Mendelian Randomization Highlights Gut Microbiota of Short-chain Fatty Acids' Producer as Protective Factor of Cerebrovascular Disease.

BACKGROUND: Recent research advancements have indicated a potential association between gut microbiota and cerebrovascular diseases, although the precise causative pathways and the directionality of this association remain to be fully elucidated. OBJECTIVE: This study utilized a bidirectional two-sample Mendelian Randomization (MR) methodology to explore the causal impact of gut microbiota compositions on the risk of cerebrovascular disease. METHODS: Genome-wide Association Study (GWAS) data pertaining to gut microbiota were obtained from the MiBioGen consortium. For Ischemic Stroke (IS), Transient Ischemic Attack (TIA), Vascular Dementia (VD), and Subarachnoid Hemorrhage (SAH), GWAS summary data were sourced from the FinnGen consortium, the IEU Open GWAS project, and the GWAS catalog, respectively. RESULTS: Our MR analyses identified that specific bacterial strains, notably those involved in the production of Short-chain Fatty Acids (SCFAs), including Barnesiella, Ruminococcus torques group, and Coprobacter, serve as protective factors against IS, TIA, and SAH. Linkage Disequilibrium Score Regression (LDSC) analysis corroborated a significant genetic correlation between these gut microbiota strains and various forms of cerebrovascular disease. In contrast, reverse MR analysis failed to establish a bidirectional causal relationship between genetically inferred gut microbiota profiles and these cerebrovascular conditions. CONCLUSION: This investigation has pinpointed particular strains of gut microbiota that play protective or detrimental roles in cerebrovascular disease pathogenesis. These findings offer valuable insights that could be pivotal for the clinical management, prevention, and treatment of cerebrovascular diseases.

Nomogram model for predicting the risk of post-stroke depression based on clinical characteristics and DNA methylation.

Objective: To construct a comprehensive nomogram model for predicting the risk of post-stroke depression (PSD) by using clinical data that are easily collected in the early stages, and the level of DNA methylation, so as to help doctors and patients prevent the occurrence of PSD as soon as possible. Methods: We continuously recruited 226 patients with a history of acute ischemic stroke and followed up for three months. Socio-demographic indicators, vascular-risk factors, and clinical data were collected at admission, and the outcome of depression was evaluated at the third month after stroke. At the same time, a DNA-methylation-related sequencing test was performed on the fasting peripheral blood of the hospitalized patients which was taken the morning after admission. Results: A total of 206 samples were randomly divided into training dataset and validation set according to the ratio of 7:3. We screened 24 potentially-predictive factors by Univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression analysis, and 10 of the factors were found to have predictive ability in the training set. The PSD nomogram model was established based on seven significant variables in multivariate logistic regression. The consistency statistic (C-index) was as high as 0.937, and the area under curve (AUC) in the ROC analysis was 0.933. Replication analysis results in the validation set suggest the C-index was 0.953 and AUC was 0.926. This shows that the model has excellent calibration and differentiating abilities. Conclusion: Gender, Rankin score, history of hyperlipidemia, time from onset to hospitalization, location of stroke, National Institutes of Health Stroke scale (NIHSS) score, and the methylation level of the cg02550950 site are all related to the occurrence of PSD. Using this information, we developed a prediction model based on methylation characteristics.

Associations of vitamin D-related single nucleotide polymorphisms with post-stroke depression among ischemic stroke population.

Objective: To investigate the relationship between single nucleotide polymorphisms (SNPs) related to vitamin D (VitD) metabolism and post-stroke depression (PSD) in patients with ischemic stroke. Methods: A total of 210 patients with ischemic stroke were enrolled at the Department of Neurology in Xiangya Hospital, Central South University, from July 2019 to August 2021. SNPs in the VitD metabolic pathway (VDR, CYP2R1, CYP24A1, and CYP27B1) were genotyped using the SNPscan™ multiplex SNP typing kit. Demographic and clinical data were collected using a standardized questionnaire. Multiple genetic models including dominant, recessive, and over-dominant models were utilized to analyze the associations between SNPs and PSD. Results: In the dominant, recessive, and over-dominant models, no significant association was observed between the selected SNPs in the CYP24A1 and CYP2R1 genes and PSD. However, univariate and multivariate logistic regression analysis revealed that the CYP27B1 rs10877012 G/G genotype was associated with a decreased risk of PSD (OR: 0.41, 95% CI: 0.18-0.92, p = 0.030 and OR: 0.42, 95% CI: 0.18-0.98, p = 0.040, respectively). Furthermore, haplotype association analysis indicated that rs11568820-rs1544410-rs2228570-rs7975232-rs731236 CCGAA haplotype in the VDR gene was associated with a reduced risk of PSD (OR: 0.14, 95% CI: 0.03-0.65, p = 0.010), whereas no significant association was observed between haplotypes in the CYP2R1 and CYP24A1 genes and PSD. Conclusion: Our findings suggest that the polymorphisms of VitD metabolic pathway genes VDR and CYP27B1 may be associated with PSD in patients with ischemic stroke.

The role of indoleamine 2,3-dioxygenase 1 in early-onset post-stroke depression.

Background: The immune-inflammatory response has been widely considered to be involved in the pathogenesis of post-stroke depression (PSD), but there is ambiguity about the mechanism underlying such association. Methods: According to Diagnostic and Statistical Manual of Mental Disorders (5th edition), depressive symptoms were assessed at 2 weeks after stroke onset. 15 single nucleotide polymorphisms (SNPs) in genes of indoleamine 2,3-dioxygenase (IDO, including IDO1 and IDO2) and its inducers (including pro-inflammatory cytokines interferon [IFN]-γ, tumor necrosis factor [TNF]-α, interleukin [IL]-1ß, IL-2 and IL-6) were genotyped using SNPscan™ technology, and serum IDO1 levels were detected by double-antibody sandwich enzyme-linked immune-sorbent assay. Results: Fifty-nine patients (31.72%) were diagnosed with depression at 2 weeks after stroke onset (early-onset PSD). The IDO1 rs9657182 T/T genotype was independently associated with early-onset PSD (adjusted odds ratio [OR] = 3.008, 95% confidence interval [CI] 1.157-7.822, p = 0.024) and the frequency of rs9657182 T allele was significantly higher in patients with PSD than that in patients with non-PSD (χ2 = 4.355, p = 0.037), but these results did not reach the Bonferroni significance threshold (p > 0.003). Serum IDO1 levels were also independently linked to early-onset PSD (adjusted OR = 1.071, 95% CI 1.002-1.145, p = 0.044) and patients with PSD had higher serum IDO1 levels than patients with non-PSD in the presence of the rs9657182 T allele but not homozygous C allele (t = -2.046, p = 0.043). Stroke patients with the TNF-α rs361525 G/G genotype had higher serum IDO1 levels compared to those with the G/A genotype (Z = -2.451, p = 0.014). Conclusions: Our findings provided evidence that IDO1 gene polymorphisms and protein levels were involved in the development of early-onset PSD and TNF-α polymorphism was associated with IDO1 levels, supporting that IDO1 which underlie strongly regulation by cytokines may be a specific pathway for the involvement of immune-inflammatory mechanism in the pathophysiology of PSD.

Establishment and verification of a nomogram model for predicting the risk of post-stroke depression.

Objective: The purpose of this study was to establish a nomogram predictive model of clinical risk factors for post-stroke depression (PSD). Patients and Methods: We used the data of 202 stroke patients collected from Xuanwu Hospital from October 2018 to September 2020 as training data to develop a predictive model. Nineteen clinical factors were selected to evaluate their risk. Minimum absolute contraction and selection operator (LASSO, least absolute shrinkage and selection operator) regression were used to select the best patient attributes, and seven predictive factors with predictive ability were selected, and then multi-factor logistic regression analysis was carried out to determine six predictive factors and establish a nomogram prediction model. The C-index, calibration chart, and decision curve analyses were used to evaluate the predictive ability, accuracy, and clinical practicability of the prediction model. We then used the data of 156 stroke patients collected by Xiangya Hospital from June 2019 to September 2020 for external verification. Results: The selected predictors including work style, number of children, time from onset to hospitalization, history of hyperlipidemia, stroke area, and the National Institutes of Health Stroke Scale (NIHSS) score. The model showed good prediction ability and a C index of 0.773 (95% confidence interval: [0.696-0.850]). It reached a high C-index value of 0.71 in bootstrap verification, and its C index was observed to be as high as 0.702 (95% confidence interval: [0.616-0.788]) in external verification. Decision curve analyses further showed that the nomogram of post-stroke depression has high clinical usefulness when the threshold probability was 6%. Conclusion: This novel nomogram, which combines patients' work style, number of children, time from onset to hospitalization, history of hyperlipidemia, stroke area, and NIHSS score, can help clinicians to assess the risk of depression in patients with acute stroke much earlier in the timeline of the disease, and to implement early intervention treatment so as to reduce the incidence of PSD.

Tetra-color superresolution microscopy based on excitation spectral demixing.

Multicolor imaging allows protein colocalizations and organelle interactions to be studied in biological research, which is especially important for single-molecule localization microscopy (SMLM). Here, we propose a multicolor method called excitation-resolved stochastic optical reconstruction microscopy (ExR-STORM). The method, which is based on the excitation spectrum of fluorescent dyes, successfully separated four spectrally very close far-red organic fluorophores utilizing three excitation lasers with cross-talk of less than 3%. Dyes that are only 5 nm apart in the emission spectrum were resolved, resulting in negligible chromatic aberrations. This method was extended to three-dimensional (3D) imaging by combining the astigmatic method, providing a powerful tool for resolving 3D morphologies at the nanoscale.

Association of homocysteine and polymorphism of methylenetetrahydrofolate reductase with early-onset post stroke depression.

Background: Homocysteine (Hcy) has been indicated to be involved in pathophysiology of post stroke depression (PSD). There is a lack of research to study the relationship between Hcy metabolism genes and PSD. Our study aims to investigate the relationship among Hcy metabolism genes, Hcy, and early-onset PSD. Materials and methods: We recruited 212 patients with stroke and collected their peripheral blood sample, clinical data, and laboratory test on admission. 12 single nucleotide polymorphisms (SNPs) in methylenetetrahydrofolate reductase (MTHFR), methionine synthase reductase (MTRR), and methionine synthase (MTR) genes were genotyped by high-resolution melt analysis. PSD was diagnosed by DSM-V at 2 weeks after stroke. Binary logistic regression and haplotype analysis were used to examine the association between Hcy metabolism genes and PSD. Mediation analysis was performed to clarify whether the SNPs exerted their effect on PSD by affecting the Hcy level. Results: 81 patients were diagnosed with PSD, and the incidence rate was 38.2%. Hcy level in PSD group was significantly higher than it in non-PSD group (p = 0.019). MTHFR rs1801133 AA genotype an A allele were associated with an elevated risk of PSD after adjustment for some confounding factors (OR = 4.021, 95% CI: 1.459∼11.080, p = 0.007 for AA genotype; OR = 1.808, 95% CI: 1.172∼2.788, p = 0.007 for A allele). Furthermore, the effect of MTHFR rs1801133 AA genotype on PSD was mediated by Hcy (OR = 1.569, 95% CI: 0.013∼3.350, p < 0.05). Conclusion: MTHFR rs1801133 and Hcy were associated with PSD, and MTHFR rs1801133 may exert an effect on PSD via mediating Hcy level. This offers a new perspective for treating PSD and understanding the mechanism of PSD.

The potential risk factors of early-onset post-stroke depression from immuno-inflammatory perspective.

Background: Mounting evidence strongly uncovered that peripheral immuno-inflammatory response induced by acute stroke is associated with the appearance of post-stroke depression (PSD), but the mechanism remains unclear. Methods: 103 stroke patients were assessed at 2 weeks after onset using Diagnostic and Statistical Manual of Mental Disorders, 5th edition and then divided into PSD and non-PSD groups. Polymorphisms of inflammatory molecules (interleukin [IL]-1ß, IL-6, IL-10, IL-18, tumor necrosis factor-α [TNF-α], interferon-γ [IFN-γ] and C-reactive protein [CRP]), complete blood count parameters, splenic attenuation (SA) and splenic volume (SV) on unenhanced chest computed tomography, demographic and other clinical characteristics were obtained. Binary logistic regression model was used to analyze the associations between inflammation-related factors and the occurrence of PSD at 2 weeks after stroke. Results: 49 patients were diagnosed with PSD at 2 weeks after onset (early-onset PSD). The C/T genotypes of CRP rs2794520 and rs1205 were less in PSD group than non-PSD group (both adjusted odds ratio = 3.364; 95%CI: 1.039-10.898; p = 0.043). For CRP rs3091244, the frequency of G allele was higher (80.61% vs. 13.89%) while the frequency of A allele was lower (6.12% vs. 71.30%) in PSD patients than non-PSD patients (χ2 = 104.380; p<0.001). SA of PSD patients was lower than that of non-PSD patients in the presence of CRP rs2794520 C/T genotype and rs1205 C/T genotype (both t = 2.122; p = 0.039). Peripheral monocyte count was less in PSD group than non-PSD group (adjusted odds ratio = 0.057; 95%CI: 0.005-0.686; p = 0.024). Conclusions: CRP polymorphisms, SA based on CRP genotype, and peripheral monocytes are associated with the risk of early-onset PSD, suggesting peripheral immuno-inflammatory activities elicited by stroke in its aetiology.