Introduction

Ischemic stroke (IS) is characterized by a high incidence, elevated mortality rates, significant disability, and a high recurrence rate, which impose a substantial health and economic burden on society and families. The primary pathophysiological mechanisms involved in IS include cell death, inflammation, immune activation, and microvascular dysfunction. The prognosis of IS is closely linked to the transcriptional regulation of gene expression during ischemic events. Several studies have demonstrated that microRNAs (miRNAs) are crucial in ischemia-reperfusion processes1,2,3. Approximately 25–48% of miRNAs in the entire human genome exist as clusters, a phenomenon attributed to the principles of evolutionary biology in the coregulation of physiological processes. miRNA regulate gene expression by binding to target messenger RNA, thereby influencing protein expression and biological functions4. MicroRNA clusters (miRNA clusters), defined as two or more miRNA genes closely located on chromosomes, are co-expressed and functionally related, making them a focal point of research in recent years.

In the human genome, miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p belong to the same clusters and are located in the intron of the Apoptosis-Associated Tyrosine Kinase (AATK) gene on chromosome 17q25.34. These microRNAs are primarily involved in the regulation of ferroptosis5, apoptosis6, the production of inflammatory mediators7,8, cell proliferation9, and neuronal differentiation10. Earlier studies have found that miRNA-338-3p, miRNA-1250, and miRNA-3065-5p are abundant in the human brain10, particularly miRNA-338-3p in the white matter. Recently, miRNA-338-3p was found to be significantly downregulated in acute IS and has been shown to exert neuroprotective effects on cell autophagy via the miR-338-3p/cPKCγ axis11. miRNA-1250-5p may be critical for inducing apoptosis, proliferation, migration, and invasion, possibly by binding to the 3’untranslated region (3ʹ UTR) of Metastasis-Associated Protein 1 (MTA1) and inhibiting its expression6. Additionally, miRNA-3065-3p could influence the proliferation and survival of nerve cells, potentially by regulating the expression of the Cytokine Receptor-Like Factor 1 (CRLF1) gene12. These studies suggest that the miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p may play significant roles in IS. Faria et al. proposed that the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters may modulate the myelination program in humans and be associated with demyelinating diseases10. However, the expression levels of these microRNAs in patients with IS remain unknown. We hypothesized that the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters are important transcriptional regulators affecting the prognosis of IS, which could facilitate further exploration of the regulatory transcriptional mechanisms underlying ischemia-reperfusion and provide molecular evidence for new therapeutic options for IS. We tested this hypothesis by investigating the expression of the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters in IS through a case-control study derived from a Chinese population.

Materials and methods

Study population

The study population comprised 83 patients with IS (the experimental group, 52 men and 31 women, mean age: 62.6 ± 10.6 years), and 50 healthy volunteers (the control group, 34 men and 16 women, mean age: 60.0 ± 7.0 years). All patients were selected in the department of Neurology, Affiliated Hospital of North Sichuan Medical College from July 2020 to December 2020. Two neurologists diagnosed them based on the 11th Clinical Revision of International Classification of diseases (ICD-11-CM) diagnostic criteria, the 4th National Cerebrovascular Conference in 1995 and the 4th National Cerebrovascular Disease Academic Conference in 2018. Patients diagnosed with transient ischemic attacks, hemorrhagic stroke, subarachnoid hemorrhages, traumatic brain injuries, spinal cord injury, tumour, neurodegenerative disease, leukemia, autoimmune diseases, rheumatoid arthritis, asthma, demyelinating disease, severe kidney and liver function damage were excluded. The volunteers were from the physical examination center of the same hospital during the same period. Informed consents were obtained for all participants. The sex, age and race of the control group were matched as closely as possible to the patients in the experimental group. This study was approved by the Ethics Committee of the North Sichuan Medical College Ethics Committee and conformed to the guidelines of the Declaration of Helsinki. Parkinson, colorectal cancer.

Indicators and methods of detection

  1. (1)

    Collection of Clinical Data: The essential characteristics of the population, medical history, IS-related scores, and laboratory indicators were collected within 24 h after admission. The parameters collected included the following: age (individuals age ≤ 45 years were classified into the young stroke group, while those age > 45 years were classified into the non-young stroke group13), gender, dyslipidemia (total cholesterol ≥ 5.72 mmol/L, triglyceride ≥ 1.70 mmol/L, or high-density lipoprotein cholesterol < 0.9 mmol/L), course of disease (the hyperacute phase is defined as a duration of no more than 24 h, the acute phase as lasting no more than 7 days, and the early subacute phase lasting no more than 14 days14), Trial of Org10172 in Acute Stroke Treatment (TOAST) classification (including five subtypes: large artery atheroscleros, caedioembolism, small vessel occlusion, stroke of other etiology, and stroke of unknown etiology)15, length of stay (LOS) (defined as LOS ≤ 14 days for the normal hospitalization group and LOS > 14 days for the prolonged hospitalization group)16, Trial of Org10172 in Acute Stroke Treatment (NIHSS, an admission NIHSS score not exceeding 3 points is defined as mild stroke, while a score exceeding 3 points is classified as not mild stroke)17, modified Rankin Scale (mRS, a discharge mRS score not exceeding 2 points is defined as the functional group, while a score exceeding 2 points is classified as the disability group18,19,20,21), white blood cell count, percentage of neutrophils, percentage of mononuclear cells, percentage of lymphocytes, hemoglobin, red blood cell count, and platelet count.

  2. (2)

    miRNA detection: Peripheral blood mononuclear cells(PBMCs) were isolated from 3 ml anticoagulated peripheral blood samples using Ficoll-Hypaque density-gradient centrifugation. Total RNAs were extracted from the PBMCs according to the manufacturer’s instructions of the miRcute miRNA Isolation Kit (TIANGEN, China). The purity and integrity of the RNA were evaluated using the NanoVue Plus spectrophotometer (BiochRom, Britain) and Agarose gel electrophoresis(BIO-RAD, America) and then stored at − 80 °C. Figure 1 showed the results of Agarose gel electrophoresis.

  A total reaction volume of 20 µl, containing 8µL RNA, 10 µL 2×miRNA RT Reaction Buffer, and 2 µL miRNA RT Enzyme Mix, was carried out for cDNA synthesis of miRNA using minute Plus miRNA first-Stran cDNA synthesis kit (TIANGEN, China) at 42 °C for 60 min, followed by 95 °C for 3 min.

 Real-time quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) was used for miRNA expression analysis of miRNA-338-3p, miRNA-1250-5p, miRNA-3065-5p and U6 (housekeeping miRNA). The total reaction volume was 20ul, including 0.4 µL Forward Primer (Table 1), 0.4 µL Reverse primer, 5.6 µL ddH2O, ten µL 2× miRcute Plus miRNA Premix (SYBR&ROX), 1.6 µL 50×ROX Reference Dye, two µL cDNA. The RT-qPCR conditions were 95 °C for 15 min, followed by five cycles at 94 °C for 20 s, 64 °C for 30 s, 72 °C for 34 s, and then 40  cycles at 94 °C for 20 s, 60 °C for 34 s. The CT values of target miRNA and housekeeping miRNA were recorded and calculated using the 2-ΔΔCt formula for the relative expressions. Figure 2 showed the predicted structure of miRNA-338, miRNA-1250 and miRNA-3065 from miRCarta.

Fig. 1
figure 1

Gels images of miRNA and U6.

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Table 1 miRNA primer sequences.
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PCR products were analyzed using agarose gel electrophoresis (1%) stained with Genegreen Nucleic Acid Dye. Gel images of miRNA and U6 were visualized. U6 was used as an internal reference. Lanes: M:Maker, (1)(2)(3) miRNA, (4)(5)(6)U6.

Fig. 2
figure 2

The predicted structure of miRNA-338, miRNA-1250 and miRNA-3065. (A) miR-338(hsa-mir-338), (B) miR-1250(hsa-mir-1250). (C) miR-3065(hsa-mir-3065). miR-338, miR-1250 and miR-3065 are all locate in chr17.From miRCarta V1.1 (https://mircarta.cs.uni-saarland.de/advanced_search/).

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Statistical analysis

Statistical analyses were conducted using IBM SPSS 25.0, and data were plotted using Prism 7.0 (Graphpad). A double-sided significance threshold of P < 0.05 was applied. Normality tests were performed using the Kolmogorov-Smirnov test, histograms, P–P plots, and Q–Q plots. For continuous variables, data are presented as mean ± standard deviation (\(\overline {x}\) ±s)or [median (P25, P75)]. Differences between the two groups were assessed using either a parametric test (Student’s t-test) or a non-parametric test (Wilcoxon rank sum test). Differences in miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p across two or more groups were compared using the Hotelling T2 test or Wilks Λ test. Categorical variables are presented as percentages (%), and differences were analyzed using the Chi-square test, Calibration Chip Test, or Fisher’s Precision Test. Correlation analyses were performed using either Pearson or Spearman methods.

Results

Baseline characteristics of the experimental group and control group

Table 2 summarizes the clinical characteristics of the experimental and control groups. There were no significant differences in gender and age between the experimental and control groups (P > 0.05).

Table 2 Demographic information, clinical characteristics.
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The expression of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p between the experimental and control groups

Table 3; Fig. 3 illustrate the expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in IS. There was no significant difference in the expression level of miRNA-338-3p between the experimental and control groups (P > 0.05). In contrast, the expression levels of miRNA-1250-5p and miRNA-3065-5p were significantly higher in the experimental group compared to the control group (P < 0.05). Overall, the expression levels of the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters in the experimental group were greater than those in the control group (P < 0.05).

Table 3 The expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p between the experimental and control groups.
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Fig. 3
figure 3

The expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in PBMCs between the experimental and control groups. (A) The expression level of miRNA-338-3p in the experimental group was higher than in the control group. However, this difference was not statistically significant. (B) The expression level of miRNA-1250-5p in the experimental group was higher than that in the control group, and the difference between the two groups was statistically significant. (C) The expression level of miRNA-3065-5p in the experimental group was also higher than in the control group, with a statistically significant difference observed between the two groups. *P < 0.05,**P < 0.01,***P < 0.001.

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Expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in the IS group

Table 4; Fig. 4 illustrate the IS population’s expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p. The expression levels of miRNA-1250-5p increase during the acute phase (up to 7 days) but decrease after seven days compared to baseline (P < 0.05). The expression levels of miRNA-3065-5p and miRNA-338-3p in patients with a discharge NIHSS score greater than 3 were higher than those in the group with a score of 3 or less (P < 0.05). Additionally, The expression levels of miRNA-3065-5p in the population with discharged mRS scores of 3 or higher was greater than that in the population with discharged mRS scores of 2 or lower (P < 0.05).

Table 4 The analysis of the expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in the experimental group.
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Fig. 4
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The expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in different groups. (A) The expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p were analyzed between groups according to the stages of the disease. The difference in miRNA-1250-5p expression between groups was statistically significant. (B) The expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p were evaluated between groups based on the discharge NIHSS score. The differences in miRNA-338-3p and miRNA-3065-5p expression between groups were statistically significant. (C) The expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p were compared between groups according to discharge mRS scores. The difference in miRNA-3065-5p expression between groups was statistically significant. *P < 0.05, **P < 0.01, ***P < 0.001.

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The correlation between the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters and IS

The expression level of miRNA-3065-5p positively correlates with the admission NIHSS score and the length of hospital stay in patients with IS (P < 0.05). Additionally, the expression levels of miRNA-338-3p and miRNA-3065-5p were positively correlated with the discharge mRS score (P < 0.05). Furthermore, the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters showed a positive correlation with the percentage of neutrophils and a negative correlation with the percentage of lymphocytes (P < 0.05) (Table 5).

Table 5 The correlational analysis between miRNA-338-3p, miRNA-1250-5p, miRNA-3065-5p, and clinical parameters in patients with IS.
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The correlation of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p

Table 6; Fig. 5 illustrate the correlation among miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in IS. The expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p were significantly positively correlated in IS.

Table 6 The correlational analysis between miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p.
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Fig. 5
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The correlational analysis between miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p groups. E: Experimental group, C: Control group. (A–C) Illustrate the correlations between miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in the experimental group, while (D–F) depict these correlations in the overall population. (A) In the experimental group, miRNA-338-3p was positively correlated with miRNA-1250-5p (r = 0.381, p < 0.001). (B) In the experimental group, miRNA-338-3p was positively correlated with miRNA-3065-5p (r = 0.422, p < 0.001). (C) In the experimental group, miRNA-1250-5p was positively correlated with miRNA-3065-5p (r = 0.531, p < 0.001). (D) In the experimental group, miRNA-338-3p was positively correlated with miRNA-1250-5p. In the control group, miRNA-338-3p was negatively correlated with miRNA-1250-5p, while a positive correlation was observed in the total population (r = 0.234, p = 0.007). (E) miRNA-338-3p positively correlated with miRNA-3065-5p in the experimental, control group, and total population (r = 0.356, p < 0.001). (F) miRNA-1250-5p was positively correlated with miRNA-3065-5p in the experimental group, control group, and total population (r = 0.452, p < 0.001).

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The ROC curves of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p

Figure 6 presents the results of the ROC analysis for miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in predicting IS. The AUC values are 0.553, 0.659, and 0.737, with 95% confidence intervals of 0.455–0.650, 0.562–0.756, and 0.651–0.822, respectively.

Fig. 6
figure 6

The ROC of miRNA-338-3p, miRNA-1250-5p and miRNA-3065-5p.

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Main association of IS with miRNA-338-3p/miRNA-1250-5p/miRNA− 3065-5p from previous analysis

The primary outcomes of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p levels were presented in Table 7 for each study.

Table 7 Summary of outcomes from the measurement of peripheral miR-338-3p/miRNA-1250-5p/miRNA-3065-5p in IS.
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Discussion

When ischemic damage occurs in the brain, oligodendrocytes exhibit a high sensitivity to ischemia and hypoxia. The deposition of fibrinogen, caused by the disruption-destruction of the blood-brain barrier (BBB), adversely affects oligodendrocytes’ cellular state and differentiation22. Studies have shown that miRNA-338-3p, miRNA-1250, and miRNA-3065-5p are abundant in the human brain and associated with oligodendrocyte precursor cells’ proliferation and differentiation10. Notably, miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p are all located within the same cluster in the intron of the AATK gene on chromosome 17q25.3. Functional analyses suggest that AATK may play a role in various pathophysiological pathways, including apoptosis, neuronal differentiation and maturation, axon formation, synaptic transmission, and glial cell proliferation (https://www.ncbi.nlm.nih.gov/gene/). However, the investigation of the miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p clusters in IS has not been thoroughly explored. In the present study, we examined the expression levels of miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p in PBMCs from IS patients and healthy individuals. Our findings indicate that the expression levels of miRNA-1250-5p and miRNA-3065-5p in the PBMCs of IS patients were significantly higher than those in the control group.

In this study, we found that miRNA-1250-5p and miRNA-3065-5p were significantly different between the experimental and control groups. The results are consistent with previous findings23, suggesting that miRNA-1250-5p and miRNA-3065-5p may be involved in the pathology of IS. In this experiment, the difference in miRNA-338-3p between the experimental and control groups was not statistically significant, which was inconsistent with some studies11,23,24. Whether miRNA-338-3p expression was upregulated24 or downregulated25,26 in ischemic injury remained controversial. A possible reason for this discrepancy was that miRNA-338 was expressed in cerebrospinal fluid (CSF) but not in serum. Additionally, miRNA-338-3p may have an independent promoter, which could account for the differences in results. Previous studies had shown that miRNA-1250-5p was critical for apoptosis induction and regulated apoptosis by upregulating MTA1 and inhibiting LncRNA ELFN1-AS1 expression by binding to the 3ʹ untranslated region (UTR) of MTA16. Its signalling pathway may also be involved in IS by participating in endothelial angiogenesis27. miRNA-3065-3p was recognized as one of the critical regulators of inflammation8. Thus, miRNA-1250-5p and miRNA-3065-5p may play a role in the pathophysiological processes associated with IS by regulating immune cell polarization, apoptosis, inflammatory responses, or promoting angiogenesis.

In this study, miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p showed significant positive correlations with each other in IS. Notably, the changes in the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters synchronized with the percentage of inflammatory cells, exhibiting a highly significant positive correlation with the percentage of neutrophils and a highly significant negative correlation with the percentage of lymphocytes. This confirms the co-expression of miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters in IS and suggests their involvement in regulating the inflammatory response associated with IS. Faria et al. demonstrated that these miRNA clusters synergistically contribute to the proliferation and differentiation of oligodendrocyte precursor cells in demyelinating diseases10. Simultaneously, they synergistically downregulated the expression of Runt-related transcription factor 2(Runx2), Bone morphogenetic protein 7 (BMP7), and Wnt family member 5 A(Wnt5a) genes to promote osteoblast differentiation in osteoblast models28. Additionally, databases such as TargetScan and miRBase suggested that miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p share many common target genes, including Zinc Finger Proteins (ZNF), Solute Carrier (SLC), Ribosomal Protein S (RPS), and Adenosine Triphosphate (ATP), among others. Notably, ZNF and SLC genes are closely associated with IS. Research has shown that ZNF and its associated proteins significantly enhance blood perfusion in ischemic tissue, mitigate inflammatory responses, promote angiogenesis, and address ischemic and inflammatory challenges by regulating gene transcription29. Zinc finger transcription factors maintain the structural integrity and functionality of the BBB by regulating the activity of closely linked proteins30. Moreover, they suppress endothelial angiogenesis by targeting the krüppel-associated box (KRAB) domain31. Thus, miRNA-338-3p, miRNA-1250-5p, and miRNA-3065-5p are hypothesized to be involved in IS by targeting the ZNF gene, which is closely associated with ischemic brain injury and repair, ultimately affecting the severity and prognosis of IS. Moreover, SLC transporters are widely distributed across the BBB, blood-cerebrospinal fluid barrier, and nerve cells32. They play critical roles in various biological processes, such as solute and drug transportation33,34,35,36, phagocytic clearance37, and the modulation of inflammation38. Therefore, the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters may co-transcribe and synergistically participate in the inflammatory response of IS, affecting the progression and prognosis of IS and could become one of the intervention targets for IS. However, further research is needed to understand its upstream and downstream mechanisms.

In summary, the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters may be involved in the pathophysiological processes of IS. The miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters are closely related to inflammatory markers, disease severity scores, and prognostic indicators in IS, suggesting that the miRNA-338-3p/miRNA-1250-5p/miRNA-3065-5p clusters may affect the severity and prognosis of IS by regulating inflammatory responses and other mechanisms.

Strengths and limitations of this study

There were some limitations in the study. First, the study was a single-center case-control study with a small sample and a single population structure, which did not represent the total population and may lead to statistical bias. Second, IS is a complex disease influenced by multiple factors and dynamic changes over time, and miRNAs may play different roles at different stages of the disease. However, we did not dynamically detect the miRNA clusters expression in the same individual.