| Objectives:In recent years,a series of studies based on the microbiota-gut-brain axis(MGBA)theory have shown that gut microbiota and acute ischemic stroke(AIS)interact with each other.AIS can cause changes in gut microbiota,affect surrounding or distant tissues and organs,and cause serious damage to liver,kidney,lung,gastrointestinal tract,cardiovascular system,etc.In turn,changes in gut microbiota,may be a risk factor for AIS and determine stroke outcome.Studies have shown that the association between gut microbiota,and stroke is expected to provide a new perspective on the treatment and prognosis of AIS.Thus,in the present study,the gut microbiota of patients with AIS and healthy controls were sequenced by 16S r DNA amplifiers.Follow-up and assessment of the neurological prognosis of the 52 patients with AIS included in the study were performed 90 days after discharge,with m RS>2 as the outcome indicator(poor prognosis).Aim 1:To explore the difference between the AIS group and the healthy control group,and to clarify the characteristics of gut microbiota,in AIS patients;The potential of intestinal flora as biomarkers in the diagnosis of AIS was explored with the help of random forest model.2:Using receiver operating characteristic curve(ROC),significant gut microbiota was selected as biomarkers to explore the predictive value of gut microbiota for different prognostic outcomes of AIS patients.Methods:The study case group included patients diagnosed with AIS who were admitted to the Neurology Department from January 2022 to May 2022.The control group included healthy people who visited the physical examination center of our hospital during the same period.The general demographic data designed by ourselves were used to evaluate the demographic characteristics.The general clinical data and clinical blood test indexes were collected from the clinical electronic medical record system.All stool collection was done within 48 hours of AIS admission.The feces of patients with AIS and healthy controls were sequenced by 16S r DNA amplifiers.To analyze the composition,diversity and abundance of gut microbiota between AIS population and healthy people,and the diagnostic value of gut microbiota as biomarkers in this study.By screening the differential flora between the AIS group and the healthy control group,to explore the correlation between the differential flora and clinical blood indexes.At the same time,the patients with AIS were followed up 90 days after discharge and the prognosis of neurological function was evaluated.MRS>2 was used as the outcome index(poor prognosis group).Random forest model was used to explore the value of intestinal flora as biomarkers in predicting different prognostic outcomes of AIS patients.Results:(1)Eighty-nine subjects were included in this present investigation,including52 patients in AIS group and 37 healthy subjects.AIS group mean age was 63.15 years old,accounting for 78.85%of males and 21.15%of females.The BMI was(25.01±3.55)kg/m~2.Healthy controls had a mean age of 54.38 years old,with 72.97%males and 27.03%females.The BMI was(23.68±2.8)kg/m~2.Age,sex,body mass index,education,housing style,and mean monthly income have no statistically difference(p>0.05).(2)Theαdiversity analysis results of AIS and healthy control group showed that the Sobs,Ace and Shannon indexes in AIS group were significantly decreased,and the variation between the two teams was statistically significant difference(p<0.05),while the Simpson index in AIS group was significantly increased,and the difference was statistically significant(p=0.047).There was no statistical difference in Chao and Coverage between the two groups(p>0.05).weighted Uni Frac and unweighted Uni Frac for PCo A indicated that there were significant differences in the bacterial structure of AIS group and a Healthy comparison unit(p<0.05).(3)The species composition and difference analysis between the AIS group and the control group showed that there were differences in intestinal flora at the level of phylum,family and genus.A marked increase in the phylum of Bacillus mimicus in healthy subjects(AIS team 28.90%vs healthy comparison team 40.91%,p=0.0205).The relative abundance of Actinobacteria significantly elevated in those in the AIS group(2.85%in the AIS group vs 1.48%in the healthy control group,p=0.0133).At the family level,Ruminococcaceae increased significantly in AIS group.At the genus level,Bacteroides and Faecalibacterium showed a decreasing trend in AIS group,the comparison between the two groups was not statistically relevant(p>0.05).The religious abundance of Roseburia was obviously reduced in the AIS set and the relative abundance of Gemmiger was significantly higher.Differences were statistically significant(p<0.05).(4)LEf Se multistage discriminant analysis of species difference screened the different flora between the two groups.The results showed that a total of 40 species screened had a significant difference between the AIS group and the healthy control group(LDA>2,p<0.05).At the phylum level,Actinobacteria were significantly enriched in the AIS group.Bacteroidetes were significantly enriched in healthy control group.(5)The random forest model built between the AIS group and the healthy control group showed that intestinal flora as a biomarker has a certain potential value in the diagnosis of AIS,and the ROC area under the curve was 0.841(95%CI:0.734～0.947).Functional difference analysis showed that at Leve L1,there were significant differences in metabolism,tissue system,genetic information processing,and cellular process pathways between the AIS group and the healthy control group.Correlation analysis between different bacterial flora and clinical blood indexes showed that albumin was significantly negatively correlated with Alistipes,Barnesiella,Christensenella,Eisenbergiella and Oscillibacter.Serum uric acid was negatively correlated with Oscillibacter,and creatinine was positively correlated with Clostridium＿IV(all p<0.05).(6)In this study,52 patients with AIS were followed up 90days after the onset of the disease.Among them,43 patients in the good prognosis group(m RS Score≤2)accounted for 82.69%,and 9 patients in the poor prognosis group(m RS Score>2)accounted for 17.31%.Species difference analysis showed that at phylum level,Bacteroidetes and Candidatus＿Saccharibacteria showed a statistically meaningful difference between the two teams(p<0.05).The alpha diversity analysis of the various prognostication groups showed no statistically significant differences between the teams(p>0.05).β-diversity analysis showed that weighted Uni Frac algorithm shows remarkable variance in bacterial structure between the good prognosis group and the poor prognosis group(p<0.05),while unweighted Uni Frac algorithm presented no significant difference in bacterial structure between the two groups(p>0.05).At the level of genera between the good and bad prognosis groups,five dominant bacteria were selected by ROC curve as predictive values for different prognostic outcomes of AIS.The areas under the curve were Spirillum:AUC=0.822(95%CI:0.694～0.949),Clostridium＿Xl Vb:AUC=0.762(95%CI:0.597～0.927),Parabacteroides:AUC=0.713(95%CI:0.513～0.913),Scutellaria:AUC=0.680(95%CI:0.521～0.838),Akkermansia:AUC=0.669(95%CI:0.474～0.864).Conclusions:(1)Changes in the composition,structure,diversity and function of the Gut Microbiota in patients with AIS compared to healthy individuals.(2)Gut microbiota,as a biomarker,has certain predictive value for the diagnosis of AIS patients and different prognostic outcomes of AIS. |
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