Predictive microbial feature analysis in patients with depression after acute ischemic stroke.

Introduction: Post-stroke depression (PSD) is the most common emotional problem following a stroke, which requires early diagnosis to improve the prognosis. Gut microbiota plays important role in the pathological mechanisms of acute ischemic stroke and influences the outcome of patients. However, the relationship between PSD and gut microbiota remains unknown. Here, we explored whether the microbial signatures of gut microbiota in the patients with stroke could be an appropriate predictor of PSD. Methods: Fecal samples were collected from 232 acute ischemic stroke patients and determined by 16s rRNA sequencing. All patients then received 17-Hamilton Depression Rating Scale (HAMD-17) assessment 3 months after discharge, and were further divided into PSD group and non-PSD group. We analyzed the differences of gut microbiota between these groups. To identify gut microbial biomarkers, we then established microbial biomarker model. Results: Our results showed that the composition of gut microbiota in the PSD patients differed significantly from that in non-PSD patients. The genus Streptococcus, Akkermansia, and Barnesiella were significantly increased in PSD patients compared to non-PSD, while the genus Escherichia-Shigella, Butyricicoccus, and Holdemanella were significantly decreased. Correlation analyses displayed that Akkermansia, Barnesiella, and Pyramidobacter were positively correlated with HAMD score, while Holdemanella was negatively correlated with HAMD score. The optimal microbial markers were determined, and the combination achieved an area under the curve (AUC) value of 0.705 to distinguish PSD from non-PSD. Conclusions: Our findings suggest that PSD patients had distinct gut microbiota compared to non-PSD patients, and explore the potential of microbial markers, which might provide clinical decision-making in PSD.

Gut microbiota signature as predictors of adverse outcomes after acute ischemic stroke in patients with hyperlipidemia.

Introduction: The alterations of gut microbiota have been associated with multiple diseases. However, the relationship between gut microbiota and adverse outcomes of hyperlipidemic stroke patients remains unclear. Here we determined the gut microbial signature to predict the poor outcome of acute ischemic stroke (AIS) with hyperlipidemia (POAH). Methods: Fecal samples from hyperlipidemic stroke patients were collected, which further analyzed by 16s rRNA gene sequencing. The diversity, community composition and differential gut microbiota were evaluated. The adverse outcomes were determined by modified Rankin Scale (mRS) scores at 3 months after admission. The diagnostic performance of microbial characteristics in predicting adverse outcomes was assessed by receiver operating characteristic (ROC) curves. Results: Our results showed that the composition and structure of gut microbiota between POAH patients and good outcome of AIS with hyperlipidemia (GOAH) patients were different. The characteristic gut microbiota of POAH patients was that the relative abundance of Enterococcaceae and Enterococcus were increased, while the relative abundance of Lachnospiraceae, Faecalibacterium, Rothia and Butyricicoccus were decreased. Moreover, the characteristic gut microbiota were correlated with many clinical parameters, such as National Institutes of Health Stroke Scale (NIHSS) score, mean arterial pressure, and history of cerebrovascular disease. Moreover, the ROC models based on the characteristic microbiota or the combination of characteristic microbiota with independent risk factors could distinguish POAH patients and GOAH patients (area under curve is 0.694 and 0.971 respectively). Conclusions: These findings revealed the microbial characteristics of POAH, which highlighted the predictive capability of characteristic microbiota in POAH patients.

Gut Microbiome Signatures Are Biomarkers for Cognitive Impairment in Patients With Ischemic Stroke.

Post-stroke cognitive impairment (PSCI) is a common neuropsychiatric complication of stroke. Mounting evidence has demonstrated a connection between gut microbiota (GM) and neuropsychiatric disease. Our previous study revealed the changes in the GM in a mouse model of vascular dementia. However, the characteristic GM of PSCI remains unclear. This study aimed to characterize the GM of PSCI and explored the potential of GM as PSCI biomarkers. A total of 93 patients with ischemic stroke were enrolled in this study. The patients were divided into two groups according to their MoCA scores 3 months after stroke onset. Clinical data and biological variables were recorded. GM composition was analyzed using 16S ribosomal RNA sequencing, and the characteristic GM was identified by linear discriminant analysis Effect Size (Lefse). Our results showed that Proteobacteria was highly increased in the PSCI group compared with the post-stroke non-cognitive impairment (PSNCI) group, the similar alterations were also observed at the class, order, family, and genus levels of Proteobacteria. After age adjustments, the abundance of Firmicutes, and its members, including Clostridia, Clostridiales, Lachnospiraceae, and Lachnospiraceae_other, were significantly decreased in the age-matched PSCI group compared with the PSNCI group. Besides, the GM was closely associated with MoCA scores and the risk factors for PSCI, including higher baseline National Institute of Health Stroke Scale score, higher homocysteine (Hcy) level, higher prevalence of stroke recurrence, leukoaraiosis, and brain atrophy. The KEGG results showed the enriched module for folding, sorting and degradation (chaperones and folding catalysts) and the decreased modules related to metabolisms of cofactors and vitamins, amino acid, and lipid in PSCI patients. A significant correlation was observed between PSCI and the abundance of Enterobacteriaceae after adjustments (P = 0.035). Moreover, the receiver operating characteristic (ROC) models based on the characteristic GM and Enterobacteriaceae could distinguish PSCI patients from PSNCI patients [area under the curve (AUC) = 0.840, 0.629, respectively]. Our findings demonstrated that the characteristic GM, especially Enterobacteriaceae, might have the ability to predict PSCI in post-stroke patients, which are expected to be used as clinical biomarkers of PSCI.

Structural Change of Gut Microbiota in Patients with Post-Stroke Comorbid Cognitive Impairment and Depression and Its Correlation with Clinical Features.

BACKGROUND: Post-stroke comorbid cognitive impairment and depression (PSCCID) is a severe neuropsychiatric complication after acute stroke. Gut microbiota dysbiosis is associated with many psychiatric disorders. Alterations in the composition of gut microbiota may serve as a critical role in patients with PSCCID. OBJECTIVE: We aimed to characterize the microbial profiles of patients with PSCCID. METHOD: A total of 175 stroke patients were recruited in the study. The composition of gut bacterial communities of patients was determined by 16S ribosomal RNA Miseq sequencing, and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States was used to demonstrate the functional alterations of gut microbiota. We further identified the characteristic gut microbiota of PSCCID using linear discriminant analysis effect size. RESULTS: Patients with PSCCID exhibited an increased abundance of Proteobacteria, including Gammaproteobacteria, Enterobacteriales, and Enterobacteriaceae, and a decreased abundance of several short-chain fatty acids-producing bacteria compared with non-PSCCID patients. The abundance of Gammaproteobacteria and Enterobacteriaceae showed negative correlations with the MoCA score. Moreover, the Kyoto Encyclopedia of Genes and Genomes results demonstrated the enriched orthologs of glycan biosynthesis and metabolism and decreased orthologs of amino acid metabolism in PSCCID patients. Importantly, the characteristic gut microbiota was identified and achieved an area under the curve of 0.847 between the two groups. CONCLUSION: In this study, we characterized the gut microbiota of PSCCID patients, and revealed the correlations of the altered gut microbiota with clinical parameters, which took a further step towards non-invasive diagnostic biomarkers for PSCCID from fecal samples.

The association between serum uric acid level and the risk of cognitive impairment after ischemic stroke.

Post-stroke cognitive impairment (PSCI) is a severe complication of stroke. Predicting PSCI is difficult because some risk factors for stroke, such as blood glucose level and blood pressure, are affected by many other elements. Although recent studies have shown that high serum uric acid (UA) levels are associated with cognitive dysfunction and may be a risk factor for PSCI, its impact remains unclear. Accordingly, the present study aimed to explore the association between serum UA level and PSCI. In total, 274 patients who experienced acute cerebral infarction, confirmed between January 2016 and December 2018, were enrolled. Baseline data and biological indicators were recorded. According to the Montreal Cognitive Assessment (MoCA) scores, patients were divided into two groups: PSCI and non-PSCI. Logistic regression analysis was used to determine possible risk factors for PSCI. Results demonstrated that serum UA levels were significantly higher in the PSCI group than in the non-PSCI group. Multivariable logistic analysis revealed that age, years of education, and UA level were independent risk factors for PSCI. PSCI patients were subdivided according to serum UA level: high and low. Hypertension history and homocysteine (Hcy) levels differed significantly between the high and low UA level groups. Further analysis revealed that a history of hypertension and Hcy demonstrated a certain correlation (r = 0.163, 0.162; P < 0.05), suggesting that serum UA level was an independent risk factor for PSCI. These findings indicate that serum UA level was correlated with PSCI in post-stroke patients and is anticipated to be used in clinical practice to reduce the incidence of PSCI.