Institution
University of Cambridge
Education•Cambridge, United Kingdom•
About: University of Cambridge is a education organization based out in Cambridge, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 118293 authors who have published 282289 publications receiving 14497093 citations. The organization is also known as: Cambridge University & Cambridge.
Topics: Population, Galaxy, Context (language use), Gene, Transplantation
Papers published on a yearly basis
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Broad Institute1, University of Pennsylvania2, Harvard University3, National Institutes of Health4, Boston University5, Lund University6, University of Copenhagen7, University of Texas Health Science Center at Houston8, deCODE genetics9, Queen Mary University of London10, University of Lübeck11, Glenfield Hospital12, University of Leicester13, University of Oxford14, University of Cambridge15, University of Ottawa16, University of Iceland17, Population Health Research Institute18, McGill University19, Vanderbilt University20, University of Missouri–Kansas City21, University of Münster22, University of Verona23, Queen's University Belfast24, MedStar Washington Hospital Center25, GlaxoSmithKline26, University of Helsinki27, Karolinska Institutet28, University of Mainz29, Utrecht University30, University of Groningen31, University of Michigan32, Centro Nacional de Investigaciones Cardiovasculares33, United States Department of Agriculture34, University of North Carolina at Chapel Hill35, University of Regensburg36, Katholieke Universiteit Leuven37, University of Edinburgh38, University of Kiel39, University of Leeds40, Aarhus University41, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico42, University of Washington43, Wellcome Trust Sanger Institute44
TL;DR: In this paper, a Mendelian randomisation analysis was performed to compare the effect of HDL cholesterol, LDL cholesterol, and genetic score on risk of myocardial infarction.
Abstract: Methods We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20 913 myocardial infarction cases, 95 407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12 482 cases of myocardial infarction and 41 331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol. – ¹³) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with noncarriers. This diff erence in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84–0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88–1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58–0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68–1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45–1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69–2·69, p=2×10
1,878 citations
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TL;DR: A subcellular map of the human proteome is presented to facilitate functional exploration of individual proteins and their role in human biology and disease and integrated into existing network models of protein-protein interactions for increased accuracy.
Abstract: Resolving the spatial distribution of the human proteome at a subcellular level can greatly increase our understanding of human biology and disease. Here we present a comprehensive image-based map ...
1,878 citations
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TL;DR: The optoelectronic properties of graphene are exploited to realize an ultrafast laser and pave the way to graphene-based photonics.
Abstract: Graphene is at the center of a significant research effort Near-ballistic transport at room temperature and high mobility make it a potential material for nanoelectronics Its electronic and mechanical properties are also ideal for micro- and nanomechanical systems, thin-film transistors, and transparent and conductive composites and electrodes Here we exploit the optoelectronic properties of graphene to realize an ultrafast laser A graphene-polymer composite is fabricated using wet-chemistry techniques Pauli blocking following intense illumination results in saturable absorption, independent of wavelength This is used to passively mode-lock an erbium-doped fiber laser working at 1559 nm, with a 524 nm spectral bandwidth and approximately 460 fs pulse duration, paving the way to graphene-based photonics
1,878 citations
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National Institutes of Health1, Mayo Clinic2, Harvard University3, American Cancer Society4, University of Melbourne5, University of Cambridge6, University of California, Irvine7, Loma Linda University8, Johns Hopkins University9, University of Minnesota10, Cancer Council Victoria11, Karolinska Institutet12, City of Hope National Medical Center13, New York University14, University of Washington15, The Queen's Medical Center16
TL;DR: In white adults, overweight and obesity (and possibly underweight) are associated with increased all-cause mortality and the hazard ratios for the men were similar.
Abstract: BACKGROUND A high body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) is associated with increased mortality from cardiovascular disease and certain cancers, but the precise relationship between BMI and all-cause mortality remains uncertain. METHODS We used Cox regression to estimate hazard ratios and 95% confidence intervals for an association between BMI and all-cause mortality, adjusting for age, study, physical activity, alcohol consumption, education, and marital status in pooled data from 19 prospective studies encompassing 1.46 million white adults, 19 to 84 years of age (median, 58). RESULTS The median baseline BMI was 26.2. During a median follow-up period of 10 years (range, 5 to 28), 160,087 deaths were identified. Among healthy participants who never smoked, there was a J-shaped relationship between BMI and all-cause mortality. With a BMI of 22.5 to 24.9 as the reference category, hazard ratios among women were 1.47 (95 percent confidence interval [CI], 1.33 to 1.62) for a BMI of 15.0 to 18.4; 1.14 (95% CI, 1.07 to 1.22) for a BMI of 18.5 to 19.9; 1.00 (95% CI, 0.96 to 1.04) for a BMI of 20.0 to 22.4; 1.13 (95% CI, 1.09 to 1.17) for a BMI of 25.0 to 29.9; 1.44 (95% CI, 1.38 to 1.50) for a BMI of 30.0 to 34.9; 1.88 (95% CI, 1.77 to 2.00) for a BMI of 35.0 to 39.9; and 2.51 (95% CI, 2.30 to 2.73) for a BMI of 40.0 to 49.9. In general, the hazard ratios for the men were similar. Hazard ratios for a BMI below 20.0 were attenuated with longer-term follow-up. CONCLUSIONS In white adults, overweight and obesity (and possibly underweight) are associated with increased all-cause mortality. All-cause mortality is generally lowest with a BMI of 20.0 to 24.9.
1,874 citations
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TL;DR: This article identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height, and all common variants together captured 60% of heritability.
Abstract: Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
1,872 citations
Authors
Showing all 119522 results
Name | H-index | Papers | Citations |
---|---|---|---|
Albert Hofman | 267 | 2530 | 321405 |
Zhong Lin Wang | 245 | 2529 | 259003 |
Solomon H. Snyder | 232 | 1222 | 200444 |
Trevor W. Robbins | 231 | 1137 | 164437 |
George Davey Smith | 224 | 2540 | 248373 |
Nicholas J. Wareham | 212 | 1657 | 204896 |
Cyrus Cooper | 204 | 1869 | 206782 |
Eric B. Rimm | 196 | 988 | 147119 |
Martin White | 196 | 2038 | 232387 |
Simon D. M. White | 189 | 795 | 231645 |
Michael Rutter | 188 | 676 | 151592 |
George Efstathiou | 187 | 637 | 156228 |
Mark Hallett | 186 | 1170 | 123741 |
David H. Weinberg | 183 | 700 | 171424 |
Paul G. Richardson | 183 | 1533 | 155912 |