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Simple Search
Hits 1 – 4 of 4
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
The trans-ancestral genomic architecture of glycemic traits.
Chen, J.
;
Spracklen, C.N.
;
Marenne, G.
...
In: Nature genetics, vol. 53, no. 6, pp. 840-860 (2021)
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4
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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