Author
Stephen O'Rahilly
Other affiliations: Dana Corporation, University of Oxford, Beth Israel Deaconess Medical Center ...read more
Bio: Stephen O'Rahilly is an academic researcher from University of Cambridge. The author has contributed to research in topics: Insulin resistance & Insulin. The author has an hindex of 138, co-authored 520 publications receiving 75686 citations. Previous affiliations of Stephen O'Rahilly include Dana Corporation & University of Oxford.
Topics: Insulin resistance, Insulin, Insulin receptor, Leptin, Adipose tissue
Papers published on a yearly basis
Papers
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TL;DR: The severe obesity found in two severely obese children who are members of the same highly consanguineous pedigree provides the first genetic evidence that leptin is an important regulator of energy balance in humans.
Abstract: The extreme obesity of the obese (ob/ob) mouse is attributable to mutations in the gene encoding leptin, an adipocyte-specific secreted protein which has profound effects on appetite and energy expenditure We know of no equivalent evidence regarding leptin's role in the control of fat mass in humans We have examined two severely obese children who are members of the same highly consanguineous pedigree Their serum leptin levels were very low despite their markedly elevated fat mass and, in both, a homozygous frame-shift mutation involving the deletion of a single guanine nucleotide in codon 133 of the gene for leptin was found The severe obesity found in these congenitally leptin-deficient subjects provides the first genetic evidence that leptin is an important regulator of energy balance in humans
2,912 citations
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Elizabeth K. Speliotes1, Elizabeth K. Speliotes2, Cristen J. Willer3, Sonja I. Berndt +410 more•Institutions (86)
TL;DR: Genetic loci associated with body mass index map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor, which may provide new insights into human body weight regulation.
Abstract: Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and similar to 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
2,632 citations
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TL;DR: Puberty is initiated when gonadotropin-releasing hormone begins to be secreted by the hypothalamus, and complementary genetic approaches in humans and mice identified genetic factors that determine the onset of puberty.
Abstract: Background Puberty, a complex biologic process involving sexual development, accelerated linear growth, and adrenal maturation, is initiated when gonadotropin-releasing hormone begins to be secreted by the hypothalamus. We conducted studies in humans and mice to identify the genetic factors that determine the onset of puberty. Methods We used complementary genetic approaches in humans and in mice. A consanguineous family with members who lacked pubertal development (idiopathic hypogonadotropic hypogonadism) was examined for mutations in a candidate gene, GPR54, which encodes a G protein–coupled receptor. Functional differences between wild-type and mutant GPR54 were examined in vitro. In parallel, a Gpr54-deficient mouse model was created and phenotyped. Responsiveness to exogenous gonadotropin-releasing hormone was assessed in both the humans and the mice. Results Affected patients in the index pedigree were homozygous for an L148S mutation in GPR54, and an unrelated proband with idiopathic hypogonadotro...
2,253 citations
01 Jan 2010
TL;DR: 18 new loci associated with body mass index are identified, one of which includes a copy number variant near GPRC5B, and genes in other newly associated loci may provide new insights into human body weight regulation.
Abstract: Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and approximately 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-)(8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
1,953 citations
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TL;DR: The administration of leptin corrects their obesity by reducing their food intake and increasing their energy expenditure and these mice also have hyperinsulinemia, corticosterone excess, and infertility, which also are reversed by treatment with leptin.
Abstract: Severely obese (ob/ob) mice are deficient in the adipocyte-derived hormone leptin, which acts on the hypothalamus to control appetite and energy expenditure.1 The administration of leptin to these mice corrects their obesity by reducing their food intake and increasing their energy expenditure.2–4 These mice also have hyperinsulinemia, corticosterone excess, and infertility, which also are reversed by treatment with leptin.5 In humans, serum leptin concentrations, in general, correlate positively with indexes of obesity.6,7 We previously described two cousins with severe, early-onset obesity and undetectable serum leptin concentrations who were homozygous for a frame-shift mutation in the leptin . . .
1,871 citations
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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
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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
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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
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National Institutes of Health1, University of Chicago2, Duke University3, Harvard University4, University of Oxford5, GlaxoSmithKline6, Johns Hopkins University7, Yale University8, deCODE genetics9, Princeton University10, Howard Hughes Medical Institute11, Washington University in St. Louis12, University of California, Berkeley13, Stanford University14, University of Michigan15, Cornell University16, University of Washington17, University of Queensland18, Vanderbilt University19, North Carolina State University20, QIMR Berghofer Medical Research Institute21
TL;DR: This paper examined potential sources of missing heritability and proposed research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
7,797 citations
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Drexel University1, Yeshiva University2, Roswell Park Cancer Institute3, Virginia Commonwealth University4, Van Andel Institute5, Science Applications International Corporation6, Massachusetts Institute of Technology7, Harvard University8, University of Miami9, Icahn School of Medicine at Mount Sinai10, University of Chicago11, Howard Hughes Medical Institute12, University of Geneva13, Stanford University14, University of Oxford15, University of North Carolina at Chapel Hill16, National Institutes of Health17
TL;DR: The Genotype-Tissue Expression (GTEx) project is described, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
Abstract: Genome-wide association studies have identified thousands of loci for common diseases, but, for the majority of these, the mechanisms underlying disease susceptibility remain unknown. Most associated variants are not correlated with protein-coding changes, suggesting that polymorphisms in regulatory regions probably contribute to many disease phenotypes. Here we describe the Genotype-Tissue Expression (GTEx) project, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
6,545 citations