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Whole genome association scan for genetic polymorphisms influencing information processing speed |
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| Authors: | Luciano Michelle Hansell Narelle K Lahti Jari Davies Gail Medland Sarah E Räikkönen Katri Tenesa Albert Widen Elisabeth McGhee Kevin A Palotie Aarno Liewald David Porteous David J Starr John M Montgomery Grant W Martin Nicholas G Eriksson Johan G Wright Margaret J Deary Ian J |
| Institution: | a Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Scotland, UK b Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia c Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland d MRC Human Genetics Unit, The Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK e Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland f Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK g Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland h University of Edinburgh Molecular Medicine Centre, Western General Hospital, Edinburgh, UK i Department of Geriatric Medicine, University of Edinburgh, Royal Victoria Hospital, UK j National Institute for Health and Welfare, Finland k Department of General Practice and Primary Health Care, University of Helsinki, Finland l Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland m Folkhalsan Research Centre, Helsinki, Finland n Vasa Central Hospital, Vasa, Finland |
| Abstract: | Processing speed is an important cognitive function that is compromised in psychiatric illness (e.g., schizophrenia, depression) and old age; it shares genetic background with complex cognition (e.g., working memory, reasoning). To find genes influencing speed we performed a genome-wide association scan in up to three cohorts: Brisbane (mean age 16 years; N = 1659); LBC1936 (mean age 70 years, N = 992); LBC1921 (mean age 82 years, N = 307), and; HBCS (mean age 64 years, N = 1080). Meta-analysis of the common measures highlighted various suggestively significant (p < 1.21 × 10−5) SNPs and plausible candidate genes (e.g., TRIB3). A biological pathways analysis of the speed factor identified two common pathways from the KEGG database (cell junction, focal adhesion) in two cohorts, while a pathway analysis linked to the GO database revealed common pathways across pairs of speed measures (e.g., receptor binding, cellular metabolic process). These highlighted genes and pathways will be able to inform future research, including results for psychiatric disease. |
| Keywords: | Information processing speed Cognitive ability Genes Biological pathways |
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