Background: The causal relationship between childhood obesity and stroke remains unclear. Our objective was to elucidate the causal relationship between childhood obesity and the risk of stroke and its subtypes by performing Mendelian randomisation (MR) analyses.Methods: Genetic instruments for childhood obesity were obtained from a genome-wide association study (GWAS) of 13,848 European participants. Summary level data for stroke, intracerebral haemorrhage, ischaemic stroke (IS), and its subtypes were evaluated using the MEGASTROKE GWAS dataset, which included 446,696 European adults. Inverse-variance weighting, weighted-median analysis, MR-Egger regression, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR-Robust Adjusted Profile Score were applied in this MR analysis. The leave-one-out sensitivity test, MR-PRESSO Global test, and Cochran’s Q test were conducted to confirm the accuracy and robustness of our results.Results: Genetic evaluations revealed that childhood obesity was associated with a higher risk of stroke (OR = 1.04, 95%CI: 1.01–1.07, p = 0.005) and IS (OR = 1.05, 95%CI: 1.02–1.08, p = 0.003), but not with intracerebral haemorrhage (ICH, OR = 0.93, 95%CI: 0.80–1.09, p = 0.39). In the subtype analysis, childhood obesity was also associated with large artery stroke (LAS, OR = 1.12, 95%CI: 1.02–1.22, p = 0.016) but not with cardioembolic stroke (OR = 1.06, 95%CI: 0.96–1.18, p = 0.21) and small vessel stroke (OR = 1.06, 95%CI: 0.98–1.15, p = 0.17). These results were stable in the sensitivity analysis and remained significant after Bonferroni correction.Conclusion: Our study provides evidence that childhood obesity is associated with a higher risk of stroke, IS, and LAS. The prevention of stroke, especially IS and LAS, should be promoted in populations with childhood obesity.

BackgroundIntracerebral hemorrhage (ICH) is associated with high mortality and disability rates. This study aimed to investigate the relationship between sex, age, study year, risk factors, bleeding site, median year of study, and the incidence of ICH.MethodLiterature on the incidence of ICH published on 1 January 1980 and 1 January 2020, was systematically retrieved from PubMed and Embase databases. The random-effects model and subgroup analysis were used to explore the relationship between the incidence of ICH and different ages, sex, bleeding sites, and risk factors.ResultsWe summarized the epidemiological changes in ICH in the past 40 years according to 52 studies and found that the total incidence of ICH is 29.9 per 100,000 person-years (95% CI: 26.5–33.3), which has not decreased worldwide. The incidence of ICH in the Asian population is much higher than in other continents. In addition, the incidence of ICH increases with age and differs at the 85-year-old boundary. Men are more likely to develop ICH than women, and the basal ganglia region is the most common area for ICH. Of the 10 risk factors examined in this study, those with hypertension had the highest incidence of ICH, followed by those with excessive alcohol consumption and heart disease.ConclusionThe prevention and treatment of ICH still need to be improved continuously according to age, sex, risk factors, and other factors, and targeted and normative strategies should be gradually developed in the future.

Intracerebral hemorrhage (ICH) is the most devastating subtype of stroke, but effective prevention and treatment strategies are lacking. Recently, gut microbiome and its metabolitesis are considered to be an influencing factor of stroke. However, little is known about the effects of the gut microbiome on ICH and host metabolic activity. Therefore, we used 16S sequencing, macrogenomics sequencing and untargeted metabolomics to explore the differences in gut microbial-metabolome interactions between patients with intracerebral hemorrhage and healthy control populations. We found a significant decrease in the phylum of Firmicutes and a significant increase of Bacteroidetes in ICH patients. At the genus level, Streptococcus, Bifidobacterium, Akkermansia, and Lactobacillus were more abundant in ICH patients. Macrogenomic analysis revealed active glycosaminoglycan degradation, heme synthesis, galactose degradation, lipopolysaccharide core region synthesis, and beta-Lactam resistance in ICH patients. Serum untargeted metabolomic analysis combined with ROC curves showed that octanoylcarnitine, decanoylcarnitine, dodecanoylcarnitine, glyceric acid, pyruvic acid, aspartic acid, methylcysteine, pyroglutamic acid, 9E-tetradecenoic acid, N-Acetylneuraminic acid, and aconitic acid were the best markers for the diagnosis of ICH. Correlation analysis showed that microbiome enriched in the gut of ICH patients were significantly correlated with serum metabolites, revealing a close correlation between the gut microbiome of ICH patients and the host metabolome, and significant differences from the healthy population. microbiota-host co-metabolites including pyruvic acid and 9E-tetradecenoic acid is associated with the the National Institutes of Health Stroke Scale (NIHSS) scores. In conclusion, microbiome-related metabolites in ICH patients was associated with the severity of ICH, the microbiota-host co-metabolites may be a potential may be potential therapeutic targets.

BackgroundTo investigate the relationship between different classes of obesity and stroke, we conducted a stratified Mendelian randomization (MR) study.MethodsThe body mass index (BMI) data of 263,407 Europeans with three classes of obesity (obesity class I, 30 kg/m2 ≤ BMI < 35 kg/m2; obesity class II, 35 kg/m2 ≤ BMI < 40 kg/m2; obesity class III, 40 kg/m2 ≤ BMI) were extracted from the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Summary-level data of stroke and its subtypes [ischemic stroke (IS) and intracerebral hemorrhage (ICH)] were obtained from the genome-wide association study (GWAS) meta-analysis, which was performed by the MEGASTROKE consortium. MR methods were used to identify the causal relationships.ResultsThe MR analysis revealed that both obesity class I [odds ratio (OR) = 1.08, 95% CI: 1.05–1.12, p = 1.0 × 10-5] and obesity class II (OR = 1.06, 95% CI: 1.03–1.09, p = 1 × 10-4) were significantly positively related to IS, while obesity class III was not (OR = 1.01, 95% CI: 0.96–1.06, p = 0.65). In contrast to IS, there was no class of obesity associated with ICH risk. Further examination of the relationship between obesity classification and IS subtypes revealed that certain degrees of obesity were related to large artery stroke (LAS) (OR = 1.14, 95% CI: 1.04–1.24, p = 2.8 × 10-3 for class I; OR = 1.08, 95% CI: 1.01–1.16, p = 0.002 for class II) and cardioembolic stroke (CES) (OR = 1.11, 95% CI: 1.02–1.20, p = 0.02 for class I; OR = 1.08, 95% CI: 1.02–1.15, p = 0.007 for class II).ConclusionsA higher risk of IS, but not ICH, could be linked to obesity classes I and II. A strong association between LAS and CES and obesity was observed among all IS subtypes in the obese population.

Hypertensive cerebral microbleeds (HCMB) may be the early stage of hypertensive intracerebral hemorrhage (HICH), which is a serious threat to health due to its high mortality and disability rates. The early clinical symptoms of HCMB may not be significant. Moreover, it is difficult to achieve early diagnosis and intervention for targeted prevention of HICH. Although hypertension (HTN) is a predisposition for HCMB, it remains unclear whether there is any difference between hypertensive patients with or without HCMB. Therefore, we carried out liquid chromatography-mass spectrometry (LC-MS) to analyze early biomarkers for HCMB in mice with hypertension and to lay the foundation for early prevention of HICH in hypertensive patients. In total, 18 C57 male mice were randomly divided into the HCMB (n = 6), HTN (n = 6), and control groups (CON, n = 6). Hematoxylin-eosin and diaminobenzidine staining were used to assess the reliability of the model. The metabolite expression level and sample category stability were tested using the displacement test of orthogonal partial least squares discriminant analysis (OPLS-DA). Significant differences in metabolites were screened out using variable importance in the projection (VIP > 1), which were determined using the OPLS-DA model and the P-value of the t-test (P < 0.05) combined with the nonparametric rank-sum test. With an area under the curve (AUC) > 0.85 and a P-value of 0.05, the receiver operating characteristic curve (ROC) was used to further screen the distinct metabolites of HCMB. Compared with the HTN and CON groups, the HCMB group had significantly higher blood pressure and lower average body weight (P < 0.05). Through untargeted LC-MS analysis, 93 distinct metabolites were identified in the HCMB (P < 0.05, VIP > 1) group. Among these potential biomarkers, six significantly decreased and eight significantly increased differential metabolites were found. Meanwhile, we found that the HCMB group had statistically distinct arginine and purine metabolism pathways (P < 0.05), and citrulline may be the most significant possible biomarker of HCMB (AUC > 0.85, P < 0.05). All of these potential biomarkers may serve as early biomarkers for HICH in hypertension.