Repurposing antidiabetic drugs for rheumatoid arthritis: results from a two-sample Mendelian randomization study

Phillyrin for sepsis-related acute lung injury: A potential strategy suppressing GSK-3β

The efficacy of clinical drugs for acute lung injury/acute respiratory distress syndrome (ALI/ARDS) remains suboptimal. Phillyrin (PHN), a compound derived from Forsythia, is believed to alleviate sepsis-related ALI/ARDS; however, its mechanisms are not fully elucidated. In this study, we screened 8331 target genes associated with ALI/ARDS from public databases and identified six hub genes relevant to PHN treatment: AKT1, GSK-3β, PPP2CA, PPP2CB, PPP2R1A, and AR. Receiver operating characteristic analysis and single-cell sequencing analysis revealed the expression of AKT1, GSK-3β, PPP2CA, PPP2CB, and PPP2R1A were markedly elevated. Molecular docking and dynamics simulations indicated that PHN forms a structurally stable complex with glycogen synthase kinase-3β (GSK-3β). Mendelian randomization analyses suggested that PHN, as a potent GSK-3β inhibitor, may promote M2 macrophage polarization and reduce neutrophil recruitment. We validated these findings through in vivo and in vitro experiments, demonstrating that PHN lowers iNOS levels and raises MMR levels by downregulating GSK-3β mRNA expression and protein activity during lipopolysaccharide (LPS)-induced macrophage inflammation. Additionally, PHN inhibited GSK-3β mRNA expression and protein activity, reducing NF-κB-p65 nuclear translocation in LPS-induced zebrafish inflammation and mice ALI. This inhibition decreased levels of TNF-α and IL-6, increased IL-10 levels, promoted M2 macrophage polarization, suppressed neutrophil recruitment, and ultimately ameliorated ALI/ARDS. In conclusion, our results indicate that PHN effectively alleviates LPS-induced ALI/ARDS by suppressing GSK-3β signaling.

Computational and Experimental Investigation of Antidiabetic Drugs on Tofacitinib Metabolism: Molecular Docking, in vitro, and in vivo Studies

Background

Tofacitinib is an orally administered Janus kinase (JAK) inhibitor that has demonstrated significant efficacy in the treatment of rheumatoid arthritis. This study aimed to investigate the effects of gliquidone and linagliptin, two hypoglycemic agents on the pharmacokinetics of tofacitinib in vitro and in vivo.

Methods

The mechanism of drug-drug interaction was studied in vitro using a murine liver microsome incubation system and in vivo by administering gliquidone and linagliptin orally to rats pretreated with various concentrations of tofacitinib. This study used waters ACQUITY UPLC I-Class/Xevo TQD ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometer. Furthermore, molecular docking was performed to simulate the interaction using computer simulations.

Results

Gliquidone and linagliptin inhibited the metabolism of tofacitinib by heparanase in vitro with IC50 values of 1.140 μM and 4.064 μM, respectively. Co-administration of gliquidone significantly increased the AUC(0-t) of tofacitinib by approximately 43.3%, accompanied by a 45.1% increase in Cmax and a 27.5% reduction in clearance (CLz/F). In contrast, linagliptin exhibited a more potent inhibitory effect, raising the AUC(0-t) approximately 4.4-fold, enhancing the Cmax by 2.86-fold, and decreasing clearance to 25.8% of the control level. These findings suggest that while both gliquidone and linagliptin significantly enhance the systemic exposure of tofacitinib, linagliptin demonstrates a markedly more significant inhibitory effect on tofacitinib's metabolism and elimination.

Conclusion

Gliquidone and linagliptin significantly altered the pharmacokinetics of tofacitinib in vitro and in vivo. This study demonstrated the drug-drug interactions between linagliptin, gliquidone, and tofacitinib, highlighting the need for clinical attention to this possibility.

Protective effect of antidiabetic drugs against male infertility: evidence from Mendelian randomization

BACKGROUND

The global prevalence of diabetes has been steadily increasing, with a growing number of younger individuals being affected. Over recent decades, various antidiabetic drugs have been repurposed for treating conditions beyond diabetes. However, the effects of antidiabetic drugs on male infertility (MIF) remain inadequately elucidated. This Mendelian randomization (MR) study aims to clarify the potential impact of antidiabetic drugs on the risk of MIF.

METHOD

We designed a comprehensive analytical workflow involving two-sample MR and summary-based MR (SMR) to assess the causal relationship between antidiabetic drug targets and MIF. First, instrumental variables were obtained based on HbA1c levels and gene expression levels. Then, MR analysis was performed after selecting positive target genes from four blood glucose level and type 2 diabetes (T2DM) datasets. Finally, we applied SMR analysis to validate and expand upon the previous conclusions. Additionally, sensitivity analyses were conducted to evaluate the robustness of the results.

RESULTS

Seven drug targets associated with five antidiabetic drugs were identified as significantly related to MIF. In the two-sample MR, the following drugs were found to reduce MIF risk through their respective significant targets: metformin (GPD1: IVW OR 0.007, 95% CI 0.000-0.204, P = 0.004), SGLT2 inhibitors (SGLT2i) (SLC5A1: IVW OR 0.048, 95% CI 0.004-0.585, P = 0.017), insulin and its analogs (IGF1R: IVW OR 0.773, 95% CI 0.648-0.922, P = 0.004), and sulfonylureas (TRPM4: IVW OR 0.869, 95% CI 0.766-0.985, P = 0.028; CTPA1: IVW OR 0.838, 95% CI 0.741-0.947, P = 0.005). In SMR analysis, antidiabetic drugs targeting the genes CPE (P = 0.03, HEIDI = 0.970) and TRPM4 (P = 0.028, HEIDI = 0.746) were found to significantly reduce the risk of MIF.

CONCLUSION

Our study indicates that metformin, SGLT2i, insulin and its analogs, as well as sulfonylureas, may offer potential therapeutic benefits for MIF. Specifically, six antidiabetic drug target genes GPD1, SLC5A1, IGF1R, TRPM4, CPT1 A, and CPE may play a role in the progression of MIF. These findings have significant implications for the development of personalized precision therapies for MIF.

Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning

Background

Recent studies have suggested a potential association between gastric cancer (GC) and myocardial infarction (MI), with shared pathogenic factors. This study aimed to identify these common factors and potential pharmacologic targets.

Methods

Data from the IEU Open GWAS project were used. Two-sample Mendelian randomization (MR) analysis was used to explore the causal link between MI and GC. Transcriptome analysis identified common differentially expressed genes, followed by enrichment analysis. Drug target MR analysis and eQTLs validated these associations with GC, and the Steiger direction test confirmed their direction. The random forest and Lasso algorithms were used to identify genes with diagnostic value, leading to nomogram construction. The performance of the model was evaluated via ROC, calibration, and decision curves. Correlations between diagnostic genes and immune cell infiltration were analyzed.

Results

MI was linked to increased GC risk (OR=1.112, P=0.04). Seventy-four genes, which are related mainly to ubiquitin-dependent proteasome pathways, were commonly differentially expressed between MI and GC. Nine genes were consistently associated with GC, and eight had diagnostic value. The nomogram built on these eight genes had strong predictive performance (AUC=0.950, validation set AUC=0.957). Immune cell infiltration analysis revealed significant correlations between several genes and immune cells, such as T cells, macrophages, neutrophils, B cells, and dendritic cells.

Conclusion

MI is associated with an increased risk of developing GC, and both share common pathogenic factors. The nomogram constructed based on 8 genes with diagnostic value had good predictive performance.

Genetic variation in targets of antihyperglycemic drugs and inflammatory bowel disease' risk: A mendelian randomization study

AIM

Antihyperglycemic drugs have potential therapeutic benefits for inflammatory bowel disease (IBD). We aimed to investigate the association between genetic variations in gene-targeted antihyperglycemic drugs and the risk of IBD.

METHODS

Summary statistics for HbA1c data were from the UK Biobank including 344,182 participants. Statistics of IBD were obtained from UK Inflammatory Bowel Disease Genetics. Two Mendelian randomization methods were employed to derive the main findings.

RESULTS

In the SMR analysis, increased expression of genetic variations in SGLT2 inhibitor targets (gene: SLC5A2) was linked to a higher risk of CD (OR: 1.97, P = 0.048). Genetic variation in brain cerebellum tissue of sulfonylurea targets (gene: ABCC8) expression was positively associated with IBD (OR = 1.11, P = 0.000). The genetic variation in the GLP-1RA targets (gene: GLP1R) expression was positively correlated with IBD (OR: 1.45, P = 0.039). The IVW-MR analysis suggested reduced IBD and CD risk with expression of increased genetic variation in the thiazolidinediones targets (gene: PPARG).

CONCLUSION

Genetic variations in SGLT2 inhibitor targets might be associated with an increased risk of CD. The ABCC8 gene might be linked to IBD, CD, and UC. There might be a positive correlation between genetic variation in the GLP-1RA targets expression and IBD occurrence.

Therapeutic targets of antidiabetic drugs and kidney stones: A druggable mendelian randomization study and experimental study in rats

Diabetes is known to increase the risk of kidney stones, but the influence of antidiabetic drugs on this risk remains uncertain. Genetic instruments for antidiabetic drugs were identified as variants, which were associated with both the expression of genes encoding target proteins of drugs and glycated hemoglobin level (HbA1c). Here, we investigated the effect of antidiabetic drugs on kidney stones in a mendelian randomization (MR) framework, and further explore the potential effect on CaOx stone rat models induced by glyoxylic acid. Genetically proxied thiazolidinediones (PPARG agonists) significantly reduced the risk of kidney stones (OR = 0.42; P=0.004) per 1-SD decrement in HbA1c, while no significant association was noted in sulfonylureas, SGLT2 inhibitors, or GLP-1 analogs. Other antidiabetic drugs were not analyzed due to unclear pharmacological targets or no identified instruments. Additionally, PPARG agonists pioglitazone ameliorated CaOx nephrocalcinosis in glyoxylic acid-induced rats. The summary-data-based MR (SMR) results showed that PPARG mRNA expression in blood or kidney was not associated with kidney stone risk, and thus we performed mediation MR of PPARG agonists, circulating metabolites, and kidney stones. Among 249 circulating metabolites, we identified an indirect effect of PPARG agonists on kidney stones through increasing phospholipids to total lipids ratio in very large VLDL, with a mediated proportion of 6.87% (P = 0.018). Our study provided evidence that PPARG agonists reduced the risk of kidney stones partially via regulating lipid metabolism, and PPARG agonists may be a promising study subject in clinical studies for the prevention of kidney stones.

Insulin Sensitivity Controls Activity of Pathogenic CD4+ T Cells in Rheumatoid Arthritis

Hyperinsulinemia connects obesity, and a poor lipid profile, with type 2 diabetes (T2D). Here, we investigated consequences of insulin exposure for T cell function in the canonical autoimmunity of rheumatoid arthritis (RA). We observed that insulin levels correlated with the glycolytic index of CD4+ cells but suppressed transcription of insulin receptor substrates, which was inversely related to insulin sensitivity. This connection between insulin levels and the glycolytic index was not seen in CD4+ cells of healthy controls. Exposure of CD4+ cells to insulin induced a senescent state recognized by cell cycle arrest and DNA content enrichment measured by flow cytometry. It also resulted in accumulation of DNA damage marker γH2AX. Insulin suppressed IFNγ production and induced the senescence-associated secretome in CD4+ cell cultures and in patients with hyperinsulinemia. Inhibition of JAK-STAT signaling (JAKi) improved insulin signaling, which activated the glycolytic index and facilitated senescence in CD4+ cell cultures. Treatment with JAKi was associated with an abundance of naïve and recent thymic emigrant T cells in the circulation of RA patients. Thus, we concluded that insulin exerts immunosuppressive ability by inducing senescence and inhibiting IFNγ production in CD4+ cells. JAKi promotes insulin effects and supports elimination of the pathogenic CD4+ cell in RA patients.

Innovate therapeutic targets for autoimmune diseases: insights from proteome-wide mendelian randomization and Bayesian colocalization

BACKGROUND

Despite growing knowledge regarding the pathogenesis of autoimmune diseases (ADs) onset, the current treatment remains unsatisfactory. This study aimed to identify innovative therapeutic targets for ADs through various analytical approaches.

RESEARCH DESIGN AND METHODS

Utilizing Mendelian randomization, Bayesian co-localization, phenotype scanning, and protein-protein interaction network, we explored potential therapeutic targets for 14 ADs and externally validated our preliminary findings.

RESULTS

This study identified 12 circulating proteins as potential therapeutic targets for six ADs. Specifically, IL12B was judged to be a risk factor for ankylosing spondylitis (p = 1.61E - 07). TYMP (p = 6.28E - 06) was identified as a protective factor for ulcerative colitis. For Crohn's disease, ERAP2 (p = 4.47E - 14), HP (p = 2.08E - 05), and RSPO3 (p = 6.52E - 07), were identified as facilitators, whereas FLRT3 (p = 3.42E - 07) had a protective effect. In rheumatoid arthritis, SWAP70 (p = 3.26E - 10), SIGLEC6 (p = 2.47E - 05), ISG15 (p = 3.69E - 05), and FCRL3 (p = 1.10E - 10) were identified as risk factors. B4GALT1 (p = 6.59E - 05) was associated with a lower risk of Type 1 diabetes (T1D). Interestingly, CTSH was identified as a protective factor for narcolepsy (p = 1.58E - 09) but a risk factor for T1D (p = 7.36E - 11), respectively. External validation supported the associations of eight of these proteins with three ADs.

CONCLUSIONS

Our integrated study identified 12 potential therapeutic targets for ADs and provided novel insights into future drug development for ADs.

Analysis of the causal relationship between immune cells and rheumatoid arthritis from the perspective of genetic variation: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Immune factors are crucial in the pathogenesis of rheumatoid arthritis (RA), and immune cells play a key role in the development of RA. However, there is still disagreement regarding the specific roles of each type of immune cell in the pathological process of RA.

METHODS

This study used bidirectional two-sample Mendelian randomization (MR) analysis to determine the causal relationship between immune cell characteristics and RA. Utilizing publicly available genetic data, we initially treated immune cell characteristics as exposures to investigate their causal effects on the risk of RA. Subsequently, we performed reverse two-sample MR using the positively selected cells from the initial analysis as outcomes, aiming to identify the core immune cells involved. Finally, a comprehensive sensitivity analysis was conducted to validate the robustness, heterogeneity, and horizontal pleiotropy of the results.

RESULTS

Using data from 731 immune cells as exposures and cell SNPs as instruments, we independently conducted two-sample MR analysis for each patient with RA. The main analytical method used was the IVW method, with a significance level set at P < 0.05 for inclusion. In total, we identified 42 immune cell phenotypes that were causally associated with the onset of RA. For the reverse MR analysis, we used RA as the exposure factor and focused on 42 immune cell phenotypes as outcomes. Our analysis revealed causal relationships between the onset of RA and 7 immune cell phenotypes. Among these, 6 showed positive causal relationships, while 1 exhibited a negative causal relationship.

CONCLUSIONS

Our study emphasized the causal relationship between immune cells and RA through bidirectional two-sample MR analysis, identifying the immune cells causally associated with RA.

Repurposing metabolic regulators: antidiabetic drugs as anticancer agents

Drug repurposing in cancer taps into the capabilities of existing drugs, initially designed for other ailments, as potential cancer treatments. It offers several advantages over traditional drug discovery, including reduced costs, reduced development timelines, and a lower risk of adverse effects. However, not all drug classes align seamlessly with a patient's condition or long-term usage. Hence, repurposing of chronically used drugs presents a more attractive option. On the other hand, metabolic reprogramming being an important hallmark of cancer paves the metabolic regulators as possible cancer therapeutics. This review emphasizes the importance and offers current insights into the repurposing of antidiabetic drugs, including metformin, sulfonylureas, sodium-glucose cotransporter 2 (SGLT2) inhibitors, dipeptidyl peptidase 4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), thiazolidinediones (TZD), and α-glucosidase inhibitors, against various types of cancers. Antidiabetic drugs, regulating metabolic pathways have gained considerable attention in cancer research. The literature reveals a complex relationship between antidiabetic drugs and cancer risk. Among the antidiabetic drugs, metformin may possess anti-cancer properties, potentially reducing cancer cell proliferation, inducing apoptosis, and enhancing cancer cell sensitivity to chemotherapy. However, other antidiabetic drugs have revealed heterogeneous responses. Sulfonylureas and TZDs have not demonstrated consistent anti-cancer activity, while SGLT2 inhibitors and DPP-4 inhibitors have shown some potential benefits. GLP-1RAs have raised concerns due to possible associations with an increased risk of certain cancers. This review highlights that further research is warranted to elucidate the mechanisms underlying the potential anti-cancer effects of these drugs and to establish their efficacy and safety in clinical settings.

Immunomodulatory Effects of SGLT2 Inhibitors and Metformin in Managing Rheumatic Diseases: A Narrative Review

Limited studies summarise the immunomodulatory effects of SGLT2 inhibitors and Metformin in managing rheumatic diseases. The present narrative review aims to fill this knowledge gap by gathering information based on existing clinical evidence. A narrative review was conducted in November 2023 to identify studies investigating the impact of SGLT2 inhibitors and Metformin on rheumatic diseases. A literature search was performed across primary databases, including Medline/PubMed, Scopus, and Web of Science. Supplementary sources like Google Scholar, PubMed Central, Cochrane Library, and ScienceDirect were also consulted. Studies were screened for relevance, and those lacking pertinent outcome data were excluded. The review corroborates the multifaceted potential of Metformin as an adjunctive therapy in autoimmune rheumatologic conditions, offering avenues for further exploration and clinical application to enhance patient outcomes. However, limited literature exists on the clinical effects of SGLT2 inhibitors in rheumatic diseases.

Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis

BACKGROUND

Osteoarthritis is a leading cause of disability, and disease-modifying osteoarthritis drugs (DMOADs) could represent a pivotal advancement in treatment. Identifying the potential of antidiabetic medications as DMOADs could impact patient care significantly.

METHODS

We designed a comprehensive analysis pipeline involving two-sample Mendelian Randomization (MR) (genetic proxies for antidiabetic drug targets), summary-based MR (SMR) (for mRNA), and colocalisation (for drug-target genes) to assess their causal relationship with 12 osteoarthritis phenotypes. Summary statistics from the largest genome-wide association meta-analysis (GWAS) of osteoarthritis and gene expression data from the eQTLGen consortium were utilised.

FINDINGS

Seven out of eight major types of clinical antidiabetic medications were identified, resulting in fourteen potential drug targets. Sulfonylurea targets ABCC8/KCNJ11 were associated with increased osteoarthritis risk at any site (odds ratio (OR): 2.07, 95% confidence interval (CI): 1.50-2.84, P < 3 × 10-4), while PPARG, influenced by thiazolidinediones (TZDs), was associated with decreased risk of hand (OR: 0.61, 95% CI: 0.48-0.76, P < 3 × 10-4), finger (OR: 0.50, 95% CI: 0.35-0.73, P < 3 × 10-4), and thumb (OR: 0.49, 95% CI: 0.34-0.71, P < 3 × 10-4) osteoarthritis. Metformin and GLP1-RA, targeting GPD1 and GLP1R respectively, were associated with reduced risk of knee and finger osteoarthritis. In the SMR analyses, gene expression of KCNJ11, GANAB, ABCA1, and GSTP1, targeted by antidiabetic drugs, was significantly linked to at least one osteoarthritis phenotype and was replicated across at least two gene expression datasets. Additionally, increased KCNJ11 expression was related to decreased osteoarthritis risk and co-localised with at least one osteoarthritis phenotype.

INTERPRETATION

Our findings suggest a potential therapeutic role for antidiabetic drugs in treating osteoarthritis. The results indicate that certain antidiabetic drug targets may modify disease progression, with implications for developing targeted DMOADs.

FUNDING

This study was funded by the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (2022), the Shanghai Municipal Health Commission Health Industry Clinical Research Project (Grant No. 20224Y0139), Beijing Natural Science Foundation (Grant No. 7244458), and the Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (Grant No. GZC20230130).

Repurposing anti-osteoporosis drugs for autoimmune diseases: A two-sample Mendelian randomization study

BACKGROUND

Despite the increasing availability of therapeutic drugs for autoimmune diseases, many patients still struggle to achieve their treatment goals. Our aim was to identify whether drugs originally used to treat bone density could be applied to the treatment of autoimmune diseases through Mendelian randomization (MR).

METHODS

Using summary statistics from genome-wide association studies, we used a two-sample MR design to estimate the correlation between autoimmune diseases and BMD-related drug targets. Data from the DrugBank and ChEMBL databases were used to identify the drug targets of anti-osteoporosis medications. The Wald ratio test or inverse-variance weighting method was used to assess the impact of genetic variation in drug target(s) on autoimmune disease therapy.

RESULTS

Through our analysis, we discovered a negative correlation between genetic variability in a specific gene (ESR1) in raloxifene/colecalciferol and various autoimmune disorders such as ankylosing spondylitis, endometriosis, IgA nephropathy, rheumatoid arthritis, sarcoidosis, systemic lupus erythematosus, and type 1 diabetes.

CONCLUSION

These results indicate a possible link between genetic differences in the drug targeting ESR1 and susceptibility to autoimmune disorders. Hence, our study offers significant support for the possible use of drugs targeting ESR1 for the management of autoimmune disorders. MR and drug repurposing are utilized to investigate the relationship between autoimmune diseases and bone mineral density, with a focus on ESR1.

The causal relationship between anti-diabetic drugs and gastrointestinal disorders: a drug-targeted mendelian randomization study

BACKGROUND

The incidence of diabetic gastrointestinal diseases is increasing year by year. This study aimed to investigate the causal relationship between antidiabetic medications and gastrointestinal disorders, with the goal of reducing the incidence of diabetes-related gastrointestinal diseases and exploring the potential repurposing of antidiabetic drugs.

METHODS

We employed a two-sample Mendelian randomization (TSMR) design to investigate the causal association between antidiabetic medications and gastrointestinal disorders, including gastroesophageal reflux disease (GERD), gastric ulcer (GU), chronic gastritis, acute gastritis, Helicobacter pylori infection, gastric cancer (GC), functional dyspepsia (FD), irritable bowel syndrome (IBS), ulcerative colitis (UC), Crohn's disease (CD), diverticulosis, and colorectal cancer (CRC). To identify potential inhibitors of antidiabetic drug targets, we collected single-nucleotide polymorphisms (SNPs) associated with metformin, GLP-1 receptor agonists, SGLT2 inhibitors, DPP-4 inhibitors, insulin, and its analogs, thiazolidinediones, sulfonylureas, and alpha-glucosidase inhibitors from published genome-wide association study statistics. We then conducted a drug-target Mendelian randomization (MR) analysis using inverse variance weighting (IVW) as the primary analytical method to assess the impact of these inhibitors on gastrointestinal disorders. Additionally, diabetes was selected as a positive control.

RESULTS

Sulfonylureas were found to significantly reduce the risk of CD (IVW: OR [95% CI] = 0.986 [0.978, 0.995], p = 1.99 × 10- 3), GERD (IVW: OR [95% CI] = 0.649 [0.452, 0.932], p = 1.90 × 10- 2), and chronic gastritis (IVW: OR [95% CI] = 0.991 [0.982, 0.999], p = 4.50 × 10- 2). However, they were associated with an increased risk of GU development (IVW: OR [95%CI] = 2 0.761 [1.259, 6.057], p = 1 0.12 × 10- 2).

CONCLUSIONS

The results indicated that sulfonylureas had a positive effect on the prevention of CD, GERD, and chronic gastritis but a negative effect on the development of gastric ulcers. However, our research found no causal evidence for the impact of metformin, GLP-1 agonists, SGLT2 inhibitors, DPP 4 inhibitors, insulin and its analogs, thiazolidinediones, or alpha-glucosidase inhibitors on gastrointestinal diseases.

Causal associations of male infertility with stroke: a two-sample Mendelian randomization study

Background

Stroke is a devastating global health issue, with high mortality and disability rates. The increasing prevalence of male infertility among reproductive-aged men has become a growing concern worldwide. However, the relationship between male infertility and stroke incidence remains uncertain. This study aimed to address this knowledge gap by employing a Mendelian randomization (MR) approach.

Method

Utilizing genetic instrumental variables derived from a genome-wide association study (GWAS) on male infertility and stroke, a two-sample MR design was implemented. Five different analysis methods, with inverse-variance weighted as the primary approach, were used to examine the genetic causal associations between male infertility and various stroke subtypes. Heterogeneity analysis, pleiotropy tests, and leave-one-out validation were conducted to assess heterogeneity, evaluate pleiotropy, and ensure the robustness of the findings.

Result

The results indicate a potential lower risk of small vessel stroke associated with male infertility (odds ratio, 95% confidence interval: 0.82, 0.68 to 0.99, p=0.044), although no significant impact on other stroke subtypes was observed. The study exhibited low heterogeneity and no apparent pleiotropy; however, the stability of the results was not optimal.

Conclusion

Male infertility might potentially confer a protective effect against small vessel stroke risk. Caution is warranted due to potential confounding factors. Additional studies are necessary to confirm these findings and provide further validation.

Associations Between Thiazolidinediones Use and Incidence of Rheumatoid Arthritis: A Retrospective Population-Based Cohort Study

OBJECTIVE

Preclinical studies suggest that thiazolidinediones (TZDs) may have a protective effect on rheumatoid arthritis (RA), but evidence from population-based studies is scarce. This study aimed to assess the association between use of TZDs and incidence of RA in a retrospective cohort of patients with type 2 diabetes mellitus (T2DM).

METHODS

A retrospective cohort of patients with T2DM who were new users of TZDs or alpha glucosidase inhibitors (AGIs) was assembled. We applied the inverse probability of treatment weighted Cox model to estimate the hazard ratio (HR) of RA incidence associated with the use of TZDs compared with AGIs.

RESULTS

The final analysis included 56,796 new users of AGIs and 14,892 new users of TZDs. The incidence of RA was 187.4 and 135.2 per 100,000 person-years in AGI users and TZD users, respectively. Compared with use of AGIs, TZD use was associated with a reduction in RA incidence, with an HR of 0.72 (95% confidence interval [95% CI] 0.59-0.89). HRs for cumulative use of TZDs for 0.51 to 4.0 years and more than 4 years with incidence of RA were 0.55 (95% CI 0.35-0.88) and 0.74 (95% CI 0.57-0.98), respectively. Various subgroup analyses and sensitivity analyses were consistent with the primary analysis.

CONCLUSION

Use of TZDs is associated with a decreased risk of incident RA in patients with T2DM.

Lipid Metabolism, Methylation Aberrant, and Osteoporosis: A Multi-omics Study Based on Mendelian Randomization

BACKGROUND

Observational studies have shown a causal association between dyslipidemia and osteoporosis, but the genetic causation and complete mechanism of which are uncertain. The disadvantage of previous observational studies is that they are susceptible to confounding factors and bias, that makes it difficult to infer a causal link between those two diseases. Abnormal epigenetic modifications, represented by DNA methylation, are important causes of many diseases. However, there are no studies showing a bridging role for methylation modifications in blood lipid metabolism and osteoporosis.

METHODS

SNPs for lipid profile (Blood VLDL cholesterol (VLDL-C), blood LDL cholesterol (LDL-C), blood HDL cholesterol (HDL-C), blood triglycerides (TG), diagnosed pure hypercholesterolaemia, blood apolipoprotein B (Apo B), blood apolipoprotein A1(Apo A1)), and bone mineral density (BMD) in different body parts (Heel BMD, lumbar BMD, whole-body BMD, femoral neck BMD) were obtained from large meta-analyses of genome-wide association studies as instrumental variables for two-sample Mendelian randomization. Assessment of the genetic effects of lipid profile-associated methylation sites and bone mineral density was carried out using the summary-data-based Mendelian randomization (SMR) method.

RESULTS

Two-sample Mendelian randomization showed that there was a negative causal association between hypercholesterolaemia and heel BMD (p = 0.0103, OR = 0.4590), and total body BMD (p = 0.0002, OR = 0.2826). LDL-C had a negative causal association with heel BMD (p = 8.68E-05, OR = 0.9586). VLDL-C had a negative causal association with heel BMD (p = 0.035, OR = 0.9484), lumbar BMD (p = 0.0316, OR = 0.9356), and total body BMD (p = 0.0035, OR = 0.9484). HDL-C had a negative causal association with heel BMD (p = 1.25E-05, OR = 0.9548), lumbar BMD (p = 0.0129, OR = 0.9358), and total body BMD (p = 0.0399, OR = 0.9644). Apo B had a negative causal association with heel BMD (p = 0.0001, OR = 0.9647). Apo A1 had a negative causal association with heel BMD (p = 0.0132, OR = 0.9746) and lumbar BMD (p = 0.0058, OR = 0.9261). The p-values of all positive results corrected by the FDR method remained significant and sensitivity analysis showed that there was no horizontal pleiotropy in the results despite the heterogeneity in some results. SMR identified 3 methylation sites associated with lipid profiles in the presence of genetic effects on BMD: cg15707428(GREB1), cg16000331(SREBF2), cg14364472(NOTCH1).

CONCLUSION

Our study provides insights into the potential causal links and co-pathogenesis between dyslipidemia and osteoporosis. The genetic effects of dyslipidaemia on osteoporosis may be related to certain aberrant methylation genetic modifications.

The landscape of the methodology in drug repurposing using human genomic data: a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record data, public availability of various databases containing biological and clinical information and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1 May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies.

Thyroid function and epilepsy: a two-sample Mendelian randomization study

Background

Thyroid hormones (THs) play a crucial role in regulating various biological processes, particularly the normal development and functioning of the central nervous system (CNS). Epilepsy is a prevalent neurological disorder with multiple etiologies. Further in-depth research on the role of thyroid hormones in epilepsy is warranted.

Methods

Genome-wide association study (GWAS) data for thyroid function and epilepsy were obtained from the ThyroidOmics Consortium and the International League Against Epilepsy (ILAE) Consortium cohort, respectively. A total of five indicators of thyroid function and ten types of epilepsy were included in the analysis. Two-sample Mendelian randomization (MR) analyses were conducted to investigate potential causal relations between thyroid functions and various epilepsies. Multiple testing correction was performed using Bonferroni correction. Heterogeneity was calculated with the Cochran's Q statistic test. Horizontal pleiotropy was evaluated by the MR-Egger regression intercept. The sensitivity was also examined by leave-one-out strategy.

Results

The findings indicated the absence of any causal relationship between abnormalities in thyroid hormone and various types of epilepsy. The study analyzed the odds ratio (OR) between thyroid hormones and various types of epilepsy in five scenarios, including free thyroxine (FT4) on focal epilepsy with hippocampal sclerosis (IVW, OR = 0.9838, p = 0.02223), hyperthyroidism on juvenile absence epilepsy (IVW, OR = 0.9952, p = 0.03777), hypothyroidism on focal epilepsy with hippocampal sclerosis (IVW, OR = 1.0075, p = 0.01951), autoimmune thyroid diseases (AITDs) on generalized epilepsy in all documented cases (weighted mode, OR = 1.0846, p = 0.0346) and on childhood absence epilepsy (IVW, OR = 1.0050, p = 0.04555). After Bonferroni correction, none of the above results showed statistically significant differences.

Conclusion

This study indicates that there is no causal relationship between thyroid-related disorders and various types of epilepsy. Future research should aim to avoid potential confounding factors that might impact the study.

Therapeutic potential of Coptis chinensis for arthritis with underlying mechanisms

Arthritis is a common degenerative disease of joints, which has become a public health problem affecting human health, but its pathogenesis is complex and cannot be eradicated. Coptis chinensis (CC) has a variety of active ingredients, is a natural antibacterial and anti-inflammatory drug. In which, berberine is its main effective ingredient, and has good therapeutic effects on rheumatoid arthritis (RA), osteoarthritis (OA), gouty arthritis (GA). RA, OA and GA are the three most common types of arthritis, but the relevant pathogenesis is not clear. Therefore, molecular mechanism and prevention and treatment of arthritis are the key issues to be paid attention to in clinical practice. In general, berberine, palmatine, coptisine, jatrorrhizine, magnoflorine and jatrorrhizine hydrochloride in CC play the role in treating arthritis by regulating Wnt1/β-catenin and PI3K/AKT/mTOR signaling pathways. In this review, active ingredients, targets and mechanism of CC in the treatment of arthritis were expounded, and we have further explained the potential role of AHR, CAV1, CRP, CXCL2, IRF1, SPP1, and IL-17 signaling pathway in the treatment of arthritis, and to provide a new idea for the clinical treatment of arthritis by CC.