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Causal association between non-steroidal anti-inflammatory drugs use and the risk of benign prostatic hyperplasia: a univariable and multivariable Mendelian randomization study.

BACKGROUND: The results of earlier observational research on the relationships between the usage of non-steroidal anti-inflammatory medicines (NSAIDs) and the risk of benign prostatic hyperplasia (BPH) have been inconsistent. METHODS: To assess these associations, we performed both univariable and multivariable Mendelian randomization (MR) studies. Instrumental variables (IVs) associated with exposures at the significance level (p&#x2009;<&#x2009;5&#x2009;&#xd7;&#x2009;10-6) were selected from a comprehensive meta-analysis conducted by the United Kingdom Biobank (UKB). Summary data for BPH were obtained from the FinnGen consortium, which comprised 30,066 cases and 119,297 controls. Sensitivity analyses were performed to evaluate heterogeneity and pleiotropy. RESULTS: We found evidence by univariable MR (UVMR) that genetically predicted NSAIDs use increased the risk of BPH (odds ratio [OR] per unit increase in log odds NSAIDs use: 1.164, 95% confidence interval [CI]: 1.041-1.302, p&#x2009;=&#x2009;0.008). After controlling for inflammation in multivariable MR (MVMR), the link persisted (OR: 1.165, 95% CI: 1.049-1.293, p&#x2009;=&#x2009;0.004). There were no indications of potential heterogeneity and pleiotropy in UVMR and MVMR analyses. CONCLUSION: The results of the MR estimates suggest that genetically predicted NSAIDs use may elevate the risk of BPH. This outcome prompts the imperative for deeper exploration into potential underlying mechanisms.

Humans↗

Single-cell expression quantitative trait locus Mendelian randomization reveals immune cell-specific causal regulatory networks and actionable targets in polycystic ovary syndrome.

ObjectiveTo systematically investigate whether the pathogenesis of polycystic ovary syndrome (PCOS) is causally related to dysregulated gene expression in specific immune cell subsets, and to evaluate the potential of these causal genes as actionable drug targets.MethodsThis study employed a two-sample Mendelian randomization (MR) framework using publicly available genome-wide association study (GWAS) summary statistics. The participant data included 797 PCOS cases and 140,558 controls (no direct patient recruitment was involved). Instrumental variables were derived from high-resolution immune cell-specific single-cell expression quantitative trait locus (sc-eQTL) data (OneK1K project) across 14 immune cell types. Primary analyses utilized the inverse-variance weighted (IVW) method. Shared causal variants were validated using Bayesian colocalization. Phenome-wide association analysis (PheWAS), external transcriptomic dataset validation (GSE8157), and DrugBank database screening were conducted for pleiotropy assessment and drug repositioning.ResultsMR analysis revealed genome-wide significant causal associations for GLIPR1 in non-classical monocytes (Mono NC) and XBP1 in CD4+ effector memory T cells (CD4 ET) with PCOS risk. Higher GLIPR1 expression was associated with a decreased PCOS risk (OR = 0.669, P = 4.34&#xd7;10-6), whereas higher XBP1 expression was associated with an increased risk (OR = 1.406, P = 9.53&#xd7;10-8). Colocalization analysis confirmed that GLIPR1 shares a causal variant with PCOS (PP.H4 = 96.73%). PheWAS and external validation confirmed the safety profile and significant upregulation (P = 0.03) of GLIPR1. Drug repositioning identified SOT-107, a Phase III protein therapy drug, as a potential interacting agent for GLIPR1.ConclusionsThis sc-eQTL MR study reveals immune cell-specific causal regulatory networks in PCOS. GLIPR1 in non-classical monocytes represents a high-confidence protective target, while XBP1 provides suggestive evidence for immune-mediated pathogenesis. The candidate drug SOT-107 highlights theoretical repositioning opportunities, though rigorous preclinical validation remains required.

Female↗

Evidence supporting the role of hypertension in the onset of migraine.

BACKGROUND: The association between hypertension and migraine remains unclear. OBJECTIVE: The aim of this study employ multi-layered evidence chain that revealed the association between hypertension and migraine. METHODS: We first strictly included data from the NHANES 1999-2004 population and applied logistic regression, subgroup analysis and RCS to assess the correlation between hypertension, SBP, DBP and migraine. Meanwhile, LDSC and Mendelian randomization were conducted based on the GWAS to determine the causal relationship between hypertension and migraine. Inverse-variance weighted (IVW) was used as the primary method. Sensitivity analysis and Colocalization analysis were performed to confirm the robustness of the results. LDSC validated the genetic correlation between traits. Enrichment analysis revealed their underlying biological mechanisms. RESULTS: After strict inclusion in NHANES, 10,743 participants were included. The logistic regression showed a significant correlation between hypertension (OR&#x2009;=&#x2009;1.21 [95% CI, 1.08-1.36], FDR&#x2009;<&#x2009;0.001)&#x3001;DBP (OR&#x2009;=&#x2009;1.01 [95% CI, 1.01-1.02], FDR&#x2009;<&#x2009;0.001) and migraine. This association did not show significant group differences in subgroup. The MR results further supported the existence of a significant causal relationship between hypertension (OR&#x2009;=&#x2009;1.77 [95% CI, 1.43-2.30], FDR&#x2009;<&#x2009;0.001)&#x3001;DBP (OR&#x2009;=&#x2009;1.02 [95% CI, 1.01-1.03], FDR&#x2009;<&#x2009;0.001) and migraine onset. Additionally, the RCS analysis showed a linear relationship (P non-linear&#x2009;=&#x2009;0.897) between the two. The LDSC result showed a significant genetic correlation between the two (Rg&#x2009;=&#x2009;0.1092, SE&#x2009;=&#x2009;0.028, P&#x2009;<&#x2009;0.001). CONCLUSION: The development of migraine caused by hypertension is mainly realized through high DBP.

Humans↗

Causal relationship between albumin, total protein, and colorectal cancer risk: A 2-sample Mendelian randomization study.

Albumin (ALB) and total protein (TP) are vital constituents of the blood, and their levels and roles in the risk of colorectal cancer (CRC) are of significance. Previous observational studies have reported correlations among ALB, TP, and CRC. However, the existence of a causal relationship between ALB and CRC in European populations has not been adequately investigated and the causal link between TP and CRC remains unexplored. To address these gaps, we applied Mendelian randomization (MR) to investigate the potential causal relationship between ALB, TP, and CRC. Two-sample MR analysis was used to investigate whether there was a causal relationship between ALB, TP, and CRC. Our exposure data were extracted from genome-wide association study (GWAS) databases sourced from the UK Biobank, containing 315,268 and 314,921 Europeans participants for ALB and TP analyses, respectively. Single nucleotide polymorphisms that were significantly associated with ALB and TP were assessed using GWAS datasets. Our data were derived from the FinnGen Consortium CRC GWAS, which contained 6509 CRC cases and 28,7137 controls. Causal inference between ALB, TP, and CRC was performed using 3 MR methods: inverse variance weighting (IVW), MR-Egger, and weighted median. The IVW analysis showed no significant causal association between ALB and CRC (OR&#x2005;=&#x2005;1.04, 95% CI&#x2005;=&#x2005;0.89-1.21, P&#x2005;=&#x2005;.65). In contrast, the IVW analysis for TP and CRC showed a significant causal association (OR&#x2005;=&#x2005;0.78, 95% CI&#x2005;=&#x2005;0.66-0.92, P&#x2005;=&#x2005;.003), suggesting a reduced risk of CRC. Through a 2-sample MR study investigating the causal relationship between ALB, TP, and CRC in a European population, our findings revealed a significant causal relationship between TP and a reduced risk of CRC.

Humans↗

Investigation of Fatty Acid Metabolism-Associated Molecular CPOX and the Underlying Mechanism in Follicular Lymphoma.

Dysregulated lipid metabolism is a key driver of follicular lymphoma (FL). This study aimed to explore the lipid metabolism-related genes (LMRGs) and clarify the underlying roles and mechanisms in FL. Bioinformatics methods, including differential analysis, WGCNA, machine learning, and Mendelian randomization, were utilized to select the LMRGs in FL. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the function of the key LMRG. Receiver operator characteristic (ROC) was used to evaluate the diagnostic value of the key gene CPOX. A pan-cancer analysis investigated CPOX's expression level and immune correlations. In vitro experiments using FL cell lines (WSU-FSCCL, DOHH2) validated CPOX expression, and CPOX knockdown in DOHH2 cells was used to assess its impact on viability, migration, invasion, and fatty acid metabolism. CPOX was confirmed to be a risk factor, significantly overexpressed in FL, and exhibited effective diagnostic ability in FL (AUC&#x2009;=&#x2009;0.731). Functional analysis linked CPOX to mitochondrial function, oxidative phosphorylation, and heme metabolic process. Pan-cancer indicated the dysregulated CPOX across multiple cancers and closely correlation with immune characteristics. Experimentally, CPOX was higher in the more invasive DOHH2 cells; and CPOX knockdown suppressed FL progression and reduced lipid droplet formation, triglyceride, total cholesterol, and free fatty acid levels. In conclusion, this study fills the gap in understanding the significance of lipid metabolism-related molecules in FL, and innovatively proposes that CPOX is a risk factor for FL. Knockdown of CPOX inhibits the FL progression, which is regulated by fatty acid metabolism.

Lymphoma, Follicular↗

Assessing the causal effect of genetically predicted metabolites and metabolic pathways on vitiligo: Evidence from Mendelian randomization and animal experiments.

Vitiligo is a common chronic skin depigmentation disorder that seriously decreases the patients' overall quality of life. Human blood metabolites could contribute to unraveling the underlying biological mechanisms of vitiligo. We used GWAS summary statistics to assess the causal association between genetically predicted 1400 serum metabolites and vitiligo risk by Mendelian randomization (MR). Then, after constructing the mouse model of vitiligo, we did non-targeted metabolomics analysis on the mouse serum and validated MR's pathway enrichment results ulteriorly. In the initial phase, MR analysis revealed causative associations between 36 metabolites and vitiligo risk, including 8 metabolite ratios and 28 individual metabolites (19 known and 9 unknown metabolites). In the validation stage, 7 metabolites were successfully validated. Of the 28 individual metabolites, most are related to lipid metabolism. Genetically predicted higher 4-oxo-retinoic acid showed the strongest protective effect on vitiligo, while the most potent risk effect was the increase in quinate. The metabolites associated with vitiligo risk are mainly enriched in alpha-linolenic acid metabolism, linoleic acid metabolism, arginine biosynthesis and metabolism pathways, validated through the serum metabolomics of vitiligo mouse. By integrating genomics and metabolomics, this study provides new insights into the association between metabolites and vitiligo, highlighting the potential roles of specific metabolites in the pathogenesis of vitiligo. These metabolites associated with vitiligo could serve as new biomarkers, further research could help to reveal how these metabolites influence specific pathways in the development of vitiligo.

Animals↗

The causal relationship between steroid hormones and risk of stroke: evidence from a two-sample Mendelian randomization study.

It is unclear how steroid hormones contribute to stroke, and conducting randomized controlled trials to obtain related evidence is challenging. Therefore, Mendelian randomization (MR) technique was employed in this study to examine this association. Through genome-wide association meta-analysis, the genetic variants of steroid hormones, including testosterone/17&#x3b2;-estradiol (T/E2) ratio, aldosterone, androstenedione, progesterone, and hydroxyprogesterone, were acquired as instrumental variables. Analysis was done on the impact of these steroid hormones on the risk of stroke subtypes. The T/E2 ratio was associated to an elevated risk of small vessel stroke (SVS) according to the inverse variance weighted approach which was the main MR analytic technique (OR, 1.23, 95% CI: 1.05-1.44, p&#x2009;=&#x2009;0.009). These findings were solid since no heterogeneity nor horizontal pleiotropy were found. The causal association between T/E2 and SVS was also confirmed in the replication study (p&#x2009;=&#x2009;0.009). Nevertheless, there was no proof that other steroid hormones increased the risk of stroke. According to this study, T/E2 ratio and SVS are causally related. However, strong evidence for the impact of other steroid hormones on stroke subtypes is still lacking. These findings may be beneficial for developing stroke prevention strategies from steroid hormones levels.

Mendelian Randomization Analysis↗

New evidence for the protective effect of gut microbiota regulation of ferroptosis-related proteins against osteoporosis.

Osteoporosis (OP), characterized by bone degradation and increased fracture susceptibility, constitutes a significant global health burden. Recent findings implicate gut microbiota and ferroptosis in the regulation of bone metabolism; however, causal evidence for the gut microbiota's influence on OP specifically via ferroptosis regulation remains to be established. This study employed two-sample Mendelian randomization (MR) using genome-wide association study (GWAS) summary statistics to investigate these causal relationships and delineate mediating pathways.We assessed causal links between gut microbiota, ferroptosis-related proteins, and OP risk. Associations for gut microbiota abundance and ferroptosis-related proteins were derived from GWAS data and Icelandic blood-derived protein quantitative trait loci, respectively. Outcome data for OP were obtained from the FinnGen Release R12. The primary analysis utilized the inverse variance weighted (IVW)&#xa0;method, supplemented by sensitivity analyses to evaluate heterogeneity and horizontal pleiotropy. &#xa0;MR analysis identified 33 gut microbial taxa causally associated with OP risk: 13 protective and 20 detrimental. Similarly, 34 ferroptosis-related proteins were categorized as protective (18) or detrimental (16) for OP. Mediation analysis revealed that the protective effect of Terrisporobacter othiniensis on OP is partially mediated by the ferroptosis regulator MDM4 (indirect effect &#x3b2; = -0.020, 95% CI: -0.068 to 0.029), accounting for 6.8% of the total effect. Sensitivity analyses showed no significant evidence of heterogeneity or horizontal pleiotropy.&#xa0;This study provides the first genetically validated evidence supporting a causal relationship between specific gut microbiota, ferroptosis-associated proteins, and OP susceptibility. Specifically, Terrisporobacter othiniensis demonstrates a novel protective mechanism, modulating OP risk partly through the ferroptosis regulator MDM4. These findings broaden understanding of the "gut-bone axis" and highlight the gut microbiota-ferroptosis pathway, particularly the MDM4/p53 axis, as a promising target for novel OP prevention and therapeutic strategies.

Ferroptosis↗

Cell-type-specific genetic associations in Lewy body dementia identified using single-cell eQTL-based Mendelian randomization.

BACKGROUND: Lewy body dementia (LBD) is a complex neurodegenerative disorder marked by &#x3b1;-synuclein aggregation and dual impairment of cognitive and motor function.While genome-wide association studies have identified risk loci, the cellular mechanisms linking genetic variation to disease susceptibility remain largely unexplored. METHODS: We performed single-cell transcriptome-wide Mendelian randomization using brain cell-type-specific eQTLs across eight major cell types. Genetic associations were evaluated using inverse-variance weighted models, followed by Bayesian colocalization analysis. Replication was performed in independent stratified LBD cohorts based on APOE &#x3b5;4 carrier status. Phenome-wide association analysis was included as a supplementary, descriptive assessment of cross-trait associations. RESULTS: Expression of ANKRD65 in excitatory neurons was significantly associated with reduced LBD risk (odds ratio = 0.65, 95 % CI: 0.52-0.81, p = 0.00013). This association passed a false discovery rate of 0.1 and showed strong evidence of colocalization (posterior probability = 0.93). Effect direction was consistent across APOE &#x3b5;4+ and &#x3b5;4- LBD subgroups in independent cohorts. No genome-wide significant associations were observed with non-neurological traits in the phenome-wide analysis. CONCLUSIONS: Our findings identify a genetically supported, cell-type-resolved association between ANKRD65 expression in excitatory neurons and LBD risk. This study demonstrates the value of integrating cell-resolved transcriptomic regulation with genetic inference to pinpoint functionally relevant targets in neurodegenerative diseases.

Humans↗

Integrative analyses of mendelian randomization and bioinformatics reveal casual relationship and genetic links between COVID-19 and knee osteoarthritis.

BACKGROUND: Clinical and epidemiological analyses have found an association between coronavirus disease 2019 (COVID-19) and knee osteoarthritis (KOA). Infection with COVID-19 may increase the risk of developing KOA. OBJECTIVES: This study aimed to investigate the potential causal relationship between COVID-19 and KOA using Mendelian randomization (MR) and to explore the underlying mechanisms through a systematic bioinformatics approach. METHODS: Our investigation focused on exploring the potential causal relationship between COVID-19, acute upper respiratory tract infection (URTI) and KOA utilizing a bidirectional MR approach. Additionally, we conducted differential gene expression analysis using public datasets related to these three conditions. Subsequent analyses, including transcriptional regulation analysis, immune cell infiltration analysis, single-cell analysis, and druggability evaluation, were performed to explore potential mechanisms and prioritize therapeutic targets. RESULTS: The results indicate that COVID-19 has a one-way impact on KOA, while URTI does not play a causal role in this association. Ribosomal dysfunction may serve as an intermediate factor connecting COVID-19 with KOA. Specifically, COVID-19 has the potential to influence the metabolic processes of the extracellular matrix, potentially impacting the joint homeostasis. A specific group of genes (COL10A1, BGN, COL3A1, COMP, ACAN, THBS2, COL5A1, COL16A1, COL5A2) has been identified as a shared transcriptomic signature in response to KOA with COVID-19. Imatinib, Adiponectin, Myricetin, Tranexamic acid, and Chenodeoxycholic acid are potential drugs for the treatment of KOA patients with COVID-19. CONCLUSIONS: This study uniquely combines Mendelian randomization and bioinformatics tools to explore the possibility of a causal relationship and genetic association between COVID-19 and KOA. These findings are expected to provide novel perspectives on the underlying biological mechanisms that link COVID-19 and KOA.

Humans↗

Artificial Intelligence-Driven Multi-Omics Analysis Reveals Hydroxytyrosol Targeting of the TXNIP-NLRP3 Inflammasome Axis in Traumatic Brain Injury.

Traumatic brain injury (TBI) induces secondary neuroinflammation driven by oxidative stress, inflammasome activation, and immune remodeling, yet specific mechanism-guided pharmacological interventions remain limited. This study established an artificial intelligence (AI)-integrated network pharmacology and multi-omics framework to evaluate whether hydroxytyrosol (HT), an olive-derived natural polyphenol, may regulate TBI-related neuroinflammatory targets centered on the TXNIP/NLRP3 inflammasome axis. Starting from the SMILES structure of HT, potential targets were predicted using PharmMapper, SwissTargetPrediction, and the Similarity Ensemble Approach and were standardized to UniProt identifiers. TBI-associated genes were integrated from GeneCards, DisGeNET, OMIM, and the Therapeutic Target Database. The overlapping target set was analyzed using STRING-based protein-protein interaction (PPI) networks, MCODE, CytoHubba, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Public GEO transcriptomic datasets (GSE123831 and GSE104687) were used for cross-platform expression validation, differential expression analysis, and exploratory CIBERSORT-based immune infiltration estimation. Random forest (RF), multilayer perceptron (MLP), graph convolutional network (GCN), graph attention network (GAT), SHAP/LIME explainability analysis, LASSO inflammatory-risk scoring, and two-sample Mendelian randomization (MR) were further applied for target prioritization, immune phenotype mapping, and genetic association analysis. Seventy-three overlapping HT-TBI targets were identified. PPI and topology analyses prioritized TXNIP, NLRP3, CASP1, MAPK1, and TP53 as key hubs enriched in inflammasome activation, oxidative stress, apoptosis, and NOD-like receptor signaling. TXNIP, NLRP3, and CASP1 were consistently upregulated in both TBI transcriptomic datasets. LM22-based immune deconvolution suggested increased pro-inflammatory immune signatures and a positive TXNIP-M1 macrophage association (r&#x202f;=&#x202f;0.63, p < 0.001), which should be interpreted as a transcriptome-derived hypothesis rather than validated murine immune-cell proportions. AI-based models consistently ranked TXNIP/NLRP3 as high-contribution features under internal validation, and removal of these targets reduced model performance. A five-gene inflammatory score achieved an internally evaluated AUC of 0.87, while two-sample MR supported positive genetic associations involving TXNIP expression, TBI risk, NLRP3 and IL-1&#x3b2; expression. Collectively, these findings prioritize the TXNIP/NLRP3/CASP1 module as a computationally supported candidate mechanism through which HT may influence oxidative stress-inflammasome-immune coupling in TBI. This study provides an interpretable drug-target-pathway-phenotype framework and identifies TXNIP, NLRP3, and CASP1 as priority nodes for future experimental validation.

Artificial Intelligence↗

The causal relationship between multiple cardiovascular diseases and glioblastoma: A Mendelian randomization study.

Observational studies suggest an association between glioblastoma (GBM) and cardiovascular diseases (CVDs), but a causal relationship remains unestablished. This study aimed to investigate the causal link between multiple CVDs and GBM risk. The inverse variance weighted method indicated that all 18 CVDs had significant causal associations with GBM (P&#x2005;<&#x2005;.05). Genetically predicted CVDs were uniformly associated with a lower risk of GBM (odds ratio&#x2005;<&#x2005;1), identifying them as potential protective factors. Sensitivity analyses confirmed the absence of significant heterogeneity or horizontal pleiotropy, and the MR-Steiger test validated the correct causal direction. This Mendelian randomization (MR) study provides evidence that a range of CVDs are causally associated with a decreased risk of developing GBM. These findings suggest shared biological pathways and offer new insights for understanding GBM etiology. We conducted a 2-sample MR analysis using publicly available genome-wide association study data. GBM was the outcome, and 18 cardiovascular-related traits (including coronary artery disease, myocardial infarction, and venous thromboembolism) were exposures. Instrumental variables were single-nucleotide polymorphisms significantly associated with exposures (P&#x2005;<&#x2005;5&#x2005;&#xd7;&#x2005;10-8). The primary analysis used the inverse variance weighted method, supplemented with MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran Q test, MR-Egger intercept test, leave-one-out analysis, and MR-Steiger directionality test, were performed to ensure robustness.

Causality↗

Aerobic Fitness and Health-Related Phenotypes: A Two-Stage Phenome-Wide Mendelian Randomization Study.

PURPOSE: We investigated potentially causal associations between genetically predicted aerobic fitness and multiple health phenotypes using a two-stage phenome-wide Mendelian randomization (MR) study. METHODS: Genetically determined aerobic fitness, as operationalized by Cai et al., served as the exposure instrument. We screened 712 health-related phenotypes as outcomes using publicly available European-ancestry genome-wide association studies (GWAS) summary statistics from OpenGWAS (Discovery GWAS n > 5000), prioritizing non-UK Biobank/non-FinnGen datasets for Discovery when available and selecting an independent GWAS for validation. Associations were estimated using the MR-Robust Adjusted Profile Score method, controlled for multiple testing (5% false discovery rate) and unaffected by violations of MR assumptions (directional concordance between discovery and validation; no evidence of horizontal pleiotropy across inverse-variance weighted, MR-Egger, weighted-median, and weighted-mode methods; negative control analysis on hair color). RESULTS: We identified 108 discovery associations, of which 34 remained valid and statistically significant after validation. Higher genetically determined aerobic fitness was associated with lower lacunar stroke risk, lower arterial stiffness, higher heart rate variability, lower diastolic blood pressure, more favorable anthropometric measures, lower use of antidiabetic drugs, lower asthma risk, lower C-reactive protein, higher bone mineral density, favorable liver function biomarkers, favorable platelet-related traits, multiple blood count-derived hematological cell indices and counts, as well as higher years of schooling. Adverse associations were confined to atrial fibrillation, valvular heart disease, and systolic blood pressure. CONCLUSIONS: Genetically determined aerobic fitness is linked to a broad pattern of favorable cardiometabolic, inflammatory, musculoskeletal, respiratory, hepatic, and hematological phenotypes, alongside a narrow set of potential cardiovascular hazards.

Humans↗

Exploring the Relationship Between Serological Metabolites and Oral Cancer: A Mendelian Randomization Study.

BACKGROUND: Oral cancer is a prevalent malignant tumor, comprising &#x223c;5% to 6% of all tumors. The 5-year survival rate for this condition is &#x223c;50%. However, the early symptoms of oral cancer are often inconspicuous and easily overlooked, leading to frequent misdiagnosis or missed diagnosis. Although some previous studies have investigated the correlation between oral cancer and serum metabolites, the exact relationship remains unclear. Consequently, it is of utmost importance to develop effective early diagnosis methods and explore the pathogenesis of oral cancer to enhance patients' survival rates and quality of life. METHODS: This Mendelian randomization (MR) study utilized the Genome-Wide Association Study (GWAS) catalog to obtain instrumental variables (IVs) that link 486 serum metabolites with oral cancer. The study then conducted a causal analysis, using serological metabolites as exposure factors and oral cancer as the outcome. The samples used in the study were exclusively from the European population. The main method used for the univariate MR analysis was the inverse variance weighting method. After excluding confounding factors, MR analysis was performed again. Sensitivity analyses were subsequently conducted to enhance the robustness of the MR results. Furthermore, metabolic pathway analysis was carried out on serum metabolites associated with oral cancer, aiming to identify and explore potential metabolic pathways. RESULTS: After MR analysis, 8 serum metabolites were screened out that are highly correlated with the causal relationship with oral cancer, including androsterone sulfate (OR=2.11, 95% CI: 1.37-3.27, P =0.0007), X-12100--hydroxytryptophan (OR=0.12, 95% CI: 0.02-0.73, P =0.022), gamma-glutamylphenylalanine (OR=7.57, 95% CI: 1.17-48.85, P =0.033), 7-methylxanthine (OR=0.22, 95% CI: 0.05-0.90, P =0.035), urate (OR=12.03, 95% CI: 1.16-124.32, P =0.037), palmate (16:0) (OR=11.01, 95% CI: 1.11-109.13, P =0.040), creatinine (OR=0.03, 95% CI: 0.00-0.90, P =0.047), guanosine (OR=2.66, 95% CI: 1.00-7.04, P =0.049), and the absence of heterogeneity and horizontal pleiotropy in this study indicates that the MR results obtained are quite reliable. CONCLUSION: Androsterone sulfate, gamma-glutamylphenylalanine, urate, palmitate (16:0), creatinine, and guanosine have been identified as risk factors for oral cancer. In contrast, X-12100--hydroxytryptophan and 7-methylxanthine may have a protective effect against oral cancer. The findings of this study have significant implications for early oral cancer diagnosis and offer valuable insights into the disease's pathogenesis.

Mendelian Randomization Analysis↗

Cell type resolved MR based on brain single cell eQTLs corroborated by single cell RNA sequencing uncovers neuroimmune and vascular programs in intracerebral hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) lacks effective neuroprotective therapies. We integrated cell type&#x2013;resolved genetic inference with single-cell profiling to map putative causal programs and multicellular circuitry relevant to ICH. METHODS: Cis-eQTLs from eight human brain cell types were used as instruments for two-sample Mendelian randomization (MR), with an ICH meta-analysis from large biobanks and a stroke consortium as the outcome. Instruments were LD-pruned and restricted to strong variants (F&#x2009;>&#x2009;10). Inverse-variance weighting (IVW) was the primary estimator, supported by robustness methods, heterogeneity/pleiotropy diagnostics, and false discovery rate control. Experimental validation used mouse collagenase ICH single-cell RNA-seq at 24&#xa0;h (n&#x2009;=&#x2009;3 sham; n&#x2009;=&#x2009;3 ICH) with Seurat integration, composition testing, Slingshot pseudotime, and CellChat. An independent mouse cohort underwent qRT&#x2013;PCR for selected genes. RESULTS: The ICH meta-analysis showed acceptable genomic control, supporting downstream MR. We identified 524 nominal gene&#x2013;cell type associations, with a glia-weighted signal landscape. Enrichment implicated autophagy/mitophagy, antigen processing, cytoskeletal and vesicular trafficking, endothelial matrix&#x2013;adhesion programs, ferroptosis, and myelin stress pathways. In mouse scRNA-seq, disease-associated microglia expanded with reciprocal loss of homeostatic microglia and increased neutrophils and T cells. Prioritized genes showed directional concordance; qRT&#x2013;PCR confirmed ARPC3 and EIF2AK2 upregulation and TBCK and SPECC1 downregulation in ICH versus sham. Pseudotime supported a shift toward disease-associated microglial states, and CellChat indicated increased network interaction strength with microglia and endothelium as hubs. CONCLUSIONS: Cell type&#x2013;specific MR combined with single-cell validation highlights neuroimmune and neurovascular programs in ICH and links genetic signals to state transitions and inferred intercellular communication.

Animals↗

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4&#x202f;= 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4&#x202f;= 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗

Programmed cell death and risk of diabetic retinopathy: a Mendelian randomization study.

BACKGROUND: Programmed cell death (PCD) plays an important role in diabetic retinopathy (DR); however, the underlying genetic mechanisms remain unclear. We used Mendelian randomization (MR) to investigate the causal relationships between PCD-related genes and DR. This study aimed to investigate the effects of PCD on the risk of DR by conducting MR analysis. METHODS: Summary statistics from gene expression quantitative trait loci (eQTL) studies (31,684 Europeans) were analyzed. Genetic instrumental variables were selected using cis-eQTL single-nucleotide polymorphisms (SNPs; P&#x2009;<&#x2009;5&#x2009;&#xd7;&#x2009;10-&#x2009;8). Summary data-based MR (SMR) was employed to assess causal associations between PCD-related genes and DR, with three additional MR methods used for sensitivity testing. Bayesian colocalization was used to examine the shared regulatory mechanisms between PCD QTLs and DR risk loci. RESULTS: Sensitivity and colocalization analyses revealed six genes that affected DR: cathepsin H (CTSH), NAD(P)H: quinone oxidoreductase 1 (NQO1), tribbles pseudokinase 3 (TRIB3), and phosphoglycerate mutase 5 (PGAM5), which increased DR risk, and iron-responsive element binding protein 2 (IREB2) and tumor necrosis factor (TNF), which exhibited protective effects. Multivariate MR confirmed significant causal effects for CTSH, IREB2, and PGAM5 (p&#x2009;<&#x2009;0.050). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis (including 10 STRING-derived genes) revealed that 13 genes were enriched in necroptosis, apoptosis, mitophagy, and TNF signaling pathways in DR. CONCLUSIONS: This MR study supports the causal involvement of PCD in DR and identifies candidate genes (CTSH, IREB2, PGAM5, NQO1, TRIB3, and TNF) for therapeutic targeting or biomarker development in DR prevention or diagnosis.

Humans↗