scispace - formally typeset
Search or ask a question
Author

Nilesh J. Samani

Bio: Nilesh J. Samani is an academic researcher from University of Leicester. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 149, co-authored 779 publications receiving 113545 citations. Previous affiliations of Nilesh J. Samani include University Hospitals of Leicester NHS Trust & Glenfield Hospital.


Papers
More filters
Journal ArticleDOI
TL;DR: A genetic predisposition to enhanced nitric oxide signaling is associated with reduced risks of coronary heart disease, peripheral arterial disease, and stroke and may prove useful in the prevention or treatment of cardiovascular disease.
Abstract: Background:Nitric oxide signaling plays a key role in the regulation of vascular tone and platelet activation. Here, we seek to understand the impact of a genetic predisposition to enhanced nitric ...

85 citations

Journal ArticleDOI
14 Oct 2020-Nature
TL;DR: A large-scale genome-wide association study identifies 17 genetic loci that are associated with the risk of myeloproliferative neoplasms (MPNs), and shows that the modulation of haematopoietic stem cell function drives MPN risk.
Abstract: Myeloproliferative neoplasms (MPNs) are blood cancers that are characterized by the excessive production of mature myeloid cells and arise from the acquisition of somatic driver mutations in haematopoietic stem cells (HSCs). Epidemiological studies indicate a substantial heritable component of MPNs that is among the highest known for cancers1. However, only a limited number of genetic risk loci have been identified, and the underlying biological mechanisms that lead to the acquisition of MPNs remain unclear. Here, by conducting a large-scale genome-wide association study (3,797 cases and 1,152,977 controls), we identify 17 MPN risk loci (P < 5.0 × 10−8), 7 of which have not been previously reported. We find that there is a shared genetic architecture between MPN risk and several haematopoietic traits from distinct lineages; that there is an enrichment for MPN risk variants within accessible chromatin of HSCs; and that increased MPN risk is associated with longer telomere length in leukocytes and other clonal haematopoietic states—collectively suggesting that MPN risk is associated with the function and self-renewal of HSCs. We use gene mapping to identify modulators of HSC biology linked to MPN risk, and show through targeted variant-to-function assays that CHEK2 and GFI1B have roles in altering the function of HSCs to confer disease risk. Overall, our results reveal a previously unappreciated mechanism for inherited MPN risk through the modulation of HSC function. A genome-wide association study identifies 17 genetic loci that are associated with the risk of myeloproliferative neoplasms (MPNs), and shows that the modulation of haematopoietic stem cell function drives MPN risk.

85 citations

Journal ArticleDOI
TL;DR: In this paper, the authors characterize the genetic architecture of naturally occurring variation in leukocyte telomere length (LTL) and identify causal links between LTL and biomedical phenotypes in 472,174 well-characterized UK Biobank participants.
Abstract: Telomeres, the end fragments of chromosomes, play key roles in cellular proliferation and senescence. Here we characterize the genetic architecture of naturally occurring variation in leukocyte telomere length (LTL) and identify causal links between LTL and biomedical phenotypes in 472,174 well-characterized UK Biobank participants. We identified 197 independent sentinel variants associated with LTL at 138 genomic loci (108 new). Genetically determined differences in LTL were associated with multiple biological traits, ranging from height to bone marrow function, as well as several diseases spanning neoplastic, vascular and inflammatory pathologies. Finally, we estimated that, at the age of 40 years, people with an LTL >1 s.d. shorter than the population mean had a 2.5-year-lower life expectancy compared with the group with ≥1 s.d. longer LDL. Overall, we furnish new insights into the genetic regulation of LTL, reveal wide-ranging influences of LTL on physiological traits, diseases and longevity, and provide a powerful resource available to the global research community.

85 citations

Journal ArticleDOI
Themistocles L. Assimes1, Hilma Holm2, Sekar Kathiresan, Muredach P. Reilly3, Gudmar Thorleifsson2, Benjamin F. Voight4, Benjamin F. Voight5, Jeanette Erdmann6, Christina Willenborg6, Dhananjay Vaidya7, Changchun Xie8, Christopher Patterson9, Thomas M. Morgan10, Mary Susan Burnett11, Mingyao Li3, Mark A. Hlatky1, Joshua W. Knowles1, John R. Thompson12, Devin Absher, Carlos Iribarren13, Alan S. Go13, Stephen P. Fortmann1, Stephen Sidney13, Neil Risch14, Hua Tang1, Richard M. Myers, Klaus Berger, Monika Stoll15, Svati H. Shah16, Gudmundur Thorgeirsson17, Karl Andersen17, Aki S. Havulinna18, J. Enrique Herrera7, Nauder Faraday19, Yoonhee Kim18, Brian G. Kral7, Rasika A. Mathias7, Ingo Ruczinski7, Bhoom Suktitipat7, Alexander F. Wilson18, Lisa R. Yanek7, Lewis C. Becker7, Patrick Linsel-Nitschke6, Wolfgang Lieb6, Inke R. König6, Christian Hengstenberg20, Marcus Fischer20, Klaus Stark20, Wibke Reinhard20, Janina Winogradow20, Martina Grassl20, Anika Grosshennig6, Michael Preuss6, Stefan Schreiber21, H.-Erich Wichmann22, Christa Meisinger23, Jean Yee24, Yechiel Friedlander25, Ron Do26, James B. Meigs5, Gordon H. Williams27, Gordon H. Williams5, David M. Nathan5, Calum A. MacRae5, Liming Qu3, Robert L. Wilensky3, William H. Matthai3, Atif Qasim3, Hakon Hakonarson28, Augusto D. Pichard11, Kenneth M. Kent11, Lowell F. Satler11, Joseph M. Lindsay11, Ron Waksman5, Ron Waksman1, Christopher W. Knouff29, Dawn M. Waterworth29, M Walker29, Vincent Mooser29, Jaume Marrugat, Gavin Lucas, Isaac Subirana, Joan Sala, Rafael Ramos30, Nicola Martinelli31, Oliviero Olivieri31, Elisabetta Trabetti31, Giovanni Malerba31, Pier Franco Pignatti31, Candace Guiducci4, Daniel B. Mirel4, Melissa Parkin4, Joel N. Hirschhorn4, Joel N. Hirschhorn5, Rosanna Asselta32, Stefano Duga32, Kiran Musunuru, Mark J. Daly5, Mark J. Daly4, Shaun Purcell4, Shaun Purcell5, Sandra Eifert22, Peter S. Braund12, Benjamin J. Wright12, Anthony J. Balmforth33, Stephen G. Ball33, Willem H. Ouwehand34, Willem H. Ouwehand35, Panos Deloukas35, Michael Scholz, François Cambien36, Andreas Huge15, Thomas Scheffold, Veikko Salomaa18, Domenico Girelli31, Christopher B. Granger16, Leena Peltonen4, Leena Peltonen37, Leena Peltonen35, Pascal P. McKeown9, David Altshuler, Olle Melander38, Joseph M. Devaney11, Stephen E. Epstein11, Daniel J. Rader5, Daniel J. Rader3, Roberto Elosua, James C. Engert26, Sonia S. Anand8, Alistair S. Hall33, Andreas Ziegler6, Christopher J. O'Donnell5, John A. Spertus39, David S. Siscovick24, Stephen M. Schwartz24, Diane M. Becker7, Unnur Thorsteinsdottir2, Unnur Thorsteinsdottir17, Kari Stefansson17, Kari Stefansson2, Heribert Schunkert6, Nilesh J. Samani12, Thomas Quertermous1 
TL;DR: The KIF6 Trp719Arg polymorphism was not associated with the risk of clinical CAD in this large replication study and Regression analyses and fixed-effects meta-analyses ruled out with high degree of confidence an increase of ≥2% in the risk among European 719Arg carriers.

85 citations

Journal ArticleDOI
25 Nov 2010-Blood
TL;DR: In this paper, a correlative analysis of genome-wide platelet RNA expression data from 37 subjects representing the normal range of platelet responsiveness within a cohort of 500 subjects, identified 63 genes in which transcript levels correlated with variation in the platelet response to adenosine diphosphate and/or the collagen-mimetic peptide.

84 citations


Cited by
More filters
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
Giuseppe Mancia1, Robert Fagard, Krzysztof Narkiewicz, Josep Redon, Alberto Zanchetti, Michael Böhm, Thierry Christiaens, Renata Cifkova, Guy De Backer, Anna F. Dominiczak, Maurizio Galderisi, Diederick E. Grobbee, Tiny Jaarsma, Paulus Kirchhof, Sverre E. Kjeldsen, Stéphane Laurent, Athanasios J. Manolis, Peter M. Nilsson, Luis M. Ruilope, Roland E. Schmieder, Per Anton Sirnes, Peter Sleight, Margus Viigimaa, Bernard Waeber, Faiez Zannad, Michel Burnier, Ettore Ambrosioni, Mark Caufield, Antonio Coca, Michael H. Olsen, Costas Tsioufis, Philippe van de Borne, José Luis Zamorano, Stephan Achenbach, Helmut Baumgartner, Jeroen J. Bax, Héctor Bueno, Veronica Dean, Christi Deaton, Çetin Erol, Roberto Ferrari, David Hasdai, Arno W. Hoes, Juhani Knuuti, Philippe Kolh2, Patrizio Lancellotti, Aleš Linhart, Petros Nihoyannopoulos, Massimo F Piepoli, Piotr Ponikowski, Juan Tamargo, Michal Tendera, Adam Torbicki, William Wijns, Stephan Windecker, Denis Clement, Thierry C. Gillebert, Enrico Agabiti Rosei, Stefan D. Anker, Johann Bauersachs, Jana Brguljan Hitij, Mark J. Caulfield, Marc De Buyzere, Sabina De Geest, Geneviève Derumeaux, Serap Erdine, Csaba Farsang, Christian Funck-Brentano, Vjekoslav Gerc, Giuseppe Germanò, Stephan Gielen, Herman Haller, Jens Jordan, Thomas Kahan, Michel Komajda, Dragan Lovic, Heiko Mahrholdt, Jan Östergren, Gianfranco Parati, Joep Perk, Jorge Polónia, Bogdan A. Popescu, Zeljko Reiner, Lars Rydén, Yuriy Sirenko, Alice Stanton, Harry A.J. Struijker-Boudier, Charalambos Vlachopoulos, Massimo Volpe, David A. Wood 
TL;DR: In this article, a randomized controlled trial of Aliskiren in the Prevention of Major Cardiovascular Events in Elderly people was presented. But the authors did not discuss the effect of the combination therapy in patients living with systolic hypertension.
Abstract: ABCD : Appropriate Blood pressure Control in Diabetes ABI : ankle–brachial index ABPM : ambulatory blood pressure monitoring ACCESS : Acute Candesartan Cilexetil Therapy in Stroke Survival ACCOMPLISH : Avoiding Cardiovascular Events in Combination Therapy in Patients Living with Systolic Hypertension ACCORD : Action to Control Cardiovascular Risk in Diabetes ACE : angiotensin-converting enzyme ACTIVE I : Atrial Fibrillation Clopidogrel Trial with Irbesartan for Prevention of Vascular Events ADVANCE : Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation AHEAD : Action for HEAlth in Diabetes ALLHAT : Antihypertensive and Lipid-Lowering Treatment to Prevent Heart ATtack ALTITUDE : ALiskiren Trial In Type 2 Diabetes Using Cardio-renal Endpoints ANTIPAF : ANgioTensin II Antagonist In Paroxysmal Atrial Fibrillation APOLLO : A Randomized Controlled Trial of Aliskiren in the Prevention of Major Cardiovascular Events in Elderly People ARB : angiotensin receptor blocker ARIC : Atherosclerosis Risk In Communities ARR : aldosterone renin ratio ASCOT : Anglo-Scandinavian Cardiac Outcomes Trial ASCOT-LLA : Anglo-Scandinavian Cardiac Outcomes Trial—Lipid Lowering Arm ASTRAL : Angioplasty and STenting for Renal Artery Lesions A-V : atrioventricular BB : beta-blocker BMI : body mass index BP : blood pressure BSA : body surface area CA : calcium antagonist CABG : coronary artery bypass graft CAPPP : CAPtopril Prevention Project CAPRAF : CAndesartan in the Prevention of Relapsing Atrial Fibrillation CHD : coronary heart disease CHHIPS : Controlling Hypertension and Hypertension Immediately Post-Stroke CKD : chronic kidney disease CKD-EPI : Chronic Kidney Disease—EPIdemiology collaboration CONVINCE : Controlled ONset Verapamil INvestigation of CV Endpoints CT : computed tomography CV : cardiovascular CVD : cardiovascular disease D : diuretic DASH : Dietary Approaches to Stop Hypertension DBP : diastolic blood pressure DCCT : Diabetes Control and Complications Study DIRECT : DIabetic REtinopathy Candesartan Trials DM : diabetes mellitus DPP-4 : dipeptidyl peptidase 4 EAS : European Atherosclerosis Society EASD : European Association for the Study of Diabetes ECG : electrocardiogram EF : ejection fraction eGFR : estimated glomerular filtration rate ELSA : European Lacidipine Study on Atherosclerosis ESC : European Society of Cardiology ESH : European Society of Hypertension ESRD : end-stage renal disease EXPLOR : Amlodipine–Valsartan Combination Decreases Central Systolic Blood Pressure more Effectively than the Amlodipine–Atenolol Combination FDA : U.S. Food and Drug Administration FEVER : Felodipine EVent Reduction study GISSI-AF : Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico-Atrial Fibrillation HbA1c : glycated haemoglobin HBPM : home blood pressure monitoring HOPE : Heart Outcomes Prevention Evaluation HOT : Hypertension Optimal Treatment HRT : hormone replacement therapy HT : hypertension HYVET : HYpertension in the Very Elderly Trial IMT : intima-media thickness I-PRESERVE : Irbesartan in Heart Failure with Preserved Systolic Function INTERHEART : Effect of Potentially Modifiable Risk Factors associated with Myocardial Infarction in 52 Countries INVEST : INternational VErapamil SR/T Trandolapril ISH : Isolated systolic hypertension JNC : Joint National Committee JUPITER : Justification for the Use of Statins in Primary Prevention: an Intervention Trial Evaluating Rosuvastatin LAVi : left atrial volume index LIFE : Losartan Intervention For Endpoint Reduction in Hypertensives LV : left ventricle/left ventricular LVH : left ventricular hypertrophy LVM : left ventricular mass MDRD : Modification of Diet in Renal Disease MRFIT : Multiple Risk Factor Intervention Trial MRI : magnetic resonance imaging NORDIL : The Nordic Diltiazem Intervention study OC : oral contraceptive OD : organ damage ONTARGET : ONgoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial PAD : peripheral artery disease PATHS : Prevention And Treatment of Hypertension Study PCI : percutaneous coronary intervention PPAR : peroxisome proliferator-activated receptor PREVEND : Prevention of REnal and Vascular ENdstage Disease PROFESS : Prevention Regimen for Effectively Avoiding Secondary Strokes PROGRESS : Perindopril Protection Against Recurrent Stroke Study PWV : pulse wave velocity QALY : Quality adjusted life years RAA : renin-angiotensin-aldosterone RAS : renin-angiotensin system RCT : randomized controlled trials RF : risk factor ROADMAP : Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention SBP : systolic blood pressure SCAST : Angiotensin-Receptor Blocker Candesartan for Treatment of Acute STroke SCOPE : Study on COgnition and Prognosis in the Elderly SCORE : Systematic COronary Risk Evaluation SHEP : Systolic Hypertension in the Elderly Program STOP : Swedish Trials in Old Patients with Hypertension STOP-2 : The second Swedish Trial in Old Patients with Hypertension SYSTCHINA : SYSTolic Hypertension in the Elderly: Chinese trial SYSTEUR : SYSTolic Hypertension in Europe TIA : transient ischaemic attack TOHP : Trials Of Hypertension Prevention TRANSCEND : Telmisartan Randomised AssessmeNt Study in ACE iNtolerant subjects with cardiovascular Disease UKPDS : United Kingdom Prospective Diabetes Study VADT : Veterans' Affairs Diabetes Trial VALUE : Valsartan Antihypertensive Long-term Use Evaluation WHO : World Health Organization ### 1.1 Principles The 2013 guidelines on hypertension of the European Society of Hypertension (ESH) and the European Society of Cardiology …

14,173 citations

Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

12,661 citations

Journal ArticleDOI
Paul Burton1, David Clayton2, Lon R. Cardon, Nicholas John Craddock3  +192 moreInstitutions (4)
07 Jun 2007-Nature
TL;DR: This study has demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in theBritish population is generally modest.
Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

9,244 citations

Journal ArticleDOI
Monkol Lek, Konrad J. Karczewski1, Konrad J. Karczewski2, Eric Vallabh Minikel2, Eric Vallabh Minikel1, Kaitlin E. Samocha, Eric Banks1, Timothy Fennell1, Anne H. O’Donnell-Luria2, Anne H. O’Donnell-Luria3, Anne H. O’Donnell-Luria1, James S. Ware, Andrew J. Hill4, Andrew J. Hill2, Andrew J. Hill1, Beryl B. Cummings1, Beryl B. Cummings2, Taru Tukiainen2, Taru Tukiainen1, Daniel P. Birnbaum1, Jack A. Kosmicki, Laramie E. Duncan1, Laramie E. Duncan2, Karol Estrada2, Karol Estrada1, Fengmei Zhao2, Fengmei Zhao1, James Zou1, Emma Pierce-Hoffman2, Emma Pierce-Hoffman1, Joanne Berghout5, David Neil Cooper6, Nicole A. Deflaux7, Mark A. DePristo1, Ron Do, Jason Flannick2, Jason Flannick1, Menachem Fromer, Laura D. Gauthier1, Jackie Goldstein2, Jackie Goldstein1, Namrata Gupta1, Daniel P. Howrigan2, Daniel P. Howrigan1, Adam Kiezun1, Mitja I. Kurki1, Mitja I. Kurki2, Ami Levy Moonshine1, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso1, Gina M. Peloso2, Ryan Poplin1, Manuel A. Rivas1, Valentin Ruano-Rubio1, Samuel A. Rose1, Douglas M. Ruderfer8, Khalid Shakir1, Peter D. Stenson6, Christine Stevens1, Brett Thomas1, Brett Thomas2, Grace Tiao1, María Teresa Tusié-Luna, Ben Weisburd1, Hong-Hee Won9, Dongmei Yu, David Altshuler1, David Altshuler10, Diego Ardissino, Michael Boehnke11, John Danesh12, Stacey Donnelly1, Roberto Elosua, Jose C. Florez2, Jose C. Florez1, Stacey Gabriel1, Gad Getz1, Gad Getz2, Stephen J. Glatt13, Christina M. Hultman14, Sekar Kathiresan, Markku Laakso15, Steven A. McCarroll1, Steven A. McCarroll2, Mark I. McCarthy16, Mark I. McCarthy17, Dermot P.B. McGovern18, Ruth McPherson19, Benjamin M. Neale1, Benjamin M. Neale2, Aarno Palotie, Shaun Purcell8, Danish Saleheen20, Jeremiah M. Scharf, Pamela Sklar, Patrick F. Sullivan21, Patrick F. Sullivan14, Jaakko Tuomilehto22, Ming T. Tsuang23, Hugh Watkins16, Hugh Watkins17, James G. Wilson24, Mark J. Daly1, Mark J. Daly2, Daniel G. MacArthur2, Daniel G. MacArthur1 
18 Aug 2016-Nature
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

8,758 citations