Genetically determined type 1 diabetes mellitus and risk of osteoporosis.

BACKGROUND: Observational evidence suggests that type 1 diabetes mellitus (T1DM) is associated with the risk of osteoporosis (OP). Nevertheless, it is not apparent whether these correlations indicate a causal relationship. To elucidate the causal relationship, a two-sample Mendelian randomization (MR) analysis was performed. METHODS: T1DM data was obtained from the large genome-wide association study (GWAS), in which 6683 cases and 12,173 controls from 12 European cohorts were involved. Bone mineral density (BMD) samples at four sites were extracted from the GEnetic Factors for OSteoporosis (GEFOS) consortium, including forearm (FA) (n = 8,143), femoral neck (FN) (n = 32,735), lumbar spine (LS) (n = 28,498), and heel (eBMD) (n = 426,824). The former three samples were from mixed populations and the last one was from European. Inverse variance weighting, MR-Egger, and weighted median tests were used to test the causal relationship between T1DM and OP. A series of sensitivity analyses were then conducted to verify the robustness of the results. RESULTS: Twenty-three independent SNPs were associated with FN-BMD and LS-BMD, twenty-seven were associated with FA-BMD, and thirty-one were associated with eBMD. Inverse variance-weighted estimates indicated a causal effect of T1DM on FN-BMD (odds ratio (OR) =1.033, 95 % confidence interval (CI): 1.012-1.054, p = 0.002) and LS-BMD (OR = 1.032, 95 % CI: 1.005-1.060, p = 0.022) on OP risk. Other MR methods, including weighted median and MR-Egger, calculated consistent trends. While no significant causation was found between T1DM and the other sites (FA-BMD: OR = 1.008, 95 % CI: 0.975-1.043, p = 0.632; eBMD: OR = 0.993, 95 % CI: 0.985-1.001, p = 0.106). No significant heterogeneity (except for eBMD) or horizontal pleiotropy was found for instrumental variables, suggesting these results were reliable and robust. CONCLUSIONS: This study shows a causal relationship between T1DM and the risk of some sites of OP (FN-BMD, LS-BMD), allowing for continued research to discover the clinical and experimental mechanisms of T1DM and OP. It also contributes to the recommendation if patients with T1DM need targeted care to promote bone health and timely prevention of osteoporosis.

Genetic evidence for causal effects of leukocyte counts on risk for rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by the accumulation of leukocytes and inflammatory mediators within the synovial tissue. Leukocyte counts are proposed to play a role in the pathogenesis of RA. However, the causality remains unclear. To investigate the causal relationship between various leukocytes and RA by implementing two-sample univariable Mendelian Randomization (MR) and multivariable MR. MR analysis was performed using respective genome-wide association study (GWAS) summary statistics for the exposure traits (eosinophil counts, neutrophil counts, lymphocyte counts, monocyte counts, basophil counts, and white blood cell counts) and outcome trait (RA). Summary statistics for leukocytes were extracted from the Blood Cell Consortium meta-analysis and INTERVAL studies. Public GWAS information for RA included 14,361 cases and 43,923 controls. Inverse variance weighted, weighted median, MR-Egger regression, MR pleiotropy residual sum and outlier, and multivariable MR analyses were performed in MR analysis. Univariable MR found elevated eosinophil counts (OR 1.580, 95% CI 1.389-2.681, p = 1.30 × 10-7) significantly increased the risk of RA. Multivariable MR further confirmed that eosinophil counts were a risk factor for RA. Increased eosinophils were associated with higher risk of RA. Further elucidations of the causality and mechanisms underlying are likely to identify feasible interventions to promote RA prevention.

Genetic Evidence Supporting a Causal Association Between mTOR-Dependent EIF-4E Circulating Protein Level and Osteoporosis.

INTRODUCTION: The mechanistic target of rapamycin (mTOR) regulates bone homeostasis, a crucial factor in osteoporosis (OP) development. However, most research is based on observational studies, and the causality remains uncertain. Therefore, we analyzed two samples of mendelian randomization (MR) to determine whether there is a causal relationship between mTOR-dependent circulating proteins and OP. METHODS: Mendelian weighting (weighted median [WM], inverse variance weighting [IVW], and MR-Egger regression) were applied to analyze the causality between bone phenotypes (bone mineral density [BMD] in forearm, femoral neck, lumbar spine, and heel) and mTOR-dependent circulating proteins (RP-S6K, 4EBP, EIF-4E, EIF-4A, and EIF-4G). Horizontal pleiotropy and heterogeneities were detected using Cochran's Q test, MR-Pleiotropy RE-Sidual Sum and Outlier (MR-PRESSO), and "leave-one-out" analysis. The proteomics-GWAS INTERVAL study was used to select the instrumental variables (IVs) for mTOR proteins. RESULTS: As phenotypes for OP, estimations of BMD were taken in four different sites: forearm (FA) (n = 8143), femoral neck (FN) (n = 32,735), lumbar spine (LS) (n = 28,498), and heel (eBMD) (n = 426,824). Based on IVW analysis, EIF4E is causally related to FA-BMD (OR = 0.938, 95% CI 0.887, 0.991, p = 0.024) but not to BMD elsewhere. CONCLUSION: MR analysis revealed a causal relationship between EIF-4E and FA-BMD, which may provide new insights into the underlying pathogenesis of OP and a new therapeutic target for OP.

Comprehensive analysis of the role of a four-gene signature based on EMT in the prognosis, immunity, and treatment of lung squamous cell carcinoma.

Epithelial-mesenchymal transition (EMT), a biological process through which epithelial cells transform into mesenchymal cells, contributes to tumor progression and metastasis. However, a comprehensive analysis of the role of EMT-related genes in Lung squamous cell carcinoma (LUSC) is still lacking. In this study, data were downloaded from available databases, including The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The association between differentially expressed EMT-related genes (EMT-RDGs) and LUSC prognosis, drug sensitivity, mutation, and immunity was analyzed using bioinformatics methods. In the results, Lasso and univariate Cox regression analyses identified four EMT-RDGs that were differentially expressed, and used to establish a prognostic model capable of distinguishing between high- and low-risk groups. Then, prognostic factors were identified by multivariate Cox regression analysis and used to construct a nomogram. The high-risk group had a significantly poorer prognosis than the low-risk group. The tumor immune environment was significantly different between the two groups, with the low-risk group exhibiting a better response to immunotherapy. In addition, the half-maximal inhibitory concentration prediction indicating that the constructed model could effectively predict sensitivity to chemotherapy. This study provides new reference for further exploration of new clinical therapeutic strategies for LUSC.

Genetically Determined Levels of mTOR-Dependent Circulating Proteins and Risk of Multiple Sclerosis.

BACKGROUND: Results from observational studies indicate an association between circulating levels of mammalian target of rapamycin (mTOR)-dependent circulating proteins and the risk of multiple sclerosis (MS). However, a causal association has not been fully elucidated. Mendelian randomization (MR) is used to overcome limitations inherent to observational studies, assess the causal association, and minimize bias due to confounding and reverse causation. METHODS: To explore the causal association between seven mTOR-dependent proteins (AKT, RP-S6K, eIF4E-BP, eIF4A, eIF4E, eIF4G, and PKC-α) and MS, we obtained summary statistics from the genome-wide association study (GWAS) meta-analysis of the International Multiple Sclerosis Genetics Consortium (47,429 patients and 68,374 controls) and the INTERVAL study (genetic associations with 2994 plasma proteins from 3301 healthy individuals). MR analyses were conducted using inverse variance weighted, weighted median estimator, and MR-Egger regression methods/models. Sensitivity analyses were performed to ensure the reliability of the findings. Single nucleotide polymorphisms (SNPs) that are independent (r2 < 0.01) and strongly associated to minerals (p < 1e-5) were selected as instrumental variables. RESULTS: The results of the MR analyses revealed that among the seven mTOR-dependent proteins selected for study, the circulating level of PKC-α (odds ratio [OR] 0.90, 95% confidence interval [CI] 0.82-0.98; P = 0.017) and RP-S6K (OR 1.12, 95% CI 1.00-1.25; P = 0.045) were associated with MS risk and that there was no sign of pleiotropy or heterogeneity. PKC-α was negatively related to MS, while RP-S6K was positively related to MS. No significant causation was found between the other proteins studied (AKT, eIF4E-BP, eIF4A, eIF4E, eIF4G) and MS. CONCLUSION: Molecules in the mTOR signaling pathway may bidirectionally regulate the occurrence and development of MS. PKC-α is a protective factor, while RP-S6K is a risk factor. Further explorations of pathways underlying the association between mTOR-dependent proteins and MS are required. PKC-α and RP-S6K might be used as future therapeutic targets for screening high-risk individuals and potentially improving opportunities for targeted prevention strategies.

Genetic Evidence Supporting Causal Roles of mTOR-Dependent Proteins in Rheumatic Fever: A Two-Sample Randomized Mendelian Study.

BACKGROUND: The expression of signaling molecules downstream of the mammalian target of rapamycin (mTOR) is dysregulated in patients with rheumatic fever (RF), but the causality of mTOR on RF remains unknown. This study aimed to investigate the causal effects of the mTOR-dependent proteins in RF. METHODS: The summary data for targets of the mTOR signaling were acquired from the publicly available INTERVAL study GWAS data. Data on RF have been obtained from the Integrated Epidemiology Unit GWAS database (38,209 cases and 156,711 healthy controls). A two-sample Mendelian randomization (MR) study was conducted to examine the association of RF risk and mTOR-dependent proteins (EIF4EBP2, EIF-4E, EIF-4G, EIF-4A, RP-S6K, and ATG7), including the inverse-variance weighted (IVW) method, MR-Egger, and weighted median, which was followed by sensitivity analyses. RESULTS: RP-S6K is associated with a lowered risk of RF with an odds ratio (OR) of 0.97, 95% confidence interval (95% CI) of 0.94-0.99 (p = 0.027). In contrast, ATG7 accounts for higher risk of RF with an OR of 1.05 (95% CI = 1.00-1.12, p = 0.047). No apparent heterogeneity and no horizontal pleiotropy were observed in the sensitivity analysis (p > 0.05). No statistical significance was identified for levels of EIF4A, EIF4G, EIF4E-BP2, and RP-S6K with RF risk (p > 0.05). CONCLUSION: MR found robust evidence of a causal association between RF and mTOR. RP-S6K and ATG7 may be targeted for intervention by repurposing existing therapeutics to reduce the risk of RF.