Promising therapeutic targets for ischemic stroke identified from plasma and cerebrospinal fluid proteomes: a multicenter Mendelian randomization study.

BACKGROUND: Ischemic stroke (IS) is more common every year, the condition is serious, and have a poor prognosis. New, efficient, and safe therapeutic targets are desperately needed as early treatment especially prevention and reperfusion is the key to lowering the occurrence of poorer prognosis. Generally circulating proteins are attractive therapeutic targets, this study aims to identify potential pharmacological targets among plasma and cerebrospinal fluid (CSF) proteins for the prevention and treatment of IS using a multicenter Mendelian randomization (MR) approach. METHODS: First, the genetic instruments of 734 plasma and 151 CSF proteins were assessed for causative connections with IS from MEGASTROKE consortium by MR to identify prospective therapeutic targets. Then, for additional validation, plasma proteins from the deCODE consortium and the Fenland consortium, as well as IS GWAS data from the FinnGen cohort, the ISGC consortium and UK biobank, were employed. A thorough evaluation of the aforementioned possible pharmacological targets was carried out using meta-analysis. The robustness of MR results was then confirmed through sensitivity analysis using several techniques, such as bidirectional MR analysis, Steiger filtering, and Bayesian colocalization. Finally, methods like Protein-Protein Interaction (PPI) Networking were utilized to investigate the relationship between putative drug targets and therapeutic agents. RESULTS: The authors discovered three proteins that may function as promising therapeutic targets for IS and meet the Bonferroni correction ( P <0.05/885=5.65×10 -5 ). Prekallikrein (OR=0.41, 95% CI: 0.27-0.63, P =3.61×10 -5 ), a protein found in CSF, has a 10-fold protective impact in IS, while the plasma proteins SWAP70 (OR=0.85, 95% CI: 0.80-0.91, P =1.64×10 -6 ) and MMP-12 (OR=0.92, 95% CI: 0.89-0.95, P =4.49×10 -6 ) of each SD play a protective role in IS. Prekallikrein, MMP-12, SWAP70 was replicated in the FinnGen cohort and ISGC database. MMP-12 (OR=0.93, 95% CI: 0.91-0.94, P <0.001), SWAP70 (OR=0.92, 95% CI: 0.90-0.94, P <0.001), and prekallikrein (OR=0.53, 95% CI: 0.33-0.72, P <0.001) may all be viable targets for IS, according to the combined meta-analysis results. Additionally, no evidence of reverse causality was identified, and Bayesian colocalization revealed MMP-12 (PPH 4 =0.995), SWAP70 (PPH 4 =0.987), and prekallikrein (PPH 4 =0.894) shared the same variant with IS, supporting the robustness of the aforementioned causation. Prekallikrein and MMP-12 were associated with the target protein of the current treatment of IS. Among them, Lanadelumab, a new drug whose target protein is a prekallikrein, may be a promising new drug for the treatment of IS. CONCLUSION: The prekallikrein, MMP-12, and SWAP70 are causally associated with the risk of IS. Moreover, MMP-12 and prekallikrein may be treated as promising therapeutic targets for medical intervention of IS.

Potential preventive markers in the intracerebral hemorrhage process are revealed by serum untargeted metabolomics in mice using hypertensive cerebral microbleeds.

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.

Epidemiology of intracerebral hemorrhage: A systematic review and meta-analysis.

Background: Intracerebral 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. Method: Literature 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. Results: We 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. Conclusion: The 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.

A systematic review and meta-analysis expounding the relationship between methylene tetrahydrofolate reductase gene polymorphism and the risk of intracerebral hemorrhage among populations.

Background: The relationship between methylenetetrahydrofolate reductase (MTHFR) gene C677T and A1298C polymorphism with the risk of intracerebral hemorrhage (ICH) has remained to be controversial in recent years. This meta-analysis is aimed to confirm the association of these. Methods: Systematically searching the related studies from the PubMed, Embase, Cochrane Library, China national knowledge internet database from 1 January 1990 to 1 June 2022. The odd ratio (ORs) and 95% confidence interval (CIs) of gene-disease correlation in various gene models were calculated by fixed or random effect model of meta-analysis. We included 20 case-control studies in this meta-analysis with a total of 1,989 ICH patients and 4,032 health controls originated from Asian, Caucasian, and African populations. Results: The statistical analysis demonstrated the association of MTHFR C677T gene polymorphism with ICH in allele model [ORT VS. C = 1.20 (95%CI: 1.06-1.36)]; homozygote model [OR TT VS. CC = 1.50 (95%CI: 1.20-1.88)]; dominant model [OR CT+ TT VS. CC = 1.23 (95%CI: 1.03-1.48)] and recessive model [ORTT VS. CT+CC = 1.37 (95%CI: 1.17-1.60)]. Besides, we also found the relationship of MTHFR C677T gene polymorphism with Asian in four comparison model (ORT VS. C = 1.19.95%CI:1.09-1.37, ORTT VS. CC = 1.46.95%CI: 1.15-1.85, OR CT+ TT VS. CC = 1.25.95%CI: 1.01-1.54, ORTT VS. CT+CC = 1.34.95%CI: 1.54-1.17) and Caucasian in four comparison model (ORT VS. C = 1.90.95%CI: 1.22-2.97, ORTT VS. CC = 2.67.95%CI: 1.42-5.00, OR CT+ TT VS. CC = 1.56.95%CI: 1.05-2.32, ORTT VS. CT+CC = 2.25.95%CI: 1.46-4.00). But no statistically significant correlation between A1298C polymorphism and the occurrence of ICH was detected in four studies. Conclusion: MTHFR C677T gene polymorphism increases the risk of ICH in Asian and Caucasian populations but has no impact on the incidence in African communities. More importantly, the risk of ICH increases in TT genotype individuals in comparison to CT and CC genotype individuals in Asian and Caucasian populations.

Multi-omics reveals specific host metabolism-microbiome associations in intracerebral hemorrhage.

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.

Childhood Obesity and Risk of Stroke: A Mendelian Randomisation Analysis.

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.

Deciphering the Irregular Risk of Stroke Increased by Obesity Classes: A Stratified Mendelian Randomization Study.

Background: To investigate the relationship between different classes of obesity and stroke, we conducted a stratified Mendelian randomization (MR) study. Methods: The 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. Results: The 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). Conclusions: A 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.