Mitochondrial related genome-wide Mendelian randomization identifies putatively causal genes for multiple cancer types

New Insights on the Therapeutic Potential of Runt-Related Transcription Factor 2 for Osteoarthritis: Evidence from Mendelian Randomization

INTRODUCTION

Research has highlighted the role of runt-related transcription factor 2 (Runx2) in the development of osteoarthritis (OA); however, its causal association remains unclear. This study aimed to explore whether Runx2 expression is causally associated with OA and assess its therapeutic potential for OA.

METHODS

Genetic proxy instruments for Runx2 expression were obtained from gene expression quantitative trait locus (eQTLs) study of eQTLGen Consortium (n = 31,684). Aggregated genome-wide association study (GWAS) data for OA (including all OA [177,517 cases and 649,173 controls], knee OA (KOA) [62,497 cases and 333,557 controls], and hip OA (HOA) [36,445 cases and 316,943 controls]) were extracted from the Genetics of Osteoarthritis Consortium. We integrated eQTLs data with OA GWAS data to estimate their causal association and to estimate the potential of Runx2 as a drug target in the treatment of OA using summary data-based Mendelian randomization (SMR) analysis. Furthermore, different OA GWAS data (including all OA [77,052 cases and 378,169 controls], KOA [24,955 cases and 378,169 controls], and HOA [15,704 cases and 378,169 controls]) derived from the GWAS Catalog database were used for replication study.

RESULTS

SMR analysis showed that high expression levels of Runx2 were associated with an increased risk of all OA [odds ratio (OR) 1.044, 95% confidence interval (CI) 1.023-1.067; P = 5.03 × 10-5], KOA (OR 1.040, 95% CI 1.006-1.075; P = 0.021), and HOA (OR 1.067, 95% CI 1.022-1.113; P = 0.003). This suggests that Runx2 inhibitors may have promising potential for the treatment of OA. Notably, the causal effects of Runx2 with all OA (OR 1.053, 95% CI 1.027-1.079; P = 3.95 × 10-5) and KOA (OR 1.043, 95% CI 1.001-1.087; P = 0.045) were repeated in the replication study, but limited evidence supported the association of Runx2 expression levels with HOA (OR 1.045, 95% CI 0.993-1.101; P = 0.094).

CONCLUSIONS

Our analyses indicate a positive correlation between Runx2 expression and OA risk across all three phenotypes, suggesting the potential of Runx2 inhibitors in the treatment of OA and providing evidence from a genetic perspective.

Causal gene identification using mitochondria-associated genome-wide mendelian randomization in atrial fibrillation

Background: Mitochondrial dysfunction is one of the important patho-mechanisms in the development of atrial fibrillation (AF) with underidentified genetic pathophysiology. Methods: Summarized data of methylation, expression and protein abundance levels of mitochondria-related genes were obtained from corresponding studies, respectively. Genes related to mitochondria dysfunction in associations with AF were obtained from the UK Biobank (discovery), and the FinnGen study (replication). Summary-data-based Mendelian randomization analysis (SMR) was performed to assess potential causal relationships between mitochondria-related genes related to the molecular features of AF. Colocalization analysis was further conducted to assess whether the identified signal pairs shared causal genetic variants. Results: Five mitochondria-related genes were found to have causal effects with AF in the sensitivity and the colocalization analyses. Strong associations with increased risk of AF were identified with increased expression level of 4 mitochondria-related genes, including PCCB (OR 1.09, 95% CI 1.05-1.12; PPH4 = 0.95), COX18 (OR 1.83, 95% CI 1.29-2.60; PPH4 = 0.83), SLC25A15 (OR 1.34, 95% CI 1.14-1.58; PPH4 = 0.85), and STX17 (OR 1.16, 95% CI 1.08-1.24; PPH4 = 0.76). Conversely, genetically predicted higher levels expression of UQCC1 (OR 0.94, 95% CI 0.91-0.97) were associated with decreased risk of AF. After further tissue-specific validation, genetically predicted expression levels of PCCB (OR 1.12, 95%, CI 1.01-1.24, p = 0.025) and STX17 (OR 1.13, 95%, CI 1.04-1.23, p = 0.006) in atrial appendage were strongly associated with the increased risk of AF. Conclusion: Mitochondria-related genes are involved either positively (PCCB, COX18, SLC25A15 and STX17) or negatively (UQCCI) in the pathogenesis and the development of AF. These candidate genes may serve as targets for potential development of agents in the prevention and treatment of AF.

Construction and validation of prognostic signatures related to mitochondria and macrophage polarization in gastric cancer

Background

Increasing evidence reveals the involvement of mitochondria and macrophage polarisation in tumourigenesis and progression. This study aimed to establish mitochondria and macrophage polarisation-associated molecular signatures to predict prognosis in gastric cancer (GC) by single-cell and transcriptional data.

Methods

Initially, candidate genes associated with mitochondria and macrophage polarisation were identified by differential expression analysis and weighted gene co-expression network analysis. Subsequently, candidate genes were incorporated in univariateCox analysis and LASSO to acquire prognostic genes in GC, and risk model was created. Furthermore, independent prognostic indicators were screened by combining risk score with clinical characteristics, and a nomogram was created to forecast survival in GC patients. Further, in single-cell data analysis, cell clusters and cell subpopulations were yielded, followed by the completion of pseudo-time analysis. Furthermore, a more comprehensive immunological analysis was executed to uncover the relationship between GC and immunological characteristics. Ultimately, expression level of prognostic genes was validated through public datasets and qRT-PCR.

Results

A risk model including six prognostic genes (GPX3, GJA1, VCAN, RGS2, LOX, and CTHRC1) associated with mitochondria and macrophage polarisation was developed, which was efficient in forecasting the survival of GC patients. The GC patients were categorized into high-/low-risk subgroups in accordance with median risk score, with the high-risk subgroup having lower survival rates. Afterwards, a nomogram incorporating risk score and age was generated, and it had significant predictive value for predicting GC survival with higher predictive accuracy than risk model. Immunological analyses revealed showed higher levels of M2 macrophage infiltration in high-risk subgroup and the strongest positive correlation between risk score and M2 macrophages. Besides, further analyses demonstrated a better outcome for immunotherapy in low-risk patients. In single-cell and pseudo-time analyses, stromal cells were identified as key cells, and a relatively complete developmental trajectory existed for stromal C1 in three subclasses. Ultimately, expression analysis revealed that the expression trend of RGS2, GJA1, GPX3, and VCAN was consistent with the results of the TCGA-GC dataset.

Conclusion

Our findings demonstrated that a novel prognostic model constructed in accordance with six prognostic genes might facilitate the improvement of personalised prognosis and treatment of GC patients.

Unraveling the significance of AGPAT4 for the pathogenesis of endometriosis via a multi-omics approach

Endometriosis is characterized by the ectopic proliferation of endometrial cells, posing considerable diagnostic and therapeutic challenges. Our study investigates AGPAT4's involvement in endometriosis pathogenesis, aiming to unveil new therapeutic targets. Our investigation by analyzing eQTL data from GWAS for preliminary screening. Subsequently, within the GEO dataset, we utilized four machine learning algorithms to precisely identify risk-associated genes. Gene validity was confirmed through five Mendelian Randomization methods. AGPAT4 expression was measured by Single-Cell Analysis, ELISA and immunohistochemistry. We investigated AGPAT4's effect on endometrial stromal cells using RNA interference, assessing cell proliferation, invasion, and migration with CCK8, wound-healing, and transwell assays. Protein expression was analyzed by western blot, and AGPAT4 interactions were explored using AutoDock. Our investigation identified 11 genes associated with endometriosis risk, with AGPAT4 and COMT emerging as pivotal biomarkers through machine learning analysis. AGPAT4 exhibited significant upregulation in both ectopic tissues and serum samples from patients with endometriosis. Reduced expression of AGPAT4 was observed to detrimentally impact the proliferation, invasion, and migration capabilities of endometrial stromal cells, concomitant with diminished expression of key signaling molecules such as Wnt3a, β-Catenin, MMP-9, and SNAI2. Molecular docking analyses further underscored a substantive interaction between AGPAT4 and Wnt3a.Our study highlights AGPAT4's key role in endometriosis, influencing endometrial stromal cell behavior, and identifies AGPAT4 pathways as promising therapeutic targets for this condition.

Application of Graph Models to the Identification of Transcriptomic Oncometabolic Pathways in Human Hepatocellular Carcinoma

Whole-tissue transcriptomic analyses have been helpful to characterize molecular subtypes of hepatocellular carcinoma (HCC). Metabolic subtypes of human HCC have been defined, yet whether these different metabolic classes are clinically relevant or derive in actionable cancer vulnerabilities is still an unanswered question. Publicly available gene sets or gene signatures have been used to infer functional changes through gene set enrichment methods. However, metabolism-related gene signatures are poorly co-expressed when applied to a biological context. Here, we apply a simple method to infer highly consistent signatures using graph-based statistics. Using the Cancer Genome Atlas Liver Hepatocellular cohort (LIHC), we describe the main metabolic clusters and their relationship with commonly used molecular classes, and with the presence of TP53 or CTNNB1 driver mutations. We find similar results in our validation cohort, the LIRI-JP cohort. We describe how previously described metabolic subtypes could not have therapeutic relevance due to their overall downregulation when compared to non-tumoral liver, and identify N-glycan, mevalonate and sphingolipid biosynthetic pathways as the hallmark of the oncogenic shift of the use of acetyl-coenzyme A in HCC metabolism. Finally, using DepMap data, we demonstrate metabolic vulnerabilities in HCC cell lines.

Causal association of plasma circulating metabolites with nephritis: a Mendelian randomization study

Background

Nephritis is a pivotal catalyst in chronic kidney disease (CKD) progression. Although epidemiological studies have explored the impact of plasma circulating metabolites and drugs on nephritis, few have harnessed genetic methodologies to establish causal relationships.

Methods

Through Mendelian randomization (MR) in two substantial cohorts, spanning large sample sizes, we evaluated over 100 plasma circulating metabolites and 263 drugs to discern their causal effects on nephritis risk. The primary analytical tool was the inverse variance weighted (IVW) analysis. Our bioinformatic scrutiny of GSE115857 (IgA nephropathy, 86 samples) and GSE72326 (lupus nephritis, 238 samples) unveiled anomalies in lipid metabolism and immunological characteristics in nephritis. Thorough sensitivity analyses (MR-Egger, MR-PRESSO, leave-one-out analysis) were undertaken to verify the instrumental variables' (IVs) assumptions.

Results

Unique lipoprotein-related molecules established causal links with diverse nephritis subtypes. Notably, docosahexaenoic acid (DHA) emerged as a protective factor for acute tubulointerstitial nephritis (ATIN) (OR1 = 0.84, [95% CI 0.78-0.90], p1 = 0.013; OR2 = 0.89, [95% CI 0.82-0.97], p2 = 0.007). Conversely, multivitamin supplementation minus minerals notably increased the risk of ATIN (OR = 31.25, [95% CI 9.23-105.85], p = 0.004). Reduced α-linolenic acid (ALA) levels due to lipid-lowering drugs were linked to both ATIN (OR = 4.88, [95% CI 3.52-6.77], p < 0.001) and tubulointerstitial nephritis (TIN) (OR = 7.52, [95% CI 2.78-20.30], p = 0.042). While the non-renal drug indivina showed promise for TIN treatment, the use of digoxin, hydroxocobalamin, and liothyronine elevated the risk of chronic tubulointerstitial nephritis (CTIN). Transcriptome analysis affirmed that anomalous lipid metabolism and immune infiltration are characteristic of IgA nephropathy and lupus nephritis. The robustness of these causal links was reinforced by sensitivity analyses and leave-one-out tests, indicating no signs of pleiotropy.

Conclusion

Dyslipidemia significantly contributes to nephritis development. Strategies aimed at reducing plasma low-density lipoprotein levels or ALA supplementation may enhance the efficacy of existing lipid-lowering drug regimens for nephritis treatment. Renal functional status should also be judiciously considered with regard to the use of nonrenal medications.

Potential therapeutic targets for membranous nephropathy: proteome-wide Mendelian randomization and colocalization analysis

Background

The currently available medications for treating membranous nephropathy (MN) still have unsatisfactory efficacy in inhibiting disease recurrence, slowing down its progression, and even halting the development of end-stage renal disease. There is still a need to develop novel drugs targeting MN.

Methods

We utilized summary statistics of MN from the Kiryluk Lab and obtained plasma protein data from Zheng et al. We performed a Bidirectional Mendelian randomization analysis, HEIDI test, mediation analysis, Bayesian colocalization, phenotype scanning, drug bank analysis, and protein-protein interaction network.

Results

The Mendelian randomization analysis uncovered 8 distinct proteins associated with MN after multiple false discovery rate corrections. Proteins related to an increased risk of MN in plasma include ABO [(Histo-Blood Group Abo System Transferase) (WR OR = 1.12, 95%CI:1.05-1.19, FDR=0.09, PPH4 = 0.79)], VWF [(Von Willebrand Factor) (WR OR = 1.41, 95%CI:1.16-1.72, FDR=0.02, PPH4 = 0.81)] and CD209 [(Cd209 Antigen) (WR OR = 1.19, 95%CI:1.07-1.31, FDR=0.09, PPH4 = 0.78)], and proteins that have a protective effect on MN: HRG [(Histidine-Rich Glycoprotein) (WR OR = 0.84, 95%CI:0.76-0.93, FDR=0.02, PPH4 = 0.80)], CD27 [(Cd27 Antigen) (WR OR = 0.78, 95%CI:0.68-0.90, FDR=0.02, PPH4 = 0.80)], LRPPRC [(Leucine-Rich Ppr Motif-Containing Protein, Mitochondrial) (WR OR = 0.79, 95%CI:0.69-0.91, FDR=0.09, PPH4 = 0.80)], TIMP4 [(Metalloproteinase Inhibitor 4) (WR OR = 0.67, 95%CI:0.53-0.84, FDR=0.09, PPH4 = 0.79)] and MAP2K4 [(Dual Specificity Mitogen-Activated Protein Kinase Kinase 4) (WR OR = 0.82, 95%CI:0.72-0.92, FDR=0.09, PPH4 = 0.80)]. ABO, HRG, and TIMP4 successfully passed the HEIDI test. None of these proteins exhibited a reverse causal relationship. Bayesian colocalization analysis provided evidence that all of them share variants with MN. We identified type 1 diabetes, trunk fat, and asthma as having intermediate effects in these pathways.

Conclusions

Our comprehensive analysis indicates a causal effect of ABO, CD27, VWF, HRG, CD209, LRPPRC, MAP2K4, and TIMP4 at the genetically determined circulating levels on the risk of MN. These proteins can potentially be a promising therapeutic target for the treatment of MN.

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD.

Methods

Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases.

Results

A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1.

Conclusions

Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

Multi-omics Mendelian randomization integrating GWAS, eQTL, and mQTL data identified genes associated with breast cancer

Breast cancer (BC) remains a major disease posing a threat to women's health, but the underlying biological interpretation remains largely unknown. Here, we aimed to identify genes associated with breast cancer and analyze their pathophysiological mechanisms based on multi-omics Mendelian randomization (MR). Summary-data-based MR (SMR) was performed to estimate the causal effects of blood and breast mammary tissue expression quantitative trait loci (eQTLs) on BC. External validation analysis was used to validate the identified genes. Integration analyses BC GWAS summaries with eQTLs and DNA methylation QTLs (mQTLs) from the blood were conducted using SMR to prioritize putative blood genes and their regulatory elements associated with BC risk. Finally, two prior genes (ATG10 and RCCD1) from blood tissue reached significant levels in both BCAC (ATG10: ORBRCR = 0.91, PBRCR = 1.29 × 10-11; RCCD1: ORBRCR = 0.90, PBRCR = 3.72 × 10-15) and FinnGen cohorts (ATG10: ORFinnGen = 0.89, PFinnGen = 8.55 × 10-5; RCCD1: ORFinnGen = 0.89, PFinnGen = 2.38 × 10-8). Additionally, those two genes from breast tissues also replicated in both BCAC (ATG10: ORBRCR = 0.95, PBRCR = 1.02 × 10-9; RCCD1: ORBRCR = 0.87, PBRCR = 4.70 × 10-10) and FinnGen cohorts (ATG10: ORFinnGen = 0.93, PFinnGen = 2.38 × 10-4; RCCD1: ORFinnGen = 0.85, PFinnGen = 3.81 × 10-6). Sensitive analysis and external validation analysis validated those two identified genes. Multi-omics MR analysis showed that the SNP signals associated with ATG10 and RCCD1 were significant across the data from BC Genome-wide association study (GWAS), eQTL, and mQTL studies. In conclusion, we identified two priority genes that are potentially associated with BC. These findings improve our limited understanding of the mechanism of BC and shed light on the development of therapeutic agents for treating BC.

Elucidating the relationship between metabolites and breast cancer: A Mendelian randomization study

The evidence about the causal roles of metabolites in breast cancer is lacking. This study conducted a systematic evaluation of the potential causal relationship between 1091 human blood metabolites, 309 metabolite ratios, and the likelihood of developing breast cancer and its subtype by employing a two-sample bidirectional Mendelian randomization (MR) approach Four metabolites, including tryptophan betaine (Odds Ratio [OR] = 1.07, 95%CI = 1.04-1.10, Bonferroni-corrected P = 0.007), X-21312 (OR = 0.90, 95%CI = 0.86-0.94, Bonferroni-corrected P = 0.02), 3-bromo-5-chloro-2,6-dihydroxybenzoic acid (OR = 0.94, 95%CI = 0.91-0.96, Bonferroni-corrected P = 0.03) and X-18921 (OR = 0.96, 95%CI = 0.94-0.98, Bonferroni-corrected P = 0.04) were significantly associated with overall breast cancer using inverse-variance weighted (IVW) method. Tryptophan betaine was also significantly associated with estrogen receptor (ER)-positive breast cancer (OR = 1.08, 95%CI = 1.04-1.11, Bonferroni-corrected P = 0.03). X-23680 (OR = 1.10, 95%CI = 1.05-1.15, Bonferroni-corrected P = 0.04) and glycine to phosphate ratio (OR = 1.07, 95%CI = 1.04-1.10, Bonferroni-corrected P = 0.04) were associated with ER-negative breast cancer. Reverse MR analysis showed no significant associations between breast cancer and metabolites. This MR study indicated compelling evidence of a causal association between metabolites and the risk of breast cancer and its subtypes, underscoring the potential impact of metabolic interference on breast cancer risk and indicating the drug targets for breast cancer.

Assessing the causal relationship between 731 immunophenotypes and the risk of lung cancer: a bidirectional mendelian randomization study

BACKGROUND

Previous studies have observed a link between immunophenotypes and lung cancer, both of which are closely associated with genetic factors. However, the causal relationship between them remains unclear.

METHODS

Bidirectional Mendelian randomization (MR) was performed on publicly available genome-wide association study (GWAS) summary statistics to analyze the causal relationships between 731 immunophenotypes and lung cancer. Sensitivity analyses were conducted to verify the robustness, heterogeneity, and potential horizontal pleiotropy of our findings.

RESULTS

Following Bonferroni adjustment, CD14- CD16+ monocyte (OR = 0.930, 95%CI 0.900-0.960, P = 8.648 × 10- 6, PBonferroni = 0.006) and CD27 on CD24+ CD27+ B cells (OR = 1.036, 95%CI 1.020-1.053, P = 1.595 × 10 - 5, PBonferroni = 0.012) were identified as having a causal role in lung cancer via the inverse variance weighted (IVW) method. At a more relaxed threshold, CD27 on IgD+ CD24+ B cell (OR = 1.035, 95%CI 1.017-1.053, P = 8.666 × 10- 5, PBonferroni = 0.063) and CD27 on switched memory B cell (OR = 1.037, 95%CI 1.018-1.056, P = 1.154 × 10- 4, PBonferroni = 0.084) were further identified. No statistically significant effects of lung cancer on immunophenotypes were found.

CONCLUSIONS

The elevated level of CD14- CD16+ monocytes was a protective factor against lung cancer. Conversely, CD27 on CD24+ CD27+ B cell was a risk factor. CD27 on class-switched memory B cells and IgD+ CD24+ B cells were potential risk factors for lung cancer. This research enhanced our comprehension of the interplay between immune responses and lung cancer risk. Additionally, these findings offer valuable perspectives for the development of immunologically oriented therapeutic strategies.

The novel phosphatase NUDT5 is a critical regulator of triple-negative breast cancer growth

BACKGROUND

The most aggressive form of breast cancer is triple-negative breast cancer (TNBC), which lacks expression of the estrogen receptor (ER) and progesterone receptor (PR), and does not have overexpression of the human epidermal growth factor receptor 2 (HER2). Treatment options for women with TNBC tumors are limited, unlike those with ER-positive tumors that can be treated with hormone therapy, or those with HER2-positive tumors that can be treated with anti-HER2 therapy. Therefore, we have sought to identify novel targeted therapies for TNBC. In this study, we investigated the potential of a novel phosphatase, NUDT5, as a potential therapeutic target for TNBC.

METHODS

The mRNA expression levels of NUDT5 in breast cancers were investigated using TCGA and METABRIC (Curtis) datasets. NUDT5 ablation was achieved through siRNA targeting and NUDT5 inhibition with the small molecule inhibitor TH5427. Xenograft TNBC animal models were employed to assess the effect of NUDT5 inhibition on in vivo tumor growth. Proliferation, death, and DNA replication assays were conducted to investigate the cellular biological effects of NUDT5 loss or inhibition. The accumulation of 8-oxo-guanine (8-oxoG) and the induction of γH2AX after NUDT5 loss was determined by immunofluorescence staining. The impact of NUDT5 loss on replication fork was assessed by measuring DNA fiber length.

RESULTS

In this study, we demonstrated the significant role of an overexpressed phosphatase, NUDT5, in regulating oxidative DNA damage in TNBCs. Our findings indicate that loss of NUDT5 results in suppressed growth of TNBC both in vitro and in vivo. This growth inhibition is not attributed to cell death, but rather to the suppression of proliferation. The loss or inhibition of NUDT5 led to an increase in the oxidative DNA lesion 8-oxoG, and triggered the DNA damage response in the nucleus. The interference with DNA replication ultimately inhibited proliferation.

CONCLUSIONS

NUDT5 plays a crucial role in preventing oxidative DNA damage in TNBC cells. The loss or inhibition of NUDT5 significantly suppresses the growth of TNBCs. These biological and mechanistic studies provide the groundwork for future research and the potential development of NUDT5 inhibitors as a promising therapeutic approach for TNBC patients.

Exploring the association between inflammatory biomarkers and gastric cancer development: A two-sample mendelian randomization analysis

This study aimed to elucidate the potential causative links between inflammatory biomarkers and gastric cancer risk via a two-sample Mendelian randomization approach. Leveraging genome-wide association study (GWAS) data, we conducted a two-sample Mendelian randomization analysis. Instrumental variable selection for inflammatory markers - namely, tissue factor, monocyte chemotactic protein-1, E-selectin, interleukin 6 receptor, and fatty acid-binding protein 4 - was informed by SNP data from the IEU database. Strongly associated SNPs served as instrumental variables. We applied a suite of statistical methods, including Inverse Variance Weighted (IVW), Weighted Median Estimator (WME), MR-Egger, and mode-based estimates, to compute the odds ratios (ORs) that articulate the impact of these markers on gastric cancer susceptibility. The IVW method revealed that the interleukin 6 receptor was inversely correlated with gastric cancer progression (OR = 0.86, 95% CI = 0.74-0.99, P = .03), whereas fatty acid-binding protein 4 was found to elevate the risk (OR = 1.21, 95% CI = 1.05-1.39, P = .03). Instrumental variables comprised 5, 4, 7, 2, and 3 SNPs respectively. Convergent findings from WME, MR-Egger, and mode-based analyses corroborated these associations. Sensitivity checks, including heterogeneity, horizontal pleiotropy assessments, and leave-one-out diagnostics, affirmed the robustness and reliability of our instruments across diverse gastric malignancy tissues without substantial bias. Our research suggests that the interleukin 6 receptor potentially mitigates, while fatty acid-binding protein 4 may contribute to the pathogenesis of gastric cancer (GC). Unraveling the intricate biological interplay between inflammation and oncogenesis offers valuable insights for preemptive strategies and therapeutic interventions in gastric malignancy management.

A Comprehensive Prognostic Model for Colon Adenocarcinoma Depending on Nuclear-Mitochondrial-Related Genes

Background: Colon adenocarcinoma (COAD) has increasing incidence and is one of the most common malignant tumors. The mitochondria involved in cell energy metabolism, oxygen free radical generation, and cell apoptosis play important roles in tumorigenesis and progression. The relationship between mitochondrial genes and COAD remains largely unknown. Methods: COAD data including 512 samples were set out from the UCSC Xena database. The nuclear mitochondrial-related genes (NMRGs)-related risk prognostic model and prognostic nomogram were constructed, and NMRGs-related gene mutation and the immune environment were analyzed using bioinformatics methods. Then, a liver metastasis model of colorectal cancer was constructed and protein expression was detected using Western blot assay. Results: A prognostic model for COAD was constructed. Comparing the prognostic model dataset and the validation dataset showed considerable correlation in both risk grouping and prognosis. Based on the risk score (RS) model, the samples of the prognostic dataset were divided into high risk group and low risk group. Moreover, pathologic N and T stage and tumor recurrence in the two risk groups were significantly different. The four prognostic factors, including age and pathologic T stage in the nomogram survival model also showed excellent predictive performance. An optimal combination of nine differentially expressed NMRGs was finally obtained, including LARS2, PARS2, ETHE1, LRPPRC, TMEM70, AARS2, ACAD9, VARS2, and ATP8A2. The high-RS group had more inflamed immune features, including T and CD4+ memory cell activation. Besides, mitochondria-associated LRPPRC and LARS2 expression levels were increased in vivo xenograft construction and liver metastases assays. Conclusion: This study established a comprehensive prognostic model for COAD, incorporating nine genes associated with nuclear-mitochondrial functions. This model demonstrates superior predictive performance across four prognostic factors: age, pathological T stage, tumor recurrence, and overall prognosis. It is anticipated to be an effective model for enhancing the prognosis and treatment of COAD.

Deciphering the vital roles and mechanism of m5C modification on RNA in cancers

5-methylcytosine (m5C modification) plays an essential role in tumors, which affects different types of RNA, the expression of downstream target genes, and downstream pathways, thus participating in the tumor process. However, the effect of m5C modification on RNA in tumors and the exact mechanism have not been systematically reviewed. Therefore, we reviewed the status and sites of m5C modification, as well as the expression pattern and biological functions of m5C regulators in tumors, and further summarized the effects and regulation mechanism of m5C modification on messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), long non-coding RNA (lncRNA) and other RNA in tumors. Finally, we summed up the interaction network, potential application, and value in clinical diagnosis and treatment of tumors. Taken together, this review benefits revealing the mechanism of m5C modification in tumor progression and provides new strategies for tumor diagnosis and treatment.

Endoplasmic reticulum stress related genome-wide Mendelian randomization identifies therapeutic genes for ulcerative colitis and Crohn's disease

Background: Endoplasmic reticulum stress (ERS) is an important pathophysiological mechanism in ulcerative colitis (UC) and Crohn's disease (CD). ERS-related genes may be influenced by genetic factors and intestinal inflammation. However, the role of ERS as a trigger or potential etiological factor for UC and CD is unclear, as the expression of ERS-related genes in UC and CD may be the cause or subsequent changes in intestinal inflammation. Here, we used a three-step summary data-based Mendelian randomization (SMR) approach integrating multi-omics data to identify putative causal effects of ERS-related genes in UC and CD. Methods: Genome-wide association study (GWAS) summary data for UC (6,968 cases and 20,464 controls) and CD (5,956 cases and 14,927 controls) were extracted as outcome, and DNA methylation quantitative trait loci (mQTL, 1,980 participants) data and expression QTL data (eQTL, 31,684 participants) from the blood were obtained as exposure. The ERS-related genes were extracted from the GeneCards database, and then the GWAS summary data were integrated with the mQTL and eQTL data associated with ERS genes by SMR. Sensitivity analysis included two-sample MR analysis, power calculations, Bayesian co-localization analysis, and phenotype scanning were performed to evaluate the robustness of the results. Results: A total of 1,193 ERS-related genes were obtained. The three-step SMR analysis showed that cg24011261 CpG site regulating GPX1 expression was associated with a low risk of UC, whereas GPX1 expression regulated by a combination of cg05055782, cg24011261, and cg05551922 CpG sites was associated with a low risk of CD. Sensitivity analysis further supports these findings. Conclusion: This multi-omics integration study identifies a causal relationship between the role of ERS in UC and CD and suggests potential new therapeutic targets for clinical practice.