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Meta-Analysis
. 2018 May 29;9(1):2098.
doi: 10.1038/s41467-018-04362-x.

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Gail Davies  1 Max Lam  2 Sarah E Harris  1   3 Joey W Trampush  4   5 Michelle Luciano  1 W David Hill  1 Saskia P Hagenaars  1   6 Stuart J Ritchie  1 Riccardo E Marioni  1   3 Chloe Fawns-Ritchie  1 David C M Liewald  1 Judith A Okely  1 Ari V Ahola-Olli  7   8 Catriona L K Barnes  9 Lars Bertram  10 Joshua C Bis  11 Katherine E Burdick  12   13   14 Andrea Christoforou  15   16 Pamela DeRosse  2   17 Srdjan Djurovic  15   18 Thomas Espeseth  19   20 Stella Giakoumaki  21 Sudheer Giddaluru  15   16 Daniel E Gustavson  22   23 Caroline Hayward  24   25 Edith Hofer  26   27 M Arfan Ikram  28   29   30 Robert Karlsson  31 Emma Knowles  32 Jari Lahti  33   34 Markus Leber  35 Shuo Li  36 Karen A Mather  37 Ingrid Melle  15   19 Derek Morris  38 Christopher Oldmeadow  39 Teemu Palviainen  40 Antony Payton  41 Raha Pazoki  42 Katja Petrovic  26 Chandra A Reynolds  43 Muralidharan Sargurupremraj  44 Markus Scholz  45   46 Jennifer A Smith  47   48 Albert V Smith  49   50 Natalie Terzikhan  28   51 Anbupalam Thalamuthu  37 Stella Trompet  52 Sven J van der Lee  28 Erin B Ware  48 B Gwen Windham  53 Margaret J Wright  54   55 Jingyun Yang  56   57 Jin Yu  17 David Ames  58   59 Najaf Amin  28 Philippe Amouyel  60 Ole A Andreassen  19   61 Nicola J Armstrong  62 Amelia A Assareh  37 John R Attia  63 Deborah Attix  64   65 Dimitrios Avramopoulos  66   67 David A Bennett  56   57 Anne C Böhmer  68   69 Patricia A Boyle  56   70 Henry Brodaty  37   71 Harry Campbell  9 Tyrone D Cannon  72 Elizabeth T Cirulli  73 Eliza Congdon  74 Emily Drabant Conley  75 Janie Corley  1 Simon R Cox  1 Anders M Dale  22   76   77   78 Abbas Dehghan  42   79 Danielle Dick  80 Dwight Dickinson  81 Johan G Eriksson  82   83   84   85 Evangelos Evangelou  42   82 Jessica D Faul  48 Ian Ford  86 Nelson A Freimer  74 He Gao  42 Ina Giegling  87 Nathan A Gillespie  88 Scott D Gordon  89 Rebecca F Gottesman  90   91 Michael E Griswold  92 Vilmundur Gudnason  49   50 Tamara B Harris  93 Annette M Hartmann  87 Alex Hatzimanolis  94   95   96 Gerardo Heiss  97 Elizabeth G Holliday  63 Peter K Joshi  9 Mika Kähönen  98   99   100 Sharon L R Kardia  47 Ida Karlsson  31 Luca Kleineidam  101   102   103   104 David S Knopman  105 Nicole A Kochan  37   106 Bettina Konte  87 John B Kwok  107   108 Stephanie Le Hellard  15   16 Teresa Lee  37   106 Terho Lehtimäki  109   110 Shu-Chen Li  111   112 Christina M Lill  113 Tian Liu  10   111 Marisa Koini  26 Edythe London  74 Will T Longstreth Jr  114   115 Oscar L Lopez  116 Anu Loukola  40 Tobias Luck  46   117 Astri J Lundervold  118   119 Anders Lundquist  120   121 Leo-Pekka Lyytikäinen  109   110 Nicholas G Martin  89 Grant W Montgomery  89   122 Alison D Murray  25   123 Anna C Need  124 Raymond Noordam  52 Lars Nyberg  120   125   126 William Ollier  127 Goran Papenberg  111   128 Alison Pattie  129 Ozren Polasek  130   131 Russell A Poldrack  132 Bruce M Psaty  11   133   134 Simone Reppermund  37   135 Steffi G Riedel-Heller  117 Richard J Rose  136 Jerome I Rotter  137   138 Panos Roussos  12   139   140 Suvi P Rovio  7 Yasaman Saba  141 Fred W Sabb  142 Perminder S Sachdev  37   106 Claudia L Satizabal  143   144 Matthias Schmid  145 Rodney J Scott  63 Matthew A Scult  146 Jeannette Simino  92 P Eline Slagboom  147 Nikolaos Smyrnis  94   95 Aïcha Soumaré  44 Nikos C Stefanis  94   95   96 David J Stott  148 Richard E Straub  149 Kjetil Sundet  19   20 Adele M Taylor  129 Kent D Taylor  137   138 Ioanna Tzoulaki  42   79   150 Christophe Tzourio  44   151 André Uitterlinden  28   152 Veronique Vitart  24 Aristotle N Voineskos  153 Jaakko Kaprio  40   82   154 Michael Wagner  103   104 Holger Wagner  102 Leonie Weinhold  145 K Hoyan Wen  28 Elisabeth Widen  40 Qiong Yang  36 Wei Zhao  47 Hieab H H Adams  28   155 Dan E Arking  67 Robert M Bilder  74 Panos Bitsios  156 Eric Boerwinkle  157   158 Ornit Chiba-Falek  64 Aiden Corvin  159 Philip L De Jager  160   161 Stéphanie Debette  44   162 Gary Donohoe  38 Paul Elliott  42   79 Annette L Fitzpatrick  115   163 Michael Gill  159 David C Glahn  32 Sara Hägg  31 Narelle K Hansell  54 Ahmad R Hariri  146 M Kamran Ikram  28   30 J Wouter Jukema  164 Eero Vuoksimaa  40   154 Matthew C Keller  165 William S Kremen  22   23 Lenore Launer  93 Ulman Lindenberger  111 Aarno Palotie  40   166   167 Nancy L Pedersen  31 Neil Pendleton  168 David J Porteous  1   3   25 Katri Räikkönen  33 Olli T Raitakari  7   169 Alfredo Ramirez  35   68   102 Ivar Reinvang  20 Igor Rudan  9 Dan Rujescu  87 Reinhold Schmidt  26 Helena Schmidt  141 Peter W Schofield  170 Peter R Schofield  171   172 John M Starr  1   173 Vidar M Steen  15   16 Julian N Trollor  37   135 Steven T Turner  174 Cornelia M Van Duijn  28 Arno Villringer  175   176 Daniel R Weinberger  149 David R Weir  48 James F Wilson  9   24 Anil Malhotra  17   177   178 Andrew M McIntosh  1   179 Catharine R Gale  1   180 Sudha Seshadri  142   143   181 Thomas H Mosley Jr  53 Jan Bressler  157 Todd Lencz  17   179 Ian J Deary  182
Affiliations
Meta-Analysis

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Gail Davies et al. Nat Commun. .

Erratum in

  • Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.
    Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill WD, Hagenaars SP, Ritchie SJ, Marioni RE, Fawns-Ritchie C, Liewald DCM, Okely JA, Ahola-Olli AV, Barnes CLK, Bertram L, Bis JC, Burdick KE, Christoforou A, DeRosse P, Djurovic S, Espeseth T, Giakoumaki S, Giddaluru S, Gustavson DE, Hayward C, Hofer E, Ikram MA, Karlsson R, Knowles E, Lahti J, Leber M, Li S, Mather KA, Melle I, Morris D, Oldmeadow C, Palviainen T, Payton A, Pazoki R, Petrovic K, Reynolds CA, Sargurupremraj M, Scholz M, Smith JA, Smith AV, Terzikhan N, Thalamuthu A, Trompet S, van der Lee SJ, Ware EB, Windham BG, Wright MJ, Yang J, Yu J, Ames D, Amin N, Amouyel P, Andreassen OA, Armstrong NJ, Assareh AA, Attia JR, Attix D, Avramopoulos D, Bennett DA, Böhmer AC, Boyle PA, Brodaty H, Campbell H, Cannon TD, Cirulli ET, Congdon E, Conley ED, Corley J, Cox SR, Dale AM, Dehghan A, Dick D, Dickinson D, Eriksson JG, Evangelou E, Faul JD, Ford I, Freimer NA, Gao H, Giegling I, Gillespie NA, Gordon SD, Gottesman RF, Griswold ME, Gudnason V, Harris TB, Hartmann AM, Hatzimanolis A, Heiss G, Holliday EG, Joshi PK, Kähönen M, Kardia SLR, Karlsson I, Kleineidam L, Knopman DS, Kochan NA, Konte B, Kwok JB, Le Hellard S, Lee T,… See abstract for full author list ➔ Davies G, et al. Nat Commun. 2019 May 1;10(1):2068. doi: 10.1038/s41467-019-10160-w. Nat Commun. 2019. PMID: 31043617 Free PMC article.

Abstract

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 × 10-8) 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.

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Conflict of interest statement

A.M.D. is a Founder of and holds equity in CorTechs Labs, Inc., and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc., and receives funding through research agreements with General Electric Healthcare and Medtronic, Inc. The terms of these arrangements have been reviewed and approved by UCSD in accordance with its conflict of interest policies. B.M.P. serves on a DSMB for a clinical trial of a device funded by the manufacturer (Zoll LifeCor), and on the steering committee of the Yale Open Data Access Project funded by Johnson & Johnson. I.J.D. is a participant in UK Biobank. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The hierarchical model of cognitive function variance. At level 1, individuals differ in specific tests that assess the various cognitive domains. Scores on all the tests correlate positively. It is found that there are especially strong correlations among the tests of the same domain, so a latent trait at the domain level can be extracted to represent this common variance. It is then found that individuals who do well in one domain also tend to do well in the other domains, so a general cognitive latent trait called g can be extracted. This model allows researchers to partition cognitive performance variance into these different levels. They can then explore the causes and consequences of variance at different levels of cognitive specificity-generality. For example, there are genetic and ageing effects on g and on some specific domains, such as memory and speed of processing. Note that the specific-test-level variance contains variation in the performance of skills that are specific to the individual test and also contains error variance. (Reproduced, with permission, from ref. )
Fig. 2
Fig. 2
Association results for general cognitive function. SNP-based (a) and gene-based (b) association results in 300,486 individuals. The red line indicates the threshold for genome-wide significance: P < 5 × 10−8 for (a), P < 2.75 × 10−6 for (b); the blue line in (a) indicates the threshold for suggestive significance: P < 1 × 10−5
Fig. 3
Fig. 3
Functional analyses of general cognitive function. Analyses include general cognitive function-associated SNPs, independent significant SNPs, and all SNPs in LD with independent significant SNPs. Functional consequences of SNPs on genes (a) indicated by functional annotation assigned by ANNOVAR. MAGMA gene-property analysis results; results are shown for average expression of 30 general tissue types (b) and 53 specific tissue types (c). The dotted line indicates the Bonferroni-corrected α level
Fig. 4
Fig. 4
Association results for reaction time. SNP-based (a) and gene-based (b) association results in 330,069 individuals. The red line indicates the threshold for genome-wide significance: P < 5 × 10−8 for (a), P < 2.75 × 10−6 for (b); the blue line in (a) indicates the threshold for suggestive significance: P < 1 × 10−5
Fig. 5
Fig. 5
Functional analyses of reaction time. Analyses include reaction time-associated SNPs, independent significant SNPs, and all SNPs in LD with independent significant SNPs. Functional consequences of SNPs on genes (a) indicated by functional annotation assigned by ANNOVAR. MAGMA gene-property analysis results; results are shown for average expression of 30 general tissue types (b) and 53 specific tissue types (c). The dotted line indicates the Bonferroni-corrected α level

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