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291 results on '"McVean, G"'

1. A frequent ancestral NFKB1 variant predicts risk of infection or allergy

Author

Chong, A. Y., primary, Brenner, N., additional, Jimenez-Kaufmann, A., additional, Cortes, A., additional, Hill, M., additional, Littlejohns, T. J., additional, Gilchrist, J. J., additional, Fairfax, B. P., additional, Knight, J. C., additional, Hodel, F., additional, Fellay, J., additional, McVean, G., additional, Moreno-Estrada, A., additional, Waterboer, T., additional, Hill, A. V. S., additional, and Mentzer, A. J., additional

Published
2022
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3. Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Author

Romagnoni, A., Jegou, S., Van Steen, K., Wainrib, G., Hugot, J. -P., Peyrin-Biroulet, L., Chamaillard, M., Colombel, J. -F., Cottone, M., D'Amato, M., D'Inca, R., Halfvarson, J., Henderson, P., Karban, A., Kennedy, N. A., Khan, M. A., Lemann, M., Levine, A., Massey, D., Milla, M., S. M. E., Ng, Oikonomou, I., Peeters, H., Proctor, D. D., Rahier, J. -F., Rutgeerts, P., Seibold, F., Stronati, L., Taylor, K. M., Torkvist, L., Ublick, K., Van Limbergen, J., Van Gossum, A., Vatn, M. H., Zhang, H., Zhang, W., Andrews, J. M., Bampton, P. A., Barclay, M., Florin, T. H., Gearry, R., Krishnaprasad, K., Lawrance, I. C., Mahy, G., Montgomery, G. W., Radford-Smith, G., Roberts, R. L., Simms, L. A., Hanigan, K., Croft, A., Amininijad, L., Cleynen, I., Dewit, O., Franchimont, D., Georges, M., Laukens, D., Theatre, E., Vermeire, S., Aumais, G., Baidoo, L., Barrie, A. M., Beck, K., Bernard, E. -J., Binion, D. G., Bitton, A., Brant, S. R., Cho, J. H., Cohen, A., Croitoru, K., Daly, M. J., Datta, L. W., Deslandres, C., Duerr, R. H., Dutridge, D., Ferguson, J., Fultz, J., Goyette, P., Greenberg, G. R., Haritunians, T., Jobin, G., Katz, S., Lahaie, R. G., Mcgovern, D. P., Nelson, L., S. M., Ng, Ning, K., Pare, P., Regueiro, M. D., Rioux, J. D., Ruggiero, E., Schumm, L. P., Schwartz, M., Scott, R., Sharma, Y., Silverberg, M. S., Spears, D., Steinhart, A. H., Stempak, J. M., Swoger, J. M., Tsagarelis, C., Zhang, C., Zhao, H., Aerts, J., Ahmad, T., Arbury, H., Attwood, A., Auton, A., Ball, S. G., Balmforth, A. J., Barnes, C., Barrett, J. C., Barroso, I., Barton, A., Bennett, A. J., Bhaskar, S., Blaszczyk, K., Bowes, J., Brand, O. J., Braund, P. S., Bredin, F., Breen, G., Brown, M. J., Bruce, I. N., Bull, J., Burren, O. S., Burton, J., Byrnes, J., Caesar, S., Cardin, N., Clee, C. M., Coffey, A. J., MC Connell, J., Conrad, D. F., Cooper, J. D., Dominiczak, A. F., Downes, K., Drummond, H. E., Dudakia, D., Dunham, A., Ebbs, B., Eccles, D., Edkins, S., Edwards, C., Elliot, A., Emery, P., Evans, D. M., Evans, G., Eyre, S., Farmer, A., Ferrier, I. N., Flynn, E., Forbes, A., Forty, L., Franklyn, J. A., Frayling, T. M., Freathy, R. M., Giannoulatou, E., Gibbs, P., Gilbert, P., Gordon-Smith, K., Gray, E., Green, E., Groves, C. J., Grozeva, D., Gwilliam, R., Hall, A., Hammond, N., Hardy, M., Harrison, P., Hassanali, N., Hebaishi, H., Hines, S., Hinks, A., Hitman, G. A., Hocking, L., Holmes, C., Howard, E., Howard, P., Howson, J. M. M., Hughes, D., Hunt, S., Isaacs, J. D., Jain, M., Jewell, D. P., Johnson, T., Jolley, J. D., Jones, I. R., Jones, L. A., Kirov, G., Langford, C. F., Lango-Allen, H., Lathrop, G. M., Lee, J., Lee, K. L., Lees, C., Lewis, K., Lindgren, C. M., Maisuria-Armer, M., Maller, J., Mansfield, J., Marchini, J. L., Martin, P., Massey, D. C., Mcardle, W. L., Mcguffin, P., Mclay, K. E., Mcvean, G., Mentzer, A., Mimmack, M. L., Morgan, A. E., Morris, A. P., Mowat, C., Munroe, P. B., Myers, S., Newman, W., Nimmo, E. R., O'Donovan, M. C., Onipinla, A., Ovington, N. R., Owen, M. J., Palin, K., Palotie, A., Parnell, K., Pearson, R., Pernet, D., Perry, J. R., Phillips, A., Plagnol, V., Prescott, N. J., Prokopenko, I., Quail, M. A., Rafelt, S., Rayner, N. W., Reid, D. M., Renwick, A., Ring, S. M., Robertson, N., Robson, S., Russell, E., Clair, D. S., Sambrook, J. G., Sanderson, J. D., Sawcer, S. J., Schuilenburg, H., Scott, C. E., Seal, S., Shaw-Hawkins, S., Shields, B. M., Simmonds, M. J., Smyth, D. J., Somaskantharajah, E., Spanova, K., Steer, S., Stephens, J., Stevens, H. E., Stirrups, K., Stone, M. A., Strachan, D. P., Su, Z., Symmons, D. P. M., Thompson, J. R., Thomson, W., Tobin, M. D., Travers, M. E., Turnbull, C., Vukcevic, D., Wain, L. V., Walker, M., Walker, N. M., Wallace, C., Warren-Perry, M., Watkins, N. A., Webster, J., Weedon, M. N., Wilson, A. G., Woodburn, M., Wordsworth, B. P., Yau, C., Young, A. H., Zeggini, E., Brown, M. A., Burton, P. R., Caulfield, M. J., Compston, A., Farrall, M., Gough, S. C. L., Hall, A. S., Hattersley, A. T., Hill, A. V. S., Mathew, C. G., Pembrey, M., Satsangi, J., Stratton, M. R., Worthington, J., Hurles, M. E., Duncanson, A., Ouwehand, W. H., Parkes, M., Rahman, N., Todd, J. A., Samani, N. J., Kwiatkowski, D. P., Mccarthy, M. I., Craddock, N., Deloukas, P., Donnelly, P., Blackwell, J. M., Bramon, E., Casas, J. P., Corvin, A., Jankowski, J., Markus, H. S., Palmer, C. N., Plomin, R., Rautanen, A., Trembath, R. C., Viswanathan, A. C., Wood, N. W., Spencer, C. C. A., Band, G., Bellenguez, C., Freeman, C., Hellenthal, G., Pirinen, M., Strange, A., Blackburn, H., Bumpstead, S. J., Dronov, S., Gillman, M., Jayakumar, A., Mccann, O. T., Liddle, J., Potter, S. C., Ravindrarajah, R., Ricketts, M., Waller, M., Weston, P., Widaa, S., Whittaker, P., Romagnoni, A., Jegou, S., Van Steen, K., Wainrib, G., Hugot, J. -P., Peyrin-Biroulet, L., Chamaillard, M., Colombel, J. -F., Cottone, M., D'Amato, M., D'Inca, R., Halfvarson, J., Henderson, P., Karban, A., Kennedy, N. A., Khan, M. A., Lemann, M., Levine, A., Massey, D., Milla, M., Ng, S. M. E., Oikonomou, I., Peeters, H., Proctor, D. D., Rahier, J. -F., Rutgeerts, P., Seibold, F., Stronati, L., Taylor, K. M., Torkvist, L., Ublick, K., Van Limbergen, J., Van Gossum, A., Vatn, M. H., Zhang, H., Zhang, W., Andrews, J. M., Bampton, P. A., Barclay, M., Florin, T. H., Gearry, R., Krishnaprasad, K., Lawrance, I. C., Mahy, G., Montgomery, G. W., Radford-Smith, G., Roberts, R. L., Simms, L. A., Hanigan, K., Croft, A., Amininijad, L., Cleynen, I., Dewit, O., Franchimont, D., Georges, M., Laukens, D., Theatre, E., Vermeire, S., Aumais, G., Baidoo, L., Barrie, A. M., Beck, K., Bernard, E. -J., Binion, D. G., Bitton, A., Brant, S. R., Cho, J. H., Cohen, A., Croitoru, K., Daly, M. J., Datta, L. W., Deslandres, C., Duerr, R. H., Dutridge, D., Ferguson, J., Fultz, J., Goyette, P., Greenberg, G. R., Haritunians, T., Jobin, G., Katz, S., Lahaie, R. G., Mcgovern, D. P., Nelson, L., Ng, S. M., Ning, K., Pare, P., Regueiro, M. D., Rioux, J. D., Ruggiero, E., Schumm, L. P., Schwartz, M., Scott, R., Sharma, Y., Silverberg, M. S., Spears, D., Steinhart, A. H., Stempak, J. M., Swoger, J. M., Tsagarelis, C., Zhang, C., Zhao, H., Aerts, J., Ahmad, T., Arbury, H., Attwood, A., Auton, A., Ball, S. G., Balmforth, A. J., Barnes, C., Barrett, J. C., Barroso, I., Barton, A., Bennett, A. J., Bhaskar, S., Blaszczyk, K., Bowes, J., Brand, O. J., Braund, P. S., Bredin, F., Breen, G., Brown, M. J., Bruce, I. N., Bull, J., Burren, O. S., Burton, J., Byrnes, J., Caesar, S., Cardin, N., Clee, C. M., Coffey, A. J., MC Connell, J., Conrad, D. F., Cooper, J. D., Dominiczak, A. F., Downes, K., Drummond, H. E., Dudakia, D., Dunham, A., Ebbs, B., Eccles, D., Edkins, S., Edwards, C., Elliot, A., Emery, P., Evans, D. M., Evans, G., Eyre, S., Farmer, A., Ferrier, I. N., Flynn, E., Forbes, A., Forty, L., Franklyn, J. A., Frayling, T. M., Freathy, R. M., Giannoulatou, E., Gibbs, P., Gilbert, P., Gordon-Smith, K., Gray, E., Green, E., Groves, C. J., Grozeva, D., Gwilliam, R., Hall, A., Hammond, N., Hardy, M., Harrison, P., Hassanali, N., Hebaishi, H., Hines, S., Hinks, A., Hitman, G. A., Hocking, L., Holmes, C., Howard, E., Howard, P., Howson, J. M. M., Hughes, D., Hunt, S., Isaacs, J. D., Jain, M., Jewell, D. P., Johnson, T., Jolley, J. D., Jones, I. R., Jones, L. A., Kirov, G., Langford, C. F., Lango-Allen, H., Lathrop, G. M., Lee, J., Lee, K. L., Lees, C., Lewis, K., Lindgren, C. M., Maisuria-Armer, M., Maller, J., Mansfield, J., Marchini, J. L., Martin, P., Massey, D. C., Mcardle, W. L., Mcguffin, P., Mclay, K. E., Mcvean, G., Mentzer, A., Mimmack, M. L., Morgan, A. E., Morris, A. P., Mowat, C., Munroe, P. B., Myers, S., Newman, W., Nimmo, E. R., O'Donovan, M. C., Onipinla, A., Ovington, N. R., Owen, M. J., Palin, K., Palotie, A., Parnell, K., Pearson, R., Pernet, D., Perry, J. R., Phillips, A., Plagnol, V., Prescott, N. J., Prokopenko, I., Quail, M. A., Rafelt, S., Rayner, N. W., Reid, D. M., Renwick, A., Ring, S. M., Robertson, N., Robson, S., Russell, E., Clair, D. S., Sambrook, J. G., Sanderson, J. D., Sawcer, S. J., Schuilenburg, H., Scott, C. E., Seal, S., Shaw-Hawkins, S., Shields, B. M., Simmonds, M. J., Smyth, D. J., Somaskantharajah, E., Spanova, K., Steer, S., Stephens, J., Stevens, H. E., Stirrups, K., Stone, M. A., Strachan, D. P., Su, Z., Symmons, D. P. M., Thompson, J. R., Thomson, W., Tobin, M. D., Travers, M. E., Turnbull, C., Vukcevic, D., Wain, L. V., Walker, M., Walker, N. M., Wallace, C., Warren-Perry, M., Watkins, N. A., Webster, J., Weedon, M. N., Wilson, A. G., Woodburn, M., Wordsworth, B. P., Yau, C., Young, A. H., Zeggini, E., Brown, M. A., Burton, P. R., Caulfield, M. J., Compston, A., Farrall, M., Gough, S. C. L., Hall, A. S., Hattersley, A. T., Hill, A. V. S., Mathew, C. G., Pembrey, M., Satsangi, J., Stratton, M. R., Worthington, J., Hurles, M. E., Duncanson, A., Ouwehand, W. H., Parkes, M., Rahman, N., Todd, J. A., Samani, N. J., Kwiatkowski, D. P., Mccarthy, M. I., Craddock, N., Deloukas, P., Donnelly, P., Blackwell, J. M., Bramon, E., Casas, J. P., Corvin, A., Jankowski, J., Markus, H. S., Palmer, C. N., Plomin, R., Rautanen, A., Trembath, R. C., Viswanathan, A. C., Wood, N. W., Spencer, C. C. A., Band, G., Bellenguez, C., Freeman, C., Hellenthal, G., Pirinen, M., Strange, A., Blackburn, H., Bumpstead, S. J., Dronov, S., Gillman, M., Jayakumar, A., Mccann, O. T., Liddle, J., Potter, S. C., Ravindrarajah, R., Ricketts, M., Waller, M., Weston, P., Widaa, S., Whittaker, P., Daly, Mark J. [0000-0002-0949-8752], Apollo - University of Cambridge Repository, Hugot, Jean-Pierre [0000-0002-8446-6056], UCL - SSS/IREC/GAEN - Pôle d'Hépato-gastro-entérologie, UCL - (MGD) Service de gastro-entérologie, Romagnoni, A, Jegou, S, VAN STEEN, Kristel, Wainrib, G, Hugot, JP, Peyrin-Biroulet, L, Chamaillard, M, Colombel, JF, Cottone, M, D'Amato, M, D'Inca, R, Halfvarson, J, Henderson, P, Karban, A, Kennedy, NA, Khan, MA, Lemann, M, Levine, A, Massey, D, Milla, M, Ng, SME, Oikonomou, I, Peeters, H, Proctor, DD, Rahier, JF, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, KM, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, MH, Zhang, H, Zhang, W, Andrews, JM, Bampton, PA, Barclay, M, Florin, TH, Gearry, R, Krishnaprasad, K, Lawrance, IC, Mahy, G, Montgomery, GW, Radford-Smith, G, Roberts, RL, Simms, LA, Hanigan, K, Croft, A, Amininijad, L, Cleynen, I, Dewit, O, Franchimont, D, Georges, M, Laukens, D, Theatre, E, Vermeire, S, Aumais, G, Baidoo, L, Barrie, AM, Beck, K, Bernard, EJ, Binion, DG, Bitton, A, Brant, SR, Cho, JH, Cohen, A, Croitoru, K, Daly, MJ, Datta, LW, Deslandres, C, Duerr, RH, Dutridge, D, Ferguson, J, Fultz, J, Goyette, P, Greenberg, GR, Haritunians, T, Jobin, G, Katz, S, Lahaie, RG, McGovern, DP, Nelson, L, Ng, SM, Ning, K, Pare, P, Regueiro, MD, Rioux, JD, Ruggiero, E, Schumm, LP, Schwartz, M, Scott, R, Sharma, Y, Silverberg, MS, Spears, D, Steinhart, AH, Stempak, JM, Swoger, JM, Tsagarelis, C, Zhang, C, Zhao, HY, AERTS, Jan, Ahmad, T, Arbury, H, Attwood, A, Auton, A, Ball, SG, Balmforth, AJ, Barnes, C, Barrett, JC, Barroso, I, Barton, A, Bennett, AJ, Bhaskar, S, Blaszczyk, K, Bowes, J, Brand, OJ, Braund, PS, Bredin, F, Breen, G, Brown, MJ, Bruce, IN, Bull, J, Burren, OS, Burton, J, Byrnes, J, Caesar, S, Cardin, N, Clee, CM, Coffey, AJ, Mc Connell, J, Conrad, DF, Cooper, JD, Dominiczak, AF, Downes, K, Drummond, HE, Dudakia, D, Dunham, A, Ebbs, B, Eccles, D, Edkins, S, Edwards, C, Elliot, A, Emery, P, Evans, DM, Evans, G, Eyre, S, Farmer, A, Ferrier, IN, Flynn, E, Forbes, A, Forty, L, Franklyn, JA, Frayling, TM, Freathy, RM, Giannoulatou, E, Gibbs, P, Gilbert, P, Gordon-Smith, K, Gray, E, Green, E, Groves, CJ, Grozeva, D, Gwilliam, R, Hall, A, Hammond, N, Hardy, M, Harrison, P, Hassanali, N, Hebaishi, H, Hines, S, Hinks, A, Hitman, GA, Hocking, L, Holmes, C, Howard, E, Howard, P, Howson, JMM, Hughes, D, Hunt, S, Isaacs, JD, Jain, M, Jewell, DP, Johnson, T, Jolley, JD, Jones, IR, Jones, LA, Kirov, G, Langford, CF, Lango-Allen, H, Lathrop, GM, Lee, J, Lee, KL, Lees, C, Lewis, K, Lindgren, CM, Maisuria-Armer, M, Maller, J, Mansfield, J, Marchini, JL, Martin, P, Massey, DCO, McArdle, WL, McGuffin, P, McLay, KE, McVean, G, Mentzer, A, Mimmack, ML, Morgan, AE, Morris, AP, Mowat, C, Munroe, PB, Myers, S, Newman, W, Nimmo, ER, O'Donovan, MC, Onipinla, A, Ovington, NR, Owen, MJ, Palin, K, Palotie, A, Parnell, K, Pearson, R, Pernet, D, Perry, JRB, Phillips, A, Plagnol, V, Prescott, NJ, Prokopenko, I, Quail, MA, Rafelt, S, Rayner, NW, Reid, DM, Renwick, A, Ring, SM, Robertson, N, Robson, S, Russell, E, St Clair, D, Sambrook, JG, Sanderson, JD, Sawcer, SJ, Schuilenburg, H, Scott, CE, Seal, S, Shaw-Hawkins, S, Shields, BM, Simmonds, MJ, Smyth, DJ, Somaskantharajah, E, Spanova, K, Steer, S, Stephens, J, Stevens, HE, Stirrups, K, Stone, MA, Strachan, DP, Su, Z, Symmons, DPM, Thompson, JR, Thomson, W, Tobin, MD, Travers, ME, Turnbull, C, Vukcevic, D, Wain, LV, Walker, M, Walker, NM, Wallace, C, Warren-Perry, M, Watkins, NA, Webster, J, Weedon, MN, Wilson, AG, Woodburn, M, Wordsworth, BP, Yau, C, Young, AH, Zeggini, E, Brown, MA, Burton, PR, Caulfield, MJ, Compston, A, Farrall, M, Gough, SCL, Hall, AS, Hattersley, AT, Hill, AVS, Mathew, CG, Pembrey, M, Satsangi, J, Stratton, MR, Worthington, J, Hurles, ME, Duncanson, A, Ouwehand, WH, Parkes, M, Rahman, N, Todd, JA, Samani, NJ, Kwiatkowski, DP, McCarthy, MI, Craddock, N, Deloukas, P, Donnelly, P, Blackwell, JM, Bramon, E, Casas, JP, Corvin, A, Jankowski, J, Markus, HS, Palmer, CNA, Plomin, R, Rautanen, A, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Pirinen, M, Strange, A, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, and Kwiatkowski, D

Subjects
Male, 692/4020/1503/257/1402, Genotype, Genotyping Techniques, LOCI, 45/43, lcsh:Medicine, Polymorphism, Single Nucleotide, Crohn's disease, genetics, genome wide association, Article, Deep Learning, Crohn Disease, INDEL Mutation, Genetics research, Humans, genetics, Genetic Predisposition to Disease, 129, lcsh:Science, Alleles, Science & Technology, genome wide association, RISK PREDICTION, 45, Models, Genetic, lcsh:R, Decision Trees, 692/308/2056, ASSOCIATION, Multidisciplinary Sciences, Crohn's disease, Logistic Models, Nonlinear Dynamics, ROC Curve, Area Under Curve, Science & Technology - Other Topics, lcsh:Q, Female, Neural Networks, Computer, INFLAMMATORY-BOWEL-DISEASE, Genome-Wide Association Study
Abstract

Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers. Tis work was supported by Fondation pour la Recherche Médical (ref DEI20151234405) and Investissements d’Avenir programme ANR-11-IDEX-0005-02, Sorbonne Paris Cite, Laboratoire d’excellence INFLAMEX. Te authors thank the students that participated to the wisdom of the crowd exercise.

Published
2019

4. Genome-wide analysis of 53,400 people with irritable bowel syndrome highlights shared genetic pathways with mood and anxiety disorders.

Author

Eijsbouts, C, Zheng, T, Kennedy, NA, Bonfiglio, F, Anderson, CA, Moutsianas, L, Holliday, J, Shi, J, Shringarpure, S, 23andMe Research Team, Voda, A-I, Bellygenes Initiative, Farrugia, G, Franke, A, Hübenthal, M, Abecasis, G, Zawistowski, M, Skogholt, AH, Ness-Jensen, E, Hveem, K, Esko, T, Teder-Laving, M, Zhernakova, A, Camilleri, M, Boeckxstaens, G, Whorwell, PJ, Spiller, R, McVean, G, D'Amato, M, Jostins, L, Parkes, M, Eijsbouts, C, Zheng, T, Kennedy, NA, Bonfiglio, F, Anderson, CA, Moutsianas, L, Holliday, J, Shi, J, Shringarpure, S, 23andMe Research Team, Voda, A-I, Bellygenes Initiative, Farrugia, G, Franke, A, Hübenthal, M, Abecasis, G, Zawistowski, M, Skogholt, AH, Ness-Jensen, E, Hveem, K, Esko, T, Teder-Laving, M, Zhernakova, A, Camilleri, M, Boeckxstaens, G, Whorwell, PJ, Spiller, R, McVean, G, D'Amato, M, Jostins, L, and Parkes, M

Abstract

Irritable bowel syndrome (IBS) results from disordered brain-gut interactions. Identifying susceptibility genes could highlight the underlying pathophysiological mechanisms. We designed a digestive health questionnaire for UK Biobank and combined identified cases with IBS with independent cohorts. We conducted a genome-wide association study with 53,400 cases and 433,201 controls and replicated significant associations in a 23andMe panel (205,252 cases and 1,384,055 controls). Our study identified and confirmed six genetic susceptibility loci for IBS. Implicated genes included NCAM1, CADM2, PHF2/FAM120A, DOCK9, CKAP2/TPTE2P3 and BAG6. The first four are associated with mood and anxiety disorders, expressed in the nervous system, or both. Mirroring this, we also found strong genome-wide correlation between the risk of IBS and anxiety, neuroticism and depression (rg > 0.5). Additional analyses suggested this arises due to shared pathogenic pathways rather than, for example, anxiety causing abdominal symptoms. Implicated mechanisms require further exploration to help understand the altered brain-gut interactions underlying IBS.

Published
2021

5. Accounting for long-range correlations in genome-wide simulations of large cohorts

Author

Nelson, D, Kelleher, J, Ragsdale, AP, Moreau, C, McVean, G, and Gravel, S

Subjects
Cancer Research, Heredity, Population genetics, QH426-470, Biochemistry, Linkage Disequilibrium, Coalescent theory, Cohort Studies, 0302 clinical medicine, Effective population size, Range (statistics), Quantitative Biology::Populations and Evolution, Genome Evolution, Genetics (clinical), Recombination, Genetic, 0303 health sciences, Genome, Simulation and Modeling, Population size, Genomics, Quantitative Biology::Genomics, Nucleic acids, Algorithms, Research Article, Genome evolution, DNA recombination, Population Size, Demographic history, Biology, Research and Analysis Methods, Molecular Evolution, Evolution, Molecular, 03 medical and health sciences, Population Metrics, Effective Population Size, Genetics, Humans, Computer Simulation, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Evolutionary Biology, Base Sequence, Models, Genetic, Biology and life sciences, Population Biology, Computational Biology, DNA, Genetics, Population, Sample size determination, Evolutionary biology, Sample Size, Genetic Polymorphism, Population Genetics, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Coalescent simulations are widely used to examine the effects of evolution and demographic history on the genetic makeup of populations. Thanks to recent progress in algorithms and data structures, simulators such as the widely-used msprime now provide genome-wide simulations for millions of individuals. However, this software relies on classic coalescent theory and its assumptions that sample sizes are small and that the region being simulated is short. Here we show that coalescent simulations of long regions of the genome exhibit large biases in identity-by-descent (IBD), long-range linkage disequilibrium (LD), and ancestry patterns, particularly when the sample size is large. We present a Wright-Fisher extension to msprime, and show that it produces more realistic distributions of IBD, LD, and ancestry proportions, while also addressing more subtle biases of the coalescent. Further, these extensions are more computationally efficient than state-of-the-art coalescent simulations when simulating long regions, including whole-genome data. For shorter regions, efficiency can be maintained via a hybrid model which simulates the recent past under the Wright-Fisher model and uses coalescent simulations in the distant past., Author summary Coalescent theory has provided deep theoretical insight into patterns of human diversity. Implementations of coalescent models in simulation software such as ms have further provided tools to interpret thousands of genomic studies. Recent technical progress has allowed for a dramatic increase in the scale at which genomes can be both measured and simulated, opening up opportunities for a finer understanding of evolutionary biology. However, we show that coalescent simulations of long regions of the genome exhibit large biases in sample relatedness, distorting haplotype sharing and ancestry patterns in simulated cohorts. We trace these biases to basic assumptions of the coalescent model, and show how the assumptions can be relaxed to provide a better description of the observed patterns of genetic polymorphism at a fraction of the computational cost.

Published
2020

6. Estimating meiotic gene conversion rates from population genetic data

Author

Gay, J., Myers, S., and McVean, G.

Subjects
Genetic variation -- Measurement, Population genetics -- Research, Haplotypes -- Properties, Haplotypes -- Models, Crossing over (Genetics) -- Models, Genetic transformation -- Measurement, Biological sciences
Abstract

Gene conversion plays an important part in shaping genetic diversity in populations, yet estimating the rate at which it occurs is difficult because of the short lengths of DNA involved. We have developed a new statistical approach to estimating gene conversion rates from genetic variation, by extending an existing model for haplotype data in the presence of crossover events. We show, by simulation, that when the rate of gene conversion events is at least comparable to the rate of crossover events, the method provides a powerful approach to the detection of gene conversion and estimation of its rate. Application of the method to data from the telomeric X chromosome of Drosophila melanogastes, in which crossover activity is suppressed, indicates that gene conversion occurs ~400 times more often than crossover events. We also extend the method to estimating variable crossover and gene conversion rates and estimate the rate of gene conversion to be ~1.5 times higher than the crossover rate in a region of human chromosome 1 with known recombination hotspots.

Published
2007

7. The DNA sequence and biological annotation of human chromosome 1

Author

Gregory, S. G., Barlow, K. F., McLay, K. E., Kaul, R., Swarbreck, D., Dunham, A., Scott, C. E., Howe, K. L., Woodfine, K., Spencer, C. C. A., Jones, M. C., Gillson, C., Searle, S., Zhou, Y., Kokocinski, F., McDonald, L., Evans, R., Phillips, K., Atkinson, A., Cooper, R., Jones, C., Hall, R. E., Andrews, T. D., Lloyd, C., Ainscough, R., Almeida, J. P., Ambrose, K. D., Anderson, F., Andrew, R. W., Ashwell, R. I. S., Aubin, K., Babbage, A. K., Bagguley, C. L., Bailey, J., Beasley, H., Bethel, G., Bird, C. P., Bray-Allen, S., Brown, J. Y., Brown, A. J., Buckley, D., Burton, J., Bye, J., Carder, C., Chapman, J. C., Clark, S. Y., Clarke, G., Clee, C., Cobley, V., Collier, R. E., Corby, N., Coville, G. J., Davies, J., Deadman, R., Dunn, M., Earthrowl, M., Ellington, A. G., Errington, H., Frankish, A., Frankland, J., French, L., Garner, P., Garnett, J., Gay, L., Ghori, M. R. J., Gibson, R., Gilby, L. M., Gillett, W., Glithero, R. J., Grafham, D. V., Griffiths, C., Griffiths-Jones, S., Grocock, R., Hammond, S., Harrison, E. S. I., Hart, E., Haugen, E., Heath, P. D., Holmes, S., Holt, K., Howden, P. J., Hunt, A. R., Hunt, S. E., Hunter, G., Isherwood, J., James, R., Johnson, C., Johnson, D., Joy, A., Kay, M., Kershaw, J. K., Kibukawa, M., Kimberley, A. M., King, A., Knights, A. J., Lad, H., Laird, G., Lawlor, S., Leongamornlert, D. A., Lloyd, D. M., Loveland, J., Lovell, J., Lush, M. J., Lyne, R., Martin, S., Mashreghi-Mohammadi, M., Matthews, L., Matthews, N. S. W., McLaren, S., Milne, S., Mistry, S., Nickerson, T., O'Dell, C. N., Oliver, K., Palmeiri, A., Palmer, S. A., Parker, A., Patel, D., Pearce, A. V., Peck, A. I., Pelan, S., Phelps, K., Phillimore, B. J., Plumb, R., Rajan, J., Raymond, C., Rouse, G., Saenphimmachak, C., Sehra, H. K., Sheridan, E., Shownkeen, R., Sims, S., Skuce, C. D., Smith, M., Steward, C., Subramanian, S., Sycamore, N., Tracey, A., Tromans, A., Van Helmond, Z., Wall, M., Wallis, J. M., White, S., Whitehead, S. L., Wilkinson, J. E., Willey, D. L., Williams, H., Wilming, L., Wray, P. W., Wu, Z., Coulson, A., Vaudin, M., Sulston, J. E., Durbin, R., Hubbard, T., Wooster, R., Dunham, I., Carter, N. P., McVean, G., Ross, M. T., Harrow, J., Olson, M. V., Beck, S., Rogers, J., and Bentley, D. R.

Subjects
Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): S. G. Gregory (corresponding author) [1, 2]; K. F. Barlow [1]; K. E. McLay [1]; R. Kaul [3]; D. Swarbreck [1]; A. Dunham [1]; C. E. Scott [1]; K. [...]

Published
2006
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11. NOX1 loss-of-function genetic variants in patients with inflammatory bowel disease

Author

Schwerd, T., Bryant, R. V., Pandey, S., Capitani, M., Meran, L., Cazier, J. -B., Jung, J., Mondal, K., Parkes, M., Mathew, C. G., Fiedler, K., McCarthy, D. J., Sullivan, P. B., Rodrigues, A., Travis, S. P. L., Moore, C., Sambrook, J., Ouwehand, W. H., Roberts, D. J., Danesh, J., Russell, R. K., Wilson, D. C., Kelsen, J. R., Cornall, R., Denson, L. A., Kugathasan, S., Knaus, U. G., Serra, E. G., Anderson, C. A., Duerr, R. H., McGovern, D. P. B., Cho, J., Powrie, Fiona, Li, V. S. W., Muise, A. M., Uhlig, H. H., Donnelly, P., Bell, J., Bentley, D., McVean, G., Ratcliffe, P., Taylor, J., Wilkie, A. O. M., Broxholme, J., Buck, D., Gregory, L., Gregory, J., Lunter, G., Tomlinson, I., Allan, C., Attar, M., Green, A., Humphray, S., Kingsbury, Z., Lamble, S., Lonie, L., Pagnamenta, A., Piazza, P., Polanco, G., Trebes, A., Copley, R., Fiddy, S., Grocock, R., Hatton, E., Holmes, C., Hughes, L., Humburg, P., Kanapin, A., Lise, S., Martin, H., Murray, L., McCarthy, D., Rimmer, A., Sahgal, N., Wright, B., Yau, C., Arancibia, Carolina, Bailey, Adam, Barnes, Ellie, Bird-Lieberman, Beth, Brain, Oliver, Braden, Barbara, Collier, Jane, East, James, Geremia, Alessandra, Howarth, Lucy, Keshav, Satish, Klenerman, Paul, Leedham, Simon, Palmer, Rebecca, Rodrigues, Astor, Simmons, Alison, Sullivan, Peter B, Travis, Simon P L, Uhlig, Holm H, Heuschkel, Rob, Zilbauer, Matthias, Auth, Marcus K. H., Shah, Neil, Kammermeier, Jochen, Croft, Nick, Barakat, Farah, Russell, Richard K., Wilson, David C., Henderson, Paul, Braegger, Christian P., Posovszky, Carsten, Fyderek, Krzysztof, Wedrychowicz, Andrzej, Zurek, Marlen, Strisciuglio, Caterina, Elawad, Mamoun, Lo, Bernice, Parkes, Miles, Satsangi, Jack, Anderson, Carl A., Jostins, L., Kennedy, N. A., Lamb, C. A., Ahmad, T., Edwards, C., Hart, A., Hawkey, C., Mansfield, J. C., Mowat, C., Newman, W. G., Satsangi, J., Simmons, A., Tremelling, M., Lee, J. C., Prescott, N. J., Lees, C. W., Barrett, J. C., UK IBD Genetics Consortium, COLORS in IBD, Oxford IBD cohort study investigators, WGS500 Consortium, INTERVAL Study, Schwerd, T., Bryant, R. V., Pandey, S., Capitani, M., Meran, L., Cazier, J. -B., Jung, J., Mondal, K., Parkes, M., Mathew, C. G., Fiedler, K., Mccarthy, D. J., Sullivan, P. B., Rodrigues, A., Travis, S. P. L., Moore, C., Sambrook, J., Ouwehand, W. H., Roberts, D. J., Danesh, J., Russell, R. K., Wilson, D. C., Kelsen, J. R., Cornall, R., Denson, L. A., Kugathasan, S., Knaus, U. G., Serra, E. G., Anderson, C. A., Duerr, R. H., Mcgovern, D. P. B., Cho, J., Powrie, Fiona, Li, V. S. W., Muise, A. M., Uhlig, H. H., Donnelly, P., Bell, J., Bentley, D., Mcvean, G., Ratcliffe, P., Taylor, J., Wilkie, A. O. M., Broxholme, J., Buck, D., Gregory, L., Gregory, J., Lunter, G., Tomlinson, I., Allan, C., Attar, M., Green, A., Humphray, S., Kingsbury, Z., Lamble, S., Lonie, L., Pagnamenta, A., Piazza, P., Polanco, G., Trebes, A., Copley, R., Fiddy, S., Grocock, R., Hatton, E., Holmes, C., Hughes, L., Humburg, P., Kanapin, A., Lise, S., Martin, H., Murray, L., Mccarthy, D., Rimmer, A., Sahgal, N., Wright, B., Yau, C., Arancibia, Carolina, Bailey, Adam, Barnes, Ellie, Bird-Lieberman, Beth, Brain, Oliver, Braden, Barbara, Collier, Jane, East, Jame, Geremia, Alessandra, Howarth, Lucy, Keshav, Satish, Klenerman, Paul, Leedham, Simon, Palmer, Rebecca, Rodrigues, Astor, Simmons, Alison, Sullivan, Peter B, Travis, Simon P L, Uhlig, Holm H, Heuschkel, Rob, Zilbauer, Matthia, Auth, Marcus K. H., Shah, Neil, Kammermeier, Jochen, Croft, Nick, Barakat, Farah, Russell, Richard K., Wilson, David C., Henderson, Paul, Braegger, Christian P., Posovszky, Carsten, Fyderek, Krzysztof, Wedrychowicz, Andrzej, Zurek, Marlen, Strisciuglio, Caterina, Elawad, Mamoun, Lo, Bernice, Parkes, Mile, Satsangi, Jack, Anderson, Carl A., Jostins, L., Kennedy, N. A., Lamb, C. A., Ahmad, T., Edwards, C., Hart, A., Hawkey, C., Mansfield, J. C., Mowat, C., Newman, W. G., Satsangi, J., Simmons, A., Tremelling, M., Lee, J. C., Prescott, N. J., Lees, C. W., Barrett, J. C., UK IBD Genetics, Consortium, COLORS in, Ibd, Oxford IBD cohort study, Investigator, Wgs500, Consortium, and Interval, Study

Subjects
Male, Genotype, Colon, Immunology, Mutation, Missense, Genetic Association Studie, Polymorphism, Single Nucleotide, Article, Mice, Animals, Humans, Immunology and Allergy, Genetic Predisposition to Disease, Child, Genetic Association Studies, Genes, Modifier, Genome, Animal, Inflammatory Bowel Disease, High-Throughput Nucleotide Sequencing, Inflammatory Bowel Diseases, digestive system diseases, Host-Pathogen Interaction, Mice, Inbred C57BL, Child, Preschool, Host-Pathogen Interactions, NADPH Oxidase 1, Reactive Oxygen Species, Reactive Oxygen Specie, Human
Abstract

Genetic defects that affect intestinal epithelial barrier function can present with very early-onset inflammatory bowel disease (VEOIBD). Using whole-genome sequencing, a novel hemizygous defect in NOX1 encoding NAPDH oxidase 1 was identified in a patient with ulcerative colitis-like VEOIBD. Exome screening of 1,878 pediatric patients identified further seven male inflammatory bowel disease (IBD) patients with rare NOX1 mutations. Loss-of-function was validated in p.N122H and p.T497A, and to a lesser degree in p.Y470H, p.R287Q, p.I67M, p.Q293R as well as the previously described p.P330S, and the common NOX1 SNP p.D360N (rs34688635) variant. The missense mutation p.N122H abrogated reactive oxygen species (ROS) production in cell lines, ex vivo colonic explants, and patient-derived colonic organoid cultures. Within colonic crypts, NOX1 constitutively generates a high level of ROS in the crypt lumen. Analysis of 9,513 controls and 11,140 IBD patients of non-Jewish European ancestry did not reveal an association between p.D360N and IBD. Our data suggest that loss-of-function variants in NOX1 do not cause a Mendelian disorder of high penetrance but are a context-specific modifier. Our results implicate that variants in NOX1 change brush border ROS within colonic crypts at the interface between the epithelium and luminal microbes.

Published
2018

12. Genomic analysis of plasmodium vivax in southern Ethiopia reveals selective pressures in multiple parasite mechanisms

Author

Auburn, S, Getachew, S, Pearson, R, Amato, R, Miotto, O, Trimarsanto, H, Zhu, S, Rumaseb, A, Marfurt, J, Noviyanti, R, Grigg, M, Barber, B, William, T, Goncalves, S, Drury, E, Sriprawat, K, Anstey, N, Nosten, F, Petros, B, Aseffa, A, McVean, G, Kwiatkowski, D, and Price, R

Subjects
Male, Adolescent, Genotype, Adaptation, Biological, Infant, Newborn, malaria, Infant, Article, Child, Preschool, parasitic diseases, Prevalence, genomics, Malaria, Vivax, Humans, Animals, Female, Parasites, Ethiopia, Selection, Genetic, Child, Plasmodium vivax, Duffy
Abstract

The Horn of Africa harbors the largest reservoir of Plasmodium vivax in the continent. Most of sub-Saharan Africa has remained relatively vivax-free due to a high prevalence of the human Duffy-negative trait, but the emergence of strains able to invade Duffy-negative reticulocytes poses a major public health threat. We undertook the first population genomic investigation of P. vivax from the region, comparing the genomes of 24 Ethiopian isolates against data from Southeast Asia to identify important local adaptions. The prevalence of the Duffy binding protein amplification in Ethiopia was 79%, potentially reflecting adaptation to Duffy negativity. There was also evidence of selection in a region upstream of the chloroquine resistance transporter, a putative chloroquine-resistance determinant. Strong signals of selection were observed in genes involved in immune evasion and regulation of gene expression, highlighting the need for a multifaceted intervention approach to combat P. vivax in the region.

Published
2019

13. Graphical Model Selection for Gaussian Conditional Random Fields in the Presence of Latent Variables

Author

Frot, B, Jostins, L, and McVean, G

Subjects
Multivariate analysis, FOS: Biological sciences, Genetics, Metabolites, ALSPAC, Conditional Markov random field, Low-Rank plus Sparse, Model Selection
Abstract

We consider the problem of learning a conditional Gaussian graphical model in the presence of latent variables. Building on recent advances in this field, we suggest a method that decomposes the parameters of a conditional Markov random field into the sum of a sparse and a low-rank matrix. We derive convergence bounds for this estimator and show that it is well-behaved in the high-dimensional regime as well as “sparsistent” (i.e., capable of recovering the graph structure). We then show how proximal gradient algorithms and semi-definite programming techniques can be employed to fit the model to thousands of variables. Through extensive simulations, we illustrate the conditions required for identifiability and show that there is a wide range of situations in which this model performs significantly better than its counterparts, for example, by accommodating more latent variables. Finally, the suggested method is applied to two datasets comprising individual level data on genetic variants and metabolites levels. We show our results replicate better than alternative approaches and show enriched biological signal. Supplementary materials for this article are available online., Journal of the American Statistical Association, 114 (526), ISSN:0162-1459, ISSN:1537-274X

Published
2019

15. Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania

Author

Band, G, Le, QS, Clarke, GM, Kivinen, K, Hubbart, C, Jeffreys, AE, Rowlands, K, Leffler, EM, Jallow, M, Conway, DJ, Sisay-Joof, F, Sirugo, G, d'Alessandro, U, Toure, OB, Thera, MA, Konate, S, Sissoko, S, Mangano, VD, Bougouma, EC, Sirima, SB, Amenga-Etego, LN, Ghansah, AK, Hodgson, AVO, Wilson, MD, Enimil, A, Ansong, D, Evans, J, Ademola, SA, Apinjoh, TO, Ndila, CM, Manjurano, A, Drakeley, C, Reyburn, H, Nguyen, HP, Nguyen, TNQ, Cao, QT, Tran, TH, Teo, YY, Manning, L, Laman, M, Michon, P, Karunajeewa, H, Siba, P, Allen, S, Allen, A, Bahlo, M, Davis, TME, Simpson, V, Shelton, J, Spencer, CCA, Busby, GBJ, Kerasidou, A, Drury, E, Stalker, J, Dilthey, A, Mentzer, AJ, McVean, G, Bojang, KA, Doumbo, O, Modiano, D, Koram, KA, Agbenyega, T, Amodu, OK, Achidi, E, Williams, TN, Marsh, K, Riley, EM, Molyneux, M, Taylor, T, Dunstan, SJ, Farrar, J, Mueller, I, Rockett, KA, Kwiatkowski, DP, Band, G, Le, QS, Clarke, GM, Kivinen, K, Hubbart, C, Jeffreys, AE, Rowlands, K, Leffler, EM, Jallow, M, Conway, DJ, Sisay-Joof, F, Sirugo, G, d'Alessandro, U, Toure, OB, Thera, MA, Konate, S, Sissoko, S, Mangano, VD, Bougouma, EC, Sirima, SB, Amenga-Etego, LN, Ghansah, AK, Hodgson, AVO, Wilson, MD, Enimil, A, Ansong, D, Evans, J, Ademola, SA, Apinjoh, TO, Ndila, CM, Manjurano, A, Drakeley, C, Reyburn, H, Nguyen, HP, Nguyen, TNQ, Cao, QT, Tran, TH, Teo, YY, Manning, L, Laman, M, Michon, P, Karunajeewa, H, Siba, P, Allen, S, Allen, A, Bahlo, M, Davis, TME, Simpson, V, Shelton, J, Spencer, CCA, Busby, GBJ, Kerasidou, A, Drury, E, Stalker, J, Dilthey, A, Mentzer, AJ, McVean, G, Bojang, KA, Doumbo, O, Modiano, D, Koram, KA, Agbenyega, T, Amodu, OK, Achidi, E, Williams, TN, Marsh, K, Riley, EM, Molyneux, M, Taylor, T, Dunstan, SJ, Farrar, J, Mueller, I, Rockett, KA, and Kwiatkowski, DP

Abstract

The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replicable associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus. Previously reported HLA associations do not replicate in these samples. This large dataset will provide a foundation for further research on thegenetic determinants of malaria resistance in diverse populations.

Published
2019

16. Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

Author

Flannick, J, Fuchsberger, C, Mahajan, A, Teslovich, TM, Agarwala, V, Gaulton, KJ, Caulkins, L, Koesterer, R, Ma, C, Moutsianas, L, McCarthy, DJ, Rivas, MA, Perry, JRB, Sim, X, Blackwell, TW, Robertson, NR, Rayner, NW, Cingolani, P, Locke, AE, Tajes, JF, Highland, HM, Dupuis, J, Chines, PS, Lindgren, CM, Hartl, C, Jackson, AU, Chen, H, Huyghe, JR, van de Bunt, M, Pearson, RD, Kumar, A, Mueller-Nurasyid, M, Grarup, N, Stringham, HM, Gamazon, ER, Lee, J, Chen, Y, Scott, RA, Below, JE, Chen, P, Huang, J, Go, MJ, Stitzel, ML, Pasko, D, Parker, SCJ, Varga, TV, Green, T, Beer, NL, Day-Williams, AG, Ferreira, T, Fingerlin, T, Horikoshi, M, Hu, C, Huh, I, Ikram, MK, Kim, B-J, Kim, Y, Kim, YJ, Kwon, M-S, Lee, S, Lin, K-H, Maxwell, TJ, Nagai, Y, Wang, X, Welch, RP, Yoon, J, Zhang, W, Barzilai, N, Voight, BF, Han, B-G, Jenkinson, CP, Kuulasmaa, T, Kuusisto, J, Manning, A, Ng, MCY, Palmer, ND, Balkau, B, Stancakova, A, Abboud, HE, Boeing, H, Giedraitis, V, Prabhakaran, D, Gottesman, O, Scott, J, Carey, J, Kwan, P, Grant, G, Smith, JD, Neale, BM, Purcell, S, Butterworth, AS, Howson, JMM, Lee, HM, Lu, Y, Kwak, S-H, Zhao, W, Danesh, J, Lam, VKL, Park, KS, Saleheen, D, So, WY, Tam, CHT, Afzal, U, Aguilar, D, Arya, R, Aung, T, Chan, E, Navarro, C, Cheng, C-Y, Palli, D, Correa, A, Curran, JE, Rybin, D, Farook, VS, Fowler, SP, Freedman, BI, Griswold, M, Hale, DE, Hicks, PJ, Khor, C-C, Kumar, S, Lehne, B, Thuillier, D, Lim, WY, Liu, J, Loh, M, Musani, SK, Puppala, S, Scott, WR, Yengo, L, Tan, S-T, Taylor, HA, Thameem, F, Wilson, G, Wong, TY, Njolstad, PR, Levy, JC, Mangino, M, Bonnycastle, LL, Schwarzmayr, T, Fadista, J, Surdulescu, GL, Herder, C, Groves, CJ, Wieland, T, Bork-Jensen, J, Brandslund, I, Christensen, C, Koistinen, HA, Doney, ASF, Kinnunen, L, Esko, T, Farmer, AJ, Hakaste, L, Hodgkiss, D, Kravic, J, Lyssenko, V, Hollensted, M, Jorgensen, ME, Jorgensen, T, Ladenvall, C, Justesen, JM, Karajamaki, A, Kriebel, J, Rathmann, W, Lannfelt, L, Lauritzen, T, Narisu, N, Linneberg, A, Melander, O, Milani, L, Neville, M, Orho-Melander, M, Qi, L, Qi, Q, Roden, M, Rolandsson, O, Swift, A, Rosengren, AH, Stirrups, K, Wood, AR, Mihailov, E, Blancher, C, Carneiro, MO, Maguire, J, Poplin, R, Shakir, K, Fennell, T, DePristo, M, de Angelis, MH, Deloukas, P, Gjesing, AP, Jun, G, Nilsson, PM, Murphy, J, Onofrio, R, Thorand, B, Hansen, T, Meisinger, C, Hu, FB, Isomaa, B, Karpe, F, Liang, L, Peters, A, Huth, C, O'Rahilly, SP, Palmer, CNA, Pedersen, O, Rauramaa, R, Tuomilehto, J, Salomaa, V, Watanabe, RM, Syvanen, A-C, Bergman, RN, Bharadwaj, D, Bottinger, EP, Cho, YS, Chandak, GR, Chan, JC, Chia, KS, Daly, MJ, Ebrahim, SB, Langenberg, C, Elliott, P, Jablonski, KA, Lehman, DM, Jia, W, Ma, RCW, Pollin, TI, Sandhu, M, Tandon, N, Froguel, P, Barroso, I, Teo, YY, Zeggini, E, Loos, RJF, Small, KS, Ried, JS, DeFronzo, RA, Grallert, H, Glaser, B, Metspalu, A, Wareham, NJ, Walker, M, Banks, E, Gieger, C, Ingelsson, E, Im, HK, Illig, T, Franks, PW, Buck, G, Trakalo, J, Buck, D, Prokopenko, I, Magi, R, Lind, L, Farjoun, Y, Owen, KR, Gloyn, AL, Strauch, K, Tuomi, T, Kooner, JS, Lee, J-Y, Park, T, Donnelly, P, Morris, AD, Hattersley, AT, Bowden, DW, Collins, FS, Atzmon, G, Chambers, JC, Spector, TD, Laakso, M, Strom, TM, Bell, GI, Blangero, J, Duggirala, R, Tai, E, McVean, G, Hanis, CL, Wilson, JG, Seielstad, M, Frayling, TM, Meigs, JB, Cox, NJ, Sladek, R, Lander, ES, Gabriel, S, Mohlke, KL, Meitinger, T, Groop, L, Abecasis, G, Scott, LJ, Morris, AP, Kang, HM, Altshuler, D, Burtt, NP, Florez, JC, Boehnke, M, McCarthy, MI, Flannick, J, Fuchsberger, C, Mahajan, A, Teslovich, TM, Agarwala, V, Gaulton, KJ, Caulkins, L, Koesterer, R, Ma, C, Moutsianas, L, McCarthy, DJ, Rivas, MA, Perry, JRB, Sim, X, Blackwell, TW, Robertson, NR, Rayner, NW, Cingolani, P, Locke, AE, Tajes, JF, Highland, HM, Dupuis, J, Chines, PS, Lindgren, CM, Hartl, C, Jackson, AU, Chen, H, Huyghe, JR, van de Bunt, M, Pearson, RD, Kumar, A, Mueller-Nurasyid, M, Grarup, N, Stringham, HM, Gamazon, ER, Lee, J, Chen, Y, Scott, RA, Below, JE, Chen, P, Huang, J, Go, MJ, Stitzel, ML, Pasko, D, Parker, SCJ, Varga, TV, Green, T, Beer, NL, Day-Williams, AG, Ferreira, T, Fingerlin, T, Horikoshi, M, Hu, C, Huh, I, Ikram, MK, Kim, B-J, Kim, Y, Kim, YJ, Kwon, M-S, Lee, S, Lin, K-H, Maxwell, TJ, Nagai, Y, Wang, X, Welch, RP, Yoon, J, Zhang, W, Barzilai, N, Voight, BF, Han, B-G, Jenkinson, CP, Kuulasmaa, T, Kuusisto, J, Manning, A, Ng, MCY, Palmer, ND, Balkau, B, Stancakova, A, Abboud, HE, Boeing, H, Giedraitis, V, Prabhakaran, D, Gottesman, O, Scott, J, Carey, J, Kwan, P, Grant, G, Smith, JD, Neale, BM, Purcell, S, Butterworth, AS, Howson, JMM, Lee, HM, Lu, Y, Kwak, S-H, Zhao, W, Danesh, J, Lam, VKL, Park, KS, Saleheen, D, So, WY, Tam, CHT, Afzal, U, Aguilar, D, Arya, R, Aung, T, Chan, E, Navarro, C, Cheng, C-Y, Palli, D, Correa, A, Curran, JE, Rybin, D, Farook, VS, Fowler, SP, Freedman, BI, Griswold, M, Hale, DE, Hicks, PJ, Khor, C-C, Kumar, S, Lehne, B, Thuillier, D, Lim, WY, Liu, J, Loh, M, Musani, SK, Puppala, S, Scott, WR, Yengo, L, Tan, S-T, Taylor, HA, Thameem, F, Wilson, G, Wong, TY, Njolstad, PR, Levy, JC, Mangino, M, Bonnycastle, LL, Schwarzmayr, T, Fadista, J, Surdulescu, GL, Herder, C, Groves, CJ, Wieland, T, Bork-Jensen, J, Brandslund, I, Christensen, C, Koistinen, HA, Doney, ASF, Kinnunen, L, Esko, T, Farmer, AJ, Hakaste, L, Hodgkiss, D, Kravic, J, Lyssenko, V, Hollensted, M, Jorgensen, ME, Jorgensen, T, Ladenvall, C, Justesen, JM, Karajamaki, A, Kriebel, J, Rathmann, W, Lannfelt, L, Lauritzen, T, Narisu, N, Linneberg, A, Melander, O, Milani, L, Neville, M, Orho-Melander, M, Qi, L, Qi, Q, Roden, M, Rolandsson, O, Swift, A, Rosengren, AH, Stirrups, K, Wood, AR, Mihailov, E, Blancher, C, Carneiro, MO, Maguire, J, Poplin, R, Shakir, K, Fennell, T, DePristo, M, de Angelis, MH, Deloukas, P, Gjesing, AP, Jun, G, Nilsson, PM, Murphy, J, Onofrio, R, Thorand, B, Hansen, T, Meisinger, C, Hu, FB, Isomaa, B, Karpe, F, Liang, L, Peters, A, Huth, C, O'Rahilly, SP, Palmer, CNA, Pedersen, O, Rauramaa, R, Tuomilehto, J, Salomaa, V, Watanabe, RM, Syvanen, A-C, Bergman, RN, Bharadwaj, D, Bottinger, EP, Cho, YS, Chandak, GR, Chan, JC, Chia, KS, Daly, MJ, Ebrahim, SB, Langenberg, C, Elliott, P, Jablonski, KA, Lehman, DM, Jia, W, Ma, RCW, Pollin, TI, Sandhu, M, Tandon, N, Froguel, P, Barroso, I, Teo, YY, Zeggini, E, Loos, RJF, Small, KS, Ried, JS, DeFronzo, RA, Grallert, H, Glaser, B, Metspalu, A, Wareham, NJ, Walker, M, Banks, E, Gieger, C, Ingelsson, E, Im, HK, Illig, T, Franks, PW, Buck, G, Trakalo, J, Buck, D, Prokopenko, I, Magi, R, Lind, L, Farjoun, Y, Owen, KR, Gloyn, AL, Strauch, K, Tuomi, T, Kooner, JS, Lee, J-Y, Park, T, Donnelly, P, Morris, AD, Hattersley, AT, Bowden, DW, Collins, FS, Atzmon, G, Chambers, JC, Spector, TD, Laakso, M, Strom, TM, Bell, GI, Blangero, J, Duggirala, R, Tai, E, McVean, G, Hanis, CL, Wilson, JG, Seielstad, M, Frayling, TM, Meigs, JB, Cox, NJ, Sladek, R, Lander, ES, Gabriel, S, Mohlke, KL, Meitinger, T, Groop, L, Abecasis, G, Scott, LJ, Morris, AP, Kang, HM, Altshuler, D, Burtt, NP, Florez, JC, Boehnke, M, and McCarthy, MI

Abstract

This corrects the article DOI: 10.1038/sdata.2017.179.

Published
2018

17. The UK Biobank resource with deep phenotyping and genomic data

Author

Bycroft, C, Freeman, C, Petkova, D, Band, G, Elliott, LT, Sharp, K, Motyer, A, Vukcevic, D, Delaneau, O, O'Connell, J, Cortes, A, Welsh, S, Young, A, Effingham, M, McVean, G, Leslie, S, Allen, N, Donnelly, P, Marchini, J, Bycroft, C, Freeman, C, Petkova, D, Band, G, Elliott, LT, Sharp, K, Motyer, A, Vukcevic, D, Delaneau, O, O'Connell, J, Cortes, A, Welsh, S, Young, A, Effingham, M, McVean, G, Leslie, S, Allen, N, Donnelly, P, and Marchini, J

Abstract

The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

Published
2018

18. A point mutation in the ion conduction pore of AMPA receptor GRIA3 causes dramatically perturbed sleep patterns as well as intellectual disability

Author

Davies, B, Brown, L, Cais, O, Watson, J, Clayton, A, Chang, V, Biggs, D, Preece, C, Hernandez-Pliego, P, Krohn, J, Bhomra, A, Twigg, S, Rimmer, A, Kanapin, A, Consortium, WGS500, Sen, A, Zaiwalla, Z, McVean, G, Foster, R, Donnelly, P, Taylor, J, Blair, E, Nutt, D, Aricescu, A, Greger, I, Peirson, S, Flint, J, and Martin, H

Abstract

The discovery of genetic variants influencing sleep patterns can shed light on the physiological processes underlying sleep. As part of a large clinical sequencing project, WGS500, we sequenced a family in which the two male children had severe developmental delay and a dramatically disturbed sleep-wake cycle, with very long wake and sleep durations, reaching up to 106-h awake and 48-h asleep. The most likely causal variant identified was a novel missense variant in the X-linked GRIA3 gene, which has been implicated in intellectual disability. GRIA3 encodes GluA3, a subunit of AMPA-type ionotropic glutamate receptors (AMPARs). The mutation (A653T) falls within the highly conserved transmembrane domain of the ion channel gate, immediately adjacent to the analogous residue in the Grid2 (glutamate receptor) gene, which is mutated in the mouse neurobehavioral mutant, Lurcher. In vitro, the GRIA3(A653T) mutation stabilizes the channel in a closed conformation, in contrast to Lurcher. We introduced the orthologous mutation into a mouse strain by CRISPR-Cas9 mutagenesis and found that hemizygous mutants displayed significant differences in the structure of their activity and sleep compared to wild-type littermates. Typically, mice are polyphasic, exhibiting multiple sleep bouts of sleep several minutes long within a 24-h period. The Gria3A653T mouse showed significantly fewer brief bouts of activity and sleep than the wild-types. Furthermore, Gria3A653T mice showed enhanced period lengthening under constant light compared to wild-type mice, suggesting an increased sensitivity to light. Our results suggest a role for GluA3 channel activity in the regulation of sleep behavior in both mice and humans.

Published
2017

19. Whole-genome sequencing of spermatocytic tumors provides insights into the mutational processes operating in the male germline

Author

Giannoulatou, E., Maher, G.J., Ding, Z., Gillis, A.J., Dorssers, L.C.J., Hoischen, A., Rajpert-De Meyts, E., McVean, G., Wilkie, A.O.M., Looijenga, L.H.J., Goriely, A., Giannoulatou, E., Maher, G.J., Ding, Z., Gillis, A.J., Dorssers, L.C.J., Hoischen, A., Rajpert-De Meyts, E., McVean, G., Wilkie, A.O.M., Looijenga, L.H.J., and Goriely, A.

Abstract

Contains fulltext : 174702.pdf (publisher's version ) (Open Access), Adult male germline stem cells (spermatogonia) proliferate by mitosis and, after puberty, generate spermatocytes that undertake meiosis to produce haploid spermatozoa. Germ cells are under evolutionary constraint to curtail mutations and maintain genome integrity. Despite constant turnover, spermatogonia very rarely form tumors, so-called spermatocytic tumors (SpT). In line with the previous identification of FGFR3 and HRAS selfish mutations in a subset of cases, candidate gene screening of 29 SpTs identified an oncogenic NRAS mutation in two cases. To gain insights in the etiology of SpT and into properties of the male germline, we performed whole-genome sequencing of five tumors (4/5 with matched normal tissue). The acquired single nucleotide variant load was extremely low (~0.2 per Mb), with an average of 6 (2-9) non-synonymous variants per tumor, none of which is likely to be oncogenic. The observed mutational signature of SpTs is strikingly similar to that of germline de novo mutations, mostly involving C>T transitions with a significant enrichment in the ACG trinucleotide context. The tumors exhibited extensive aneuploidy (50-99 autosomes/tumor) involving whole-chromosomes, with recurrent gains of chr9 and chr20 and loss of chr7, suggesting that aneuploidy itself represents the initiating oncogenic event. We propose that SpT etiology recapitulates the unique properties of male germ cells; because of evolutionary constraints to maintain low point mutation rate, rare tumorigenic driver events are caused by a combination of gene imbalance mediated via whole-chromosome aneuploidy. Finally, we propose a general framework of male germ cell tumor pathology that accounts for their mutational landscape, timing and cellular origin.

Published
2017

20. Whole-genome sequencing of spermatocytic tumors provides insights into the mutational processes operating in the male germline

Author

Giannoulatou, E, Maher, GJ, Ding, Z, Gillis, AJM, Dorssers, LCJ, Hoischen, A, Meyts, ERD, McVean, G, Wilkie, AOM, Looijenga, LHJ, Goriely, A, Giannoulatou, E, Maher, GJ, Ding, Z, Gillis, AJM, Dorssers, LCJ, Hoischen, A, Meyts, ERD, McVean, G, Wilkie, AOM, Looijenga, LHJ, and Goriely, A

Abstract

© 2017 Giannoulatou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Adult male germline stem cells (spermatogonia) proliferate by mitosis and, after puberty, generate spermatocytes that undertake meiosis to produce haploid spermatozoa. Germ cells are under evolutionary constraint to curtail mutations and maintain genome integrity. Despite constant turnover, spermatogonia very rarely form tumors, so-called spermatocytic tumors (SpT). In line with the previous identification of FGFR3 and HRAS selfish mutations in a subset of cases, candidate gene screening of 29 SpTs identified an oncogenic NRAS mutation in two cases. To gain insights in the etiology of SpT and into properties of the male germline, we performed whole-genome sequencing of five tumors (4/5 with matched normal tissue). The acquired single nucleotide variant load was extremely low (~0.2 per Mb), with an average of 6 (2±9) non-synonymous variants per tumor, none of which is likely to be oncogenic. The observed mutational signature of SpTs is strikingly similar to that of germline de novo mutations, mostly involving C>T transitions with a significant enrichment in the ACG trinucleotide context. The tumors exhibited extensive aneuploidy (50±99 autosomes/ tumor) involving whole-chromosomes, with recurrent gains of chr9 and chr20 and loss of chr7, suggesting that aneuploidy itself represents the initiating oncogenic event. We propose that SpT etiology recapitulates the unique properties of male germ cells; because of evolutionary constraints to maintain low point mutation rate, rare tumorigenic driver events are caused by a combination of gene imbalance mediated via whole-chromosome aneuploidy. Finally, we propose a general framework of male germ cell tumor pathology that accounts for their mutational landscape, timing

Published
2017

21. Whole-genome sequencing of spermatocytic tumors provides insights into the mutational processes operating in the male germline

Author

Giannoulatou, E. (Eleni), Maher, G.J. (Geoffrey), Ding, Z. (Zhihao), Gillis, A.J.M. (Ad J. M.), Dorssers, L.C.J. (Lambert), Hoischen, A. (Alex), Meyts, E.R.-D. (Ewa Rajpert-De), McVean, G. (Gil), Wilkie, A.O.M. (Andrew), Looijenga, L.H.J. (Leendert), Goriely, A. (Anne), Giannoulatou, E. (Eleni), Maher, G.J. (Geoffrey), Ding, Z. (Zhihao), Gillis, A.J.M. (Ad J. M.), Dorssers, L.C.J. (Lambert), Hoischen, A. (Alex), Meyts, E.R.-D. (Ewa Rajpert-De), McVean, G. (Gil), Wilkie, A.O.M. (Andrew), Looijenga, L.H.J. (Leendert), and Goriely, A. (Anne)

Abstract

Adult male germline stem cells (spermatogonia) proliferate by mitosis and, after puberty, generate spermatocytes that undertake meiosis to produce haploid spermatozoa. Germ cells are under evolutionary constraint to curtail mutations and maintain genome integrity. Despite constant turnover, spermatogonia very rarely form tumors, so-called spermatocytic tumors (SpT). In line with the previous identification of FGFR3 and HRAS selfish mutations in a subset of cases, candidate gene screening of 29 SpTs identified an oncogenic NRAS mutation in two cases. To gain insights in the etiology of SpT and into properties of the male germline, we performed whole-genome sequencing of five tumors (4/5 with matched normal tissue). The acquired single nucleotide variant load was extremely low (~0.2 per Mb), with an average of 6 (2±9) non

Published
2017
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22. Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank

Author

Cortes, A, Dendrou, CA, Motyer, A, Jostins, L, Vukcevic, D, Dilthey, A, Donnelly, P, Leslie, S, Fugger, L, McVean, G, Cortes, A, Dendrou, CA, Motyer, A, Jostins, L, Vukcevic, D, Dilthey, A, Donnelly, P, Leslie, S, Fugger, L, and McVean, G

Abstract

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data can transform understanding of the human phenome and accelerate progress toward precision medicine. However, a critical question when analyzing high-dimensional and heterogeneous data is how best to interrogate increasingly specific subphenotypes while retaining statistical power to detect genetic associations. Here we develop and employ a new Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to analyze genetic variants against UK Biobank disease phenotypes derived from self-reporting and hospital episode statistics. Our method displays a more than 20% increase in power to detect genetic effects over other approaches and identifies new associations between classical human leukocyte antigen (HLA) alleles and common immune-mediated diseases (IMDs). By applying the approach to genetic risk scores (GRSs), we show the extent of genetic sharing among IMDs and expose differences in disease perception or diagnosis with potential clinical implications.

Published
2017

23. Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

Author

Flannick, J, Fuchsberger, C, Mahajan, A, Teslovich, TM, Agarwala, V, Gaulton, KJ, Caulkins, L, Koesterer, R, Ma, C, Moutsianas, L, McCarthy, DJ, Rivas, MA, Perry, JRB, Sim, X, Blackwell, TW, Robertson, NR, Rayner, NW, Cingolani, P, Locke, AE, Tajes, JF, Highland, HM, Dupuis, J, Chines, PS, Lindgren, CM, Hartl, C, Jackson, AU, Chen, H, Huyghe, JR, De Bunt, MV, Pearson, RD, Kumar, A, Muller-Nurasyid, M, Grarup, N, Stringham, HM, Gamazon, ER, Lee, J, Chen, Y, Scott, RA, Below, JE, Chen, P, Huang, J, Go, MJ, Stitzel, ML, Pasko, D, Parker, SCJ, Varga, TV, Green, T, Beer, NL, Day-Williams, AG, Ferreira, T, Fingerlin, T, Horikoshi, M, Hu, C, Huh, I, Ikram, MK, Kim, B-J, Kim, Y, Kim, YJ, Kwon, M-S, Lee, S, Lin, K-H, Maxwell, TJ, Nagai, Y, Wang, X, Welch, RP, Yoon, J, Zhang, W, Barzilai, N, Voight, BF, Han, B-G, Jenkinson, CP, Kuulasmaa, T, Kuusisto, J, Manning, A, Ng, MCY, Palmer, ND, Balkau, B, Stancakova, A, Abboud, HE, Boeing, H, Giedraitis, V, Prabhakaran, D, Gottesman, O, Scott, J, Carey, J, Kwan, P, Grant, G, Smith, JD, Neale, BM, Purcell, S, Butterworth, AS, Howson, JMM, Lee, HM, Lu, Y, Kwak, S-H, Zhao, W, Danesh, J, Lam, VKL, Park, KS, Saleheen, D, So, WY, Tam, CHT, Afzal, U, Aguilar, D, Arya, R, Aung, T, Chan, E, Navarro, C, Cheng, C-Y, Palli, D, Correa, A, Curran, JE, Rybin, D, Farook, VS, Fowler, SP, Freedman, BI, Griswold, M, Hale, DE, Hicks, PJ, Khor, C-C, Kumar, S, Lehne, B, Thuillier, D, Lim, WY, Liu, J, Loh, M, Musani, SK, Puppala, S, Scott, WR, Yengo, L, Tan, S-T, Taylor, HA, Thameem, F, Wilson, G, Wong, TY, Njolstad, PR, Levy, JC, Mangino, M, Bonnycastle, LL, Schwarzmayr, T, Fadista, J, Surdulescu, GL, Herder, C, Groves, CJ, Wieland, T, Bork-Jensen, J, Brandslund, I, Christensen, C, Koistinen, HA, Doney, ASF, Kinnunen, L, Esko, T, Farmer, AJ, Hakaste, L, Hodgkiss, D, Kravic, J, Lyssenko, V, Hollensted, M, Jorgensen, ME, Jorgensen, T, Ladenvall, C, Justesen, JM, Karajamaki, A, Kriebel, J, Rathmann, W, Lannfelt, L, Lauritzen, T, Narisu, N, Linneberg, A, Melander, O, Milani, L, Neville, M, Orho-Melander, M, Qi, L, Qi, Q, Roden, M, Rolandsson, O, Swift, A, Rosengren, AH, Stirrups, K, Wood, AR, Mihailov, E, Blancher, C, Carneiro, MO, Maguire, J, Poplin, R, Shakir, K, Fennell, T, DePristo, M, De Angelis, MH, Deloukas, P, Gjesing, AP, Jun, G, Nilsson, PM, Murphy, J, Onofrio, R, Thorand, B, Hansen, T, Meisinger, C, Hu, FB, Isomaa, B, Karpe, F, Liang, L, Peters, A, Huth, C, O'Rahilly, SP, Palmer, CNA, Pedersen, O, Rauramaa, R, Tuomilehto, J, Salomaa, V, Watanabe, RM, Syvanen, A-C, Bergman, RN, Bharadwaj, D, Bottinger, EP, Cho, YS, Chandak, GR, Chan, JC, Chia, KS, Daly, MJ, Ebrahim, SB, Langenberg, C, Elliott, P, Jablonski, KA, Lehman, DM, Jia, W, Ma, RC, Pollin, TI, Sandhu, M, Tandon, N, Froguel, P, Barroso, I, Teo, YY, Zeggini, E, Loos, RJF, Small, KS, Ried, JS, DeFronzo, RA, Grallert, H, Glaser, B, Metspalu, A, Wareham, NJ, Walker, M, Banks, E, Gieger, C, Ingelsson, E, Im, HK, Illig, T, Franks, PW, Buck, G, Trakalo, J, Buck, D, Prokopenko, I, Magi, R, Lind, L, Farjoun, Y, Owen, KR, Gloyn, AL, Strauch, K, Tuomi, T, Kooner, JS, Lee, J-Y, Park, T, Donnelly, P, Morris, AD, Hattersley, AT, Bowden, DW, Collins, FS, Atzmon, G, Chambers, JC, Spector, TD, Laakso, M, Strom, TM, Bell, GI, Blangero, J, Duggirala, R, Tai, E, McVean, G, Hanis, CL, Wilson, JG, Seielstad, M, Frayling, TM, Meigs, JB, Cox, NJ, Sladek, R, Lander, ES, Gabriel, S, Mohlke, KL, Meitinger, T, Groop, L, Abecasis, G, Scott, LJ, Morris, AP, Kang, HM, Altshuler, D, Burtt, NP, Florez, JC, Boehnke, M, McCarthy, MI, Flannick, J, Fuchsberger, C, Mahajan, A, Teslovich, TM, Agarwala, V, Gaulton, KJ, Caulkins, L, Koesterer, R, Ma, C, Moutsianas, L, McCarthy, DJ, Rivas, MA, Perry, JRB, Sim, X, Blackwell, TW, Robertson, NR, Rayner, NW, Cingolani, P, Locke, AE, Tajes, JF, Highland, HM, Dupuis, J, Chines, PS, Lindgren, CM, Hartl, C, Jackson, AU, Chen, H, Huyghe, JR, De Bunt, MV, Pearson, RD, Kumar, A, Muller-Nurasyid, M, Grarup, N, Stringham, HM, Gamazon, ER, Lee, J, Chen, Y, Scott, RA, Below, JE, Chen, P, Huang, J, Go, MJ, Stitzel, ML, Pasko, D, Parker, SCJ, Varga, TV, Green, T, Beer, NL, Day-Williams, AG, Ferreira, T, Fingerlin, T, Horikoshi, M, Hu, C, Huh, I, Ikram, MK, Kim, B-J, Kim, Y, Kim, YJ, Kwon, M-S, Lee, S, Lin, K-H, Maxwell, TJ, Nagai, Y, Wang, X, Welch, RP, Yoon, J, Zhang, W, Barzilai, N, Voight, BF, Han, B-G, Jenkinson, CP, Kuulasmaa, T, Kuusisto, J, Manning, A, Ng, MCY, Palmer, ND, Balkau, B, Stancakova, A, Abboud, HE, Boeing, H, Giedraitis, V, Prabhakaran, D, Gottesman, O, Scott, J, Carey, J, Kwan, P, Grant, G, Smith, JD, Neale, BM, Purcell, S, Butterworth, AS, Howson, JMM, Lee, HM, Lu, Y, Kwak, S-H, Zhao, W, Danesh, J, Lam, VKL, Park, KS, Saleheen, D, So, WY, Tam, CHT, Afzal, U, Aguilar, D, Arya, R, Aung, T, Chan, E, Navarro, C, Cheng, C-Y, Palli, D, Correa, A, Curran, JE, Rybin, D, Farook, VS, Fowler, SP, Freedman, BI, Griswold, M, Hale, DE, Hicks, PJ, Khor, C-C, Kumar, S, Lehne, B, Thuillier, D, Lim, WY, Liu, J, Loh, M, Musani, SK, Puppala, S, Scott, WR, Yengo, L, Tan, S-T, Taylor, HA, Thameem, F, Wilson, G, Wong, TY, Njolstad, PR, Levy, JC, Mangino, M, Bonnycastle, LL, Schwarzmayr, T, Fadista, J, Surdulescu, GL, Herder, C, Groves, CJ, Wieland, T, Bork-Jensen, J, Brandslund, I, Christensen, C, Koistinen, HA, Doney, ASF, Kinnunen, L, Esko, T, Farmer, AJ, Hakaste, L, Hodgkiss, D, Kravic, J, Lyssenko, V, Hollensted, M, Jorgensen, ME, Jorgensen, T, Ladenvall, C, Justesen, JM, Karajamaki, A, Kriebel, J, Rathmann, W, Lannfelt, L, Lauritzen, T, Narisu, N, Linneberg, A, Melander, O, Milani, L, Neville, M, Orho-Melander, M, Qi, L, Qi, Q, Roden, M, Rolandsson, O, Swift, A, Rosengren, AH, Stirrups, K, Wood, AR, Mihailov, E, Blancher, C, Carneiro, MO, Maguire, J, Poplin, R, Shakir, K, Fennell, T, DePristo, M, De Angelis, MH, Deloukas, P, Gjesing, AP, Jun, G, Nilsson, PM, Murphy, J, Onofrio, R, Thorand, B, Hansen, T, Meisinger, C, Hu, FB, Isomaa, B, Karpe, F, Liang, L, Peters, A, Huth, C, O'Rahilly, SP, Palmer, CNA, Pedersen, O, Rauramaa, R, Tuomilehto, J, Salomaa, V, Watanabe, RM, Syvanen, A-C, Bergman, RN, Bharadwaj, D, Bottinger, EP, Cho, YS, Chandak, GR, Chan, JC, Chia, KS, Daly, MJ, Ebrahim, SB, Langenberg, C, Elliott, P, Jablonski, KA, Lehman, DM, Jia, W, Ma, RC, Pollin, TI, Sandhu, M, Tandon, N, Froguel, P, Barroso, I, Teo, YY, Zeggini, E, Loos, RJF, Small, KS, Ried, JS, DeFronzo, RA, Grallert, H, Glaser, B, Metspalu, A, Wareham, NJ, Walker, M, Banks, E, Gieger, C, Ingelsson, E, Im, HK, Illig, T, Franks, PW, Buck, G, Trakalo, J, Buck, D, Prokopenko, I, Magi, R, Lind, L, Farjoun, Y, Owen, KR, Gloyn, AL, Strauch, K, Tuomi, T, Kooner, JS, Lee, J-Y, Park, T, Donnelly, P, Morris, AD, Hattersley, AT, Bowden, DW, Collins, FS, Atzmon, G, Chambers, JC, Spector, TD, Laakso, M, Strom, TM, Bell, GI, Blangero, J, Duggirala, R, Tai, E, McVean, G, Hanis, CL, Wilson, JG, Seielstad, M, Frayling, TM, Meigs, JB, Cox, NJ, Sladek, R, Lander, ES, Gabriel, S, Mohlke, KL, Meitinger, T, Groop, L, Abecasis, G, Scott, LJ, Morris, AP, Kang, HM, Altshuler, D, Burtt, NP, Florez, JC, Boehnke, M, and McCarthy, MI

Abstract

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

Published
2017

24. Resolving $\textit{TYK2}$ locus genotype-to-phenotype differences in autoimmunity

Author

Dendrou, CA, Cortes, A, Shipman, L, Evans, HG, Attfield, KE, Jostins, L, Barber, T, Kaur, G, Kuttikkatte, SB, Leach, OA, Desel, C, Faergeman, SL, Cheeseman, J, Neville, MJ, Sawcer, S, Compston, A, Johnson, AR, Everett, C, Bell, JI, Karpe, F, Ultsch, M, Eigenbrot, C, McVean, G, Fugger, L, Sawcer, Stephen [0000-0001-7685-0974], and Apollo - University of Cambridge Repository

Subjects
CD4-Positive T-Lymphocytes, Male, Genotype, Protein Conformation, Quantitative Trait Loci, Mutation, Missense, Autoimmunity, Polymorphism, Single Nucleotide, Autoimmune Diseases, Epigenesis, Genetic, Mice, Animals, Humans, Genetic Association Studies, Recombination, Genetic, TYK2 Kinase, Sequence Analysis, RNA, Homozygote, Genetic Variation, Genomics, Janus Kinase 2, HEK293 Cells, Phenotype, Immune System, Leukocytes, Mononuclear, Cytokines, Female, Transcriptome, Signal Transduction
Abstract

Thousands of genetic variants have been identified, which contribute to the development of complex diseases, but determining how to elucidate their biological consequences for translation into clinical benefit is challenging. Conflicting evidence regarding the functional impact of genetic variants in the tyrosine kinase 2 ($\textit{TYK2}$) gene, which is differentially associated with common autoimmune diseases, currently obscures the potential of TYK2 as a therapeutic target. We aimed to resolve this conflict by performing genetic meta-analysis across disorders; subsequent molecular, cellular, in vivo, and structural functional follow-up; and epidemiological studies. Our data revealed a protective homozygous effect that defined a signaling optimum between autoimmunity and immunodeficiency and identified TYK2 as a potential drug target for certain common autoimmune disorders.

Published
2016

25. Indels, structural variation, and recombination drive genomic diversity in Plasmodium falciparum

Author

Miles, A, Iqbal, Zamin, Vauterin, P, Pearson, R, Campino, S, Theron, M, Gould, K, Mead, D, Drury, E, O'Brien, J, Ruano Rubio, V, MacInnis, B, Mwangi, J, Samarakoon, U, Ranford-Cartwright, L, Ferdig, M, Hayton, K, Su, XZ, Wellems, T, Rayner, J, McVean, G, and Kwiatkowski, D

Subjects
Recombination, Genetic, Resource, DNA Copy Number Variations, Plasmodium falciparum, Drug Resistance, Chromosome Mapping, Genetic Variation, High-Throughput Nucleotide Sequencing, Polymorphism, Single Nucleotide, Meiosis, INDEL Mutation, Humans, Malaria, Falciparum, Genome, Protozoan
Abstract

The malaria parasite Plasmodium falciparum has a great capacity for evolutionary adaptation to evade host immunity and develop drug resistance. Current understanding of parasite evolution is impeded by the fact that a large fraction of the genome is either highly repetitive or highly variable and thus difficult to analyze using short-read sequencing technologies. Here, we describe a resource of deep sequencing data on parents and progeny from genetic crosses, which has enabled us to perform the first genome-wide, integrated analysis of SNP, indel and complex polymorphisms, using Mendelian error rates as an indicator of genotypic accuracy. These data reveal that indels are exceptionally abundant, being more common than SNPs and thus the dominant mode of polymorphism within the core genome. We use the high density of SNP and indel markers to analyze patterns of meiotic recombination, confirming a high rate of crossover events and providing the first estimates for the rate of non-crossover events and the length of conversion tracts. We observe several instances of meiotic recombination within copy number variants associated with drug resistance, demonstrating a mechanism whereby fitness costs associated with resistance mutations could be compensated and greater phenotypic plasticity could be acquired.

Published
2016

26. An insight into the genetic variation of Schistosoma japonicum in mainland China using DNA microsatellite markers

Author

Shrivastava, J, Qian, BZ, Mcvean, G, and Webster, JP

Subjects
parasitic diseases
Abstract

This study presents the first microsatellite investigation into the level of genetic variation among Schistosoma japonicum from different geographical origins. S. japonicum isolates were obtained from seven endemic provinces across mainland China: Zhejiang (Jiashan County), Anhui (Guichi County), Jiangxi (Yongxiu County), Hubei (Wuhan County), Hunan (Yueyang area), Sichuan 1 (Maoshan County), Sichuan 2 (Tianquan County), Yunnan (Dali County), and also one province in the Philippines (Sorsogon). DNA from 20 individuals from each origin were screened against 11 recently isolated and characterized S. japonicum microsatellites, and a set of nine loci were selected based on their polymorphic information content. High levels of polymorphism were obtained between and within population samples, with Chinese and Philippine strains appearing to follow different lineages, and with distinct branching between provinces. Moreover, across mainland China, genotype clustering appeared to be related to habitat type and/or intermediate host morph. These results highlight the suitability of microsatellites for population genetic studies of S. japonicum and suggest that there may be different strains of S. japonicum circulating in mainland China.

Published
2016

27. Genome-Wide Association Study Implicates HLA-C*01:02 as a Risk Factor at the Major Histocompatibility Complex Locus in Schizophrenia

Author

Strange, A, Riley, BP, Spencer, CCA, Morris, DW, Pirinen, M, O'Dushlaine, CT, Su, Z, Maher, BS, Freeman, C, Cormican, P, Bellenguez, C, Kenny, EM, Band, G, Wormley, B, Donohoe, G, Dilthey, A, Moutsianas, L, Quinn, E, Edkins, S, Judge, R, Coleman, K, Hunt, S, Tropea, D, Roche, S, Cummings, L, Kelleher, E, McKeon, P, Dinan, T, McDonald, C, Murphy, KC, O'Callaghan, E, O'Neill, FA, Waddington, JL, Walsh, D, Giannoulatou, E, Langford, C, Deloukas, P, Gray, E, Dronov, S, Potter, S, Pearson, R, Vukcevic, D, Tashakkori-Ghanbaria, A, Blackwell, JM, Bramon, E, Brown, MA, Casas, JP, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Stone, J, Scolnick, E, Purcell, S, Sklar, P, Ripke, S, Walters, J, Owen, MJ, O'Donovan, MC, Peltonen, L, McVean, G, Kendler, KS, Gill, M, Donnelly, P, Corvin, A, Conso, ISG, Consortium, SGENE, Psychiat, SWG, and Consor, WTCC

Subjects
Adult, Male, Genotype, Locus (genetics), Single-nucleotide polymorphism, Genome-wide association study, Human leukocyte antigen, HLA-C Antigens, Major histocompatibility complex, Polymorphism, Single Nucleotide, Article, HLA-C, Calcium Channels, T-Type, Young Adult, Risk Factors, Databases, Genetic, tourette-syndrome, SNP, Humans, genetics, Genetic Predisposition to Disease, Allele, gene, Biological Psychiatry, Aged, Genetics, cacna1i, breakpoint, Aged, 80 and over, biology, deletions, polygene score, classical hla alleles, Middle Aged, hlac, major histocompatibility complex, disruption, biology.protein, Schizophrenia, Female, immp2l, Ireland, Genome-Wide Association Study
Abstract

BACKGROUND: We performed a genome-wide association study (GWAS) to identify common risk variants for schizophrenia. METHODS: The discovery scan included 1606 patients and 1794 controls from Ireland, using 6,212,339 directly genotyped or imputed single nucleotide polymorphisms (SNPs). A subset of this sample (270 cases and 860 controls) was subsequently included in the Psychiatric GWAS Consortium-schizophrenia GWAS meta-analysis. RESULTS: One hundred eight SNPs were taken forward for replication in an independent sample of 13,195 cases and 31,021 control subjects. The most significant associations in discovery, corrected for genomic inflation, were (rs204999, p combined = 1.34 × 10(-9) and in combined samples (rs2523722 p combined = 2.88 × 10(-16)) mapped to the major histocompatibility complex (MHC) region. We imputed classical human leukocyte antigen (HLA) alleles at the locus; the most significant finding was with HLA-C*01:02. This association was distinct from the top SNP signal. The HLA alleles DRB1*03:01 and B*08:01 were protective, replicating a previous study. CONCLUSIONS: This study provides further support for involvement of MHC class I molecules in schizophrenia. We found evidence of association with previously reported risk alleles at the TCF4, VRK2, and ZNF804A loci.

Published
2016

30. A second generation human haplotype map of over 3.1 million SNPs

Author

Frazer, KA, Ballinger, DG, Cox, DR, Hinds, DA, Stuve, LL, Gibbs, RA, Belmont, JW, Boudreau, A, Hardenbol, P, Leal, SM, Pasternak, S, Wheeler, DA, Willis, TD, Yu, F, Yang, H, Zeng, C, Gao, Y, Hu, H, Hu, W, Li, C, Lin, W, Liu, S, Pan, H, Tang, X, Wang, J, Wang, W, Yu, J, Zhang, B, Zhang, Q, Zhao, H, Zhou, J, Gabriel, SB, Barry, R, Blumenstiel, B, Camargo, A, Defelice, M, Faggart, M, Goyette, M, Gupta, S, Moore, J, Nguyen, H, Onofrio, RC, Parkin, M, Roy, J, Stahl, E, Winchester, E, Ziaugra, L, Altshuler, D, Shen, Y, Yao, Z, Huang, W, Chu, X, He, Y, Jin, L, Liu, Y, Sun, W, Wang, H, Wang, Y, Xiong, X, Xu, L, Waye, MM, Tsui, SK, Xue, H, Wong, JT, Galver, LM, Fan, JB, Gunderson, K, Murray, SS, Oliphant, AR, Chee, MS, Montpetit, A, Chagnon, F, Ferretti, V, Leboeuf, M, Olivier, JF, Phillips, MS, Roumy, S, Sallée, C, Verner, A, Hudson, TJ, Kwok, PY, Cai, D, Koboldt, DC, Miller, RD, Pawlikowska, L, Taillon-Miller, P, Xiao, M, Tsui, LC, Mak, W, Song, YQ, Tam, PK, Nakamura, Y, Kawaguchi, T, Kitamoto, T, Morizono, T, Nagashima, A, Ohnishi, Y, Sekine, A, Tanaka, T, Tsunoda, T, Deloukas, P, Bird, CP, Delgado, M, Dermitzakis, ET, Gwilliam, R, Hunt, S, Morrison, J, Powell, D, Stranger, BE, Whittaker, P, Bentley, DR, Daly, MJ, de Bakker, PI, Barrett, J, Chretien, YR, Maller, J, McCarroll, S, Patterson, N, Pe'er, I, Price, A, Purcell, S, Richter, DJ, Sabeti, P, Saxena, R, Schaffner, SF, Sham, PC, Varilly, P, Stein, LD, Krishnan, L, Smith, AV, Tello-Ruiz, MK, Thorisson, GA, Chakravarti, A, Chen, PE, Cutler, DJ, Kashuk, CS, Lin, S, Abecasis, GR, Guan, W, Li, Y, Munro, HM, Qin, ZS, Thomas, DJ, McVean, G, Auton, A, Bottolo, L, Cardin, N, Eyheramendy, S, Freeman, C, Marchini, J, Myers, S, Spencer, C, Stephens, M, Donnelly, P, Cardon, LR, Clarke, G, Evans, DM, Morris, AP, Weir, BS, Mullikin, JC, Sherry, ST, Feolo, M, Skol, A, Zhang, H, Matsuda, I, Fukushima, Y, Macer, DR, Suda, E, Rotimi, CN, Adebamowo, CA, Ajayi, I, Aniagwu, T, Marshall, PA, Nkwodimmah, C, Royal, CD, Leppert, MF, Dixon, M, Peiffer, A, Qiu, R, Kent, A, Kato, K, Niikawa, N, Adewole, IF, Knoppers, BM, Foster, MW, Clayton, EW, Watkin, J, Muzny, D, Nazareth, L, Sodergren, E, Weinstock, GM, Yakub, I, Birren, BW, Wilson, RK, Fulton, LL, Rogers, J, Burton, J, Carter, NP, Clee, CM, Griffiths, M, Jones, MC, McLay, K, Plumb, RW, Ross, MT, Sims, SK, Willey, DL, Chen, Z, Han, H, Kang, L, Godbout, M, Wallenburg, JC, L'Archevêque, P, Bellemare, G, Saeki, K, An, D, Fu, H, Li, Q, Wang, Z, Wang, R, Holden, AL, Brooks, LD, McEwen, JE, Guyer, MS, Wang, VO, Peterson, JL, Shi, M, Spiegel, J, Sung, LM, Zacharia, LF, Collins, FS, Kennedy, K, Jamieson, R, and Stewart, J

Subjects
Male, Recombination, Genetic, Genetics, Linkage disequilibrium, education.field_of_study, Multidisciplinary, Homozygote, Racial Groups, Haplotype, Population, Single-nucleotide polymorphism, Tag SNP, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Article, Haplotypes, Humans, Female, Selection, Genetic, International HapMap Project, education, Imputation (genetics), Genetic association
Abstract

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r 2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r 2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations. ©2007 Nature Publishing Group., link_to_OA_fulltext

Published
2016

31. Integrating common and rare genetic variation in diverse human populations

Author

Altshuler, D, Gibbs, R, Peltonen, L, Dermitzakis, E, Schaffner, S, Yu, F, Bonnen, P, de Bakker, P, Deloukas, P, Gabriel, S, Gwilliam, R, Hunt, S, Inouye, M, Jia, X, Palotie, A, Parkin, M, Whittaker, P, Chang, K, Hawes, A, Lewis, L, Ren, Y, Wheeler, D, Muzny, D, Barnes, C, Darvishi, K, Hurles, M, Korn, J, Kristiansson, K, Lee, C, McCarrol, SA, Nemesh, J, Keinan, A, Montgomery, S, Pollack, S, Price, A, Soranzo, N, Gonzaga-Jauregui, C, Anttila, V, Brodeur, W, Daly, M, Leslie, S, McVean, G, Moutsianas, L, Nguyen, H, Zhang, Q, Ghori, M, McGinnis, R, McLaren, W, Takeuchi, F, Grossman, SR, Shlyakhter, I, Hostetter, E, Sabeti, P, Adebamowo, C, Foster, M, Gordon, DR, Licinio, J, Manca, M, Marshall, P, Matsuda, I, Ngare, D, Wang, V, Reddy, D, Rotimi, C, Royal, C, Sharp, R, Zeng, C, Brooks, L, McEwen, J, Dermitzakis, Emmanouil, and Montgomery, Stephen

Subjects
DNA Copy Number Variations, Single-nucleotide polymorphism, Genome-wide association study, Human genetic variation, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Genome, Human, 0302 clinical medicine, Population Groups, Population Groups/*genetics, Human Genome Project, Humans, ddc:576.5, Copy-number variation, International HapMap Project, 030304 developmental biology, Genetics, 0303 health sciences, Multidisciplinary, SNP genotyping, Minor allele frequency, 030217 neurology & neurosurgery, Imputation (genetics)
Abstract

Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called 'HapMap 3', includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of

Published
2010

32. Imputation of KIR Types from SNP Variation Data

Author

Vukcevic, D, Traherne, J, Næss, S, Ellinghaus, E, Kamatani, Y, Dilthey, A, Lathrop, M, Karlsen, T, Franke, A, Moffatt, M, Cookson, W, Trowsdale, J, McVean, G, Sawcer, S, Leslie, S, Traherne, James [0000-0002-6003-8559], Trowsdale, John [0000-0002-0150-5698], Sawcer, Stephen [0000-0001-7685-0974], Apollo - University of Cambridge Repository, and Wellcome Trust

Subjects
Male, NK CELL RECEPTORS, DNA Copy Number Variations, Genotype, LOCI, chemical and pharmacologic phenomena, SUSCEPTIBILITY, ERAP1, Polymorphism, Single Nucleotide, DISEASE, Dermatitis, Atopic, Cohort Studies, Receptors, KIR, Genetics, otorhinolaryngologic diseases, Humans, Genetics(clinical), Family, Genetic Predisposition to Disease, Genetics & Heredity, RISK, CLASSICAL HLA ALLELES, Science & Technology, High-Throughput Nucleotide Sequencing, hemic and immune systems, 11 Medical And Health Sciences, Sequence Analysis, DNA, 06 Biological Sciences, Asthma, Europe, Case-Control Studies, LIGANDS, Female, Life Sciences & Biomedicine
Abstract

Large population studies of immune system genes are essential for characterizing their role in diseases, including autoimmune conditions. Of key interest are a group of genes encoding the killer cell immunoglobulin-like receptors (KIRs), which have known and hypothesized roles in autoimmune diseases, resistance to viruses, reproductive conditions, and cancer. These genes are highly polymorphic, which makes typing expensive and time consuming. Consequently, despite their importance, KIRs have been little studied in large cohorts. Statistical imputation methods developed for other complex loci (e.g., human leukocyte antigen [HLA]) on the basis of SNP data provide an inexpensive high-throughput alternative to direct laboratory typing of these loci and have enabled important findings and insights for many diseases. We present KIR∗IMP, a method for imputation of KIR copy number. We show that KIR∗IMP is highly accurate and thus allows the study of KIRs in large cohorts and enables detailed investigation of the role of KIRs in human disease.

Published
2015

33. The Power of Gene-Based Rare Variant Methods to Detect Disease-Associated Variation and Test Hypotheses About Complex Disease

Author

Moutsianas, L., Agarwala, V., Fuchsberger, C., Flannick, J., Rivas, M.A., Gaulton, K.J., Albers, P.K., GoT2D Consortium (McCarthy, M.I., Gieger, C., Grallert, H., Hrabě de Angelis, M., Huth, C., Kriebel, J., Meisinger, C., Meitinger, T., Müller-Nurasyid, M., Peters, A., Ried, J.S., Strauch, K., Strom, T.M.), McVean, G., Boehnke, M., and Altshuler, D.

Subjects
Phenotype, Diabetes Mellitus, Type 2, Genetic Diseases, Inborn, Genetic Variation, Humans, Computer Simulation, Exome, Genetic Predisposition to Disease, Models, Theoretical, Alleles, Linkage Disequilibrium, Research Article, Genome-Wide Association Study
Abstract

Genome and exome sequencing in large cohorts enables characterization of the role of rare variation in complex diseases. Success in this endeavor, however, requires investigators to test a diverse array of genetic hypotheses which differ in the number, frequency and effect sizes of underlying causal variants. In this study, we evaluated the power of gene-based association methods to interrogate such hypotheses, and examined the implications for study design. We developed a flexible simulation approach, using 1000 Genomes data, to (a) generate sequence variation at human genes in up to 10K case-control samples, and (b) quantify the statistical power of a panel of widely used gene-based association tests under a variety of allelic architectures, locus effect sizes, and significance thresholds. For loci explaining ~1% of phenotypic variance underlying a common dichotomous trait, we find that all methods have low absolute power to achieve exome-wide significance (~5-20% power at α=2.5×10-6) in 3K individuals; even in 10K samples, power is modest (~60%). The combined application of multiple methods increases sensitivity, but does so at the expense of a higher false positive rate. MiST, SKAT-O, and KBAC have the highest individual mean power across simulated datasets, but we observe wide architecture-dependent variability in the individual loci detected by each test, suggesting that inferences about disease architecture from analysis of sequencing studies can differ depending on which methods are used. Our results imply that tens of thousands of individuals, extensive functional annotation, or highly targeted hypothesis testing will be required to confidently detect or exclude rare variant signals at complex disease loci., Author Summary Re-sequencing technologies allow for a more complete interrogation of the role of human variation in complex disease. The inadequate power of single variant methods to assess the role of less common variation has led to the development of numerous statistical methods for testing aggregate groups of variants for association with disease. Such endeavors pose substantial analytical challenges, however, due to the diverse array of genetic hypotheses that need to be considered. In this work, we systematically quantify and compare the performance of a panel of commonly used gene-based association methods under a range of allelic architectures, significance thresholds, locus effect sizes, sample sizes, and filters for neutral variation. We find that MiST, SKAT-O, and KBAC have the highest mean power across simulated datasets. Across all methods, however, the power to detect even loci of relatively large effect is very low at exome-wide significance thresholds for sample sizes comparable with those of ongoing sequencing studies; as such, the absence of signal in studies of a few thousand individuals does not exclude a role for rare variation in complex traits. Finally, we directly compare the results reported by different gene-based methods in order to identify their comparative advantages and disadvantages under distinct locus architectures. Our findings have implications for meaningful interpretation of both positive and negative findings in ongoing and future sequencing studies.

Published
2015

34. Genomic epidemiology of artemisinin resistant malaria

Author

Amato, R., Miotto, O., Woodrow, C.J., Almagro-Garcia, J., Sinha, I., Campino, S., Mead, D., Drury, E., Kekre, M., Sanders, M., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andrianaranjaka, V., Apinjoh, T., Ashley, E., Auburn, S., Awandare, G.A., Baraka, V., Barry, Alyssa, Boni, M.F., Borrmann, S., Bousema, T., Branch, O., Bull, P.C., Chotivanich, K., Conway, D.J., Craig, A., Day, N.P., Djimdé, A., Dolecek, C., Dondorp, A.M., Drakeley, C., Duffy, P., Echeverry, D.F., Egwang, T.G., Fairhurst, R.M., Faiz, A., Fanello, C.I., Hien, T.T., Hodgson, A., Imwong, M., Ishengoma, D., Lim, P., Lon, C., Marfurt, J., Marsh, K., Mayxay, M., Michon, P., Mobegi, V., Mokuolu, O.A., Montgomery, J., Mueller, I., Kyaw, M.P., Newton, P.N., Nosten, F., Noviyanti, R., Nzila, A., Ocholla, H., Oduro, A., Onyamboko, M., Ouedraogo, J.B., Phyo, A.P.P., Plowe, C., Price, R.N., Pukrittayakamee, S., Randrianarivelojosia, M., Ringwald, P., Ruiz, L., Saunders, D., Shayo, A., Siba, P., Takala-Harrison, S., Thanh, T.N.N., Thathy, V., Verra, F., Wendler, J., White, N.J., Ye, H., Cornelius, V.J., Giacomantonio, R., Muddyman, D., Henrichs, C., Malangone, C., Jyothi, D., Pearson, R.D., Rayner, J.C., McVean, G., Rockett, K.A., Miles, A., Vauterin, P., Jeffery, B., Manske, M., Stalker, J., Macinnis, B., Kwiatkowski, D.P., Amato, R., Miotto, O., Woodrow, C.J., Almagro-Garcia, J., Sinha, I., Campino, S., Mead, D., Drury, E., Kekre, M., Sanders, M., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andrianaranjaka, V., Apinjoh, T., Ashley, E., Auburn, S., Awandare, G.A., Baraka, V., Barry, Alyssa, Boni, M.F., Borrmann, S., Bousema, T., Branch, O., Bull, P.C., Chotivanich, K., Conway, D.J., Craig, A., Day, N.P., Djimdé, A., Dolecek, C., Dondorp, A.M., Drakeley, C., Duffy, P., Echeverry, D.F., Egwang, T.G., Fairhurst, R.M., Faiz, A., Fanello, C.I., Hien, T.T., Hodgson, A., Imwong, M., Ishengoma, D., Lim, P., Lon, C., Marfurt, J., Marsh, K., Mayxay, M., Michon, P., Mobegi, V., Mokuolu, O.A., Montgomery, J., Mueller, I., Kyaw, M.P., Newton, P.N., Nosten, F., Noviyanti, R., Nzila, A., Ocholla, H., Oduro, A., Onyamboko, M., Ouedraogo, J.B., Phyo, A.P.P., Plowe, C., Price, R.N., Pukrittayakamee, S., Randrianarivelojosia, M., Ringwald, P., Ruiz, L., Saunders, D., Shayo, A., Siba, P., Takala-Harrison, S., Thanh, T.N.N., Thathy, V., Verra, F., Wendler, J., White, N.J., Ye, H., Cornelius, V.J., Giacomantonio, R., Muddyman, D., Henrichs, C., Malangone, C., Jyothi, D., Pearson, R.D., Rayner, J.C., McVean, G., Rockett, K.A., Miles, A., Vauterin, P., Jeffery, B., Manske, M., Stalker, J., Macinnis, B., and Kwiatkowski, D.P.

Published
2016

35. Genomic epidemiology of artemisinin resistant malaria

Author

Amato, R, Miotto, O, Woodrow, CJ, Almagro-Garcia, J, Sinha, I, Campino, S, Mead, D, Drury, E, Kekre, M, Sanders, M, Amambua-Ngwa, A, Amaratunga, C, Amenga-Etego, L, Andrianaranjaka, V, Apinjoh, T, Ashley, E, Auburn, S, Awandare, GA, Baraka, V, Barry, A, Boni, MF, Borrmann, S, Bousema, T, Branch, O, Bull, PC, Chotivanich, K, Conway, DJ, Craig, A, Day, NP, Djimde, A, Dolecek, C, Dondorp, AM, Drakeley, C, Duffy, P, Echeverry, DF, Egwang, TG, Fairhurst, RM, Faiz, MA, Fanello, CI, Tran, TH, Hodgson, A, Imwong, M, Ishengoma, D, Lim, P, Lon, C, Marfurt, J, Marsh, K, Mayxay, M, Michon, P, Mobegi, V, Mokuolu, OA, Montgomery, J, Mueller, I, Kyaw, MP, Newton, PN, Nosten, F, Noviyanti, R, Nzila, A, Ocholla, H, Oduro, A, Onyamboko, M, Ouedraogo, J-B, Phyo, APP, Plowe, C, Price, RN, Pukrittayakamee, S, Randrianarivelojosia, M, Ringwald, P, Ruiz, L, Saunders, D, Shayo, A, Siba, P, Takala-Harrison, S, Thanh, T-NN, Thathy, V, Verra, F, Wendler, J, White, NJ, Ye, H, Cornelius, VJ, Giacomantonio, R, Muddyman, D, Henrichs, C, Malangone, C, Jyothi, D, Pearson, RD, Rayner, JC, McVean, G, Rockett, KA, Miles, A, Vauterin, P, Jeffery, B, Manske, M, Stalker, J, Maclnnis, B, Kwiatkowski, DP, Amato, R, Miotto, O, Woodrow, CJ, Almagro-Garcia, J, Sinha, I, Campino, S, Mead, D, Drury, E, Kekre, M, Sanders, M, Amambua-Ngwa, A, Amaratunga, C, Amenga-Etego, L, Andrianaranjaka, V, Apinjoh, T, Ashley, E, Auburn, S, Awandare, GA, Baraka, V, Barry, A, Boni, MF, Borrmann, S, Bousema, T, Branch, O, Bull, PC, Chotivanich, K, Conway, DJ, Craig, A, Day, NP, Djimde, A, Dolecek, C, Dondorp, AM, Drakeley, C, Duffy, P, Echeverry, DF, Egwang, TG, Fairhurst, RM, Faiz, MA, Fanello, CI, Tran, TH, Hodgson, A, Imwong, M, Ishengoma, D, Lim, P, Lon, C, Marfurt, J, Marsh, K, Mayxay, M, Michon, P, Mobegi, V, Mokuolu, OA, Montgomery, J, Mueller, I, Kyaw, MP, Newton, PN, Nosten, F, Noviyanti, R, Nzila, A, Ocholla, H, Oduro, A, Onyamboko, M, Ouedraogo, J-B, Phyo, APP, Plowe, C, Price, RN, Pukrittayakamee, S, Randrianarivelojosia, M, Ringwald, P, Ruiz, L, Saunders, D, Shayo, A, Siba, P, Takala-Harrison, S, Thanh, T-NN, Thathy, V, Verra, F, Wendler, J, White, NJ, Ye, H, Cornelius, VJ, Giacomantonio, R, Muddyman, D, Henrichs, C, Malangone, C, Jyothi, D, Pearson, RD, Rayner, JC, McVean, G, Rockett, KA, Miles, A, Vauterin, P, Jeffery, B, Manske, M, Stalker, J, Maclnnis, B, and Kwiatkowski, DP

Abstract

The current epidemic of artemisinin resistant Plasmodium falciparum in Southeast Asia is the result of a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non-synonymous mutations, many of which cause radical amino-acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of variations that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions.

Published
2016

36. Human genomic regions with exceptionally high levels of population differentiation identified from 911 whole-genome sequences

Author

Colonna, V, Ayub, Q, Chen, Y, Pagani, L, Luisi, P, Pybus, M, Garrison, E, Xue, Y, Tyler-Smith, C, Abecasis, GR, Auton, A, Brooks, LD, Depristo, MA, Durbin, RM, Handsaker, RE, Kang, HM, Marth, GT, McVean, G, Altshuler, DM, Bentley, DR, Chakravarti, A, Clark, AG, Donnelly, P, Eichler, EE, Flicek, P, Gabriel, SB, Gibbs, RA, Green, ED, Hurles, ME, Knoppers, BM, Korbel, JO, Lander, ES, Lee, C, Lehrach, H, Mardis, ER, McVean, GA, Nickerson, DA, Schmidt, JP, Sherry, ST, Wang, J, Wilson, RK, Dinh, H, Kovar, C, Lee, S, Lewis, L, Muzny, D, Reid, J, Wang, M, Fang, X, Guo, X, Jian, M, Jiang, H, Jin, X, Li, G, Li, J, Li, Y, Li, Z, Liu, X, Lu, Y, Ma, X, Su, Z, Tai, S, Tang, M, Wang, B, Wang, G, Wu, H, Wu, R, Yin, Y, Zhang, W, Zhao, J, Zhao, M, Zheng, X, Zhou, Y, Gupta, N, Clarke, L, Leinonen, R, Smith, RE, Zheng-Bradley, X, Grocock, R, Humphray, S, James, T, Kingsbury, Z, Sudbrak, R, Albrecht, MW, Amstislavskiy, VS, Borodina, TA, Lienhard, M, Mertes, F, Sultan, M, Timmermann, B, Yaspo, ML, Fulton, L, Fulton, R, Weinstock, GM, Balasubramaniam, S, Burton, J, Danecek, P, Keane, TM, Kolb-Kokocinski, A, McCarthy, S, Molecular Dynamics, Biomimetics, Urban and Regional Studies Institute, Nanomedicine & Drug Targeting, Artificial Intelligence, Micromechanics, Molecular Cell Biology, Van Swinderen Institute for Particle Physics and G, Archaeology of Northwestern Europe, Polymer Chemistry and Bioengineering, Christianity and the History of Ideas, Scientific Visualization and Computer Graphics, Chemical Technology, Macromolecular Chemistry & New Polymeric Materials, Bernoulli Institute, Surfaces and Thin Films, Hemelrijk group, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Falcao Salles lab, Synthetic Organic Chemistry, Psychometrics and Statistics, Bio-inspired systems and circuits, Advanced Production Engineering, Drug Design, The 1000 Genomes Project Consortium, Faculteit Medische Wetenschappen/UMCG, Wellcome Trust, Consiglio Nazionale delle Ricerche, EMBO, and 1000 Genomes Project Consortium

Subjects
Historia y Arqueología, lactase persistence, POSITIVE SELECTION, BALANCING SELECTION, SOFT SWEEP, Biología, standing variation, Population, Biology, Balancing selection, Genome, Polymorphism, Single Nucleotide, Genètica de poblacions humanes, Ciencias Biológicas, purl.org/becyt/ford/1 [https], selective sweep, functional annotation cluster, Genética y Herencia, HUMANIDADES, Genetic drift, Gene Frequency, INDEL Mutation, Humans, Selection, Genetic, education, purl.org/becyt/ford/1.6 [https], Selection (genetic algorithm), education.field_of_study, purl.org/becyt/ford/6 [https], Genome, Human, Research, Genetic Drift, Levenshtein distance, Selecció natural, Sequence Analysis, DNA, Human genetics, Otras Historia y Arqueología, Evolutionary biology, Human genome, purl.org/becyt/ford/6.1 [https], Selective sweep, Genètica humana -- Variació, CIENCIAS NATURALES Y EXACTAS
Abstract

It contains associated material.-- The 1000 Genomes Project Consortium, [Background] Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes., [Results] We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively., [Conclusions] We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research. © 2014 Colonna et al., This work was supported by The Wellcome Trust (098051), an Italian National Research Council (CNR) short-term mobility fellowship from the 2013 program to VC, and an EMBO Short Term Fellowship ASTF 324–2010 to VC.

Published
2014

37. Nonhuman genetics. Strong male bias drives germline mutation in chimpanzees

Author

Venn, O, Turner, I, Mathieson, I, de Groot, N, Bontrop, R, and McVean, G

Abstract

Germ line mutation determines rates of molecular evolution, genetic diversity and fitness load. In humans, the average point mutation rate is 1.2 x 10^-8 per base pair per generation, with every additional year of father’s age contributing 2 mutations across the genome and males contributing 3-4 times more mutation than females. To assess whether such patterns are shared with our closest living relatives we sequenced the genomes of a nine-member pedigree of Western chimpanzees, Pan troglodytes verus. Our results indicate a mutation rate of 1.2 x 10^-8 per base pair per generation, but a male contribution 7-8 times that of females and a paternal age effect of 3 mutations per year of father’s age. Thus mutation rates and patterns differ between closely related species.

Published
2014

38. Clinical whole-genome sequencing in severe early-onset epilepsy reveals new genes and improves molecular diagnosis

Author

Martin, H, Kim, G, Pagnamenta, A, Murakami, Y, Carvill, G, Meyer, E, Copley, R, Rimmer, A, Barcia, G, Fleming, MR, Kronengold, J, Brown, MR, Hudspith, K, Broxholme, J, Kanapin, A, Cazier, J, Kinoshita, T, Nabbout, R, Bentley, D, McVean, G, Heavin, S, Zaiwalla, Z, McShane, T, Mefford, H, Shears, D, Stewart, H, Kurian, M, Scheffer, I, Blair, E, Donnelly, P, Kaczmarek, L, and Taylor, J

Subjects
Male, Epilepsy, NAV1.2 Voltage-Gated Sodium Channel, Potassium Channels, High-Throughput Nucleotide Sequencing, Membrane Proteins, Nerve Tissue Proteins, Articles, Potassium Channels, Sodium-Activated, Uniparental Disomy, Young Adult, Child, Preschool, Mutation, Humans, KCNQ2 Potassium Channel, Genetic Predisposition to Disease, Proto-Oncogene Proteins c-cbl, Pathology, Molecular, Child, Chromosomes, Human, Pair 9, Genome-Wide Association Study
Abstract

In severe early-onset epilepsy, precise clinical and molecular genetic diagnosis is complex, as many metabolic and electro-physiological processes have been implicated in disease causation. The clinical phenotypes share many features such as complex seizure types and developmental delay. Molecular diagnosis has historically been confined to sequential testing of candidate genes known to be associated with specific sub-phenotypes, but the diagnostic yield of this approach can be low. We conducted whole-genome sequencing (WGS) on six patients with severe early-onset epilepsy who had previously been refractory to molecular diagnosis, and their parents. Four of these patients had a clinical diagnosis of Ohtahara Syndrome (OS) and two patients had severe non-syndromic early-onset epilepsy (NSEOE). In two OS cases, we found de novo non-synonymous mutations in the genes KCNQ2 and SCN2A. In a third OS case, WGS revealed paternal isodisomy for chromosome 9, leading to identification of the causal homozygous missense variant in KCNT1, which produced a substantial increase in potassium channel current. The fourth OS patient had a recessive mutation in PIGQ that led to exon skipping and defective glycophosphatidyl inositol biosynthesis. The two patients with NSEOE had likely pathogenic de novo mutations in CBL and CSNK1G1, respectively. Mutations in these genes were not found among 500 additional individuals with epilepsy. This work reveals two novel genes for OS, KCNT1 and PIGQ. It also uncovers unexpected genetic mechanisms and emphasizes the power of WGS as a clinical tool for making molecular diagnoses, particularly for highly heterogeneous disorders.

Published
2014

39. Contributions of intrinsic mutation rate and selfish selection to levels of de novo HRAS mutations in the paternal germline

Author

Giannoulatou, E, McVean, G, Taylor, IB, McGowan, SJ, Maher, GJ, Iqbal, Z, Pfeifer, SP, Turner, I, Wright, EMMB, Shorto, J, Itani, A, Turner, K, Gregory, L, Buck, D, Rajpert-De Meyts, E, Looijenga, LHJ (Leendert), Kerr, B, Wilkie, AOM, Goriely, A, and Pathology

Subjects
SDG 3 - Good Health and Well-being
Abstract

The RAS proto-oncogene Harvey rat sarcoma viral oncogene homolog (HRAS) encodes a small GTPase that transduces signals from cell surface receptors to intracellular effectors to control cellular behavior. Although somatic HRAS mutations have been described in many cancers, germline mutations cause Costello syndrome (CS), a congenital disorder associated with predisposition to malignancy. Based on the epidemiology of CS and the occurrence of HRAS mutations in spermatocytic seminoma, we proposed that activating HRAS mutations become enriched in sperm through a process akin to tumorigenesis, termed selfish spermatogonial selection. To test this hypothesis, we quantified the levels, in blood and sperm samples, of HRAS mutations at the p.G12 codon and compared the results to changes at the p.A11 codon, at which activating mutations do not occur. The data strongly support the role of selection in determining HRAS mutation levels in sperm, and hence the occurrence of CS, but we also found differences from the mutation pattern in tumorigenesis. First, the relative prevalence of mutations in sperm correlates weakly with their in vitro activating properties and occurrence in cancers. Second, specific tandem base substitutions (predominantly GC>TT/AA) occur in sperm but not in cancers; genomewide analysis showed that this same mutation is also overrepresented in constitutional pathogenic and polymorphic variants, suggesting a heightened vulnerability to these mutations in the germline. We developed a statistical model to show how both intrinsic mutation rate and selfish selection contribute to the mutational burden borne by the paternal germline.

Published
2013

40. A global reference for human genetic variation

Author

Auton, A., Brooks, L.D., Durbin, R.M., Garrison, E., Kang, H.M., Korbel, J.O., Marchini, J., McCarthy, S., McVean, G., Abecasis, G.R., Albers, C.A., et al., Auton, A., Brooks, L.D., Durbin, R.M., Garrison, E., Kang, H.M., Korbel, J.O., Marchini, J., McCarthy, S., McVean, G., Abecasis, G.R., Albers, C.A., and et al.

Abstract

Contains fulltext : 152128.pdf (publisher's version ) (Open Access)

Published
2015

41. Erratum: Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas (Nature Genetics (2013) 45 (136-144))

Author

Palles, C, Cazier, J-B, Howarth, KM, Domingo, E, Jones, AM, Broderick, P, Kemp, Z, Spain, SL, Almeida, EG, Salguero, I, Sherborne, A, Chubb, D, Carvajal-Carmona, LG, Ma, Y, Kaur, K, Dobbins, S, Barclay, E, Gorman, M, Martin, L, Kovac, MB, Humphray, S, Lucassen, A, Holmes, CC, Bentley, D, Donnelly, P, Taylor, J, Petridis, C, Roylance, R, Sawyer, EJ, Kerr, DJ, Clark, S, Grimes, J, Kearsey, SE, Thomas, HJW, McVean, G, Houlston, RS, and Tomlinson, I

Published
2013

42. The origin, evolution, and functional impact of short insertion-deletion variants identified in 179 human genomes

Author

Montgomery, S., Goode, D., Kvikstad, E., Albers, C., Zhang, Z., Mu, X., Ananda, G., Howie, B., Karczewski, K., Smith, K., Anaya, V., Richardson, R., Davis, J., 1000 Genome Project, C., Timmermann, B., MacArthur, D., Sidow, A., Duret, L., Gerstein, M., Makova, K., Marchini, J., McVean, G., and Lunter, G.

Subjects
food and beverages
Abstract

Short insertions and deletions (indels) are the second most abundant form of human genetic variation, but our understanding of their origins and functional effects lags behind that of other types of variants. Using population-scale sequencing, we have identified a high-quality set of 1.6 million indels from 179 individuals representing 3 diverse human populations. We show that rates of indel mutagenesis are highly heterogeneous, with 43-48% of indels occurring in 4.03% of the genome we classify as indel hotspots, while in the remaining 96% their prevalence is 16-times lower than that for SNPs. Polymerase slippage can explain upwards of 3/4 of all indels, including virtually all hotspot indels. The remainder are mostly simple deletions in complex sequence, but insertions do occur and are significantly associated with pseudo-palindromic sequence features compatible with the fork stalling and template switching (FoSTeS) mechanism more commonly associated with large structural variations. We introduce a quantitative model of polymerase slippage showing an excellent fit to observed levels of variation, which enables us to identify a minority of indel-hypermutagenic protein-coding genes, some of which are associated with recurrent mutations leading to disease. Accounting for mutational rate heterogenetity due to sequence context, we find that indels across functional sequence are generally subject to stronger purifying selection than SNPs. We find that indel length modulates selection strength, as is well known of frameshift mutations in coding regions, but also longer indels and indels affecting multiple functionally constrained nucleotides are more strongly selected against in various non-coding contexts. We further find that indels are enriched in associations with gene expression, and find evidence for a contribution of nonsense-mediated decay to this association. Finally, we show that indels can be integrated in existing GWAS studies, and although we do not find direct evidence that potentially causal protein-coding indels are enriched with strong associations to known disease-associated SNPs, many of our findings suggest that the causal variant underlying some of these associations may be indels.

Published
2013

43. Bayesian refinement of association signals for 14 loci in 3 common diseases

Author

Maller, JB, McVean, G, Byrnes, J, Vukcevic, D, Palin, K, Su, Z, Howson, JMM, Auton, A, Myers, S, Morris, A, Pirinen, M, Brown, MA, Burton, PR, Caulfield, MJ, Compston, A, Farrall, M, Hall, AS, Hattersley, AT, Hill, AVS, Mathew, CG, Pembrey, M, Satsangi, J, Stratton, MR, Worthington, J, Craddock, N, Hurles, M, Ouwehand, W, Parkes, M, Rahman, N, Duncanson, A, Todd, JA, Kwiatkowski, DP, Samani, NJ, Gough, SCL, McCarthy, MI, Deloukas, P, and Donnelly, P

Subjects
endocrine system diseases, Posterior probability, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Single-nucleotide polymorphism, Genome-wide association study, Coronary Artery Disease, Biology, FTO gene, Polymorphism, Single Nucleotide, Article, Bayes' theorem, Genetics, Humans, CTLA-4 Antigen, Genetic Predisposition to Disease, Genetic association, Cyclin-Dependent Kinase Inhibitor p15, Homeodomain Proteins, tRNA Methyltransferases, Genes, p16, Proteins, nutritional and metabolic diseases, Bayes Theorem, Cyclin-Dependent Kinase 5, Graves Disease, TRNA Methyltransferases, Diabetes Mellitus, Type 2, Genetic Loci, TCF7L2, Transcription Factor 7-Like 2 Protein, Genome-Wide Association Study, Transcription Factors
Abstract

To further investigate susceptibility loci identified by genome-wide association studies, we genotyped 5,500 SNPs across 14 associated regions in 8,000 samples from a control group and 3 diseases: type 2 diabetes (T2D), coronary artery disease (CAD) and Graves' disease. We defined, using Bayes theorem, credible sets of SNPs that were 95% likely, based on posterior probability, to contain the causal disease-associated SNPs. In 3 of the 14 regions, TCF7L2 (T2D), CTLA4 (Graves' disease) and CDKN2A-CDKN2B (T2D), much of the posterior probability rested on a single SNP, and, in 4 other regions (CDKN2A-CDKN2B (CAD) and CDKAL1, FTO and HHEX (T2D)), the 95% sets were small, thereby excluding most SNPs as potentially causal. Very few SNPs in our credible sets had annotated functions, illustrating the limitations in understanding the mechanisms underlying susceptibility to common diseases. Our results also show the value of more detailed mapping to target sequences for functional studies. © 2012 Nature America, Inc. All rights reserved.

Published
2012

47. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease

Author

Jostins, Luke, Ripke, Stephan, Weersma, Rinse K., Duerr, Richard H., Mcgovern, Dermot P., Hui, Ken Y., Lee, James C., Philip Schumm, L., Sharma, Yashoda, Anderson, Carl A., Essers, Jonah, Mitrovic, Mitja, Ning, Kaida, Cleynen, Isabelle, Theatre, Emilie, Spain, Sarah L., Raychaudhuri, Soumya, Goyette, Philippe, Wei, Zhi, Abraham, Clara, Achkar, Jean Paul, Ahmad, Tariq, Amininejad, Leila, Ananthakrishnan, Ashwin N., Andersen, Vibeke, Andrews, Jane M., Baidoo, Leonard, Balschun, Tobias, Bampton, Peter A., Bitton, Alain, Boucher, Gabrielle, Brand, Stephan, Büning, Carsten, Cohain, Ariella, Cichon, Sven, D'Amato, Mauro, De Jong, Dirk, Devaney, Kathy L., Dubinsky, Marla, Edwards, Cathryn, Ellinghaus, David, Ferguson, Lynnette R., Franchimont, Denis, Fransen, Karin, Gearry, Richard, Georges, Michel, Gieger, Christian, Glas, Jürgen, Haritunians, Talin, Hart, Ailsa, Hawkey, Chris, Hedl, Matija, Xinli, Hu, Karlsen, Tom H., Kupcinskas, Limas, Kugathasan, Subra, Latiano, Anna, Laukens, Debby, Lawrance, Ian C., Lees, Charlie W., Louis, Edouard, Mahy, Gillian, Mansfield, John, Morgan, Angharad R., Mowat, Craig, Newman, William, Palmieri, Orazio, Ponsioen, Cyriel Y., Potocnik, Uros, Prescott, Natalie J., Regueiro, Miguel, Rotter, Jerome I., Russell, Richard K., Sanderson, Jeremy D., Sans, Miquel, Satsangi, Jack, Schreiber, Stefan, Simms, Lisa A., Sventoraityte, Jurgita, Targan, Stephan R., Taylor, Kent D., Tremelling, Mark, Verspaget, Hein W., De Vos, Martine, Wijmenga, Cisca, Wilson, David C., Winkelmann, Juliane, Xavier, Ramnik J., Zeissig, Sebastian, Zhang, Bin, Zhang, Clarence K., Zhao, Hongyu, Silverberg, Mark S., Annese, Vito, Hakonarson, Hakon, Brant, Steven R., Radford Smith, Graham, Mathew, Christopher G., Rioux, John D., Schadt, Eric E., Daly, Mark J., Franke, Andre, Parkes, Miles, Vermeire, Severine, Barrett, Jeffrey C., Cho, Judy H., Barclay, M, Peyrin Biroulet, L, Chamaillard, M, Colombel, Jf, Cottone, M, Croft, A, D'Incà, R, Halfvarson J, Hanigan K, Henderson, P, Hugot, Jp, Karban, A, Kennedy, Na, Khan, Ma, Lémann, M, Levine, A, Massey, D, Milla, M, Montgomery, Gw, Ng, Sm, Oikonomou, I, Peeters, H, Proctor, Dd, Rahier, Jf, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, Laura, Taylor, Km, Törkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, Mh, Zhang, H, Zhang, W, Andrews, Jm, Bampton, Pa, Florin, Th, Gearry, R, Krishnaprasad, K, Lawrance, Ic, Mahy, G, Radford Smith, G, Roberts, Rl, Simms, La, Amininijad, L, Cleynen, I, Dewit, O, Franchimont, D, Georges, M, Laukens, D, Theatre, E, Vermeire, S, Aumais, G, Baidoo, L, Barrie AM 3rd, Beck, K, Bernard, Ej, Binion, Dg, Bitton, A, Brant, Sr, Cho, Jh, Cohen, A, Croitoru, K, Daly, Mj, Datta, Lw, Deslandres, C, Duerr, Rh, Dutridge, D, Ferguson, J, Fultz, J, Goyette, P, Greenberg, Gr, Haritunians, T, Jobin, G, Katz, S, Lahaie, Rg, Mcgovern, Dp, Nelson, L, Ning, K, Paré, P, Regueiro, Md, Rioux, Jd, Ruggiero, E, Schumm, L, Schwartz, M, Scott, R, Sharma, Y, Silverberg, Ms, Spears, D, Steinhart, A, Stempak, Jm, Swoger, Jm, Tsagarelis, C, Zhang, C, Zhao, H, Aerts, J, Ahmad, T, Arbury, H, Attwood, A, Auton, A, Ball, Sg, Balmforth, Aj, Barnes, C, Barrett, Jc, Barroso, I, Barton, A, Bennett, Aj, Bhaskar, S, Blaszczyk, K, Bowes, J, Brand, Oj, Braund, Ps, Bredin, F, Breen, G, Brown, Mj, Bruce, In, Bull, J, Burren, Os, Burton, J, Byrnes, J, Caesar, S, Cardin, N, Clee, Cm, Coffey, Aj, Connell, Jm, Conrad, Df, Cooper, Jd, Dominiczak, Af, Downes, K, Drummond, He, Dudakia, D, Dunham, A, Ebbs, B, Eccles, D, Edkins, S, Edwards, C, Elliot, A, Emery, P, Evans, Dm, Evans, G, Eyre, S, Farmer, A, Ferrier, In, Flynn, E, Forbes, A, Forty, L, Franklyn, Ja, Frayling, Tm, Freathy, Rm, Giannoulatou, E, Gibbs, P, Gilbert, P, Gordon Smith, K, Gray, E, Green, E, Groves, Cj, Grozeva, D, Gwilliam, R, Hall, A, Hammond, N, Hardy, M, Harrison, P, Hassanali, N, Hebaishi, H, Hines, S, Hinks, A, Hitman, Ga, Hocking, L, Holmes, C, Howard, E, Howard, P, Howson, Jm, Hughes, D, Hunt, S, Isaacs, Jd, Jain, M, Jewell, Dp, Johnson, T, Jolley, Jd, Jones, Ir, Jones, La, Kirov, G, Langford, Cf, Lango Allen, H, Lathrop, Gm, Lee, J, Lee, Kl, Lees, C, Lewis, K, Lindgren, Cm, Maisuria Armer, M, Maller, J, Mansfield, J, Marchini, Jl, Martin, P, Massey, Dc, Mcardle, Wl, Mcguffin, P, Mclay, Ke, Mcvean, G, Mentzer, A, Mimmack, Ml, Morgan, Ae, Morris, Ap, Mowat, C, Munroe, Pb, Myers, S, Newman, W, Nimmo, Er, O'Donovan, Mc, Onipinla, A, Ovington, Nr, Owen, Mj, Palin, K, Palotie, A, Parnell, K, Pearson, R, Pernet, D, Perry, Jr, Phillips, A, Plagnol, V, Prescott, Nj, Prokopenko, I, Quail, Ma, Rafelt, S, Rayner, Nw, Reid, Dm, Renwick, A, Ring, Sm, Robertson, N, Robson, S, Russell, E, St Clair, D, Sambrook, Jg, Sanderson, Jd, Sawcer, Sj, Schuilenburg, H, Scott, Ce, Seal, S, Shaw Hawkins, S, Shields, Bm, Simmonds, Mj, Smyth, Dj, Somaskantharajah, E, Spanova, K, Steer, S, Stephens, J, Stevens, He, Stirrups, K, Stone, Ma, Strachan, Dp, Su, Z, Symmons, Dp, Thompson, Jr, Thomson, W, Tobin, Md, Travers, Me, Turnbull, C, Vukcevic, D, Wain, Lv, Walker, M, Walker, Nm, Wallace, C, Warren Perry, M, Watkins, Na, Webster, J, Weedon, Mn, Wilson, Ag, Woodburn, M, Wordsworth, Bp, Yau, C, Young, Ah, Zeggini, E, Brown, Ma, Burton, Pr, Caulfield, Mj, Compston, A, Farrall, M, Gough, Sc, Hall, As, Hattersley, At, Hill, Av, Mathew, Cg, Pembrey, M, Satsangi, J, Stratton, Mr, Worthington, J, Hurles, Me, Duncanson, A, Ouwehand, Wh, Parkes, M, Rahman, N, Todd, Ja, Samani, Nj, Kwiatkowski, Dp, Mccarthy, Mi, Craddock, N, Deloukas, P, Donnelly, P, Blackwell, Jm, Bramon, E, Casas, Jp, Corvin, A, Jankowski, J, Markus, Hs, Palmer, Cn, Plomin, R, Rautanen, A, Trembath, Rc, Viswanathan, Ac, Wood, Nw, Spencer, Cc, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Pirinen, M, Strange, A, Blackburn, H, Bumpstead, Sj, Dronov, S, Gillman, M, Jayakumar, A, Mccann, Ot, Liddle, J, Potter, Sc, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P., AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, Gastroenterology and Hepatology, and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)

Subjects
Genome-wide association study, Disease, SUSCEPTIBILITY, Inflammatory bowel disease, NUMBER, 0302 clinical medicine, Crohn Disease, NETWORK, Genetics, 0303 health sciences, Multidisciplinary, Genomics, Ulcerative colitis, 3. Good health, Colitis, Ulcerative, Genetic Predisposition to Disease, Genome, Human, Haplotypes, Humans, Inflammatory Bowel Diseases, Mycobacterium, Mycobacterium Infections, Mycobacterium tuberculosis, Phenotype, Polymorphism, Single Nucleotide, Reproducibility of Results, Genome-Wide Association Study, Host-Pathogen Interactions, IRGM, Medical genetics, 030211 gastroenterology & hepatology, EXPRESSION, medicine.medical_specialty, Immunology, Biology, Molecular gastro-enterology and hepatology Pathogenesis and modulation of inflammation [IGMD 2], TUBERCULOSIS, 03 medical and health sciences, Medical research, medicine, Allele, METAANALYSIS, 030304 developmental biology, HYPER-IGE SYNDROME, MUTATIONS, medicine.disease, RISK LOCI, Genetic architecture, digestive system diseases
Abstract

Crohn's disease and ulcerative colitis, the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry, with rising prevalence in other populations(1). Genome-wide association studies and subsequent meta-analyses of these two diseases(2,3) as separate phenotypes have implicated previously unsuspected mechanisms, such as autophagy(4), in their pathogenesis and showed that some IBD loci are shared with other inflammatory diseases(5). Here we expand on the knowledge of relevant pathways by undertaking a meta-analysis of Crohn's disease and ulcerative colitis genome-wide association scans, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci, that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional (consistently favouring one allele over the course of human history) and balancing (favouring the retention of both alleles within populations) selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe considerable overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.

Published
2012

48. Interaction between ERAP1 and HLA-B27 in ankylosing spondylitis implicates peptide handling in the mechanism for HLA-B27 in disease susceptibility

Author

Evans, Dm, Spencer, Cc, Pointon, Jj, Su, Z, Harvey, D, Kochan, G, Oppermann, U, Dilthey, A, Pirinen, M, Stone, Ma, Appleton, L, Moutsianas, L, Leslie, S, Wordsworth, T, Kenna, Tj, Karaderi, T, Thomas, Gp, Ward, Mm, Weisman, Mh, Farrar, C, Bradbury, La, Danoy, P, Inman, Rd, Maksymowych, W, Gladman, D, Rahman, P, Spondyloarthritis Research Consortium of Canada, Morgan, A, Marzo Ortega, H, Bowness, P, Gaffney, K, Gaston, Js, Smith, M, Bruges Armas, J, Couto, Ar, Sorrentino, Rosa, Paladini, Fabiana, Ferreira, Ma, Xu, H, Liu, Y, Jiang, L, Lopez Larrea, C, Díaz Peña, R, López Vázquez, A, Zayats, T, Band, G, Bellenguez, C, Blackburn, H, Blackwell, Jm, Bramon, E, Bumpstead, Sj, Casas, Jp, Corvin, A, Craddock, N, Deloukas, P, Dronov, S, Duncanson, A, Edkins, S, Freeman, C, Gillman, M, Gray, E, Gwilliam, R, Hammond, N, Hunt, Se, Jankowski, J, Jayakumar, A, Langford, C, Liddle, J, Markus, Hs, Mathew, Cg, Mccann, Ot, Mccarthy, Mi, Palmer, Cn, Peltonen, L, Plomin, R, Potter, Sc, Rautanen, A, Ravindrarajah, R, Ricketts, M, Samani, N, Sawcer, Sj, Strange, A, Trembath, Rc, Viswanathan, Ac, Waller, M, Weston, P, Whittaker, P, Widaa, S, Wood, Nw, Mcvean, G, Reveille, Jd, Wordsworth, Bp, Brown, Ma, Donnelly, P, Australo Anglo American Spondyloarthritis Consortium, and Wellcome Trust Case Control Consortium, 2

Subjects
Receptors, Peptide, HLA-B27, ERAP1, ANKYLOSING SPONDYLITIS, Inflammatory arthritis, Population, Genome-wide association study, Human leukocyte antigen, Biology, CD8-Positive T-Lymphocytes, Bioinformatics, Aminopeptidases, White People, Minor Histocompatibility Antigens, Meta-Analysis as Topic, Genetics, medicine, Humans, Spondylitis, Ankylosing, education, Spondylitis, HLA-B27 Antigen, education.field_of_study, Ankylosing spondylitis, HLA-B27, Polymorphism, Genetic, Interleukin-12 Subunit p40, Membrane Proteins, medicine.disease, Endoplasmic reticulum aminopeptidase 2, Peptide Fragments, CARD Signaling Adaptor Proteins, Core Binding Factor Alpha 3 Subunit, Latent TGF-beta Binding Proteins, Receptors, Tumor Necrosis Factor, Type I, Case-Control Studies, Immunology, Disease Susceptibility, Receptors, Prostaglandin E, EP4 Subtype, Genome-Wide Association Study
Abstract

Ankylosing spondylitis is a common form of inflammatory arthritis predominantly affecting the spine and pelvis that occurs in approximately 5 out of 1,000 adults of European descent. Here we report the identification of three variants in the RUNX3, LTBR-TNFRSF1A and IL12B regions convincingly associated with ankylosing spondylitis (P < 5 × 10(-8) in the combined discovery and replication datasets) and a further four loci at PTGER4, TBKBP1, ANTXR2 and CARD9 that show strong association across all our datasets (P < 5 × 10(-6) overall, with support in each of the three datasets studied). We also show that polymorphisms of ERAP1, which encodes an endoplasmic reticulum aminopeptidase involved in peptide trimming before HLA class I presentation, only affect ankylosing spondylitis risk in HLA-B27-positive individuals. These findings provide strong evidence that HLA-B27 operates in ankylosing spondylitis through a mechanism involving aberrant processing of antigenic peptides.

Published
2011

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