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Association between microRNA binding site polymorphisms in immunoinflammatory genes and recurrence risk of ischemic stroke
Genomics xxx (xxxx) xxx–xxx
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Genomics journal homepage: www.elsevier.com/locate/ygeno
Original Article
Association between microRNA binding site polymorphisms in immunoinflammatory genes and recurrence risk of ischemic stroke Ruixia Zhu, Yating Zhao, Tongling Xiao, Qianwen Wang, Xu Liu
⁎
Department of Neurology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
A R T I C LE I N FO
A B S T R A C T
Keywords: microRNA Polymorphism Ischemic stroke Prognosis
MicroRNA binding site polymorphisms in immunoinflammatory genes have been implicated as candidate biomarkers for prediction of complex human diseases. However, the roles of microRNA binding site polymorphisms in stroke onset and prognosis remain unclear. Thus, for the first time, five potential functional polymorphisms in immunoinflammatory genes (CXCR2 rs1126579, TLR4 rs11536889, ADIPOR2 rs12342, MMP-2 rs7201 and MMP-9 rs1056628) were genotyped in 657 patients with ischemic stroke. These five polymorphisms were not related with age onset of ischemic stroke. However, we found that ADIPOR2 rs12342 was significantly associated with a decreased recurrence risk, especially for the patients with small-vessel disease. Moreover, by using multivariate Cox regression, the variant genotype GG/GA of rs12342 was observed as an independent protective factor for stroke recurrence, even after Bonferroni correction. In addition, after the addition of rs12342 in the model with clinical factors, the new model showed the improved discriminatory ability to predict stroke recurrence. In short, our results suggested that ADIPOR2 rs12342 may be a novel genetic biomarker and therapeutic target for ischemic stroke recurrence. Further studies are required to replicate our findings and clarify the potential biological mechanism.
1. Introduction As a major health threat worldwide, ischemic stroke is a leading cause of long-term disability and mortality in adults [1]. As the aging of the population, ischemic stroke burden continues to increase globally and the American Heart Association predicts that the direct stroke-related medical costs will reach $183 billion by 2030 [2,3]. Due to rapid advances in medical technology, stroke mortality has decreased and most patients can survive after the first stroke. Unfortunately, the survivors of ischemic stroke would face a higher risk of recurrent stroke, which is more likely to be costly, disabling and fatal [4]. Thus, discovery of novel biomarkers to identify stroke patients at an imminent risk of recurrence is urgently needed to improve stroke prevention and prognosis. Conventional risk factors that may affect the susceptibility and prognosis of ischemic stroke such as hypertension, diabetes and smoking are well investigated, but much more remains unexplained [5,6]. Genetic factors, indicated by evidence from case-control, twin and family-based studies, would result in a predisposition to ischemic stroke [7,8]. Immunoinflammation is an essential process in the pathophysiology of ischemic stroke. Some inflammatory markers, such as
C-reactive protein, IL-6 and lipoprotein-associated phospholipase A2, have been associated with stroke risk and prognosis [9]. Immunemediated inflammation may play an important role in arterial endothelial injury, vascular inflammation and arteriosclerosis [10,11]. Moreover, the immune response to acute cerebral ischemia is a major factor in stroke outcome and anti-inflammatory intervention has the potential of improving the prognosis in experimental stroke [12,13]. Thus, genetic variants involved in immunoinflammatory responses are under investigation to find the relationship with the susceptibility and recurrence of ischemic stroke [14–16]. MicroRNA binding site polymorphisms are though as a group of potential functional polymorphisms, which can affect the expression of target genes [17,18]. Moreover, these polymorphisms may change the individual susceptibility and prognosis to the diseases [19,20]. Recent studies have demonstrated that microRNA binding site polymorphisms in immunoinflammatory genes were related with ischemic stroke susceptibility [21,22]. However, the roles of microRNA binding site polymorphisms in stroke onset and prognosis remain unclear. Thus, we performed a prospective cohort study to investigate the relationship between five potential functional polymorphisms in immunoinflammatory genes (CXCR2 rs1126579, TLR4 rs11536889, ADIPOR2
⁎ Corresponding author at: Department of Neurology, First Affiliated Hospital of China Medical University, No. 155 North Nanjing Street, Shenyang 110001, Liaoning, China. E-mail address: [email protected] (X. Liu).
https://doi.org/10.1016/j.ygeno.2019.12.020 Received 13 September 2019; Received in revised form 14 December 2019; Accepted 25 December 2019 0888-7543/ © 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Ruixia Zhu, et al., Genomics, https://doi.org/10.1016/j.ygeno.2019.12.020
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120 s. Next, the LDR reaction contained the following: 2 μl of PCR product, 0.4 μl of individual probe, 1 μl 10× ligation buffer, 0.25 μl Taq DNA ligase and 6 μl double-distilled water. The cycling parameters were set as: 94 °C for 60 s; 38 cycles× 56 °C for 240 s. Finally, the LDR product was analyzed using ABI 3730XL Sequencer and Gene-Mapper software. In addition, 5% of our samples were randomly chosen for validation, and the concordance rate was 100%.
rs12342, MMP-2 rs7201 and MMP-9 rs1056628) and the clinical behavior of ischemic stroke in Chinese population. 2. Materials and methods 2.1. Study populations A total of 657 patients with ischemic stroke were enrolled prospectively from the First Affiliated Hospital of China Medical University. All patients suffered from a focal neurological deficit > 24 h and underwent magnetic resonance imaging or computed tomography to confirm the diagnosis. With regard to TOAST classification, ischemic stroke can be divided into 5 types: large-artery atherosclerosis (LAA), small-vessel occlusion (SVO), cardioembolism, stroke with undetermined etiology and stroke with other determined etiology [23]. Only the stroke patients with LAA and SVO subtypes were included in our study, while other subtypes were excluded. Subsequent follow-up was carried out every three months until ischemic stroke recurrence or the last follow-up period (December 2018) by telephone contact or clinical visit using a standard questionnaire. Finally, among 657 patients with ischemic stroke, 610 completed the follow-up with an average 42 months and 47 (7.2%) were lost during the follow-up. The study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the First Affiliated Hospital of China Medical university. All participants were given written informed consent.
2.3. Statistical analysis A one-way analysis of variance (ANOVA) was used to assess whether presence of genetic polymorphisms could influence age of stroke onset. The recurrence time was determined from the diagnosis date of ischemic stroke to the date of stroke recurrence or the last time of follow-up. The recurrence curves were constructed by the Kaplan-Meier method, and the difference between recurrence time was evaluated using the log rank test. The hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by Cox proportional hazards regression model with adjustments for age, sex, diabetes, hypertension, hyperlipidemia, drinking and smoking. Moreover, Bonferroni adjustment was applied to correct for multiple comparisons. Receiver operating characteristic (ROC) curve was constructed from the logistic regression model, and the area under the curve (AUC) was used to assess the predictive performance of the model. All the statistical analyses were performed with SPSS 17.0 software. A P value of < 0.05 was considered statistically significant.
2.2. DNA extraction and genotyping 3. Results
Genomic DNA was extracted from blood samples according to standard procedures and stored at −20 °C. Genotyping was performed using the polymerase chain reaction-ligase detection reaction (PCRLDR) method [24,25]. The primer and probe sequences of PCR-LDR were shown in Table 1. The multiple PCR amplification was performed within the mixture of 1 μl genomic DNA sample, 1 μl of individual primer, 3.0 mM Mg2+, 0.3 mM dNTPs, 1 × GC-I buffer, 1 U Hot-Start Taq polymerase. The cycling parameters were as follows: 95 °C for 120 s; 11 cycles × (94 °C for 20 s, 65 °C for 40 s, and 72 °C for 90 s); 24 cycles× (94 °C for 20 s, 59 °C for 30 s, and 72 °C for 90 s); 72 °C for
3.1. MicroRNA binding site polymorphisms and age onset of stroke A total of 657 patients with ischemic stroke were included in the current study. We did not observe the association between microRNA binding site polymorphisms in immunoinflammatory genes and the age onset of ischemic stroke (P > .05), which suggested that these genetic variants cannot predict the onset time of ischemic stroke (Fig. 1).
Table 1 Primer sequences and probes of microRNA binding site polymorphisms. Polymorphisms
Primer sequences and probes
rs1056628F rs1056628R rs1056628RA rs1056628RC rs1056628RP rs1126579F rs1126579R rs1126579FC rs1126579FP rs1126579FT rs11536889F rs11536889R rs11536889FC rs11536889FG rs11536889FP rs12342F rs12342R rs12342FC rs12342FP rs12342FT rs7201F rs7201R rs7201FA rs7201FC rs7201FP
TCTGCCAGGACCGCTTCTACTG TCCTCCCTTTCCTCCAGAACAGA TGTTCGTGGGCCGGATTAGTTCCCCAGGGTTGGTCCCTGT TCTCTCGGGTCAATTCGTCCTTTCCCCAGGGTTGGTCCCTGG GGGGATTTACATGGCACTGCCTTTTTTTTT TTTCGCCATGGACTCCTCAAGAT AGGCACCAGGGCAAGCTTTCTA TTCCGCGTTCGGACTGATATCCCCATTGTGGTCACAGGATGC AGAGGAGGCCACGTTCTTACTAGTTTTTTTTTTTTTT TACGGTTATTCGGGCTCCTGTCCCCATTGTGGTCACAGGACGT CCTGTTGGGCAATGCTCCTTGA TTTCTGAGGAGGCTGGATGAACA TACGGTTATTCGGGCTCCTGTGCTCCTTGACCACATTTTGGGTAC TTCCGCGTTCGGACTGATATGCTCCTTGACCACATTTTGGGTAG AGTGGATGTTATCAYTGAGAAAACAATGTTTTTTTTTTTTTTTTTTT TCTTGGCCCATAGGTGAACCAC TCCCACCTTTTGCTGGAGATTG TCTCTCGGGTCAATTCGTCCTTGTCCTGAGCATGGGGACTTGC GTCCTCAGTAGGTGTTTGGGAATRTGTTTTTTTT TGTTCGTGGGCCGGATTAGTGTCCTGAGCATGGGGACTCGT CCGGGCCTGGAGAACTAGAGAA TGTGAAAGGAGAAGAGCCTGAAGTG TGTTCGTGGGCCGGATTAGTCCCTCAGAGCCACCCCTAAAGAGCTA TCTCTCGGGTCAATTCGTCCTTCCCTCAGAGCCACCCCTAAAGAGTTC CTTTGATATTTTCAACGCAGCCCTTTTTTTTTT
2
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Fig. 1. Correlation between microRNA binding site polymorphisms and age at stroke onset (AA, major homozygote; Aa, heterozygote; aa, minor homozygote).
3.2. MicroRNA binding site polymorphisms and recurrence risk of stroke and its subtypes
Table 3 Association of microRNA binding site polymorphisms with stroke recurrence. Genotype
The clinical characteristics of 610 ischemic stroke patients for the prognosis analysis was listed in Table 2. Of these, 422 patients (69.2%) were males, and 411 (67.4%) were hypertensive patients. At the end of the follow up period, 175 people had a recurrent stroke. As indicated in Table 2, hypertension and male were observed to increase the recurrence risk of ischemic stroke (P < .05). The relationship between microRNA binding site polymorphisms and the recurrence risk was shown in Table 3. As a result, only ADIPOR2 rs12342 was significantly associated with stroke recurrence (GG vs. AA: P = .025; GA vs. AA: P = .011; GG/GA vs. AA: P = .004, Fig. 2), while the other genetic variants from CXCR2, TLR4, MMP-2 and MMP-9 were not associated with recurrence risk. Then, Cox regression analysis was applied to calculate the association between ADIPOR2 rs12342 polymorphism and stroke recurrence risk for different genetic models. Cox regression analysis revealed a similar result that rs12342
rs1126579 TT CT CC rs11536889 GG CG CC rs12342 AA GA GG AA GG/GA rs7201 AA CA CC rs1056628 AA
Table 2 Clinical characteristics of stroke patients. Variable
Age ≤55 > 55 Sex Male Female Diabetes No Yes Hypertension No Yes Hyperlipidemia No Yes Smoking No Yes Drinking No Yes TOAST LAA SVO
Patients N= 610
Recurrence N=175
172 438
44 131
422 188
131 44
382 228
106 69
199 411
44 131
326 284
94 81
380 230
110 65
478 132
133 42
391 219
113 62
Patients
Recurrence
Log-rank P
235 288 87
65 91 19
0.758 0.226
369 211 30
108 59 8
0.940 0.849
197 299 114 197 413
74 76 25 74 101
328 239 43
91 72 12
610
175
0.011 0.025 0.004
0.534 0.827
Log-rank P
was associated with the recurrence risk of ischemic stroke under homozygous, heterozygous and dominant models (Table 4). Meantime, it indicated that ADIPOR2 rs12342 was an independent protective factor for stroke recurrence (HR = 0.638, 95% CI = 0.472–0.864, Table 5). Furthermore, the Bonferroni correction test was used to control for multiple comparisons. We defined the statistical significance level at 0.0125 (0.05/4 genetic models = 0.0125) and found that ADIPOR2 rs12342 was still significantly associated with stroke recurrence (GA vs. AA: P = .011, GA + GG vs. AA: P = .004). Subsequent subgroup analysis based on ischemic stroke subtype, we observed that the rs12342 GG/GA genotype was associated with a decreased recurrence risk for small-vessel disease subtype, but not large-artery atherosclerosis (SVD: P = .010, LAA: P = .068, Table 6 and Fig. 2). In addition, by using logistic regression analysis and ROC curves, we evaluated the potential of ADIPOR2 rs12342 to improve the identification of ischemic stroke recurrence. As shown in Fig. 3, the AUC was 57.9% by using clinical factors, but with the addition of the SNP, the AUC was improved to 61.0%, which also supported prognostic impact of ADIPOR2 rs12342 in predicting stroke recurrence.
0.120
0.041
0.429
0.032
0.665
0.937
0.531
0.138
3
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Fig. 2. Kaplan-Meier survival plots for stroke recurrence based on ADIPOR2 rs12342 genotypes. A recurrence plot under dominant model. B recurrence plot for small-vessel occlusion subtype. Table 4 Association between ADIPOR2 rs12342 and stroke recurrence. Genotype
Patients
Recurrence
P
HR
Table 6 Stratified analysis of ADIPOR2 rs12342 genotypes associated with stroke recurrence.
(95 % CI)a
Variable Genotypic model AA GA GG
197 299 114
74 76 25
0.011 0.013
0.658 0.558
0.476-0.910 0.352-0.883
Dominant model GA+GG vs AA
101/413
74/197
0.004
0.638
0.472-0.864
Recessive model GG vs GA+AA
25/114
150/496
0.129
0.719
0.469-1.101
Total Age ≤55 > 55 Sex Male Female Diabetes No Yes Hypertension No Yes Hyperlipidemia No Yes Drinking No Yes Smoking No Yes TOAST SVO LAA
a Adjusted for age, sex, hypertension, diabetes, hyperlipidemia, smoking and drinking.
Table 5 Multivariate cox regression analysis for recurrence. Variables
P
HR
95% CI
Age Sex Diabetes Hypertension Hyperlipidemia Drinking Smoking rs12342 (GA + GG vs AA)
0.079 0.014 0.406 0.030 0.972 0.793 0.611 0.004
1.014 1.580 1.141 1.464 1.006 1.056 0.910 0.638
0.998–1.029 1.095–2.280 0.836–1.557 1.038–2.065 0.736–1.374 0.704–1.582 0.631–1.310 0.472–0.864
3.3. Stratification analysis for ADIPOR2 rs12342
Genotype (recurrence/patients)
P
HR (95 % CI)a
GA+GG
AA
101/413
74/197
24/113 77/300
20/59 54/138
0.071 0.022
0.569 (0.308-1.050) 0.662 (0.465-0.942)
78/288 23/125
53/134 21/63
0.018 0.070
0.654 (0.460-0.930) 0.564 (0.303-1.048)
63/258 38/155
43/124 31/73
0.054 0.020
0.681 (0.461-1.007) 0.563 (0.346-0.915)
25/137 76/276
19/62 55/135
0.168 0.009
0.649 (0.351-1.200) 0.628 (0.442-0.891)
54/214 47/199
40/112 34/85
0.117 0.009
0.720 (0.477-1.085) 0.552 (0.352-0.864)
78/324 23/89
55/154 19/43
0.024 0.117
0.642 (0.438-0.942) 0.610 (0.328-1.133)
65/253 36/160
45/127 29/70
0.179 0.004
0.769 (0.524-1.128) 0.480 (0.291-0.793)
31/142 70/271
31/77 43/120
0.010 0.068
0.516 (0.311-0.855) 0.698 (0.474-1.026)
a Adjusted for age, sex, hypertension, diabetes, hyperlipidemia, smoking and drinking.
Stratified analyses by age, sex, diabetes, hypertension, hyperlipidemia, drinking and smoking status for ADIPOR2 rs12342 polymorphism were shown in Table 6. The decreased recurrence risk for rs12342 GG/GA genotype was more evident among patients with old age and smoking habit (HR = 0.662, 95% CI = 0.465–0.942; HR = 0.480, 95% CI = 0.291–0.793). Additionally, we found that this decreased risk was more pronounced in the subjects with diabetes, hypertension and hyperlipidemia. (HR = 0.563, 95% CI = 0.346–0.915; HR = 0.628, 95% CI = 0.442–0.891; HR = 0.552, 95% CI = 0.352–0.864).
4. Discussion To the best of our knowledge, this is the first study to investigate the relationship of five microRNA binding site polymorphisms in immunoinflammatory genes (CXCR2 rs1126579, TLR4 rs11536889, ADIPOR2 rs12342, MMP-2 rs7201 and MMP-9 rs1056628) with stroke onset and recurrence in the northern Chinese population. Our results found that the ADIPOR2 rs12342 polymorphism was significantly associated with recurrence risk, but not the age onset of 4
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Fig. 3. Receiver operating characteristic curves for prediction of stroke recurrence based on clinical variables; clinical variables plus ADIPOR2 rs12342 genotypes.
Furthermore, bioinformatics analysis showed that rs12342 is located in the miR-1197 recognition sequence and can alter the mRNA-miRNA interaction (http://mirdsnp.ccr.buffalo.edu). Further functional researches are needed to verify our hypothesis and explore the underlying molecular mechanism. In addition to ADIPOR2 rs12342, we also investigated the genetic variants within CXCR2, TLR4, MMP-2 and MMP-9. CXCR2 is highly expressed in neutrophils, mediates neutrophil recruitment into atherosclerotic plaque, and thus results in vascular inflammation and plaque destabilization [31]. Regarding to rs1126579 within 3′ untranslated region of CXCR2, it is located in the binding site of miR-516a-3p and can affect the CXCR2 expression through bioinformatics analysis, which has already been confirmed in lung cancer tissues [32]. TLR4 is a wellknown inflammation-related molecule and expressed by murine macrophage and lipid-rich atherosclerotic plaques in human [33]. The activated TLR4 may initiate an inflammatory signaling cascade and induce the production of cytokines and proteases, such as MIP-1α, MIP-2 and MCP-1, which play an important role in the deterioration of atherosclerotic cardiovascular disease [34]. Moreover, Sato et al. found that the C variant of TLR4 rs11536889 lost a motif binding with miR642a and miR-1236, and thus leaded to translational regulation of TLR4 expression [35]. As for gelatinases including MMP-2 and MMP-9, they have the ability to activate many pro-inflammatory factors as IL-1, CXCL-8 and TNF-α, digest type IV collagen and facilitate to cross the endothelium by leukocyte, which in turn cause the spreading of inflammatory process [36]. Also, pretreatment of neurons with selective MMP-2/9 inhibitor could significantly decrease gelatinase activity, reduce neuronal apoptosis and promote neuronal survival after oxygenglucose deprivation [37]. With regard to MMP-2 rs7201, it is predicted to be within the microRNA-520 binding site and the reporter assay showed that the variant C allele had a higher expression level than A allele [38]. Unfortunately, in our current prospective study, we have not observed the association between above three polymorphisms and the recurrence risk or age of stroke onset. Additionally, Yuan et al. reported that a potential functional polymorphism rs1056628 at miR491-5p binding site of MMP-9 conferred an increased risk for
ischemic stroke. A 36.2% decreased recurrence risk was observed in patients with GG/GA genotype within rs12342 compared with AA genotype, suggesting that the G allele may be a protective factor for stroke recurrence. Moreover, multivariate Cox regression analysis indicated that the rs12342 GG/GA genotype was independently associated with stroke recurrence, even after Bonferroni correction. Meantime, by using ROC curves, the observed improvement of discrimination of stroke recurrence by adding genetic factors supported prognostic impact of ADIPOR2 rs12342 and potential clinical application. Moreover, we performed the subgroup analysis based on stroke subtypes and found a more evident protective effect of the rs12342 GG/ GA genotype on SVO subtype. SVO stroke patients of G allele carriers had a 48.4% reduction in recurrence risk than the patients of AA genotype. In addition, the stratified analyses demonstrated that the decreased risk was more prominent for the rs12342 GG/GA genotype in the patients with old age, smoking habit and comorbidities. In total, the above findings indicated that ADIPOR2 rs12342 polymorphism may be a new genetic biomarker and potential therapeutic target for ischemic stroke recurrence. How can we explain the association of ADIPOR2 rs12342 polymorphism with stroke recurrence? Growing studies suggested that adiponectin exerted anti-inflammatory and atheroprotective effects through its receptors, ADIPOR1 and ADIPOR2 [26]. Furthermore, overexpression of ADIPOR2 may potentiate the anti-inflammatory action of globular adiponectin via p38 AMPK/PPAR-α pathway in vascular endothelial cells [27]. Meantime, by targeting ADIPOR2, micro-499a and micro-375 can regulate cytokines such as TNF-α and IL-6, induce endothelial to mesenchymal transition, and promote vascular inflammation and atherosclerosis development [28,29]. In addition, there existed less ADIPOR2 in unstable carotid atherosclerotic plaques, indicating that decreased downstream signaling of ADIPOR2 may cause adiponectin resistance and accumulation of pro-inflammatory cytokines, leading to plaques vulnerable to rupture [30]. As for rs12342 within ADIPOR2, it located in the 3′ untranslated region and cannot change amino acid sequence. However, it may affect the stability and translation of the ADIPOR2 mRNA and play a vital role in gene expression. 5
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atherosclerotic cerebral infarction [22]. However, in our study, no polymorphism was detected at this locus for 657 patients from northern Chinese population. The major strength of our study is the design of prospective investigation with an average 42 months of follow-up. Moreover, our findings are biologically reasonable with regard to the putative function of these genetic polymorphisms on microRNA binding sites. Besides, a wide range of clinical data was collected such as hypertension, diabetes, smoking and drinking, which allowed us to evaluate the independent effect of these polymorphisms for stroke recurrence. At the same time, certain limitations must be acknowledged. First, our study was a singlecenter study with homogenous ethnic background and relatively small sample size. Thus, the studies with larger sample sizes and other ethnic populations are wanted to replicate our findings. Second, some clinical rating scales for stroke prognosis such as Barthel index and mRS scores were unavailable. Besides, the detailed individual data related to drug and lifestyle interventions were absent. In further researches, more detailed personal information and clinical scales will be needed, which would allow for more precise adjusted estimates. Lastly, our study only included two most common subtypes of ischemic stroke (LAA and SVO), and this may restrict the general application to the other three stroke subtypes. In conclusion, our results suggested that ADIPOR2 rs12342 can predict the recurrence of ischemic stroke. More studies are needed to confirm our findings and explore the potential molecular mechanism.
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Genomics journal homepage: www.elsevier.com/locate/ygeno
Original Article
Association between microRNA binding site polymorphisms in immunoinflammatory genes and recurrence risk of ischemic stroke Ruixia Zhu, Yating Zhao, Tongling Xiao, Qianwen Wang, Xu Liu
⁎
Department of Neurology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
A R T I C LE I N FO
A B S T R A C T
Keywords: microRNA Polymorphism Ischemic stroke Prognosis
MicroRNA binding site polymorphisms in immunoinflammatory genes have been implicated as candidate biomarkers for prediction of complex human diseases. However, the roles of microRNA binding site polymorphisms in stroke onset and prognosis remain unclear. Thus, for the first time, five potential functional polymorphisms in immunoinflammatory genes (CXCR2 rs1126579, TLR4 rs11536889, ADIPOR2 rs12342, MMP-2 rs7201 and MMP-9 rs1056628) were genotyped in 657 patients with ischemic stroke. These five polymorphisms were not related with age onset of ischemic stroke. However, we found that ADIPOR2 rs12342 was significantly associated with a decreased recurrence risk, especially for the patients with small-vessel disease. Moreover, by using multivariate Cox regression, the variant genotype GG/GA of rs12342 was observed as an independent protective factor for stroke recurrence, even after Bonferroni correction. In addition, after the addition of rs12342 in the model with clinical factors, the new model showed the improved discriminatory ability to predict stroke recurrence. In short, our results suggested that ADIPOR2 rs12342 may be a novel genetic biomarker and therapeutic target for ischemic stroke recurrence. Further studies are required to replicate our findings and clarify the potential biological mechanism.
1. Introduction As a major health threat worldwide, ischemic stroke is a leading cause of long-term disability and mortality in adults [1]. As the aging of the population, ischemic stroke burden continues to increase globally and the American Heart Association predicts that the direct stroke-related medical costs will reach $183 billion by 2030 [2,3]. Due to rapid advances in medical technology, stroke mortality has decreased and most patients can survive after the first stroke. Unfortunately, the survivors of ischemic stroke would face a higher risk of recurrent stroke, which is more likely to be costly, disabling and fatal [4]. Thus, discovery of novel biomarkers to identify stroke patients at an imminent risk of recurrence is urgently needed to improve stroke prevention and prognosis. Conventional risk factors that may affect the susceptibility and prognosis of ischemic stroke such as hypertension, diabetes and smoking are well investigated, but much more remains unexplained [5,6]. Genetic factors, indicated by evidence from case-control, twin and family-based studies, would result in a predisposition to ischemic stroke [7,8]. Immunoinflammation is an essential process in the pathophysiology of ischemic stroke. Some inflammatory markers, such as
C-reactive protein, IL-6 and lipoprotein-associated phospholipase A2, have been associated with stroke risk and prognosis [9]. Immunemediated inflammation may play an important role in arterial endothelial injury, vascular inflammation and arteriosclerosis [10,11]. Moreover, the immune response to acute cerebral ischemia is a major factor in stroke outcome and anti-inflammatory intervention has the potential of improving the prognosis in experimental stroke [12,13]. Thus, genetic variants involved in immunoinflammatory responses are under investigation to find the relationship with the susceptibility and recurrence of ischemic stroke [14–16]. MicroRNA binding site polymorphisms are though as a group of potential functional polymorphisms, which can affect the expression of target genes [17,18]. Moreover, these polymorphisms may change the individual susceptibility and prognosis to the diseases [19,20]. Recent studies have demonstrated that microRNA binding site polymorphisms in immunoinflammatory genes were related with ischemic stroke susceptibility [21,22]. However, the roles of microRNA binding site polymorphisms in stroke onset and prognosis remain unclear. Thus, we performed a prospective cohort study to investigate the relationship between five potential functional polymorphisms in immunoinflammatory genes (CXCR2 rs1126579, TLR4 rs11536889, ADIPOR2
⁎ Corresponding author at: Department of Neurology, First Affiliated Hospital of China Medical University, No. 155 North Nanjing Street, Shenyang 110001, Liaoning, China. E-mail address: [email protected] (X. Liu).
https://doi.org/10.1016/j.ygeno.2019.12.020 Received 13 September 2019; Received in revised form 14 December 2019; Accepted 25 December 2019 0888-7543/ © 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Ruixia Zhu, et al., Genomics, https://doi.org/10.1016/j.ygeno.2019.12.020
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120 s. Next, the LDR reaction contained the following: 2 μl of PCR product, 0.4 μl of individual probe, 1 μl 10× ligation buffer, 0.25 μl Taq DNA ligase and 6 μl double-distilled water. The cycling parameters were set as: 94 °C for 60 s; 38 cycles× 56 °C for 240 s. Finally, the LDR product was analyzed using ABI 3730XL Sequencer and Gene-Mapper software. In addition, 5% of our samples were randomly chosen for validation, and the concordance rate was 100%.
rs12342, MMP-2 rs7201 and MMP-9 rs1056628) and the clinical behavior of ischemic stroke in Chinese population. 2. Materials and methods 2.1. Study populations A total of 657 patients with ischemic stroke were enrolled prospectively from the First Affiliated Hospital of China Medical University. All patients suffered from a focal neurological deficit > 24 h and underwent magnetic resonance imaging or computed tomography to confirm the diagnosis. With regard to TOAST classification, ischemic stroke can be divided into 5 types: large-artery atherosclerosis (LAA), small-vessel occlusion (SVO), cardioembolism, stroke with undetermined etiology and stroke with other determined etiology [23]. Only the stroke patients with LAA and SVO subtypes were included in our study, while other subtypes were excluded. Subsequent follow-up was carried out every three months until ischemic stroke recurrence or the last follow-up period (December 2018) by telephone contact or clinical visit using a standard questionnaire. Finally, among 657 patients with ischemic stroke, 610 completed the follow-up with an average 42 months and 47 (7.2%) were lost during the follow-up. The study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the First Affiliated Hospital of China Medical university. All participants were given written informed consent.
2.3. Statistical analysis A one-way analysis of variance (ANOVA) was used to assess whether presence of genetic polymorphisms could influence age of stroke onset. The recurrence time was determined from the diagnosis date of ischemic stroke to the date of stroke recurrence or the last time of follow-up. The recurrence curves were constructed by the Kaplan-Meier method, and the difference between recurrence time was evaluated using the log rank test. The hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by Cox proportional hazards regression model with adjustments for age, sex, diabetes, hypertension, hyperlipidemia, drinking and smoking. Moreover, Bonferroni adjustment was applied to correct for multiple comparisons. Receiver operating characteristic (ROC) curve was constructed from the logistic regression model, and the area under the curve (AUC) was used to assess the predictive performance of the model. All the statistical analyses were performed with SPSS 17.0 software. A P value of < 0.05 was considered statistically significant.
2.2. DNA extraction and genotyping 3. Results
Genomic DNA was extracted from blood samples according to standard procedures and stored at −20 °C. Genotyping was performed using the polymerase chain reaction-ligase detection reaction (PCRLDR) method [24,25]. The primer and probe sequences of PCR-LDR were shown in Table 1. The multiple PCR amplification was performed within the mixture of 1 μl genomic DNA sample, 1 μl of individual primer, 3.0 mM Mg2+, 0.3 mM dNTPs, 1 × GC-I buffer, 1 U Hot-Start Taq polymerase. The cycling parameters were as follows: 95 °C for 120 s; 11 cycles × (94 °C for 20 s, 65 °C for 40 s, and 72 °C for 90 s); 24 cycles× (94 °C for 20 s, 59 °C for 30 s, and 72 °C for 90 s); 72 °C for
3.1. MicroRNA binding site polymorphisms and age onset of stroke A total of 657 patients with ischemic stroke were included in the current study. We did not observe the association between microRNA binding site polymorphisms in immunoinflammatory genes and the age onset of ischemic stroke (P > .05), which suggested that these genetic variants cannot predict the onset time of ischemic stroke (Fig. 1).
Table 1 Primer sequences and probes of microRNA binding site polymorphisms. Polymorphisms
Primer sequences and probes
rs1056628F rs1056628R rs1056628RA rs1056628RC rs1056628RP rs1126579F rs1126579R rs1126579FC rs1126579FP rs1126579FT rs11536889F rs11536889R rs11536889FC rs11536889FG rs11536889FP rs12342F rs12342R rs12342FC rs12342FP rs12342FT rs7201F rs7201R rs7201FA rs7201FC rs7201FP
TCTGCCAGGACCGCTTCTACTG TCCTCCCTTTCCTCCAGAACAGA TGTTCGTGGGCCGGATTAGTTCCCCAGGGTTGGTCCCTGT TCTCTCGGGTCAATTCGTCCTTTCCCCAGGGTTGGTCCCTGG GGGGATTTACATGGCACTGCCTTTTTTTTT TTTCGCCATGGACTCCTCAAGAT AGGCACCAGGGCAAGCTTTCTA TTCCGCGTTCGGACTGATATCCCCATTGTGGTCACAGGATGC AGAGGAGGCCACGTTCTTACTAGTTTTTTTTTTTTTT TACGGTTATTCGGGCTCCTGTCCCCATTGTGGTCACAGGACGT CCTGTTGGGCAATGCTCCTTGA TTTCTGAGGAGGCTGGATGAACA TACGGTTATTCGGGCTCCTGTGCTCCTTGACCACATTTTGGGTAC TTCCGCGTTCGGACTGATATGCTCCTTGACCACATTTTGGGTAG AGTGGATGTTATCAYTGAGAAAACAATGTTTTTTTTTTTTTTTTTTT TCTTGGCCCATAGGTGAACCAC TCCCACCTTTTGCTGGAGATTG TCTCTCGGGTCAATTCGTCCTTGTCCTGAGCATGGGGACTTGC GTCCTCAGTAGGTGTTTGGGAATRTGTTTTTTTT TGTTCGTGGGCCGGATTAGTGTCCTGAGCATGGGGACTCGT CCGGGCCTGGAGAACTAGAGAA TGTGAAAGGAGAAGAGCCTGAAGTG TGTTCGTGGGCCGGATTAGTCCCTCAGAGCCACCCCTAAAGAGCTA TCTCTCGGGTCAATTCGTCCTTCCCTCAGAGCCACCCCTAAAGAGTTC CTTTGATATTTTCAACGCAGCCCTTTTTTTTTT
2
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Fig. 1. Correlation between microRNA binding site polymorphisms and age at stroke onset (AA, major homozygote; Aa, heterozygote; aa, minor homozygote).
3.2. MicroRNA binding site polymorphisms and recurrence risk of stroke and its subtypes
Table 3 Association of microRNA binding site polymorphisms with stroke recurrence. Genotype
The clinical characteristics of 610 ischemic stroke patients for the prognosis analysis was listed in Table 2. Of these, 422 patients (69.2%) were males, and 411 (67.4%) were hypertensive patients. At the end of the follow up period, 175 people had a recurrent stroke. As indicated in Table 2, hypertension and male were observed to increase the recurrence risk of ischemic stroke (P < .05). The relationship between microRNA binding site polymorphisms and the recurrence risk was shown in Table 3. As a result, only ADIPOR2 rs12342 was significantly associated with stroke recurrence (GG vs. AA: P = .025; GA vs. AA: P = .011; GG/GA vs. AA: P = .004, Fig. 2), while the other genetic variants from CXCR2, TLR4, MMP-2 and MMP-9 were not associated with recurrence risk. Then, Cox regression analysis was applied to calculate the association between ADIPOR2 rs12342 polymorphism and stroke recurrence risk for different genetic models. Cox regression analysis revealed a similar result that rs12342
rs1126579 TT CT CC rs11536889 GG CG CC rs12342 AA GA GG AA GG/GA rs7201 AA CA CC rs1056628 AA
Table 2 Clinical characteristics of stroke patients. Variable
Age ≤55 > 55 Sex Male Female Diabetes No Yes Hypertension No Yes Hyperlipidemia No Yes Smoking No Yes Drinking No Yes TOAST LAA SVO
Patients N= 610
Recurrence N=175
172 438
44 131
422 188
131 44
382 228
106 69
199 411
44 131
326 284
94 81
380 230
110 65
478 132
133 42
391 219
113 62
Patients
Recurrence
Log-rank P
235 288 87
65 91 19
0.758 0.226
369 211 30
108 59 8
0.940 0.849
197 299 114 197 413
74 76 25 74 101
328 239 43
91 72 12
610
175
0.011 0.025 0.004
0.534 0.827
Log-rank P
was associated with the recurrence risk of ischemic stroke under homozygous, heterozygous and dominant models (Table 4). Meantime, it indicated that ADIPOR2 rs12342 was an independent protective factor for stroke recurrence (HR = 0.638, 95% CI = 0.472–0.864, Table 5). Furthermore, the Bonferroni correction test was used to control for multiple comparisons. We defined the statistical significance level at 0.0125 (0.05/4 genetic models = 0.0125) and found that ADIPOR2 rs12342 was still significantly associated with stroke recurrence (GA vs. AA: P = .011, GA + GG vs. AA: P = .004). Subsequent subgroup analysis based on ischemic stroke subtype, we observed that the rs12342 GG/GA genotype was associated with a decreased recurrence risk for small-vessel disease subtype, but not large-artery atherosclerosis (SVD: P = .010, LAA: P = .068, Table 6 and Fig. 2). In addition, by using logistic regression analysis and ROC curves, we evaluated the potential of ADIPOR2 rs12342 to improve the identification of ischemic stroke recurrence. As shown in Fig. 3, the AUC was 57.9% by using clinical factors, but with the addition of the SNP, the AUC was improved to 61.0%, which also supported prognostic impact of ADIPOR2 rs12342 in predicting stroke recurrence.
0.120
0.041
0.429
0.032
0.665
0.937
0.531
0.138
3
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Fig. 2. Kaplan-Meier survival plots for stroke recurrence based on ADIPOR2 rs12342 genotypes. A recurrence plot under dominant model. B recurrence plot for small-vessel occlusion subtype. Table 4 Association between ADIPOR2 rs12342 and stroke recurrence. Genotype
Patients
Recurrence
P
HR
Table 6 Stratified analysis of ADIPOR2 rs12342 genotypes associated with stroke recurrence.
(95 % CI)a
Variable Genotypic model AA GA GG
197 299 114
74 76 25
0.011 0.013
0.658 0.558
0.476-0.910 0.352-0.883
Dominant model GA+GG vs AA
101/413
74/197
0.004
0.638
0.472-0.864
Recessive model GG vs GA+AA
25/114
150/496
0.129
0.719
0.469-1.101
Total Age ≤55 > 55 Sex Male Female Diabetes No Yes Hypertension No Yes Hyperlipidemia No Yes Drinking No Yes Smoking No Yes TOAST SVO LAA
a Adjusted for age, sex, hypertension, diabetes, hyperlipidemia, smoking and drinking.
Table 5 Multivariate cox regression analysis for recurrence. Variables
P
HR
95% CI
Age Sex Diabetes Hypertension Hyperlipidemia Drinking Smoking rs12342 (GA + GG vs AA)
0.079 0.014 0.406 0.030 0.972 0.793 0.611 0.004
1.014 1.580 1.141 1.464 1.006 1.056 0.910 0.638
0.998–1.029 1.095–2.280 0.836–1.557 1.038–2.065 0.736–1.374 0.704–1.582 0.631–1.310 0.472–0.864
3.3. Stratification analysis for ADIPOR2 rs12342
Genotype (recurrence/patients)
P
HR (95 % CI)a
GA+GG
AA
101/413
74/197
24/113 77/300
20/59 54/138
0.071 0.022
0.569 (0.308-1.050) 0.662 (0.465-0.942)
78/288 23/125
53/134 21/63
0.018 0.070
0.654 (0.460-0.930) 0.564 (0.303-1.048)
63/258 38/155
43/124 31/73
0.054 0.020
0.681 (0.461-1.007) 0.563 (0.346-0.915)
25/137 76/276
19/62 55/135
0.168 0.009
0.649 (0.351-1.200) 0.628 (0.442-0.891)
54/214 47/199
40/112 34/85
0.117 0.009
0.720 (0.477-1.085) 0.552 (0.352-0.864)
78/324 23/89
55/154 19/43
0.024 0.117
0.642 (0.438-0.942) 0.610 (0.328-1.133)
65/253 36/160
45/127 29/70
0.179 0.004
0.769 (0.524-1.128) 0.480 (0.291-0.793)
31/142 70/271
31/77 43/120
0.010 0.068
0.516 (0.311-0.855) 0.698 (0.474-1.026)
a Adjusted for age, sex, hypertension, diabetes, hyperlipidemia, smoking and drinking.
Stratified analyses by age, sex, diabetes, hypertension, hyperlipidemia, drinking and smoking status for ADIPOR2 rs12342 polymorphism were shown in Table 6. The decreased recurrence risk for rs12342 GG/GA genotype was more evident among patients with old age and smoking habit (HR = 0.662, 95% CI = 0.465–0.942; HR = 0.480, 95% CI = 0.291–0.793). Additionally, we found that this decreased risk was more pronounced in the subjects with diabetes, hypertension and hyperlipidemia. (HR = 0.563, 95% CI = 0.346–0.915; HR = 0.628, 95% CI = 0.442–0.891; HR = 0.552, 95% CI = 0.352–0.864).
4. Discussion To the best of our knowledge, this is the first study to investigate the relationship of five microRNA binding site polymorphisms in immunoinflammatory genes (CXCR2 rs1126579, TLR4 rs11536889, ADIPOR2 rs12342, MMP-2 rs7201 and MMP-9 rs1056628) with stroke onset and recurrence in the northern Chinese population. Our results found that the ADIPOR2 rs12342 polymorphism was significantly associated with recurrence risk, but not the age onset of 4
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Fig. 3. Receiver operating characteristic curves for prediction of stroke recurrence based on clinical variables; clinical variables plus ADIPOR2 rs12342 genotypes.
Furthermore, bioinformatics analysis showed that rs12342 is located in the miR-1197 recognition sequence and can alter the mRNA-miRNA interaction (http://mirdsnp.ccr.buffalo.edu). Further functional researches are needed to verify our hypothesis and explore the underlying molecular mechanism. In addition to ADIPOR2 rs12342, we also investigated the genetic variants within CXCR2, TLR4, MMP-2 and MMP-9. CXCR2 is highly expressed in neutrophils, mediates neutrophil recruitment into atherosclerotic plaque, and thus results in vascular inflammation and plaque destabilization [31]. Regarding to rs1126579 within 3′ untranslated region of CXCR2, it is located in the binding site of miR-516a-3p and can affect the CXCR2 expression through bioinformatics analysis, which has already been confirmed in lung cancer tissues [32]. TLR4 is a wellknown inflammation-related molecule and expressed by murine macrophage and lipid-rich atherosclerotic plaques in human [33]. The activated TLR4 may initiate an inflammatory signaling cascade and induce the production of cytokines and proteases, such as MIP-1α, MIP-2 and MCP-1, which play an important role in the deterioration of atherosclerotic cardiovascular disease [34]. Moreover, Sato et al. found that the C variant of TLR4 rs11536889 lost a motif binding with miR642a and miR-1236, and thus leaded to translational regulation of TLR4 expression [35]. As for gelatinases including MMP-2 and MMP-9, they have the ability to activate many pro-inflammatory factors as IL-1, CXCL-8 and TNF-α, digest type IV collagen and facilitate to cross the endothelium by leukocyte, which in turn cause the spreading of inflammatory process [36]. Also, pretreatment of neurons with selective MMP-2/9 inhibitor could significantly decrease gelatinase activity, reduce neuronal apoptosis and promote neuronal survival after oxygenglucose deprivation [37]. With regard to MMP-2 rs7201, it is predicted to be within the microRNA-520 binding site and the reporter assay showed that the variant C allele had a higher expression level than A allele [38]. Unfortunately, in our current prospective study, we have not observed the association between above three polymorphisms and the recurrence risk or age of stroke onset. Additionally, Yuan et al. reported that a potential functional polymorphism rs1056628 at miR491-5p binding site of MMP-9 conferred an increased risk for
ischemic stroke. A 36.2% decreased recurrence risk was observed in patients with GG/GA genotype within rs12342 compared with AA genotype, suggesting that the G allele may be a protective factor for stroke recurrence. Moreover, multivariate Cox regression analysis indicated that the rs12342 GG/GA genotype was independently associated with stroke recurrence, even after Bonferroni correction. Meantime, by using ROC curves, the observed improvement of discrimination of stroke recurrence by adding genetic factors supported prognostic impact of ADIPOR2 rs12342 and potential clinical application. Moreover, we performed the subgroup analysis based on stroke subtypes and found a more evident protective effect of the rs12342 GG/ GA genotype on SVO subtype. SVO stroke patients of G allele carriers had a 48.4% reduction in recurrence risk than the patients of AA genotype. In addition, the stratified analyses demonstrated that the decreased risk was more prominent for the rs12342 GG/GA genotype in the patients with old age, smoking habit and comorbidities. In total, the above findings indicated that ADIPOR2 rs12342 polymorphism may be a new genetic biomarker and potential therapeutic target for ischemic stroke recurrence. How can we explain the association of ADIPOR2 rs12342 polymorphism with stroke recurrence? Growing studies suggested that adiponectin exerted anti-inflammatory and atheroprotective effects through its receptors, ADIPOR1 and ADIPOR2 [26]. Furthermore, overexpression of ADIPOR2 may potentiate the anti-inflammatory action of globular adiponectin via p38 AMPK/PPAR-α pathway in vascular endothelial cells [27]. Meantime, by targeting ADIPOR2, micro-499a and micro-375 can regulate cytokines such as TNF-α and IL-6, induce endothelial to mesenchymal transition, and promote vascular inflammation and atherosclerosis development [28,29]. In addition, there existed less ADIPOR2 in unstable carotid atherosclerotic plaques, indicating that decreased downstream signaling of ADIPOR2 may cause adiponectin resistance and accumulation of pro-inflammatory cytokines, leading to plaques vulnerable to rupture [30]. As for rs12342 within ADIPOR2, it located in the 3′ untranslated region and cannot change amino acid sequence. However, it may affect the stability and translation of the ADIPOR2 mRNA and play a vital role in gene expression. 5
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atherosclerotic cerebral infarction [22]. However, in our study, no polymorphism was detected at this locus for 657 patients from northern Chinese population. The major strength of our study is the design of prospective investigation with an average 42 months of follow-up. Moreover, our findings are biologically reasonable with regard to the putative function of these genetic polymorphisms on microRNA binding sites. Besides, a wide range of clinical data was collected such as hypertension, diabetes, smoking and drinking, which allowed us to evaluate the independent effect of these polymorphisms for stroke recurrence. At the same time, certain limitations must be acknowledged. First, our study was a singlecenter study with homogenous ethnic background and relatively small sample size. Thus, the studies with larger sample sizes and other ethnic populations are wanted to replicate our findings. Second, some clinical rating scales for stroke prognosis such as Barthel index and mRS scores were unavailable. Besides, the detailed individual data related to drug and lifestyle interventions were absent. In further researches, more detailed personal information and clinical scales will be needed, which would allow for more precise adjusted estimates. Lastly, our study only included two most common subtypes of ischemic stroke (LAA and SVO), and this may restrict the general application to the other three stroke subtypes. In conclusion, our results suggested that ADIPOR2 rs12342 can predict the recurrence of ischemic stroke. More studies are needed to confirm our findings and explore the potential molecular mechanism.
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