UNASSIGNED: Previous observational clinical studies and meta-analyses have yielded inconsistent results regarding the relationship between vitamin D and headache, and the causal relationship remains unclear. The aim of this study was to investigate the causal relationship between vitamin D and headache by bidirectional two-sample Mendelian randomisation (MR) analysis.
UNASSIGNED: The relationship between high levels of vitamin D and headache was investigated by two-sample MR analysis using publicly available genome-wide association study (GWAS) data. The primary method was inverse variance weighting (IVW), and secondary methods were weighted median and MR-Egger methods. No heterogeneity or horizontal multidirectionality was found in the MR results. The robustness and validity of the findings were assessed using the leave-behind method.
UNASSIGNED: A significant causal relationship was found between high vitamin D levels and headache using the IVW method (OR = 0.848; p = 0.007; 95% CI = 0.752-0.956). However, in a reverse analysis, no evidence of a causal relationship between headache and high levels of vitamin D was found using the IVW method (OR = 1.001; p = 0.906; 95% CI = 0.994-1.006). Our MR analyses showed no significant horizontal multidimensionality or heterogeneity (p > 0.05). Sensitivity analyses confirmed that MR estimates were not affected by single nucleotide polymorphisms (SNPs). Confirmation that our results are robust and valid has been obtained by the leave-one-out method.
UNASSIGNED: Our study suggests that high levels of vitamin D prevent the risk of headache. However, there is no evidence of a causal relationship between headache and high levels of vitamin D. Vitamin D may reduce the risk of headache.

Prior research has identified associations between immune cells and aplastic anaemia (AA); however, the causal relationships between them have not been conclusively established. A two-sample Mendelian randomisation analysis was conducted to investigate the causal link between 731 immune cell signatures and AA risk using publicly available genetic data. Four types of immune signatures, including relative cell, absolute cell (AC), median fluorescence intensities and morphological parameters, were considered sensitivity analyses were also performed to verify the robustness of the results and assess potential issues such as heterogeneity and horizontal pleiotropy. Following multiple test adjustments using the False Discovery Rate (FDR) method, no statistically significant impact of any immunophenotype on AA was observed. However, twelve immunophenotypes exhibited a significant correlation with AA without FDR correction (p of IVW < 0.01), of which eight were harmful to AA: CD127- CD8br %T cell (Treg panel), CD25 on IgD + CD38dim (B cell panel), CD38 on naive-mature B cell (B cell panel), CD39 + resting Treg % CD4 Treg (Treg panel), CD39 + secreting Treg AC (Treg panel), CD8 on CD28 + CD45RA- CD8br (Treg panel), HLA DR + NK AC (TBNK panel), Naive DN (CD4-CD8-) AC (Maturation stages of T cell panel); and four were protective to AA: CD86 on CD62L + myeloid DC (cDC panel), DC AC (cDC panel), DN (CD4-CD8-) NKT %T cell (TBNK panel), and TD CD4 + AC (Maturation stages of T cell panel). The results of this study demonstrate a close link between immune cells and AA by genetic means, thereby improving the current understanding of the interaction between immune cells and AA risk and providing guidance for future clinical research.

OBJECTIVE: Research has previously established connections between the intestinal microbiome and the progression of some cancers. However, there is a noticeable gap in the literature in regard to using Mendelian randomisation (MR) to delve into potential causal relationships between the gut microbiota (GM) and basal cell carcinoma (BCC). Therefore, the purpose of our study was to use MR to explore the causal relationship between four kinds of GM (Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae) and BCC.
METHODS: We used genome-wide association study (GWAS) data and MR to explore the causal relationship between four kinds of GM and BCC. This study primarily employed the random effect inverse variance weighted (IVW) model for analysis, as complemented by additional methods including the simple mode, weighted median, weighted mode and MR‒Egger methods. We used heterogeneity and horizontal multiplicity to judge the reliability of each analysis. MR-PRESSO was mainly used to detect and correct outliers.
RESULTS: The random-effects IVW results showed that Bacteroides (OR = 0.936, 95% CI = 0.787-1.113, p = 0.455), Streptococcus (OR = 0.974, 95% CI = 0.875-1.083, p = 0.629), Proteobacteria (OR = 1.113, 95% CI = 0.977-1.267, p = 0.106) and Lachnospiraceae (OR = 1.027, 95% CI = 0.899-1.173, p = 0.688) had no genetic causal relationship with BCC. All analyses revealed no horizontal pleiotropy, heterogeneity or outliers.
CONCLUSIONS: We found that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae do not increase the incidence of BCC at the genetic level, which provides new insight for the study of GM and BCC.

The purpose of this study was to investigate the relationship between oxidative stress and cognitive function, encompassing cognitive performance, intelligence, memory, reaction time, speech and vision by a bidirectional Mendelian randomisation study. Independent genetic variants associated with glutathione S-transferase (GST), catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPX), peroxiredoxin (PRDX), sulfhydryl oxidase (SOX) and thyroid peroxidase (TPO) were explored using a genome-wide association study (GWAS). The inverse variance weighted (IVW) or Wald ratio method was employed to ascertain the relationship between antioxidant enzymes and cognitive function. The MR analyses indicated that the MR effect estimates of GST (β = 0.0352, P = 0.0047, FDR = 0.0164) and TPO (β = 0.0531, P = 0.0003, FDR = 0.0021) were significantly associated with cognitive performance elevation. Furthermore, genetically predicted GST (β = 0.0334, P = 0.0043, FDR = 0.0151) and TPO (β = 0.0496, P = 0.0031, FDR = 0.0151) were found to be associated with high intelligence. Additionally, there were also some associations of SOX (β = 0.0243, P = 0.0283, FDR = 0.066) on high cognitive performance, TPO (β = 0.1189, P = 0.0315, FDR = 0.2205) on larger maximum digits remembered correctly, and SOX (β = - 0.2435, P = 0.0395, FDR = 0.1185) on reaction time. Nevertheless, the associations between antioxidant enzymes and speech and linguistic disorders, as well as visual disturbances, were not significant. We did not find reverse causation between antioxidant enzymes and cognitive function traits. This study provides evidence of potential causal relationships between oxidative stress and cognitive function.

BACKGROUND: Many studies have found an association between mood-disorder-related traits and endometriosis and adenomyosis. However, the cause-effect relationship remains unclear.
OBJECTIVE: We conducted Mendelian randomisation analyses to evaluate any causal relationship between mood disorders and endometriosis as well as different sites of endometriosis.
METHODS: Summary-level statistics for mood-disorder-related traits and endometriosis (8288 cases, 68 969 controls) in European populations were derived from large-scale data-sets of genome-wide association studies. A two-sample Mendelian randomisation was performed using the inverse-variance weighted and weight median methods. Further sensitivity analyses, including heterogeneity, pleiotropy and leave-one-out analyses, were conducted to test the consistency of the results.
RESULTS: Genetically determined mood swings (odds ratio = 2.557, 95% CI: 1.192-5.483, P = 0.016) and major depression (odds ratio = 1.233, 95% CI: 1.019-1.493, P = 0.031) were causally associated with an increased risk of endometriosis. Mood swings (odds ratio = 4.238, 95% CI: 1.194-15.048, P = 0.025) and major depression (odds ratio = 1.512, 95% CI: 1.052-2.173, P = 0.025) were also causally associated with the risk of adenomyosis. Sensitivity analyses confirmed the reliability of the results.
CONCLUSIONS: Our results suggest that mood-disorder-related traits increase the risk of endometriosis and adenomyosis. This study provides new insights into the potential pathogenesis of endometriosis and adenomyosis, and highlights the importance of preventing endometriosis and adenomyosis in patients with mood-disorder-related traits.

Previous observational studies have indicated a complex association between chronic pain and frailty. This study aimed to examine the bidirectional causal relationship between frailty and chronic pain and to quantify mediating effects of known modifiable risk factors.
A bidirectional two-sample Mendelian randomisation (MR) analysis was applied in this study. Summary genome-wide association statistics for frailty, as defined by both frailty index (FI) and Fried Frailty Score (FFS), pain at seven site-specific chronic pain (SSCP) (headache, facial, neck/shoulder, stomach/abdominal, back, hip and knee) and multisite chronic pain (MCP) were extracted from populations of European ancestry. Genetic instrumental variables strongly correlated with each exposure were selected. The inverse-variance-weighted method was the primary method used in the MR, supplemented by a range of sensitivity and validation analyses. Two-step MR analysis was undertaken to evaluate the mediating effects of several proposed confounders.
Genetically predicted higher FI and FFS were associated with an increased risk of MCP and specific types of SSCP, including neck/shoulder pain, stomach/abdominal pain, back pain, hip pain and knee pain. In the reverse direction analysis, genetic liability to MCP was found to be associated with increased FI and FFS. These results remained consistent across sensitivity and validation assessments. Two-step MR suggested a mediating role for body mass index, smoking initiation, physical inactivity, educational attainment and depression.
Our research provided genetic evidence that the association between frailty and chronic pain was bidirectional where the coexistence of both conditions will exacerbate each other.

BACKGROUND: Epidemiological evidence suggests that there is an association between rheumatoid arthritis (RA) and Alzheimer\'s disease (AD). However, the causal relationship between RA and AD remains unclear. Therefore, this study aimed to investigate the causal relationship between RA and AD.
METHODS: Using publicly available genome-wide association study datasets, bidirectional two-sample Mendelian randomization (TSMR) was performed using the inverse-variance weighted (IVW), weighted median, MR‒Egger regression, simple mode, and weighted mode methods.
RESULTS: The results of MR for the causal effect of RA on AD (IVW, odds ratio [OR] = 0.959, 95% confidence interval [CI]: 0.941-0.978, P = 2.752E-05; weighted median, OR = 0.960, 95% CI: 0.937-0.984, P = 0.001) revealed a causal association between genetic susceptibility to RA and an increased risk of AD. The results of MR for the causal effect of AD on RA (IVW, OR = 0.978, 95% CI: 0.906-1.056, P = 0.576; weighted median, OR = 0.966, 95% CI: 0.894-1.043, P = 0.382) indicated that there was no causal association between genetic susceptibility to AD and an increased risk of RA.
CONCLUSIONS: The results of this two-way two-sample Mendelian randomization analysis revealed a causal association between genetic susceptibility to RA and a reduced risk of AD but did not reveal a causal association between genetic susceptibility to AD and an increased or reduced risk of RA.

cumulative evidence from cohort studies suggested that there were inconsistent conclusions as to whether there was a bidirectional association between depression and frailty. Therefore, this study used a bidirectional two-sample Mendelian randomisation (MR) study to investigate the causal relationship between depression and frailty.
we performed univariate and multivariate bidirectional MR analyses to assess the causal association between depression and frailty. Independent genetic variants associated with depression and frailty were selected as instrumental variables. Inverse variance weighted (IVW), MR-Egger, weighted median and weighted mode were mainly used in univariate MR analysis. Multivariate MR (MVMR) analyses used multivariable inverse variance-weighted methods to individually and jointly adjust for three potential confounders, body mass index (BMI), age at menarche (AAM) and waist-to-hip ratio (WHR, adjusted for BMI).
univariate MR analysis showed a positive causal relationship between depression and risk of frailty (IVW, odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.23-1.37, P = 6.54E-22). Causal relationship between frailty and risk of depression (IVW, OR = 1.69, 95% CI = 1.33-2.16, P = 2.09E-05). MVMR analysis revealed that the bidirectional causal association between depression and frailty remained after adjusting for three potential confounders, BMI, AAM and WHR (adjusted for BMI), individually and in combination.
our findings supported a causal relationship between genetically predicted depression and frailty in both directions.

Polycystic ovary syndrome (PCOS) is often accompanied by increased oxidative stress levels; however, it is still unclear whether PCOS itself is causally related to oxidative stress (OS), whether OS can increase the occurrence of PCOS, and which characteristics of PCOS increase OS levels. Therefore, this study explored the causal relationship between PCOS, its characteristics, and OS.
Two-sample bidirectional and two-sample Mendelian randomisation studies were performed based on publicly available statistics from genome-wide association studies. PCOS; its characteristics, such as testosterone, low-density lipoprotein, high-density lipoprotein; and 11 major OS markers (superoxide dismutase, glutathione S-transferase, glutathione peroxidase, catalase, uric acid, zinc, tocopherol, ascorbic acid, retinol, albumin, and total bilirubin), were studied. The main analytical method used was inverse variance weighting (IVW). Pleiotropy was evaluated using the Mendelian randomisation-Egger intercept. Q and P values were used to assess heterogeneity.
There was no causal relationship between PCOS and the OS indices (all P > 0.05). There was a causal relationship between the OS index, ascorbate level, and PCOS (IVW, odds ratio: 2.112, 95% confidence interval: 1.257-3.549, P = 0.005). In addition, there was a causal relationship between testosterone, low-density lipoprotein, high-density lipoprotein, sex hormone-binding globulin, body mass index, triacylglycerol, age at menarche, and most OS indices according to the IVW method. The F statistics showed that there was no weak instrumental variable. A sensitivity analysis was performed using the leave-one-out method. No pleiotropy was observed. The results were robust, and the conclusions were reliable.
This study showed for the first time that there was no causal relationship between PCOS and OS. However, there was a causal relationship between the OS index, ascorbate level, and PCOS. It revealed that PCOS itself could not increase OS, and the increase in OS in PCOS was related to other potential factors, such as testosterone, low-density lipoprotein, high-density lipoprotein, sex hormone-binding globulin, body mass index, triacylglycerol, and age at menarche.

Drug development is a costly, time-consuming, and challenging endeavour, with only a few agents reaching the threshold of approval for clinical use. Therefore, approaches to more efficiently identify targets that are likely to translate to clinical benefit are required. Interrogation of the human genome in large patient cohorts has rapidly advanced our knowledge of the genetic architecture and underlying mechanisms of many diseases, including nonalcoholic fatty liver disease (NAFLD). There are no approved pharmacotherapies for NAFLD currently. Genetic insights provide a powerful and new approach to infer and prioritise candidate drugs, with such selection avoiding myriad pitfalls, while defining likely benefits. In this review, we discuss the prospects and challenges for the optimal utilisation of genetic findings for improving and accelerating the NAFLD drug discovery pipeline.