JoVE Visualize What is visualize?
Stop Reading. Start Watching.
Advanced Search
Stop Reading. Start Watching.
Regular Search
Find video protocols related to scientific articles indexed in Pubmed.
GWAS of 126,559 individuals identifies genetic variants associated with educational attainment.
Cornelius A Rietveld, Sarah E Medland, Jaime Derringer, Jian Yang, Tonu Esko, Nicolas W Martin, Harm-Jan Westra, Konstantin Shakhbazov, Abdel Abdellaoui, Arpana Agrawal, Eva Albrecht, Behrooz Z Alizadeh, Najaf Amin, John Barnard, Sebastian E Baumeister, Kelly S Benke, Lawrence F Bielak, Jeffrey A Boatman, Patricia A Boyle, Gail Davies, Christiaan de Leeuw, Niina Eklund, Daniel S Evans, Rudolf Ferhmann, Krista Fischer, Christian Gieger, Håkon K Gjessing, Sara Hägg, Jennifer R Harris, Caroline Hayward, Christina Holzapfel, Carla A Ibrahim-Verbaas, Erik Ingelsson, Bo Jacobsson, Peter K Joshi, Astanand Jugessur, Marika Kaakinen, Stavroula Kanoni, Juha Karjalainen, Ivana Kolčić, Kati Kristiansson, Zoltan Kutalik, Jari Lahti, Sang H Lee, Peng Lin, Penelope A Lind, Yongmei Liu, Kurt Lohman, Marisa Loitfelder, George McMahon, Pedro Marques Vidal, Osorio Meirelles, Lili Milani, Ronny Myhre, Marja-Liisa Nuotio, Christopher J Oldmeadow, Katja E Petrovic, Wouter J Peyrot, Ozren Polašek, Lydia Quaye, Eva Reinmaa, John P Rice, Thais S Rizzi, Helena Schmidt, Reinhold Schmidt, Albert V Smith, Jennifer A Smith, Toshiko Tanaka, Antonio Terracciano, Matthijs J H M van der Loos, Veronique Vitart, Henry Völzke, Jürgen Wellmann, Lei Yu, Wei Zhao, Jüri Allik, John R Attia, Stefania Bandinelli, François Bastardot, Jonathan Beauchamp, David A Bennett, Klaus Berger, Laura J Bierut, Dorret I Boomsma, Ute Bültmann, Harry Campbell, Christopher F Chabris, Lynn Cherkas, Mina K Chung, Francesco Cucca, Mariza de Andrade, Philip L De Jager, Jan-Emmanuel De Neve, Ian J Deary, George V Dedoussis, Panos Deloukas, Maria Dimitriou, Guðný Eiríksdóttir, Martin F Elderson, Johan G Eriksson, David M Evans, Jessica D Faul, Luigi Ferrucci, Melissa E Garcia, Henrik Grönberg, Vilmundur Guðnason, Per Hall, Juliette M Harris, Tamara B Harris, Nicholas D Hastie, Andrew C Heath, Dena G Hernandez, Wolfgang Hoffmann, Adriaan Hofman, Rolf Holle, Elizabeth G Holliday, Jouke-Jan Hottenga, William G Iacono, Thomas Illig, Marjo-Riitta Järvelin, Mika Kähönen, Jaakko Kaprio, Robert M Kirkpatrick, Matthew Kowgier, Antti Latvala, Lenore J Launer, Debbie A Lawlor, Terho Lehtimäki, Jingmei Li, Paul Lichtenstein, Peter Lichtner, David C Liewald, Pamela A Madden, Patrik K E Magnusson, Tomi E Mäkinen, Marco Masala, Matt McGue, Andres Metspalu, Andreas Mielck, Michael B Miller, Grant W Montgomery, Sutapa Mukherjee, Dale R Nyholt, Ben A Oostra, Lyle J Palmer, Aarno Palotie, Brenda W J H Penninx, Markus Perola, Patricia A Peyser, Martin Preisig, Katri Räikkönen, Olli T Raitakari, Anu Realo, Susan M Ring, Samuli Ripatti, Fernando Rivadeneira, Igor Rudan, Aldo Rustichini, Veikko Salomaa, Antti-Pekka Sarin, David Schlessinger, Rodney J Scott, Harold Snieder, Beate St Pourcain, John M Starr, Jae Hoon Sul, Ida Surakka, Rauli Svento, Alexander Teumer, , Henning Tiemeier, Frank J A van Rooij, David R Van Wagoner, Erkki Vartiainen, Jorma Viikari, Peter Vollenweider, Judith M Vonk, Gérard Waeber, David R Weir, H-Erich Wichmann, Elisabeth Widén, Gonneke Willemsen, James F Wilson, Alan F Wright, Dalton Conley, George Davey-Smith, Lude Franke, Patrick J F Groenen, Albert Hofman, Magnus Johannesson, Sharon L R Kardia, Robert F Krueger, David Laibson, Nicholas G Martin, Michelle N Meyer, Danielle Posthuma, A Roy Thurik, Nicholas J Timpson, André G Uitterlinden, Cornelia M van Duijn, Peter M Visscher, Daniel J Benjamin, David Cesarini, Philipp D Koellinger.
Science
PUBLISHED: 05-30-2013
Show Abstract
Hide Abstract
A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ? 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ?2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
Related JoVE Video
GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies.
BMC Bioinformatics
PUBLISHED: 04-24-2013
Show Abstract
Hide Abstract
Genome-wide association studies have become very popular in identifying genetic contributions to phenotypes. Millions of SNPs are being tested for their association with diseases and traits using linear or logistic regression models. This conceptually simple strategy encounters the following computational issues: a large number of tests and very large genotype files (many Gigabytes) which cannot be directly loaded into the software memory. One of the solutions applied on a grand scale is cluster computing involving large-scale resources. We show how to speed up the computations using matrix operations in pure R code.
Related JoVE Video
Serum testosterone levels in males are not associated with entrepreneurial behavior in two independent observational studies.
Physiol. Behav.
PUBLISHED: 03-08-2013
Show Abstract
Hide Abstract
Previous research has suggested a positive association between testosterone (T) and entrepreneurial behavior in males. However, this evidence was found in a study with a small sample size and has not been replicated. In the present study, we aimed to verify this association using two large, independent, population-based samples of males. We tested the association of T with entrepreneurial behavior, operationalized as self-employment, using data from the Rotterdam Study (N=587) and the Study of Health in Pomerania (N=1697). Total testosterone (TT) and sex hormone-binding globulin (SHBG) were measured in the serum. Free testosterone (FT), non-SHBG-bound T (non-SHBG-T), and the TT/SHBG ratio were calculated and used as measures of bioactive serum T, in addition to TT adjusted for SHBG. Using logistic regression models, we found no significant associations between any of the serum T measures and self-employment in either of the samples. To our knowledge, this is the first large-scale study on the relationship between serum T and entrepreneurial behavior.
Related JoVE Video
The molecular genetic architecture of self-employment.
PLoS ONE
PUBLISHED: 01-01-2013
Show Abstract
Hide Abstract
Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (?(g)(2)/?(P)(2)?=?25%, h(2)?=?55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10(-5) were tested in a replication sample (n?=?3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p?0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.
Related JoVE Video
Fast linear mixed model computations for genome-wide association studies with longitudinal data.
Stat Med
Show Abstract
Hide Abstract
Genome-wide association studies are characterized by a huge number of statistical tests performed to discover new disease-related genetic variants [in the form of single-nucleotide polymorphisms (SNPs)] in human DNA. Many SNPs have been identified for cross-sectionally measured phenotypes. However, there is a growing interest in genetic determinants of the evolution of traits over time. Dealing with correlated observations from the same individual, we need to apply advanced statistical techniques. The linear mixed model is popular but also much more computationally demanding than fitting a linear regression model to independent observations. We propose a conditional two-step approach as an approximate method to explore the longitudinal relationship between the trait and the SNP. In a simulation study, we compare several fast methods with respect to their accuracy and speed. The conditional two-step approach is applied to relate SNPs to longitudinal bone mineral density responses collected in the Rotterdam Study.
Related JoVE Video
Estimating emergence sequences of permanent teeth in Flemish schoolchildren using interval-censored biplots: a graphical display of tooth emergence sequences.
Community Dent Oral Epidemiol
Show Abstract
Hide Abstract
The aim of the present study was to investigate the pattern of emergence of permanent teeth using nonparametric techniques.
Related JoVE Video

What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.