| Title |
Association of three-gene interaction among MTHFR, ALOX5AP and NOTCH3 with thrombotic stroke: a multicenter case–control study
|
|---|---|
| Published in |
Human Genetics, April 2009
|
| DOI | 10.1007/s00439-009-0659-0 |
| Pubmed ID | |
| Authors |
Junhao Liu, Kai Sun, Yongyi Bai, Weili Zhang, Xiaojian Wang, Yibo Wang, Hu Wang, Jingzhou Chen, Xiaodong Song, Ying Xin, Zhe Liu, Rutai Hui |
| Abstract |
Stroke is a common complex trait and does not follow Mendelian pattern of inheritance. Gene-gene or gene-environment interactions may be responsible for the complex trait. How the interactions contribute to stroke is still under research. This study aimed to explore the association between gene-gene interactions and stroke in Chinese in a large case-control study. Nearly 4,000 participants were recruited from seven clinical centers. Eight variants in five candidate genes were examined for stroke risk. Gene-gene interactions were explored by using Generalized Multifactor Dimensionality Reduction (GMDR). A significant gene-gene interaction was found by GMDR. The best model including MTHFR C677T, ALOX5AP T2354A and NOTCH3 C381T scored 10 for Cross-Validation Consistency and 9 for Sign Test (P = 0.0107). The individuals with combination of MTHFR 677TT, ALOX5AP 2354AA and NOTCH3 381TT/TC had a significantly higher risk of thrombotic stroke (OR 3.165, 95% CI 1.461-6.858, P = 0.003). Our results show that combination of these alleles conferred higher risk for stroke than single risk allele. The gene-gene interaction may serve as a novel area for stroke research. The three-locus combination may change the susceptibility of particular subjects to the disease. |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Germany | 1 | 4% |
| Italy | 1 | 4% |
| Korea, Republic of | 1 | 4% |
| Unknown | 24 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 18% |
| Student > Bachelor | 5 | 18% |
| Researcher | 4 | 14% |
| Professor > Associate Professor | 3 | 11% |
| Student > Master | 3 | 11% |
| Other | 7 | 25% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 36% |
| Agricultural and Biological Sciences | 7 | 25% |
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Mathematics | 2 | 7% |
| Psychology | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 3 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 20 April 2010.
All research outputs
#7,453,479
of 22,786,691 outputs
Outputs from Human Genetics
#933
of 2,953 outputs
Outputs of similar age
#32,615
of 93,234 outputs
Outputs of similar age from Human Genetics
#9
of 12 outputs
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