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1	The trans-ancestral genomic architecture of glycemic traits
	Chen, J; Spracklen, CN; Marenne, G. - : Nature Research, 2021
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2	The trans-ancestral genomic architecture of glycemic traits.
	Chen, J; Spracklen, CN; Marenne, G. - 2021
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3	Genetic contributions to variation in general cognitive function: A meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)
	Davies, G; Armstrong, N; Bis, JC; Bressler, J; Chouraki, V; Giddaluru, S; Hofer, E; Ibrahim-Verbaas, CA; Kirin, M; Lahti, J; Van Der Lee, SJ; Le Hellard, S; Liu, T; Marioni, RE; Oldmeadow, C; Postmus, I; Smith, AV; Smith, JA; Thalamuthu, A; Thomson, R; Vitart, V; Wang, J; Yu, L; Zgaga, L; Zhao, W; Boxall, R; Harris, SE; Hill, WD; Liewald, DC; Luciano, M; Adams, H; Ames, D; Amin, N; Amouyel, P; Assareh, AA; Au, R; Becker, JT; Beiser, A; Berr, C; Bertram, L; Boerwinkle, E; Buckley, BM; Campbell, H; Corley, J; De Jager, PL; Dufouil, C; Eriksson, JG; Espeseth, T; Faul, JD; Ford, I; Scotland, G; Gottesman, RF; Griswold, ME; Gudnason, V; Harris, TB; Heiss, G; Hofman, A; Holliday, EG; Huffman, J; Kardia, SLR; Kochan, N; Knopman, DS; Kwok, JB; Lambert, JC; Lee, T; Li, G; Li, SC; Loitfelder, M; Lopez, OL; Lundervold, AJ; Lundqvist, A; Mather, KA; Mirza, SS; Nyberg, L; Oostra, BA; Palotie, A; Papenberg, G; Pattie, A; Petrovic, K; Polasek, O; Psaty, BM; Redmond, P; Reppermund, S; Rotter, JI; Schmidt, H; Schuur, M; Schofield, PW; Scott, RJ; Steen, VM; Stott, DJ; Van Swieten, JC; Taylor, KD; Trollor, J; Trompet, S; Uitterlinden, AG; Weinstein, G; Widen, E; Windham, BG; Jukema, JW; Wright, AF. - 2015
	Abstract: General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10-9, MIR2113; rs17522122, P=2.55 × 10-8, AKAP6; rs10119, P=5.67 × 10-9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10-6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ∼1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10-17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C.
	Keyword: 06 Biological Sciences; 11 Medical and Health Sciences; 17 Psychology and Cognitive Sciences
	URL: https://doi.org/10.1038/mp.2014.188 http://handle.unsw.edu.au/1959.4/unsworks_13655
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