Edinburgh Research Explorer

GWAS-based pathway analysis differentiates between fluid and crystallized intelligence

Research output: Contribution to journalArticle

  • Andrea Christoforou
  • Thomas Espeseth
  • Gail Davies
  • Carla P D Fernandes
  • Sudheer Giddaluru
  • Manuel Mattheisen
  • David C Liewald
  • Antony Payton
  • William Ollier
  • Michael Horan
  • Neil Pendleton
  • Paul Haggarty
  • Srdjan Djurovic
  • Stefan Herms
  • Per Hoffman
  • Sven Cichon
  • Astri Lundervold
  • Ivar Reinvang
  • Vidar M Steen
  • Stephanie Le Hellard

Related Edinburgh Organisations

Access status

Open

Documents

  • Download as Adobe PDF

    Rights statement: This is a copy of an accepted unedited manuscript.

    Accepted author manuscript, 776 KB, PDF-document

http://onlinelibrary.wiley.com/doi/10.1111/gbb.12152/abstract
Original languageEnglish
Pages (from-to)663-674
JournalGenes Brain and Behavior
Volume13
Issue number7
Early online date28 Jun 2014
DOIs
StatePublished - 28 Jun 2014

Abstract

Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status, and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation.

Download statistics

No data available

ID: 16356217