskin, L, Rennert, G, Rosse, S, Severi, G, Schoen, RE, Seminara, D, Shu, X-O, Slattery, ML, Tsugane, S, White, E, Xiang, Y-B, Zanke, BW, Zheng, W, Le Marchand, L, Casey, G, Gruber, SB, Peters, U, Schumacher, FR, Schmit, SL, Jiao, S, Edlund, CK, Wang, H, Zhang, B, Hsu, L, Huang, S-C, Fischer, CP, Harju, JF, Idos, GE, Lejbkowicz, F, Manion, FJ, McDonnell, K, McNeil, CE, Melas, M, Rennert, HS, Shi, W, Thomas, DC, Van Den Berg, DJ, Hutter, CM, Aragaki, AK, Butterbach, K, Caan, BJ, Carlson, CS, Chanock, SJ, Curtis, KR, Fuchs, CS, Gala, M, Giocannucci, EL, Gogarten, SM, Hayes, RB, Henderson, B, Hunter, DJ, Jackson, RD, Kolonel, LN, Kooperberg, C, Kury, S, LaCroix, A, Laurie, CC, Laurie, CA, Lemire, M, Levine, D, Ma, J, Makar, KW, Qu, C, Taverna, D, Ulrich, CM, Wu, K, Kono, S, West, DW, Berndt, SI, Bezieau, S, Brenner, H, Campbell, PT, Chan, AT, Chang-Claude, J, Coetzee, GA, Conti, DV, Duggan, D, Figueiredo, JC, Fortini, BK, Gallinger, SJ, Gauderman, WJ, Giles, G, Green, R, Haile, R, Harrison, TA, Hoffmeister, M, Hopper, JL, Hudson, TJ, Jacobs, E, Iwasaki, M, Jee, SH, Jenkins, M, Jia, W-H, Joshi, A, Li, L, Lindor, NM, Matsuo, K, Moreno, V, Mukherjee, B, Newcomb, PA, Potter, JD, Raskin, L, Rennert, G, Rosse, S, Severi, G, Schoen, RE, Seminara, D, Shu, X-O, Slattery, ML, Tsugane, S, White, E, Xiang, Y-B, Zanke, BW, Zheng, W, Le Marchand, L, Casey, G, Gruber, SB, and Peters, U
- Abstract
Genetic susceptibility to colorectal cancer is caused by rare pathogenic mutations and common genetic variants that contribute to familial risk. Here we report the results of a two-stage association study with 18,299 cases of colorectal cancer and 19,656 controls, with follow-up of the most statistically significant genetic loci in 4,725 cases and 9,969 controls from two Asian consortia. We describe six new susceptibility loci reaching a genome-wide threshold of P<5.0E-08. These findings provide additional insight into the underlying biological mechanisms of colorectal cancer and demonstrate the scientific value of large consortia-based genetic epidemiology studies.
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- 2015
7. Genome-wide association study of colorectal cancer identifies six new susceptibility loci (vol 6, 7138, 2015)
- Author
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Schumacher, FR, Schmit, SL, Jiao, S, Edlund, CK, Wang, H, Zhang, B, Hsu, L, Huang, S-C, Fischer, CP, Harju, JF, Idos, GE, Lejbkowicz, F, Manion, FJ, McDonnell, K, McNeil, CE, Melas, M, Rennert, HS, Shi, W, Thomas, DC, Van den Berg, DJ, Hutter, CM, Aragaki, AK, Butterbach, K, Caan, BJ, Carlson, CS, Chanock, SJ, Curtis, KR, Fuchs, CS, Gala, M, Giovannucci, EL, Gogarten, SM, Hayes, RB, Henderson, B, Hunter, DJ, Jackson, RD, Kolonel, LN, Kooperberg, C, Kuery, S, LaCroix, A, Laurie, CC, Laurie, CA, Lemire, M, Levine, D, Ma, J, Makar, KW, Qu, C, Taverna, D, Ulrich, CM, Wu, K, Kono, S, West, DW, Berndt, SI, Bezieau, S, Brenner, H, Campbell, PT, Chan, AT, Chang-Claude, J, Coetzee, GA, Conti, DV, Duggan, D, Figueiredo, JC, Fortini, BK, Gallinger, SJ, Gauderman, WJ, Giles, G, Green, R, Haile, R, Harrison, TA, Hoffmeister, M, Hopper, JL, Hudson, TJ, Jacobs, E, Iwasaki, M, Jee, SH, Jenkins, M, Jia, W-H, Joshi, A, Li, L, Lindor, NM, Matsuo, K, Moreno, V, Mukherjee, B, Newcomb, PA, Potter, JD, Raskin, L, Rennert, G, Rosse, S, Severi, G, Schoen, RE, Seminara, D, Shu, X-O, Slattery, ML, Tsugane, S, White, E, Xiang, Y-B, Zanke, BW, Zheng, W, Le Marchand, L, Casey, G, Gruber, SB, Peters, U, Schumacher, FR, Schmit, SL, Jiao, S, Edlund, CK, Wang, H, Zhang, B, Hsu, L, Huang, S-C, Fischer, CP, Harju, JF, Idos, GE, Lejbkowicz, F, Manion, FJ, McDonnell, K, McNeil, CE, Melas, M, Rennert, HS, Shi, W, Thomas, DC, Van den Berg, DJ, Hutter, CM, Aragaki, AK, Butterbach, K, Caan, BJ, Carlson, CS, Chanock, SJ, Curtis, KR, Fuchs, CS, Gala, M, Giovannucci, EL, Gogarten, SM, Hayes, RB, Henderson, B, Hunter, DJ, Jackson, RD, Kolonel, LN, Kooperberg, C, Kuery, S, LaCroix, A, Laurie, CC, Laurie, CA, Lemire, M, Levine, D, Ma, J, Makar, KW, Qu, C, Taverna, D, Ulrich, CM, Wu, K, Kono, S, West, DW, Berndt, SI, Bezieau, S, Brenner, H, Campbell, PT, Chan, AT, Chang-Claude, J, Coetzee, GA, Conti, DV, Duggan, D, Figueiredo, JC, Fortini, BK, Gallinger, SJ, Gauderman, WJ, Giles, G, Green, R, Haile, R, Harrison, TA, Hoffmeister, M, Hopper, JL, Hudson, TJ, Jacobs, E, Iwasaki, M, Jee, SH, Jenkins, M, Jia, W-H, Joshi, A, Li, L, Lindor, NM, Matsuo, K, Moreno, V, Mukherjee, B, Newcomb, PA, Potter, JD, Raskin, L, Rennert, G, Rosse, S, Severi, G, Schoen, RE, Seminara, D, Shu, X-O, Slattery, ML, Tsugane, S, White, E, Xiang, Y-B, Zanke, BW, Zheng, W, Le Marchand, L, Casey, G, Gruber, SB, and Peters, U
- Published
- 2015
8. Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31
- Author
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Permuth-Wey, J, Lawrenson, K, Shen, HC, Velkova, A, Tyrer, JP, Chen, Z, Lin, HY, Ann Chen, Y, Tsai, YY, Qu, X, Ramus, SJ, Karevan, R, Lee, J, Lee, N, Larson, MC, Aben, KK, Anton-Culver, H, Antonenkova, N, Antoniou, AC, Armasu, SM, Bacot, F, Baglietto, L, Bandera, EV, Barnholtz-Sloan, J, Beckmann, MW, Birrer, MJ, Bloom, G, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Brown, R, Butzow, R, Cai, Q, Campbell, I, Chang-Claude, J, Chanock, S, Chenevix-Trench, G, Cheng, JQ, Cicek, MS, Coetzee, GA, Cook, LS, Couch, FJ, Cramer, DW, Cunningham, JM, Dansonka-Mieszkowska, A, Despierre, E, Doherty, JA, Dörk, T, Du Bois, A, Dürst, M, Easton, DF, Eccles, D, Edwards, R, Ekici, AB, Fasching, PA, Fenstermacher, DA, Flanagan, JM, Garcia-Closas, M, Gentry-Maharaj, A, Giles, GG, Glasspool, RM, Gonzalez-Bosquet, J, Goodman, MT, Gore, M, Górski, B, Gronwald, J, Hall, P, Halle, MK, Harter, P, Heitz, F, Hillemanns, P, Hoatlin, M, Høgdall, CK, Høgdall, E, Hosono, S, Jakubowska, A, Jensen, A, Jim, H, Kalli, KR, Karlan, BY, Kaye, SB, Kelemen, LE, Kiemeney, LA, Kikkawa, F, and Konecny, GE
- Subjects
endocrine system diseases ,female genital diseases and pregnancy complications - Abstract
Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3′ untranslated region at putative microRNA (miRNA)-binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA-related single-nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (odds ratio=1.12, P=10-8) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10-10). Variation at 17q21.31 is associated with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes. © 2013 Macmillan Publishers Limited. All rights reserved.
- Published
- 2013
9. Chromatin accessibility reveals insights into androgen receptor activation and transcriptional specificity
- Author
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Tewari, A.K., Yardimci, G.G., Shibata, Y., Sheffield, N.C., Song, L., Taylor, B.S., Georgiev, S.G., Coetzee, GA., Ohler, U., Furey, T.S., Crawford, G.E., and Febbo, P.G.
- Subjects
Cardiovascular and Metabolic Diseases - Abstract
BACKGROUND: Epigenetic mechanisms such as chromatin accessibility impact transcription factor binding to DNA and transcriptional specificity. The androgen receptor (AR), a master regulator of the male phenotype and prostate cancer pathogenesis, acts primarily through ligand-activated transcription of target genes. Although several determinants of AR transcriptional specificity have been elucidated, our understanding of the interplay between chromatin accessibility and AR function remains incomplete. RESULTS: We used deep sequencing to assess chromatin structure via DNase I hypersensitivity and mRNA abundance, and paired these datasets with three independent AR ChIP-seq datasets. Our analysis revealed qualitative and quantitative differences in chromatin accessibility that corresponded to both AR binding and an enrichment of motifs for potential collaborating factors, one of which was identified as SP1. These quantitative differences were significantly associated with AR-regulated mRNA transcription across the genome. Base-pair resolution of the DNase I cleavage profile revealed three distinct footprinting patterns associated with the AR-DNA interaction, suggesting multiple modes of AR interaction with the genome. CONCLUSIONS: In contrast with other DNA-binding factors, AR binding to the genome does not only target regions that are accessible to DNase I cleavage prior to hormone induction. AR binding is invariably associated with an increase in chromatin accessibility and, consequently, changes in gene expression. Furthermore, we present the first in vivo evidence that a significant fraction of AR binds only to half of the full AR DNA motif. These findings indicate a dynamic quantitative relationship between chromatin structure and AR-DNA binding that impacts AR transcriptional specificity.
- Published
- 2012
10. A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer
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Al Olama, AA, Kote-Jarai, Z, Berndt, SI, Conti, DV, Schumacher, F, Han, Y, Benlloch, S, Hazelett, DJ, Wang, Z, Saunders, E, Leongamornlert, D, Lindstrom, S, Jugurnauth-Little, S, Dadaev, T, Tymrakiewicz, M, Stram, DO, Rand, K, Wan, P, Stram, A, Sheng, X, Pooler, LC, Park, K, Xia, L, Tyrer, J, Kolonel, LN, Le Marchand, L, Hoover, RN, Machiela, MJ, Yeager, M, Burdette, L, Chung, CC, Hutchinson, A, Yu, K, Goh, C, Ahmed, M, Govindasami, K, Guy, M, Tammela, TLJ, Auvinen, A, Wahlfors, T, Schleutker, J, Visakorpi, T, Leinonen, KA, Xu, J, Aly, M, Donovan, J, Travis, RC, Key, TJ, Siddiq, A, Canzian, F, Khaw, K-T, Takahashi, A, Kubo, M, Pharoah, P, Pashayan, N, Weischer, M, Nordestgaard, BG, Nielsen, SF, Klarskov, P, Roder, MA, Iversen, P, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Stanford, JL, Kolb, S, Holt, S, Knudsen, B, Coll, AH, Gapstur, SM, Diver, WR, Stevens, VL, Maier, C, Luedeke, M, Herkommer, K, Rinckleb, AE, Strom, SS, Pettaway, C, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Choklcalingam, AP, Cannon-Albright, L, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Park, J, Sellers, T, Lin, H-Y, Isaacs, WB, Partin, AW, Brenner, H, Dieffenbach, AK, Stegmaier, C, Chen, C, Giovannucci, EL, Ma, J, Stampfer, M, Penney, KL, Mucci, L, John, EM, Ingles, SA, Kittles, RA, Murphy, AB, Pandha, H, Michael, A, Kierzek, AM, Blot, W, Signorello, LB, Zheng, W, Albanes, D, Virtamo, J, Weinstein, S, Nemesure, B, Carpten, J, Leske, C, Wu, S-Y, Hennis, A, Kibel, AS, Rybicki, BA, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Zheng, SL, Batra, J, Clements, J, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Slavov, C, Kaneva, R, Mitev, V, Witte, JS, Casey, G, Gillanders, EM, Seminara, D, Riboli, E, Hamdy, FC, Coetzee, GA, Li, Q, Freedman, ML, Hunter, DJ, Muir, K, Gronberg, H, Nea, DE, Southey, M, Giles, GG, Severi, G, Cook, MB, Nakagawa, H, Wiklund, F, Kraft, P, Chanock, SJ, Henderson, BE, Easton, DF, Eeles, RA, Haiman, CA, Al Olama, AA, Kote-Jarai, Z, Berndt, SI, Conti, DV, Schumacher, F, Han, Y, Benlloch, S, Hazelett, DJ, Wang, Z, Saunders, E, Leongamornlert, D, Lindstrom, S, Jugurnauth-Little, S, Dadaev, T, Tymrakiewicz, M, Stram, DO, Rand, K, Wan, P, Stram, A, Sheng, X, Pooler, LC, Park, K, Xia, L, Tyrer, J, Kolonel, LN, Le Marchand, L, Hoover, RN, Machiela, MJ, Yeager, M, Burdette, L, Chung, CC, Hutchinson, A, Yu, K, Goh, C, Ahmed, M, Govindasami, K, Guy, M, Tammela, TLJ, Auvinen, A, Wahlfors, T, Schleutker, J, Visakorpi, T, Leinonen, KA, Xu, J, Aly, M, Donovan, J, Travis, RC, Key, TJ, Siddiq, A, Canzian, F, Khaw, K-T, Takahashi, A, Kubo, M, Pharoah, P, Pashayan, N, Weischer, M, Nordestgaard, BG, Nielsen, SF, Klarskov, P, Roder, MA, Iversen, P, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Stanford, JL, Kolb, S, Holt, S, Knudsen, B, Coll, AH, Gapstur, SM, Diver, WR, Stevens, VL, Maier, C, Luedeke, M, Herkommer, K, Rinckleb, AE, Strom, SS, Pettaway, C, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Choklcalingam, AP, Cannon-Albright, L, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Park, J, Sellers, T, Lin, H-Y, Isaacs, WB, Partin, AW, Brenner, H, Dieffenbach, AK, Stegmaier, C, Chen, C, Giovannucci, EL, Ma, J, Stampfer, M, Penney, KL, Mucci, L, John, EM, Ingles, SA, Kittles, RA, Murphy, AB, Pandha, H, Michael, A, Kierzek, AM, Blot, W, Signorello, LB, Zheng, W, Albanes, D, Virtamo, J, Weinstein, S, Nemesure, B, Carpten, J, Leske, C, Wu, S-Y, Hennis, A, Kibel, AS, Rybicki, BA, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Zheng, SL, Batra, J, Clements, J, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Slavov, C, Kaneva, R, Mitev, V, Witte, JS, Casey, G, Gillanders, EM, Seminara, D, Riboli, E, Hamdy, FC, Coetzee, GA, Li, Q, Freedman, ML, Hunter, DJ, Muir, K, Gronberg, H, Nea, DE, Southey, M, Giles, GG, Severi, G, Cook, MB, Nakagawa, H, Wiklund, F, Kraft, P, Chanock, SJ, Henderson, BE, Easton, DF, Eeles, RA, and Haiman, CA
- Abstract
Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.
- Published
- 2014
11. Does a polymorphism in the CYP17 gene predict mammographic density?
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Ursin, G, primary, Ingles, SA, additional, Spencer Feigelson, H, additional, Coetzee, GA, additional, Bernstein, L, additional, Pike, MC, additional, and Buley, A, additional
- Published
- 2000
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12. Identification and properties of the proline664-leucine mutant LDL receptor in South Africans of Indian origin.
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Rubinsztein, DC, primary, Coetzee, GA, additional, Marais, AD, additional, Leitersdorf, E, additional, Seftel, HC, additional, and van der Westhuyzen, DR, additional
- Published
- 1992
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13. Association of prostate cancer risk with genetic polymorphisms in vitamin D receptor and androgen receptor.
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Ingles SA, Ross RK, Yu MC, Irvine RA, La Pera G, Haile RW, Coetzee GA, Ingles, S A, Ross, R K, Yu, M C, Irvine, R A, La Pera, G, Haile, R W, and Coetzee, G A
- Abstract
Background: Prostate cancer is an increasingly common disease for which there are few well-established risk factors. Family history data suggest a genetic component; however, the majority of prostate cancer cases cannot be explained by a single-gene model. Prostate cell division is influenced by two steroid hormones, testosterone and vitamin D, the action of each being mediated by its respective receptor. The genes for the two receptors are candidates in a multigenic model for prostate cancer susceptibility.Purpose: We examined genetic polymorphisms in two steroid receptors, the androgen receptor (AR) and the vitamin D receptor (VDR), in a case-control pilot study of prostate cancer.Methods: Fifty-seven non-Hispanic white case patients with prostate cancer and 169 non-Hispanic white control subjects were genotyped for a previously described microsatellite (CAG repeats) in the AR gene and for a newly discovered poly-A microsatellite in the 3'-untranslated region (3'UTR) of the VDR gene. To compare genotypes with respect to prostate cancer risk, we estimated odds ratios (ORs) by using logistic regression. ORs were also estimated separately for advanced and localized cases of disease. All P values resulted from two-sided tests.Results: Both the AR and the VDR polymorphisms were associated, individually and after mutual adjustment, with prostate cancer. Adjusted ORs (95% confidence intervals [CIs]) for prostate cancer were 2.10 (95% CI = 1.11-3.99) for individuals carrying an AR CAG allele with fewer than 20 repeats versus an allele with 20 or more repeats and 4.61 (95% CI = 1.34-15.82) for individuals carrying at least one long (A18 to A22) VDR poly-A allele versus two short (A14 to A17) poly-A alleles. For both the AR and VDR genes, the at-risk genotypes were more strongly associated with advanced disease than with localized disease.Conclusions: In this pilot study, genetic variation in both the VDR and the AR genes was associated with prostate cancer, and both genes appear to preferentially confer risk for advanced disease. These two genetic risk factors, if confirmed, are among the strongest risk factors yet identified for prostate cancer.Implications: These results are consistent with a multigenic model of prostate cancer susceptibility. On the basis of the joint effect of several genetic loci, one might ultimately be able to construct a risk profile to predict advanced disease, so that men whose disease is unlikely to progress to an advanced stage can possibly be spared aggressive treatment. [ABSTRACT FROM AUTHOR]- Published
- 1997
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14. The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers
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Amos, CI, Dennis, J, Wang, Z, Byun, J, Schumacher, FR, Gayther, SA, Casey, G, Hunter, DJ, Sellers, TA, Gruber, SB, Dunning, AM, Michailidou, K, Fachal, L, Doheny, K, Spurdle, AB, Li, Y, Xiao, X, Romm, J, Pugh, E, Coetzee, GA, Hazelett, DJ, Bojesen, SE, Caga-Anan, C, Haiman, CA, Kamal, A, Luccarini, C, Tessier, D, Vincent, D, Bacot, F, Van Den Berg, DJ, Nelson, S, Demetriades, S, Goldgar, DE, Couch, FJ, Forman, JL, Giles, GG, Conti, DV, Bickeböller, H, Risch, A, Waldenberger, M, Brüske-Hohlfeld, I, Hicks, BD, Ling, H, McGuffog, L, Lee, A, Kuchenbaecker, K, Soucy, P, Manz, J, Cunningham, JM, Butterbach, K, Kote-Jarai, Z, Kraft, P, FitzGerald, L, Lindström, S, Adams, M, McKay, JD, Phelan, CM, Benlloch, S, Kelemen, LE, Brennan, P, Riggan, M, O'Mara, TA, Shen, H, Shi, Y, Thompson, DJ, Goodman, MT, Nielsen, SF, Berchuck, A, Laboissiere, S, Schmit, SL, Shelford, T, Edlund, CK, Taylor, JA, Field, JK, Park, SK, Offit, K, Thomassen, M, Schmutzler, R, Ottini, L, Hung, RJ, Marchini, J, Amin Al Olama, A, Peters, U, Eeles, RA, Seldin, MF, Gillanders, E, Seminara, D, Antoniou, AC, Pharoah, PDP, Chenevix-Trench, G, Chanock, SJ, Simard, J, and Easton, DF
- Subjects
Male ,Genotype ,Genetic Variation ,Prognosis ,Polymorphism, Single Nucleotide ,Risk Assessment ,3. Good health ,Neoplasms ,Prevalence ,Humans ,Female ,Genetic Predisposition to Disease ,Selection, Genetic ,Genome-Wide Association Study - Abstract
BACKGROUND: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. METHODS: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. RESULTS: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. CONCLUSIONS: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. IMPACT: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.
15. Does a polymorphism in the CYP17gene predict mammographic density?
- Author
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Ursin, G, Ingles, SA, Spencer Feigelson, H, Coetzee, GA, Bernstein, L, Pike, MC, and Buley, A
- Published
- 2000
- Full Text
- View/download PDF
16. Gene expression asymmetry in Parkinson's Disease; variation of CCT and BEX gene expression levels are correlated with hemisphere specific severity.
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Pierce SE, van der Schans EJC, Ensink E, and Coetzee GA
- Abstract
Parkinson's Disease (PD) develops unilaterally, which may be related to brain hemispheric differences in gene expression. Here we measured bulk RNA-seq levels in neuronal nuclei obtained from prefrontal cortex postmortem brain samples from males and females with PD and from healthy controls. Left and right hemispheres from each brain were related the side of symptom onset and compared. We employed two a priori approaches; first we identified genes differentially expressed between PD and controls and between left vs right PD brain hemispheres. Second, we examined the presence of, and correlates to, variable asymmetry seen in candidate PD differentially expressed genes. We found large variation among individuals with PD, and PD stratification by gene expression similarity was required for patterns of genetic asymmetry to emerge. For a subset of PD brains, hemispherical variation of CCT and BEX gene levels correlated with the side of PD symptom onset.
- Published
- 2024
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17. Parkinson's disease risk enhancers in microglia.
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Booms A, Pierce SE, van der Schans EJC, and Coetzee GA
- Abstract
Genome-wide association studies have identified thousands of single nucleotide polymorphisms that associate with increased risk for Parkinson's disease (PD), but the functions of most of them are unknown. Using assay for transposase-accessible chromatin (ATAC) and H3K27ac chromatin immunoprecipitation (ChIP) sequencing data, we identified 73 regulatory elements in microglia that overlap PD risk SNPs. To determine the target genes of a "risk enhancer" within intron two of SNCA , we used CRISPR-Cas9 to delete the open chromatin region where two PD risk SNPs reside. The loss of the enhancer led to reduced expression of multiple genes including SNCA and the adjacent gene MMRN1 . It also led to expression changes of genes involved in glucose metabolism, a process that is known to be altered in PD patients. Our work expands the role of SNCA in PD and provides a connection between PD-associated genetic variants and underlying biology that points to a risk mechanism in microglia., Competing Interests: The authors declare no competing interests., (© 2024 The Authors.)
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- 2024
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18. The Parkinson's disease variant rs356182 regulates neuronal differentiation independently from alpha-synuclein.
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Prahl JD, Pierce SE, van der Schans EJC, Coetzee GA, and Tyson T
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- Humans, Cell Differentiation genetics, Dopaminergic Neurons metabolism, Gene Expression, alpha-Synuclein genetics, alpha-Synuclein metabolism, Parkinson Disease genetics, Parkinson Disease metabolism
- Abstract
One of the most significant risk variants for Parkinson's disease (PD), rs356182, is located at the PD-associated locus near the alpha-synuclein (α-syn) encoding gene, SNCA. SNCA-proximal variants, including rs356182, are thought to function in PD risk through enhancers via allele-specific regulatory effects on SNCA expression. However, this interpretation discounts the complex activity of genetic enhancers and possible non-conical functions of α-syn. Here we investigated a novel risk mechanism for rs356182. We use CRISPR-Cas9 in LUHMES cells, a model for dopaminergic midbrain neurons, to generate precise hemizygous lesions at rs356182. The PD-protective (A/-), PD-risk (G/-) and wild-type (A/G) clones were neuronally differentiated and then compared transcriptionally and morphologically. Among the affected genes was SNCA, whose expression was promoted by the PD-protective allele (A) and repressed in its absence. In addition to SNCA, hundreds of genes were differentially expressed and associated with neurogenesis and axonogenesis-an effect not typically ascribed to α-syn. We also found that the transcription factor FOXO3 specifically binds to the rs356182 A-allele in differentiated LUHMES cells. Finally, we compared the results from the rs356182-edited cells to our previously published knockouts of SNCA and found only minimal overlap between the sets of significant differentially expressed genes. Together, the data implicate a risk mechanism for rs356182 in which the risk-allele (G) is associated with abnormal neuron development, independent of SNCA expression. We speculate that these pathological effects manifest as a diminished population of dopaminergic neurons during development leading to the predisposition for PD later in life., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
- Published
- 2023
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19. Genetic Elements at the Alpha-Synuclein Locus.
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Prahl J and Coetzee GA
- Abstract
Genome-wide association studies have consistently shown that the alpha-synuclein locus is significantly associated with Parkinson's disease. The mechanism by which this locus modulates the disease pathology and etiology remains largely under-investigated. This is due to the assumption that SNCA is the only driver of the functional aspects of several single nucleotide polymorphism (SNP) risk-signals at this locus. Recent evidence has shown that the risk associated with the top GWAS-identified variant within this locus is independent of SNCA expression, calling into question the validity of assigning function to the nearest gene, SNCA . In this review, we examine additional genes and risk variants present at the SNCA locus and how they may contribute to Parkinson's disease. Using the SNCA locus as an example, we hope to demonstrate that deeper and detailed functional validations are required for high impact disease-linked variants., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Prahl and Coetzee.)
- Published
- 2022
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20. Alpha-synuclein negatively controls cell proliferation in dopaminergic neurons.
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Prahl J, Pierce SE, Coetzee GA, and Tyson T
- Subjects
- Animals, Cell Proliferation, Gene Expression, Humans, Mice, Dopaminergic Neurons metabolism, Parkinson Disease metabolism, alpha-Synuclein genetics, alpha-Synuclein metabolism
- Abstract
As researchers grapple with the mechanisms and implications of alpha-synuclein (α-syn) in neuropathology, it is often forgotten that the function(s) of α-syn in healthy cells remain largely elusive. Previous work has relied on observing α-syn localization in the cell or using knockout mouse models. Here, we address the specific role of α-syn in human dopaminergic neurons by disrupting its gene (SNCA) in the human dopaminergic neuron cell line, LUHMES. SNCA-null cells were able to differentiate grossly normally and showed modest effects on gene expression. The effects on gene expression were monodirectional, resulting primarily in the significant decrease of expression for 401 genes, implicating them as direct, or indirect positive targets of α-syn. Gene ontological analysis of these genes showed enrichment in terms associated with proliferation, differentiation, and synapse activity. These results add to the tapestry of α-syn biological functions. SIGNIFICANCE STATEMENT: The normal functions of α-syn have remained controversial, despite its clear importance in Parkinson's Disease pathology, where it accumulates in Lewy bodies and contributes to neurodegeneration. Its name implies synaptic and nuclear functions, but how it participates at these locations has not been resolved. Via knock-out experiments in dopaminergic neurons, we implicate α-syn as a functional participant in synapse activity and in proliferation/differentiation, the latter being novel and provide insight into α-syn's role in neuronal development., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2022
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21. Functions of Intracellular Alpha-Synuclein in Microglia: Implications for Parkinson's Disease Risk.
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Booms A and Coetzee GA
- Abstract
Alpha-synuclein accumulation in dopaminergic neurons is one of the primary features of Parkinson's disease (PD). Despite its toxic properties during PD, alpha-synuclein has some important physiological functions. Although the activity of the protein has been extensively studied in neurons, the protein is also expressed in other cell types including immune cells and glia. Genetic studies show that mutations in synuclein alpha ( SNCA ), the gene that encodes alpha-synuclein, and alterations in its expression levels are a significant risk factor for PD, which likely impact the functions of a broad range of cell types. The consequences of altered SNCA expression in other cell types is beginning to be explored. Microglia, the primary macrophage population in the Central Nervous System (CNS), for example, are affected by variations in alpha-synuclein levels and functions. Studies suggest that deviations of alpha-synuclein's normal activity influence hematopoiesis, the process that gives rise to microglia, and microglia's immune functions. Alpha-synuclein levels also dictate the efficiency of SNARE-mediated vesicle formation, which could influence autophagy and cytokine release in microglia. Starting from the time of conception, these effects could impact one's risk for developing PD. Further studies are needed to determine the physiological role of alpha-synuclein and how the protein is affected during PD in non-neuronal cells such as microglia. In this review we will discuss the known roles of alpha-synuclein in differentiation, immune responses, and vesicle formation, with insights into how abnormal alpha-synuclein expression and activity are linked to altered functions of microglia during PD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Booms and Coetzee.)
- Published
- 2021
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22. The enigma and implications of brain hemispheric asymmetry in neurodegenerative diseases.
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Lubben N, Ensink E, Coetzee GA, and Labrie V
- Abstract
The lateralization of the human brain may provide clues into the pathogenesis and progression of neurodegenerative diseases. Though differing in their presentation and underlying pathologies, neurodegenerative diseases are all devastating and share an intriguing theme of asymmetrical pathology and clinical symptoms. Parkinson's disease, with its distinctive onset of motor symptoms on one side of the body, stands out in this regard, but a review of the literature reveals asymmetries in several other neurodegenerative diseases. Here, we review the lateralization of the structure and function of the healthy human brain and the common genetic and epigenetic patterns contributing to the development of asymmetry in health and disease. We specifically examine the role of asymmetry in Parkinson's disease, Alzheimer's disease, amyotrophic lateral sclerosis, and multiple sclerosis, and interrogate whether these imbalances may reveal meaningful clues about the origins of these diseases. We also propose several hypotheses for how lateralization may contribute to the distinctive and enigmatic features of asymmetry in neurodegenerative diseases, suggesting a role for asymmetry in the choroid plexus, neurochemistry, protein distribution, brain connectivity and the vagus nerve. Finally, we suggest how future studies may reveal novel insights into these diseases through the lens of asymmetry., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)
- Published
- 2021
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23. Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry.
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Graff M, Justice AE, Young KL, Marouli E, Zhang X, Fine RS, Lim E, Buchanan V, Rand K, Feitosa MF, Wojczynski MK, Yanek LR, Shao Y, Rohde R, Adeyemo AA, Aldrich MC, Allison MA, Ambrosone CB, Ambs S, Amos C, Arnett DK, Atwood L, Bandera EV, Bartz T, Becker DM, Berndt SI, Bernstein L, Bielak LF, Blot WJ, Bottinger EP, Bowden DW, Bradfield JP, Brody JA, Broeckel U, Burke G, Cade BE, Cai Q, Caporaso N, Carlson C, Carpten J, Casey G, Chanock SJ, Chen G, Chen M, Chen YI, Chen WM, Chesi A, Chiang CWK, Chu L, Coetzee GA, Conti DV, Cooper RS, Cushman M, Demerath E, Deming SL, Dimitrov L, Ding J, Diver WR, Duan Q, Evans MK, Falusi AG, Faul JD, Fornage M, Fox C, Freedman BI, Garcia M, Gillanders EM, Goodman P, Gottesman O, Grant SFA, Guo X, Hakonarson H, Haritunians T, Harris TB, Harris CC, Henderson BE, Hennis A, Hernandez DG, Hirschhorn JN, McNeill LH, Howard TD, Howard B, Hsing AW, Hsu YH, Hu JJ, Huff CD, Huo D, Ingles SA, Irvin MR, John EM, Johnson KC, Jordan JM, Kabagambe EK, Kang SJ, Kardia SL, Keating BJ, Kittles RA, Klein EA, Kolb S, Kolonel LN, Kooperberg C, Kuller L, Kutlar A, Lange L, Langefeld CD, Le Marchand L, Leonard H, Lettre G, Levin AM, Li Y, Li J, Liu Y, Liu Y, Liu S, Lohman K, Lotay V, Lu Y, Maixner W, Manson JE, McKnight B, Meng Y, Monda KL, Monroe K, Moore JH, Mosley TH, Mudgal P, Murphy AB, Nadukuru R, Nalls MA, Nathanson KL, Nayak U, N'Diaye A, Nemesure B, Neslund-Dudas C, Neuhouser ML, Nyante S, Ochs-Balcom H, Ogundiran TO, Ogunniyi A, Ojengbede O, Okut H, Olopade OI, Olshan A, Padhukasahasram B, Palmer J, Palmer CD, Palmer ND, Papanicolaou G, Patel SR, Pettaway CA, Peyser PA, Press MF, Rao DC, Rasmussen-Torvik LJ, Redline S, Reiner AP, Rhie SK, Rodriguez-Gil JL, Rotimi CN, Rotter JI, Ruiz-Narvaez EA, Rybicki BA, Salako B, Sale MM, Sanderson M, Schadt E, Schreiner PJ, Schurmann C, Schwartz AG, Shriner DA, Signorello LB, Singleton AB, Siscovick DS, Smith JA, Smith S, Speliotes E, Spitz M, Stanford JL, Stevens VL, Stram A, Strom SS, Sucheston L, Sun YV, Tajuddin SM, Taylor H, Taylor K, Tayo BO, Thun MJ, Tucker MA, Vaidya D, Van Den Berg DJ, Vedantam S, Vitolins M, Wang Z, Ware EB, Wassertheil-Smoller S, Weir DR, Wiencke JK, Williams SM, Williams LK, Wilson JG, Witte JS, Wrensch M, Wu X, Yao J, Zakai N, Zanetti K, Zemel BS, Zhao W, Zhao JH, Zheng W, Zhi D, Zhou J, Zhu X, Ziegler RG, Zmuda J, Zonderman AB, Psaty BM, Borecki IB, Cupples LA, Liu CT, Haiman CA, Loos R, Ng MCY, and North KE
- Subjects
- Africa ethnology, Black or African American genetics, Europe ethnology, Female, Humans, Male, Polymorphism, Single Nucleotide genetics, Black People genetics, Body Height genetics, Genome-Wide Association Study
- Abstract
Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations., (Copyright © 2021 American Society of Human Genetics. All rights reserved.)
- Published
- 2021
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24. Epigenomic analysis of Parkinson's disease neurons identifies Tet2 loss as neuroprotective.
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Marshall LL, Killinger BA, Ensink E, Li P, Li KX, Cui W, Lubben N, Weiland M, Wang X, Gordevicius J, Coetzee GA, Ma J, Jovinge S, and Labrie V
- Subjects
- Animals, Cell Line, Tumor, DNA Methylation, Dioxygenases, Epigenomics, Female, Humans, Male, Mice, Inbred C57BL, Mice, Knockout, DNA-Binding Proteins genetics, Epigenesis, Genetic, Gene Expression Regulation, Neurons metabolism, Neuroprotection, Parkinson Disease genetics, Prefrontal Cortex metabolism, Proto-Oncogene Proteins genetics
- Abstract
Parkinson's disease (PD) pathogenesis may involve the epigenetic control of enhancers that modify neuronal functions. Here, we comprehensively examine DNA methylation at enhancers, genome-wide, in neurons of patients with PD and of control individuals. We find a widespread increase in cytosine modifications at enhancers in PD neurons, which is partly explained by elevated hydroxymethylation levels. In particular, patients with PD exhibit an epigenetic and transcriptional upregulation of TET2, a master-regulator of cytosine modification status. TET2 depletion in a neuronal cell model results in cytosine modification changes that are reciprocal to those observed in PD neurons. Moreover, Tet2 inactivation in mice fully prevents nigral dopaminergic neuronal loss induced by previous inflammation. Tet2 loss also attenuates transcriptional immune responses to an inflammatory trigger. Thus, widespread epigenetic dysregulation of enhancers in PD neurons may, in part, be mediated by increased TET2 expression. Decreased Tet2 activity is neuroprotective, in vivo, and may be a new therapeutic target for PD.
- Published
- 2020
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25. Post-GWAS knowledge gap: the how, where, and when.
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Pierce SE, Booms A, Prahl J, van der Schans EJC, Tyson T, and Coetzee GA
- Abstract
Genetic risk for complex diseases very rarely reflects only Mendelian-inherited phenotypes where single-gene mutations can be followed in families by linkage analysis. More commonly, a large set of low-penetrance, small effect-size variants combine to confer risk; they are normally revealed in genome-wide association studies (GWAS), which compare large population groups. Whereas Mendelian inheritance points toward disease mechanisms arising from the mutated genes, in the case of GWAS signals, the effector proteins and even general risk mechanism are mostly unknown. Instead, the utility of GWAS currently lies primarily in predictive and diagnostic information. Although an amazing body of GWAS-based knowledge now exists, we advocate for more funding towards the exploration of the fundamental biology in post-GWAS studies; this research will bring us closer to causality and risk gene identification. Using Parkinson's Disease as an example, we ask, how, where, and when do risk loci contribute to disease?, Competing Interests: Competing InterestsThe authors declare no competing interests., (© The Author(s) 2020.)
- Published
- 2020
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26. MCF-7 as a Model for Functional Analysis of Breast Cancer Risk Variants.
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Booms A, Coetzee GA, and Pierce SE
- Subjects
- Breast Neoplasms pathology, Female, Genetic Predisposition to Disease, Genome-Wide Association Study methods, Haplotypes, Humans, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Risk Factors, Biomarkers, Tumor genetics, Breast Neoplasms genetics, CCCTC-Binding Factor genetics, MCF-7 Cells, Models, Genetic
- Abstract
Background: Breast cancer genetic predisposition is governed by more than 142 loci as revealed by genome-wide association studies (GWAS). The functional contribution of these risk loci to breast cancer remains unclear, and additional post-GWAS analyses are required., Methods: We identified active regulatory elements (enhancers, promoters, and chromatin organizing elements) by histone H3K27 acetylation and CTCF occupancy and determined the enrichment of risk variants at these sites. We compared these results with previously published data and for other cell lines, including human mammary epithelial cells, and related these data to gene expression., Results: In terms of mapping accuracy and resolution, our data augment previous annotations of the MCF-7 epigenome. After intersection with GWAS risk variants, we found 39 enhancers and 15 CTCF occupancy sites that, between them, overlapped 96 breast cancer credible risk variants at 42 loci. These risk enhancers likely regulate the expression of dozens of genes, which are enriched for GO categories, including estrogen and prolactin signaling., Conclusions: Ten (of 142) breast cancer risk loci likely function via enhancers that are active in MCF-7 and are well suited to targeted manipulation in this system. In contrast, risk loci cannot be mapped to specific CTCF-binding sites, and the genes linked to risk CTCF sites did not show functional enrichment. The identity of risk enhancers and their associated genes suggests that some risk may function during later processes in cancer progression., Impact: Here, we report how the ER
+ cell line MCF-7 can be used to dissect risk mechanisms for breast cancer., (©2019 American Association for Cancer Research.)- Published
- 2019
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27. Understanding Non-Mendelian Genetic Risk.
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Coetzee GA
- Abstract
This opinion paper highlights strategies for a better understanding of non-Mendelian genetic risk that was revealed by genome-wide association studies (GWAS) of complex diseases. The genetic risk resides predominantly in non-coding regulatory DNA, such as in enhancers. The identification of mechanisms, the causal variants (mainly SNPs), and their target genes are, however, not always apparent but are likely involved in a network of risk determinants; the identification presents a bottle-neck in the full understanding of the genetics of complex phenotypes. Here, we propose strategies to identify functional SNPs and link risk enhancers with their target genes. The strategies are 1) identifying fine-mapped SNPs that break/form response elements within chromatin bio-features in relevant cell types 2) considering the nearest gene on linear DNA, 3) analyzing eQTLs, 4) mapping differential DNA methylation regions and relating them to gene expression, 5) employing genomic editing with CRISPR/cas9 and 6) identifying topological associated chromatin domains using chromatin conformation capture., (© 2019 Bentham Science Publishers.)
- Published
- 2019
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28. Genetically engineered stem cell-derived neurons can be rendered resistant to alpha-synuclein aggregate pathology.
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Brundin P and Coetzee GA
- Subjects
- Humans, Neurons, Stem Cells, Synucleinopathies, alpha-Synuclein
- Published
- 2019
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29. Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus.
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Buckley MA, Woods NT, Tyrer JP, Mendoza-Fandiño G, Lawrenson K, Hazelett DJ, Najafabadi HS, Gjyshi A, Carvalho RS, Lyra PC Jr, Coetzee SG, Shen HC, Yang AW, Earp MA, Yoder SJ, Risch H, Chenevix-Trench G, Ramus SJ, Phelan CM, Coetzee GA, Noushmehr H, Hughes TR, Sellers TA, Goode EL, Pharoah PD, Gayther SA, and Monteiro ANA
- Subjects
- Base Sequence, Cell Cycle Proteins genetics, Cell Line, Tumor, Chromosome Mapping, Cystadenocarcinoma, Serous genetics, DNA, Neoplasm genetics, DNA-Binding Proteins genetics, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, HEK293 Cells, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Carcinoma, Ovarian Epithelial genetics, Chromosomes, Human, Pair 9, Ovarian Neoplasms genetics
- Abstract
Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro , verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. See related commentary by Choi and Brown, p. 439 ., (©2018 American Association for Cancer Research.)
- Published
- 2019
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30. Novel Common Genetic Susceptibility Loci for Colorectal Cancer.
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Schmit SL, Edlund CK, Schumacher FR, Gong J, Harrison TA, Huyghe JR, Qu C, Melas M, Van Den Berg DJ, Wang H, Tring S, Plummer SJ, Albanes D, Alonso MH, Amos CI, Anton K, Aragaki AK, Arndt V, Barry EL, Berndt SI, Bezieau S, Bien S, Bloomer A, Boehm J, Boutron-Ruault MC, Brenner H, Brezina S, Buchanan DD, Butterbach K, Caan BJ, Campbell PT, Carlson CS, Castelao JE, Chan AT, Chang-Claude J, Chanock SJ, Cheng I, Cheng YW, Chin LS, Church JM, Church T, Coetzee GA, Cotterchio M, Cruz Correa M, Curtis KR, Duggan D, Easton DF, English D, Feskens EJM, Fischer R, FitzGerald LM, Fortini BK, Fritsche LG, Fuchs CS, Gago-Dominguez M, Gala M, Gallinger SJ, Gauderman WJ, Giles GG, Giovannucci EL, Gogarten SM, Gonzalez-Villalpando C, Gonzalez-Villalpando EM, Grady WM, Greenson JK, Gsur A, Gunter M, Haiman CA, Hampe J, Harlid S, Harju JF, Hayes RB, Hofer P, Hoffmeister M, Hopper JL, Huang SC, Huerta JM, Hudson TJ, Hunter DJ, Idos GE, Iwasaki M, Jackson RD, Jacobs EJ, Jee SH, Jenkins MA, Jia WH, Jiao S, Joshi AD, Kolonel LN, Kono S, Kooperberg C, Krogh V, Kuehn T, Küry S, LaCroix A, Laurie CA, Lejbkowicz F, Lemire M, Lenz HJ, Levine D, Li CI, Li L, Lieb W, Lin Y, Lindor NM, Liu YR, Loupakis F, Lu Y, Luh F, Ma J, Mancao C, Manion FJ, Markowitz SD, Martin V, Matsuda K, Matsuo K, McDonnell KJ, McNeil CE, Milne R, Molina AJ, Mukherjee B, Murphy N, Newcomb PA, Offit K, Omichessan H, Palli D, Cotoré JPP, Pérez-Mayoral J, Pharoah PD, Potter JD, Qu C, Raskin L, Rennert G, Rennert HS, Riggs BM, Schafmayer C, Schoen RE, Sellers TA, Seminara D, Severi G, Shi W, Shibata D, Shu XO, Siegel EM, Slattery ML, Southey M, Stadler ZK, Stern MC, Stintzing S, Taverna D, Thibodeau SN, Thomas DC, Trichopoulou A, Tsugane S, Ulrich CM, van Duijnhoven FJB, van Guelpan B, Vijai J, Virtamo J, Weinstein SJ, White E, Win AK, Wolk A, Woods M, Wu AH, Wu K, Xiang YB, Yen Y, Zanke BW, Zeng YX, Zhang B, Zubair N, Kweon SS, Figueiredo JC, Zheng W, Marchand LL, Lindblom A, Moreno V, Peters U, Casey G, Hsu L, Conti DV, and Gruber SB
- Subjects
- Case-Control Studies, Ethnicity statistics & numerical data, Follow-Up Studies, Genotype, Humans, Prognosis, United States epidemiology, Colorectal Neoplasms epidemiology, Colorectal Neoplasms genetics, Ethnicity genetics, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Polymorphism, Single Nucleotide
- Abstract
Background: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk., Methods: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided., Results: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0., Conclusions: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening., (© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
- Published
- 2019
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31. CRISPR-mediated deletion of prostate cancer risk-associated CTCF loop anchors identifies repressive chromatin loops.
- Author
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Guo Y, Perez AA, Hazelett DJ, Coetzee GA, Rhie SK, and Farnham PJ
- Subjects
- Acetylation, Cell Line, Tumor, Enhancer Elements, Genetic genetics, Histones metabolism, Humans, Lysine metabolism, Male, Polymorphism, Single Nucleotide genetics, Risk Factors, Small-Conductance Calcium-Activated Potassium Channels genetics, Up-Regulation genetics, CCCTC-Binding Factor metabolism, Chromatin metabolism, Clustered Regularly Interspaced Short Palindromic Repeats genetics, Gene Deletion, Prostatic Neoplasms genetics
- Abstract
Background: Recent genome-wide association studies (GWAS) have identified more than 100 loci associated with increased risk of prostate cancer, most of which are in non-coding regions of the genome. Understanding the function of these non-coding risk loci is critical to elucidate the genetic susceptibility to prostate cancer., Results: We generate genome-wide regulatory element maps and performed genome-wide chromosome confirmation capture assays (in situ Hi-C) in normal and tumorigenic prostate cells. Using this information, we annotate the regulatory potential of 2,181 fine-mapped prostate cancer risk-associated SNPs and predict a set of target genes that are regulated by prostate cancer risk-related H3K27Ac-mediated loops. We next identify prostate cancer risk-associated CTCF sites involved in long-range chromatin loops. We use CRISPR-mediated deletion to remove prostate cancer risk-associated CTCF anchor regions and the CTCF anchor regions looped to the prostate cancer risk-associated CTCF sites, and we observe up to 100-fold increases in expression of genes within the loops when the prostate cancer risk-associated CTCF anchor regions are deleted., Conclusions: We identify GWAS risk loci involved in long-range loops that function to repress gene expression within chromatin loops. Our studies provide new insights into the genetic susceptibility to prostate cancer.
- Published
- 2018
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32. Parkinson's disease genetic risk in a midbrain neuronal cell line.
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Pierce SE, Tyson T, Booms A, Prahl J, and Coetzee GA
- Subjects
- Amino Acid Sequence genetics, Cell Line, Humans, Genetic Predisposition to Disease genetics, Mesencephalon pathology, Neurons pathology, Parkinson Disease genetics, Parkinson Disease pathology
- Abstract
In genome-wide association studies of complex diseases, many risk polymorphisms are found to lie in non-coding DNA and likely confer risk through allele-dependent differences in gene regulatory elements. However, because distal regulatory elements can alter gene expression at various distances on linear DNA, the identity of relevant genes is unknown for most risk loci. In Parkinson's disease, at least some genetic risk is likely intrinsic to a neuronal subpopulation of cells in the brain regions affected. In order to compare neuron-relevant methods of pairing risk polymorphisms to target genes as well as to further characterize a single-cell model of a neurodegenerative disease, we used the portionally-dopaminergic, neuronal, mesencephalic-derived cell line LUHMES to dissect differentiation-specific mechanisms of gene expression. We compared genome-wide gene expression in undifferentiated and differentiated cells with genome-wide histone H3K27ac and CTCF-bound regions. Whereas promoters and CTCF binding were largely consistent between differentiated and undifferentiated cells, enhancers were mostly unique. We matched the differentiation-specific appearance or disappearance of enhancers with changes in gene expression and identified 22,057 enhancers paired with 6388 differentially expressed genes by proximity. These enhancers are enriched with at least 13 transcription factor response elements, driving a cluster of genes involved in neurogenesis. We show that differentiated LUHMES cells, but not undifferentiated cells, show enrichment for PD-risk SNPs. Candidate genes for these loci are largely unrelated, though a subset is linked to synaptic vesicle cycling and transport, implying that PD-related disruption of these pathways is intrinsic to dopaminergic neurons., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2018
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33. The Five Dimensions of Parkinson's Disease Genetic Risk.
- Author
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Coetzee GA and Pierce S
- Subjects
- Chromatin ultrastructure, Enhancer Elements, Genetic genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Promoter Regions, Genetic genetics, Quantitative Trait Loci, Risk Factors, Time Factors, Chromatin genetics, Parkinson Disease genetics
- Abstract
Genome-wide association studies of Parkinson's disease have revealed polymorphic variants associated with closely mapped genes of interest. We propose here that those genes may only represent the tip of an iceberg of regulatory effects and do not necessary reflect disease relevance. To usefully interpret a risk locus, one needs to consider 5 dimensions of information, which represent the three-dimensional structure of chromatin (dimensions #1- 3), which is locally variable across time (dimension #4), and, most importantly, dependent on cell type and context (dimension #5).
- Published
- 2018
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34. Characterizing Genetic Susceptibility to Breast Cancer in Women of African Ancestry.
- Author
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Feng Y, Rhie SK, Huo D, Ruiz-Narvaez EA, Haddad SA, Ambrosone CB, John EM, Bernstein L, Zheng W, Hu JJ, Ziegler RG, Nyante S, Bandera EV, Ingles SA, Press MF, Deming SL, Rodriguez-Gil JL, Zheng Y, Yao S, Han YJ, Ogundiran TO, Rebbeck TR, Adebamowo C, Ojengbede O, Falusi AG, Hennis A, Nemesure B, Ambs S, Blot W, Cai Q, Signorello L, Nathanson KL, Lunetta KL, Sucheston-Campbell LE, Bensen JT, Chanock SJ, Marchand LL, Olshan AF, Kolonel LN, Conti DV, Coetzee GA, Stram DO, Olopade OI, Palmer JR, and Haiman CA
- Subjects
- Alleles, Breast Neoplasms pathology, Case-Control Studies, Chromosome Mapping, Female, Genetic Loci, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen metabolism, Risk Factors, Black or African American genetics, Biomarkers, Tumor genetics, Breast Neoplasms genetics, Genetic Predisposition to Disease
- Abstract
Background: Genome-wide association studies have identified approximately 100 common genetic variants associated with breast cancer risk, the majority of which were discovered in women of European ancestry. Because of different patterns of linkage disequilibrium, many of these genetic markers may not represent signals in populations of African ancestry. Methods: We tested 74 breast cancer risk variants and conducted fine-mapping of these susceptibility regions in 6,522 breast cancer cases and 7,643 controls of African ancestry from three genetic consortia (AABC, AMBER, and ROOT). Results: Fifty-four of the 74 variants (73%) were found to have ORs that were directionally consistent with those previously reported, of which 12 were nominally statistically significant ( P < 0.05). Through fine-mapping, in six regions ( 3p24, 12p11, 14q13, 16q12/FTO, 16q23, 19p13 ), we observed seven markers that better represent the underlying risk variant for overall breast cancer or breast cancer subtypes, whereas in another two regions ( 11q13, 16q12/TOX3 ), we identified suggestive evidence of signals that are independent of the reported index variant. Overlapping chromatin features and regulatory elements suggest that many of the risk alleles lie in regions with biological functionality. Conclusions: Through fine-mapping of known susceptibility regions, we have revealed alleles that better characterize breast cancer risk in women of African ancestry. Impact: The risk alleles identified represent genetic markers for modeling and stratifying breast cancer risk in women of African ancestry. Cancer Epidemiol Biomarkers Prev; 26(7); 1016-26. ©2017 AACR ., (©2017 American Association for Cancer Research.)
- Published
- 2017
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35. Parkinson's disease-associated genetic variation is linked to quantitative expression of inflammatory genes.
- Author
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Pierce S and Coetzee GA
- Subjects
- Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Quantitative Trait Loci, Histocompatibility Antigens Class II genetics, Parkinson Disease genetics, Polymorphism, Single Nucleotide
- Abstract
Genome-wide association studies (GWAS) have linked dozens of single nucleotide polymorphisms (SNPs) with Parkinson's disease (PD) risk. Ascertaining the functional and eventual causal mechanisms underlying these relationships has proven difficult. The majority of risk SNPs, and nearby SNPs in linkage disequilibrium (LD), are found in intergenic or intronic regions and confer risk through allele-dependent expression of multiple unknown target genes. Combining GWAS results with publicly available GTEx data, generated through eQTL (expression quantitative trait loci) identification studies, enables a direct association of SNPs to gene expression levels and aids in narrowing the large population of potential genetic targets for hypothesis-driven experimental cell biology. Separately, overlapping of SNPs with putative enhancer segmentations can strengthen target filtering. We report here the results of analyzing 7,607 PD risk SNPs along with an additional 23,759 high linkage disequilibrium-associated variants paired with eQTL gene expression. We found that enrichment analysis on the set of genes following target filtering pointed to a single large LD block at 6p21 that contained multiple HLA-MHC-II genes. These MHC-II genes remain associated with PD when the genes were filtered for correlation between GWAS significance and eQTL levels, strongly indicating a direct effect on PD etiology.
- Published
- 2017
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36. The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers.
- Author
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Amos CI, Dennis J, Wang Z, Byun J, Schumacher FR, Gayther SA, Casey G, Hunter DJ, Sellers TA, Gruber SB, Dunning AM, Michailidou K, Fachal L, Doheny K, Spurdle AB, Li Y, Xiao X, Romm J, Pugh E, Coetzee GA, Hazelett DJ, Bojesen SE, Caga-Anan C, Haiman CA, Kamal A, Luccarini C, Tessier D, Vincent D, Bacot F, Van Den Berg DJ, Nelson S, Demetriades S, Goldgar DE, Couch FJ, Forman JL, Giles GG, Conti DV, Bickeböller H, Risch A, Waldenberger M, Brüske-Hohlfeld I, Hicks BD, Ling H, McGuffog L, Lee A, Kuchenbaecker K, Soucy P, Manz J, Cunningham JM, Butterbach K, Kote-Jarai Z, Kraft P, FitzGerald L, Lindström S, Adams M, McKay JD, Phelan CM, Benlloch S, Kelemen LE, Brennan P, Riggan M, O'Mara TA, Shen H, Shi Y, Thompson DJ, Goodman MT, Nielsen SF, Berchuck A, Laboissiere S, Schmit SL, Shelford T, Edlund CK, Taylor JA, Field JK, Park SK, Offit K, Thomassen M, Schmutzler R, Ottini L, Hung RJ, Marchini J, Amin Al Olama A, Peters U, Eeles RA, Seldin MF, Gillanders E, Seminara D, Antoniou AC, Pharoah PD, Chenevix-Trench G, Chanock SJ, Simard J, and Easton DF
- Subjects
- Female, Genotype, Humans, Male, Neoplasms epidemiology, Neoplasms physiopathology, Prevalence, Prognosis, Risk Assessment, Selection, Genetic, Genetic Predisposition to Disease epidemiology, Genetic Variation genetics, Genome-Wide Association Study methods, Neoplasms genetics, Polymorphism, Single Nucleotide genetics
- Abstract
Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits., Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background., Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis., Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures., Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR., Competing Interests: There are no conflicts of interest, (©2016 American Association for Cancer Research.)
- Published
- 2017
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37. Identification of activated enhancers and linked transcription factors in breast, prostate, and kidney tumors by tracing enhancer networks using epigenetic traits.
- Author
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Rhie SK, Guo Y, Tak YG, Yao L, Shen H, Coetzee GA, Laird PW, and Farnham PJ
- Subjects
- Breast Neoplasms genetics, Breast Neoplasms metabolism, Breast Neoplasms pathology, Cell Line, Tumor, DNA Methylation, DNA-Binding Proteins genetics, Female, GATA3 Transcription Factor genetics, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Histones genetics, Histones metabolism, Homeodomain Proteins antagonists & inhibitors, Homeodomain Proteins genetics, Homeodomain Proteins metabolism, Humans, Kidney Neoplasms genetics, Kidney Neoplasms metabolism, Kidney Neoplasms pathology, Male, Prostatic Neoplasms genetics, Prostatic Neoplasms metabolism, Prostatic Neoplasms pathology, RNA Interference, RNA, Small Interfering metabolism, Transcription Factors antagonists & inhibitors, Transcription Factors metabolism, Enhancer Elements, Genetic genetics, Epigenomics, Transcription Factors genetics
- Abstract
Background: Although technological advances now allow increased tumor profiling, a detailed understanding of the mechanisms leading to the development of different cancers remains elusive. Our approach toward understanding the molecular events that lead to cancer is to characterize changes in transcriptional regulatory networks between normal and tumor tissue. Because enhancer activity is thought to be critical in regulating cell fate decisions, we have focused our studies on distal regulatory elements and transcription factors that bind to these elements., Results: Using DNA methylation data, we identified more than 25,000 enhancers that are differentially activated in breast, prostate, and kidney tumor tissues, as compared to normal tissues. We then developed an analytical approach called Tracing Enhancer Networks using Epigenetic Traits that correlates DNA methylation levels at enhancers with gene expression to identify more than 800,000 genome-wide links from enhancers to genes and from genes to enhancers. We found more than 1200 transcription factors to be involved in these tumor-specific enhancer networks. We further characterized several transcription factors linked to a large number of enhancers in each tumor type, including GATA3 in non-basal breast tumors, HOXC6 and DLX1 in prostate tumors, and ZNF395 in kidney tumors. We showed that HOXC6 and DLX1 are associated with different clusters of prostate tumor-specific enhancers and confer distinct transcriptomic changes upon knockdown in C42B prostate cancer cells. We also discovered de novo motifs enriched in enhancers linked to ZNF395 in kidney tumors., Conclusions: Our studies characterized tumor-specific enhancers and revealed key transcription factors involved in enhancer networks for specific tumor types and subgroups. Our findings, which include a large set of identified enhancers and transcription factors linked to those enhancers in breast, prostate, and kidney cancers, will facilitate understanding of enhancer networks and mechanisms leading to the development of these cancers.
- Published
- 2016
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38. Enrichment of risk SNPs in regulatory regions implicate diverse tissues in Parkinson's disease etiology.
- Author
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Coetzee SG, Pierce S, Brundin P, Brundin L, Hazelett DJ, and Coetzee GA
- Subjects
- Chromosomes, Human, Gene Expression Regulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Parkinson Disease genetics, Promoter Regions, Genetic, Transcription Factors genetics, Transcription Factors metabolism, Parkinson Disease etiology, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Regulatory Sequences, Nucleic Acid
- Abstract
Recent genome-wide association studies (GWAS) of Parkinson's disease (PD) revealed at least 26 risk loci, with associated single nucleotide polymorphisms (SNPs) located in non-coding DNA having unknown functions in risk. In order to explore in which cell types these SNPs (and their correlated surrogates at r(2) ≥ 0.8) could alter cellular function, we assessed their location overlap with histone modification regions that indicate transcription regulation in 77 diverse cell types. We found statistically significant enrichment of risk SNPs at 12 loci in active enhancers or promoters. We investigated 4 risk loci in depth that were most significantly enriched (-logeP > 14) and contained 8 putative enhancers in the different cell types. These enriched loci, along with eQTL associations, were unexpectedly present in non-neuronal cell types. These included lymphocytes, mesendoderm, liver- and fat-cells, indicating that cell types outside the brain are involved in the genetic predisposition to PD. Annotating regulatory risk regions within specific cell types may unravel new putative risk mechanisms and molecular pathways that contribute to PD development.
- Published
- 2016
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39. 4C-seq revealed long-range interactions of a functional enhancer at the 8q24 prostate cancer risk locus.
- Author
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Cai M, Kim S, Wang K, Farnham PJ, Coetzee GA, and Lu W
- Subjects
- Cell Line, Tumor, Genome-Wide Association Study, Humans, Male, Chromosomes, Human, Pair 8 genetics, Chromosomes, Human, Pair 8 metabolism, Enhancer Elements, Genetic, Genetic Loci, Neoplasm Proteins genetics, Neoplasm Proteins metabolism, Prostatic Neoplasms genetics, Prostatic Neoplasms metabolism, Prostatic Neoplasms pathology, Transcription Factors genetics, Transcription Factors metabolism
- Abstract
Genome-wide association studies (GWAS) have identified >100 independent susceptibility loci for prostate cancer, including the hot spot at 8q24. However, how genetic variants at this locus confer disease risk hasn't been fully characterized. Using circularized chromosome conformation capture (4C) coupled with next-generation sequencing and an enhancer at 8q24 as "bait", we identified genome-wide partners interacting with this enhancer in cell lines LNCaP and C4-2B. These 4C-identified regions are distributed in open nuclear compartments, featuring active histone marks (H3K4me1, H3K4me2 and H3K27Ac). Transcription factors NKX3-1, FOXA1 and AR (androgen receptor) tend to occupy these 4C regions. We identified genes located at the interacting regions, and found them linked to positive regulation of mesenchymal cell proliferation in LNCaP and C4-2B, and several pathways (TGF beta signaling pathway in LNCaP and p53 pathway in C4-2B). Common genes (e.g. MYC and POU5F1B) were identified in both prostate cancer cell lines. However, each cell line also had exclusive genes (e.g. ELAC2 and PTEN in LNCaP and BRCA2 and ZFHX3 in C4-2B). In addition, BCL-2 identified in C4-2B might contribute to the progression of androgen-refractory prostate cancer. Overall, our work reveals key genes and pathways involved in prostate cancer onset and progression.
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- 2016
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40. Prostate Cancer Susceptibility in Men of African Ancestry at 8q24.
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Han Y, Rand KA, Hazelett DJ, Ingles SA, Kittles RA, Strom SS, Rybicki BA, Nemesure B, Isaacs WB, Stanford JL, Zheng W, Schumacher FR, Berndt SI, Wang Z, Xu J, Rohland N, Reich D, Tandon A, Pasaniuc B, Allen A, Quinque D, Mallick S, Notani D, Rosenfeld MG, Jayani RS, Kolb S, Gapstur SM, Stevens VL, Pettaway CA, Yeboah ED, Tettey Y, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Chokkalingam AP, John EM, Murphy AB, Signorello LB, Carpten J, Leske MC, Wu SY, Hennis AJM, Neslund-Dudas C, Hsing AW, Chu L, Goodman PJ, Klein EA, Zheng SL, Witte JS, Casey G, Lubwama A, Pooler LC, Sheng X, Coetzee GA, Cook MB, Chanock SJ, Stram DO, Watya S, Blot WJ, Conti DV, Henderson BE, and Haiman CA
- Subjects
- Aged, Aged, 80 and over, Case-Control Studies, Humans, Male, Middle Aged, RNA, Long Noncoding genetics, United States epidemiology, Black or African American genetics, Chromosomes, Human, Pair 8, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Prostatic Neoplasms genetics
- Abstract
The 8q24 region harbors multiple risk variants for distinct cancers, including >8 for prostate cancer. In this study, we conducted fine mapping of the 8q24 risk region (127.8-128.8Mb) in search of novel associations with common and rare variation in 4853 prostate cancer case patients and 4678 control subjects of African ancestry. All statistical tests were two-sided. We identified three independent associations at P values of less than 5.00×10(-8), all of which were replicated in studies from Ghana and Uganda (combined sample = 5869 case patients, 5615 control subjects; rs114798100: risk allele frequency [RAF] = 0.04, per-allele odds ratio [OR] = 2.31, 95% confidence interval [CI] = 2.04 to 2.61, P = 2.38×10(-40); rs72725879: RAF = 0.33, OR = 1.37, 95% CI = 1.30 to 1.45, P = 3.04×10(-27); and rs111906932: RAF = 0.03, OR = 1.79, 95% CI = 1.53 to 2.08, P = 1.39×10(-13)). Risk variants rs114798100 and rs111906923 are only found in men of African ancestry, with rs111906923 representing a novel association signal. The three variants are located within or near a number of prostate cancer-associated long noncoding RNAs (lncRNAs), including PRNCR1, PCAT1, and PCAT2. These findings highlight ancestry-specific risk variation and implicate prostate-specific lncRNAs at the 8q24 prostate cancer susceptibility region., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2016
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41. Reducing GWAS Complexity.
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Hazelett DJ, Conti DV, Han Y, Al Olama AA, Easton D, Eeles RA, Kote-Jarai Z, Haiman CA, and Coetzee GA
- Subjects
- Animals, Genome-Wide Association Study trends, Humans, Polymorphism, Single Nucleotide physiology, Genetic Predisposition to Disease genetics, Genome, Human genetics, Genome-Wide Association Study methods, Linkage Disequilibrium physiology
- Abstract
Genome-wide association studies (GWAS) have revealed numerous genomic 'hits' associated with complex phenotypes. In most cases these hits, along with surrogate genetic variation as measure by numerous single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium, are not in coding genes making assignment of functionality or causality intractable. Here we propose that fine-mapping along with the matching of risk SNPs at chromatin biofeatures lessen this complexity by reducing the number of candidate functional/causal SNPs. For example, we show here that only on average 2 SNPs per prostate cancer risk locus are likely candidates for functionality/causality; we further propose that this manageable number should be taken forward in mechanistic studies. The candidate SNPs can be looked up for each prostate cancer risk region in 2 recent publications in 2015 (1,2) from our groups.
- Published
- 2016
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42. The PsychENCODE project.
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Akbarian S, Liu C, Knowles JA, Vaccarino FM, Farnham PJ, Crawford GE, Jaffe AE, Pinto D, Dracheva S, Geschwind DH, Mill J, Nairn AC, Abyzov A, Pochareddy S, Prabhakar S, Weissman S, Sullivan PF, State MW, Weng Z, Peters MA, White KP, Gerstein MB, Amiri A, Armoskus C, Ashley-Koch AE, Bae T, Beckel-Mitchener A, Berman BP, Coetzee GA, Coppola G, Francoeur N, Fromer M, Gao R, Grennan K, Herstein J, Kavanagh DH, Ivanov NA, Jiang Y, Kitchen RR, Kozlenkov A, Kundakovic M, Li M, Li Z, Liu S, Mangravite LM, Mattei E, Markenscoff-Papadimitriou E, Navarro FC, North N, Omberg L, Panchision D, Parikshak N, Poschmann J, Price AJ, Purcaro M, Reddy TE, Roussos P, Schreiner S, Scuderi S, Sebra R, Shibata M, Shieh AW, Skarica M, Sun W, Swarup V, Thomas A, Tsuji J, van Bakel H, Wang D, Wang Y, Wang K, Werling DM, Willsey AJ, Witt H, Won H, Wong CC, Wray GA, Wu EY, Xu X, Yao L, Senthil G, Lehner T, Sklar P, and Sestan N
- Subjects
- Animals, Brain pathology, Chromosome Mapping methods, Humans, Mental Disorders diagnosis, Transcriptome genetics, Brain physiology, Chromosome Mapping trends, Epigenesis, Genetic genetics, Genetic Code genetics, Mental Disorders genetics
- Published
- 2015
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43. motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites.
- Author
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Coetzee SG, Coetzee GA, and Hazelett DJ
- Subjects
- Algorithms, Animals, Binding Sites, Genomics, Humans, Mice, Sequence Analysis, DNA, Mutation, Polymorphism, Single Nucleotide, Regulatory Elements, Transcriptional, Regulatory Sequences, Nucleic Acid, Software, Transcription Factors metabolism
- Abstract
Unlabelled: Functional annotation represents a key step toward the understanding and interpretation of germline and somatic variation as revealed by genome-wide association studies (GWAS) and The Cancer Genome Atlas (TCGA), respectively. GWAS have revealed numerous genetic risk variants residing in non-coding DNA associated with complex diseases. For sequences that lie within enhancers or promoters of transcription, it is not straightforward to assess the effects of variants on likely transcription factor binding sites. Consequently we introduce motifbreakR, which allows the biologist to judge whether the sequence surrounding a polymorphism or mutation is a good match, and how much information is gained or lost in one allele of the polymorphism or mutation relative to the other. MotifbreakR is flexible, giving a choice of algorithms for interrogation of genomes with motifs from many public sources that users can choose from. MotifbreakR can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within bioconductor., Availability and Implementation: https://github.com/Simon-Coetzee/MotifBreakR, www.bioconductor.org., Contact: dennis.hazelett@cshs.org., (© The Author 2015. Published by Oxford University Press.)
- Published
- 2015
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44. Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer.
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Lawrenson K, Iversen ES, Tyrer J, Weber RP, Concannon P, Hazelett DJ, Li Q, Marks JR, Berchuck A, Lee JM, Aben KK, Anton-Culver H, Antonenkova N, Bandera EV, Bean Y, Beckmann MW, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bruinsma F, Butzow R, Campbell IG, Carty K, Chang-Claude J, Chenevix-Trench G, Chen A, Chen Z, Cook LS, Cramer DW, Cunningham JM, Cybulski C, Plisiecka-Halasa J, Dennis J, Dicks E, Doherty JA, Dörk T, du Bois A, Eccles D, Easton DT, Edwards RP, Eilber U, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Goode EL, Goodman MT, Gronwald J, Harter P, Hasmad HN, Hein A, Heitz F, Hildebrandt MA, Hillemanns P, Hogdall E, Hogdall C, Hosono S, Jakubowska A, Paul J, Jensen A, Karlan BY, Kjaer SK, Kelemen LE, Kellar M, Kelley JL, Kiemeney LA, Krakstad C, Lambrechts D, Lambrechts S, Le ND, Lee AW, Cannioto R, Leminen A, Lester J, Levine DA, Liang D, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger LF, Matsuo K, McGuire V, McLaughlin JR, Nevanlinna H, McNeish I, Menon U, Modugno F, Moysich KB, Narod SA, Nedergaard L, Ness RB, Noor Azmi MA, Odunsi K, Olson SH, Orlow I, Orsulic S, Pearce CL, Pejovic T, Pelttari LM, Permuth-Wey J, Phelan CM, Pike MC, Poole EM, Ramus SJ, Risch HA, Rosen B, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Budzilowska A, Sellers TA, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Sucheston L, Tangen IL, Teo SH, Terry KL, Thompson PJ, Timorek A, Tworoger SS, Van Nieuwenhuysen E, Vergote I, Vierkant RA, Wang-Gohrke S, Walsh C, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Woo YL, Wu X, Wu AH, Yang H, Zheng W, Ziogas A, Coetzee GA, Freedman ML, Monteiro AN, Moes-Sosnowska J, Kupryjanczyk J, Pharoah PD, Gayther SA, and Schildkraut JM
- Subjects
- Carcinoma, Ovarian Epithelial, Case-Control Studies, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Checkpoint Kinase 2 genetics, Neoplasms, Glandular and Epithelial genetics, Ovarian Neoplasms genetics
- Abstract
Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
- Published
- 2015
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45. Corrigendum: genome-wide association study of colorectal cancer identifies six new susceptibility loci.
- Author
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Schumacher FR, Schmit SL, Jiao S, Edlund CK, Wang H, Zhang B, Hsu L, Huang SC, Fischer CP, Harju JF, Idos GE, Lejbkowicz F, Manion FJ, McDonnell K, McNeil CE, Melas M, Rennert HS, Shi W, Thomas DC, Van Den Berg DJ, Hutter CM, Aragaki AK, Butterbach K, Caan BJ, Carlson CS, Chanock SJ, Curtis KR, Fuchs CS, Gala M, Giovannucci EL, Gogarten SM, Hayes RB, Henderson B, Hunter DJ, Jackson RD, Kolonel LN, Kooperberg C, Küry S, LaCroix A, Laurie CC, Laurie CA, Lemire M, Levine D, Ma J, Makar KW, Qu C, Taverna D, Ulrich CM, Wu K, Kono S, West DW, Berndt SI, Bezieau S, Brenner H, Campbell PT, Chan AT, Chang-Claude J, Coetzee GA, Conti DV, Duggan D, Figueiredo JC, Fortini BK, Gallinger SJ, Gauderman WJ, Giles G, Green R, Haile R, Harrison TA, Hoffmeister M, Hopper JL, Hudson TJ, Jacobs E, Iwasaki M, Jee SH, Jenkins M, Jia WH, Joshi A, Li L, Lindor NM, Matsuo K, Moreno V, Mukherjee B, Newcomb PA, Potter JD, Raskin L, Rennert G, Rosse S, Severi G, Schoen RE, Seminara D, Shu XO, Slattery ML, Tsugane S, White E, Xiang YB, Zanke BW, Zheng W, Le Marchand L, Casey G, Gruber SB, and Peters U
- Published
- 2015
- Full Text
- View/download PDF
46. Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions.
- Author
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Han Y, Hazelett DJ, Wiklund F, Schumacher FR, Stram DO, Berndt SI, Wang Z, Rand KA, Hoover RN, Machiela MJ, Yeager M, Burdette L, Chung CC, Hutchinson A, Yu K, Xu J, Travis RC, Key TJ, Siddiq A, Canzian F, Takahashi A, Kubo M, Stanford JL, Kolb S, Gapstur SM, Diver WR, Stevens VL, Strom SS, Pettaway CA, Al Olama AA, Kote-Jarai Z, Eeles RA, Yeboah ED, Tettey Y, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Chokkalingam AP, Isaacs WB, Chen C, Lindstrom S, Le Marchand L, Giovannucci EL, Pomerantz M, Long H, Li F, Ma J, Stampfer M, John EM, Ingles SA, Kittles RA, Murphy AB, Blot WJ, Signorello LB, Zheng W, Albanes D, Virtamo J, Weinstein S, Nemesure B, Carpten J, Leske MC, Wu SY, Hennis AJ, Rybicki BA, Neslund-Dudas C, Hsing AW, Chu L, Goodman PJ, Klein EA, Zheng SL, Witte JS, Casey G, Riboli E, Li Q, Freedman ML, Hunter DJ, Gronberg H, Cook MB, Nakagawa H, Kraft P, Chanock SJ, Easton DF, Henderson BE, Coetzee GA, Conti DV, and Haiman CA
- Subjects
- Chromosome Mapping methods, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Molecular Sequence Annotation, Prostatic Neoplasms ethnology, Quantitative Trait Loci, Asian People genetics, Black People genetics, Hispanic or Latino genetics, Polymorphism, Single Nucleotide, Prostatic Neoplasms genetics, White People genetics
- Abstract
Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
- Published
- 2015
- Full Text
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47. Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.
- Author
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Amin Al Olama A, Dadaev T, Hazelett DJ, Li Q, Leongamornlert D, Saunders EJ, Stephens S, Cieza-Borrella C, Whitmore I, Benlloch Garcia S, Giles GG, Southey MC, Fitzgerald L, Gronberg H, Wiklund F, Aly M, Henderson BE, Schumacher F, Haiman CA, Schleutker J, Wahlfors T, Tammela TL, Nordestgaard BG, Key TJ, Travis RC, Neal DE, Donovan JL, Hamdy FC, Pharoah P, Pashayan N, Khaw KT, Stanford JL, Thibodeau SN, Mcdonnell SK, Schaid DJ, Maier C, Vogel W, Luedeke M, Herkommer K, Kibel AS, Cybulski C, Wokołorczyk D, Kluzniak W, Cannon-Albright L, Brenner H, Butterbach K, Arndt V, Park JY, Sellers T, Lin HY, Slavov C, Kaneva R, Mitev V, Batra J, Clements JA, Spurdle A, Teixeira MR, Paulo P, Maia S, Pandha H, Michael A, Kierzek A, Govindasami K, Guy M, Lophatonanon A, Muir K, Viñuela A, Brown AA, Freedman M, Conti DV, Easton D, Coetzee GA, Eeles RA, and Kote-Jarai Z
- Subjects
- Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Chromosome Mapping methods, Polymorphism, Single Nucleotide, Prostatic Neoplasms genetics, White People genetics
- Abstract
Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region., (© The Author 2015. Published by Oxford University Press.)
- Published
- 2015
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48. Genome-wide association study of colorectal cancer identifies six new susceptibility loci.
- Author
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Schumacher FR, Schmit SL, Jiao S, Edlund CK, Wang H, Zhang B, Hsu L, Huang SC, Fischer CP, Harju JF, Idos GE, Lejbkowicz F, Manion FJ, McDonnell K, McNeil CE, Melas M, Rennert HS, Shi W, Thomas DC, Van Den Berg DJ, Hutter CM, Aragaki AK, Butterbach K, Caan BJ, Carlson CS, Chanock SJ, Curtis KR, Fuchs CS, Gala M, Giovannucci EL, Gogarten SM, Hayes RB, Henderson B, Hunter DJ, Jackson RD, Kolonel LN, Kooperberg C, Küry S, LaCroix A, Laurie CC, Laurie CA, Lemire M, Levine D, Ma J, Makar KW, Qu C, Taverna D, Ulrich CM, Wu K, Kono S, West DW, Berndt SI, Bezieau S, Brenner H, Campbell PT, Chan AT, Chang-Claude J, Coetzee GA, Conti DV, Duggan D, Figueiredo JC, Fortini BK, Gallinger SJ, Gauderman WJ, Giles G, Green R, Haile R, Harrison TA, Hoffmeister M, Hopper JL, Hudson TJ, Jacobs E, Iwasaki M, Jee SH, Jenkins M, Jia WH, Joshi A, Li L, Lindor NM, Matsuo K, Moreno V, Mukherjee B, Newcomb PA, Potter JD, Raskin L, Rennert G, Rosse S, Severi G, Schoen RE, Seminara D, Shu XO, Slattery ML, Tsugane S, White E, Xiang YB, Zanke BW, Zheng W, Le Marchand L, Casey G, Gruber SB, and Peters U
- Subjects
- Case-Control Studies, Humans, Odds Ratio, Polymorphism, Single Nucleotide, Colorectal Neoplasms genetics, Genetic Predisposition to Disease, Genome-Wide Association Study
- Abstract
Genetic susceptibility to colorectal cancer is caused by rare pathogenic mutations and common genetic variants that contribute to familial risk. Here we report the results of a two-stage association study with 18,299 cases of colorectal cancer and 19,656 controls, with follow-up of the most statistically significant genetic loci in 4,725 cases and 9,969 controls from two Asian consortia. We describe six new susceptibility loci reaching a genome-wide threshold of P<5.0E-08. These findings provide additional insight into the underlying biological mechanisms of colorectal cancer and demonstrate the scientific value of large consortia-based genetic epidemiology studies.
- Published
- 2015
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49. Cell-type-specific enrichment of risk-associated regulatory elements at ovarian cancer susceptibility loci.
- Author
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Coetzee SG, Shen HC, Hazelett DJ, Lawrenson K, Kuchenbaecker K, Tyrer J, Rhie SK, Levanon K, Karst A, Drapkin R, Ramus SJ, Couch FJ, Offit K, Chenevix-Trench G, Monteiro AN, Antoniou A, Freedman M, Coetzee GA, Pharoah PD, Noushmehr H, and Gayther SA
- Subjects
- Chromatin genetics, Chromatin metabolism, Female, Genome-Wide Association Study, Histones genetics, Histones metabolism, Humans, Organ Specificity, Ovarian Neoplasms metabolism, Polymorphism, Single Nucleotide, Regulatory Sequences, Nucleic Acid, Genetic Predisposition to Disease, Ovarian Neoplasms genetics
- Abstract
Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most single-nucleotide polymorphisms (SNPs) associated with cancer risk lie in non-protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs) and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared with normal human mammary epithelial cells and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissue-specific regulatory signatures compared to non-gynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P = 3.8 × 10(-30)), OSECs (P = 2.4 × 10(-23)) and HMECs (P = 6.7 × 10(-15)) but not for EECs (P = 0.45) or LNCaP cells (P = 0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) suggesting both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets of germline genetic susceptibility variants for ovarian cancer., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
- Published
- 2015
- Full Text
- View/download PDF
50. Identification of a Novel Mucin Gene HCG22 Associated With Steroid-Induced Ocular Hypertension.
- Author
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Jeong S, Patel N, Edlund CK, Hartiala J, Hazelett DJ, Itakura T, Wu PC, Avery RL, Davis JL, Flynn HW, Lalwani G, Puliafito CA, Wafapoor H, Hijikata M, Keicho N, Gao X, Argüeso P, Allayee H, Coetzee GA, Pletcher MT, Conti DV, Schwartz SG, Eaton AM, and Fini ME
- Subjects
- Adult, Female, Follow-Up Studies, Genome-Wide Association Study, Genotype, Glucocorticoids adverse effects, Humans, Male, Middle Aged, Mucins biosynthesis, Ocular Hypertension chemically induced, Ocular Hypertension metabolism, Trabecular Meshwork metabolism, Gene Expression Regulation, Intraocular Pressure drug effects, Mucins genetics, Ocular Hypertension genetics, RNA, Messenger genetics, Triamcinolone adverse effects
- Abstract
Purpose: The pathophysiology of ocular hypertension (OH) leading to primary open-angle glaucoma shares many features with a secondary form of OH caused by treatment with glucocorticoids, but also exhibits distinct differences. In this study, a pharmacogenomics approach was taken to discover candidate genes for this disorder., Methods: A genome-wide association study was performed, followed by an independent candidate gene study, using a cohort enrolled from patients treated with off-label intravitreal triamcinolone, and handling change in IOP as a quantitative trait., Results: An intergenic quantitative trait locus (QTL) was identified at chromosome 6p21.33 near the 5' end of HCG22 that attained the accepted statistical threshold for genome-level significance. The HCG22 transcript, encoding a novel mucin protein, was expressed in trabecular meshwork cells, and expression was stimulated by IL-1, and inhibited by triamcinolone acetate and TGF-β. Bioinformatic analysis defined the QTL as an approximately 4 kilobase (kb) linkage disequilibrium block containing 10 common single nucleotide polymorphisms (SNPs). Four of these SNPs were identified in the National Center for Biotechnology Information (NCBI) GTEx eQTL browser as modifiers of HCG22 expression. Most are predicted to disrupt or improve motifs for transcription factor binding, the most relevant being disruption of the glucocorticoid receptor binding motif. A second QTL was identified within the predicted signal peptide of the HCG22 encoded protein that could affect its secretion. Translation, O-glycosylation, and secretion of the predicted HCG22 protein was verified in cultured trabecular meshwork cells., Conclusions: Identification of two independent QTLs that could affect expression of the HCG22 mucin gene product via two different mechanisms (transcription or secretion) is highly suggestive of a role in steroid-induced OH.
- Published
- 2015
- Full Text
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