| Literature DB >> 25869804 |
D A Bennett1, I J Deary2,3, M A Ikram4,5,6,7, L J Launer8, A L Fitzpatrick9, S Seshadri10,11, C M van Duijn12,6, T H Mosley13, C A Ibrahim-Verbaas12,4,14, J Bressler15,14, S Debette10,16,17,14, M Schuur12,4,14, A V Smith18,19,14, J C Bis20,14, G Davies2,14, S Trompet21,22, J A Smith23, C Wolf24, L B Chibnik25, Y Liu26, V Vitart27, M Kirin28, K Petrovic29, O Polasek30, L Zgaga31, C Fawns-Ritchie2, P Hoffmann32,33,34, J Karjalainen35, J Lahti36,37, D J Llewellyn38, C O Schmidt39, K A Mather40, V Chouraki41, Q Sun42, S M Resnick43, L M Rose44, C Oldmeadow45, M Stewart28, B H Smith46, V Gudnason18,19, Q Yang11,47, S S Mirza5,6, J W Jukema21, P L deJager25, T B Harris8, D C Liewald2,3, N Amin12, L H Coker48, O Stegle49, O L Lopez50, R Schmidt29, A Teumer51, I Ford52, N Karbalai24, J T Becker50,53,54, M K Jonsdottir55, R Au10,11, Rsn Fehrmann35, S Herms33,34, M Nalls56, W Zhao23, S T Turner57, K Yaffe58, K Lohman26, J C van Swieten4, Slr Kardia23, D S Knopman59, W M Meeks60, G Heiss61, E G Holliday45, P W Schofield62, T Tanaka63, D J Stott64, J Wang47, P Ridker44, A J Gow2,3, A Pattie2, J M Starr2,65, L J Hocking66, N J Armstrong40,67,68, S McLachlan28, J M Shulman69,70, L C Pilling71, G Eiriksdottir18, R J Scott45, N A Kochan40,72, A Palotie73,74,75, Y-C Hsieh76, J G Eriksson37,77,78,79,80, A Penman81, R F Gottesman82, B A Oostra12, L Yu1, A L DeStefano10,11,47, A Beiser10,11,47, M Garcia8, J I Rotter83,84,85, M M Nöthen34,86, A Hofman5,6, P E Slagboom87, Rgj Westendorp88, B M Buckley89, P A Wolf10,11, A G Uitterlinden5,6,90, B M Psaty20,9,91,92, H J Grabe93, S Bandinelli14, D I Chasman44, F Grodstein42, K Räikkönen36, J-C Lambert41, D J Porteous94, J F Price28, P S Sachdev40,72, L Ferrucci63, J R Attia45, I Rudan28, C Hayward27, A F Wright27, J F Wilson28, S Cichon33,34,95, L Franke35, H Schmidt29, J Ding96, Ajm de Craen22, M Fornage97.
Abstract
To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.Entities:
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Year: 2015 PMID： 25869804 PMCID： PMC4722802 DOI： 10.1038/mp.2015.37
Source DB: PubMed Journal: Mol Psychiatry ISSN： 1359-4184 Impact factor: 15.992