Objective: We conducted a Mendelian randomization (MR) study to disentangle the comparative effects of lipids and apolipoproteins on ischemic stroke. Methods: Single-nucleotide polymorphisms associated with low-and high-density lipoprotein (LDL and HDL) cholesterol, triglycerides, and apolipoprotein A-I and B (apoA-I and apoB) at the level of genomewide significance (p < 5 × 10 −8) in the UK Biobank were used as instrumental variables. Summary-level data for ischemic stroke and its subtypes were obtained from the MEGASTROKE consortium with 514,791 individuals (60,341 ischemic stroke cases, and 454,450 non-cases). Results: Increased levels of apoB, LDL cholesterol, and triglycerides were associated with higher risk of any ischemic stroke, large artery stroke, and small vessel stroke in the main and sensitivity univariable MR analyses. In multivariable MR analysis including apoB, LDL cholesterol, and triglycerides in the same model, apoB retained a robust effect (p < 0.05), whereas the estimate for LDL cholesterol was reversed, and that for triglycerides largely attenuated. Decreased levels of apoA-I and HDL cholesterol were robustly associated with increased risk of any ischemic stroke, large artery stroke, and small vessel stroke in all univariable MR analyses, but the association for apoA-I was attenuated to the null after mutual adjustment. Interpretation: The present MR study reveals that apoB is the predominant trait that accounts for the etiological basis of apoB, LDL cholesterol, and triglycerides in relation to ischemic stroke, in particular large artery and small vessel stroke. Whether HDL cholesterol exerts a protective effect on ischemic stroke independent of apoA-I needs further investigation.

Aims/hypothesis Observational studies have shown a bidirectional association between major depressive disorder (MDD) and cardiometabolic diseases. We conducted a two-sample bidirectional Mendelian randomisation (MR) study to assess the causal associations of MDD with type 2 diabetes, coronary artery disease (CAD) and heart failure and vice versa. Methods We extracted summary-level data for MDD, type 2 diabetes, CAD and heart failure from corresponding published large genome-wide association studies of individuals mainly of European-descent. In total, 96 SNPs for MDD, 202 SNPs for type 2 diabetes, 44 SNPs for CAD and 12 SNPs for heart failure were proposed as instrumental variables at the genome-wide significance level (p < 5 × 10 −8). The random-effects inverse-variance weighted method was used for the main analyses. Results Genetic liability to MDD was significantly associated with type 2 diabetes and CAD at the Bonferroni-corrected significance level. The ORs of type 2 diabetes and CAD were respectively 1.26 (95% CI 1.10, 1.43; p = 6 × 10 −4) and 1.16 (95% CI 1.05, 1.29; p = 0.0047) per one-unit increase in log e odds of MDD. There was a suggestive association between MDD and heart failure (OR 1.11 [95% CI 1.01, 1.21]; p = 0.033). We found limited evidence supporting causal effects of cardiometabolic diseases on MDD risk in the reverse MR analyses. Conclusions/interpretation The present study strengthened the evidence that MDD is a potential risk factor for type 2 diabetes and CAD. Whether MDD is causally related to heart failure needs further study. Data availability All data included in this study were uploaded as supplements and are also publicly available through published GWASs and open GWAS datasets (UK Biobank, 23andMe and Psychiatric Genomics: https://datashare.is.ed.ac.uk/handle/

Background and Objectives:Previous studies have highlighted anti-diabetic drugs as repurposing candidates for Alzheimer´s disease (AD), but the disease-modifying effects are still unclear.METHODS:A two-sample Mendelian randomization (MR) study design was applied to examine the association between genetic variation in the targets of four anti-diabetic drug classes and AD risk. Genetic summary statistics for blood glucose were analyzed using UK Biobank data of 326,885 participants, while summary statistics for AD were retrieved from previous genome-wide association studies (GWAS) comprising 24,087 clinically diagnosed AD cases and 55,058 controls. Positive control analysis on type 2 diabetes (T2DM), insulin secretion, insulin resistance, and obesity-related traits was conducted to validate the selection of instrumental variables (IVs).RESULTS:In the positive control analysis, genetic variation in sulfonylurea targets was associated with higher insulin secretion, a lower risk of T2DM, and an increment in body mass index, waist circumference, and hip circumference, consistent with drug mechanistic actions and previous trial evidence. In the primary analysis, genetic variation in sulfonylurea targets was associated with a lower risk of AD (OR=0.38 per 1 mmol/L decrement in blood glucose, 95%CI=0.19-0.72, P=0.0034). These results for sulfonylureas were largely unchanged in the sensitivity analysis using a genetic variant, rs757110, that has been validated to modulate the target proteins of sulfonylureas (OR=0.35 per 1 mmol/L decrement in blood glucose, 95%CI=0.15-0.82, P=0.016). An association between genetic variations in the GLP-1 analogue target and a lower risk of AD was also observed (OR=0.32 per 1 mmol/L decrement in blood glucose, 95%CI=0.13-0.79, P=0.014). However, this result should be interpreted with caution because the positive control analyses for GLP-1 analogues did not comply with a weight-loss effect as shown in previous clinical trials. Results regarding other drug classes were inconclusive.DISCUSSION:Genetic variation in sulfonylurea targets was associated with a lower risk of AD, and future studies are warranted to clarify the underlying mechanistic pathways between sulfonylureas and AD.

Objective To investigate the association between obesity‐related traits and risk of rheumatoid arthritis (RA). Methods We conducted genetic correlation analysis and a 2‐sample Mendelian randomization (MR) study, using genome‐wide genetic data based on >850,000 individuals of European ancestry. Summary statistics were collected from the largest genome‐wide association study conducted to date for body mass index (BMI; n = 806,810), waist‐to‐hip ratio (WHR; n = 697,734), WHR adjusted for BMI (WHRadjBMI; n = 694,649), and RA (ncase = 14,361, ncontrol = 43,923). We conducted cross‐trait linkage disequilibrium score regression and ρ‐HESS analyses to quantify genetic correlation between pairs of traits (causal overlap). For each obesity‐related exposure, we utilized independent, genome‐wide significant single‐nucleotide polymorphisms (P < 5 × 10−9) as instruments to perform MR analysis (causal relationship). We interrogated the causal relationship both in the general population and in a sex‐specific manner and calculated odds ratios (ORs) and 95% confidence intervals (95% CIs). Sensitivity analyses were performed to validate MR model assumptions. Results Despite a negligible overall genetic correlation between the 3 obesity‐related traits and RA, we found significant local genetic correlations at several regions on chromosome 6 (positions 28–29M, 30–35M, and 50–52M), highlighting a shared genetic basis. We further observed an increased risk of RA per SD increment (4.8 kg/m2) in genetically predicted BMI (OR 1.22 [95% CI 1.09–1.37]). The effect was consistent across sensitivity analyses and comparable between sexes (OR 1.22 [95% CI 1.04–1.44] in male subjects and 1.19 [95% CI 1.04–1.36] in female subjects). However, we did not find evidence supporting a causal role of either WHR (OR 0.98 [95% CI 0.84–1.14]) or WHRadjBMI (OR 0.90 [95% CI 0.79–1.04]) in RA. Conclusion Genetically predicted BMI significantly increases RA risk. Future studies are needed to understand the biologic mechanisms underlying this link.

Supplemental Digital Content is Available in the Text. Mendelian randomization study supports that depression is a causal risk factor for headache and pain at neck/shoulder, back, and abdominal/stomach.