| Title |
A genome-wide association study of cognitive function in Chinese adult twins
|
|---|---|
| Published in |
Biogerontology, August 2017
|
| DOI | 10.1007/s10522-017-9725-5 |
| Pubmed ID | |
| Authors |
Chunsheng Xu, Dongfeng Zhang, Yili Wu, Xiaocao Tian, Zengchang Pang, Shuxia Li, Qihua Tan |
| Abstract |
Multiple loci or genes have been identified using genome-wide association studies mainly in western countries but with inconsistent results. No similar studies have been conducted in the world's largest and rapidly aging Chinese population. The paper aimed to identify the specific genetic variants associated with cognitive function in middle and old-aged Chinese dizygotic twins (DZ). Cognitive function was measured on 139 pairs of DZ by Montreal Cognitive Assessment. The subjects were genotyped at 1048575 SNP positions. Regression-based mixed-effect kinship model of GWAS was conducted to test the SNPs. Gene-based analysis was performed on VEGAS2. The statistically significant genes were then subject to gene set enrichment analysis to further identify the specific biological pathways associated with cognitive function. No SNPs reached genome-wide significance although there were 13 SNPs of suggestive significance (P < 10(-5)). Gene-based analysis found 823 significant genes topped by TNRC18P1 (P = 1.00 × 10(-6)), FGFR1OP2 (P = 6.00 × 10(-6)), and AKR1D1 (P = 2.30 × 10(-5)). Enrichment analysis identified 46 biological pathways, mainly involving in signaling transmission, metabolic process and Alzheimer's disease. Analysis of SNPs involved in the regulatory motif detected cell-type specific enhancers involving aorta and colon smooth muscle both have been reported to implicate in cognition. We conclude that genetic variations are significantly involved in functional genes, biological pathways and the regulatory domain that mediate cognitive performances. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 19% |
| Researcher | 5 | 16% |
| Student > Doctoral Student | 3 | 10% |
| Student > Ph. D. Student | 3 | 10% |
| Student > Master | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 9 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 19% |
| Agricultural and Biological Sciences | 4 | 13% |
| Medicine and Dentistry | 2 | 6% |
| Neuroscience | 2 | 6% |
| Chemical Engineering | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 12 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 August 2017.
All research outputs
#17,911,821
of 22,997,544 outputs
Outputs from Biogerontology
#480
of 659 outputs
Outputs of similar age
#227,805
of 317,683 outputs
Outputs of similar age from Biogerontology
#7
of 9 outputs
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