Examining non-syndromic autosomal recessive intellectual disability (NS-ARID) genes for an enriched association with intelligence differences

W. D. Hill, G. Davies, D. C. Liewald, A. Payton, C. J. McNeil, L. J. Whalley, M. Horan, W. Ollier, J. M. Starr, N. Pendleton, N. K. Hansel, G. W. Montgomery, S. E. Medland, N. G. Martin, M. J. Wright, T. C. Bates, I. J. Deary

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Two themes are emerging regarding the molecular genetic aetiology of intelligence. The first is that intelligence is influenced by many variants and those that are tagged by common single nucleotide polymorphisms account for around 30% of the phenotypic variation. The second, in line with other polygenic traits such as height and schizophrenia, is that these variants are not randomly distributed across the genome but cluster in genes that work together. Less clear is whether the very low range of cognitive ability (intellectual disability) is simply one end of the normal distribution describing individual differences in cognitive ability across a population. Here, we examined 40 genes with a known association with non-syndromic autosomal recessive intellectual disability (NS-ARID) to determine if they are enriched for common variants associated with the normal range of intelligence differences. The current study used the 3511 individuals of the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium. In addition, a text mining analysis was used to identify gene sets biologically related to the NS-ARID set. Gene-based tests indicated that genes implicated in NS-ARID were not significantly enriched for quantitative trait loci (QTL) associated with intelligence. These findings suggest that genes in which mutations can have a large and deleterious effect on intelligence are not associated with variation across the range of intelligence differences.

Original languageEnglish
Pages (from-to)80-89
Number of pages10
Early online date17 Dec 2015
Publication statusPublished - Jan 2016

Bibliographical note

We thank the cohort participants who contributed to these studies and the research staff who collected phenotypic data. Genotyping of the CAGES cohorts and the analyses conducted here were supported by the UK's Biotechnology and Biological Sciences Research Council (BBSRC). Phenotype collection in the Lothian Birth Cohort 1921 was supported by the BBSRC, The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Research Into Ageing (continues as part of Age UK's The Disconnected Mind project). Phenotype collection in the Aberdeen Birth Cohort 1936 was supported by BBSRC, the Wellcome Trust and Alzheimer's Research UK. Phenotype collection in the Manchester and Newcastle Longitudinal Studies of Cognitive Ageing cohorts was supported by Social Science Research Council, Medical Research Council, Economic and Social Research Council, Research Into Ageing, Wellcome Trust and Unilever plc. The work was undertaken in The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1). Funding from the BBSRC, EPSRC, ESRC and MRC is gratefully acknowledged.

Authors MJ Wright, N K Hansell, SE Medland, NG Martin, and GW Montgomery would like to acknowledge and thank their twin sample for their participation; the Australian Research Council (ARC) for supporting data collection (A7960034, A79906588, A79801419, DP0212016, DP0343921, DP0664638, DP1093900), and the National Health & Medical Research Council (NHMRC) for funding genotyping (Medical Bioinformatics Genomics Proteomics Programme, 389891). SE Medland is supported by an ARC Future Fellowship. Statistical analyses were carried out on the GenEpi Cluster which is financially supported by contributions from grants from the NHMRC (389892;496682;496688;496739;613672) and ARC (FT0991022;FT0991360).


  • Gene set analysis
  • Genetics
  • GWAS
  • Intellectual disabilities


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