Background: Epidemiological studies have reported discrepant findings on the relationship between education level and outcomes after stroke. We aimed to prospectively investigate the relationship between education level and mortality, recurrent stroke, and cardiovascular events in Chinese patients with ischemic stroke. Methods and Results: We included 3861 participants from the China Antihypertensive Trial in Acute Ischemic Stroke. Education level was categorized as illiteracy, primary school, middle school, and college. Study outcomes were all‐cause mortality, stroke‐specific mortality, recurrent stroke, and cardiovascular events within 2 years after ischemic stroke. A meta‐analysis was conducted to incorporate the results of the current study and previous other studies on the association of education level with outcomes after stroke. Within 2 years after ischemic stroke, there were 327 (8.5%) all‐cause deaths, 264 (6.8%) stroke‐specific deaths, 303 (7.9%) recurrent strokes, and 364 (9.4%) cardiovascular events, respectively. The Kaplan–Meier curves showed that patients with the lowest education level had the highest cumulative incidence rates of all‐cause mortality, stroke‐specific mortality, and cardiovascular events (log‐rank P ≤0.01). After adjusted for covariates, hazard ratios and 95% CIs of illiteracy versus college education were 2.79 (1.32–5.87) for all‐cause mortality, 3.68 (1.51–8.98) for stroke‐specific mortality, 2.82 (1.20–6.60) for recurrent stroke, and 3.46 (1.50–7.95) for cardiovascular events. The meta‐analysis confirmed the significant association between education status and mortality after stroke (pooled relative risk for lowest versus highest education level, 1.24 [95% CI, 1.05–1.46]). Conclusions: Low education level was significantly associated with increased risk of mortality, recurrent stroke, and cardiovascular events after ischemic stroke, independently of established risk factors. Registration: URL: https://www.clini​caltr​ials.gov ; Unique identifier: NCT01840072.

Aims: Sleep disorders are associated with an increased risk of cardiometabolic diseases in observational studies, but the causality remains unclear. In this study, we leveraged two-sample Mendelian randomization (MR) analyses to assess the causal associations of self-reported daytime napping, daytime sleepiness, and other sleep phenotypes with cardiometabolic diseases including ischaemic stroke (IS), coronary artery disease (CAD), heart failure (HF), and Type 2 diabetes mellitus (T2DM).Methods and results: We selected genetic variants as instrumental variables for self-reported daytime napping, daytime sleepiness, morning person, insomnia, short sleep duration, and long sleep duration from European-descent genome-wide association studies (GWASs). Summary statistics for cardiometabolic diseases originated from four different GWASs with a total of 2 500 086 participants. We used the inverse-variance weighted method to explore the role of self-reported sleep phenotypes on the aetiology of cardiometabolic diseases in the main analyses, followed by several sensitivity analyses for robustness validation. Genetically predicted self-reported daytime napping [T2DM: OR, 1.56 (95% confidence interval, 1.21–2.02)], insomnia [IS: OR, 1.07 (1.04–1.11)]; CAD: OR, 1.13 (1.08–1.17); HF: OR, 1.10 (1.07–1.14); T2DM: OR, 1.16 (1.11–1.22); and short sleep duration [CAD: OR, 1.37 (1.21–1.55)] were causally associated with an elevated risk of cardiometabolic diseases. Moreover, genetically determined self-reported daytime sleepiness [CAD: OR, 2.05 (1.18–3.57); HF: OR, 1.82 (1.15–2.87)] and morning person [HF: 1.06 OR, (1.01–1.11)] had potential detrimental effect on cardiometabolic risks.Conclusion: Self-reported daytime napping, insomnia, and short sleep duration had causal roles in the development of cardiometabolic diseases, while self-reported daytime sleepiness and morning person was the potential risk factor for cardiometabolic diseases.

Background and Purpose: Complement C3 has been implicated in inflammation and ischemia/reperfusion injury, but its impact on the prognosis of ischemic stroke remains unclear. Aim of this study was to prospectively investigate the association between serum complement C3 and adverse clinical outcomes after ischemic stroke. Methods: We measured serum complement C3 levels for 3474 patients with ischemic stroke in 26 participating hospitals and collected data of clinical outcomes at 3 months after ischemic stroke. The primary outcome was composite outcome of death and major disability (modified Rankin Scale score ≥3) at 3 months after stroke onset and secondary outcomes included major disability, death, and vascular events. Results: During 3 months of follow-up, 866 participants (25.4%) developed primary outcome. After multivariate adjustment, elevated serum complement C3 levels were associated with increased risk of primary outcome (odds ratio, 1.30 [95% CI, 1.02–1.65]; P _trend =0.038) when 2 extreme tertiles were compared. Each SD increase of log-transformed complement C3 was associated with 13% (95% CI, 2%–25%) increased risk of primary outcome. Multivariable-adjusted spline regression model showed a linear relationship between serum complement C3 and the risk of primary outcome ( P _linearity =0.022). Addition of serum complement C3 to conventional risk factors significantly improved the risk prediction of primary outcome (net reclassification index: 8.87%, P =0.028; integrated discrimination index: 0.19%, P =0.029). Conclusions: High serum complement C3 levels at baseline were associated with increased risks of adverse clinical outcomes at 3 months after ischemic stroke, suggesting that serum complement C3 may be a valuable prognostic biomarker for ischemic stroke.

Previous study found that estimated glucose disposal rate (eGDR) was significantly associated with cardiovascular disease (CVD). However, little is known about the change in eGDR over time and its association with the development of CVD. The aim of this study was to investigate the association of change in eGDR with CVD risk. This study used data of two prospective cohorts: UK Biobank and China Health and Retirement Longitudinal Study (CHARLS) with two measurements of eGDR. Changes in the eGDR were classified using K‑means clustering analysis, and the cumulative eGDR was also calculated. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) after adjusting for potential confounders. A total of 11,682 individuals from the UK Biobank, and 4,974 individuals from the CHARLS were included. The median follow-up periods were 9.7 years in the UK Biobank and 3.0 years in the CHARLS. Compared with persistently high level of eGDR (class 1), individuals with low level increasing (class 3) and persistently low level of eGDR (class 4) showed elevated risks of incident CVD in both UK Biobank (HR = 2.79, 95% 2.15–3.62 for class 3; HR = 3.19, 95% 2.50–4.08 for class 4) and CHARLS (HR = 1.66, 95% 1.29–2.13 for class 3; HR = 1.69, 95% 1.34–2.14 for class 4). In addition, lower level of cumulative eGDR were associated with elevated risks of incident CVD. The dose-response curve between cumulative eGDR and CVD risk showed a negative linear relationship. Different changes in eGDR level are associated with different risks of incident CVD. Dynamic monitoring of eGDR level is of significant importance for the CVD prevention and treatment.

Background: Preclinical and epidemiological studies indicate a potential chemopreventive role of low-density lipoprotein cholesterol (LDL-C) -lowering drugs in the risks of breast cancer and prostate cancer, but the causality remains unclear. We aimed to evaluate the association of genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, Niemann-Pick C1-Like 1 (NPC1L1), and proprotein convertase subtilisin/kexin type 9 (PCSK9) with risks of breast cancer and prostate cancer using a two-sample Mendelian randomization (MR) method. Methods: Single-nucleotide polymorphisms (SNPs) in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study (GWAS) meta-analysis from the Global Lipids Genetics Consortium (GLGC; up to 188,577 European individuals) were used to proxy inhibition of HMG-CoA reductase, NPC1L1, and PCSK9. Summary statistics with outcomes were obtained from a GWAS meta-analysis of the Breast Cancer Association Consortium (BCAC; 228,951 European females) and a Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL; 140,254 European males) consortium. SNPs were combined into multiallelic models and MR estimates representing lifelong inhibition of targets were generated using the inverse-variance weighted method. Results: Genetically proxied inhibition of HMG-CoA reductase (OR: 0.84; 95% CI 0.74–0.95; P = 0.005) and NPC1L1 (OR: 0.72; 95% CI 0.58–0.90; P = 0.005) equivalent to a 1-mmol/L (38.7 mg/dL) reduction in LDL-C was associated with reduced breast cancer risk. There were no significant associations of genetically proxied inhibition of PCSK9 with breast cancer. In contrast, genetically proxied inhibition of PCSK9 (OR: 0.81; 95% CI 0.73–0.90; P < 0.001) but not HMG-CoA reductase and NPC1L1 was negatively associated with prostate cancer. In the secondary analysis, genetically proxied inhibition of HMG-CoA reductase (OR: 0.82; 95% CI 0.71–0.95; P = 0.008) and NPC1L1 (OR: 0.66; 95% CI 0.50–0.86; P = 0.002) was associated with estrogen receptor-positive breast cancer, whereas there was no association of HMG-CoA reductase and NPC1L1 with estrogen receptor-negative breast cancer. Conclusions: Genetically proxied inhibition of HMG-CoA reductase and NPC1L1 was significantly associated with lower odds of breast cancer, while genetically proxied inhibition of PCSK9 was associated with reduced risk of prostate cancer. Further randomized controlled trials are needed to confirm the respective roles of these LDL-C-lowering drugs in breast cancer and prostate cancer.

To identify promising drug targets for psychiatric disorders, we applied Mendelian randomization (MR) design to systematically screen blood metabolome for potential mediators of psychiatric disorders and further predict target-mediated side effects. We selected 92 unique blood metabolites from 3 metabolome genome-wide association studies (GWASs) with totally 147 827 participants. Summary statistics for bipolar disorder (BIP), attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), schizophrenia (SCZ), panic disorder (PD), autistic spectrum disorder (ASD), and anorexia nervosa (AN) originated from the Psychiatric Genomics Consortium, involving 1 143 340 participants. Mendelian randomization (MR) analyses were conducted to estimate associations of blood metabolites with psychiatric disorders. Phenome-wide MR analysis was further performed to predict side effects mediated by metabolite-targeted interventions. Eight metabolites were identified associated with psychiatric disorders, including five established mediators: N-acetylornithine (BIP: OR, 0.72 [95% CI, 0.66–0.79]; SCZ: OR, 0.74 [0.64–0.84]), glycine (BIP: OR, 0.62 [0.50–0.77]), docosahexaenoic acid (MDD: OR, 0.96 [0.94–0.97]), 3-Hydroxybutyrate (MDD: OR, 1.14 [1.08–1.21]), butyrylcarnitine (SCZ: OR, 1.22 [1.12–1.32]); and three novel mediators: 1-arachidonoylglycerophosphocholine (1-arachidonoyl-GPC)(BIP: OR, 0.31 [0.23–0.41]), glycoproteins (BIP: OR, 0.94 [0.92–0.97]), sphingomyelins (AN: OR, 1.12 [1.06–1.19]). Phenome-wide MR analysis showed that all identified metabolites except for N-acetylornithine and 3-Hydroxybutyrate had additional effects on nonpsychiatric diseases, while glycine, 3-Hydroxybutyrate, N-acetylornithine, and butyrylcarnitine had no adverse side effects. This MR study identified five established and three novel mediators for psychiatric disorders. N-acetylornithine, glycine, 3-Hydroxybutyrate, and butyrylcarnitine might be promising targets against psychiatric disorders with no predicted adverse side effects.