Accumulating evidences have indicated that lipid-lowering drugs have effect for the treatment of cancers. However, causal associations between lipid-lowering drugs and the risk of cancers are still unclear. In our study, we utilized single nucleotide polymorphisms of proprotein convertase subtilis kexin 9 (PCSK9) inhibitors and 3-hydroxy-3-methylglutaryl-assisted enzyme A reductase (HMGCR) inhibitors and performed a drug target Mendelian randomization to explore the causal association between lipid-lowering drugs and the risk of cancers. Five regression methods were carried out, including inverse variance weighted (IVW) method, MR Egger, weighted median, simple mode and weighted mode methods, of which IVW method was considered as the main analysis. Our outcome dataset contained the risk of breast cancer (BC), colorectal cancer, endometrial cancer, gastric cancer (GC), hepatocellular carcinoma (HCC), lung cancer, esophageal cancer, prostate cancer (PC), and skin cancer (SC). Our results demonstrated that PCSK9 inhibitors were significant associated with a decreased effect of GC [IVW: OR = 0.482, 95% CI: 0.264–0.879, P = .017]. Besides, genetic inhibitions of HMGCR were significant correlated with an increased effect of BC [IVW: OR = 1.421, 95% CI: 1.056–1.911, P = .020], PC [IVW: OR = 1.617, 95% CI: 1.234–2.120, P = .0005] and SC [IVW: OR = 1.266, 95% CI: 1.022–1.569, P = .031]. For GC [IVW: OR = 0.559, 95% CI: 0.382–0.820, P = .0029] and HCC [IVW: OR = 0.241, 95% CI: 0.085–0.686, P = .0077], HMGCR inhibitors had a protective risk. Our method suggested that PCSK9 inhibitors were significant associated with a protective effect of GC. Genetic inhibitions of HMGCR were significant correlated with an increased effect of BC, PC and SC. Meanwhile, HMGCR inhibitors had a protective risk of GC and HCC. Subsequent studies still needed to assess potential effects between lipid-lowering drugs and the risk of cancers with clinical trials.

Growing evidences of recent studies have shown that gut microbrome are causally related to digestive system diseases (DSDs). However, causal relationships between the gut microbiota and the risk of DSDs still remain unclear. We utilized identified gut microbiota based on class, family, genus, order and phylum information and digestive system diseases genome-wide association study (GWAS) dataset for two-sample Mendelian randomization (MR) analysis. The inverse variance weighted (IVW) method was used to evaluate causal relationships between gut microbiota and 7 DSDs, including chronic gastritis, colorectal cancer, Crohn’s disease, gastric cancer, gastric ulcer, irritable bowel syndrome and esophageal cancer. Finally, we verified the robustness of MR results based on heterogeneity and pleiotropy analysis. We discovered 15 causal associations with genetic liabilities in the gut microbiota and DSDs, such as genus Victivallis, genus RuminococcaceaeUCG005, genus Ruminococcusgauvreauiigroup, genus Oxalobacter and so on. Our MR analysis revealed that the gut microbiota is causally associated with DSDs. Further researches of the gut microbiota and the pathogenesis of DSDs are still significant and provide new methods for the prevention and treatment of DSDs.

Evidence from observational researches have suggested that mental diseases are able to affect thyroid diseases. However, the causal relationship between mental diseases and the risk of thyroid diseases still remains unclear. Herein, we conducted a two-sample Mendelian randomization (MR) statistical analysis method to assess the causality between mental diseases and thyroid diseases. Initially, publicly available genome-wide association studies summary data were leveraged to obtain single-nucleotide polymorphisms based on set parameters. Subsequently, a two-sample MR was utilized to analyze causal relationships between mental diseases (Alzheimer disease, bipolar disorder, major depressive disorder, Parkinson disease, schizophrenia) and thyroid diseases (hyperthyroidism/thyrotoxicosis, hypothyroidism) with removing outliers based on MR-PRESSO method. Finally, 8 regression MR methods (inverse variance weighted [IVW], IVW fixed effects, c, MR Egger, weighted median, penalized weighted median, simple mode, weighted mode) were performed to evaluate bias and effectiveness, of which IVW was considered as the primary method. Our results demonstrated that most of mental diseases have no causal relationships with thyroid diseases except bipolar disorder and hyperthyroidism/thyrotoxicosis based on IVW method [odds ratio: 0.999, 95% confidence interval: 0.998–1.000, P = .028], and bipolar disorder and hypothyroidism based on IVW method [odds ratio: 0.997, 95% confidence interval: 0.995–0.999, P = .002]. Then we subsequently conducted a consistent robustness analysis to assess heterogeneity and horizontal pleiotropy. Our method reports causal relationships exist mental diseases and the risk of thyroid diseases. Subsequent researches are still warranted to determine how mental diseases influence the development of thyroid diseases.