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DNA markers associated with general and specific cognitive abilities
Authors:Stephen A. Petrill  Robert PlominGerald E. McClearn   Deborah L. Smith  Sylvia VignettiMichael J. Chorney  Karen ChorneyLee A. Thompson  Douglas K. DettermanCamilla Benbow  David LubinskiJoanna Daniels   Michael J. Owen  Peter McGuffin
Affiliation:Social, Genetic, and Development Psychiatry Research Centre Institute of Psychiatry, London, UK;Pennsylvania State University, USA;Milton S. Hershey Medical Center Pennsylvania State University, USA;Case Western Reserve University, USA;Iowa State University, USA;University of Wales College of Medicine, UK
Abstract:Multivariate quantitative genetic research suggests a hierarchical model of cognitive abilities where genetic effects are largely general, cutting across most cognitive abilities. Some genetic effects, however, are specific to certain cognitive abilities. These results lead to a hypothesis for molecular genetic research: Although most genes associated with one cognitive ability will be related to other cognitive abilities, some genes will be specific to a particular cognitive ability. The current research explored this hypothesis in an analysis of data in specific cognitive abilities from 86 children from 6 to 12 years of age from a larger allelic association study of general cognitive ability. Eight DNA markers were entered simultaneously in separate multiple regression analyses predicting each of four specific cognitive ability factors (Verbal, Spatial, Perceptual Speed, Memory), as well as WISC-R subtest scores. Four marjers (CTGB33, EST00083, HLA, and SOD2) showed similar effects across the cognitive ability scales, suggesting that they are related to general cognitive ability (g). These associations became negligible when the effects of ‘g’ (WISC-R IQ) were removed. Three markers (ADH5, DM, and NGFB) continued to be significantly associated with specific cognitive ability scales after the effects of ‘g’ were removed. Although preliminary, these molecular genetic results support the hierarchical model predicted by quantitative genetic research.
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