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Nilesh J. Samani

Researcher at University of Leicester

Publications -  836
Citations -  127518

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.

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A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium

Nicole Soranzo, +87 more
- 01 Nov 2009 - 
TL;DR: A long-range haplotype at 12q24 associated with coronary artery disease and myocardial infarction is identified and it is shown that this haplotype demonstrates extensive disease pleiotropy, as it contains known risk loci for type 1 diabetes, hypertension and celiac disease and has been spread by a selective sweep specific to European and geographically nearby populations.
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New susceptibility locus for coronary artery disease on chromosome 3q22.3

Jeanette Erdmann, +60 more
- 01 Mar 2009 - 
TL;DR: A three-stage analysis of genome-wide SNP data in 1,222 German individuals with myocardial infarction and 1,298 controls is presented and suggestive association with a locus on 12q24.31 near HNF1A-C12orf43 is identified.

Genome-wide association analyses identify 18 new loci associated with serum urate concentrations

Anna Koettgen, +224 more
TL;DR: In this article, the authors identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4).
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The transcriptional landscape of age in human peripheral blood

Marjolein J. Peters, +158 more
TL;DR: Differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index and the transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models.