Institution
University of Iceland
Education•Reykjavik, Suðurnes, Iceland•
About: University of Iceland is a education organization based out in Reykjavik, Suðurnes, Iceland. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 5423 authors who have published 16199 publications receiving 694762 citations. The organization is also known as: Háskóli Íslands.
Papers published on a yearly basis
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University of Helsinki1, National Institutes of Health2, Wellcome Trust Centre for Human Genetics3, University of Tartu4, University of Ferrara5, University Medical Center Groningen6, Amgen7, Karolinska Institutet8, Uppsala University9, VU University Amsterdam10, Erasmus University Rotterdam11, Lund University12, Leiden University Medical Center13, National Institute for Health Research14, University of Lübeck15, Medical Research Council16, Technische Universität München17, University of Tampere18, Steno Diabetes Center19, Ludwig Maximilian University of Munich20, Harvard University21, Massachusetts Institute of Technology22, European Bioinformatics Institute23, University of Leicester24, Turku University Hospital25, Uppsala University Hospital26, Erasmus University Medical Center27, University College London28, University of Turku29, University of Oxford30, University of Iceland31, Minerva Foundation Institute for Medical Research32, University of Liverpool33, Imperial College London34, Wellcome Trust Sanger Institute35
TL;DR: Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, association to lipid traits in 93 loci is identified, including 79 previously identified loci with new lead SNPs and 10 new loci, including 15 locu with a low-frequency lead SNP and 10 loco with a missense lead SNP.
Abstract: Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.
279 citations
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Lisette Stolk1, John R. B. Perry2, John R. B. Perry3, Daniel I. Chasman4 +195 more•Institutions (54)
TL;DR: A meta-analysis of 22 genome-wide association studies in 38,968 women of European descent identified 13 loci newly associated with age at natural menopause, including genes implicated in DNA repair, immune function and immune function.
Abstract: To newly identify loci for age at natural menopause, we carried out a meta-analysis of 22 genome-wide association studies (GWAS) in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 loci newly associated with age at natural menopause (at P < 5 × 10(-8)). Candidate genes located at these newly associated loci include genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG and PRIM1) and immune function (IL11, NLRP11 and PRRC2A (also known as BAT2)). Gene-set enrichment pathway analyses using the full GWAS data set identified exoDNase, NF-κB signaling and mitochondrial dysfunction as biological processes related to timing of menopause.
279 citations
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TL;DR: Nonlinear PCA, performed by autoassociative neural network, has emerged as a good unsupervised technique to fit the information content of hyperspectral data into few components and results show that NLPCA permits one to obtain better classification accuracies than using linear PCA.
Abstract: Morphological profiles (MPs) have been proposed in recent literature as aiding tools to achieve better results for classification of remotely sensed data. MPs are in general built using features containing most of the information content of the data, such as the components derived from principal component analysis (PCA). Recently, nonlinear PCA (NLPCA), performed by autoassociative neural network, has emerged as a good unsupervised technique to fit the information content of hyperspectral data into few components. The aim of this letter is to investigate the classification accuracies obtained using extended MPs built from the features of NPCA. A comparison of the two approaches has been validated on two different data sets having different spatial and spectral resolutions/coverages, over the same ground truth, and also using two different classification algorithms. The results show that NLPCA permits one to obtain better classification accuracies than using linear PCA.
278 citations
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Boston University1, Erasmus University Rotterdam2, University of North Carolina at Chapel Hill3, Uppsala University4, National Institutes of Health5, University of Maryland, Baltimore6, Cedars-Sinai Medical Center7, Washington University in St. Louis8, University of Iceland9, Mayo Clinic10, University of Texas Health Science Center at Houston11, Johns Hopkins University12, University of Minnesota13, University of Washington14, University of Edinburgh15, University of Zagreb16, Harvard University17, Yeshiva University18
TL;DR: It is established that common variants in NRXN3 are associated with WC, BMI, and obesity, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder.
Abstract: Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4610 27 )]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3610 28 for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4610 26 , 0.024 z-score units (0.10 kg/m 2 ) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07–1.19; p = 3.2610 25 per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.
278 citations
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TL;DR: The proposed method deals with the joint use of the spatial and the spectral information provided by the remote-sensing images with very high spatial resolution and is competitive with other contextual methods.
277 citations
Authors
Showing all 5561 results
Name | H-index | Papers | Citations |
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Albert Hofman | 267 | 2530 | 321405 |
Kari Stefansson | 206 | 794 | 174819 |
Ronald Klein | 194 | 1305 | 149140 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Unnur Thorsteinsdottir | 167 | 444 | 121009 |
Vilmundur Gudnason | 159 | 837 | 123802 |
Hakon Hakonarson | 152 | 968 | 101604 |
Bernhard O. Palsson | 147 | 831 | 85051 |
Andrew T. Hattersley | 146 | 768 | 106949 |
Fernando Rivadeneira | 146 | 628 | 86582 |
Rattan Lal | 140 | 1383 | 87691 |
Jonathan G. Seidman | 137 | 563 | 89782 |
Christine E. Seidman | 134 | 519 | 67895 |
Augustine Kong | 134 | 237 | 89818 |
Timothy M. Frayling | 133 | 500 | 100344 |