Genetic susceptibility to breast cancer increases the risk of neutropenia and agranulocytosis: insights from Mendelian randomization.

PURPOSE: The causal relationship between breast cancer and its estrogen receptor (ER) subtypes and neutropenia and agranulocytosis is unclear. METHODS: In two-sample Mendelian randomization (MR), we used inverse variance weighting (IVW), Bayesian weighted MR (BWMR), MR-Egger, weighted median, simple mode, and weighted mode methods to analyze causality for ER-positive breast cancer, ER-negative breast cancer, overall breast cancer, and drug-induced neutropenia and agranulocytosis. To validate the results, we performed the analysis again using GWAS data on neutropenia from different databases. In multivariable MR (MVMR), we assessed the independent effects of ER-positive and ER-negative breast cancer on causality. RESULTS: Two-sample MR analysis showed a causal relationship between ER-positive breast cancer (IVW odds ratio (OR) = 1.319, P = 7.580 × 10-10), ER-negative breast cancer (OR = 1.285, P = 1.263 × 10-4), overall breast cancer (OR = 1.418, P = 2.123 × 10-13), and drug-induced neutropenia and a causal relationship between ER-positive breast cancer (OR = 1.349, P = 1.402 × 10-7), ER-negative breast cancer (OR = 1.235, P = 7.615 × 10-3), overall breast cancer (OR = 1.429, P = 9.111 × 10-10), and neutropenia. Similarly, ER-positive breast cancer (OR = 1.213, P = 5.350 × 10-8), ER-negative breast cancer (OR = 1.179, P = 1.300 × 10-3), and overall breast cancer (OR = 1.275, P = 8.642 × 10-11) also had a causal relationship with agranulocytosis. MVMR analysis showed that ER-positive breast cancer remained causally associated with drug-induced neutropenia (OR = 1.233, P = 4.188 × 10-4), neutropenia (OR = 1.283, P = 6.363 × 10-4), and agranulocytosis (OR = 1.142, P = 4.549 × 10-3). Heterogeneity analysis and pleiotropy test showed that our results were reliable. CONCLUSION: Our study provides genetic evidence for a causal association between breast cancer and its estrogen receptor subtypes and neutropenia. In clinical practice, in addition to focusing on therapeutic factors, additional attention should be given to breast cancer patients to avoid severe neutropenia.

Association between tobacco smoke exposure and depression: the NHANES 2005-2018 and Mendelian randomization study.

OBJECTIVE: The relationship between tobacco smoke exposure (TSE) and depression is controversial. This study combined observational research and Mendelian randomization (MR) to explore the relationship of depression with both smoking status and cotinine levels. METHOD: We collected relevant data from the National Health and Nutrition Examination Survey (NHANES) database from 2005 to 2018, and used weighted multifactorial logistic regression modelling to assess the correlation between TSE and depression, and assessed the causal relationship of depression with both smoking status and cotinine levels by MR. RESULT: Current smokers had the highest risk of depression (OR 1.94; P < 0.01); there was a positive trend for correlation between daily smoking and depression (OR 1.66; P for trend < 0.01). Serum ketamine levels above 3.00 ng/ml had a higher risk of depression (OR 2.13; P < 0.001). MR results showed that current smoking (OR = 4.66; P < 0.001) and previous smoking (OR 2.09; P < 0.01) were risk factors for the onset of depression, and that there was no causal association between cotinine levels and depression. CONCLUSION: Smoking is significantly associated with depression and plays a potential causal role in the development of depression. Cotinine was significantly associated with depression, however MR results showed no causal relationship between cotinine and depression.

Causal relations between ischemic stroke and epilepsy: A bidirectional Mendelian randomization study.

Background: Although previous studies have reported a bidirectional relationship between ischemic stroke (IS) and epilepsy, the existence of a causal nexus and its directionality remains a topic of controversy. Methods: The single nucleotide polymorphisms (SNPs) associated with IS were extracted from the Genome-Wide Association Study (GWAS) database. Pooled genetic data encompassing all epilepsy cases, as well as generalized and focal epilepsy subtypes, were acquired from the International League Against Epilepsy's GWAS study. In this study, the primary analysis approach utilized the inverse variance weighting (IVW) method as the main analytical technique. To enhance the robustness of the findings against potential pleiotropy, additional sensitivity analyses were conducted. Results: In the forward analysis, the IVW method demonstrated that IS was associated with an increased risk of all epilepsy (odds ratio (OR) = 1.127, 95 % confidence interval (CI) = 1.038-1.224, P = 0.004) and generalized epilepsy (IVW: OR = 1.340, 95 % CI = 1.162-1.546, P = 5.70 × 10-5). There was no substantial causal relationship observed between IS and focal epilepsy (P > 0.05). Furthermore, generalized epilepsy, focal epilepsy, and all epilepsy did not show a causal relationship with IS. Conclusion: This Mendelian randomization (MR) analysis demonstrates that IS increases the risk of developing epilepsy, especially generalized epilepsy. Conversely, no clear causal association was found between epilepsy and the onset of stroke. Therefore, the possible mechanisms of the effect of epilepsy on the pathogenesis of IS still need to be further investigated.

Hearing loss is not associated with risk of Parkinson's disease: A Mendelian randomization study.

Purpose: A few observational studies have indicated that Parkinson's disease (PD) risk may be higher in those with hearing loss, but the two's causal relationship is yet unknown. Using Mendelian randomization (MR) methods, this study sought to explore the causal link between hearing loss and the risk of PD. Methods: We identified single nucleotide polymorphisms (SNPs) linked to hearing loss (P-value<5E-08) in a genome-wide association study (GWAS) included 323,978 people from the UK Biobank. The summary data for PD in the discovery group came from a GWAS meta-analysis of 33,647 cases and 449,056 healthy participants of European descent. Using summary data from the aforementioned GWAS of PD (N = 33,647) and hearing loss (N = 323,978), we carried out a two-sample MR study. As validation groups, two separate PD GWAS studies were used. Inverse variance weighting (IVW) was utilized in the principal MR analysis. For our findings to be reliable, further analyses were carried out with the Cochran's Q test, MR-Egger intercept, and leave-one-out analysis. In addition, we assessed the causal link between various forms of hearing loss and PD using the IVW approach. Results: Twenty-two SNPs with genome-wide significance linked to hearing loss were used as instrumental factors. In the discovery dataset, we failed to detect a causal relationship between hearing loss and PD (OR = 1.297; 95 % CI = 0.420-4.007; P-value = 0.651). The findings of other methods agreed with the IVW method. The results were robust under sensitivity analyses. Furthermore, the above findings were confirmed in two validation PD datasets. Additionally, no causal correlation was found between genetic prediction of four different types of hearing loss and PD (conductive hearing loss, IVW: OR = 1.058, 95%CI = 0.988-1.133, P-value = 0.108; sudden idiopathic hearing loss, IVW: OR = 0.936, 95%CI = 0.863-1.016, P-value = 0.113; mixed conductive and sensorineural hearing loss, IVW: OR = 0.963, 95%CI = 0.878-1.058, P-value = 0.436; sensorineural hearing loss, IVW: OR = 1.050, 95%CI = 0.948-1.161, P-value = 0.354). Conclusion: In those of European heritage, our investigation revealed no causal link between hearing loss and PD risk.

Integrated analysis of single-cell RNA-seq, bulk RNA-seq, Mendelian randomization, and eQTL reveals T cell-related nomogram model and subtype classification in rheumatoid arthritis.

Objective: Rheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy. Methods: scRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features. Results: By analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients. Conclusion: Our findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

Causal association between immune cells and lung cancer risk: a two-sample bidirectional Mendelian randomization analysis.

Background: Previous studies have highlighted the crucial role of immune cells in lung cancer development; however, the direct link between immunophenotypes and lung cancer remains underexplored. Methods: We applied two-sample Mendelian randomization (MR) analysis, using genetic variants as instruments to determine the causal influence of exposures on outcomes. This method, unlike traditional randomized controlled trials (RCTs), leverages genetic variants inherited randomly at conception, thus reducing confounding and preventing reverse causation. Our analysis involved three genome-wide association studies to assess the causal impact of 731 immune cell signatures on lung cancer using genetic instrumental variables (IVs). We initially used the standard inverse variance weighted (IVW) method and further validated our findings with three supplementary MR techniques (MR-Egger, weighted median, and MR-PRESSO) to ensure robustness. We also conducted MR-Egger intercept and Cochran's Q tests to assess heterogeneity and pleiotropy. Additionally, reverse MR analysis was performed to explore potential causality between lung cancer subtypes and identified immunophenotypes, using R software for all statistical calculations. Results: Our MR analysis identified 106 immune signatures significantly associated with lung cancer. Notably, we found five suggestive associations across all sensitivity tests (P<0.05): CD25 on IgD- CD24- cells in small cell lung carcinoma (ORIVW =0.885; 95% CI: 0.798-0.983; P IVW =0.022); CD27 on IgD+ CD24+ cells in lung squamous cell carcinoma (ORIVW =1.054; 95% CI: 1.010-1.100; P IVW =0.015); CCR2 on monocyte cells in lung squamous cell carcinoma (ORIVW =0.941; 95% CI: 0.898-0.987; P IVW =0.012); CD123 on CD62L+ plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) as well as on plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) in lung squamous cell carcinoma. Conclusion: This study establishes a significant genomic link between immune cells and lung cancer, providing a robust basis for future clinical research aimed at lung cancer management.

Impaired GK-GKRP interaction rather than direct GK activation worsens lipid profiles and contributes to long-term complications: a Mendelian randomization study.

BACKGROUND: Glucokinase (GK) plays a key role in glucose metabolism. In the liver, GK is regulated by GK regulatory protein (GKRP) with nuclear sequestration at low plasma glucose level. Some GK activators (GKAs) disrupt GK-GKRP interaction which increases hepatic cytoplasmic GK level. Excess hepatic GK activity may exceed the capacity of glycogen synthesis with excess triglyceride formation. It remains uncertain whether hypertriglyceridemia associated with some GKAs in previous clinical trials was due to direct GK activation or impaired GK-GKRP interaction. METHODS: Using publicly available genome-wide association study summary statistics, we selected independent genetic variants of GCKR and GCK associated with fasting plasma glucose (FPG) as instrumental variables, to mimic the effects of impaired GK-GKRP interaction and direct GK activation, respectively. We applied two-sample Mendelian Randomization (MR) framework to assess their causal associations with lipid-related traits, risks of metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular diseases. We verified these findings in one-sample MR analysis using individual-level statistics from the Hong Kong Diabetes Register (HKDR). RESULTS: Genetically-proxied impaired GK-GKRP interaction increased plasma triglycerides, low-density lipoprotein cholesterol and apolipoprotein B levels with increased odds ratio (OR) of 14.6 (95% CI 4.57-46.4) per 1 mmol/L lower FPG for MASLD and OR of 2.92 (95% CI 1.78-4.81) for coronary artery disease (CAD). Genetically-proxied GK activation was associated with decreased risk of CAD (OR 0.69, 95% CI 0.54-0.88) and not with dyslipidemia. One-sample MR validation in HKDR showed consistent results. CONCLUSIONS: Impaired GK-GKRP interaction, rather than direct GK activation, may worsen lipid profiles and increase risks of MASLD and CAD. Development of future GKAs should avoid interfering with GK-GKRP interaction.

Unraveling the association between gut microbiota and chemotherapy efficacy: a two-sample Mendelian randomization study.

Emerging evidence has underscored the complex link between gut microbiota and chemotherapy efficacy; however, establishing causality remains elusive due to confounding factors. This study, leveraging bidirectional two-sample Mendelian randomization (MR) analyses, explores the casual relationship between gut microbiota and chemotherapy efficacy. Utilizing genome-wide association study (GWAS) data from the MiBioGen consortium for gut microbiota and IEU Open GWAS for chemotherapy efficacy, we employed genetic variants as instrumental variables (IVs). The inverse variance weighted (IVW) method, weighted median estimator (WME), and MR-Egger regression method were applied, with sensitivity analyses ensuring robustness. Furthermore, we conducted reverse MR analyses between chemotherapy efficacy and identified significant gut microbial taxa. The results indicated that genus Butyricicoccus (OR = 3.7908, 95% CI: 1.4464-9.9350, P = 0.01), Dorea (OR = 3.3295, 95% CI: 1.2794-8.6643, P = 0.01), Hungatella (OR = 2.6284, 95% CI: 1.0548-6.5498, P = 0.04), and Turicibacter (OR = 2.5694, 95% CI: 1.0392-6.3526, P = 0.04) were positively associated with chemotherapy efficacy using the IVW method. Conversely, family Porphyromonadaceae (OR = 0.2283, 95% CI: 0.0699-0.7461, P = 0.01) and genus Eggerthella (OR = 0.4953, 95% CI: 0.2443-1.0043, P = 0.05) exhibited negative associations. WME demonstrated consistent results with IVW method only for genus Eggerthella (OR = 0.3343, 95% CI: 0.1298-0.8610, P = 0.02). No significant heterogeneity or horizontal pleiotropy was observed. Reverse MR analyses revealed no significant causal effect of chemotherapy on identified gut microbiota. This study sheds light on the intricate relationship between gut microbiota, with a particular emphasis on the genus Eggerthella, and chemotherapy efficacy, offering valuable insights for refining cancer treatment strategies.IMPORTANCEGlobal advancements in cancer treatment, particularly in chemotherapy, have notably decreased mortality rates in recent years. However, the correlation between gut microbiota and chemotherapy efficacy remains elusive. Our study, emphasizing the role of genus Eggerthella, represented a crucial advance in elucidating this intricate interplay. The identified associations offer potential therapeutic targets, contributing to global efforts for enhanced treatment precision and improved patient outcomes. Furthermore, our findings hold promise for personalized therapeutic interventions, shaping improved strategies in the ever-evolving landscape of cancer treatment.

Causal impact of statins on susceptibility to osteoarthritis: insights from a two-sample Mendelian randomization analysis.

BACKGROUND: Osteoarthritis is a widely prevalent cause of pain and disability among older adults. It is an incurable condition, and most treatments are aimed at alleviating symptoms. AIM: This study aimed to investigate the impact of statins on osteoarthritis by using a two-sample Mendelian randomization approach, using genetic variants associated with statin use as instrumental variables. METHOD: Information on single nucleotide polymorphisms associated with statin medication was obtained from the FinnGen study, and data on osteoarthritis were sourced from the UK Biobank. The inverse variance weighted method was used as the primary analytical approach for the Mendelian randomization analysis. Sensitivity analyses were conducted to evaluate horizontal pleiotropy and heterogeneity. To examine the genetic relationship between statins and osteoarthritis, linkage disequilibrium score regression-based estimates were used. RESULTS: Mendelian randomization analysis indicated a positive effect of statin use on the treatment of osteoarthritis (odds ratio 0.951, 95% confidence interval 0.914-0.99, p < 0.05). This conclusion was supported by various Mendelian randomization methods. Sensitivity analyses revealed no significant directional pleiotropy or influential single nucleotide polymorphisms that could compromise the overall causal inference. Linkage disequilibrium score regression-based estimates suggested a modest genetic correlation between statin use and osteoarthritis (Rg = 0.098, Se = 0.034, p < 0.05), thus reinforcing the robustness of the Mendelian randomization analysis. CONCLUSION: Statins reduce the risk of osteoarthritis, aligning with the results of observational studies. Further research is essential to validate these results and explore the underlying mechanisms in detail.

Identification of novel drug targets for multiple sclerosis by integrating plasma genetics and proteomes.

BACKGROUND: Genome-wide association studies (GWAS) have revealed numerous loci associated with multiple sclerosis (MS). However, the challenge lies in deciphering the mechanisms by which these loci influence the target traits. Here, we employed an integrative analytical pipeline to efficiently transform genetic associations to identify novel proteins for MS. METHODS: We systematically integrated MS GWAS data (N = 115,803) with human plasma proteome data (N = 7213) and conducted proteome-wide association studies (PWAS) to identify MS-associated pathogenic proteins. Following this, we employed Mendelian randomization and Bayesian colocalization analyses to verify the causal relationship between these significant plasma proteins and MS. Lastly, we utilized the Drug-Gene Interaction Database (DGIdb) to identify potential drug targets for MS. RESULTS: The PWAS identified 25 statistically significant cis-regulated plasma proteins associated with MS at a false discovery rate of P < 0.05. Further analysis revealed that the abundance of 7 of these proteins (PLEK, TNXB, CASP3, CD59, CR1, TAPBPL, ATXN3) was causally related to the incidence of MS. Our findings indicated that genetically predicted higher levels of TNXB and CD59 were associated with a lower risk of MS, whereas higher levels of PLEK, CASP3, CR1, TAPBPL, and ATXN3 were associated with an increased risk of MS. Three plasma proteins (PLEK, CR1, CD59) were validated by colocalization analysis. Among these, CR1 was prioritized as a target for Eculizumab due to its significant association with MS risk. Additionally, PLEK, CR1, and CD59 were identified as druggable target genes. CONCLUSIONS: Our proteomic analysis has identified PLEK, CR1, and CD59 as potential drug targets for MS treatment. Developing pharmacological inducers or inhibitors for these proteins could pave the way for new therapeutic approaches, potentially improving outcomes for MS patients.

Mendelian randomization analysis reveals higher whole body water mass may increase risk of bacterial infections.

BACKGROUND AND PURPOSE: The association of water loading with several infections remains unclear. Observational studies are hard to investigate definitively due to potential confounders. In this study, we employed Mendelian randomization (MR) analysis to assess the association between genetically predicted whole body water mass (BWM) and several infections. METHODS: BWM levels were predicted among 331,315 Europeans in UK Biobank using 418 SNPs associated with BWM. For outcomes, we used genome-wide association data from the UK Biobank and FinnGen consortium, including sepsis, pneumonia, intestinal infections, urinary tract infections (UTIs) and skin and soft tissue infections (SSTIs). Inverse-variance weighted MR analyses as well as a series of sensitivity analyses were conducted. RESULTS: Genetic prediction of BWM is associated with an increased risk of sepsis (OR 1.34; 95% CI 1.19 to 1.51; P = 1.57 × 10- 6), pneumonia (OR: 1.17; 95% CI 1.08 to 1.29; P = 3.53 × 10- 4), UTIs (OR: 1.26; 95% CI 1.16 to 1.37; P = 6.29 × 10- 8), and SSTIs (OR: 1.57; 95% CI 1.25 to 1.96; P = 7.35 × 10- 5). In the sepsis and pneumonia subgroup analyses, the relationship between BWM and infection was observed in bacterial but not in viral infections. Suggestive evidence suggests that BWM has an effect on viral intestinal infections (OR: 0.86; 95% CI 0.75 to 0.99; P = 0.03). There is limited evidence of an association between BWM levels and bacteria intestinal infections, and genitourinary tract infection (GUI) in pregnancy. In addition, MR analyses supported the risk of BWM for several edematous diseases. However, multivariable MR analysis shows that the associations of BWM with sepsis, pneumonia, UTIs and SSTIs remains unaffected when accounting for these traits. CONCLUSIONS: In this study, the causal relationship between BWM and infectious diseases was systematically investigated. Further prospective studies are necessary to validate these findings.

Causal association between major depressive disorder and venous thromboembolism: a bidirectional mendelian randomization study.

Purpose: Major depressive disorder (MDD) and venous thromboembolism (VTE) may be linked in observational studies. However, the causal association remains ambiguous. Therefore, this study investigates the causal associations between them. Methods: We performed a two-sample univariable and multivariable bidirectional Mendelian randomization (MR) analysis to evaluate the associations between MDD and VTE. The summary genetic associations of MDD statistics were obtained from the Psychiatric Genomics Consortium and UK Biobank. Information on VTE, deep vein thrombosis (DVT), and pulmonary embolism (PE) were obtained from the FinnGen Biobank. Inverse-variance weighting was used as the main analysis method. Other methods include weighted median, MR-Egger, Simple mode, and Weighted mode. Results: Univariable MR analysis revealed no significant associations between MDD and VTE risk (odds ratio (OR): 0.936, 95% confidence interval (CI): 0.736-1.190, p = 0.590); however, after adjusting the potential relevant polymorphisms of body mass index and education, the multivariable MR analysis showed suggestive evidence of association between them (OR: 1.163, 95% CI: 1.004-1.346, p = 0.044). Univariable MR analysis also revealed significant associations between MDD and PE risk (OR: 1.310, 95% CI: 1.073-1.598, p = 0.008), but the association between them was no longer significant in MVMR analysis (p = 0.072). We found no significant causal effects between MDD and DVT risk in univariable or multivariable MR analyses. There was also no clear evidence showing the causal effects between VTE, PE, or DVT and MDD risk. Conclusion: We provide suggestive genetic evidence to support the causal association between MDD and VTE risk. No causal associations were observed between VTE, PE, or DVT and MDD risk. Further validation of these associations and investigations of potential mechanisms are required.

Association between gut microbiota and hepatocellular carcinoma and biliary tract cancer: A mendelian randomization study.

BACKGROUND: An increasing number of studies have begun to discuss the relationship between gut microbiota and diseases, yet there is currently a lack of corresponding articles describing the association between gut microbiota and hepatocellular carcinoma (HCC) and biliary tract cancer (BTC). This study aims to explore the relationship between them using Mendelian randomization (MR) analysis method. AIM: To assess the relationship between gut microbiota and HCC and BTC. METHODS: We obtained Genome-wide association study (GWAS) data for the gut microbiome from the intestinal microbiota genomic library (MiBioGen, https://mibiogen.gcc.rug.nl/). Additionally, we accessed data pertaining to HCC and BTC from the IEU open GWAS platform (https://gwas.mrcieu.ac.uk/). Our analysis employed fundamental instrumental variable analysis methods, including inverse-variance weighted, MR and Egger. To ensure the dependability of the results, we subjected the results to tests for multiple biases and heterogeneity. RESULTS: During our investigation, we discovered 11 gut microbiota linked to an increased risk to BTC and HCC. The former included the genus Eubacterium hallii group (P = 0.017), Candidatus Soleaferrea (P = 0.034), Flavonifractor (P = 0.021), Lachnospiraceae FCS020 (P = 0.034), the order Victivallales (P = 0.018), and the class Lentisphaeria (P = 0.0.18). The latter included the genus Desulfovibrio (P = 0.042), Oscillibacter (P = 0.023), the family Coriobacteriaceae (P = 0.048), the order Coriobacteriales (P = 0.048), and the class Coriobacteriia (P = 0.048). Furthermore, in BTC, we observed 2 protective gut microbiota namely the genus Dorea (P = 0.041) and Lachnospiraceae ND3007 group (P = 0.045). All results showed no evidence of multiplicity or heterogeneity. CONCLUSION: This study explores a causal link between gut microbiota and HCC and BTC. These insights may enhance the mechanistic knowledge of microbiota-related HCC and BTC pathways, potentially informing therapeutic strategies.

Unraveling the biological link between diabetes mellitus and prostate cancer: Insights and implications.

This article is a comprehensive study based on research on the connection between diabetes mellitus (DM) and prostate cancer (PCa). It investigates the potential role of DM as an independent risk factor for PCa, delving into the biological links, including insulin resistance and hormonal changes. The paper critically analyzes previous studies that have shown varying results and introduces mendelian randomization as a method for establishing causality. It emphasizes the importance of early DM screening and lifestyle modifications in preventing PCa, and proposes future research directions for further under-standing the DM - PCa relationship.

The interplay between systemic inflammatory factors and endometriosis: A bidirectional mendelian randomization study.

OBJECTIVE: To utilize vast genetic data to reveal the interplay between 41 systemic inflammatory factors and endometriosis. DESIGN: Bidirectional Mendelian randomization study. MAINS OUTCOME MEASURES: This study obtained believable genetic instrumental variables for systemic inflammatory factors. The effect of systemic inflammatory factors on different endometriosis phenotypes, and the effect of endometriosis on the concentrations of systemic inflammatory factors were investigated. RESULTS: In this mendelian randomization study, we found 20 causal relationships involving 18 systemic inflammatory factors and it was shown that Monocyte chemotactic protein-1, Macrophage inflammatory protein-1a, Granulocyte colony-stimulating factor, Macrophage migration inhibitory factor, Interleukin-4, Interleukin-5, Interleukin-8, Interleukin-9, Interleukin-12p70, Interleukin-16, and Interleukin-17 may be the upstream causes of endometriosis (P<0.05). Additionally, if the definition of exposure in the mendelian randomization was endometriosis, it could suggestively cause an increase in Eotaxin, cutaneous T-cell attracting chemokine, and Interferon gamma-induced protein 10 levels, and a decrease in growth-regulated oncogene-alpha, Interleukin-2 receptor, alpha subunit, platelet-derived growth factor BB, and Interleukin-18 (P<0.05). Reverse causality was not observed between a single systemic inflammatory factor and endometriosis. CONCLUSIONS: Our findings indicate that several systemic inflammatory factors may act as the initiator at the onset of endometriosis. Additionally, several other inflammatory factors are far more probable to involved downstream during disease development.

Body shape from birth to adulthood is associated with skeletal development: A Mendelian randomization study.

BACKGROUND: Observational studies have shown that childhood obesity is associated with adult bone health but yield inconsistent results. We aimed to explore the potential causal association between body shape and skeletal development. METHODS: We used two-sample Mendelian randomization (MR) to estimate causal relationships between body shape from birth to adulthood and skeletal phenotypes, with exposures including placental weight, birth weight, childhood obesity, BMI, lean mass, fat mass, waist circumference, and hip circumference. Independent genetic instruments associated with the exposures at the genome-wide significance level (P < 5 × 10-8) were selected from corresponding large-scale genome-wide association studies. The inverse-variance weighted analysis was chosen as the primary method, and complementary MR analyses included the weighted median, MR-Egger, weighted mode, and simple mode. RESULTS: The MR analysis shows strong evidence that childhood (ß = -1.29 × 10-3, P = 8.61 × 10-5) and adulthood BMI (ß = -1.28 × 10-3, P = 1.45 × 10-10) were associated with humerus length. Tibiofemoral angle was negatively associated with childhood BMI (ß = -3.60 × 10-1, P = 3.00 × 10-5) and adolescent BMI (ß = -3.62 × 10-1, P = 2.68 × 10-3). In addition, genetically predicted levels of appendicular lean mass (ß = 1.16 × 10-3, P = 1.49 × 10-13), whole body fat mass (ß = 1.66 × 10-3, P = 1.35 × 10-9), waist circumference (ß = 1.72 × 10-3, P = 6.93 × 10-8) and hip circumference (ß =1.28 × 10-3, P = 4.34 × 10-6) were all associated with tibia length. However, we found no causal association between placental weight, birth weight and bone length/width. CONCLUSIONS: This large-scale MR analysis explores changes in growth patterns in the length/width of major bone sites, highlighting the important role of childhood body shape in bone development and providing insights into factors that may drive bone maturation.

Exploring potential causal links between air pollutants and congenital malformations: A two-sample Mendelian Randomization study.

Observational studies have suggested an association between air pollutants and congenital malformations; however, conclusions are inconsistent and the causal associations have not been elucidated. In this study, based on publicly available genetic data, a two-sample Mendelian randomization (MR) was applied to explore the associations between particulate matter 2.5 (PM2.5), NOX, NO2 levels and 11 congenital malformations. Inverse variance weighted (IVW), MR-Egger and weighted median were used as analytical methods, with IVW being the main method. A series of sensitivity analyses were used to verify the robustness of the results. For significant associations, multivariable MR (MVMR) was utilized to explore possible mediating effects. The IVW results showed that PM2.5 was associated with congenital malformations of digestive system (OR = 7.72, 95 %CI = 2.33-25.54, P = 8.11E-4) and multiple systems (OR = 8.63, 95 %CI = 1.02-73.43, P = 0.048) risks; NOX was associated with circulatory system (OR = 4.65, 95 %CI = 1.15-18.86, P = 0.031) and cardiac septal defects (OR = 14.09, 95 %CI = 1.62-122.59, P = 0.017) risks; NO2 was correlated with digestive system (OR = 27.12, 95 %CI = 1.81-407.07, P = 0.017) and cardiac septal defects (OR = 22.57, 95 %CI = 2.50-203.45, P = 0.005) risks. Further MVMR analyses suggest that there may be interactions in the effects of these air pollutants on congenital malformations. In conclusion, this study demonstrated a causal association between air pollution and congenital malformations from a genetic perspective.

B-cell hub genes play a cardiovascular pathogenic role of in childhood obesity and Kawasaki disease as revealed by transcriptomics-based analyses.

The study aims to explore the central genes that Kawasaki disease (KD) and Obesity (OB) may jointly contribute to coronary artery disease. Investigating single-cell datasets (GSE168732 and GSE163830) from a comprehensive gene expression database, we identified characteristic immune cell subpopulations in KD and OB. B cells emerged as the common immune cell characteristic subgroup in both conditions. Subsequently, we analyzed RNA sequencing datasets (GSE18606 and GSE87493) to identify genes associated with B-cell subpopulations in KD and OB. Lastly, a genome-wide association study and Mendelian randomization were conducted to substantiate the causal impact of these core genes on myocardial infarction. Quantitative real-time PCR (qRT-PCR) to validate the expression levels of hub genes in KD and OB. The overlapping characteristic genes of B cell clusters in both KD and OB yielded 70 shared characteristic genes. PPI analysis led to the discovery of eleven key genes that significantly contribute to the crosstalk. Employing receiver operating characteristic analysis, we evaluated the specificity and sensitivity of these core genes and scored them using Cytoscape software. The inverse variance weighting analysis suggested an association between TNFRSF17 and myocardial infarction risk, with an odds ratio of 0.9995 (95% CI = 0.9990-1.0000, p = 0.049). By employing a single-cell combined transcriptome data analysis, we successfully pinpointed central genes associated with both KD and OB. The implications of these findings extend to shedding light on the increased risk of coronary artery disease resulting from the co-occurrence of OB and KD.

Investigating the causal association between obesity and risk of hepatocellular carcinoma and underlying mechanisms.

Obesity is a global health concern and independent risk factor for cancers including hepatocellular carcinoma (HCC). However, evidence on the causal links between obesity and HCC is limited and inconclusive. This study aimed to investigate the causal relationship between obesity-related traits and HCC risk and explore underlying mechanisms using bioinformatics approaches. Two-sample Mendelian randomization analysis was conducted leveraging publicly available genome-wide association study summary data on obesity traits (body mass index, body fat percentage, waist circumference, waist-to-hip ratio, visceral adipose tissue volume) and HCC. Associations of obesity with primary mechanisms (insulin resistance, adipokines, inflammation) and their effects on HCC were examined. Differentially expressed genes in obesity and HCC were identified and functional enrichment analyses were performed. Correlations with tumor microenvironment (TME) and immunotherapy markers were analyzed. Genetically predicted higher body mass index and body fat percentage showed significant causal relationships with increased HCC risk. Overall obesity also demonstrated causal links with insulin resistance, circulating leptin levels, C-reactive protein levels and risk of severe insulin resistant type 2 diabetes. Four differentially expressed genes (ESR1, GCDH, FAHD2A, DCXR) were common in obesity and HCC. Enrichment analyses indicated their roles in processes like RNA capping, viral transcription, IL-17 signaling and endocrine resistance. They exhibited negative correlations with immune cell infiltration and immunotherapy markers in HCC. Overall obesity likely has a causal effect on HCC risk in Europeans, possibly via influencing primary mechanisms. The identified differentially expressed genes may be implicated in obesity-induced hepatocarcinogenesis through regulating cell cycle, inflammation and immune evasion. Further research on precise mechanisms is warranted.

Gut microbiome and major depressive disorder: insights from two-sample Mendelian randomization.

BACKGROUND: Existing evidence suggests that alterations in the gut microbiome are closely associated with major depressive disorder (MDD). We aimed to reveal the causal relationships between MDD and various microbial taxa in the gut. METHODS: We used the two-sample Mendelian randomization (TSMR) to explore the bidirectional causal effects between gut microbiota and MDD. The genome-wide association studies summary results of gut microbiota were obtained from two large consortia, the MibioGen consortium and the Dutch Microbiome Project, which we analyzed separately. RESULTS: Our TSMR analysis identified 10 gut bacterial taxa that were protective against MDD, including phylum Actinobacteria, order Clostridiales, and family Bifidobacteriaceae (OR: 0.96 ∼ 0.98). Ten taxa were associated with an increased risk of MDD, including phyla Firmicutes and Proteobacteria, class Actinobacteria, and genus Alistipes (OR: 1.01 ∼ 1.09). On the other hand, MDD may decrease the abundance of 12 taxa, including phyla Actinobacteria and Firmicutes, families Bifidobacteriaceae and Defluviitaleaceae (OR: 0.63 ∼ 0.88). MDD may increase the abundance of 8 taxa, including phylum Bacteroidetes, genera Parabacteroides, and Bacteroides (OR: 1.12 ∼ 1.43). CONCLUSIONS: Our study supports that there are mutual causal relationships between certain gut microbiota and the development of MDD suggesting that gut microbiota may be targeted in the treatment of MDD.