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1. 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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2. The DNA sequence and analysis of human chromosome 6

Author

Mungall, A. J., Palmer, S. A., Sims, S. K., Edwards, C. A., Ashurst, J. L., Wilming, L., Jones, M. C., Horton, R., Hunt, S. E., Scott, C. E., Gilbert, J. G. R., Clamp, M. E., Bethel, G., Milne, S., Ainscough, R., Almeida, J. P., Ambrose, K. D., Andrews, T. D., Ashwell, R. I. S., Babbage, A. K., Bagguley, C. L., Bailey, J., Banerjee, R., Barker, D. J., Barlow, K. F., Bates, K., Beare, D. M., Beasley, H., Beasley, O., Bird, C. P., Blakey, S., Bray-Allen, S., Brook, J., Brown, A. J., Brown, J. Y., Burford, D. C., Burrill, W., Burton, J., Carder, C., Carter, N. P., Chapman, J. C., Clark, S. Y., Clark, G., Clee, C. M., Clegg, S., Cobley, V., Collier, R. E., Collins, J. E., Colman, L. K., Corby, N. R., Coville, G. J., Culley, K. M., Dhami, P., Davies, J., Dunn, M., Earthrowl, M. E., Ellington, A. E., Evans, K. A., Faulkner, L., Francis, M. D., Frankish, A., Frankland, J., French, L., Garner, P., Garnett, J., Ghori, M. J. R., Gilby, L. M., Gillson, C. J., Glithero, R. J., Grafham, D. V., Grant, M., Gribble, S., Griffiths, C., Griffiths, M., Hall, R., Halls, K. S., Hammond, S., Harley, J. L., Hart, E. A., Heath, P. D., Heathcott, R., Holmes, S. J., Howden, P. J., Howe, K. L., Howell, G. R., Huckle, E., Humphray, S. J., Humphries, M. D., Hunt, A. R., Johnson, C. M., Joy, A. A., Kay, M., Keenan, S. J., Kimberley, A. M., King, A., Laird, G. K., Langford, C., Lawlor, S., Leongamornlert, D. A., Leversha, M., Lloyd, C. R., Lloyd, D. M., Loveland, J. E., Lovell, J., Martin, S., Mashreghi-Mohammadi, M., Maslen, G. L., Matthews, L., McCann, O. T., McLaren, S. J., McLay, K., McMurray, A., Moore, M. J. F., Mullikin, J. C., Niblett, D., Nickerson, T., Novik, K. L., Oliver, K., Overton-Larty, E. K., Parker, A., Patel, R., Pearce, A. V., Peck, A. I., Phillimore, B., Phillips, S., Plumb, R. W., Porter, K. M., Ramsey, Y., Ranby, S. A., Rice, C. M., Ross, M. T., Searle, S. M., Sehra, H. K., Sheridan, E., Skuce, C. D., Smith, S., Smith, M., Spraggon, L., Squares, S. L., Steward, C. A., Sycamore, N., Tamlyn-Hall, G., Tester, J., Theaker, A. J., Thomas, D. W., Thorpe, A., Tracey, A., Tromans, A., Tubby, B., Wall, M., Wallis, J. M., West, A. P., White, S. S., Whitehead, S. L., Whittaker, H., Wild, A., Willey, D. J., Wilmer, T. E., Wood, J. M., Wray, P. W., Wyatt, J. C., Young, L., Younger, R. M., Bentley, D. R., Coulson, A., Durbin, R., Hubbard, T., Sulston, J. E., Dunham, I., Rogers, J., and Beck, S.

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

Author(s): A. J. Mungall (corresponding author) [1, 2]; S. A. Palmer [1]; S. K. Sims [1]; C. A. Edwards [1]; J. L. Ashurst [1]; L. Wilming [1]; M. C. Jones [...]

Published
2003
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3. The physical maps for sequencing human chromosomes 1, 6, 9, 10, 13, 20 and X

Author

Bentley, D. R., Deloukas, P., Dunham, A., French, L., Gregory, S. G., Humphray, S. J., Mungall, A. J., Ross, M. T., Carter, N. P., Dunham, I., Scott, C. E., Ashcroft, K. J., Atkinson, A. L., Aubin, K., Beare, D. M., Bethel, G., Brady, N., Brook, J. C., Burford, D. C., Burrill, W. D., Burrows, C., Butler, A. P., Carder, C., Catanese, J. J., Clee, C. M., Clegg, S. M., Cobley, V., Coffey, A. J., Cole, C. G., Collins, J. E., Conquer, J. S., Cooper, R. A., Culley, K. M., Dawson, E., Dearden, F. L., Durbin, R. M., de Jong, P. J., Dhami, P. D., Earthrowl, M. E., Edwards, C. A., Evans, R. S., Gillson, C. J., Ghori, J., Green, L., Gwilliam, R., Halls, K. S., Hammond, S., Harper, G. L., Heathcott, R. W., Holden, J. L., Holloway, E., Hopkins, B. L., Howard, P. J., Howell, G. R., Huckle, E. J., Hughes, J., Hunt, P. J., Hunt, S. E., Izmajlowicz, M., Jones, C. A., Joseph, S. S., Laird, G., Langford, C. F., Lehvaslaiho, M. H., Leversha, M. A., McCann, O. T., McDonald, L. M., McDowall, J., Maslen, G. L., Mistry, D., Moschonas, N. K., Neocleous, V., Pearson, D. M., Phillips, K. J., Porter, K. M., Prathalingam, S. R., Ramsey, Y. H., Ranby, S. A., Rice, C. M., Rogers, J., Rogers, L. J., Sarafidou, T., Scott, D. J., Sharp, G. J., Shaw-Smith, C. J., Smink, L. J., Soderlund, C., Sotheran, E. C., Steingruher, H. E., Sulston, J. E., Taylor, A., Taylor, R. G., Thorpe, A. A., Tinsley, E., Warry, G. L., Whittaker, A., Whittaker, P., Williams, S. H., Wilmer, T. E., Wooster, R., and Wright, C. L.

Published
2001

4. A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease

Author

Scott, RA, Freitag, DF, Li, L, Chu, AY, Surendran, P, Young, R, Grarup, N, Stancáková, A, Chen, Y, Varga, TV, Yaghootkar, H, Luan, J, Zhao, JH, Willems, SM, Wessel, J, Wang, S, Maruthur, N, Michailidou, K, Pirie, A, Van Der Lee, SJ, Gillson, C, Al Olama, AA, Amouyel, P, Arriola, L, Arveiler, D, Aviles-Olmos, I, Balkau, B, Barricarte, A, Barroso, I, Garcia, SB, Bis, JC, Blankenberg, S, Boehnke, M, Boeing, H, Boerwinkle, E, Borecki, IB, Bork-Jensen, J, Bowden, S, Caldas, C, Caslake, M, Cupples, LA, Cruchaga, C, Czajkowski, J, Den Hoed, M, Dunn, JA, Earl, HM, Ehret, GB, Ferrannini, E, Ferrieres, J, Foltynie, T, Ford, I, Forouhi, NG, Gianfagna, F, Gonzalez, C, Grioni, S, Hiller, L, Jansson, JH, Jørgensen, ME, Jukema, JW, Kaaks, R, Kee, F, Kerrison, ND, Key, TJ, Kontto, J, Kote-Jarai, Z, Kraja, AT, Kuulasmaa, K, Kuusisto, J, Linneberg, A, Liu, C, Marenne, G, Mohlke, KL, Morris, AP, Muir, K, Müller-Nurasyid, M, Munroe, PB, and Navarro, C

Abstract

Copyright 2016 by the American Association for the Advancement of Science; all rights reserved. Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11, 806 individuals by targeted exome sequencing and follow-up in 39, 979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process.

Published
2016

5. Mendelian Randomization Studies Do Not Support a Causal Role for Reduced Circulating Adiponectin Levels in Insulin Resistance and Type 2 Diabetes

Author

Collins, F. S., Warren, L. L., Wu, Y., Boehnke, M., Hattersley, A. T., Jackson, A. U., Hivert, M.-F., Henneman, P., Dastani, Z., Kahonen, M., el Bouazzaoui, F., Hong, J., Kronenberg, F., Cheung, C. Y. Y., Ballantyne, C. M., Yaghootkar, H., Lyytikainen, L.-P., Zhao, J. H., Xie, W., Kedenko, L., Pankow, J. S., Buxbaum, S. G., Gillson, C., Bergman, R. N., Kuusisto, J., Scott, R. A., Forouhi, N. G., Lamina, C., Gustafsson, S., Stancakova, A., Dupuis, J., and Dunn, S. H.

Abstract

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics–based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26–0.35) increase in fasting insulin, a 0.34-SD (0.30–0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47–2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI −0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (−0.20 SD; 95% CI −0.38 to −0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75–1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: −0.03 SD; 95% CI −0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95–1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

Published
2013
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6. Erratum: The DNA sequence and biological annotation of human chromosome 1

Author

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

Published
2006
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7. Corrigendum: 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., and Cooper, R.

Subjects
AUTHORS
Abstract

A correction to the article "The DNAsequence and Biological Annotation of Human Chromosome" that was published in the Vol.441 of the issue 2006 is provided.

Published
2006
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8. Evolution be Gene Loss in Humans.

Author

Tyler-Smith, Chris, Xue, Y., Daly, A., Gillson, C., Yngvadottir, B., Liu, M., Searle, S., Hunt, S., Delgano, M., Morrison, J., Deloukas, P., Huckle, E., Greenhill, J., and Bailey, J.

Subjects
HUMAN genetics
Abstract

Presents an abstract of the article "Evolution be Gene Loss in Humans," by Chris Tyler-Smith, Y.. Xue, A. Daly, C. Gillson, B. Yngvadottir, M. Liu, S. Searle, S. Hunt, M. Delgano, J. Morrison, P. Deloukas, E. Huckle, J. Greenhill, J. Bailey, and J. Burton.

Published
2005

9. A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease.

Author

Scott RA, Freitag DF, Li L, Chu AY, Surendran P, Young R, Grarup N, Stancáková A, Chen Y, Varga TV, Yaghootkar H, Luan J, Zhao JH, Willems SM, Wessel J, Wang S, Maruthur N, Michailidou K, Pirie A, van der Lee SJ, Gillson C, Al Olama AA, Amouyel P, Arriola L, Arveiler D, Aviles-Olmos I, Balkau B, Barricarte A, Barroso I, Garcia SB, Bis JC, Blankenberg S, Boehnke M, Boeing H, Boerwinkle E, Borecki IB, Bork-Jensen J, Bowden S, Caldas C, Caslake M, Cupples LA, Cruchaga C, Czajkowski J, den Hoed M, Dunn JA, Earl HM, Ehret GB, Ferrannini E, Ferrieres J, Foltynie T, Ford I, Forouhi NG, Gianfagna F, Gonzalez C, Grioni S, Hiller L, Jansson JH, Jørgensen ME, Jukema JW, Kaaks R, Kee F, Kerrison ND, Key TJ, Kontto J, Kote-Jarai Z, Kraja AT, Kuulasmaa K, Kuusisto J, Linneberg A, Liu C, Marenne G, Mohlke KL, Morris AP, Muir K, Müller-Nurasyid M, Munroe PB, Navarro C, Nielsen SF, Nilsson PM, Nordestgaard BG, Packard CJ, Palli D, Panico S, Peloso GM, Perola M, Peters A, Poole CJ, Quirós JR, Rolandsson O, Sacerdote C, Salomaa V, Sánchez MJ, Sattar N, Sharp SJ, Sims R, Slimani N, Smith JA, Thompson DJ, Trompet S, Tumino R, van der A DL, van der Schouw YT, Virtamo J, Walker M, Walter K, Abraham JE, Amundadottir LT, Aponte JL, Butterworth AS, Dupuis J, Easton DF, Eeles RA, Erdmann J, Franks PW, Frayling TM, Hansen T, Howson JM, Jørgensen T, Kooner J, Laakso M, Langenberg C, McCarthy MI, Pankow JS, Pedersen O, Riboli E, Rotter JI, Saleheen D, Samani NJ, Schunkert H, Vollenweider P, O'Rahilly S, Deloukas P, Danesh J, Goodarzi MO, Kathiresan S, Meigs JB, Ehm MG, Wareham NJ, and Waterworth DM

Subjects
Alleles, Diabetes Mellitus, Type 2 genetics, Dipeptidyl Peptidase 4 genetics, Genotype, Humans, Obesity genetics, Receptor, Cannabinoid, CB2 genetics, Receptor, Serotonin, 5-HT2C genetics, Receptors, Somatostatin genetics, Sodium-Glucose Transporter 1 genetics, Coronary Disease genetics, Glucagon-Like Peptide-1 Receptor genetics
Abstract

Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process., (Copyright © 2016, American Association for the Advancement of Science.)

Published
2016
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10. A low-frequency variant in MAPK14 provides mechanistic evidence of a link with myeloperoxidase: a prognostic cardiovascular risk marker.

Author

Waterworth DM, Li L, Scott R, Warren L, Gillson C, Aponte J, Sarov-Blat L, Sprecher D, Dupuis J, Reiner A, Psaty BM, Tracy RP, Lin H, McPherson R, Chissoe S, Wareham N, and Ehm MG

Subjects
Adult, Aged, Cardiovascular Diseases blood, Cardiovascular Diseases diagnosis, Dyslipidemias blood, Dyslipidemias genetics, Exome, Female, Genotype, Humans, Linear Models, Logistic Models, Male, Metabolic Syndrome blood, Metabolic Syndrome genetics, Middle Aged, Obesity blood, Obesity genetics, Polymorphism, Single Nucleotide, Prognosis, Risk Factors, Sequence Analysis, DNA, Cardiovascular Diseases genetics, Mitogen-Activated Protein Kinase 11 genetics, Mitogen-Activated Protein Kinase 14 genetics, Peroxidase blood
Abstract

Background: Genetics can be used to predict drug effects and generate hypotheses around alternative indications. To support Losmapimod, a p38 mitogen-activated protein kinase inhibitor in development for acute coronary syndrome, we characterized gene variation in MAPK11/14 genes by exome sequencing and follow-up genotyping or imputation in participants well-phenotyped for cardiovascular and metabolic traits., Methods and Results: Investigation of genetic variation in MAPK11 and MAPK14 genes using additive genetic models in linear or logistic regression with cardiovascular, metabolic, and biomarker phenotypes highlighted an association of RS2859144 in MAPK14 with myeloperoxidase in a dyslipidemic population (Genetic Epidemiology of Metabolic Syndrome Study), P=2.3×10(-6)). This variant (or proxy) was consistently associated with myeloperoxidase in the Framingham Heart Study and Cardiovascular Health Study studies (replication meta-P=0.003), leading to a meta-P value of 9.96×10(-7) in the 3 dyslipidemic groups. The variant or its proxy was then profiled in additional population-based cohorts (up to a total of 58 930 subjects) including Cohorte Lausannoise, Ely, Fenland, European Prospective Investigation of Cancer, London Life Sciences Prospective Population Study, and the Genetics of Obesity Associations study obesity case-control for up to 40 cardiovascular and metabolic traits. Overall analysis identified the same single nucleotide polymorphisms to be nominally associated consistently with glomerular filtration rate (P=0.002) and risk of obesity (body mass index ≥30 kg/m(2), P=0.004)., Conclusions: As myeloperoxidase is a prognostic marker of coronary events, the MAPK14 variant may provide a mechanistic link between p38 map kinase and these events, providing information consistent with current indication of Losmapimod for acute coronary syndrome. If replicated, the association with glomerular filtration rate, along with previous biological findings, also provides support for kidney diseases as alternative indications., (© 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.)

Published
2014
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11. Mendelian randomization studies do not support a causal role for reduced circulating adiponectin levels in insulin resistance and type 2 diabetes.

Author

Yaghootkar H, Lamina C, Scott RA, Dastani Z, Hivert MF, Warren LL, Stancáková A, Buxbaum SG, Lyytikäinen LP, Henneman P, Wu Y, Cheung CY, Pankow JS, Jackson AU, Gustafsson S, Zhao JH, Ballantyne CM, Xie W, Bergman RN, Boehnke M, el Bouazzaoui F, Collins FS, Dunn SH, Dupuis J, Forouhi NG, Gillson C, Hattersley AT, Hong J, Kähönen M, Kuusisto J, Kedenko L, Kronenberg F, Doria A, Assimes TL, Ferrannini E, Hansen T, Hao K, Häring H, Knowles JW, Lindgren CM, Nolan JJ, Paananen J, Pedersen O, Quertermous T, Smith U, Lehtimäki T, Liu CT, Loos RJ, McCarthy MI, Morris AD, Vasan RS, Spector TD, Teslovich TM, Tuomilehto J, van Dijk KW, Viikari JS, Zhu N, Langenberg C, Ingelsson E, Semple RK, Sinaiko AR, Palmer CN, Walker M, Lam KS, Paulweber B, Mohlke KL, van Duijn C, Raitakari OT, Bidulescu A, Wareham NJ, Laakso M, Waterworth DM, Lawlor DA, Meigs JB, Richards JB, and Frayling TM

Subjects
Adiponectin genetics, Blood Glucose metabolism, Female, Genetic Predisposition to Disease, Genetic Variation, Humans, Male, Mendelian Randomization Analysis, Odds Ratio, Polymorphism, Single Nucleotide, Regression Analysis, Adiponectin blood, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 genetics, Insulin Resistance genetics
Abstract

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

Published
2013
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12. The association of the mitochondrial DNA OriB variant (16184-16193 polycytosine tract) with type 2 diabetes in Europid populations.

Author

Ye Z, Gillson C, Sims M, Khaw KT, Plotka M, Poulton J, Langenberg C, and Wareham NJ

Subjects
Diabetes Mellitus, Type 2 epidemiology, Genetic Predisposition to Disease, Humans, DNA, Mitochondrial genetics, Diabetes Mellitus, Type 2 genetics
Abstract

Aims/hypothesis: The association between the mitochondrial DNA 16181-16193 polycytosine variant (known as the OriB variant as it maps to the OriB origin of replication) and type 2 diabetes has not been reliably characterised, with studies reporting conflicting results. We report a systematic review of published literature in Europid populations, new data from the Norfolk Diabetes Case-Control Study and a meta-analysis to help quantify this association., Methods: We performed a systematic review identifying all the studies of the OriB variant and type 2 diabetes in Europid populations published before January 2013. We typed the OriB variant by pyrosequencing and sequencing in the Norfolk Diabetes Case-Control Study, which comprised 5,574 type 2 diabetes cases and 6,950 population-based controls., Results: Overall, the meta-analysis included eight published studies plus the current new results, with a total of 11,794 type 2 diabetes cases and 14,465 controls. In the Norfolk Diabetes Case-Control Study, the OR for type 2 diabetes for the OriB variant was 1.09 (95% CI 0.96, 1.24). In a combined analysis, the relative risk for type 2 diabetes for the OriB variant in Europid populations was 1.10 (95% CI 1.01, 1.20; p = 0.03) CONCLUSIONS/INTERPRETATION: Results from this systematic review and meta-analysis suggest that the mitochondrial DNA OriB variant is modestly associated with an increased risk of type 2 diabetes in Europid populations, with an effect size comparable with that of recently identified variants from genome-wide association studies.

Published
2013
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