Gene Collection and Processing
During our research endeavor, we initially isolated and scrutinized a corpus of gene expression correlations pertaining to "acute myocardial infarction". These findings originated from the Gene Expression Omnibus (GEO), a property of the National Center for Biotechnology Information (NCBI), accessible via this URL: http://www.ncbi.nlm.nih.gov/geo/. To assure the authenticity and dependability of these data, we confined our selection solely to gene expression datasets comprising of healthy demographics (N) and subjects afflicted with osteoporosis (OP), excluding all non-humane specimens. Specifically, two datasets, GSE66360 (comprising N = 50, PA = 49) and GSE48060 (comprising N = 21, PA = 31), were chosen for thorough examination. Moreover, we retrieved miRNA-seq expression data from GSE249812 (comprising N = 5, PA = 5) and single-cell RNA-seq data from GSE269269. Notably, we sourced the 378 genes with an apoptotic cell score of 7 or higher from the GeneCards database (accessible at this URL: https://www.genecards.org) as complementary information [19].
A differential regulation of apoptotic genes was observed in comparison between the Acute Myocardial Infarction (AMI) cohort and normal individuals.
We initiated our research by meticulously examining Peripheral Blood Mononuclear Cells (PBMCs) obtained from a total of 49 patients diagnosed with Acute Myocardial Infarction (AMI), and 50 unaffected individuals utilizing multimodal MRI. This analysis encompassed transcriptome profiling data for these cells, detailed as GSE66360. Subsequently, the raw data was harmonized and subjected to Principal Component Analysis (PCA) to unearth the unique expression profiles distinguishing the two sample cohorts. To further delineate these differentially expressed genes, we employed volcano and heat map methodologies (with screening parameters set at log2FC exceeding 1 and P-value less than 0.05). Furthermore, we pinpointed 1604 Differentially Expressed Genes (DEGs) and 378 Oligosaccharides and Sulfatides Related genes, collectively referred to as OSRG. This gene group was cross-referenced and their intricate correlations were illustrated via a Venn diagram. Ultimately, we successfully identified 55 apoptosis-associated genes exhibiting significant alterations in expression levels, which were strongly correlated with acute myocardial infarction. Additionally, we performed an extensive examination of another miRNA dataset, GSE249812, to discern miRNAs demonstrating differential expression patterns between AMI patients and healthy controls.
Consensual Clustering and Joint Expression Analysis
Upon scrutinizing the GSE48060 genome expression profiling dataset, we initially computed the median absolute deviation (MAD) score for each gene before eliminating the foremost 50% of genes boasting the lowest MAD score. Subsequently, utilizing the R-dependent goodSamplesGenes function within the WGCNA application, these genes along with their corresponding observations were systematically inspected to rule out potential inconsistencies. Post this, we employed the WGCNA methodology to form a scale-free co-expression network, wherein the β parameter was fixed at 7 and the sensitivity was adjusted to 3. Upon this foundation, modules exhibiting a correlation coefficient between genes inferior to 0.25 were amalgamated, yielding 7 modules possessing substantial co-expression attributes. Notably, certain modules designated as "gray" do not align with any pre-existing modules in the co-expression analysis.
Enrichment Analysis of Key Module Characteristic Genes via GO and KEGG
Utilizing WGCNA's sophisticated deep clustering analytical methodology, we proficiently isolated the pivotal module exhibiting significant correlation with phenotypic manifestation from an extensive array of pertinent data, concurrently yielding a comprehensive compilation of all genes encompassed within this module. Subsequently, we employ the "clusterProfile" auxiliary package of the R programming idiom to construct a Gene Ontology for each gene within the designated green module. Through rigorous multidimensional scrutiny and exploration, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, our objective is to delve deeper into the underlying biological mechanisms and potential biological pathways implicated in acute myocardial infarction (AMI).
Assessment and comparative examination of pivotal genes
Through the application of a Venn diagram, we illustrate the intricate interplay among the pivotal module gene clusters of the Weighted Gene Coefficient Network Analysis (WGCNA), apoptotic-associated genes, and variously expressed genes implicated in acute myocardial infarction. Eventually, two paramount genes, namely PTEN and BCL2L11, were identified as potential contributors to this disease scenario.
Mendelian randomization (MR) analysis
We utilized a Venn diagram to illustrate the interplay among the critical module genes within the Weighted Gene Correlation Network Analysis (WGCNA), apoptotic genes, and differentially expressed genes pertaining to acute myocardial infarction. Subsequently, two vital genes, namely PTEN and BCL2L11, were pinpointed. This paper utilizes the ARMI dataset sourced from both CardioGRAMplusC4D (accessible at http://www.cardiogramplusc4d.org/) and LeeLab (repository reference: https://leelab.org/proteomics-and-genomics/), two independent genome-wide association study (GWAS) databases (with respective identifiers of ieu - a − 798 and ukb saige − 411.2). Upon gaining access to these datasets, we navigated through the GWAS directory (specific link: https://www.ebi.ac.uk/gwas/), identified the SNP associated with the BCL2L11 gene, and employed the Mendelian randomization approach via the MR-Base platform. Throughout this procedure, we primarily relied on the inverse variance weighting (IVW) methodology for comprehensive analysis, along with the MR Egger intercept to gauge the influence of horizontal pleiotropy. Moreover, to ascertain the robustness of causality, we executed a series of sensitivity analyses, encompassing Cochran's Q test, MR Presso test, and missing an exception analysis. All aforementioned statistical evaluations were executed utilizing the "TwoSampleMR" (version 0.5.6) module in the R.p software, with a significance threshold of 0.05 being adopted unless specified otherwise.
RT-qPCR and Cell experiments
1. In Vitro Culture of Cardiomyocytes
Human-derived cardiomyocytes (derivatives of type CA16) are initially rejuvenated in accordance with established protocols, subsequently transferred to a Petri dish enriched with 9% fetal bovine serum and Dulbecco's Modified Eagle Medium (DMEM) medium, along with a 1% solution of penicillin and streptomycin by volume to foster a favorable bacterial milieu. Incubation is conducted within an incubator maintaining a concentration of 5% carbon dioxide by volume and a temperature of 37°C, with regular monitoring of cell proliferation. A fresh culture medium is replenished every third day, followed by cell passage. Cells in the logarithmic growth phase are chosen as the subject for ensuing experiments.
2. Group Treatment of Cardiomyocytes
Cardiomyocytes CA16 in the logarithmic growth phase are segregated into four distinct groups based on diverse treatment modalities: Normal group (N), Hypoxia group (H), Overexpression control group (NC + H), and miR-30e-5p + H group (miR + H). Herein, the Normal group is maintained under standard conditions for 24 hours; the Hypoxic group undergoes H2O2 treatment prior to cultivation under normal conditions. The Overexpression control group (NC + H) and miR-30e-5p + H group (miR + H) are subjected to lentivirus infection, respectively. Specifically, the (NC + H) group is cultivated under normal conditions, whereas the (miR + H) group is cultivated post H2O2 hypoxia treatment under normal conditions. All cultures are executed in a 37°C incubator with a volume fraction of 5% carbon dioxide.
3. Protocol for Hypoxia Treatment via an Inductive Method
Based on the scrutiny of data derived from prior hydrogen peroxide induction experimentation, we discerned that as the H2O2 concentration escalated, miR-30e-5p expression decreased significantly. Consequently, the H2O2 concentration appointed for this experimental setup was fixed at 75 µM, and the duration of the treatment period was calibrated to 24 hours. Cells in the exponential growth phase were plated into 6-well plates post-trypsinization of the hypoxic group (H), miR-30e-5p + H group, exposed to a concentration of 75 µM H2O2, and cultivated in a 37°C incubator enriched with 5% carbon dioxide for 24 hours. Control group: The N group was exempt from any intervention; the H group solely required incubation for 24 hours post-hypoxia treatment; both the NC + H and miR + H groups were persistently infected and loaded with lentivirus, henceforth maintained at 37°C for uninterrupted cultivation. Post completion of the treatment period, cells from each group were isolated and processed independently for assessment of pertinent indicators.
4. Procedure for Lentivirus Infection of Cardiomyocytes
To ensure efficient lentiviral infection, it is imperative to cultivate 293T cells in 96-well plates and the corresponding plasmid of interest for infection beforehand. Once the cell density attains a suitable range of approximately 50%-70%, the infection procedure may commence. Equilibrate the DMEM blend thoroughly with a solution comprising 0.16 µg of the h-BIM-3'UTR target plasmid and 5 pmol of hsa-miR-30e-5p/Negative Control (NC), and store at room temperature (i.e., Solution A). Subsequently, blend another DMEM blend thoroughly with a solution incorporating 0.3 µl of infection reagent (manufactured by Hanheng Biotech at a concentration of 0.8 mg/ml), and allow to stand for 5 minutes at room temperature (i.e., Solution B). Lastly, amalgamate Solution A and Solution B thoroughly and leave at room temperature for 20 minutes. Prior to infection, the cells must be replenished with fresh medium and subsequently agitated uniformly with the aforementioned infection mixture. Adjust the culture conditions to 37°C with a volume fraction of 5% carbon dioxide, rejuvenate the medium once more 6 hours post-infection, and harvest cells for detection 24 hours subsequent.
5. Examination of Real-Time PCR Protocols
Initially, cell samples subjected to diverse conditions and transfected for a period of up to 24 hours are trialed via trypsinization before precipitation with TRizol® Reagent. This procedure extracts all RNA fragments, which are subsequently quantified and converted into complementary DNA through reverse transcription methodology. Ultimately, the PCR analyzer carries out real-time PCR amplification.
6. In-depth Study of Apoptosis Mechanisms
Upon completion of the transfection process, the cells undergo digestion using EDTA-free trypsin (the duration of trypsinization must be judiciously controlled to prevent false positives). Subsequently, centrifugation at 2,000 revolutions per minute for 5 minutes is employed to isolate the cells. Following this, the cells are washed twice with PBS (centrifuging at 2,000 rpm for 5 minutes each), resulting in a collection of 1 to 5×10^5 cells. A volume of 500 µL of Binding Buffer is added to resuspend these cells. Subsequently, 5 µL of Annexin V-FITC is incorporated, thoroughly mixed, and incubated at room temperature and in darkness for 5 minutes. Subsequently, an additional 5 µL of Caspase-3 substrate, Cropidium Iodide, is added, re-mixed, and allowed to react at room temperature and in darkness for 10 minutes. Throughout this one-hour period, the cells are observed and scrutinized utilizing flow cytometry.
7. Procedural Protocol for Lentivirus Infection of Cardiomyocytes
Ahead of infection, cardiomyocytes were plated in 6-well plates and nurtured over 2 to 3 days to facilitate restoration of their functional activity. Optimal cell density ranges between 40% and 60%. Five infection groups were established with varying MOI values: 3, 10, 20, 50, and 100, each comprising two replicate wells. One well received a final concentration of 5 µg/ml Polybrene, whilst the other remained devoid. Polybrene enhances viral cellular invasion yet may inflict harm on specific cell types. Post infection, the initial culture supernatant was discarded and substituted with fresh medium. Three to four days post infection, the cells were scrutinized under a fluorescence microscope; successfully infected cells exhibited green fluorescence. Efficacy of infection could be gauged either visually or via cell count to ascertain the optimal multiplicity of infection (MOI).
In accordance with experimental specifications, cardiomyocytes were plated in 6-well plates and nurtured over 2 to 3 days to facilitate restoration of their functional activity. Optimal cell density ranges between 40% and 60%. The selected lentivirus was thawed from − 80°C freezer, gradually defrosted on ice, and allowed to reach complete thawing prior to initiating the lentiviral infection protocol. The original medium in the Petri dish was replaced with half volume of fresh myocardial maintenance medium, supplemented with Polybrene at a final concentration of 5 µg/ml. Subsequently, the MOI value of 3 determined in the preceding experiment was transposed into the corresponding quantity of the targeted lentiviral stock solution. This solution was then added to the cardiomyocytes in the Petri dish as per this quantity, ensuring even distribution. Following addition of the lentiviral solution, the Petri dish was transferred directly into a 37°C incubator for a period of 4 hours. Upon completion of the 4-hour infection period, the Petri dish was removed and an additional half volume of fresh myocardial maintenance medium (Polybrene supplemented at a final concentration of 5 µg/ml) was added directly to the medium. The following day post infection (approximate duration of 12 to 16 hours), the original medium was exchanged for fresh myocardial maintenance medium (Polybrene-free) and continued incubation at 37°C. Seventy-two hours post infection, the dish was examined under a fluorescence microscope to assess GFP fluorescence expression efficiency of cardiomyocytes.
8. Implementation of Caspase-3 Activity Detection Technology
Firstly, adherence to the prescribed procedure is crucial, wherein the thawed reagent should be promptly utilized upon reversion to liquid form. Secondly, a standard dilution formulation is required, whereby the assay buffer and lysate are proportioned in accordance with a 9:1 ratio. Subsequently, the pNA (10 mM) present in the kit is serially diluted to concentrations of 0 µM, 10 µM, 20 µM, 50 µM, 100 µM, and 200 µM, serving as a control group for ensuing experiments. Following this, the optical density (OD) values of the aforementioned pRNA concentrations are assessed at a specific wavelength of 405 nm utilizing a microplate reader. On the basis of each pRNA concentration and its corresponding OD value, a standard curve is constructed. Subsequently, the cells are enzymatically digested via myocardial digest, centrifuged at a speed of 900 g at 4°C for a duration of 5 minutes, cardiomyocytes are isolated, and the supernatant is meticulously discarded to ensure maximum cellular aspiration.
Post-wash with pre-cooled PBS, repeat the process until complete supernatant clearance. Subsequently, operate under refrigerated conditions, add the lysate at a ratio of 100 µl lysate per 2 million cell volume, resuspend the pellet, and allow lysis to occur for 15 minutes. Once more, centrifuge at 16,000 g at 4°C for 15 minutes, discarding the supernatant, which constitutes the cell lysate. Carefully aspirate the supernatant and transfer it to a centrifuge tube previously treated with an ice bath. Immediately thereafter, assess the caspase 3 enzyme activity. Simultaneously, a subset of samples may be quantified employing the Bradford method, aiming to achieve a protein concentration within the range of 1–3 mg/ml to ensure that every 10 µl of the test sample comprises a minimum of 10–30 µg of protein content. Lastly, aliquot an appropriate quantity of Ac-DEVD-pNA (2 mM) and store it on an ice bath for future utilization.
Position the 96-well plate in a darkened environment at 37°C and incubate for 1–2 hours. Upon observing a discernible color shift, configure a microplate reader to register the OD value of the 96-well plate at a wavelength of 405 nm. Should the signal intensity alteration be insignificant, extend the incubation period until the 96-well plate exhibits a darker coloration and augmented signal. The absorbance of the caspase-3-catalyzed pNA in the sample is calculated using the corresponding equation. By referencing the standard curve, the precise quantity of pNA catalyzed in the sample can be ascertained. Given that one unit of enzyme activity is defined as the quantity of enzyme capable of hydrolyzing and cleaving 1 nmol of Ac-DEVD-pNA to yield 1 nmol of pNA of Caspase-3 per hour at 37°C with substrate saturation, we can indirectly estimate the number of enzyme activity units of Caspase 3 present in the test sample. Additionally, the Bradford method is employed to determine the protein concentration of the sample being analyzed. Ultimately, the enzymatic activity units of Caspase-3 contained in a unit mass protein of the sample being evaluated are calculated.
Examine the Relationships between MicroRNAs and Messenger RNAs within Drug Prediction Networks
The exceptional precision of the miRBase database (accessible via https://mirbase.org/) facilitated our acquisition of comprehensive annotation details pertaining to an extensive selection of meticulously chosen microRNA sites. Utilizing these data, we successfully identified the microRNA interacting with the BCL2L11 gene and established a microRNA-messenger RNA network model. Moreover, we utilized the TargetScan database (URL https://www.targetscan.org/) to validate BCL2L11 binding sites to microRNAs with substantial certainty.
The RNAactDrug Database (located at http://bio-bigdata.hrbmu.edu.cn/RNAactDrug/) serves as a comprehensive repository utilizing deep integration analysis of three pharmacogenomic databases (GDSC, CellMiner, and CCLE) across four molecular dimensions (expression, copy number variation, mutation, and methylation). This resource uncovers potential correlations between drug sensitivity and RNA entities, encompassing messenger RNA, long noncoding RNA, and microRNA. We procured information on microRNA, messenger RNA, and drug susceptibility. Concurrently, we employed the RNAfold database (URL http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi) and the Vfold3D database (URL http://rna.physics.missouri.edu/vfold3D/) to forecast the 3D structure of the targeted microRNA. Simultaneously, the three-dimensional structure of the drug molecule was retrieved from Pubchem.
Statistical Analysis Methods
All raw data manipulation is executed using R software (version 4.2.1). To discern if a significant disparity exists between two cohorts of independent samples, we utilize either the t-test or Wilcoxon's rank-sum test. For situations involving more than two independent groups, the Kruskal-Wallis test is applied to evaluate the discrepancy. All p-values are designated as bilateral, with p < 0.05 serving as the threshold for statistical significance.
Ethical Review Process
This research did not involve any human experimentation, hence no informed consent form was necessitated.
Consequentiality
Differentially expressed genes associated with apoptosis
Investigation into Whole Blood Peripheral Blood Mononuclear Cells from a collective number of 50 health individuals and a total of 49 patients afflicted with Acute Myocardial Infarction (AMI) was conducted utilizing the comprehensive RNA-seq dataset GSE66360. Upon preliminary exploration of the data, it became apparent that, although uniformity was apparent amongst all 99 sampled tissues, significant disparity existed between the two study cohorts portrayed in Fig. 2.A. This insight led us to employ the sophisticated differential expression analysis methodology to uncover the underlying biological disparities among these groups, culminating in the identification of 1605 candidate genes exhibiting varied expression profiles (Fig. 2.B). These were depicted in the intuitive volcano maps (Fig. 2.C) and heat maps (Fig. 2.D). Further, a curated list of 378 genes associated with programmed cell death via literature research was derived and an exclusive subset of 55 apoptosis-centric genes found to display statistically significant deviations in their expression levels (detailed in Table 1), comprising influential genes such as Interleukin 1β (IL1B), Phosphoinositide-dependent kinase interacting protein 1 (Phosphoinositide-dependent Kinase interacting Protein 1), PMAIP1, Cell Cycle Kinase Inhibitor 1A, CDKN1A), Growth Arrest and DNA Damage Inducible 45 Alpha, Growth arrest and DNA damage inducible 45 alpha, GADD45A), Matrix Metalloproteinase 9 (MMP9), Fibroblast Activation Protein, FOS), Interferon Response Factor 3 (IER3), Double Strand DNA Binding Protein 3, DDIT3), Nuclear Factor κB Inhibitor α (NFKBIA), B Cell Lymphoma/Leukemia 2 Family Member A1, Tumor Protein 53 Binding Protein 2, Tumor protein 53 binding protein 2, TP53BP2), X Chromosome Inactivation Specific Transcription Factor (XIST), Jun Protein (Jun Protein, JUN), Early Growth Response Gene 1 (EGR1), Granzyme B (Granzyme B), Tumor necrosis factor Ankyrin Repeat Containing Protein 3 (TNFAIP3), TNFR Receptor 4, TLR4), Cysteine Aspartate Specific Proteinase 10 (CASP10), Hemoxygenase 1 (Hemoxygenase 1), HMOX1, Serine/Threonine Kinase 17B, STK17B, Death Associated Protein Kinase 1, DAPK1), B Cell Lymphoma/Leukemia 2 Family Member L13 (BCL2L13), Interleukin 6 (Interleukin 6) IL6), ATP-Binding Cassette Transporter Subfamily B Member 1 (ATP-binding Cassette Transporter Subfamily B Member 1, ABCB1), TNF Receptor Superfamily Member 10C (TNFRSF10C), Difluorinated Flavone Binds, DFFB), Protein Kinase C Catalytic Subunit δ (PRKCD), Programmed Cell Death 4, PDCD4), Death Cones Attachment Protein γ as ppartner for TAPAPHERIN, DAXX), Peptidase with Glutamic-Aspartic Acid Specificity 2 (PTGS2), Interleukin 18 (Interleukin 18) (B Cell Lymphoma/Leukemia 2 Family Member L11, B cell lymphoma /Leukemia 2 family member L11, BCL2L11), Insulin-Like Growth Factor Binding Protein 3 (Insulin-like Growth Factor Binding Protein 3, IGFBP3), Butyrophilin Activating Receptor (BFAR), Myc gene (Myelocytomatosis oncogene, Interferon Regulatory Factor 27 (IRF27), Chemokine (C-X-C Motif) Ligand 8, CXCL8), CTX DNA Sequence (CTSD), CD40L High Molecule Weight Glycoprotein, CD40LG), Transthyretin (TGM2), Ras-related Nuclear Protein 34, Transthyretin (TGM2) RNF34, Interleukin 24 (IL24), KIT protooncogene (KIT), and Mitochondrial oxidative phosphorylation regulator 1 are prevalent, MOAP1), cysteine aspartate specific proteinase 6 (CASP6), phosphatase tensin homologue deleted on chromosome ten (PTEN), Cell Division Cycle 4, CDK4), Vascular Endothelial Growth Factor A (VEGFA), Tumor necrosis factor Superfamily Member 10 (TNFSF10), among others.
Investigation of crucial modules employing WGCNA methodology
Within the investigation of GSE48060 (N = 21; acute myocardial infarction [AMI] = 31), we meticulously determined the optimalsoft threshold parameter β at 6, serving as our foundation for subsequent examination (cf. Figure 3.A). Exemplified via the clustering diagram (Fig. 3.B), we discern the formation of clusters encompassing the two datasets and their corresponding hierarchical structure of seven modules. The correlation diagram further elucidates the interplay among these seven modules, with color utilized to visually represent their proximity (cf. Figure 3.C). Ultimately, we successfully established the correlations between the seven modules and phenotypes, with the notable correlation between the green module and the severity of acute myocardial infarction (AMI) being particularly noteworthy (cf. Figures 3.D and 3.E). Consequently, we opted to undertake a more comprehensive follow-up analysis of this green module.
GO and KEGG pathway enrichment analysis pertaining to the green module
Within the third grouping of 'green' modules unearthed by our innovative WGCNA methodology, a total of 1084 genes were chosen for additional bioinformatics scrutiny (cf., Fig. 4.A). This exploration aimed to elucidate the plausible roles and mechanisms depicted by these genes. Specifically, we applied the tailored tuple cluster paradigm to investigate the genes encompassed within these green modules (cf., Figs. 4.B for specific genes within the green module, and Fig. 4.C for selected gene expressions). This involved primarily correlation analyses of biological processes and functions across diverse hierarchical levels. The genes identified exhibited strong associations with numerous cellular functions, encompassing cell lethality, leucocyte-mediated immune response, lymphocyte-induced immune response, leucocyte-driven cytotoxicity, and the destruction of other biological entities. Furthermore, we executed an extensive examination of these genes utilizing the KEGG database, revealing significant correlations with various signaling pathways, such as leucocyte-induced immune response, cell lethality, lymphocyte-induced immune response, leucocyte-driven cytotoxicity, and lymphocyte-regulated immune regulation (cf., FIGS. 4.D and 4.E for comprehensive analysis).
Determination of pivotal genes and utilization of the principle of Mendelian randomization for analysis
Following extensive systemic examination of AMI genes differing in expression, apoptogenic genes, and green module genes, we accurately pinpointed two vital genes - BCL2L11 and PTEN (detailed representation is provided in Fig. 5.A). Furthermore, to bolster the credibility and scientific rigor of our Methods Research, we incorporated the innovative strategy of Mendelian randomization into analyzing the extensive data acquired from GWAS (further elucidated in Fig. 5.B). To guarantee the validity of this analysis, we chose two GWAS investigations, intimately linked to AMI, boasting comparatively autonomous data sets as investigative subjects. All scrutinized SNPs exhibit F statistics exceeding 10, signifying their non-trivial IV status. The primary data encompassed within the AMI dataset demonstrate an intimate connection with the BCL2L11 dataset. Notably, three SNPs are particularly pertinent to the BCL2L11 dataset (illustrated in Fig. 5.C). Given the potential causal link between BCL2L11 and acute myocardial infarction, we initially discovered a substantial inverse correlation between BCL2L11 and acute myocardial infarction from the findings of the initial dataset (identifier: eiu-a-798). Conversely, in the subsequent dataset (identifier: ukb-saige-411.2), despite observing the identical negative correlation pattern, it did not attain statistical significance (depicted in Fig. 5.D). As per the outcomes of IVW analysis, the odds ratio (OR) of the former dataset was 0.83 (95% confidence interval (CI) = 0.72–0.97; P = 0.017), whereas in the latter analysis, OR transformed to 0.86 (95%CI = 0.72–1.02; P = 0.080). Additional weighted median analysis revealed that the results of the former dataset were statistically significant, whilst the remaining two MR Analysis methodologies failed to draw analogous conclusions. To secure more definitive evidence, we also executed a meta-analysis of these two datasets. By computing I2 to gauge heterogeneity, a fixed-effect model was chosen for subsequent analysis, which unequivocally demonstrated a negative correlation between BCL2L11 and acute myocardial infarction (OR = 0.84,95%CI = 0.75–0.94, P < 0.01) (as illustrated in Fig. 5.E).
Experimental validation
During the execution of this investigation, an extensive exploration into the impact of hypoxia on gene expression and apoptosis regulation commenced through conducting cellular cultivation, building upon prior preliminary experimentation, which yielded varying levels of miR-30e-5p transcripts post diverse intervals of exposure to identical concentrations of H2O2 (detailed datasets are illustrated in Fig. 6's Table 1). Two significant periods of interest were identified, including 24h post treatment under various H2O2 dosages yielding distinct miR-30e-5p expressions (Fig. 6's Table 2), followed by treatments employing 75µM and 100µM H2O2, leading to subsequent results depicted in Tables 3 and 4.
Upon fractionating the cells, lentiviral transfer methods were implemented (Table 5 shows accompanying outcomes), resulting in the creation of four pools of pNA standards (illustrated in Fig. 6's A).
The pivotal timeframe of this research was chosen as 24 hours of hypoxia, during which comprehensive analysis and comparison were performed. Initially, gene expression patterns in groups N and H following hypoxia were scrutinized. Results revealed a substantial decrease in miR-30e-5p expression in group H (P < 0.05) (Fig. 7.A illustrates the specific expression level). This observation implies that hypoxia may alter cell physiology via controlling specific gene expression. Subsequently, a miR-30e-5p overexpression model was established utilizing gene augmentation techniques based on transfection methodologies. Post model establishment, the NC + H group and the miR + H group were compared and evaluated. Results indicated a significant increase in Mir-30E-5p expression in the miR + H group (P < 0.05). This outcome further substantiated the efficacy of the constructed miR-30e-5p overexpression model.
Subsequently, the apoptotic rate of CA16 cells post hypoxia induction was initially examined through Caspase-3 activity assays. As demonstrated in the graph, compared to group N, the Caspase-3 activity level in group H post hypoxia exhibited a marked upward trend (P < 0.05) (Fig. 7.B illustrates these findings). These observations suggest that hypoxia might stimulate apoptosis. To obtain more precise measurements, apoptosis kits and flow cytometry were utilized. The results corroborated those from the Caspase-3 activity tests. Specifically, compared to group N, the apoptosis percentage of CA16 cells in group H post hypoxia was considerably elevated (P < 0.05) (Fig. 7.C depicts these results). However, following lentivirus infection with miR-30e-5p overexpression, the apoptosis ratio of CA16 cells in the Mir-+ H group was notably reduced when compared to the NC + H group (P < 0.05). These findings indicate that overexpression of miR-30e-5p can efficiently suppress apoptosis triggered by hypoxia. Furthermore, flow cytometry results are presented in Fig. 7.D for clarity.
miRNA–mRNA networks and drug prediction
Initially, comprehensive data amalgamation and scrutiny were conducted utilizing miRBase database, followed by production of the miRNA network diagram featuring BCL2L11 as the primary regulatory target (detailed illustrations are presented in Figs. 8.A, 8.B, and 8.C). Subsequently, employing precise miRNA sequencing methodologies, we delved into the normal cohort and the acute myocardial infarction (AMI) group within clinical specimens. Concurrently, meticulous statistical evaluation of these data was performed, revealing that only one miRNA, miR-30e-5p, exhibited substantial differential expression in the AMI group (p value < 0.05), exhibiting a marked decrease in expression when compared to the normal group. Notably, the conserved interaction interface between miR-30e-5p and BCL2L11 mRNA was identified via TargetScan database (Figs. 9.A and 9.B provide additional details). Furthermore, through extensive exploration using the RNAactDrug database, we discovered that the sensitivity of Ispinesib Mesylate, Bleomycin (50 uM), and several other drugs demonstrated a notable positive correlation with the expression level of BCL2L11. Conversely, WZ3105 displayed a significant inverse correlation. Additionally, we procured the three-dimensional structural data of Ispinesib Mesylate, Bleomycin, and WZ3105 from PubChem database, and computationally predicted the 3D structure of miR-30e-5p using RNAfold and Vfold3D databases. Ultimately, the corresponding molecular mechanism model was successfully formulated (detailed depictions are illustrated in Figs. 9.C, 9.D, and 9.E).