Hereditas最新文献

Background and purpose: Research shows that people with multiple sclerosis (MS) are more likely to experience cardiovascular complications. However, the precise mechanisms underlying this association remain unclear. This study investigated the causal relationship between MS and coronary heart disease (CHD) using Mendelian randomization (MR) techniques to clarify direct effects and identify relevant target genes.

Methods: We conducted various methods, including two-sample MR. method, reverse, and multivariable MR analyses, to examine the causal relationship between MS and CHD. These. methodologies effectively mitigate confounding variables and neutralize adverse causal effects. Additionally, the study explored the involvement of social factors through a two-step MR analysis. The research team performed a thorough screening of differentially expressed genes in MS based on GEO database, identifying potential target genes that may be associated with genetic risk of CHD. Enrichment analyses and protein-protein interaction studies were used to elucidate biological functions associated with these genes. We included colocalization analysis and summary data-based Mendelian randomization (SMR) method for further screening of core genes to obtain target genes.Finally, we investigated how these genes might affect health by conducting a phenome-wide MR analysis.

Results: Our findings revealed that genetic predisposition to MS significantly increases the risk of CHD, with an IVW-MR analysis yielding an odds ratio of 1.091 (95% CI: 1.030, 1.155, P = 0.0029). Mediation analysis revealed that frailty mediated 20.2% of the effect of MS on CHD (P = 0.026), suggesting that frailty is a critical pathway in this relationship. Additionally, low-density lipoprotein (LDL) is associated with an increased risk of developing both MS and CHD. We identified 3025 differentially expressed genes and 130 genes causally linked to CHD. Protein-protein interaction network analysis identified 77 interacting genes, with core genes such as SREBF1 involved in organelle regulation and nucleic acid metabolism. Colocalization analysis further supported the presence of shared genetic variants between IL6R and SREBF1 associated with CHD, with posterior probabilities (PPH4) of 90.2% and 92.3%, respectively. Interestingly, summary mendelian randomization (SMR) analysis revealed that SREBF1 may be a target gene for MS(bSMR=-0.174,PSMR = 0.0218, PHEIDI = 0.2806, topSNP: rs12951376). Further analysis of the phenome-wide MR did not find significant evidence of side effect associated with targeted therapy against SREBF1.

Conclusion: This study provided genetic evidence indicating that indivduals with MS face higher risk of coronary heart disease. Furthermore, SREBF1 maybe a critical target gene which would significantly contribute to drug development.

Background: Rheumatoid arthritis (RA) increases the risk of stroke. However, the relationship between RA and stroke remains unclear. This study aimed to explore the shared genetics architecture (i.e., common genetic basis between different traits, diseases, or phenotypes) of RA and stroke, aiming to improve the intervention and management of patients with RA and stroke.

Methods: Pooled statistics from publicly available genome-wide association studies for RA (8,255 cases and 409,001 controls) and stroke (43,132 cases and 43,132 controls) were used. A genome-wide positive association was conducted to (examine the comprehensive effects of genetic variants on a particular trait, disease, or phenotype at the genome-wide scale). Local genetic correlation studies used linkage disequilibrium score regression and super genetic covariance analyzer. Single nucleotide polymorphisms (SNPs) at risk were identified using genome-wide association study multiple trait analysis and PLINK software (P_snp <5e-08), followed by functional localization and annotation using Functional Mapping and Annotation of Genome-Wide Association Studies to identify specific genes and genetic variants that may contribute to the disease. Finally, a transcriptome-wide association study explored the relationship between genes and their association with RA risk.

Results: A genome-wide significant positive correlation was evident between RA and stroke (genetic correlation = 0.3756). Among the localized genomic regions, the correlation between RA and stroke in the region of chr2:201572564-202,829,668 was the most significant (p = 0.0015). We identified 179 significant SNPs and five common risk genes for RA and stroke (IRF5, RNASET2, ZNF438, UBE2LS, and SYNGR1). These genes are involved in the immune-inflammatory pathway.

Conclusions: The findings suggest a shared genetic structure between RA and stroke. These findings may provide new insights into RA and stroke pathogenesis, and contribute to the development of new diagnostic markers and therapeutic targeted drugs to improve the clinical outcomes of patients with RA and stroke.

Background: Endoplasmic reticulum stress (ERS) and mitochondrial dysfunction (MD) involved in bone metabolism disorders. However, the particular mechanisms of ERS and MD related genes (ERS&MDRGs) in osteoporosis (OP) have not been elucidated. In present study, biomarkers related to ERS and MD in OP were identified.

Methods: Differentially expressed genes (DEGs) were obtained based on GEO dataset. ERS&MDRGs were derived from Genecard database. Initially, ERS&MD related DEGs (ERS&MDRDEGs) were obtained by overlapping DEGs and ERS&MDRGs. The key module was screened by WGCNA. The intersection of ERS&MDRDEGs and key module was screened by machine learning to obtain key genes. Then, receiver operating characteristic curve (ROC) was drawn to calculated diagnostic accuracy of key genes. The ssGSEA and Cibersort algorithms were performed to analyze immune cell infiltration. The miRNA-mRNA-TF network were draw by cytoscape software. Moleculaer docking and DGIdb database were employed for screening potential drugs. Finally, the expression of key genes was verified by qRT-PCR.

Results: The 122 ERS&MDRDEGs were obtained by preliminary screening. ERS&MDRDEGs were mainly enriched in lipid metabolism, calcium ion transport, and ossification. The 5 key genes were identified, including AAAS, ESR1, SLC12A2, TAF15, and VAMP2. Immune infiltration analysis showed monocyte and macrophage were different between OP and control groups. The miRNA-mRNA-TF regulatory network indicated has-miR-625-5p, has-miR-296-3p, CTCT and EP300 as potential regulatory targets. The 2 potential small molecule drugs, namely bumetanide and elacestrant were screened. The expression of AAAS, ESR1, VAMP2 were higher, and SLC12A2 and TAF15 were lower in OP than control group.

Conclusion: This research identified 5 key genes AAAS, ESR1, SLC12A2, TAF15 and VAMP2. Bumetanide and elacestrant were potential drugs. These findings provided valuable insights into the pathophysiology of OP and the development of new therapeutic strategies.

Background: Previous research has established a correlation between immune cells and an increased likelihood of Chronic pancreatitis (CP). However, studies investigating the causal relationship remain limited.

Methods: This study utilized publicly available genome-wide association study (GWAS) databases and conducted a two-sample Mendelian randomization (MR) analysis to examine the causal relationships (CRs) among 731 immune cells, 1,400 metabolites, and CP. Mediation MR analysis was also performed to assess whether metabolites serve as mediators in the relationship between immune cells and CP.

Results: Our study identified four immune cell types that act as risk factors for CP, with odds ratios (OR) ranging between 1.076 and 1.177. In contrast, three immune cell types were found to serve as protective factors, exhibiting OR values between 0.846 and 0.913. Additionally, four metabolites were implicated as risk factors for CP, with OR values ranging from 1.243 to 1.334. On the other hand, eight metabolites were discovered to have a protective effect, with OR values between 0.580 and 0.871. Mediation analysis revealed that cholesterol levels mediate the causal relationship between immune cell cells and CP, with a mediation effect of 0.00918, accounting for 9.18% of the total effect.

Conclusions: Our findings provide valuable insights into the genetic underpinnings of CP, highlighting the role of immune cells and plasma metabolites in its pathogenesis. The mediation analysis further suggests that the presence of CD25 on IgD-CD38-B cells may facilitate CP development through the elevation of cholesterol levels. These results not only deepen our understanding of CP but also suggest potential biological targets for therapeutic intervention. Future clinical research should focus on these mediators to develop more effective treatment strategies for CP.

Objectives: The study investigates the role of Cell Division Cycle Associated (CDCA) genes in colorectal cancer (COAD) by analyzing their differential expression, epigenetic alterations, prognostic significance, and functional associations.

Methodology: This study employed a detailed in silico and in vitro experiments-based methodology.

Results: RT-qPCR assays reveal significantly elevated mRNA levels of CDCA2, CDCA3, CDCA4, CDCA5, CDCA7, and CDCA8 genes in COAD cell lines compared to controls. Bisulfite sequencing indicates reduced promoter methylation of CDCA gene promoters in COAD cell lines, suggesting an epigenetic regulatory mechanism. Analysis of large TCGA datasets confirms increased CDCA gene expression in COAD tissues. Survival analysis using cSurvival database demonstrates negative correlations between CDCA gene expression and patient overall survival. Additionally, Lasso regression-based models of CDCA genes predict survival outcomes in COAD patients. Investigating immune modulation, CDCA gene expression inversely correlates with immune cell infiltration and immune modulators. miRNA-mRNA network analysis identifies regulatory miRNAs targeting CDCA genes, validated by RT-qPCR showing up-regulation of has-mir-10a-5p and has-mir-20a-5p in COAD cell lines and tissues. Drug sensitivity analysis suggests resistance to specific drugs in COAD patients with elevated CDCA gene expression. Furthermore, CDCA gene expression correlates with crucial functional states in COAD, including "angiogenesis, apoptosis, differentiation, hypoxia, inflammation, and metastasis." Additional in vitro experiments revealed that CDCA2 and CDCA3 knockdown in SW480 and SW629 cells significantly reduced cell proliferation and colony formation while enhancing cell migration.

Conclusion: Overall, the study elucidates the multifaceted role of CDCA genes in COAD progression, providing insights into potential diagnostic, prognostic, and therapeutic implications.

Background: Observational studies have shown an association between cerebrospinal fluid (CSF) metabolites and low back pain (LBP), but the causal relationship between these factors remains unclear.

Methods: We performed a two-sample Mendelian randomization (MR) analysis to examine whether there is a causal relationship between CSF metabolites and LBP. We applied several MR methods, including inverse variance weighting, weighted median, MR-Egger, Wald ratio, and MR-PRESSO, to test the causal relationship and conducted a sensitivity analysis to assess the robustness of the results.

Results: We identified a total of 12 CSF metabolites significantly associated with LBP, of which Bilirubin, 5,6-dihydrothymine, Erythronate, Mannitol/sorbitol, and Butyrate have a potential inhibitory causal effect on LBP risk (p < 0.05). Meanwhile, 2-hydroxyadipate, Gamma-glutamyl-alpha-lysine, Indoleacetate, N-acetylputrescine, Palmitoyl dihydrosphingomyelin, S-methylcysteine, and 2,3-dihydroxy-5-methylthio-4-pentenoate play a causal role in increasing the risk of LBP (p < 0.05). No significant estimates of heterogeneity or pleiotropy were detected.

Conclusion: Our study emphasizes the causal relationship between CSF metabolites and LBP risk, providing reference for clinical treatment and prognosis of LBP.

Background: Immunotherapy has introduced new breakthroughs in improving the survival of head and neck squamous cell carcinoma (HNSCC) patients, yet drug resistance remains a critical challenge. Developing personalized treatment strategies based on the molecular heterogeneity of HNSCC is essential to enhance therapeutic efficacy and prognosis.

Methods: We integrated four HNSCC datasets (TCGA-HNSCC, GSE27020, GSE41613, and GSE65858) from TCGA and GEO databases. Using 10 multi-omics consensus clustering algorithms via the MOVICS package, we identified two molecular subtypes (CS1 and CS2) and validated their stability. A machine learning-driven prognostic signature was constructed by combining 101 algorithms, ultimately selecting 30 prognosis-related genes (PRGs) with the Elastic Net model. This signature was further linked to immune infiltration, functional pathways, and therapeutic sensitivity.

Results: CS1 exhibited superior survival outcomes in both TCGA and META-HNSCC cohorts. The PRG-based signature stratified patients into low- and high-risk groups, with the low-risk group showing prolonged survival, enhanced immune cell infiltration (B cells, T cells, monocytes), and activated immune functions (cytolytic activity, T cell co-stimulation). High-risk patients were more sensitive to radiotherapy and chemotherapy (e.g., Cisplatin, 5-Fluorouracil), while low-risk patients responded better to immunotherapy and targeted therapies.

Conclusion: Our study delineates two molecular subtypes of HNSCC and establishes a robust prognostic model using multi-omics data and machine learning. These findings provide a framework for personalized treatment selection, offering clinical insights to optimize therapeutic strategies for HNSCC patients.

Background: Mitochondrial permeability transition (MPT)-driven necrosis (MPTDN) is a non-apoptotic mode of cell death triggered by oxidative stress and cytosolic Ca²⁺ overload. Recent evidence suggests that activation of MPTND can effectively induce cancer cell death and may represent a novel therapeutic strategy for cancer. Yet, the role of MPTDN-related genes in non-small cell lung cancer (NSCLC) remains unrevealed. This study aimed to identify MPTDN-related biomarkers for predicting prognosis and guiding treatment in NSCLC.

Methods: Gene expression profiles and clinical information of NSCLC were collected from public databases, and MPTDN-related genes were obtained from published article. Differential expressed MPTDN-related genes in NSCLC and control were screened, and molecular clusters were obtained. Based on the differentially expressed genes (DGEs) between clusters, univariate Cox and LASSO regression analyses were performed to screen biomarkers, followed by nomogram construction. Correlations between these biomarkers and immune cell infiltration, immune checkpoints, and chemotherapeutic agents were observed. Expression levels of MPTDN-related biomarkers were detected using RT-qPCR in NSCLC tissues and cells. Moreover, the biological function of ARL14 in NSLCL was verified in vitro.

Results: Thirty-five differential MPTDN-related genes were identified, and two molecular clusters were obtained. Three biomarkers with prognostic values were finally screened, including ARL14, ZDHHC11B, and HLF. Among them, ARL14 was significantly upregulated in tumor samples, while ZDHHC11B and HLF were downregulated. Nomogram containing three genes exhibited predictive accuracy in 1, 3, and 5-year survival rates. Three gene were strongly associated with most immune cells, immune checkpoints, and drugs sensitivity. RT-qPCR confirmed that expression levels of three genes in tissues or cells were consistent with the results of bioinformatics analysis. Finally, ARL14 knockdown inhibited the malignant phenotype of NSCLC cells.

Conclusion: We first performed the comprehensive analysis of MPTDN in NSCLC and screened three NSCLC-related biomarkers as promising biomarkers. ARL14 might be a new potential target for therapy of NSCLC.

Background: Gastric cancer (GC) presents a significant global health burden, necessitating a deeper understanding of its molecular underpinnings for improved diagnostics and therapeutics.

Methods: In this study, we investigated the expression profiles and clinical implications of MAP3K genes in GC using in silico and in vitro experiments.

Results: Utilizing RT-qPCR analysis, we observed significant up-regulation of MAP3K1, MAP3K4, MAP3K5, MAP3K6, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 in GC cell lines, while MAP3K2, MAP3K3, MAP3K11, MAP3K12, MAP3K13, MAP3K14, and MAP3K15 exhibited down-regulation. Prognostic evaluation revealed that elevated expression of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 was associated with shorter overall survival (OS), emphasizing their clinical significance. Furthermore, the diagnostic potential was demonstrated through robust Receiver operating characteristics (ROC) curve analysis, indicating the strong discriminatory power of these genes in distinguishing GC patients. Proteomic analysis further confirmed the higher expression of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 genes in GC. Methylation profiling further supported the idea that promoter hypomethylation of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 genes was associated with their up-regulation. Single-cell functional analysis elucidated the involvement of MAP3K genes in shaping the tumor microenvironment. miRNA-mRNA network analysis revealed intricate regulatory mechanisms, with hsa-mir-200b-3p emerging as a key regulator. Finally, the MAP3K1 knockdown has shown significant impacts on the cellular behavior of the BGC823 cells.

Conclusion: This comprehensive assessment provides valuable insights into the role of MAP3K genes in GC, offering avenues for further research and therapeutic exploration.

Background: Previous observational studies have reported an association between chronic obstructive pulmonary disease (COPD) and osteoporosis (OP). The aim of this study is to investigate the causal relationship between COPD and OP by two-sample Mendelian randomization (MR) analysis. The current status of cross-sectional research between COPD and OP in the past decade was explored through bibliometrics.

Methods: Single nucleotide polymorphisms (SNPs) that have been found to be strongly associated with COPD were used as instrumental variables (IVs) in MR Analysis. The primary outcome of the study was BMD measurement at five specific anatomical sites, namely the whole body, femoral neck, lumbar spine, forearm, and heel. These BMD measurements were derived primarily from a genome-wide association study (GWAS) and summary statistics from the International Genetic Factors Consortium for Osteoporosis (GEFOS). The main analysis method was inverse variance weighting (IVW). Multiple sensitivity analyses were performed to assess the robustness and reliability of the current MR Results. Further confirmatory MR Analysis between COPD and OP was applied. In bibliometrics. Publications were extracted from the Web of Science core collection publications related to osteoporosis and sarcopenia published between January 2014 and October 2024; Bibliometrics and visualization were performed by Microsoft Office Excel, Citespace, and R (Bibliometrix).

Results: The MR Findings suggest that there is no causal relationship between COPD and BMD at five specific anatomical sites. The results of the primary IVW MR Analysis were generally supported by our sensitivity MR Analysis. We performed MR Analysis for the validation of COPD and OP (IVW OR: 1.019; 95%CI: 0.898-1.564; p = 0.768) also did not support a causal relationship between COPD and BMD. A total of 471 articles written by 1119 organizations from 42 countries/regions by 3331 authors and published in 238 journals were identified in the bibliometric analysis. China is the leading country in terms of the number of publications. China Medical University contributed the most publications. The International Journal of Chronic Obstructive Pulmonary Disease has the highest publication in this field.

Conclusions: In conclusion, This MR Study found no causal relationship between COPD and OP, suggesting that the observed associations may be due to common genetic effects or environmental confounders. The global research trends in this field in the past decade were summarized through bibliometric analysis, and care became the focus of future research on the relationship between copd and OP.