Prognostic biomarkers for lung adenocarcinoma based on Mendelian randomization analysis

A novel Mendelian randomisation framework unravels one gene expression component, correlated with proliferation and genome stability-related features, associated with telomere length in lung adenocarcinoma tumours, which provides insights into how telomere length influences the genetic basis of lung cancer aetiology.

A novel Mendelian randomisation framework unravels one gene expression component, correlated with proliferation and genome stability-related features, associated with telomere length in lung adenocarcinoma tumours, which provides insights into how telomere length influences the genetic basis of lung cancer aetiology.

Background Preeclampsia and eclampsia are severe pregnancy disorders marked by hypertension and potential organ damage. The etiological basis of preeclampsia and eclampsia is not fully understood. Previous studies have revealed a link between sleep abnormality and preeclampsia/eclampsia, but the causal relationship remains unclear. In this study, we explored the genetic links between sleep and preeclampsia/eclampsia using genome-wide association study (GWAS) summary data and Mendelian randomization (MR) analysis. Methods RNA sequence dataset GSE114691 was downloaded from the Gene Expression Omnibus database, comprising placental tissues from patients with preeclampsia and controls. Differential expression analysis was conducted with R (v4.2.3) and DESeq2 (v1.38.3). Gene set enrichment analysis (GSEA) was carried out using HTSanalyzeR2. GWAS summary data on preeclampsia/eclampsia and genetic markers for sleep abnormality were sourced from the FinnGen Consortium and IEU genetic databases. The Mendelian randomization analysis was conducted with TwoSampleMR (v0.6.2), and the inverse variance weighted (IVW) approach was employed as the principal method. Results GSEA analysis revealed that the orexin receptor pathway showed heightened expression in the preeclampsia group versus controls. The random-effects IVW results showed that sleeplessness/insomnia has a genetic causal relationship with preeclampsia (OR = 2.08, 95% CI: 1.07–4.06, p = 0.0318), while sleep duration has evidence of regulating eclampsia (OR = 0.09, 95% CI: 0.01–0.67, p = 0.0187). Conclusion This study provides significant evidence for a genetic causal association between sleep abnormalities and preeclampsia/eclampsia.

To investigate the genetic causality for the insomnia and common orthopedic diseases, such as rheumatoid arthritis (RA), ankylosing spondylitis (AS), osteoporosis (OP), and gout (GT). The genome-wide association study (GWAS) summary data on insomnia were obtained from a published study, while the GWAS summary data on RA, AS, OP, and GT were sourced from the FinnGen consortium. We utilized the TwoSampleMR package of the R software (version 4.1.2) to conduct a two-sample Mendelian randomization (MR) analysis. Our primary method of analysis was the random-effects inverse variance weighted (IVW) approach. Subsequently, we conducted a series of sensitivity analyses for the MR analysis. The MR analysis revealed a positive genetic causal relationship between insomnia and RA (P=0.016, odds ratio [OR] 95% confidence interval [CI]=1.112 [1.020-1.212]). However, no significant genetic causal relationship was observed between insomnia and AS (P=0.194, OR 95% CI=1.121 [0.944-1.331]), OP (P=0.788, OR 95% CI=1.016 [0.904-1.142]), and GT (P=0.757, OR 95% CI=1.018 [0.912-1.136]). The MR analysis did not exhibit heterogeneity, horizontal pleiotropy, outlier effects, or dependence on a single SNP, and demonstrated normal distribution, which guaranteed the robustness of the results. The results of this study suggest that insomnia may be a significant risk factor for RA, and controlling insomnia may represent a promising strategy for preventing RA. While insomnia was not observed to be associated with AS, OP, and GT at the genetic level, other levels of association cannot be excluded.

TOPBP1 interacting checkpoint and replication regulator (TICRR), a hub gene of the Cdk2-mediated initiation step of DNA replication, has been shown an essential role in tumorigenesis by accelerating the DNA replication of tumor cells. RT-qPCR was used to detect the mRNA expression of TICRR in LUAD tumors and adjacent normal tissues. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database of LUAD were acquired to analyze the critical role of TICRR expression in survival prognosis and clinicopathology characters in LUAD. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed using the R package. The correlation of TICRR expression with immune cellinfiltration, RNA epigenetic modification, DNA damage repair (DDR) pathway, and cell metabolism of LUAD was further explored to verify significant conclusions. TICRR was significantly upregulated in most cancer types, including LUAD, lung squamous cell carcinoma (LUSC), and others. Cox regression analysis indicated the overexpression of TICRR was associated with poor survival in several cancers. In LUAD, TICRR expression was positively correlated with tumor stage and was increased in smoking, male, and high tumor mutational burden (TMB) patients. Enrichment analysis revealed that TICRR could influence tumor proliferation and prognosis via activating pathways involving cell cycle, DNA repair, DNA replication, cysteine metabolism, oxidative phosphorylation, and ubiquitin-mediated proteolysis pathways. Interestingly, high TICRR expression correlated with DDR pathway signature (34 genes), 37 m6A/m5C regulated genes, and some metabolism-regulated genes. Silencing the TICRR gene affects cysteine metabolism and modifies cancer-related pathways, with decreased cell cycle and increased B/T cell receptor signaling. Our TICRR risk model accurately predicts LUAD patient prognosis, validated across GEO datasets, and is integrated with clinical characteristics via a nomogram, facilitating personalized treatment strategies and enhancing patient management. Taken together, TICRR has emerged as a promising prognostic biomarker in lung adenocarcinoma (LUAD), with implications in immune activation, cell cycle regulation, RNA modification, and tumor energy metabolism. These findings suggest that TICRR could serve as a viable therapeutic target and a reliable prognostic indicator for LUAD.

This study aimed to investigate the potential association between white blood cell counts and the risk of lung cancer, including its subtypes, through Mendelian randomization (MR) analysis. We conducted a two-sample MR analysis using genome-wide association study (GWAS) summary statistics for the both exposure traits (eosinophil count, neutrophil count, lymphocyte count, monocyte count, basophil count, and total white blood cell count) and outcome traits (lung cancer and its subtypes). The GWAS dataset for lung cancer included 29,266 cases (11273 lung adenocarcinoma (LUAD), 7426 lung squamous cell carcinoma (LSCC), 2664 small cell lung cancer (SCLC)) and 56,450 controls. In MR analysis, we employed methods such as Inverse variance weighted (IVW), weighted median, MR-Egger regression, MR pleiotropy residual sum and outlier. MR analysis revealed an elevated total white blood cell (WBC) count significantly increased the risk of LUAD (IVW: OR = 1.484, 95% CI = 1.219–1.749, p = 0.003). The results confirmed a causal relationship between monocyte count and LUAD (IVW: OR = 1.687, 95% CI:1.542–1.830, p < 0.001). An increased total WBC count was associated with a higher risk of LUAD. Additionally, analysis of WBC subtypes counts indicated that monocyte count plays an crucial role in the elevated risk of LUAD.

BackgroundCutaneous melanoma (CM) is strongly associated with ultraviolet (UV) radiation, which contributes to the transformation of melanocytes into melanoma by inducing specific DNA damage. Here, we investigated the causal relationship between CM and genes related to sun-damaged skin, exploring specific target genes through various bioinformatics analyses.MethodsThe Gene Expression Omnibus (GEO) database was used to obtain differential genes for CM and normal skin, and the Genome-Wide Association Studies (GWAS) analysis offered summary-level melanoma data for CM. Mendelian randomization (MR) analyses were used to examine the correlated linkage between CM and sun-exposed skin genes. The MR studies were conducted mainly using Inverse Variance Weighting (IVW), MR-Egger, Weighted Median, simple and weighted patterns to predict the correlation between sun-exposed skin and CM. Finally, the role of target genes in CM was revealed by pan-cancer analysis, expression and immune-infiltration evaluations, immuno-checking targeting analysis, immunotherapy response analysis, survival analysis, and protein-protein interactions (PPI) network and enrichment analyses.ResultUsing matrix data from the GSE15605, GSE46517, and GSE111452 datasets, bioinformatics analysis revealed 232 differentially expressed genes (DEGs) between CM and typical tissues. MR analysis indicated that only CTSS has a deleterious effect linking skin exposure to sunlight and CM. Analysis of CTSS expression in tumors and tissues, along with the construction of a prognostic model, revealed that CTSS expression was higher in both primary CM and metastatic CM compared to normal skin tissue. However, patients with higher CTSS expression had a higher prognosis. In addition, high CTSS expression was significantly and positively correlated with tumor mutation rate, tumor microenvironment, immune cell infiltration, immune checkpoints and immunotherapy efficacy.ConclusionUsing MR analysis, we found a positive causal relationship between the CTSS gene in sun-exposed skin and CM. Additionally, increased CTSS may provide a basis for biomarker prediction of CM prognosis, immune status and immunotherapy.

Ankylosing spondylitis (AS) is an immune-mediated chronic inflammatory disease that leads to bone hyperplasia and spinal ankylosis. Iron homeostasis plays a very important role in the inflammatory response and is closely related to the pathogenesis of AS. This study aimed to use large-scale genome-wide association study (GWAS) summary data to study the genetic causal relationship between AS and iron homeostasis using Mendelian randomization (MR). Genome-wide association study summary data of AS and iron homeostasis-related indicators were obtained from the FinnGen consortium and the DeCODE genetics database, respectively. We used four iron homeostasis-related indicators: ferritin, serum iron, total iron binding capacity (TIBC), and transferrin saturation (TSAT) for two-sample MR analyses to test for genetic causal association with AS using the "TwoSampleMR" package of the R software (version 4.1.2). The random-effects inverse variance weighted (IVW) method was the main analysis method used for MR. We examined the MR analysis results for heterogeneity, horizontal pleiotropy, and possible outliers. In addition, we confirmed the robustness of the MR analysis by testing whether the results were affected by a single SNP and whether they followed a normal distribution. The random-effects IVW results showed that ferritin [p = 0.225, OR 95% confidence interval (CI) = 0.836 (0.627-1.116)], serum iron [p = 0.714, OR 95% CI = 0.948 (0.714-1.260)], TIBC [p = 0.380, OR 95% CI = 0.917 (0.755-1.113)], and TSAT [p = 0.674, OR 95% CI = 0.942 (0.713-1.244)] have no genetic causal relationship with AS. We detected no heterogeneity，horizontal pleiotropy and possible outliers in our MR analysis (p > 0.05). In addition, our MR analysis results were not affected by a single SNP, and were normally distributed. Our study did not detect a genetic causal relationship between AS and iron homeostasis. Nonetheless, this does not rule out a relationship between the two at other mechanistic levels.

Although previous studies have shown that gut microbiota may be involved in the occurrence of deep venous thrombosis (DVT), the specific link between the two remains unclear. The present study aimed to explore this question from a genetic perspective. Genome-wide association study (GWAS) summary data of DVT were obtained from the UK Biobank (N = 9,059). GWAS summary data of the gut microbiota were obtained from the Flemish Gut Flora Project (N = 2,223) and two German cohorts (FoCus, N = 950; PopGen, N = 717). All the participants were of European ancestry. Linkage disequilibrium score (LDSC) regression has great potential for analyzing the heritability of disease or character traits. LDSC regression was used to analyze the genetic correlation between DVT and the gut microbiota based on the GWAS summary data obtained from previous studies. Mendelian randomization (MR) was used to analyze the genetic causal relationship between DVT and the gut microbiota. We used the random effects inverse variance weighted, MR Egger, weighted median, simple mode, and weighted mode to perform MR analysis. We performed a sensitivity analysis of the MR analysis results by examining heterogeneity and horizontal pleiotropy. Linkage disequilibrium score analysis showed that Streptococcaceae (correlation coefficient = -0.542, SE = 0.237, P = 0.022), Dialister (correlation coefficient = -0.623, SE = 0.316, P = 0.049), Streptococcus (correlation coefficient = -0.576, SE = 0.264, P = 0.029), and Lactobacillales (correlation coefficient = -0.484, SE = 0.237, P = 0.042) had suggestive genetic correlation with DVT. In addition, the MR analysis showed that Streptococcaceae had a positive genetic causal relationship with DVT (P = 0.027, OR = 1.005). There was no heterogeneity or horizontal pleiotropy in the MR analysis (P > 0.05). In this study, four gut microbes (Streptococcaceae, Dialister Streptococcus, Lactobacillales) had suggestive genetic correlations with DVT, and Streptococcaceae had a positive causal relationship with DVT. Our findings provide a new research direction for the further study of and prevention of DVT.

Genome-wide association studies (GWASs) have identified genetic susceptibility variants for both leukocyte telomere length (LTL) and lung cancer susceptibility. Our study aims to explore the shared genetic basis between these traits and investigate their impact on somatic environment of lung tumours. We performed genetic correlation, Mendelian randomisation (MR), and colocalisation analyses using the largest available GWASs summary statistics of LTL (N=464,716) and lung cancer (N=29,239 cases and 56,450 controls). Principal components analysis based on RNA-sequencing data was used to summarise gene expression profile in lung adenocarcinoma cases from TCGA (N=343). Although there was no genome-wide genetic correlation between LTL and lung cancer risk, longer LTL conferred an increased risk of lung cancer regardless of smoking status in the MR analyses, particularly for lung adenocarcinoma. Of the 144 LTL genetic instruments, 12 colocalised with lung adenocarcinoma risk and revealed novel susceptibility loci, including MPHOSPH6, PRPF6, and POLI. The polygenic risk score for LTL was associated with a specific gene expression profile (PC2) in lung adenocarcinoma tumours. The aspect of PC2 associated with longer LTL was also associated with being female, never smokers, and earlier tumour stages. PC2 was strongly associated with cell proliferation score and genomic features related to genome stability, including copy number changes and telomerase activity. This study identified an association between longer genetically predicted LTL and lung cancer and sheds light on the potential molecular mechanisms related to LTL in lung adenocarcinomas. Institut National du Cancer (GeniLuc2017-1-TABAC-03-CIRC-1-TABAC17-022), INTEGRAL/NIH (5U19CA203654-03), CRUK (C18281/A29019), and Agence Nationale pour la Recherche (ANR-10-INBS-09).

The aim was to study the genetic correlation and causal relationship between spondyloarthritis (SpA) and blood metabolites based on the large-scale genome-wide association study (GWAS) summary data. The GWAS summary data (3966 SpA and 448,298 control cases) of SpA were from the UK Biobank, and the GWAS summary data (486 blood metabolites) of human blood metabolites were from a published study. First, the genetic correlation between SpA and blood metabolites was analyzed by linkage disequilibrium score (LDSC) regression. Next, we used Mendelian randomization (MR) analysis to perform access causal relationship between SpA and blood metabolites. Random effects inverse variance weighted (IVW) was the main analysis method, and the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The MR analysis results were dominated by the random effects IVW. The Cochran’s Q statistic (MR-IVW) and Rucker’s Q statistic (MR Egger) were used to check heterogeneity. MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) were used to check horizontal pleiotropy. The MR-PRESSO was also used to check outliers. The “leave-one-out” analysis was used to assess whether the MR analysis results were affected by a single SNP and thus test the robustness of the MR results. Finally, we identified seven blood metabolites that are genetically related to SpA: X-10395 (correlation coefficient = −0.546, p = 0.025), pantothenate (correlation coefficient = −0.565, p = 0.038), caprylate (correlation coefficient = −0.333, p = 0.037), pelargonate (correlation coefficient = −0.339, p = 0.047), X-11317 (correlation coefficient = −0.350, p = 0.038), X-12510 (correlation coefficient = −0.399, p = 0.034), and X-13859 (Correlation coefficient = −0.458, p = 0.015). Among them, X-10395 had a positive genetic causal relationship with SpA (p = 0.014, OR = 1.011). The blood metabolites that have genetic correlation and causal relationship with SpA found in this study provide a new idea for the study of the pathogenesis of SpA and the determination of diagnostic indicators.

Background: The speckle-type POZ protein (SPOP) has emerged as an important regulator of protein degradation in various cancers. However, the precise role of SPOP in lung adenocarcinoma (LUAD) remains unclear, particularly in relation to its expression patterns, prognostic significance, and potential as a therapeutic target. This study aimed to investigate the expression, prognostic value, and biological functions of SPOP in LUAD, and to explore its potential as a biomarker for personalized treatment strategies.Methods: We performed a comprehensive analysis of SPOP expression using multiple public datasets, including TCGA, TCGA-GTEx, and GEO. Survival analyses were conducted through Cox regression and Kaplan-Meier methods to assess the prognostic significance of SPOP in LUAD. Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA) were employed to uncover biological pathways associated with SPOP expression. Immune microenvironment analysis and drug sensitivity data from the GDSC database were used to explore the potential role of SPOP in immune modulation and therapeutic response. The biological role of SPOP in LUAD was further explored through molecular docking analysis and experimental validation.Results: SPOP expression was significantly reduced in LUAD compared to normal tissues, with lower expression correlating with poor overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). Cox regression analysis confirmed that SPOP is an independent prognostic factor for LUAD. Functional analyses revealed that low SPOP expression was associated with disrupted immune regulation and altered metabolic pathways, potentially driving tumor progression. Immune profiling identified significant correlations between SPOP expression and immune cell recruitment, inflammatory signaling, and LUAD subtypes. Drug sensitivity analysis suggested that low SPOP expression is linked to increased sensitivity to zibotentan and 5-fluorouracil. Additionally, molecular docking analysis revealed key interaction sites between SPOP and NANOG, and SPOP knockdown in A549 and T24 cells resulted in downregulation of immune markers CD47 and CD155.Conclusion: SPOP is a reliable independent prognostic biomarker in LUAD, influencing tumor progression, immune microenvironment, and therapeutic response. Our findings support the potential of SPOP as a novel therapeutic target for personalized treatment strategies in LUAD.

A recent study has reported that anti-reflux surgery reduced the risk of lung cancer. However, the exact causal association between gastro-esophageal reflux disease (GORD) and lung cancer remains obscure. Therefore, we conducted a multivariable and network Mendelian randomization (MR) study to explore this potential association and mediation effect. Independent single nucleotide polymorphisms (SNPs) strongly associated with GORD were selected as instrumental variables (IVs) from the corresponding genome-wide association studies (GWAS). The summary statistics were obtained from the largest GORD GWAS meta-analysis of 367 441 (78 707 cases) European individuals, and the summary statistics of lung cancer and pathological subtypes came from International Lung Cancer Consortium (ILCCO) and FinnGen databases. Univariable and multivariable MR analyses were performed to investigate and verify the causal relationship between genetically predicted GORD and lung cancer. Network MR analysis was conducted to reveal the mediating role of GORD between smoking initiation and lung cancer. The univariable MR analysis demonstrated that GORD was associated with an increased risk of total lung cancer in both ILCCO [inverse variance weighted (IVW): odds ratio (OR) = 1.37, 95% confidence interval (CI) 1.16-1.62, P = 1.70E-04] and FinnGen database (IVW: OR = 1.25, 95% confidence interval CI 1.03-1.52, P = 2.27E-02). The consistent results were observed after adjusting the potential confounders [smoking traits, body mass index (BMI) and type 2 diabetes] in multivariable MR analyses. In subtype analyses, GORD was associated with lung adenocarcinoma (IVW: OR = 1.27, 95% CI 1.02-1.59, P = 3.48E-02) and lung squamous cell carcinomas (IVW: OR = 1.50, 95% CI 1.22-1.86, P = 1.52E-04). Moreover, GORD mediated 32.43% (95% CI 14.18-49.82%) and 25.00% (95% CI 3.13-50.00%) of the smoking initiation effects on lung cancer risk in the ILCCO and FinnGen databases, respectively. This study provides credible evidence that genetically predicted GORD was significantly associated with an increased risk of total lung cancer, lung adenocarcinoma and lung squamous cell carcinomas. Furthermore, our results suggest GORD is involved in the mechanism of smoking initiation-induced lung cancer.

Background:Genome-wide association studies (GWASs) have identified genetic susceptibility variants for both leukocyte telomere length (LTL) and lung cancer susceptibility. Our study aims to explore the shared genetic basis between these traits and investigate their impact on somatic environment of lung tumours.Methods:We performed genetic correlation, Mendelian randomisation (MR), and colocalisation analyses using the largest available GWASs summary statistics of LTL (N=464,716) and lung cancer (N=29,239 cases and 56,450 controls). Principal components analysis based on RNA-sequencing data was used to summarise gene expression profile in lung adenocarcinoma cases from TCGA (N=343).Results:Although there was no genome-wide genetic correlation between LTL and lung cancer risk, longer LTL conferred an increased risk of lung cancer regardless of smoking status in the MR analyses, particularly for lung adenocarcinoma. Of the 144 LTL genetic instruments, 12 colocalised with lung adenocarcinoma risk and revealed novel susceptibility loci, including MPHOSPH6, PRPF6, and POLI. The polygenic risk score for LTL was associated with a specific gene expression profile (PC2) in lung adenocarcinoma tumours. The aspect of PC2 associated with longer LTL was also associated with being female, never smokers, and earlier tumour stages. PC2 was strongly associated with cell proliferation score and genomic features related to genome stability, including copy number changes and telomerase activity.Conclusions:This study identified an association between longer genetically predicted LTL and lung cancer and sheds light on the potential molecular mechanisms related to LTL in lung adenocarcinomas.Funding:Institut National du Cancer (GeniLuc2017-1-TABAC-03-CIRC-1-TABAC17‐022), INTEGRAL/NIH (5U19CA203654-03), CRUK (C18281/A29019), and Agence Nationale pour la Recherche (ANR-10-INBS-09).

BackgroundWe aimed to evaluate the potential association between genetically predicted vanin-2 (VNN2) expression and lung adenocarcinoma (LUAD) risk, and to explore the immune cell subtype that may underlie this relationship.MethodsWe integrated whole-blood expression quantitative trait loci (eQTL) data from eQTLGen, plasma protein quantitative trait loci (pQTL) data from deCODE, and LUAD genome-wide association study (GWAS) data from European-ancestry cohorts, together with differential expression analysis using GEPIA2, to identify candidate genes for subsequent single-cell eQTL (sc-eQTL) Mendelian randomization (MR) analysis. For the sc-eQTL analysis, VNN2-associated eQTLs from 14 immune cell types profiled in the OneK1K single-cell eQTL resource were tested for associations with LUAD risk.ResultsBulk-level MR analysis showed that genetically predicted increases in VNN2 expression and protein levels were significantly associated with a reduced risk of LUAD (eQTL-MR: odds ratio (OR) = 0.964, 95% confidence interval (95% CI), 0.934–0.995; P = 0.024; pQTL-MR: OR = 0.946, 95% CI, 0.921–0.970; P = 2.87 × 10−5). Transcriptomic analyses confirmed significant downregulation of VNN2 in LUAD tumors compared with normal lung tissues. sc-eQTL MR identified the strongest association in resting natural killer (rNK) cells (OR = 0.896, 95% CI, 0.829–0.967; P = 0.005).ConclusionsMulti-omics and sc-eQTL MR analyses indicated that genetically predicted increases in VNN2 expression were associated with a reduced risk of LUAD, with the most pronounced effect observed in rNK cells. These findings suggest a potential cell type–specific role of VNN2 in LUAD susceptibility and warrant further studies to validate its biological relevance and clinical implications.