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15 July 2020: Clinical Research  

Association Between Ghrelin Gene Polymorphism and Cerebral Infarction

Li Chen1ABE, Hua Zhao1BCF, Jing Shen2DF, Xiaoyu Ji3ACG*

DOI: 10.12659/MSM.924539

Med Sci Monit 2020; 26:e924539

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Abstract

BACKGROUND: The aim of this study was to explore the associations of ghrelin gene polymorphisms at rs26312, rs26802 and rs27647 with cerebral infarction.

MATERIAL AND METHODS: A total of 200 cerebral infarction patients in our hospital were enrolled as the disease group, while 200 healthy people were enrolled as the control group. Peripheral venous blood was collected from both groups, and the ghrelin gene polymorphisms at rs26312, rs26802, and rs27647 in nucleated cells were detected through sequencing.

RESULTS: The genotype distribution at ghrelin gene loci rs26802 and rs27647 in the disease group was significantly different from that in the control group. The distribution of recessive model at ghrelin gene locus rs26802 in the disease group was different from that in the control group, in which the TG+GG frequency was evidently higher in the disease group. The AA genotype at ghrelin gene locus rs26312 was remarkably associated with the ghrelin gene expression level, and the expression level of ghrelin gene in the disease group was remarkably lower than that in the control group. The genotype at ghrelin gene locus rs26312 was associated with activated partial thromboplastin time (APTT), and APTT was significantly shorter in patients with GG genotype. The genotype at ghrelin gene locus rs26802 was associated with D-dimer, and the D-dimer level was significantly lower in patients with TG genotype. The genotype at ghrelin gene locus rs27647 was associated with prothrombin time (PT), and PT was obviously shorter in patients with TT genotype.

CONCLUSIONS: The ghrelin gene polymorphisms are remarkably associated with the occurrence of cerebral infarction.

Keywords: Association, cerebral infarction, Case-Control Studies, Gene Frequency, Genetic Association Studies, Genotype, Haplotypes, Polymorphism, Single Nucleotide, Risk Factors

Background

Cerebral infarction is one of the frequently-occurring diseases in middle-aged and elderly people around the world, and its morbidity rate is higher in China [1,2]. The occurrence of cerebral infarction is mainly related to the increase in blood viscosity and cerebral vascular stenosis, and it is also closely related to such factors as metabolism, vascular fragility, and age [3,4]. Cerebral infarction has a serious impact on the cerebral function of patients, causes ischemia and even necrosis in some brain tissues, and leads to function disorder or loss in some regions of the brain, thus greatly affecting the quality of life of patients after treatment, and can even be life-threatening. The pathogenesis of cerebral infarction is complex and may be related to the mutation and abnormal expression of multiple genes [5].

Gene polymorphism refers to the individual differences in alleles or genotypes at the same locus in the population, which increases or decreases susceptibility of the population to some diseases, or affects the gene expression, thereby affecting the occurrence of disease [6,7]. Studies have demonstrated that multiple gene polymorphisms affect the occurrence of cerebral infarction. For example, CTSS gene [8] and PPARG2 gene [9] polymorphisms are associated with the occurrence of cerebral infarction in the Chinese population, and the ALDH2 gene polymorphism affects the collateral circulation and prognosis of cerebral infarction patients [10]. As the ligand for the growth hormone secretagogue receptor, the ghrelin gene promotes the release of growth hormone, thereby affecting various biological functions. However, the association between ghrelin gene polymorphism and susceptibility to cerebral infarction has not been reported yet.

In this study, the ghrelin gene polymorphisms at loci rs26312, rs26802, and rs27647 in peripheral venous blood nucleated cells were studied in cerebral infarction patients and healthy people, combined with the haplotype analysis and detection of coagulation indexes, so as to explore the associations of ghrelin gene polymorphisms with cerebral infarction.

Material and Methods

GENERAL DATA:

A total of 200 patients diagnosed with cerebral infarction in our hospital from 2017 to the present (disease group) and 200 healthy people at the physical examination center (control group) were enrolled in the study. The general and clinical data in both groups were collected, including name, admission ID, gender, age, body mass index (BMI), disease history, and drug allergy history. The mean age was (65.21±5.83) years old in the disease group and (64.92±4.24) years old in the control group. There were no statistically significant differences in such general data as age and gender between the 2 groups.

Inclusion criteria for cerebral infarction patients in disease group were: middle-aged and elderly patients with new-onset cerebral infarction, those with clinical symptoms of cerebral infarction such as headache, dizziness and epileptic seizure, those with cerebral ischemic lesions shown in brain CT and MRI, and those with cerebral vascular stenosis or occlusion and poor blood flow shown in cerebral angiography.

This study was approved by the Ethics Committee of Jingzhou Central Hospital. Signed written informed consent was obtained from all participants before the study began.

SAMPLE COLLECTION AND PROCESSING:

About 6–8 mL of peripheral venous blood was collected from both groups and centrifuged using a centrifuge at 3000 rpm for 8 min within 2 h. Then, the upper-layer serum and mid-layer nucleated cells were transferred into new centrifuge tubes. The upper-layer serum was stored in liquid nitrogen for later detection, and the genomic deoxyribonucleic acid (DNA) was extracted from the mid-layer nucleated cells.

GENOMIC DNA EXTRACTION:

The genomic DNA was extracted from the peripheral venous blood in both groups using the blood genome extraction kit (Tiangen, Beijing, China) in strict accordance with the instructions of the kit. According to the volume of sample, an appropriate amount of protease K solution was added into the centrifuge tube, and peripheral venous blood samples and buffer were also added. The mixture was mixed evenly using a vortex oscillator and incubated at 65°C for 8–10 min. Then, 2 mL of absolute alcohol was added into the samples, mixed evenly, and transferred into an absorption column. We added 2 mL of buffer into the absorption column, followed by centrifugation at 3000 rpm for 1 min. Finally, 200 μL of elution buffer was added into the absorption column, and the resulting solution was the genomic DNA.

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The polymorphic regions at ghrelin gene loci rs26312, rs26802, and rs27647 were amplified using the PCR instrument. The total PCR system was 25 μL, including 1 μL of forward primers, 1 μL of reverse primers, 0.5 μL of DNA template, 12.5 μL of high-fidelity heat-resistant Taq DNA polymerase, and 10 μL of dH2O. The PCR conditions were: 95°C for 5 min, (95°C for 30 s, 57°C for 40 s, and 72°C for 35 s)×45 cycles, and 72°C for 5 min. The primers of polymorphic loci were:

The PCR products were sent to Jiangsu Biotechnology Co. (Nanjing, China) for sequencing, and the polymorphisms at ghrelin gene loci were analyzed in both groups.

DETECTION OF GHRELIN GENE EXPRESSIONS:

The ghrelin gene expression was detected via reverse transcription-quantitative PCR (RT-qPCR) in both groups. The RNA sample was extracted using the TRIzol method and reversely transcribed into complementary deoxyribose nucleic acid (cDNA). The gene primers were designed using Primer Premier 5.0 and synthesized by Sangon (Shanghai, China):

The total PCR system was 25 μL, including 1 μL of forward primers, 1 μL of reverse primers, 0.5 μL of cDNA template, 12.5 μL of SYBR premix Taq, and 10 μL of dH2O. The PCR conditions were: 94°C for 2 min, (95°C for 35 s, 56°C for 40 s, and 72°C for 35 s)×45 cycles, and 72°C for 5 min.

DETECTION OF CLINICAL INDEXES:

The peripheral venous blood was extracted in both groups, and the clinical coagulation indexes prothrombin time (PT), activated partial thromboplastin time (APTT), and D-dimer were detected within 2 h in the Clinical Examination Room of the Laboratory Department using the full-automatic coagulation analyzer.

STATISTICAL ANALYSIS:

Statistical Product and Service Solutions (SPSS) 23.0 software (IBM, Armonk, NY, USA) was used for statistical analysis. Enumeration data were compared using the χ2 test, and the Hardy-Weinberg equilibrium test was performed. Haplotype analysis was conducted using the SHEsis website. P<0.05 suggested the statistically significant difference.

Results

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As shown in Table 1, the allele distribution at ghrelin gene locus rs26802 was different between the control group and disease group (P=0.013), and the T allele frequency in the disease group (178) was significantly lower than that in the control group (213).

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As shown in Table 2, the genotype distribution at ghrelin gene loci rs26802 (P=0.026) and rs27647 (P=0.006) in the disease group was significantly different from that in the control group. The TT genotype frequency at rs26802 in the disease group was obviously lower than that in the control group, while the CT genotype frequency at rs27647 in the disease group was obviously higher than that in the control group.

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As shown in Table 3, the distribution of recessive model at ghrelin gene locus rs26802 in the disease group was different from that in the control group (P=0.033), in which the TG+GG frequency was evidently higher in the disease group. The distribution of dominant model (P=0.023) and heterozygous model (P=0.007) at rs27647 in the disease group was also different from that in the control group, in which the CC+CT frequency in dominant model and CT frequency in heterozygous model were evidently higher in the disease group.

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According to the haplotype analysis and linkage disequilibrium analysis of ghrelin gene loci rs26312, rs26802, and rs27647 (Tables 4, 5), the haplotype frequency of ghrelin AGC (P=0.000), ATC (P=0.000), and GTT (P=0.011) in the disease group was markedly different from that in the control group, in which the disease group had a markedly higher haplotype frequency of ghrelin AGC and a markedly lower haplotype frequency of ATC and GTT. Moreover, the linkage disequilibrium was higher at ghrelin gene loci rs26802 and rs26312 (D′=0.631).

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The detection results of the associations of genotypes at ghrelin gene loci rs26312, rs26802, and rs27647 with gene expressions revealed that the AA genotype at ghrelin gene locus rs26312 was remarkably associated with the ghrelin gene expression level (P<0.05), and the expression level of ghrelin gene in the disease group was remarkably lower than that in the control group (Figures 1–3).

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The genotype at ghrelin gene locus rs26312 was associated with APTT (P=0.031), and APTT was significantly shorter in patients with GG genotype. The genotype at ghrelin gene locus rs26802 was associated with D-dimer (P=0.043), and the D-dimer level significantly increased in patients with TG genotype. The genotype at ghrelin gene locus rs27647 was associated with PT (P=0.037), and PT was obviously shorter in patients with TT genotype (Table 6).

Discussion

The occurrence of cerebral infarction, one of the major diseases affecting the health of middle-aged and elderly people, is related to many factors [11,12]. The pathogenesis of cerebral infarction is mainly related to the metabolite level and vascular function in patients, and it is also affected by the expression of some genes or pathways [13]. Studies have shown that N-acetylcysteine plays an important role in the pathogenesis of cerebral infarction and can affect its prognosis [14], and substances such as acrolein are also involved in this process [15]. Therefore, studying the specific factors affecting the occurrence of cerebral infarction has importance in the prevention and treatment of disease.

The protein encoded by the ghrelin gene is the ligand for the growth hormone secretagogue receptor, which mainly regulates the concentration of growth hormone in the body and affects some of the body’s functions through affecting the release of growth hormone, such as regulating growth and development, affecting sugar, lipid and protein metabolism, and relaxing the cardiovascular system [16,17]. It has been proved that the ghrelin gene polymorphisms can affect the occurrence and susceptibility to a variety of diseases, such as polycystic ovary syndrome [18], chronic hepatitis C [19], and type 2 diabetes mellitus [20]. In cerebral infarction patients, the effects of ghrelin gene polymorphisms have not been studied yet. In this study, it was found that the allele distribution at ghrelin gene locus rs26802 was different between the control group and disease group (P=0.013), and the T allele frequency in the disease group was significantly lower than that in the control group, indicating that the ghrelin gene polymorphisms can indeed affect the occurrence of cerebral infarction. The genotype distribution at ghrelin gene loci rs26802 (P=0.026) and rs27647 (P=0.006) in the disease group was significantly different from that in the control group. The TT genotype frequency at rs26802 in the disease group was obviously lower than that in the control group, while the CT genotype frequency at rs27647 in the disease group was obviously higher than that in the control group. The above results suggest that the genotypes at rs26802 and rs27647 can obviously affect the susceptibility of cerebral infarction patients. The population with rs27647 CT genotype has a significantly higher risk of cerebral infarction, while that with rs26802 TT genotype is less susceptible to cerebral infarction.

In this study, it was found through polymorphic analysis and modeling that the distribution of recessive model at ghrelin gene locus rs26802 in the disease group was different from that in the control group (P=0.033), in which the TG+GG frequency was evidently higher in the disease group. The distribution of dominant model (P=0.023) and heterozygous model (P=0.007) at rs27647 in the disease group was also different from that in the control group, in which the CC+CT frequency in dominant model and CT frequency in heterozygous model were evidently higher in the disease group, which demonstrate that the effects of ghrelin gene polymorphisms on cerebral infarction may be jointly realized by multiple genotypes at the same locus. According to haplotype analysis, the haplotype frequency of ghrelin AGC (P=0.000), ATC (P=0.000) and GTT (P=0.011) in the disease group was markedly different from that in the control group, in which the disease group had a markedly higher haplotype frequency of ghrelin AGC and a markedly lower haplotype frequency of ATC and GTT, suggesting that the combined analysis of 3 polymorphic loci of ghrelin may perform better in determining the susceptibility to cerebral infarction. The linkage disequilibrium was higher at ghrelin gene loci rs26802 and rs26312 (D′=0.631), confirming that the 2 loci jointly affect the ghrelin gene polymorphisms.

The AA genotype at ghrelin gene locus rs26312 was remarkably associated with the gene expression level (P<0.05), and the expression level of ghrelin gene in the disease group was remarkably lower than that in the control group, indicating that the effect of the ghrelin gene on cerebral infarction may occur through altering the expression level of the ghrelin gene and affecting the release of growth hormone.

We found that the genotype at ghrelin gene locus rs26312 was associated with APTT (P=0.031), and APTT was significantly shorter in patients with GG genotype. The genotype at ghrelin gene locus rs26802 was associated with D-dimer (P=0.043), and the D-dimer level was significantly higher in patients with TG genotype. The genotype at ghrelin gene locus rs27647 was associated with PT (P=0.037), and PT was obviously shorter in patients with TT genotype. These findings prove that the ghrelin gene polymorphisms can serve as an important predictive index for the clinical progression and prognosis of cerebral infarction.

Conclusions

These findings prove that the ghrelin gene polymorphisms can serve as an important predictive index for the clinical progression and prognosis of cerebral infarction.

References

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8. Luo L, Zhu M, Zhou J, Association between CTSS gene polymorphism and the risk of acute atherosclerotic cerebral infarction in Chinese population: A case-control study: Biosci Rep, 2018; 38(6) pii: BSR20180586

9. Li X, Zhang BL, Zhang XG, Su XL, Correlation between PPARg2 gene Pro12Ala polymorphism and cerebral infarction in an Inner Mongolian Han Chinese population: Genet Mol Res, 2016; 15(2)

10. Qu Y, Zhang H, Li H, Aldehyde dehydrogenase 2 (ALDH2) Glu504Lys polymorphism affects collateral circulation and short-term prognosis of acute cerebral infarction patients: Med Sci Monit, 2017; 23; 4559-66

11. Goncalves B, Turon R, Mendes A, Effect of early brain infarction after subarachnoid hemorrhage: A systematic review and meta-analysis: World Neurosurg, 2018; 115; e292-98

12. Mohammadi MT, Overproduction of nitric oxide intensifies brain infarction and cerebrovascular damage through reduction of claudin-5 and ZO-1 expression in striatum of ischemic brain: Pathol Res Pract, 2016; 212; 959-64

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14. Uemura T, Watanabe K, Ko K, Protective effects of brain infarction by N-acetylcysteine derivatives: Stroke, 2018; 49; 1727-33

15. Uemura T, Watanabe K, Ishibashi M, Aggravation of brain infarction through an increase in acrolein production and a decrease in glutathione with aging: Biochem Biophys Res Commun, 2016; 473; 630-35

16. Allbrand M, Aman J, Lodefalk M, Placental ghrelin and leptin expression and cord blood ghrelin, adiponectin, leptin, and C-peptide levels in severe maternal obesity: J Matern Fetal Neonatal Med, 2018; 31; 2839-46

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