Differential gene expression in hemodialysis patients with "cold" zheng

Transcriptomic and machine learning analyses identify hub genes of metabolism and host immune response that are associated with the progression of breast capsular contracture

Capsular contracture is a prevalent and severe complication that affects the postoperative outcomes of patients who receive silicone breast implants. At present, prosthesis replacement is the major treatment for capsular contracture after both breast augmentation procedures and breast reconstruction following breast cancer surgery. However, the mechanism(s) underlying breast capsular contracture remains unclear. This study aimed to identify the biological features of breast capsular contracture and reveal the potential underlying mechanism using RNA sequencing. Sample tissues from 12 female patients (15 breast capsules) were divided into low capsular contracture (LCC) and high capsular contracture (HCC) groups based on the Baker grades. Subsequently, 41 lipid metabolism-related genes were identified through enrichment analysis, and three of these genes were identified as candidate genes by SVM-RFE and LASSO algorithms. We then compared the proportions of the 22 types of immune cells between the LCC and HCC groups using a CIBERSORT analysis and explored the correlation between the candidate hub features and immune cells. Notably, PRKAR2B was positively correlated with the differentially clustered immune cells, which were M1 macrophages and follicular helper T cells (area under the ROC = 0.786). In addition, the expression of PRKAR2B at the mRNA or protein level was lower in the HCC group than in the LCC group. Potential molecular mechanisms were identified based on the expression levels in the high and low PRKAR2B groups. Our findings indicate that PRKAR2B is a novel diagnostic biomarker for breast capsular contracture and might also influence the grade and progression of capsular contracture.

Comprehensive Analysis of Immune-Related Metabolic Genes in Lung Adenocarcinoma

PURPOSE

The immunotherapy of lung adenocarcinoma (LUAD) has received much attention in recent years and metabolic reprogramming is linked to immune infiltration in the tumor microenvironment. Therefore, it is indispensable to dissect the role of immune-related metabolic genes in lung adenocarcinoma.

METHODS

In this study, we screened immune-related genes by Pearson correlation. The function of these genes was explored by gene ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. The differently expressed immune-related genes were analyzed by Limma. Furthermore, the LUAD patients were clustered based on immune-related genes through consensus clustering. The Unicox was used to identify survival-immune-related metabolic genes. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to optimize the gene sets. A prediction model was constructed and tested. The potential therapeutic target was selected based on two criteria, these immune-related metabolic genes that were highly expressed in tumor tissues and negatively correlated with the survival of patients in LUAD. Quantitative real-time PCR (qRT-PCR) was used for in vitro experimental validations.

RESULTS

We identified 346 immune-related genes, mainly involved in arachidonic acid metabolism and peroxisome proliferator-activated receptor (PPAR) signaling. Moreover, a total of 141 immune-related genes were dysregulated between tumor and normal tissues. We clustered three subtypes of LUAD based on immune-related metabolic genes and these subtypes exhibited different survival and immune status. We found Ribonucleotide Reductase Regulatory Subunit M2 (RRM2) as a potential therapeutic target, which is positively correlated with the cyclin-dependent kinase family of genes.

CONCLUSION

We comprehensively analyzed the immune-related metabolic genes in LUAD. RRM2 was determined as a promising metabolic checkpoint for lung adenocarcinoma.

Identification of differentially expressed non-coding RNAs and mRNAs involved in Qi stagnation and blood stasis syndrome

Qi stagnation and blood stasis syndrome (QSBSS) is a common Zheng in Traditional Chinese Medicine (TCM), describes the condition of unsmooth flow of Qi and blood, which manifests as distending pain in a fixed body part and emotional disorders, including irritability and depression. However, the underlying molecular mechanisms remain largely elusive. RNAs are the connection between DNA and proteins, which reflect the interaction between the genotypes and the phenotype. Of note, non-coding (nc)RNA is a type of RNA that is not translated into any protein, but has regulatory functions. Despite the growing interest in exploring the biological basis of TCM Zhengs, the specific roles of ncRNAs in QSBSS have remained largely elusive. In the present study, next-generation sequencing was performed to investigate the ncRNA profile in patients with three different types of disease, but who had QSBSS. A total of 104 long non-coding RNAs, 2 circular RNAs and 697 mRNAs were identified to be significantly differentially expressed in QSBSS patients. Further bioinformatics analysis revealed that the most significantly enriched pathways by the differentially expressed RNAs in QSBSS were the sphingolipid signaling pathway, the neurotrophin signaling pathway, 5′AMP-activated protein kinase and endocytosis. In addition, a network pharmacology analysis indicated that several of the differentially expressed RNAs were included in the targets of TCM herbs for treating QSBSS. The present study was the first to identify ncRNAs that are deregulated in QSBSS by next-generation sequencing technology. The results may offer insight into the biological basis of TCM Zheng and the optimization of ancient formulae, as well as the discovery of novel drugs, to pave the way toward advanced TCM theory and improved health care delivery.

Differential gene expression profiles between two subtypes of ischemic stroke with blood stasis syndromes

Ischemic stroke is a cerebrovascular thrombotic disease with high morbidity and mortality. Qi deficiency blood stasis (QDBS) and Yin deficiency blood stasis (YDBS) are the two major subtypes of ischemic stroke according to the theories of traditional Chinese medicine. This study was conducted to distinguish these two syndromes at transcriptomics level and explore the underlying mechanisms. Male rats were randomly divided into three groups: sham group, QDBS/MCAO group and YDBS/MCAO group. Morphological changes were assessed after 24 h of reperfusion. Microarray analysis with circulating mRNA was then performed to identify differential gene expression profile, gene ontology and pathway enrichment analyses were carried out to predict the gene function, gene co-expression and pathway networks were constructed to identify the hub biomarkers, which were further validated by western blotting and Tunel staining analysis. Three subsets of dysregulated genes were acquired, including 445 QDBS-specific genes, 490 YDBS-specific genes and 1676 blood stasis common genes. Our work reveals for the first time that T cell receptor, MAPK and apoptosis pathway were identified as the hub pathways based on the pathway networks, while Nfκb1, Egfr and Casp3 were recognized as the hub genes by co-expression networks. This research helps contribute to a clearer understanding of the pathological characteristics of ischemic stroke with QDBS and YDBS syndrome, the proposed biomarkers might provide insight into the accurate diagnose and proper treatment for ischemic stroke with blood stasis syndrome.

Transcriptomics: a sword to cut the Gordian knot of traditional Chinese medicine

The systemic effects of traditional Chinese medicine (TCM) seem to be a Gordian knot, impossible to untie for decades. With the advent of transcriptomics, a useful sword is provided to cut the knot and shed some light on complex bioprocesses and intrinsic connections among them. Here, we revisit studies on TCM ZHENGs using this approach, highlight its applications on elucidating the potential scientific basis of ZHENG and investigating mechanisms of action for the TCM formula, and demonstrating its unique role in novel TCM drug design and discovery through active ingredient detection from TCM and compatibility theory study of TCM. The limitations and future perspectives of transcriptomics approaches to TCM study are also discussed.

Progress and perspectives of biomarker discovery in Chinese medicine research

Biomarker discovery in Chinese medicine (CM) has recently attracted a great deal of attention, owing to the promise of high-throughput technologies development and the potential of Chinese herbal medicine. Furthermore, it seems that pattern classification in CM might be serving as inspirational analogy and a practical guide, which might contribute to biomarkers discovery rather than just being used as diagnostic method. Although much work is still needed to identify markers, efforts are now being directed towards discovering biomarkers or biomarkers based network that could target herbal formulae. In this article, we review progress in biomarker discovery development, discuss current biomarker discovery in CM highlighting challenges and opportunities of pattern classification and presenting a perspective of the future integrative modeling approaches as an emerging trend in biomarker discovery.

Clinical Applications of Omics Technologies on ZHENG Differentiation Research in Traditional Chinese Medicine

Traditional Chinese medicine (TCM) ZHENG is the basic concept of TCM theory. The effectiveness of TCM treatment depends on the accuracy of ZHENG differentiation. ZHENG differentiation, using the "four diagnostic methods," has the drawbacks of subjectivity and variability. Following development of omics technologies, which study the functional activities of human body from a system-wide perspective, it has been more and more applied in study of objectivity differentiating TCM ZHENG and understanding its biological mechanisms. This paper reviewed the literatures of clinical TCM ZHENG differentiation researches, underlying omics technologies, and indicated the increased trends of related articles with four kinds of omics technologies, including genomics, transcriptomics, proteomics and metabolomics, and the correlations between ZHENG differentiation and findings in omics studies. Moreover, the paper summarized the typical omics application in common studied diseases and TCM ZHENGs and discussed the main problems and countermeasure of ZHENG differentiation researches. The work here may provide a reference for further research of TCM ZHENG differentiation using omics technologies.

Association between cold dialysis and cardiovascular survival in hemodialysis patients

BACKGROUND

Higher cardiovascular mortality has been noted in patients with chronic kidney disease (CKD). CKD patients are also known to have impaired energy expenditure but the role of energy expenditure in cardiovascular disease is not yet known. Furthermore, the association between cold dialysis (CD) and clinical outcomes in hemodialysis patients is unclear.

METHODS

This was a single-center retrospective cohort study consisting of two groups: a CD group with dialyzate temperature <35.5 °C and a standard dialysis (SD) group with dialyzate temperature between 35.5 and 37 °C. The end points of the study were overall mortality, cardiac mortality and non-cardiac mortality. The study analyzed the associations between dialyzate temperature and long-term survival in CD and SD groups. Propensity score analysis was used to control for intergroup baseline differences.

RESULTS

Baseline characteristics of both groups were similar. Kaplan-Meier analysis showed that CD was significantly associated with a lower risk for overall mortality (P = 0.006) and cardiac mortality (P = 0.023) but not for non-cardiac mortality or infectious mortality. After multivariate Cox regression analysis, adjusting for propensity scores and other possible confounding factors, CD remained a significant beneficial factor for overall mortality (P = 0.030) and cardiac mortality (P = 0.034).

CONCLUSION

Our studies show that CD is significantly and independently associated with a lower risk for overall mortality and cardiac mortality.

Molecular basis for cold-intolerant yang-deficient constitution of traditional Chinese medicine

Based on the theory of constitution of Traditional Chinese Medicine (TCM), the human population can be classified into nine constitutions including a balanced constitution and eight unbalanced constitutions (Yang-deficient, Yin-deficient, Qi-deficient, Phlegm-wetness, Wetness-heat, Stagnant blood, Depressed, and Inherited special constitutions). Generally, unbalanced constitutions are more susceptible to certain diseases than balanced constitutions. However, whether such constitution classification has modern genetic and biochemical basis is poorly understood. Here we examined gene expression profiles in peripheral white blood cells from eight individuals with Yang-deficient constitutions and six individuals with balanced constitutions using Affymetrix U133 plus 2.0 expression array. Based on a q < 0.05 and fold-change > or = 2 cutoff, we have identified that 785 genes are up-regulated and 954 genes are down-regulated in Yang-deficient constitution compared to a balanced constitution. Importantly, we found that the expression of thyroid hormone receptor beta (TRbeta) and several key nuclear receptor coactivators including steroid receptor coactivator 1 (SRC1), steroid receptor coactivator 3 (SRC3), cAMP-response element-binding protein (CREB) binding protein (CBP) and Mediator is significantly decreased. Such decreased expression of TR transcription complex may lead to impaired thermogenesis, providing a molecular explanation of the main symptom associated with Yang-deficient constitution, cold intolerance. Future studies are needed to validate these gene expression changes in additional populations and address the underlying mechanisms for differential gene expression.