%0 Journal Article %J Nature Genetics %D 2018 %T Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence %A Savage, Jeanne E. %A Philip R Jansen %A Stringer, Sven %A Watanabe, Kyoko %A Bryois, Julien %A Christiaan de Leeuw %A Nagel, Mats %A Awasthi, Swapnil %A Barr, Peter B. %A Coleman, Jonathan R. I. %A Grasby, Katrina L. %A Anke R Hammerschlag %A Kaminski, Jakob A. %A Karlsson, Robert %A Krapohl, Eva %A Lam, Max %A Nygaard, Marianne %A Chandra A Reynolds %A Joey W Trampush %A Young, Hannah %A Zabaneh, Delilah %A Hägg, Sara %A Narelle K Hansell %A Ida Karlsson %A Linnarsson, Sten %A Grant W Montgomery %A Muñoz-Manchado, Ana B. %A Quinlan, Erin B. %A Schumann, Gunter %A Skene, Nathan G. %A Webb, Bradley T. %A White, Tonya %A Dan E Arking %A Avramopoulos, Dimitrios %A Robert M Bilder %A Bitsios, Panos %A Katherine E Burdick %A Tyrone D. Cannon %A Chiba-Falek, Ornit %A Christoforou, Andrea %A Elizabeth T. Cirulli %A Congdon, Eliza %A Corvin, Aiden %A Gail Davies %A Ian J Deary %A DeRosse, Pamela %A Dickinson, Dwight %A Djurovic, Srdjan %A Donohoe, Gary %A Conley, Emily Drabant %A Johan G Eriksson %A Espeseth, Thomas %A Nelson A. Freimer %A Giakoumaki, Stella %A Giegling, Ina %A Gill, Michael %A David C. Glahn %A Ahmad R Hariri %A Hatzimanolis, Alex %A Matthew C Keller %A Knowles, Emma %A Koltai, Deborah %A Konte, Bettina %A Lahti, Jari %A Stephanie Le Hellard %A Lencz, Todd %A David C Liewald %A London, Edythe %A Astri J Lundervold %A Anil K. Malhotra %A Melle, Ingrid %A Morris, Derek %A Anna C Need %A William E R Ollier %A Aarno Palotie %A Payton, Antony %A Pendleton, Neil %A Russell A Poldrack %A Katri Räikkönen %A Reinvang, Ivar %A Roussos, Panos %A Rujescu, Dan %A Fred W Sabb %A Matthew A Scult %A Smeland, Olav B. %A Smyrnis, Nikolaos %A John M Starr %A Vidar M Steen %A Nikos C Stefanis %A Richard E Straub %A Sundet, Kjetil %A Henning Tiemeier %A Aristotle N Voineskos %A Daniel R Weinberger %A Elisabeth Widen %A Yu, Jin %A Gonçalo R Abecasis %A Andreassen, Ole A. %A Breen, Gerome %A Christiansen, Lene %A Debrabant, Birgit %A Danielle M. Dick %A Heinz, Andreas %A Hjerling-Leffler, Jens %A Mohammed Arfan Ikram %A Kendler, Kenneth S. %A Nicholas G Martin %A Sarah E Medland %A Nancy L Pedersen %A Plomin, Robert %A Tinca J Polderman %A Ripke, Stephan %A van der Sluis, Sophie %A Patrick F. Sullivan %A Scott Vrieze %A Margaret J Wright %A Posthuma, Danielle %K Genome-Wide Association Study %K Intelligence %K Meta-analyses %X Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders. %B Nature Genetics %V 50 %P 912 - 919 %8 Jan-07-2018 %G eng %U http://www.nature.com/articles/s41588-018-0152-6http://www.nature.com/articles/s41588-018-0152-6.pdfhttp://www.nature.com/articles/s41588-018-0152-6http://www.nature.com/articles/s41588-018-0152-6.pdf %N 7 %! Nat Genet %R 10.1038/s41588-018-0152-6 %0 Journal Article %J Nature Communications %D 2018 %T Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. %A Gail Davies %A Lam, Max %A Sarah E Harris %A Joey W Trampush %A Luciano, Michelle %A W David Hill %A Hagenaars, Saskia P %A Ritchie, Stuart J %A Riccardo E Marioni %A Fawns-Ritchie, Chloe %A David C Liewald %A Okely, Judith A %A Ahola-Olli, Ari V %A Barnes, Catriona L K %A Bertram, Lars %A Joshua C. Bis %A Katherine E Burdick %A Christoforou, Andrea %A DeRosse, Pamela %A Djurovic, Srdjan %A Espeseth, Thomas %A Giakoumaki, Stella %A Giddaluru, Sudheer %A Gustavson, Daniel E %A Caroline Hayward %A Edith Hofer %A Ikram, M Arfan %A Karlsson, Robert %A Knowles, Emma %A Lahti, Jari %A Leber, Markus %A Li, Shuo %A Mather, Karen A %A Melle, Ingrid %A Morris, Derek %A Christopher J Oldmeadow %A Palviainen, Teemu %A Payton, Antony %A Pazoki, Raha %A Katja E Petrovic %A Chandra A Reynolds %A Sargurupremraj, Muralidharan %A Scholz, Markus %A Smith, Jennifer A %A Smith, Albert V %A Terzikhan, Natalie %A Thalamuthu, Anbupalam %A Trompet, Stella %A Sven J van der Lee %A Erin B Ware %A Windham, B Gwen %A Margaret J Wright %A Yang, Jingyun %A Yu, Jin %A Ames, David %A Amin, Najaf %A Amouyel, Philippe %A Andreassen, Ole A %A Armstrong, Nicola J %A Assareh, Amelia A %A John R. Attia %A Attix, Deborah %A Avramopoulos, Dimitrios %A David A Bennett %A Böhmer, Anne C %A Patricia A. Boyle %A Brodaty, Henry %A Campbell, Harry %A Tyrone D. Cannon %A Elizabeth T. Cirulli %A Congdon, Eliza %A Conley, Emily Drabant %A Corley, Janie %A Cox, Simon R %A Dale, Anders M %A Dehghan, Abbas %A Danielle M. Dick %A Dickinson, Dwight %A Johan G Eriksson %A Evangelou, Evangelos %A Jessica Faul %A Ford, Ian %A Nelson A. Freimer %A Gao, He %A Giegling, Ina %A Gillespie, Nathan A %A Gordon, Scott D %A Gottesman, Rebecca F %A Michael E Griswold %A Gudnason, Vilmundur %A Tamara B Harris %A Hartmann, Annette M %A Hatzimanolis, Alex %A Gerardo Heiss %A Holliday, Elizabeth G %A Joshi, Peter K %A Kähönen, Mika %A Sharon L R Kardia %A Ida Karlsson %A Kleineidam, Luca %A David S Knopman %A Kochan, Nicole A %A Konte, Bettina %A Kwok, John B %A Stephanie Le Hellard %A Lee, Teresa %A Lehtimäki, Terho %A Li, Shu-Chen %A Lill, Christina M %A Liu, Tian %A Koini, Marisa %A London, Edythe %A Longstreth, Will T %A Lopez, Oscar L %A Loukola, Anu %A Luck, Tobias %A Astri J Lundervold %A Lundquist, Anders %A Lyytikäinen, Leo-Pekka %A Nicholas G Martin %A Grant W Montgomery %A Murray, Alison D %A Anna C Need %A Noordam, Raymond %A Nyberg, Lars %A William E R Ollier %A Papenberg, Goran %A Pattie, Alison %A Polasek, Ozren %A Russell A Poldrack %A Psaty, Bruce M %A Reppermund, Simone %A Steffi G Riedel-Heller %A Rose, Richard J %A Rotter, Jerome I %A Roussos, Panos %A Rovio, Suvi P %A Saba, Yasaman %A Fred W Sabb %A Sachdev, Perminder S %A Satizabal, Claudia L %A Schmid, Matthias %A Rodney J Scott %A Matthew A Scult %A Simino, Jeannette %A Slagboom, P Eline %A Smyrnis, Nikolaos %A Soumaré, Aïcha %A Nikos C Stefanis %A Stott, David J %A Richard E Straub %A Sundet, Kjetil %A Taylor, Adele M %A Kent D Taylor %A Tzoulaki, Ioanna %A Tzourio, Christophe %A André G Uitterlinden %A Vitart, Veronique %A Aristotle N Voineskos %A Kaprio, Jaakko %A Wagner, Michael %A Wagner, Holger %A Weinhold, Leonie %A Wen, K Hoyan %A Elisabeth Widen %A Yang, Qiong %A Zhao, Wei %A Hieab H Adams %A Dan E Arking %A Robert M Bilder %A Bitsios, Panos %A Boerwinkle, Eric %A Chiba-Falek, Ornit %A Corvin, Aiden %A Philip L de Jager %A Debette, Stéphanie %A Donohoe, Gary %A Elliott, Paul %A Fitzpatrick, Annette L %A Gill, Michael %A David C. Glahn %A Hägg, Sara %A Narelle K Hansell %A Ahmad R Hariri %A Ikram, M Kamran %A Jukema, J Wouter %A Vuoksimaa, Eero %A Matthew C Keller %A Kremen, William S %A Lenore J Launer %A Lindenberger, Ulman %A Aarno Palotie %A Nancy L Pedersen %A Pendleton, Neil %A David J Porteous %A Katri Räikkönen %A Olli T Raitakari %A Ramirez, Alfredo %A Reinvang, Ivar %A Rudan, Igor %A Schmidt, Reinhold %A Schmidt, Helena %A Peter W Schofield %A Peter R Schofield %A John M Starr %A Vidar M Steen %A Trollor, Julian N %A Turner, Steven T %A Cornelia M van Duijn %A Villringer, Arno %A Daniel R Weinberger %A David R Weir %A James F Wilson %A Anil K. Malhotra %A McIntosh, Andrew M %A Gale, Catharine R %A Seshadri, Sudha %A Thomas H Mosley %A Bressler, Jan %A Lencz, Todd %A Ian J Deary %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Cognition %K Genetic Loci %K Genetic Predisposition to Disease %K Humans %K Mental Disorders %K Middle Aged %K Multifactorial Inheritance %K Neurodegenerative Diseases %K Neurodevelopmental Disorders %K Polymorphism, Single Nucleotide %K Reaction Time %K Young Adult %X

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

%B Nature Communications %V 9 %P 2098 %G eng %N 1 %R 10.1038/s41467-018-04362-x %0 Journal Article %J PLoS One %D 2017 %T Genetic variants specific to aging-related verbal memory: Insights from GWASs in a population-based cohort. %A Thalida E. Arpawong %A Pendleton, Neil %A Mekli, Krisztina %A John J McArdle %A Margaret Gatz %A Armoskus, Chris %A James A Knowles %A Carol A Prescott %K Cognitive Ability %K Genetics %K GWAS %K Memory %X Verbal memory is typically studied using immediate recall (IR) and delayed recall (DR) scores, although DR is dependent on IR capability. Separating these components may be useful for deciphering the genetic variation in age-related memory abilities. This study was conducted to (a) construct individual trajectories in IR and independent aspects of delayed recall, or residualized-DR (rDR), across older adulthood; and (b) identify genetic markers that contribute to four estimated phenotypes: IR and rDR levels and changes after age 60. A cognitively intact sample (N = 20,650 with 125,164 observations) was drawn from the U.S. Health and Retirement Study, a nationally representative study of adults aged 50 and older. Mixed effects regression models were constructed using repeated measures from data collected every two years (1996-2012) to estimate level at age 60 and change in memory post-60 in IR and rDR. Genome-wide association scans (GWAS) were conducted in the genotypic subsample (N = 7,486) using ~1.2 million single nucleotide polymorphisms (SNPs). One SNP (rs2075650) in TOMM40 associated with rDR level at the genome-wide level (p = 5.0x10-08), an effect that replicated in an independent sample from the English Longitudinal Study on Ageing (N = 6,898 with 41,328 observations). Meta-analysis of rDR level confirmed the association (p = 5.0x10-11) and identified two others in TOMM40 (rs71352238 p = 1.0x10-10; rs157582 p = 7.0x10-09), and one in APOE (rs769449 p = 3.1 x10-12). Meta-analysis of IR change identified associations with three of the same SNPs in TOMM40 (rs157582 p = 8.3x10-10; rs71352238 p = 1.9x10-09) and APOE (rs769449 p = 2.2x10-08). Conditional analyses indicate GWAS signals on rDR level were driven by APOE, whereas signals on IR change were driven by TOMM40. Additionally, we found that TOMM40 had effects independent of APOE e4 on both phenotypes. Findings from this first U.S. population-based GWAS study conducted on both age-related immediate and delayed verbal memory merit continued examination in other samples and additional measures of verbal memory. %B PLoS One %V 12 %P e0182448 %8 2017 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/28800603?dopt=Abstract %R 10.1371/journal.pone.0182448 %0 Journal Article %J Nature Communications %D 2017 %T Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity. %A Joshi, Peter K %A Nicola Pirastu %A Kentistou, Katherine A %A Fischer, Krista %A Edith Hofer %A Schraut, Katharina E %A Clark, David W %A Nutile, Teresa %A Barnes, Catriona L K %A Paul Rhj Timmers %A Shen, Xia %A Gandin, Ilaria %A McDaid, Aaron F %A Hansen, Thomas Folkmann %A Gordon, Scott D %A Giulianini, Franco %A Boutin, Thibaud S %A Abdellaoui, Abdel %A Zhao, Wei %A Medina-Gomez, Carolina %A Traci M Bartz %A Trompet, Stella %A Leslie A Lange %A Raffield, Laura %A van der Spek, Ashley %A Galesloot, Tessel E %A Proitsi, Petroula %A Yanek, Lisa R %A Bielak, Lawrence F %A Payton, Antony %A Murgia, Federico %A Concas, Maria Pina %A Biino, Ginevra %A Tajuddin, Salman M %A Seppälä, Ilkka %A Amin, Najaf %A Boerwinkle, Eric %A Børglum, Anders D %A Campbell, Archie %A Ellen W Demerath %A Demuth, Ilja %A Jessica Faul %A Ford, Ian %A Gialluisi, Alessandro %A Gögele, Martin %A Graff, Mariaelisa %A Aroon Hingorani %A Jouke-Jan Hottenga %A Hougaard, David M %A Hurme, Mikko A %A Ikram, M Arfan %A Jylhä, Marja %A Kuh, Diana %A Ligthart, Lannie %A Lill, Christina M %A Lindenberger, Ulman %A Lumley, Thomas %A Mägi, Reedik %A Marques-Vidal, Pedro %A Sarah E Medland %A Lili Milani %A Nagy, Reka %A William E R Ollier %A Peyser, Patricia A %A Pramstaller, Peter P %A Ridker, Paul M %A Fernando Rivadeneira %A Ruggiero, Daniela %A Saba, Yasaman %A Schmidt, Reinhold %A Schmidt, Helena %A Slagboom, P Eline %A Smith, Blair H %A Smith, Jennifer A %A Sotoodehnia, Nona %A Steinhagen-Thiessen, Elisabeth %A van Rooij, Frank J A %A Verbeek, André L %A Vermeulen, Sita H %A Vollenweider, Peter %A Wang, Yunpeng %A Werge, Thomas %A Whitfield, John B %A Alan B Zonderman %A Lehtimäki, Terho %A Michele K Evans %A Pirastu, Mario %A Fuchsberger, Christian %A Bertram, Lars %A Pendleton, Neil %A Sharon L R Kardia %A Ciullo, Marina %A Becker, Diane M %A Wong, Andrew %A Psaty, Bruce M %A Cornelia M van Duijn %A Wilson, James G %A Jukema, J Wouter %A Lambertus A Kiemeney %A André G Uitterlinden %A Franceschini, Nora %A Kari E North %A David R Weir %A Andres Metspalu %A Dorret I Boomsma %A Caroline Hayward %A Daniel I Chasman %A Nicholas G Martin %A Sattar, Naveed %A Campbell, Harry %A Tõnu Esko %A Kutalik, Zoltán %A James F Wilson %K Alleles %K Body Mass Index %K Coronary Disease %K Education %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K HLA-DQ alpha-Chains %K HLA-DRB1 Chains %K Humans %K Insulin Resistance %K Life Style %K Lipoprotein(a) %K Lipoproteins, HDL %K Longevity %K Lung Neoplasms %K Obesity %K Polymorphism, Single Nucleotide %K Smoking %K Socioeconomic factors %X

Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents' survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan.Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan.

%B Nature Communications %V 8 %P 910 %G eng %N 1 %R 10.1038/s41467-017-00934-5 %0 Journal Article %J Nature %D 2016 %T Genome-wide association study identifies 74 loci associated with educational attainment. %A Okbay, Aysu %A Jonathan P. Beauchamp %A Mark Alan Fontana %A Lee, James J %A Pers, Tune H %A Cornelius A Rietveld %A Turley, Patrick %A Chen, Guo-Bo %A Emilsson, Valur %A Meddens, S Fleur W %A Oskarsson, Sven %A Pickrell, Joseph K %A Thom, Kevin %A Pascal N Timshel %A de Vlaming, Ronald %A Abdel Abdellaoui %A Ahluwalia, Tarunveer S %A Bacelis, Jonas %A Baumbach, Clemens %A Bjornsdottir, Gyda %A Brandsma, Johannes H %A Maria Pina Concas %A Derringer, Jaime %A Furlotte, Nicholas A %A Galesloot, Tessel E %A Giorgia G Girotto %A Gupta, Richa %A Hall, Leanne M %A Sarah E Harris %A Edith Hofer %A Horikoshi, Momoko %A Huffman, Jennifer E %A Kaasik, Kadri %A Ioanna Panagiota Kalafati %A Karlsson, Robert %A Kong, Augustine %A Lahti, Jari %A Sven J van der Lee %A Christiaan de Leeuw %A Penelope A Lind %A Lindgren, Karl-Oskar %A Tian Liu %A Mangino, Massimo %A Marten, Jonathan %A Mihailov, Evelin %A Michael B Miller %A van der Most, Peter J %A Christopher J Oldmeadow %A Payton, Antony %A Pervjakova, Natalia %A Wouter J Peyrot %A Qian, Yong %A Olli T Raitakari %A Rueedi, Rico %A Salvi, Erika %A Schmidt, Börge %A Schraut, Katharina E %A Jianxin Shi %A Albert Vernon Smith %A Poot, Raymond A %A St Pourcain, Beate %A Teumer, Alexander %A Thorleifsson, Gudmar %A Verweij, Niek %A Vuckovic, Dragana %A Jürgen Wellmann %A Westra, Harm-Jan %A Yang, Jingyun %A Wei Zhao %A Zhihong Zhu %A Alizadeh, Behrooz Z %A Amin, Najaf %A Bakshi, Andrew %A Baumeister, Sebastian E %A Biino, Ginevra %A Bønnelykke, Klaus %A Patricia A. Boyle %A Campbell, Harry %A Cappuccio, Francesco P %A Gail Davies %A De Neve, Jan-Emmanuel %A Deloukas, Panos %A Demuth, Ilja %A Ding, Jun %A Eibich, Peter %A Eisele, Lewin %A Eklund, Niina %A Jessica Faul %A Feitosa, Mary F %A Andreas J Forstner %A Gandin, Ilaria %A Gunnarsson, Bjarni %A Halldórsson, Bjarni V %A Tamara B Harris %A Andrew C Heath %A Lynne J Hocking %A Holliday, Elizabeth G %A Homuth, Georg %A Horan, Michael A %A Jouke-Jan Hottenga %A Philip L de Jager %A Joshi, Peter K %A Jugessur, Astanand %A Marika A Kaakinen %A Kähönen, Mika %A Kanoni, Stavroula %A Keltigangas-Järvinen, Liisa %A Lambertus A Kiemeney %A Kolcic, Ivana %A Koskinen, Seppo %A Kraja, Aldi T %A Kroh, Martin %A Kutalik, Zoltán %A Latvala, Antti %A Lenore J Launer %A Lebreton, Maël P %A Douglas F Levinson %A Paul Lichtenstein %A Lichtner, Peter %A David C Liewald %A Loukola, Anu %A Pamela A F Madden %A Mägi, Reedik %A Mäki-Opas, Tomi %A Riccardo E Marioni %A Marques-Vidal, Pedro %A Meddens, Gerardus A %A McMahon, George %A Meisinger, Christa %A Meitinger, Thomas %A Milaneschi, Yusplitri %A Lili Milani %A Grant W Montgomery %A Myhre, Ronny %A Nelson, Christopher P %A Nyholt, Dale R %A William E R Ollier %A Aarno Palotie %A Paternoster, Lavinia %A Nancy L Pedersen %A Katja E Petrovic %A David J Porteous %A Katri Räikkönen %A Ring, Susan M %A Robino, Antonietta %A Rostapshova, Olga %A Rudan, Igor %A Rustichini, Aldo %A Veikko Salomaa %A Sanders, Alan R %A Sarin, Antti-Pekka %A Schmidt, Helena %A Rodney J Scott %A Smith, Blair H %A Jennifer A Smith %A Staessen, Jan A %A Steinhagen-Thiessen, Elisabeth %A Strauch, Konstantin %A Antonio Terracciano %A Tobin, Martin D %A Ulivi, Sheila %A Vaccargiu, Simona %A Quaye, Lydia %A van Rooij, Frank J A %A Venturini, Cristina %A Anna A E Vinkhuyzen %A Völker, Uwe %A Völzke, Henry %A Vonk, Judith M %A Vozzi, Diego %A Waage, Johannes %A Erin B Ware %A Gonneke Willemsen %A John R. Attia %A David A Bennett %A Klaus Berger %A Bertram, Lars %A Bisgaard, Hans %A Dorret I Boomsma %A Ingrid B Borecki %A Bültmann, Ute %A Chabris, Christopher F %A Francesco Cucca %A Cusi, Daniele %A Ian J Deary %A George Dedoussis %A Cornelia M van Duijn %A Johan G Eriksson %A Franke, Barbara %A Lude L Franke %A Paolo P. Gasparini %A Gejman, Pablo V %A Gieger, Christian %A Hans-Jörgen Grabe %A Gratten, Jacob %A Groenen, Patrick J F %A Gudnason, Vilmundur %A van der Harst, Pim %A Caroline Hayward %A Hinds, David A %A Hoffmann, Wolfgang %A Hyppönen, Elina %A Iacono, William G %A Jacobsson, Bo %A Järvelin, Marjo-Riitta %A Jöckel, Karl-Heinz %A Kaprio, Jaakko %A Sharon L R Kardia %A Lehtimäki, Terho %A Lehrer, Steven F %A Patrik K E Magnusson %A Nicholas G Martin %A McGue, Matt %A Andres Metspalu %A Pendleton, Neil %A Brenda W J H Penninx %A Markus Perola %A Nicola Pirastu %A Pirastu, Mario %A Polasek, Ozren %A Posthuma, Danielle %A Power, Christine %A Province, Michael A %A Nilesh J Samani %A Schlessinger, David %A Schmidt, Reinhold %A Thorkild I. A. Sørensen %A Timothy Spector %A Stefansson, Kari %A Thorsteinsdottir, Unnur %A A. Roy Thurik %A Nicholas J Timpson %A Henning Tiemeier %A Tung, Joyce Y %A André G Uitterlinden %A Vitart, Veronique %A Vollenweider, Peter %A David R Weir %A James F Wilson %A Alan F Wright %A Dalton C Conley %A Krueger, Robert F %A George Davey Smith %A Hofman, Albert %A David I Laibson %A Sarah E Medland %A Meyer, Michelle N %A Yang, Jian %A Johannesson, Magnus %A Peter M Visscher %A Tõnu Esko %A Philipp D Koellinger %A Cesarini, David %A Daniel J. Benjamin %K Alzheimer's disease %K Bipolar Disorder %K Cognitive Ability %K Education %K Fetus %K Genome-Wide Association Study %K Humans %K Molecular Sequence Annotation %K Polymorphism, Single Nucleotide %K Schizophrenia %K United Kingdom %X

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

%B Nature %V 533 %P 539-42 %8 2016 05 26 %G eng %N 7604 %1 http://www.ncbi.nlm.nih.gov/pubmed/27225129?dopt=Abstract %R 10.1038/nature17671