Startseite Relationship between CRP gene polymorphisms and ischemic stroke risk: A systematic review and meta-analysis
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Relationship between CRP gene polymorphisms and ischemic stroke risk: A systematic review and meta-analysis

  • Zhizhi Chen , Feifei Jiang , Ming Yang und Jie Yang EMAIL logo
Veröffentlicht/Copyright: 16. November 2022
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Open Life Sciences
Aus der Zeitschrift Open Life Sciences Band 17 Heft 1

Abstract

Ischemic stroke (IS), usually caused due to an abrupt blockage of an artery, is the leading cause of disability and the second leading cause of death worldwide. The association of the C-reactive protein (CRP) gene (s3093059 T/C and rs1205 C/T) polymorphisms and IS susceptibility has been widely studied, but the results remain inconsistent. Our study aimed to assess the association between CRP gene (s3093059 T/C and rs1205 C/T) polymorphisms and IS risk. PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, and WanFang databases were searched up to April 2022 to identify eligible studies. The Newcastle-Ottawa scale (NOS) score was calculated to assess study quality. The odd ratios (ORs) with a 95% confidence interval (CI) were calculated to assess the association between CRP gene (rs3093059 T/C and rs1205 C/T) polymorphisms and IS risk. Eighteen case–control studies with 6339 cases and 29580 controls were identified. We found that CRP (s3093059 T/C and rs1205 C/T) polymorphism was not significantly associated with the risk of IS in any genetic model (recessive model: OR 1.00, 95% CI 0.79–1.26; OR 1.06, 95% CI 0.90–1.25). When stratified analysis by country, genotype method, source of controls, and NOS score, still no statistically significant association was found. Our study indicated that the CRP (rs3093059 T/C and rs1205 C/T) polymorphisms were not associated with the susceptibility to IS.

Keywords: ischemic stroke; C-reactive protein; polymorphism; meta-analysis

1 Introduction

Ischemic stroke (IS) is the more common type and is regarded as the leading cause of death, physical disability, and cognitive decline worldwide [1]. With the global population aged 65 and over growing faster than all other age groups, the incidence of stroke is also increasing. Accordingly, early accurate identification of modifiable risk factors and management of the people potentially at high risk of stroke are of great significance. There is strong evidence of a connection between the chronically activated and sustained inflammatory states and a variety of diseases including cancer [2], neurodegenerative disease [3], and cardiovascular and cerebrovascular disease [4]. The inflammatory processes have been observed in atherosclerotic initiation, plaque rupture, platelet activation, and coagulation system activation, which all contribute to the occurrence of IS [5]. Thus, inflammatory factor C-reactive protein (CRP), as one of the underlying circulating inflammatory markers, was identified to be a reactant in an acute phase of IS. In addition, elevated CRP levels are also generally associated with poor outcomes in acute IS patients [6]. However, the controversies have shown differences with respect to the risk prediction of IS because of genetic factors that influence CRP levels [7]. For example, some studies suggested that there was a positive relationship between elevated CRP and atherosclerosis as a precursor to IS [8]. Also, some showed that high-sensitivity CRP was not associated with IS and atherosclerotic changes [9,10]. Therefore, we speculated that the concentration of CRP in plasma depends on the CRP gene polymorphism. So far, approximately 30 single nucleotide polymorphisms (SNPs) of the CRP gene have been confirmed [11]. Their gene variability could be considered a predictive genetic marker for IS, so investigating the relationship between crucial binding sites SNPs and IS susceptibility may have diagnostic and prognostic implications.

Understanding the relationship between gene polymorphism and disease may help inform the design of pharmacotherapies by using multiple silico techniques [12,13,14]. A number of studies have been conducted to investigate the potential associations between common polymorphisms (rs2794521 (717G>A), rs3091244 (286CT>A), rs1800947 (1,059G>C), rs1130864 (1,444C>T)) in CRP gene and IS risk [15,16]. However, there is still a lack of summary conclusions about the association of CRP rs3093059 (757T>C) and rs1205 C/T polymorphism (2147C>T) with IS risk, though these SNPs polymorphism has also been proposed as possible biomarkers to predict IS risk in some researches. Therefore, we aimed to evaluate whether these two sites’ polymorphisms are associated with the risk of IS through a meta-analysis using all available data.

2 Materials and methods

This meta-analysis was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [17].

2.1 Literature search

A systematic literature search was conducted by using the combination of the following terms: “CRP,”, “CRP” “rs3093059,” “rs1205,” “polymorphism,” “variant,” and “IS” based on PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, and WanFang databases before April 2022. There were no language restrictions during the literature search. Additionally, the references of relevant articles were manually searched for potential studies.

2.2 Inclusion and Exclusion Criteria

The criteria for including studies in this meta-analysis were as follows: (1) the design of the study was case–control or cohort studies; (2) studies assessed the association between CRE gene polymorphism (rs3093059 or rs1205) and IS risk; (3) studies provided available genotype distribution in cases and controls; (4) the genotype distribution of control group conformed to Hardy–Weinberg equilibrium (HWE). The exclusion criteria were (1) studies that reported incomplete data or without data in cases and controls group; (2) duplicate data; and (3) review, case reports, or animal experiments.

2.3 Data extraction and quality assessment

Two authors independently extracted the following information from included studies: first author’s name, year of publication, country, ethnicity, genotype methods, genotype counts in cases groups and control groups, HWE results for control groups, and Newcastle-Ottawa scale (NOS) assessment. The NOS was calculated for the quality assessment of included studies. Discrepancies were resolved by consensus.

2.4 Statistical analyses

Meta-analyses were performed using the STATA version 12.0 (Stata Corporation, College Station, TX, USA), with a value of p < 0.05 which was considered statistically significant. To estimate a summary effect size for IS risk, the odds ratios (ORs) with 95% confidence intervals (CIs) were calculated by using the command “metan” based on five genetic models: allelic model, heterozygous model, homozygous model, dominant model, and recessive model. The significance of the pooled OR was determined by Z-test. Between-study heterogeneities were evaluated with I 2 statistic and Cochran’s Chi-square-based Q test. A fixed-effect model (Mantel–Haenszel method) was used when I 2 was ≤ 50%. Otherwise, analyses would be performed with random-effect models (Mantel–Haenszel method). HWE was tested by Chi-square test in controls. Sensitivity analysis was used to verify the stabilities of synthetic results. Publication bias was assessed using Begg’s funnel plots and Egger’s regression by “metafunnel” and “metabias” commands. We also conducted subgroup analyses by country, genotype method, source of controls, and NOS score. Trim-and-fill method was performed to adjust OR value when publication bias was found.

3 Results

3.1 Characteristics of included studies

By retrieving relevant databases, 531 possible related articles were initially identified. 104 were excluded due to duplication, and then 398 articles were excluded through screening title and abstract. Finally, 18 articles [11,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] were included in this meta-analysis (Figure 1). As shown in Table 1, nine studies focused on rs3093059 T/C polymorphism (including 3,109 patients and 4,939 controls), and 12 studies focused on rs1205 C/T polymorphism (including 4346 patients and 25870 controls). These studies were published from 2006 to 2016, and NOS scores ranged from 6 to 8 points. All the control populations were consistent with HWE. All the studies were conducted on Asians. The studies were carried out in China and Japan.

Figure 1 Flowchart of study selection.
Figure 1

Flowchart of study selection.

Table 1

Characteristics of the investigated studies of the association between the CRP (rs3093059, rs1205) polymorphisms and IS risk

First author Year Country Ethnicity Genotype method Source of controls Case Control Case Control HWE NOS
Rs3093059 TT TC CC TT TC CC
Jiang et al. 2014 China Asian PCR-RFLP HB 548 993 387 148 13 648 313 32 0.435 7
Chen et al. 2015 China Asian PCR-RFLP HB 159 175 108 48 3 115 56 4 0.349 6
Zhao et al. 2018 China Asian Mass ARRAY HB 373 613 263 96 14 431 169 13 0.449 7
Li et al. 2013 China Asian PCR-RFLP HB 129 192 54 51 24 99 70 23 0.061 6
Jiang et al. 2012 China Asian PCR-RFLP PB 510 994 362 135 13 649 314 31 0.346 7
Du et al. 2015 China Asian PCR-RFLP HB 158 290 101 52 5 200 86 4 0.118 6
Wu et al. 2017 China Asian TaqMan PB 580 582 382 172 26 301 238 43 0.666 7
Shen et al. 2009 China Asian PCR-RFLP PB 552 994 386 148 18 649 314 31 0.346 6
Huang et al. 2016 China Asian TaqMan HB 100 106 52 39 9 67 34 5 0.798 8
Rs1205 CC CT TT CC CT CC
Wu et al. 2010 China Asian PCR-RFLP HB 150 125 74 67 9 57 55 13 0.960 7
Liu et al. 2015 China Asian PCR-RFLP HB 60 12 16 29 15 17 31 17 0.753 6
Xu et al. 2015 China Asian PCR-RFLP HB 113 113 20 52 41 19 58 36 0.593 7
Wu et al. 2017 China Asian TaqMan PB 580 582 30 172 378 53 222 307 0.165 7
Huang et al. 2016 China Asian TaqMan HB 100 106 49 38 13 47 40 19 0.052 8
Luo et al. 2015 China Asian PCR-RFLP HB 113 113 20 52 41 19 58 36 0.593 6
Deng et al. 2012 China Asian PCR-RFLP HB 105 121 20 47 38 20 62 39 0.577 7
Yu et al. 2012 China Asian PCR-RFLP HB 1,572 1,485 548 729 295 512 715 258 0.757 6
Zhao et al. 2018 China Asian Mass ARRAY HB 376 613 61 187 128 104 285 224 0.413 7
Wang et al. 2009 China Asian TaqMan HB 564 564 110 282 172 94 297 173 0.078 6
Morita et al. 2006 Japan Asian TaqMan PB 152 304 72 68 12 137 125 42 0.122 7
Miller et al. 2005 Japan Asian TaqMan PB 461 21,732 212 191 58 9,700 9,580 2,452 0.238 8

HWE, Hardy–Weinberg equilibrium; HB, hospital-based source of control; PB, population-based source of control; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; NOS, Newcastle-Ottawa scale.

3.2 CRP rs3093059 T/C polymorphism and IS risk

The main results for the association between CRP rs3093059 T/C polymorphism and IS risk are summarized in Table 2. Based on global population, none of five genetic models indicated a significant association with IS risk (homozygote, CC vs TT: OR = 1.08, 95% CI 0.91–1.16, p = 0.637; recessive, CC vs TC + TT: OR = 1.00, 95% CI 0.79–1.26, p = 0.975; dominant, TT vs TC + CC: OR = 0.91, 95% CI 0.75–1.10, p = 0.327; homozygote, CC vs TT: OR = 1.06, 95% CI 0.71–1.58, p = 0.786; heterozygote, TC vs TT: OR = 0.87, 95% CI 0.73–1.03, p = 0.112; allele, C vs T: OR = 0.95, 95% CI 0.80–1.14, p = 0.592) (Figure 2). Moreover, the synthesized result suggested a null association between the rs3093059 T/C polymorphism and IS risk in the subgroup analysis according to source of controls, genotype method, and NOS score (Table 2). Significant between-study heterogeneities were observed in some genetic models; thus, to confirm the robustness of the meta-analysis, sensitivity analyses were necessary to be carried out. As shown in Figure 3, none of the studies affected the pooled result in the dominant genetic model, which suggested that our results were statistically robust. In addition, publication bias usually makes it difficult to have confidence in any reported differences. Thus, Begg’s and Egger’s linear regression tests were used to visualize publication bias, and the results of Begg’s test and Egger’s test suggested a statistically significant publication bias in heterozygous and allelic genetic models (Table 2). Therefore, we conducted the trim-and-fill method to make the OR value more reliable. It is interesting to note that OR value was significantly decreased (heterozygous genetic model: OR = 0.74; 95% CI 0.62–0.89, p = 0.001; allelic genetic model: OR = 0.78; 95% CI 0.64–0.95, p = 0.012). We used meta-regression to detect the influence covariates and found the source of controls (heterozygous genetic model: coefficient −0.349, 95% CI 0.500–0.994, p  =  0.047; allelic genetic model: coefficient −0.375, 95% CI 0.476–0.993, p  =  0.047) the influence factor.

Table 2

Overall and subgroup analyses for CRP rs3093059polymorphism and IS risk

Comparison Studies Overall effect Heterogeneity Publication bias
OR (95% CI) Z-score p-value I 2 (%) p-value Begg’s test Egger’s test
Recessive genetic model
Overall 8 1.00 (0.79, 1.26) 0.03 0.975 41.2 0.092 0.404 0.165
PCR-RFLP 5 1.05 (0.78, 1.41) 0.33 0.741 8.5 0.362 — —
Mass ARRAY 1 1.80 (0.84, 3.87) 1.50 0.133 — — — —
TaqMan 2 0.73 (0.46, 1.14) 1.40 0.160 73.4 0.052
HB 5 1.33 (0.95, 1.87) 1.67 0.094 16.1 0.310
PB 3 0.76 (0.55, 1.06) 1.61 0.107 8.0 0.337
NOS score <7 4 1.33 (0.90, 1.96) 1.44 0.150 0 0.522
NOS score ≥7 4 0.85 (0.63, 1.14) 1.09 0.276 51.1 0.085
Dominant genetic model
Overall 8 0.91 (0.75, 1.10) 0.98 0.327 72.3 0.001 0.095 0.015
PCR-RFLP 5 0.91 (0.76, 1.09) 1.05 0.294 53.5 0.056
Mass ARRAY 1 0.99 (0.75, 1.31) 0.07 0.947 — —
TaqMan 2 0.91 (0.33, 2.54) 0.18 0.856 91.4 0.001
HB 5 1.07 (0.85, 1.34) 0.57 0.570 56.4 0.043
PB 3 0.70 (0.56, 0.88) 3.01 0.003 66.2 0.052
NOS score <7 4 1.04 (0.78, 1.40) 0.29 0.775 76.3 0.002
NOS score ≥7 4 0.82 (0.64, 1.06) 1.49 0.136 59.9 0.058
Heterozygous genetic model
Overall 8 0.87 (0.73, 1.03) 1.59 0.112 61.0 0.009 0.037 0.013
PCR-RFLP 5 0.87 (0.75, 1.01) 1.78 0.075 31.2 0.201
Mass ARRAY 1 0.93 (0.69, 1.25) 0.48 0.633 — —
TaqMan 2 0.88 (0.35, 2.24) 0.26 0.793 88.4 0.003
HB 5 1.00 (0.83, 1.21) 0.01 0.997 34.4 0.179
PB 3 0.71 (0.58, 0.87) 3.35 0.001 54.1 0.113
NOS score <7 4 0.99 (0.76, 1.27) 0.11 0.911 43.6 0.150
NOS score ≥7 4 0.80 (0.64, 1.01) 1.92 0.055 67.0 0.016
Overall 8 1.06 (0.71, 1.58) 0.27 0.786 59.3 0.012 0.297 0.128
PCR-RFLP 5 1.04 (0.70, 1.55) 0.21 0.831 34.0 0.181
Mass ARRAY 1 1.76 (0.82, 3.81) 1.45 0.148 — —
TaqMan 2 0.96 (0.21, 4.50) 0.05 0.962 83.5 0.014
HB 5 1.43 (0.90, 2.28) 1.50 0.135 36.0 0.167
PB 3 0.69 (0.44, 1.06) 1.69 0.092 40.8 0.185
NOS score <7 4 1.36 (0.86, 2.14) 1.33 0.182 13.3 0.326
NOS score ≥7 4 0.90 (0.52, 1.54) 0.40 0.690 65.3 0.021
Allelic genetic model
Overall 8 0.95 (0.80, 1.14) 0.54 0.592 76.6 0.001 0.037 0.015
PCR-RFLP 5 0.95 (0.80, 1.13) 0.56 0.579 63.8 0.017
Mass ARRAY 1 1.05 (0.82, 1.35) 0.42 0.675 — —
TaqMan 2 0.95 (0.39, 2.28) 0.12 0.906 92.2 0.001
HB 5 1.10 (0.89, 1.37) 0.89 0.373 65.4 0.013
PB 3 0.75 (0.62, 0.92) 2.84 0.004 66.3 0.051
NOS score <7 4 1.08 (0.82, 1.40) 0.54 0.590 66.1 0.031
NOS score ≥7 4 0.87 (0.69, 1.10) 1.16 0.246 79.1 0.001

OR, odds ratio; CI, confidence interval; HB, hospital-based source of control; PB, population-based source of control; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; NOS, Newcastle-Ottawa scale.

Figure 2 OR and 95% CIs of the associations between C-reactive protein (CRP) rs3093059 T/C polymorphism and IS risk: (a) CC vs TC + TT; (b) TT vs TC + CC; (c) TC vs TT; (d) CC vs TT; (e) C vs T.
Figure 2

OR and 95% CIs of the associations between C-reactive protein (CRP) rs3093059 T/C polymorphism and IS risk: (a) CC vs TC + TT; (b) TT vs TC + CC; (c) TC vs TT; (d) CC vs TT; (e) C vs T.

Figure 3 Sensitivity analysis was used to estimate the individual influence of studies on pooled results under the dominant genetic model.
Figure 3

Sensitivity analysis was used to estimate the individual influence of studies on pooled results under the dominant genetic model.

3.3 CRP rs1205 C/T polymorphism and IS risk

The main results for the association between CRP rs1205 C/T polymorphism and IS risk are summarized in Table 3. The results indicated that there were no significant associations between CRP rs1205 C/T polymorphism and IS risk under homozygote (TT vs CC: OR = 1.08, 95% CI 0.91–1.16, p = 0.637), heterozygote (CT vs CC: OR = 0.91, 95% CI 0.75–1.11, p = 0.288), dominant (CC vs CT + TT: OR = 0.97, 95% CI 0.89–1.06, p = 0.524), recessive (TT vs CT + CC: OR = 1.06, 95% CI 0.90–1.25, p = 0.495), and allele (T vs C: OR = 1.02, 95% CI 0.92–1.13, p = 0.776 [Figure 4]). The synthesized result suggested a null association between the CRP rs1205 C/T polymorphism and IS risk in the subgroup analysis according to country, genotype method, source of controls, and NOS score (Table 3). Significant between-study heterogeneity was observed in some genetic models; thus, to confirm the robustness of the meta-analysis, sensitivity analyses were necessary to be carried out. As shown in Figure 5, none of the studies affected the pooled result, which suggested that our results were statistically robust. Begg’s and Egger’s linear regression tests were used to visualize publication bias, and the results of Begg’s test and Egger’s test suggested no statistically significant publication bias in all genetic models (Table 3).

Table 3

Overall and subgroup analyses for CRP rs1205 polymorphism and IS risk

Comparison Studies Overall effect Heterogeneity Publication bias
OR (95% CI) Z-Score p-Value I 2 (%) p-Value Begg’s test Egger’s test
Recessive genetic model
Overall 12 1.06 (0.90, 1.25) 0.68 0.495 53.9 0.013 0.244 0.175
PCR-RFLP 6 1.09 (0.94, 1.28) 1.14 0.253 0 0.725 — —
Mass ARRAY 1 0.90 (0.68, 1.17) 0.80 0.426 — — — —
TaqMan 5 1.03 (0.74, 1.44) 0.19 0.850 77.3 0.001 — —
HB 9 1.02 (0.91, 1.15) 0.34 0.731 0 0.690 — —
PB 3 1.11 (0.68, 1.80) 0.40 0.687 83.4 0.002 — —
NOS score <7 4 1.07 (0.93, 1.23) 0.89 0.376 0 0.866 — —
NOS score ≥7 8 1.01 (0.77, 1.33) 0.08 0.935 69 0.002 — —
China 10 1.09 (0.91, 1.30) 0.94 0.349 53.2 0.023 — —
Japan 2 0.83 (0.40, 1.71) 0.50 0.615 75.5 0.043 — —
Dominant genetic model
Overall 12 0.97 (0.89, 1.06) 0.64 0.524 0 0.573 0.837 0.935
PCR-RFLP 6 0.96 (0.84, 1.10) 0.54 0.588 0 0.994 — —
Mass ARRAY 1 1.06 (0.75, 1.49) 0.30 0.761 — — — —
TaqMan 5 0.97 (0.84, 1.10) 0.51 0.610 54.8 0.065 — —
HB 9 0.95 (0.85, 1.06) 0.95 0.341 0 0.984 — —
PB 3 1.02 (0.87, 1.19) 0.24 0.811 71.9 0.028 — —
NOS score <7 4 0.95 (0.84, 1.08) 0.77 0.444 0 0.794 — —
NOS score ≥7 8 0.99 (0.87, 1.13) 0.14 0.889 16 0.304 — —
China 10 0.98 (0.88, 1.10) 0.29 0.770 3.4 0.408 — —
Japan 2 0.94 (0.80, 1.11) 0.72 0.471 0 0.863 — —
Heterozygous genetic model
Overall 12 0.91 (0.75, 1.11) 1.06 0.288 0 0.943 0.732 0.857
PCR-RFLP 6 0.94 (0.81, 1.08) 0.91 0.362 0 0.991 — —
Mass ARRAY 1 1.12 (0.78, 1.61) 0.60 0.548 — — — —
TaqMan 5 0.94 (0.81, 1.08) 0.88 0.380 0 0.496 — —
HB 9 0.93 (0.83, 1.05) 1.11 0.265 0 0.974 — —
PB 3 0.98 (0.83, 1.16) 0.27 0.790 15.2 0.308 — —
NOS score <7 4 0.92 (0.80, 1.06) 1.16 0.248 0 0.837 — —
NOS score ≥7 8 0.98 (0.85, 1.12) 0.35 0.726 0 0.828 — —
China 10 0.96 (0.85, 1.07) 0.78 0.436 0 0.883 — —
Japan 2 0.93 (0.78, 1.12) 0.75 0.453 0 0.587 — —
Homozygous genetic model
Overall 12 1.08 (0.91, 1.16) 0.47 0.637 37.3 0.093 0.244 0.380
PCR-RFLP 6 1.03 (0.86, 1.23) 0.33 0.739 0 0.823 — —
Mass ARRAY 1 0.97 (0.66, 1.43) 0.13 0.894 — — — —
TaqMan 5 1.04 (0.87, 1.26) 0.44 0.661 73.8 0.004 — —
HB 9 0.97 (0.84, 1.13) 0.35 0.725 0 0.849 — —
PB 3 1.19 (0.95, 1.49) 1.48 0.140 82.5 0.003 — —
NOS score <7 4 1.01 (0.85, 1.19) 0.09 0.930 0 0.731 — —
NOS score ≥7 8 1.06 (0.88, 1.26) 0.59 0.554 56.6 0.024 — —
China 10 1.05 (0.91, 1.20) 0.66 0.512 36.7 0.115 — —
Japan 2 0.97 (0.74, 1.27) 0.25 0.804 68.3 0.076 — —
Allelic genetic model
Overall 12 1.02 (0.92, 1.13) 0.28 0.776 56,4 0.008 0.945 0.665
PCR-RFLP 6 1.01 (0.93, 1.11) 0.29 0.772 0 0.916 — —
Mass ARRAY 1 0.96 (0.80, 1.16) 0.39 0.699 — — — —
TaqMan 5 1.02 (0.81, 1.28) 1.13 0.260 82.6 0.001 — —
HB 9 0.99 (0.92, 1.06) 0.40 0.691 0 0.927 — —
PB 3 1.10 (0.78, 1.56) 0.54 0.586 89.1 0.001 — —
NOS score <7 4 1.00 (0.92, 1.09) 0.03 0.976 0 0.839 — —
NOS score ≥7 8 1.01 (0.86, 1.20) 0.15 0.884 70.6 0.001 — —
China 10 1.03 (0.91, 1.17) 0.52 0.601 60.7 0.006 — —
Japan 2 0.95 (0.82, 1.12) 0.58 0.560 20.3 0.263 — —

OR, odds ratio; CI, confidence interval; HB, hospital-based source of control; PB, population-based source of control; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; NOS, Newcastle-Ottawa scale.

Figure 4 OR and 95% CIs of the associations between CRP rs1205 C/T polymorphism and IS risk: (a) TT vs CT + CC; (b) CC vs CT + TT; (c) CT vs CC; (d) TT vs CC; (e) T vs C.
Figure 4

OR and 95% CIs of the associations between CRP rs1205 C/T polymorphism and IS risk: (a) TT vs CT + CC; (b) CC vs CT + TT; (c) CT vs CC; (d) TT vs CC; (e) T vs C.

Figure 5 Sensitivity analysis was used to estimate the individual influence of studies on pooled results under the recessive genetic model.
Figure 5

Sensitivity analysis was used to estimate the individual influence of studies on pooled results under the recessive genetic model.

4 Discussion

This meta-analysis included the literature published in recent years about the association between CRP polymorphisms (rs3093059, rs1205) and IS susceptibility. The pooled results revealed that CRP polymorphisms (rs3093059, rs1205) might not associate with IS risk.

CRP, a glycoprotein released by the liver, has been regarded as an essential mediator and a hallmark of the acute-phase response to inflammation and is recommended for use in risk assessment in IS patients [35]. CRP is an evolutionarily conserved protein with a unique pentameric structure and binds to ligands in a calcium-dependent manner [36]. Once binding to ligands, CRP interacts with the classical complement pathway and Fcγ receptors to participate in the activation of the innate immune system [37,38]. The gene of CRP is located on chromosome 1 and has only two exons and a single intron, including 204-amino acid peptides in the coding regions of exons and 280-base pairs in the domain of the intron [39]. Due to the existence of single-nucleotide polymorphisms (SNPs), CRP genetic variants and individual variations in the inflammatory response are significant. Many researchers have proved that the altered serum level of CRP should be attributed to the CRP gene variations on chromosomes 1q21 to 1q23 [40]. A couple of sequence variations at this locus have been shown to modulate plasma CRP levels and the risk of IS [41]. So the SNPs of CRP are a vital factor in the development of IS.

As an inflammation-associated protein, CRP can be divided into two structurally and functionally independent forms: (1) net anti-inflammatory, serum-associated native pentameric CRP, and (2) pro-inflammatory tissue-associated, monomeric CRP (mCRP) [37,42]. Several studies proved that a dramatic increase in the expression of mCRP had been observed in blood vessels of damaged brain regions in IS patients [43,44,45]. Krupinski and his colleagues found a higher expression of mCRP within microvessels with unstable plaques while normal-looking arteries, and stable fibrous lesions contained a significantly lower expression [44]. It suggested that mCRP may have a pathological role in developing unstable atherosclerosis and/or increased risk of plaque thrombosis, which could lead to the occurrence of IS. mCRP increases the activation of the inflammation both in vitro and in vivo, getting deposited chronically within the brain after IS, and may play a role in perpetuating neuroinflammation after brain injury [35]. Of course, there are still some opposite opinions. The function of CRP in the development of IS should be studied further.

Though the clear mechanism is ambiguous, CRP is closely related to the occurrence, development, and outcome of IS. The results of clinical studies show that CRP levels increase in the first 48 h after onset, are still elevated at 7 days and remain high for 3–6 months after IS [46,47]. CRP levels correlate with IS severity and can be a marker of IS etiology, with higher CRP in more severe cardioembolic or large artery disease stroke than in stroke caused by small artery disease [47,48,49]. Numbers of clinical studies use CRP as a biomarker to predict the occurrence of IS, and try to explore the relationship between SNPs of CRP and IS. The effect of CRP SNPs such as rs1800947, rs1417938, rs1130864, and rs3093077 on circulating protein level and the outcome has been assessed in a cohort of in-patients with cardiovascular diseases (e.g., IS) by Schulz et al. They found that both CRP level ≥5 mg/L and SNP rs1800947 of the CRP gene were independent risk factors for further adverse vascular events among patients with cardiovascular diseases within a 3-year follow-up [50]. A study of clinical samples by Williams et al. found that SNPs at rs3093068, rs16842599, and rs11265260 loci of CRP were associated with the occurrence and recurrence of IS [51]. Manuela and his colleagues consider that CRP levels after a minor first cerebrovascular event (transient ischemic attack or lacunar stroke) can contribute to identifying patients at high risk of a second ischemic event. Rs3093059 is located in the promoter region of the CRP gene. The mutation of this site would provide convenience for LHX2 binding to promote expression [52]. C alleles at rs3093059 were positively associated with increased CRP elevation in IS patients, which is inconsonant with our results. After multivariate adjustment, rs3093059 was found to be associated with decreased IS risk in the Chinese population [24]. Also, no association was detected between CRP gene polymorphisms and IS risk in the Swedish [41] population and Indian population [53]. It suggested that whether Rs3093059 can be judged as a risk factor in IS cases may be related to the population and environment. The rs1205 was located in the untranslated region of the CRP gene region. It was reported that CRP rs1205 polymorphism is associated with elevated CRP levels in Aortic stenosis patients and cardioembolic stroke [54]. However, it was found a negative association in our study is attributed to the type of stroke and the underlying condition of the patient. Circulating levels of CRP could be influenced by age, obesity, sex, smoking, diabetes, and use of medications summarily [55].

To our knowledge, this study is the first meta-analysis to focus on CRP polymorphisms (rs3093059 T/C and rs1205 C/T) and IS risk and proved CRP rs3093059 T/C and rs1205 C/T polymorphisms have little association with the risk of IS. Based on the aforementioned analysis, our study still has some limitations and shortages. On the one hand, the data are still relatively small and may not provide sufficient power to estimate the association between CRP gene polymorphisms and IS risk. Few studies have investigated the association between the CRP gene and patients’ stroke subtypes and patient-based characteristics, which has to be confirmed in more populations. On the other hand, as a type of retrospective study, a meta-analysis may encounter recall or selection bias, possibly influencing the reliability of our study results. Therefore, more studies with larger sample sizes are needed to accurately provide a more representative conclusion.

5 Conclusion

The current meta-analysis result suggests that CRP (rs3093059 T/C and rs1205 C/T) polymorphisms might not be associated with the risk of IS. In addition, CRP genetic variant might be associated with multiple internal and external factors, which suggests that further efforts are needed to dissect subgroups and patients’ overall physical condition. However, large sample size and well-designed studies within different ethnic are needed to confirm the findings of our study

# These authors contributed equally to this work.

  1. Funding information: Authors state no funding involved.

  2. Author contributions: Z.C. and J.Y. conceived the study. Z.C., F.J., and M.Y. searched the databases and extracted the data. ZC and FJ performed the data analysis. Z.C., F.J., and J.Y. wrote the paper. All the authors read and approved the final manuscript.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Received: 2022-06-19
Revised: 2022-08-28
Accepted: 2022-09-04
Published Online: 2022-11-16

© 2022 Zhizhi Chen et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  104. Cloning and identification of the CTLA-4IgV gene and functional application of vaccine in Xinjiang sheep
  105. Antitumor activity of RUNX3: Upregulation of E-cadherin and downregulation of the epithelial–mesenchymal transition in clear-cell renal cell carcinoma
  106. PHF8 promotes osteogenic differentiation of BMSCs in old rat with osteoporosis by regulating Wnt/β-catenin pathway
  107. A review of the current state of the computer-aided diagnosis (CAD) systems for breast cancer diagnosis
  108. Bilateral dacryoadenitis in adult-onset Still’s disease: A case report
  109. A novel association between Bmi-1 protein expression and the SUVmax obtained by 18F-FDG PET/CT in patients with gastric adenocarcinoma
  110. The role of erythrocytes and erythroid progenitor cells in tumors
  111. Relationship between platelet activation markers and spontaneous abortion: A meta-analysis
  112. Abnormal methylation caused by folic acid deficiency in neural tube defects
  113. Silencing TLR4 using an ultrasound-targeted microbubble destruction-based shRNA system reduces ischemia-induced seizures in hyperglycemic rats
  114. Plant Sciences
  115. Seasonal succession of bacterial communities in cultured Caulerpa lentillifera detected by high-throughput sequencing
  116. Cloning and prokaryotic expression of WRKY48 from Caragana intermedia
  117. Novel Brassica hybrids with different resistance to Leptosphaeria maculans reveal unbalanced rDNA signal patterns
  118. Application of exogenous auxin and gibberellin regulates the bolting of lettuce (Lactuca sativa L.)
  119. Phytoremediation of pollutants from wastewater: A concise review
  120. Genome-wide identification and characterization of NBS-encoding genes in the sweet potato wild ancestor Ipomoea trifida (H.B.K.)
  121. Alleviative effects of magnetic Fe3O4 nanoparticles on the physiological toxicity of 3-nitrophenol to rice (Oryza sativa L.) seedlings
  122. Selection and functional identification of Dof genes expressed in response to nitrogen in Populus simonii × Populus nigra
  123. Study on pecan seed germination influenced by seed endocarp
  124. Identification of active compounds in Ophiopogonis Radix from different geographical origins by UPLC-Q/TOF-MS combined with GC-MS approaches
  125. The entire chloroplast genome sequence of Asparagus cochinchinensis and genetic comparison to Asparagus species
  126. Genome-wide identification of MAPK family genes and their response to abiotic stresses in tea plant (Camellia sinensis)
  127. Selection and validation of reference genes for RT-qPCR analysis of different organs at various development stages in Caragana intermedia
  128. Cloning and expression analysis of SERK1 gene in Diospyros lotus
  129. Integrated metabolomic and transcriptomic profiling revealed coping mechanisms of the edible and medicinal homologous plant Plantago asiatica L. cadmium resistance
  130. A missense variant in NCF1 is associated with susceptibility to unexplained recurrent spontaneous abortion
  131. Assessment of drought tolerance indices in faba bean genotypes under different irrigation regimes
  132. The entire chloroplast genome sequence of Asparagus setaceus (Kunth) Jessop: Genome structure, gene composition, and phylogenetic analysis in Asparagaceae
  133. Food Science
  134. Dietary food additive monosodium glutamate with or without high-lipid diet induces spleen anomaly: A mechanistic approach on rat model
  135. Binge eating disorder during COVID-19
  136. Potential of honey against the onset of autoimmune diabetes and its associated nephropathy, pancreatitis, and retinopathy in type 1 diabetic animal model
  137. FTO gene expression in diet-induced obesity is downregulated by Solanum fruit supplementation
  138. Physical activity enhances fecal lactobacilli in rats chronically drinking sweetened cola beverage
  139. Supercritical CO2 extraction, chemical composition, and antioxidant effects of Coreopsis tinctoria Nutt. oleoresin
  140. Functional constituents of plant-based foods boost immunity against acute and chronic disorders
  141. Effect of selenium and methods of protein extraction on the proteomic profile of Saccharomyces yeast
  142. Microbial diversity of milk ghee in southern Gansu and its effect on the formation of ghee flavor compounds
  143. Ecology and Environmental Sciences
  144. Effects of heavy metals on bacterial community surrounding Bijiashan mining area located in northwest China
  145. Microorganism community composition analysis coupling with 15N tracer experiments reveals the nitrification rate and N2O emissions in low pH soils in Southern China
  146. Genetic diversity and population structure of Cinnamomum balansae Lecomte inferred by microsatellites
  147. Preliminary screening of microplastic contamination in different marine fish species of Taif market, Saudi Arabia
  148. Plant volatile organic compounds attractive to Lygus pratensis
  149. Effects of organic materials on soil bacterial community structure in long-term continuous cropping of tomato in greenhouse
  150. Effects of soil treated fungicide fluopimomide on tomato (Solanum lycopersicum L.) disease control and plant growth
  151. Prevalence of Yersinia pestis among rodents captured in a semi-arid tropical ecosystem of south-western Zimbabwe
  152. Effects of irrigation and nitrogen fertilization on mitigating salt-induced Na+ toxicity and sustaining sea rice growth
  153. Bioengineering and Biotechnology
  154. Poly-l-lysine-caused cell adhesion induces pyroptosis in THP-1 monocytes
  155. Development of alkaline phosphatase-scFv and its use for one-step enzyme-linked immunosorbent assay for His-tagged protein detection
  156. Development and validation of a predictive model for immune-related genes in patients with tongue squamous cell carcinoma
  157. Agriculture
  158. Effects of chemical-based fertilizer replacement with biochar-based fertilizer on albic soil nutrient content and maize yield
  159. Genome-wide identification and expression analysis of CPP-like gene family in Triticum aestivum L. under different hormone and stress conditions
  160. Agronomic and economic performance of mung bean (Vigna radiata L.) varieties in response to rates of blended NPS fertilizer in Kindo Koysha district, Southern Ethiopia
  161. Influence of furrow irrigation regime on the yield and water consumption indicators of winter wheat based on a multi-level fuzzy comprehensive evaluation
  162. Discovery of exercise-related genes and pathway analysis based on comparative genomes of Mongolian originated Abaga and Wushen horse
  163. Lessons from integrated seasonal forecast-crop modelling in Africa: A systematic review
  164. Evolution trend of soil fertility in tobacco-planting area of Chenzhou, Hunan Province, China
  165. Animal Sciences
  166. Morphological and molecular characterization of Tatera indica Hardwicke 1807 (Rodentia: Muridae) from Pothwar, Pakistan
  167. Research on meat quality of Qianhua Mutton Merino sheep and Small-tail Han sheep
  168. SI: A Scientific Memoir
  169. Suggestions on leading an academic research laboratory group
  170. My scientific genealogy and the Toronto ACDC Laboratory, 1988–2022
  171. Erratum
  172. Erratum to “Changes of immune cells in patients with hepatocellular carcinoma treated by radiofrequency ablation and hepatectomy, a pilot study”
  173. Erratum to “A two-microRNA signature predicts the progression of male thyroid cancer”
  174. Retraction
  175. Retraction of “Lidocaine has antitumor effect on hepatocellular carcinoma via the circ_DYNC1H1/miR-520a-3p/USP14 axis”
https://doi.org/10.1515/biol-2022-0505
Schlagwörter für diesen Artikel
ischemic stroke; C-reactive protein; polymorphism; meta-analysis
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  116. Cloning and prokaryotic expression of WRKY48 from Caragana intermedia
  117. Novel Brassica hybrids with different resistance to Leptosphaeria maculans reveal unbalanced rDNA signal patterns
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  120. Genome-wide identification and characterization of NBS-encoding genes in the sweet potato wild ancestor Ipomoea trifida (H.B.K.)
  121. Alleviative effects of magnetic Fe3O4 nanoparticles on the physiological toxicity of 3-nitrophenol to rice (Oryza sativa L.) seedlings
  122. Selection and functional identification of Dof genes expressed in response to nitrogen in Populus simonii × Populus nigra
  123. Study on pecan seed germination influenced by seed endocarp
  124. Identification of active compounds in Ophiopogonis Radix from different geographical origins by UPLC-Q/TOF-MS combined with GC-MS approaches
  125. The entire chloroplast genome sequence of Asparagus cochinchinensis and genetic comparison to Asparagus species
  126. Genome-wide identification of MAPK family genes and their response to abiotic stresses in tea plant (Camellia sinensis)
  127. Selection and validation of reference genes for RT-qPCR analysis of different organs at various development stages in Caragana intermedia
  128. Cloning and expression analysis of SERK1 gene in Diospyros lotus
  129. Integrated metabolomic and transcriptomic profiling revealed coping mechanisms of the edible and medicinal homologous plant Plantago asiatica L. cadmium resistance
  130. A missense variant in NCF1 is associated with susceptibility to unexplained recurrent spontaneous abortion
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  132. The entire chloroplast genome sequence of Asparagus setaceus (Kunth) Jessop: Genome structure, gene composition, and phylogenetic analysis in Asparagaceae
  133. Food Science
  134. Dietary food additive monosodium glutamate with or without high-lipid diet induces spleen anomaly: A mechanistic approach on rat model
  135. Binge eating disorder during COVID-19
  136. Potential of honey against the onset of autoimmune diabetes and its associated nephropathy, pancreatitis, and retinopathy in type 1 diabetic animal model
  137. FTO gene expression in diet-induced obesity is downregulated by Solanum fruit supplementation
  138. Physical activity enhances fecal lactobacilli in rats chronically drinking sweetened cola beverage
  139. Supercritical CO2 extraction, chemical composition, and antioxidant effects of Coreopsis tinctoria Nutt. oleoresin
  140. Functional constituents of plant-based foods boost immunity against acute and chronic disorders
  141. Effect of selenium and methods of protein extraction on the proteomic profile of Saccharomyces yeast
  142. Microbial diversity of milk ghee in southern Gansu and its effect on the formation of ghee flavor compounds
  143. Ecology and Environmental Sciences
  144. Effects of heavy metals on bacterial community surrounding Bijiashan mining area located in northwest China
  145. Microorganism community composition analysis coupling with 15N tracer experiments reveals the nitrification rate and N2O emissions in low pH soils in Southern China
  146. Genetic diversity and population structure of Cinnamomum balansae Lecomte inferred by microsatellites
  147. Preliminary screening of microplastic contamination in different marine fish species of Taif market, Saudi Arabia
  148. Plant volatile organic compounds attractive to Lygus pratensis
  149. Effects of organic materials on soil bacterial community structure in long-term continuous cropping of tomato in greenhouse
  150. Effects of soil treated fungicide fluopimomide on tomato (Solanum lycopersicum L.) disease control and plant growth
  151. Prevalence of Yersinia pestis among rodents captured in a semi-arid tropical ecosystem of south-western Zimbabwe
  152. Effects of irrigation and nitrogen fertilization on mitigating salt-induced Na+ toxicity and sustaining sea rice growth
  153. Bioengineering and Biotechnology
  154. Poly-l-lysine-caused cell adhesion induces pyroptosis in THP-1 monocytes
  155. Development of alkaline phosphatase-scFv and its use for one-step enzyme-linked immunosorbent assay for His-tagged protein detection
  156. Development and validation of a predictive model for immune-related genes in patients with tongue squamous cell carcinoma
  157. Agriculture
  158. Effects of chemical-based fertilizer replacement with biochar-based fertilizer on albic soil nutrient content and maize yield
  159. Genome-wide identification and expression analysis of CPP-like gene family in Triticum aestivum L. under different hormone and stress conditions
  160. Agronomic and economic performance of mung bean (Vigna radiata L.) varieties in response to rates of blended NPS fertilizer in Kindo Koysha district, Southern Ethiopia
  161. Influence of furrow irrigation regime on the yield and water consumption indicators of winter wheat based on a multi-level fuzzy comprehensive evaluation
  162. Discovery of exercise-related genes and pathway analysis based on comparative genomes of Mongolian originated Abaga and Wushen horse
  163. Lessons from integrated seasonal forecast-crop modelling in Africa: A systematic review
  164. Evolution trend of soil fertility in tobacco-planting area of Chenzhou, Hunan Province, China
  165. Animal Sciences
  166. Morphological and molecular characterization of Tatera indica Hardwicke 1807 (Rodentia: Muridae) from Pothwar, Pakistan
  167. Research on meat quality of Qianhua Mutton Merino sheep and Small-tail Han sheep
  168. SI: A Scientific Memoir
  169. Suggestions on leading an academic research laboratory group
  170. My scientific genealogy and the Toronto ACDC Laboratory, 1988–2022
  171. Erratum
  172. Erratum to “Changes of immune cells in patients with hepatocellular carcinoma treated by radiofrequency ablation and hepatectomy, a pilot study”
  173. Erratum to “A two-microRNA signature predicts the progression of male thyroid cancer”
  174. Retraction
  175. Retraction of “Lidocaine has antitumor effect on hepatocellular carcinoma via the circ_DYNC1H1/miR-520a-3p/USP14 axis”
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