Project description:We investigated the expression profiles of lncRNAs and mRNAs in peripheral blood mononuclear cells (PBMCs) from subjects with 13 Phlegm-dampness constitution (PDC) and nine balanced Balanced constitution (BC). The differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were identified by the “limma” method. Goal was to determine whether long non-coding RNAs (lncRNAs) play a regulatory role in metabolic disease in subjects with PDC.
Project description:Using high-throughput antibody microarray, through cross-sectional sample detection and verification of samples that had undergone physical changes over time, it was found that people with balanced constitution and dampness constitution in Chinese medicine showed differences in serum protein expression. The differences were expressed as the level changes of 19 proteins such as Dectin-2, Siglec-7, AIF and TACI. The research results provided the basis for the scientific expression of traditional Chinese medicine (TCM) constitution.
Project description:Rationale: Although there is no available theory or effective technology to differentiate, subhealth symptoms caused by prolonged exposure of incorrect diet or humid environment are triggers for chronic disease, which become a serious problem of human health. These symptoms are similar as dampness in traditional Chinese medicine (TCM). They can lead to dampness constitution (DC) and dampness syndrome (DS), which easily resulting in a variety of human immune and metabolic diseases, especially hyperlipidemia in human beings. However, its clinical diagnosis still mainly depends on the doctor’s judgement and constitution scales. It is urgent to develop an objective, accurate and effective clinical diagnosis technology to meet this significant clinical challenge. Methods: Coupling TiO2 enrichment method and exosome proteomics, we obtained high-quality serum exosome proteins and proteome profiling in healthy subjects with balanced constitution (BC) and typical dampness groups through data-independent acquisition mass spectrometry (DIA-MS). Two groups of potential diagnostic markers of dampness were identified by machine learning algorithm. These proteins were verified by the expression changes in BC, hyperlipidemia subjects with balanced constitution (HBC) and with dampness constitution (HDC) groups. Furthermore, these proteins were also verified by the expression changes before and after 16 week’s use of Fuling-zexie decoction, a well-known traditional Chinese medicine prescription in conditioning dampness. Results: Serum exosome proteome can be saved as identity of dampness syndrome. By comparing the exosome proteome of the individuals from balanced constitution and dampness groups, 89 differentially-expressed exosome proteins were identified, which were involved in dampness-relevant biological processes, such as immune activity, inflammation and lipid metabolism. Finally, a panel of fourteen proteins included group A (IGA2, IGHV1-69, IGHV3-38, IGHV4-28, IGKV3-15, IGKV4-1) and group B proteins (CRP, FAN3, F9, F10, GP5, SERPING1, SPP2, PCSK9) screened through random forest approach could efficiently differentiate dampness from healthy subjects with balanced constitution (BC) and typical dampness groups. To further verify the panel composed of these fourteen proteins, we analyzed 41 serum exosome proteomes contained BC, HBC and HDC groups, showing that combination of six proteins in group A and six proteins in group B could accurately distinguish between HDC and BC, and eight proteins in group B could accurately distinguish between HBC and HDC. Moreover, we analyzed 30 serum exosome proteomes from the dampness groups with hyperlipidemia before and after 16 weeks’ treatment with traditional Chinese medicine Fuling-zexie decoction or placebo. The results showed that ten proteins were dampness specifical proteins and changed in the direction of improvement with the removal of dampness. Finally, we identified thirteen proteins as potential diagnostic biomarkers. Conclusion: These results demonstrated the clinical applicability of our serum exosome proteomics in characterizing and differentiating dampness. The differential dampness specific diagnostic markers obtained from the serum exosome proteomics followed by machine learning approach have potential application value in identification of dampness.
Project description:Transcriptional profiling of human PBMCs comparing healthy controls, patients with diabetic nephropathy and patients with ESRD. PBMCs were analyzed as they mediate inflammatory injury. Goal was to determine effects of increasing severity of diabetic nephropathy on global PBMC gene expression. Microarray analysis of PBMCs taken from patients with varying degrees of diabetic nephropathy.
Project description:To characterize the primary and recall responses to EV71 vaccines, PBMC from 19 recipients before and after vaccination with EV71 vaccine are collected and their gene expression signatures after stimulation with EV71 antigen were compared. Four-condition experiment,pre-vaccination PBMCs (stimulation vs. no stimulation with EV71 antigen) vs. post-vaccination PBMCs (stimulation vs. no stimulation with EV71 antigen)