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Gregory SG, Barlow KF, McLay KE, Kaul R, Swarbreck D, Dunham A, Scott CE, Howe KL, Woodfine K, Spencer CCA, Jones MC, Gillson C, Searle S, Zhou Y, Kokocinski F, McDonald L, Evans R, Phillips K, Atkinson A, Cooper R, Jones C, Hall RE, Andrews TD, Lloyd C, Ainscough R, Almeida JP, Ambrose KD, Anderson F, Andrew RW, Ashwell RIS, Aubin K, Babbage AK, Bagguley CL, Bailey J, Beasley H, Bethel G, Bird CP, Bray-Allen S, Brown JY, Brown AJ, Buckley D, Burton J, Bye J, Carder C, Chapman JC, Clark SY, Clarke G, Clee C, Cobley V, Collier RE, Corby N, Coville GJ, Davies J, Deadman R, Dunn M, Earthrowl M, Ellington AG, Errington H, Frankish A, Frankland J, French L, Garner P, Garnett J, Gay L, Ghori MRJ, Gibson R, Gilby LM, Gillett W, Glithero RJ, Grafham DV, Griffiths C, Griffiths-Jones S, Grocock R, Hammond S, Harrison ESI, Hart E, Haugen E, Heath PD, Holmes S, Holt K, Howden PJ, Hunt AR, Hunt SE, Hunter G, Isherwood J, James R, Johnson C, Johnson D, Joy A, Kay M, Kershaw JK, Kibukawa M, Kimberley AM, King A, Knights AJ, Lad H, Laird G, Lawlor S, Leongamornlert DA, Lloyd DM, Loveland J, Lovell J, Lush MJ, Lyne R, Martin S, Mashreghi-Mohammadi M, Matthews L, Matthews NSW, McLaren S, Milne S, Mistry S, Moore MJF, Nickerson T, O'Dell CN, Oliver K, Palmeiri A, Palmer SA, Parker A, Patel D, Pearce AV, Peck AI, Pelan S, Phelps K, Phillimore BJ, Plumb R, Rajan J, Raymond C, Rouse G, Saenphimmachak C, Sehra HK, Sheridan E, Shownkeen R, Sims S, Skuce CD, Smith M, Steward C, Subramanian S, Sycamore N, Tracey A, Tromans A, Van Helmond Z, Wall M, Wallis JM, White S, Whitehead SL, Wilkinson JE, Willey DL, Williams H, Wilming L, Wray PW, Wu Z, Coulson A, Vaudin M, Sulston JE, Durbin R, Hubbard T, Wooster R, Dunham I, Carter NP, McVean G, Ross MT, Harrow J, Olson MV, Beck S, Rogers J, Bentley DR, Banerjee R, Bryant SP, Burford DC, Burrill WDH, Clegg SM, Dhami P, Dovey O, Faulkner LM, Gribble SM, Langford CF, Pandian RD, Porter KM, Prigmore E. The DNA sequence and biological annotation of human chromosome 1. Nature 2006; 441:315-21. [PMID: 16710414 DOI: 10.1038/nature04727] [Citation(s) in RCA: 140] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2005] [Accepted: 03/13/2006] [Indexed: 11/08/2022]
Abstract
The reference sequence for each human chromosome provides the framework for understanding genome function, variation and evolution. Here we report the finished sequence and biological annotation of human chromosome 1. Chromosome 1 is gene-dense, with 3,141 genes and 991 pseudogenes, and many coding sequences overlap. Rearrangements and mutations of chromosome 1 are prevalent in cancer and many other diseases. Patterns of sequence variation reveal signals of recent selection in specific genes that may contribute to human fitness, and also in regions where no function is evident. Fine-scale recombination occurs in hotspots of varying intensity along the sequence, and is enriched near genes. These and other studies of human biology and disease encoded within chromosome 1 are made possible with the highly accurate annotated sequence, as part of the completed set of chromosome sequences that comprise the reference human genome.
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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, Frayling TM. Mendelian randomization studies do not support a causal role for reduced circulating adiponectin levels in insulin resistance and type 2 diabetes. Diabetes 2013; 62:3589-98. [PMID: 23835345 PMCID: PMC3781444 DOI: 10.2337/db13-0128] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2013] [Accepted: 06/25/2013] [Indexed: 12/24/2022]
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.
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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 JMM, 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, Waterworth DM. A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease. Sci Transl Med 2016; 8:341ra76. [PMID: 27252175 PMCID: PMC5219001 DOI: 10.1126/scitranslmed.aad3744] [Citation(s) in RCA: 92] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 05/10/2016] [Indexed: 02/06/2023]
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.
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Ye Z, Gillson C, Sims M, Khaw KT, Plotka M, Poulton J, Langenberg C, Wareham NJ. The association of the mitochondrial DNA OriB variant (16184-16193 polycytosine tract) with type 2 diabetes in Europid populations. Diabetologia 2013; 56:1907-13. [PMID: 23702607 PMCID: PMC3737432 DOI: 10.1007/s00125-013-2945-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2013] [Accepted: 05/03/2013] [Indexed: 12/28/2022]
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.
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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, Ehm MG. A low-frequency variant in MAPK14 provides mechanistic evidence of a link with myeloperoxidase: a prognostic cardiovascular risk marker. J Am Heart Assoc 2014; 3:jah3667. [PMID: 25164947 PMCID: PMC4310399 DOI: 10.1161/jaha.114.001074] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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.
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Gregory SG, Barlow KF, McLay KE, Kaul R, Swarbreck D, Dunham A, Scott CE, Howe KL, Woodfine K, Spencer CCA, Jones MC, Gillson C, Searle S, Zhou Y, Kokocinski F, McDonald L, Evans R, Phillips K, Atkinson A, Cooper R, Jones C, Hall RE, Andrews TD, Lloyd C, Ainscough R, Almeida JP, Ambrose KD, Anderson F, Andrew RW, Ashwell RIS, Aubin K, Babbage AK, Bagguley CL, Bailey J, Banerjee R, Beasley H, Bethel G, Bird CP, Bray-Allen S, Brown JY, Brown AJ, Bryant SP, Buckley D, Burford DC, Burrill WDH, Burton J, Bye J, Carder C, Chapman JC, Clark SY, Clarke G, Clee C, Clegg SM, Cobley V, Collier RE, Corby N, Coville GJ, Davies J, Deadman R, Dhami P, Dovey O, Dunn M, Earthrowl M, Ellington AG, Errington H, Faulkner LM, Frankish A, Frankland J, French L, Garner P, Garnett J, Gay L, Ghori MRJ, Gibson R, Gilby LM, Gillett W, Glithero RJ, Grafham DV, Gribble SM, Griffiths C, Griffiths-Jones S, Grocock R, Hammond S, Harrison ESI, Hart E, Haugen E, Heath PD, Holmes S, Holt K, Howden PJ, Hunt AR, Hunt SE, Hunter G, Isherwood J, James R, Johnson C, Johnson D, Joy A, Kay M, Kershaw JK, Kibukawa M, Kimberley AM, King A, Knights AJ, Lad H, Laird G, Langford CF, Lawlor S, Leongamornlert DA, Lloyd DM, Loveland J, Lovell J, Lush MJ, Lyne R, Martin S, Mashreghi-Mohammadi M, Matthews L, Matthews NSW, McLaren S, Milne S, Mistry S, oore MJFM, Nickerson T, O'Dell CN, Oliver K, Palmeiri A, Palmer SA, Pandian RD, Parker A, Patel D, Pearce AV, Peck AI, Pelan S, Phelps K, Phillimore BJ, Plumb R, Porter KM, Prigmore E, Rajan J, Raymond C, Rouse G, Saenphimmachak C, Sehra HK, Sheridan E, Shownkeen R, Sims S, Skuce CD, Smith M, Steward C, Subramanian S, Sycamore N, Tracey A, Tromans A, Van Helmond Z, Wall J. M. Wallis M, White S, Whitehead SL, Wilkinson JE, Willey DL, Williams H, Wilming L, Wray PW, Wu Z, Coulson A, Vaudin M, Sulston JE, Durbin R, Hubbard T, Wooster R, Dunham I, Carter NP, McVean G, Ross MT, Harrow J, Olson MV, Beck S, Rogers J, Bentley DR. Erratum: The DNA sequence and biological annotation of human chromosome 1. Nature 2006. [DOI: 10.1038/nature05152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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