Association of laboratory parameters and genetic polymorphisms with ischemic stroke in Chinese Han population
- Authors:
- Published online on: March 16, 2021 https://doi.org/10.3892/etm.2021.9921
- Article Number: 490
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Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Stroke is an episode of neurological dysfunction caused by focal cerebral, spinal or retinal infarction, and has become the second leading cause of disability and death in adults worldwide (1,2). Ischemic stroke (IS) is the most common type of stroke. There are multiple risk factors for IS, which include age, sex, body mass index (BMI), hyperlipidemia, hypertension, diabetes, smoking and particulate matter 2.5 pollution (3,4).
Previous studies have examined the roles of polymorphisms in numerous genes involved in the pathogenesis of IS, including C-C motif chemokine 11, paraoxonase 1, angiotensin-converting enzyme (ACE), and methylenetetrahydrofolate reductase (MTHFR) (5-7). It has been reported that the ACE I/D polymorphism is significantly associated with IS in different ethnic groups (8). However, other studies failed to observe this association (9,10). Patients with the MTHFR 677TT genotype have vascular occlusion, infarct and increased levels of blood homocysteine, which form the basis for the association of this genetic polymorphism with hypertension (11). Polymorphism of MTHFR has important roles in hypertension and IS, both of which are caused by atherosclerotic vascular disease (12). Numerous studies have been performed to investigate the potential association between polymorphisms of β fibrinogen (β-Fg) and the risk of IS. However, the results of these studies were inconsistent, and the sample sizes of individual studies were inadequate to draw definite conclusions (13-15). The 4G/5G polymorphism in the promoter of the plasminogen activator inhibitor-1 gene (PAI-1) is one of the most frequently studied (16). A single 4G allele is considered to be a risk factor for coronary artery disease and the 4G/4G genotype is thought to increase the risk of coronary artery disease (17,18). Several studies addressed the association between the 4G/5G polymorphism and stroke, but these results were inconsistent (19,20). Although PAI-1 may be an important factor in the occurrence of IS, the association between PAI-1 gene polymorphisms and the risk of IS has remained to be elucidated. Apolipoprotein E (ApoE) polymorphism involves a single amino substitution and results in three major alleles (ε2, ε3 and ε4) with six corresponding phenotypes (ε2/ε2, ε3/ε3, ε4/ε4, ε2/ε3, ε2/ε4 and ε3/ε4) (21). The relationship between ApoE genotype and stroke is unclear because of inconsistent study results. Certain reports indicated a positive association between ApoE4-containing genotypes and stroke, but others indicated no relationships between ApoE isoforms and dyslipidemia or stroke (22,23). The influence of the gene polymorphisms on clinical laboratory parameters of IS has not been described in the Chinese Han population, to the best of our knowledge.
The aim of the present study was to evaluate potential associations between polymorphisms in six genes, namely ACE D/I, MTHFR C677T, β-Fg A/G, 455/148T/C, PAI-1, 4G/5G and ApoE ε2,3,4, and clinical laboratory parameters of IS in the Chinese Han population. Such data may be used to provide a control range of laboratory parameters according to genotype for the early prevention of IS in patients with diabetes and hyperlipidemia.
Patients and methods
Patients
The medical records of all newly diagnosed patients with proven diabetes and hyperlipidemia who were admitted to Shanghai Tongji Hospital (Shanghai, China) from October 2016 to November 2018 were examined. The present study was approved by the ethics committee of Shanghai Tongji Hospital (Shanghai, China) and was conducted according to the Declaration of Helsinki. All participants provided informed consent in written form. For participants who were unable to communicate, written consent was obtained from their legal relatives.
Patients who met the following criteria were included: i) Fasting blood glucose (FBG) ≥7.0 mmol/l or 2-h oral glucose tolerance test ≥11.1 mmol/l; ii) triglyceride (TG) ≥1.7 mmol/l orlow-density lipoprotein cholesterol (LDL-C) ≥3.37 mmol/l or total cholesterol (CHOL) ≥5.18 mmol/l; iii) a diagnosis of IS meeting the standards of Chinese guidelines for the diagnosis and treatment of acute ischemic stroke in 2014(24), which were issued by Chinese Medical Association; and iv) Chinese Han population and unrelated to other participants in the study.
Patients with a diagnosis of any of the following conditions were excluded: i) Other types of cerebrovascular disease, including intracranial hemorrhage, subarachnoid hemorrhage, cerebrovascular malformation or cerebral aneurysm; and ii) severe systemic diseases, including cancer, severe inflammatory disease or serious chronic diseases (e.g. hepatic failure or renal failure).
The control group comprised 336 individuals without a history of cerebrovascular disease who were physical examined in the hospital during the same period. Age, sex, use of oral contraceptives and history of thrombotic events or drug abuse were recorded. The baseline characteristics of patients and controls are presented in Table SI.
Serum lipid, glucose and transaminase measurement
Blood samples (~3 ml fasting blood) were collected from each study participant and then separated by centrifugation at 840 x g for 10 min in a SPINCHRON™ DLX centrifuge (Beckman Coulter). Serum levels of FBG, CHOL, TG, LDL-C, high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were analyzed by an automatic biochemical analyzer (DXC800; Beckman Coulter).
DNA extraction and genetic analysis
Genomic DNA was extracted from peripheral blood leukocytes using a TIANamp Genomic DNA kit (Tiangen Biotech) following the protocol of the manufacturer. Polymorphisms were genotyped using allele-specific PCR and restriction fragment length polymorphism analysis described in Data S1. PCR primers were synthesized by Sangon Biotech Co., Ltd.; the sequences are listed in Table SII. Amplified PCR products of intron 16 of ACE were separated on a 2% agarose gel (Bio-Rad Laboratories, Inc.) (Fig. 1). The presence of 191-bp fragments indicated the D allele, 480-bp fragments represented the I allele and 191- and 480-bp fragments represented the D/I allele. Amplification products of β-Fg-455 were digested by HaeIII (FD0154; Thermo Fisher Scientific, Inc.) and then separated on a 2% agarose gel (Fig. 1). The presence of 343-, 383- and 575-bp fragments represented the GG allele; 343- and 958-bp fragments represented the AA allele, and 343-, 383-, 575- and 958-bp fragments represented the G/A allele. Amplification products of β-Fg-148 were digested by HindIII (FD0505; Thermo Fisher Scientific, Inc.) (Fig. 1). The presence of 100- and 200-bp fragments represented the CC allele, the presence of 300-bp fragments represented the TT allele and the presence of 100-, 200- and 300-bp fragments represented the T/C allele. Amplification products of MTHFR were digested by HinfI (FD0804; Thermo Fisher Scientific, Inc.) (Fig. 1). The presence of 100- and 200-bp fragments represented the TT allele, 300-bp fragments represented the CC allele and 100-, 200- and 300-bp fragments represented the T/C allele. Amplification products of PAI-1and ApoE ε2,3,4 gene alleles were separated on a 2% agarose gel and subjected to first-generation sequencing by Genewiz, Inc..
Statistical analysis
SPSS statistical software version 21.0 (IBM Corp.) was used for statistical analysis. Pearson's chi-squared test or Fisher's exact test were used for statistical comparisons of count data. Continuous variables are expressed as the mean ± standard deviation. Receiver operating characteristic (ROC) curve analysis was used to analyze laboratory parameters related to IS. Logistic regression was used to analyze the models 1 and 2. P<0.05 was considered to indicate statistical significance.
Results
Relationships between laboratory parameters and genotype and allele frequencies
Table I indicates the associations between laboratory parameters and the ACE I/D, β-Fg-455 A/G and PAI-1 4G/5G gene polymorphisms. The D allele of ACE I/D was associated with high levels of TC and LDL-C, as presented in Table II. Furthermore, a significant association between the β-Fg-455 A/G polymorphism and LDL-C levels and an association between PAI-1 4G/5G and TG were observed (Table I). The frequency of the 4G/5G genotype of PAI-1 4G/5G was highest in the TG <1.70 mmol/l group and the frequency of the 4G/5G genotype was equal to that of the 4G4G genotype in the TG ≥1.70 mmol/l group. However, there were no significant differences in genotype frequency distributions of the MTHFR C677T, β-Fg-148T/C and ApoE ε2-4 polymorphisms for the parameters of FBG, TC, TG and LDL-C (Table I).
 | Table IAssociation of laboratory parameters with genotype frequencies of ACE I/D, MTHFR C677T, β-Fg-455A/G, β-Fg-148T/C, PAI-1 4G/5G and ApoE ε2-4. |
| Table IIAssociation of laboratory parameters with allele frequencies of ACE I/D, MTHFR C677T, β-Fg-455A/G, β-Fg-148T/C, PAI-1 4G/5G and ApoE ε2-4. |
Table SIII indicates the association between the BMI, ACE I/D, β-Fg-455A/G and PAI-1 4G/5G gene polymorphisms. The frequency of the ACE genotype DD in obese (BMI≥28.00 kg/m2) and overweight (28.00>BMI ≥24.00 kg/m2) subjects was higher than that in normal subjects (24.00>BMI≥18.5 kg/m2). As presented in Table SIV, the D allele of the ACE gene was associated with a high BMI. Furthermore, a significant association between β-Fg-455 gene polymorphisms and the BMI was observed (Table SIII). The relationship between the PAI-1 gene and the BMI is presented in Table SIII. The frequency of the AA genotype of the β-Fg-455 gene in obese subjects was ~8% higher than that in normal subjects, while that in overweight subjects was ~6% higher (P<0.05). Furthermore, the frequency of the PAI-1 5G5G genotype in obese and overweight subjects was significantly higher than that in normal subjects (P<0.05). However, there was no significant difference in the MTHFR C677T, β-Fg-148T/C and ApoE ε2-4 genotypes between groups of high/low HDL-C, ALT and AST (Table SIII).
Predictive value of clinical laboratory parameters for IS
As presented in Table III, high levels of FBG, TG and LDL-C were risk factors for IS. The results suggested that the risk of IS increased by 6.47-, 4.64- and 7.62-fold along with each 1-mmol/l increment of FBG, TG and LDL-C, respectively. Age and sex were included for adjusting in model 2 and these risk values increased to 5.38-, 5.41- and 6.21-fold for FGB, TG and LDL, respectively. The results in Table SV suggested that a high BMI is a risk factor for IS. It was indicated that with the increase of the BMI by 1 kg/m2, the risk increased by 2.26-fold. When age and sex were included for adjusting in model 2, the risk increased by 2.35-fold. HDL-C was indicated to be a protective factor against IS. With the increase of HDL-C by 1 mmol/l, the risk of disease was reduced to 27% and after adjustment for age and sex, it was 32%.
ROC curve analysis of laboratory parameters for IS
Area under the curve values at the 95% confidence interval (95% CI) for IS predicted by laboratory parameters were as follows: FBG, 0.828 (0.784-0.867); TC, 0.595 (0.541-0.648); TG, 0.702 (0.650-0.751); LDL-C, 0.638 (0.584-0.689); and BMI, 0.735 (0.685-0.786) (Tables IV, SVI and Fig. S1). It was observed that FBG had better specificity (0.833) and sensitivity (0.694) for predicting IS compared to the other parameters. The optimal cut-off point of FGB for predicting IS was 5.27 mmol/l. Among the five parameters, LDL-C had the highest specificity (0.999) with an optimal cut-off point for predicting IS of 3.36 mmol/l. The sensitivity values of TC, TG, LDL-C and BMI for predicting IS were poor (0.265, 0.471, 0.284 and 0.591, respectively), although their specificity values were better.
The relationships between IS and allele frequencies of ACE I/D, MTHFR C677T, β-Fg-455A/G, β-Fg-148T/C, PAI-1 4G/5G and ApoE ε2-4 genes are presented in Table V and Fig. 2. Significant differences in the genotype frequencies of ACE I/D, β-Fg-455 A/G and β-Fg-148 T/C genes between patients with IS and the control group were present (Fig. 2). However, only the allele frequencies of ACE I/D and β-Fg-148 T/C were significantly different between the two groups (Table V). More specifically, the frequencies of the D allele of ACE I/D and the C allele of β-Fg-148 T/C were higher in the IS group, whereas the frequencies of the I allele of ACE I/D and the T allele of β-Fg-148 T/C in the IS group were lower compared with those in the control group.
| Table VRelationship between ischemic stroke and allele frequencies of ACE I/D, MTHFR C677T, β-Fg-455 A/G, β-Fg-148 T/C, PAI-1 4G/5G and ApoE ε2-4. |
Discussion
Strokes are the second leading cause of death and the leading cause of permanent disability in adults worldwide (25), with IS accounting for 85% of the total number of strokes (26). IS is caused by the occlusion of major arteries or branches of the brain, which leads to vascular occlusion and deprivation of oxygen and energy. This is followed by the formation of reactive oxygen species, then the release of glutamate, the accumulation of intracellular calcium and the induction of inflammatory processes (27). Previous studies have reported that IS is closely related to certain genes, as well as blood glucose and blood lipid levels (28-31). However, it is currently not possible to control or treat stroke at the genetic level. To explore this possibility, the relationships between IS and genetic and laboratory parameters (FBG, TC, TG, LDL-C, HDL-C, ALT, AST and BMI) were examined in the present study.
The results of the present study revealed correlations between IS and the ACE I/D, β-Fg-455A/G and β-Fg-148T/C polymorphisms. Frequencies of both the D allele of ACE I/D and the C allele of β-Fg-148T/C in the IS group were higher than those in the control group, suggesting that IS is closely related to the D allele of those two alleles, which is consistent with the studies performed by Zhao et al (32) and Wu et al (33).
In accordance with the results of a study by Lin et al (30), the present results indicated that FBG was an effective parameter for predicting IS, suggesting that routine monitoring for FBG may effectively control and prevent the progression of IS. In a study performed by Anderson et al (34), hyperglycemia was indicated to affect mitochondrial function in the ischemic penumbra, resulting in cortical acidosis and cell death. Hyperglycemia also impaired cerebrovascular reactivity in the microvasculature, which may disturb reperfusion after recanalization (35). Diabetes or hyperglycemia may alter blood-brain barrier permeability and induce disruption of the blood-brain barrier, which may aggravate the formation of brain edema and lead to hemorrhagic transformation (36). In addition, the results of the present study suggested that hyperlipidemia is a risk factor for IS. Lee et al (31) pointed out that a high TG level is a risk factor for IS and that the risk is 1.28-fold higher than that of individuals with normal TG levels. Lee et al (31) also noted that the presence of LDL-C ≥130 mg/dl may increase the risk of IS. Furthermore, Pawelczyk et al (37) reported a significant increase in the plasma concentration of soluble P-selectin (sP-selectin) in patients with stroke and hyperlipidemia and hyperglycemia compared with normolipidemic/normoglycemic patients with stroke. On the one hand, a strong positive correlation was observed between hyperglycemia and sP-selectin levels, which emphasizes the leading role of hyperglycemia in atherothrombosis progression. On the other hand, hyperlipidemia was also associated with an increase in the plasma sP-selectin level (37). This glycoprotein has a role in stimulating the release of procoagulant microparticles, which induces a procoagulant state (38).
Methods to treat IS mainly comprise initial treatment with intra-arterial thrombolysis, endovascular mechanical thrombectomy and antiplatelet treatment (39). However, such treatments rarely negate the possibility of recurrence of IS. Studying associations of stroke-related genes with blood glucose and blood lipids may offer alternative approaches. The present results suggested that LDL-C and TG were closely related to the ACE I/D, β-Fg-455 A/G and PAI-1 4G/5G polymorphisms, consistent with the results of Li (40) and Guney et al (41). The results of the present study also indicated that hyperlipidemia was correlated with the D allele of ACE I/D, which confirmed the results of Suzuki et al (42) and Lee and Tsai (43), who demonstrated positive associations of hyperlipidemia with the DD genotype and D allele frequency of ACE I/D.
There are certain limitations to the present study. First, the study enrolled patients with IS at a hospital rather than patients from a community-based general population. Furthermore, the study comprised a single population with limited sample size; thus, the results require to be confirmed in multiple centers using larger sample sizes and in different ethnic populations. In addition, the study did not collect data on several other major risk parameters of IS (such as homocysteine, fibrinogen or prothrombin), which should also be examined in future research. Finally, dietary habits exhibited a marked variation among the participants making it is difficult to assess the impact of dietary habits on IS in the present study.
In summary, the present study indicated that the D allele of ACE I/D and the C allele of β-Fg-148 T/C were significantly associated with IS and that the frequency of the D allele of ACE I/D was significantly higher in individuals with hyperlipidemia. High levels of FGB, TG, LDL-C and BMI were risk factors for IS, with optimal predictive cut-off points of 5.27, 1.32 and 3.36 mmol/l and 23.12 kg/m2, respectively. The present results suggested that individuals with hyperlipidemia or a high frequency of the D allele of ACE I/D may be at risk of IS. By contrast, there were no significant differences in TC levels and the MTHFR C677T, PAI-1 4G/5G and ApoE ε2-4 gene polymorphisms between patients with IS and controls. Identifying the relationships among IS, stroke-related genes and blood lipid and blood glucose levels may lead to a better understanding of the pathophysiology of IS in the Chinese Han population and may provide a reasonable control range of laboratory parameters for the prevention of IS in patients with diabetes and hyperlipidemia as early as possible.
Supplementary Material
The experimental details of allele-specific PCR and restriction fragment length polymorphism analysis. Polymorphisms were genotyped using allele-specific PCR and restriction fragment length polymorphism analysis. PCR primers were synthesized by Sangon Biotech Co., Ltd.; the sequences are listed in Table SII. PCR conditions of ACE were as follows: 95˚C for 2 min, followed by 35 cycles at 95˚C for 30 sec, 55˚C for 30 sec, and 72˚C for 30 sec, final step was performed at 72˚C for 5 min. Amplified PCR products of intron 16 of ACE were separated on a 2% agarose gel (Bio-Rad Laboratories, Inc.) (Fig. 1). The presence of 191-bp fragments indicated the D allele, 480-bp fragments represented the I allele and 191- and 480-bp fragments represented the D/I allele. PCR conditions of β-Fg-455 were as follows: 94˚C for 2 min, followed by 35 cycles at 94˚C for 30 sec, 55˚C for 30 sec, and 72˚C for 80 sec, the final step was performed at 72˚C for 5 min. Amplification products of β-Fg-455 were digested by HaeIII (FD0154; Thermo Fisher Scientific, Inc.) and then separated on a 2% agarose gel (Fig. 1). The presence of 343-, 383- and 575-bp fragments represented the GG allele; 343- and 958-bp fragments represented the AA allele, and 343-, 383-, 575- and 958-bp fragments represented the G/A allele. PCR conditions of β-Fg-148 were as follows: 94˚C for 2 min, followed by 35 cycles at 94˚C for 30 sec, 58.5˚C for 30 sec, and 72˚C for 30 sec, final step was performed at 72˚C for 5 min. Amplification products of β-Fg-148 were digested by HindIII (cat. no. FD0505; Thermo Fisher Scientific, Inc.) (Fig. 1). The presence of 100- and 200-bp fragments represented the CC allele, the presence of 300-bp fragments represented the TT allele and the presence of 100-, 200- and 300-bp fragments represented the T/C allele. PCR conditions of MTHFR were as follows: 94˚C for 2 min, followed by 35 cycles at 94˚C for 30 sec, 58˚C for 30 sec, and 72˚C for 30 sec, and the final step was performed at 72˚C for 5 min. Amplification products of MTHFR were digested by HinfⅠ (FD0804; Thermo Fisher Scientific, Inc.) (Fig. 1). The presence of 100- and 200-bp fragments represented the TT allele, 300-bp fragments represented the CC allele and 100-, 200- and 300-bp fragments represented the T/C allele. PCR conditions of PAI-1 were as follows: 94˚C for 2 min, followed by 35 cycles at 94˚C for 30 sec, 58.5˚C for 45 sec, and 72˚C for 30 sec, and the final step was performed at 72˚C for 5 min. PCR conditions of ApoE ε2,3,4 were as follows: 95˚C for 2 min, followed by 35 cycles at 95˚C for 30 sec, 60˚C for 45 sec, and 72˚C for 55 sec, and the final step was performed at 72˚C for 5 min.
ROC curve analysis of laboratory parameters to distinguish patients with ischemic stroke from normal controls. ROC, receiver operating characteristic; FBG, fasting blood glucose; TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; BMI, body mass index.
Characteristics of the two groups at baseline.
Sequences of PCR primers.
Association of BMI, HDL-C, ALT and AST with genotype frequencies of ACE I/D, MTHFR C677T, β-Fg-455A/G, β-Fg-148T/C, PAI-1 4G/5G and ApoE ε2-4 genes.
Association of BMI, HDL-C, ALT and AST with allele frequencies of ACE I/D, MTHFR C677T, β-Fg-455A/G, β-Fg-148T/C, PAI-1 4G/5G and ApoE ε2-4 genes.
Prediction of ischemic stroke by the BMI and the levels of HDL-C, ALT and AST.
ROC curve analysis of BMI for ischemic stroke.
Acknowledgements
The authors thank Dr Michelle Kahmeyer-Gabbe for editing the English text of a draft of this manuscript.
Funding
This work was supported by the National Natural Science Foundation of China (grant nos. 81974314, 81873975, 81802084 and 81902984), the Excellent Academic Leader Training Program of Shanghai Health System (grant no. 2018BR31), the Medical Guidance Science and Technology Support Project of Shanghai (grant no. 19411964800) and the Clinical Research and Cultivation Project of Shanghai Tongji Hospital [grant nos. ITJ(ZD)1803, ITJ(ZD)1905 and ITJ(QN)1905].
Availability of data and material
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
JW and XC collected the data and performed the statistical analysis and interpretation of the result. ZS analyzed the patient data, wrote the manuscript and approved the final version. YY, JW and WQ acquired, analyzed, and interpreted the data for the work. PN and DL designed the overall study and revised the manuscript, and also checked and approved the authenticity of the raw date. All authors read and approved the manuscript.
Ethics approval and consent to participate
This study was approved by the ethics committee of Shanghai Tongji Hospital (Shanghai, China) and was performed according to the Declaration of Helsinki. All participants provided written informed consent. If the subjects were unable to communicate, written informed consent was obtained from their legal relatives.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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