| Literature DB >> 32292824 |
Jianmin Li1, Ming Wen2, Zhiping Zhang3, Zhihua Qiu4, Yiming Sun5.
Abstract
Stroke is the major cause of death and disability worldwide. ABCA1 R219K has been suggested as a risk factor for ischemic stroke, but the results remain inconclusive in the Chinese population. This study aimed to assess the association between ABCA1 R219K and ischemic stroke using meta-analysis. A systematic literature search was conducted to select eligible studies and the pooled odds ratio (OR) with 95% confidence interval (CI) was used to evaluate the strength of association. Fourteen studies containing 2865 cases and 3227 controls were included in the meta-analysis and the results suggested that there is a strong association between ABCA1 R219K and the ischemic stroke risks (K vs. R: OR = 0.837, 95% CI: 0.735- 0.954, p=0.008; KK vs. RR: OR = 0.689, 95% CI: 0.520-0.912, p=0.009; KK+RK vs. RR: OR = 0.782, 95% CI: 0.691-0.885, p<0.001). Subgroup analysis revealed that significant association was found for the 4 genetic models (p<0.05) in the Southern population, while in the northern population significant association was only found under the dominant model (KK+RK vs. RR: OR = 0.744, 95% CI: 0.583- 0.949, p<0.017). This meta-analysis suggested that ABCA1 R219K polymorphism might be a protective factor against developing IS, indicating this SNP may contribute to the pathogenesis of ischemic stroke and might be potentially used as a biomarker to predict the susceptibility to ischemic stroke.Entities:
Keywords: ABCA1; Ischemic stroke; R219K; meta-analysis
Year: 2020 PMID: 32292824 PMCID: PMC7147290 DOI: 10.1515/med-2020-0039
Source DB: PubMed Journal: Open Med (Wars)
Figure 1The flow diagram of the selection process for the meta-analysis
Characteristics of included studies for the meta-analysis of R219K and ischemic stroke in Chinese population
| Case | Control | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Study | Region | N | RR | RK | KK | N | RR | RK | KK | Genotype | HWE(P) | Reference |
| Xiao 2004 | Hunan-South | 379 | 149 | 172 | 58 | 351 | 112 | 172 | 67 | PCR-RFLP | 0.9467478 | [ |
| Cui 2005 | Xi’An-North | 96 | 15 | 35 | 46 | 90 | 21 | 45 | 24 | PCR-RFLP | 0.9915804 | [ |
| Wang 2007a | Xinjiang-North | 58 | 19 | 35 | 4 | 60 | 14 | 36 | 10 | PCR-RFLP | 0.1116795 | [ |
| Wang 2007b | Xinjiang-North | 58 | 23 | 27 | 8 | 60 | 21 | 34 | 5 | PCR-RFLP | 0.0882217 | [ |
| Deng 2008 | Hunan-South | 109 | 30 | 60 | 19 | 339 | 110 | 168 | 61 | PCR-RFLP | 0.8208377 | [ |
| Zhang 2008 | Ningxia-North | 177 | 43 | 87 | 47 | 234 | 40 | 129 | 65 | PCR-RFLP | 0.0777884 | [ |
| Liu 2009 | Guangxi-South | 131 | 70 | 52 | 9 | 135 | 53 | 60 | 22 | PCR-RFLP | 0.4739363 | [ |
| Zhao 2010 | Hunan-South | 211 | 69 | 94 | 48 | 211 | 68 | 111 | 32 | PCR-RFLP | 0.2241758 | [ |
| Wang 2010 | Fujian-South | 324 | 107 | 172 | 45 | 152 | 41 | 77 | 34 | PCR-RFLP | 0.8502736 | [ |
| Yi 2011 | Guizhou-South | 240 | 45 | 109 | 86 | 240 | 36 | 97 | 107 | PCR-RFLP | 0.0770234 | [ |
| Xue 2012 | Fujian-South | 182 | 70 | 91 | 24 | 229 | 62 | 118 | 49 | PCR-RFLP | 0.6079555 | [ |
| Zhang 2012 | Ningxia-North | 105 | 30 | 63 | 12 | 257 | 63 | 125 | 69 | PCR-RFLP | 0.6685466 | [ |
| Zhou 2013 | Hunan-South | 279 | 98 | 128 | 53 | 351 | 112 | 172 | 67 | PCR-RFLP | 0.9467478 | [ |
| Cai 2014 | Hunan-South | 156 | 65 | 48 | 43 | 160 | 65 | 45 | 50 | PCR-RFLP | <0.0001 | [ |
| Sun 2015 | Shandong-North | 360 | 135 | 181 | 44 | 358 | 98 | 169 | 91 | PCR-RFLP | 0.2936262 | [ |
Meta-analysis on the association between ABCA1 R219K and ischemic stroke
| Publication bias (P) | ||||||
|---|---|---|---|---|---|---|
| Population | Genetic model | Pooled OR (95% CI) | P | Heterogeneity (P) | Begg’s | Egger’s |
| K vs. R | 0.837 (0.735, 0.954) | 0.008 | 0.000 | 0.784 | 0.495 | |
| KK vs. RK+RR | 0.772 (0.594, 1.003) | 0.053 | 0.000 | 0.784 | 0.915 | |
| Overall | KK vs. RR | 0.689 (0.520, 0.912) | 0.009 | 0.000 | 0.927 | 0.724 |
| KK+RK vs. RR | 0.782 (0.691, 0.885) | 0.000 | 0.294 | 0.649 | 0.170 | |
| K vs. R | 0.838 (0.734, 0.957) | 0.009 | 0.031 | 0.297 | 0.839 | |
| KK vs. RK+RR | 0.786 (0.619, 0.996) | 0.046 | 0.025 | 1.000 | 0.797 | |
| South | KK vs. RR | 0.718 (0.544, 0.949) | 0.020 | 0.021 | 0.532 | 0.754 |
| KK+RK vs. RR | 0.803 (0.693, 0.932) | 0.004 | 0.304 | 1.000 | 0.640 | |
| K vs. R | 0.856 (0.632, 1.158) | 0.313 | 0.000 | 0.188 | 0.304 | |
| KK vs. RK+RR | 0.773 (0.396, 1.510) | 0.451 | 0.000 | 0.573 | 0.614 | |
| North | KK vs. RR | 0.666 (0.342, 1.296) | 0.232 | 0.000 | 0.348 | 0.423 |
| KK+RK vs. RR | 0.744 (0.583, 0.949) | 0.017 | 0.287 | 0.348 | 0.258 | |
| K vs. R | 0.833 (0.725, 0.957) | 0.010 | 0.000 | 0.288 | 0.220 | |
| HWE | KK vs. RK+RR | 0.767 (0.578, 1.017) | 0.066 | 0.000 | 0.757 | 0.884 |
| KK vs. RR | 0.677 (0.500, 0.915) | 0.011 | 0.000 | 0.918 | 0.686 | |
| KK+RK vs. RR | 0.771 (0.677, 0.878) | 0.000 | 0.280 | 0.757 | 0.193 | |
Figure 2Forest plot of ORs for the association between ABCA1 R219K and ischemic stroke risk under the dominant model (KK+RK vs. RR, stratified by population region). The circle and horizontal lines represent the OR and 95 % CI and the area of the squares reflect the weight of individual studies included in the meta-analysis. The diamonds represent the pooled ORs and 95 % CI.
Figure 3Sensitivity analysis for the association between ABCA1 R219K and ischemic stroke for the included studies.
Figure 4Begg’s funnel plot for association between ABCA1 R219K and ischemic stroke.