Study On The Syndrome Characteristics And Biological Markers Of Type 2 Diabetes Associated With Multimodal Blood Glucose Indexe

Objective:Based on the pathogenesis theory of "heat damage Qi Yin" in Type 2 Diabetes Mellitus（T2DM）,this study explores the correlation between T2DM syndrome elements and multi-mode blood glucose indexes.And then explores the clinical characterization and biological markers of the main related syndrome elements（phlegm-heat syndrome）,the details are as follows:1 The correlation between T2DM syndrome elements and multi-mode blood glucose indexes was investigated based on propensity score matching（PSM）and inverse probability treatment weight（IPTW）.2 Through cross-sectional investigation,clinical characterization of phlegm-heat syndrome,which is related to multi-mode blood glucose index,was explored.3 Biological markers of phlegm-heat syndrome of T2DM were explored from the perspective of intestinal flora and serum metabolites.Methods:1 In this study,T2DM cases were screened by hospital information system.Then we extracted infarmation,including general condition,medical history,TCM diagnosis information,syndrome element diagnosis,multi-mode blood glucose index The multi-mode blood glucose index including Time In Rang（TIR）,Time Below Range（TBR）,Time Above Range（TAR）,Standard Deviation of Blood Glucose,（SDBG）、Postprandial Glucose Excursion（PPGE）,Largest Amplitudeof Glycemic Excursions（LAGE）,Glycosylated Hemoglobin(HbA1c.And the confounding factors were controlled by PSM and IPTW,and the correlation between syndrome elements and multi-mode blood glucose index was analyzed statistically by generalized linear model.2 The clinical characteristics of phlegm-heat syndrome were investigated by crosssectional investigation.DS01-G tongue diagnostic instrument,MyEyeD-10 white-eye camera and scale were used to collect the informationg,including general conditions,medical history,TCM symptoms,multi-mode blood glucose index,laboratory tests,objective tongue diagnosis information and objective eye diagnosis information of the T2DMpatients with/without phlegm-heat syndrome.Chi-square test,T-test of two independent samples and non-parametric test were used to compare the two groups.logistic regression was used for multivariate analysis and establishing prediction model.Receiver operating characteristic curve（ROC）was used to test the model.3 Patients with typical T2DM phlegm-heat syndrome（TR group）,patients without typical T2DM phlegm-heat syndrome（C group）and healthy volunteers（H group）were included in the study,wich is to explore the biological markers of T2DM phlegm-heat syndrome.Fecal samples were examined by 16s rDNA high-throughput sequencing technology;And alpha diversity analysis,Beta diversity analysis,microbial multivariate statistical analysis,Welch’s t-test analysis and other methods were used to compare the characteristics of intestinal flora.Serum Short Chain Fatty Acids（SCFAs）and metabolomics were detected in serum samples by chromatography-mass spectrometry.And Multiple difference analysis,principal component analysis,two-independent sample t test and one-way analysis of variance were used to compare the different SCFAs and other metabolites in the three groups.Spearman correlation analysis was used to analyze the correlation between intestinal flora and multi-mode blood glucose index,intestinal flora and short-chain fatty acids and other circulating metabolites.We subjected with T2DM who showed significantly alleviate in phlegm-heat syndrome（phlegm-heat syndrome score alleviated by≥70%）and no change in medication type during hospitalization.General data,medical history,blood glucose information,TCM diagnostic information,fecal samples and serum samples were collected from patients with high phlegm-heat syndrome score（TF group）and low phlegm-heat syndrome score（TL group）.Paired Chi-square test,T-test of two paired samples and nonparametric test were used to analyze the clinical data.16s rDNA high-throughput sequencing technology was used to detect fecal samples.And species annotation,Alpha diversity analysis,Beta diversity analysis,microbial multivariate statistical analysis,Welch’s t-test analysis and other methods were used to analyze intestinal flora characteristics of the two groups of patients.SCFAs and metabolomics in serum samples were detected by chromatography-mass spectrometry.Multiple difference analysis,principal component analysis,T-test analysis were used to analyze SCFAs and other metabolomics.Results:1.A total of 816 cases were included in this study by screening 2247 cases.After adjustment for PSM and IPTW,phlegm-heat syndrome was negatively correlated with TIR reaching the standard,HbA1c reaching the standard and SDBG reaching the standard.After adjustment for IPTW,phlegm-heat syndrome was negatively correlated with COGI.Only after adjusting for IPTW,dampness-heat syndrome was negatively correlated with SDBG,PPGE and HbA1c reaching the standard;yin deficiency syndrome was negatively correlated with TIR reaching the standard;blood stasis syndrome was negatively correlated with PPGE reaching the standard;blood deficiency syndrome was negatively correlated with SDBG and LAGE reaching the standard;yang deficiency syndrome was negatively correlated with TIR,PPGE reaching and LAGE reaching the standard,but the above syndrome types were not correlated with multi-mode blood glucose indexes after PSM adjustment.After adjustment for IPTW and PSM,qi-deficiency syndrome was only negatively correlated with SDBG reaching the standard.There was a balance between the jiere syndrome and non-jiere syndrome,and jiere syndrome was only negatively correlated with HbA1c reaching the standard.Stasis heat syndrome and non-stasis heat syndrome were balanced,but only negatively correlated with HbA1c reaching the standard（P<0.05）.In conclusion,TIR,average blood glucose level（HbA1c）and blood glucose fluctuation level（SDBG）were only correlated with phlegm-heat syndrome of T2DM,and the results remained stable after adjusting for confounding factors.2 In this study,phlegm-heat syndrome of T2DM,which was found to be the most correlated with multi-mode blood glucose indexes in the above analysis,was taken as the research object.A total of 317 patients were included according to the natrium standard,including 82 T2DM patients with phlegm-heat syndrome and 235 T2DM patients with non-phlegm-heat syndrome.Through the analysis of the two groups,it was found that the BMI,the proportion of drinking history,the proportion of hyperlipidemia,TAR,SDBG,HbA1c,7 times of blood glucose,triglycerides,and the proportion of some items on the scale of phlegm-heat syndrome of T2DM group（including "the tip of the tongue red and the coating yellow and greasy","obesity","irritability and insomnia","pulse slip number","heavy body distress","abdominal fullness stuffy","dizziness","chest tightness","headache and heavy head","adverse sputum production"）,partial objectified tongue diagnosis characteristics（including "red tongue",tongue middle-lab-A,tongue tip-Lab-a,"yellow and white or yellow coating",tongue middle-lab-b,tongue root-Lab-b,tongue whole tongue-Lab-b,"tongue Liver-coated"）and partial objectivated visual features（"dark yellow complexions","dark yellow haze","dark pink haze"）were significantly higher than those in T2DM non-phlegm-heat syndrome group（P<0.05）.The TIR,COGI,total protein and high density lipoprotein of T2DM phlegm-heat syndrome were significantly lower than those of T2DM non-phlegm-heat syndrome group（P<0.05）.The phlegm-heat syndrome prediction model of T2DM was established by logistic regression:-3.708-0.219 ×HbA1c× TIR × SDBG+8.715 ×"Red on the tip of the tongue,Yellow and greasy tongue coating "+ 5.832 ×"disturbance and insomnia "+3.738 ×" body obesity "+0.411 ×" liver-middle-lab-b "+0.513×"liver-whole-tongue Lab-b ",the area under ROC curve was 0.915（95%CI:0.877-0.954,P<0.001）.When the optimal tangent point is 14.2,the sensitivity and specificity of the model are 0.772 and 0.934.3 In this study,13 patients with T2DM phlegm-heat syndrome（TR group）,9 patients with T2DM noe-phlegm-heat syndrome（C group）,and 9 healthy volunteers（H group）were included in the study to explore biological markers of T2DM phlegm-heat syndrome.The analysis of intestinal flora showed that compared with group H,there were 5,8,14,14 and 39 species of characteristic flora in group TR at the level of phylum,class,order,family and genus,respectively.Compared with group C,TR group had 2,3,7,7 and 58 species of characteristic bacteria at the level of phylum,class,order,family and genus,respectively,and 31 species of bacteria were correlated with blood glucose index,including Butyricimonas,Rikenellaceae RC9,gut groupSulfuricurvum,Coprococcus,Lachnospira,Tyzzerella₃,Romboutsia,Ruminococcaceae UCG 002,Polynucleobacter,Escherichia_Shigella,Akkermansia,Pseudorhodobacter,Gordonia,Enterorhabdus,Proteiniphilum,Sulfurovum,Rikenella,Roseovarius,Candidatus Competibacter,Candidatus Megaira,Woeseia,Prevotellaceae UCG-001,Brevundimonas,Roseibacillus,Paenibacillus,Clostridium sensu stricto 13,Candidatus Solibacter,Propionigenium,Microbacterium,Jeotgalicoccus,Candidatus Megaira.In this study,7 T2DM patients with phlegm-heat syndrome significantly alleviate（phlegm-heat syndrome score improved ≥ 70%）and no change in medication types during hospitalization were included.By analyzing the gut flora,Rikenellaceae RC9 gut was found in TF group when phlegm-heat syndrome score was high.The abundance of group,Proteiniphilum,Sulfurovum,Rikenella,Enterorhabdus,Pseudorhodobacter,Desulfitobacterium is higher than that of Desulfitobacterium with low phlegm-heat syndrome score（TL group）.There was no significant difference in short-chain fatty acids between the two groups.Serum metabolomics analysis showed that the levels of 3-methyl-2-oxy-butyric acid and 3-methyl-2-oxy-valerate in TF group were significantly higher than those in TL group,while the levels of n-acetyl-aspartic acid in TF group were significantly lower than those in TL group.After the enrichment analysis of different metabolites,six pathways were obtained,which were closely related to amino acid metabolism and energy metabolism.Conclusions:Phlegm-heat syndrome of T2DM was negatively correlated with TIR,SDBG reach and HbA1c reaching the standard,and remained stable after adjusting for confounding factors,which was the main syndrome associated with multi-mode blood glucose index.T2DM patients with phlegm-heat syndrome have significant clinical features in TCM symptoms,pulse diagnosis,tongue diagnosis,eye diagnosis,drinking history,glucose metabolism index,lipid metabolism index."Upset insomnia","red tongue tip",yellow and greasy tongue coating","body obesity","tongue middle-lab-B","tongue whole-lab-B",HbA1c,TIR and SDBG are of great value in the diagnosis of T2DM phlegm-heat syndrome,and can be used as variables to construct the prediction model of T2DM phlegm-heat.This model has good sensitivity and specificity and can be used in clinical screening of phlegm-heat syndrome of T2DM.In addition,the intestinal flora and serum metabolites of T2DM patients with phlegm-heat syndrome showed significant changes compared with T2DM patients without phlegm-heat syndrome and healthy people,and the intestinal flora and serum metabolites were correlated with the severity of phlegm-heat syndrome.This elucidates part of the biological basis of the symptoms and signs such as "body obesity","upset insomnia" and more serious disorders of glucose and lipid metabolism commonly seen in phlegm-heat syndrome of T2DM,and provides a new target for clinical improvement of metabolic disorders of T2DM from the perspective of combination of disease and syndrome.