Single Nucleotide Polymorphism in microRNA Genes and their association with Lung Disorders

Abstract

Background: Chronic Obstructive Pulmonary Disorder (COPD) and lung cancer represent significant global health challenges, driven by complex interactions between genetic predispositions and environmental factors like smoking and biomass exposure. Despite extensive research, the precise molecular mechanisms underlying their pathogenesis, particularly the role of microRNAs (miRNAs), remain incompletely understood. MicroRNAs are small, non-coding RNA molecules that post-transcriptionally regulate gene expression by binding to the 3' untranslated regions (3'UTRs) of target messenger RNAs (mRNAs), influencing crucial cellular processes such as proliferation, apoptosis, and inflammation. Single nucleotide polymorphisms (SNPs) within miRNA genes or their target sites can significantly alter miRNA function, leading to aberrant gene expression and contributing to disease development. Existing literature highlights several critical gaps. Firstly, there is a notable lack of regional and ethnic diversity in studies investigating miRNA SNPs and COPD susceptibility, particularly in the North Indian population. This gap limits the understanding of ethnic-specific genetic predispositions. Secondly, while the role of miRNAs in gene silencing is established, the structural basis of miRNA-mRNA-Argonaute (AGO) protein interactions in lung cancer remains underexplored. A comprehensive bioinformatics approach integrating multiple predictive algorithms and thermodynamic analysis is needed to identify functionally relevant miRNA-target site SNPs (miR-TS-SNPs) in lung cancer. Addressing these gaps is crucial for advancing the understanding of miRNA biology in respiratory disorders and paving the way for novel diagnostic and therapeutic approaches. Objectives: The primary objective of this study is to comprehensively investigate the intricate role of miRNA SNPs in the pathogenesis and clinical outcomes of COPD. This involves identifying associations between specific miRNA SNP variants and susceptibility to COPD within the North Indian population, correlating these genetic variations with various clinical parameters and symptoms. Furthermore, the study aims to predict and analyze the functional impact of SNPs located in miRNA binding sites within the genes involved in lung cancer and COPD, utilizing advanced bioinformatics and structural modeling techniques to elucidate their roles in gene regulation and disease progression. Methodology: A comprehensive methodology was employed, combining a case-control genetic association study with extensive bioinformatics analyses. For COPD Susceptibility (Case-Control Study): A case-control study was designed, recruiting 323 COPD cases and 350 healthy controls from the North Indian population, all adhering to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2024 guidelines. Ethical approval was obtained, and informed consent was acquired from all participants. Detailed demographic and clinical data, including age, gender, smoking status, pack-years, spirometry values (FEV1, FVC, FEV1/FVC ratio), GOLD severity and group, mMRC, and CAT scores, were collected. Genomic DNA was extracted from peripheral blood samples using a modified standard protocol and assessed for quality and quantity. Genotyping of six specific miRNA SNPs (miR-25 rs1527423 T>C, miR-3117 rs7911488 A>G, miR605 rs2043556 A>G, miR-149 rs2292832 C>T, miR-499 rs3746444 C>T, and miR-608 rs4919510 C>G) was performed using the PCR-RFLP technique, with 20% random sample reproducibility testing. Statistical Analysis for COPD Susceptibility: Demographic analysis involved Chi-square tests for categorical variables and t-tests for continuous variables. Allelic and genotypic frequencies were assessed, and Hardy-Weinberg Equilibrium (HWE) was tested. Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusted for age, gender, and smoking status, to determine associations with COPD risk under codominant, dominant, and recessive models. Stratified analyses were conducted based on age, gender, smoking status, pack-years, and clinical parameters. Combinatorial analysis identified significant SNP-SNP doublet interactions, with Benjamini-Hochberg False Discovery Rate (FDR) correction applied for multiple comparisons. Multifactor Dimensionality Reduction (MDR) analysis was performed to detect complex genegene interactions, evaluating cross-validation consistency (CVC) and prediction error. Classification and Regression Tree (CART) analysis was utilized to construct decision trees, identifying subgroups with varying COPD risk. For miR-TS-SNPs in Lung Cancer Genes (Bioinformatics Analysis): A comprehensive bioinformatics pipeline was developed. A list of lung cancer-associated genes was retrieved from UniProtKB. Putative miR-TS-SNPs in the 3'-UTR regions of these genes were identified using MirSNP, miRdSNP, and miRNASNP databases. SNPs with a minor allele frequency (MAF) > 0.1% were selected, and cross-prediction was performed using TargetScan Human 7.1. The impact of miR-TS-SNPs on miRNA:mRNA binding stability was assessed by calculating Gibbs binding free energy (ΔG) using RNAcofold, and SNPs were categorized into high-, mid-, and low-impact tiers based on ΔΔG values. Gene expression profiling of highimpact genes was performed in various lung cancer cell lines using EMBL's Expression Atlas and in normal vs. lung adenocarcinoma (LUAD) tissues using UALCAN. Genotype-Tissue Expression (GTEx) portal was used to identify expression quantitative trait loci (eQTLs) in normal lung tissue. Enrichment analysis (WebGestalt, KOBAS-I) and gene network analysis (GeneMANIA in Cytoscape) were conducted to understand biological processes, molecular functions, and pathways. Survival analysis for high-impact SNP target genes was performed using the Kaplan-Meier plotter (KM Plotter) with TCGA data. For Structural Dynamics of AGO-mediated Gene Silencing in Lung Cancer: MiRNAs targeting lung cancer oncogenes and tumor suppressor genes were screened from miRCancer and miRDisease, validated with MiRWalk 2.0 and miRTarBase for MFE. Functional annotation and enrichment analysis of target genes were performed using DAVID, UniProt, and ShinyGO. 2D and 3D structural predictions of miRNA-mRNA duplexes were done using RNAfold and RNA-COMPOSER. Argonaute (AGO) protein structure (PDB ID: 3F73) was prepared. Molecular docking between AGO protein and miRNAs, and between AGO protein and miRNAmRNA duplexes, was performed using the HDOCK server, followed by interaction analysis using Discovery Studio Visualize, PLIP, and PDBsum. miRNA expression profiling in various human cancers and LUAD was analyzed using TCGA and UALCAN. Receiver Operating Characteristic (ROC) curve analysis and survival prediction (KM Plotter) were conducted for selected miRNAs. For miR-TS-SNPs in COPD Genes (Bioinformatics Analysis): COPD-related genes were retrieved from UniProtKB, DisGeNET, literature, and STRING. miR-TSSNPs were identified using PolyMiRTS Database 3.0, filtered by MAF > 0.05, and cross-validated with MiRWalk, TargetScan, miRdb, and miRTarBase. The impact on miRNA-mRNA binding stability was calculated using RNAcofold. GTEx portal was used for lung eQTL analysis. Enrichment (DAVID, Metascape, Toppgene, WebGestalt) and network analysis (GeneMANIA) were performed to understand functional associations. Results: COPD Susceptibility in the North Indian Population: A significant association was identified between the miR-25 T>C rs1527423 polymorphism and increased COPD risk. The genotypic frequencies differed significantly between cases and controls (χ 2 =33.85, df=2, p < 0.0001). The heterozygous (TC) genotype was over-represented in cases (13.93%) compared to controls (2.28%). Under the codominant model, the TC genotype conferred a 6.058-fold increased risk (OR=6.058, 95%CI= 2.77-13.20, p < 0.001), and the dominant model (TC+CC) showed a 6.381-fold increased risk (OR=6.381, 95%CI=2.936-13.87. p< 0.0001), both remaining significant after Bonferroni correction. Stratified analysis further revealed this association across all age groups (<65 years: OR=5.73, p=0.0009; ≥65 years: OR=9.26, p=0.0019), and specifically in males (OR=5.61, p<0.0001) and smokers (OR=4.71, p=0.0002). No significant association was found between miR-25 rs1527423 and clinical parameters (COPD duration, GOLD score, CAT score, GOLD group, mMRC grade) or clinical symptoms (cough, expectoration, breathlessness, mucus production, body movement limitations). Pulmonary Function Tests (PFTs) also showed no significant differences across miR-25 genotypes. For miR-3117 A>G rs7911488, no overall significant association with COPD risk was observed. However, age-stratified analysis revealed a potential age-dependent effect: the AG genotype showed a significant protective effect in individuals younger than 65 years (AOR = 0.56, p = 0.04), while the AG+GG genotypes were associated with an increased COPD risk in those aged ≥65 years (AOR = 1.61, p = 0.03). The AG genotype was significantly associated with higher odds of expectoration (AOR = 3.54, p = 0.01) but lower risk of breathlessness (AOR = 0.31, p = 0.024) and body movement difficulties (AOR = 0.45, p = 0.038). miR-605 A>G rs2043556 showed no overall significant association with COPD risk. However, in non-smokers, the AG (OR = 0.16, p = 0.022) and GG (OR = 0.11, p = 0.0053) genotypes were associated with a significantly reduced risk of COPD, suggesting a strong protective effect. Conversely, in heavy smokers (≥24 pack-years), the AG genotype was associated with a significantly increased risk (OR = 9.01, p = 0.0103). miR-149 C>T rs2292832 showed no overall significant association with COPD risk. However, the CT genotype showed a statistically significant association with a higher risk of being in the GOLD Group E (OR = 2.51, 95% CI: 1.08-5.85, p = 0.0331), indicating a link to more severe COPD. miR-499 C>T rs3746444 showed no significant association with overall COPD risk or in any stratified analyses. miR-608 C>G rs4919510 showed a significant association with increased COPD risk in the overall population, particularly for the CG genotype (AOR = 1.43, p = 0.03) and under the dominant model (AOR = 1.45, p = 0.02). Age-stratified analysis revealed that the GG genotype conferred a higher risk in individuals <65 years (OR = 2.87, p = 0.02), while the CG genotype showed a stronger association in those ≥65 years (OR = 2.38, p = 0.0009). In males, the CG genotype was associated with increased risk (OR = 1.41, p = 0.042). In smokers, the dominant model showed increased risk (OR = 1.48, p = 0.028), but the GG genotype showed a protective effect in non-smokers (OR = 0.36, p = 0.04). Combinatorial analysis of SNP-SNP interactions identified several significant doublet combinations increasing COPD risk, notably miR-3117 A>G rs4655646 and miR-25 T>C rs1527423 (OR=25.69, p=0.024), and miR-605 A>G rs2043556 and miR-25 T>C rs1527423 (OR=21.00, p=0.0007). MDR analysis identified miR-25 as the best single-factor model (p=0.06). CART analysis confirmed miR-25 as the root node, indicating its central role as the strongest risk factor, with specific genotype combinations showing up to an 11-fold increased risk. miR-TS-SNPs in Lung Cancer Genes (Bioinformatics Analysis): A comprehensive bioinformatics pipeline identified 100 miR-TS-SNPs with MAF > 0.1% in lung cancer-associated genes. Calculation of Gibbs binding free energy (ΔΔG) categorized 29 SNPs as high-impact. Genes harboring these high-impact SNPs (e.g., EIF2AK1, AKAP1, EGFR, CDKN1A) were highly expressed in various lung cancer cell lines. Enrichment analysis revealed their involvement in phosphotransferase and kinase activities, cell death, and cell cycle, with KEGG pathways showing enrichment in "Pathways in Cancer" and "miRNAs in Cancer." GTEx analysis identified eQTLs in normal lung tissue for FAM124B (rs3738954, rs3738953) and PPIL2 (rs12484060). Survival analysis showed that high expression of PIK3C2A, PDLIM5, RET, and CSF1R was associated with significantly improved survival in lung cancer patients. Structural Dynamics of AGO-mediated Gene Silencing in Lung Cancer: Thirty-six miRNAs targeting lung cancer oncogenes and tumor suppressor genes were shortlisted. Functional annotation of their target genes revealed involvement in apoptosis, cell cycle, cell proliferation, and angiogenesis, with VEGFA, PTEN, and TP53 being key genes. Molecular docking studies demonstrated strong binding affinities between selected miRNAs (miR-21-5p, miR-221-3p, miR-126-3p, miR-34a-5p) and their target mRNAs (PTEN, VEGFA, TP53), and with the AGO protein. Hydrogen bonds and hydrophobic interactions were crucial for these stable complexes. miRNA expression profiling showed miR-21-5p and miR-34a-5p were significantly overexpressed in LUAD compared to normal tissue. Survival analysis indicated that high expression of miR-21-5p was associated with poorer overall survival in LUAD patients (HR=1.41, p=0.021). ROC analysis suggested miR-126-5p as a potential predictive biomarker (AUC=0.607). miR-TS-SNPs in COPD Genes (Bioinformatics Analysis): Fifty-seven COPD-related genes were retrieved. PolyMiRTS identified 634 SNPs in their 3'-UTR regions, which were narrowed down to 51 high-confidence miR-TS-SNPs with MAF > 0.05. The impact on miRNA-mRNA binding stability was quantified, categorizing SNPs into high-, mid-, and low-impact tiers. rs1058747 (PHLPP2 C>T) showed a distinctly high |ΔΔG|total value (25.37), indicating a substantial impact. GTEx analysis identified eQTLs for rs1058750 C>T and rs2052585 C>G in the PHLPP2 gene in normal lung tissue. Enrichment analysis revealed the involvement of these genes in hemostasis, blood coagulation, apoptosis, and "tumor necrosis factor binding," with "aldosterone-regulated sodium reabsorption" as a major pathway. Conclusion: In summary, this study provides compelling evidence for the significant association of the miR25 rs1527423 polymorphism with COPD susceptibility in the North Indian population, highlighting its potential as a central genetic risk factor, particularly in males and smokers. The comprehensive bioinformatics investigation successfully identified high-confidence miR-TS-SNPs in genes relevant to both lung cancer and COPD, elucidating their predicted impact on miRNA-mRNA interactions and their involvement in critical disease pathways. Furthermore, the structural dynamics analysis of AGO-miRNA and AGO-miRNA-mRNA complexes offers novel insights into the molecular mechanisms of miRNA-mediated gene regulation in lung cancer. These findings collectively underscore the multifaceted role of miRNAs and their genetic variants in the pathogenesis of lung disorders, providing valuable insights into potential regulatory mechanisms and identifying promising targets for future research and the development of novel diagnostic and therapeutic strategies.