Identification of key genes and expression profiles in osteoarthritis by co-expressed network analysis

BackgroundThe underlying molecular characteristics of osteoarthritis (OA), a common age-related joint disease, remains elusive. Here, we aimed to identify potential early diagnostic biomarkers and elucidate underlying mechanisms of OA using weighted gene co-expression network analysis (WGCNA).Material and methodsWe obtained the gene expression profile dataset GSE55235, GSE55457, and GSE55584, from the Gene Expression Omnibus. WGCNA was used to investigate the changes in co-expressed genes between normal and OA synovial membrane samples. Modules that were highly correlated to OA were subjected to functional enrichment analysis using the R clusterProfiler package. Differentially expressed genes (DEGs) between the two samples were screened using the “limma” package in R. A Venn diagram was constructed to intersect the genes in significant modules and DEGs. RT -PCR was used to further verify the hub gene expression levels between normal and OA samples.ResultsThe preserved significant module was found to be highly associated with OA development and progression (P < 1e-200, correlation = 0.92). Functional enrichment analysis suggested that the antiquewhite4 module was highly correlated to FoxO signaling pathway, and the metabolism of fatty acids and 2-oxocarboxylic acid. A total of 13 hub genes were identified based on significant module network topology and DEG analysis, and RT-PCR confirmed that these genes were significantly increased in OA samples compared with that in normal samples.ConclusionsWe identified 13 hub genes correlated to the development and progression of OA, which may provide new biomarkers and drug targets for OA.     

双龙方组分诱导大鼠BMSCs分化的差异基因筛选及聚类分析

利用基因芯片筛选双龙方有效组分(总人参皂苷及总丹酚酸)诱导大鼠骨髓间充质干细胞(BMSCs)类心肌细胞分化过程中的差异表达基因, 并对其进行聚类分析, 在基因水平研究了双龙方组分对大鼠BMSCs分化的影响. 对大鼠BMSCs进行分组培养, 分别收集10, 20, 30及40 d的细胞样本, 提取tRNA, 经基因芯片检测, 筛选出BMSCs变化过程中的差异表达基因并进行生物信息学分析, 同时通过差异表达基因对样本进行Hierarchical聚类分析. 在BMSCs的分化过程中, 筛选出179条差异表达基因, 经分析发现它们与能量代谢和信号传导等多类基因密切相关. 对样本进行聚类分析发现其聚为两大类: 10和20 d的样本聚为一类, 30和40 d的样本聚为一类. 说明BMSCs在20~30 d之间可能发生了显著的改变.     

Genetic and expression alterations in association with the sarcomatous change of cholangiocarcinoma cells

Cholangiocarcinoma (CC) is an intrahepatic bile duct carcinoma with a high mortality rate and a poor prognosis. Sarcomatous change/epithelial mesenchymal transition (EMT) of CC frequently leads to aggressive intrahepatic spread and metastasis. The aim of this study was to identify the genetic alterations and gene expression pattern that might be associated with the sarcomatous change in CC. Previously, we established 4 human CC cell lines (SCK, JCK1, Cho-CK, and Choi-CK). In the present study, we characterized a typical sarcomatoid phenotype of SCK, and classified the other cell lines according to tumor cell differentiation (a poorly differentiated JCK, a moderately differentiated Cho-CK, and a well differentiated Choi-CK cells), both morphologically and immunocytologically. We further analyzed the genetic alterations of two tumor suppressor genes (p53 and FHIT) and the expression of Fas/FasL gene, well known CC-related receptor and its ligand, in these four CC cell lines. The deletion mutation of p53 was found in the sarcomatoid SCK cells. These cells expressed much less Fas/FasL mRNAs than did the other ordinary CC cells. We further characterize the gene expression pattern that is involved in the sarcomatous progression of CC, using cDNA microarrays that contained 18,688 genes. Comparison of the expression patterns between the sarcomatoid SCK cells and the differentiated Choi-CK cells enabled us to identify 260 genes and 247 genes that were significantly over-expressed and under-expressed, respectively. Northern blotting of the 14 randomly selected genes verified the microarray data, including the differential expressions of the LGALS1, TGFBI, CES1, LDHB, UCHL1, ASPH, VDAC1, VIL2, CCND2, S100P, CALB1, MAL2, GPX1, and ANXA8 mRNAs. Immunohistochemistry also revealed in part the differential expressions of these gene proteins. These results suggest that those genetic and gene expression alterations may be relevant to the sarcomatous change/EMT in CC cells.     

Construction and analysis of a diabetic nephropathy related protein-protein interaction network reveals nine critical and functionally associated genes

Diabetic nephropathy (DN) is one of the common diabetic complications, but the mechanisms are still largely unknown. In this study, we constructed a DN related protein-protein interaction network (DNPPIN) on the basis of RNA-seq analysis of renal cortices of DN and normal mice, and the STRING database. We analyzed DNPPIN in detail revealing nine critical proteins which are central in DNPPIN, and contained in one network module which is functionally enriched in ribosome, nucleic acid binding and metabolic process. Overall, this study identified nine critical and functionally associated protein-coding genes concerning DN. These genes could be a starting point of future research towards the goal of elucidating the mechanisms of DN pathogenesis and progression.     

Bipartite network analysis reveals metabolic gene expression profiles that are highly associated with the clinical outcomes of acute myeloid leukemia

Dysregulated and reprogrammed metabolism are one of the most important characteristics of cancer, and exploiting cancer cell metabolism can aid in understanding the diverse clinical outcomes for patients. To investigate the differences in metabolic pathways among patients with acute myeloid leukemia (AML) and differential survival outcomes, we systematically conducted microarray data analysis of the metabolic gene expression profiles from 384 patients available from the Gene Expression Omnibus and Cancer Genome Atlas databases. Pathway enrichment analysis of differentially expressed genes (DEGs) showed that the metabolic differences between low-risk and high-risk patients mainly existed in two pathways: biosynthesis of unsaturated fatty acids and oxidative phosphorylation. Using the gene-pathway bipartite network, 62 metabolic genes were identified from 272 DEGs involved in 88 metabolic pathways. Based on the expression patterns of the 62 genes, patients with shorter overall survival (OS) durations in the training set (hazard ratio (HR) = 1.58, p = 0.038) and in two test sets (HR = 1.69 and 1.56 and p = 0.089 and 0.029, respectively) were well discriminated by hierarchical clustering analysis. Notably, the expression profiles of ALAS2, BCAT1, BLVRB, and HK3 showed distinct differences between the low-risk and high-risk patients. In addition, models for predicting the OS outcome of AML from the 62 gene signatures achieved improved performance compared with previous studies. In conclusion, our findings reveal significant differences in metabolic processes of patients with AML with diverse survival durations and provide valuable information for clinical translation.     

Gene selection of rat hepatocyte proliferation using adaptive sparse group lasso with weighted gene co-expression network analysis

Grouped gene selection is the most important task for analyzing the microarray data of rat liver regeneration. Many existing gene selection methods cannot outstand the interactions among the selected genes. In the process of rat liver regeneration, one of the most important events involved in many biological processes is the proliferation of rat hepatocytes, so it can be used as a measure of the effectiveness of the method. Here we proposed an adaptive sparse group lasso to select genes in groups for rat hepatocyte proliferation. The weighted gene co-expression networks analysis was used to identify modules corresponding to gene pathways, based on which a strategy of dividing genes into groups was proposed. A strategy of adaptive gene selection was also presented by assessing the gene significance and introducing the adaptive lasso penalty. Moreover, an improved blockwise descent algorithm was proposed. Experimental results demonstrated that the proposed method can improve the classification accuracy, and select less number of significant genes which act jointly in groups and have direct or indirect effects on rat hepatocyte proliferation. The effectiveness of the method was verified by the method of rat hepatocyte proliferation.     

显微共聚焦拉曼光谱结合群分析的黑色直液笔墨迹鉴别研究

黑色直液笔是一种新型书写工具,目前对该种笔墨迹的相关研究较少。为给文件检验工作中墨迹的分析提供新的参考依据,本实验使用显微共聚焦拉曼光谱技术,采集了30支不同品牌、型号的黑色直液笔墨迹光谱数据,进行Savitzky-Golay卷积平滑处理后,依据光谱图的拉曼位移及拉曼谱峰差异对墨迹进行初步分析。设置聚类方法为组间联接,区间距离测量方式为平方欧式距离,对采集的光谱数据进行群分析,将30支黑色直液笔墨迹样本分成了3类,并与品牌建立了相关联系;同时通过主成分分析验证了群分析的可靠性和准确性。研究表明,显微共聚焦拉曼光谱技术结合群分析方法可实现对黑色直液笔墨迹的无损分析及有效鉴别,该方法操作简便、结果准确,适用于法庭科学文件检验。     

氢化物发生原子荧光结合计算法测定大气颗粒物中砷的形态

运用碱式消解法对样品进行前处理,采用氢化物发生-原子荧光光谱数学计算法测定大气颗粒物中As(Ⅲ)和As(Ⅴ)的含量。探讨了还原剂用量、酸介质及其酸度、载气及屏蔽气流量和观测高度等对荧光强度的影响,分析了共存离子对砷测定的干扰。在选定的最佳条件下,得到检出限为0.34μg/L,加标回收率为87.8%～108.2%。方法可用于测定大气颗粒物中不同形态的砷。     

Quantitative and fingerprinting analysis of Atractylodes rhizome based on gas chromatography with flame ionization detection combined with chemometrics

This study assessed the feasibility of gas chromatography with flame ionization detection fingerprinting combined with chemometrics for quality analysis of Atractylodes rhizome. We extracted essential oils from 20 Atractylodes lancea and Atractylodes koreana samples by hydrodistillation. The variation in extraction yields (1.33–4.06%) suggested that contents of the essential oils differed between species. The volatile components (atractylon, atractydin, and atractylenolide I, II, and III) were quantified by gas chromatography with flame ionization detection and confirmed by gas chromatography with mass spectrometry, and the results demonstrated that the number and content of volatile components differed between A. lancea and A. koreana. We then calculated the relative peak areas of common components and similarities of samples by comparing the chromatograms of A. lancea and A. koreana extracts. Also, we employed several chemometric techniques, including similarity analysis, hierarchical clustering analysis, principal component analysis, and partial least‐squares discriminate analysis, to analyze the samples. Results were consistent across analytical methods and showed that samples could be separated according to species. Five volatile components in the essential oils were quantified to further validate the results of the multivariate statistical analysis. The method is simple, stable, accurate, and reproducible. Our results provide a foundation for quality control analysis of A. lancea and A. koreana.     

Comparison of sample preparation methods combined with gas chromatography with electron‐capture detection for the analysis of multipesticide residues in lotus seeds

Sample preparation is always the major bottleneck in analytical chemistry for the determination of pesticide residues. Different sample preparation methods have been proposed due to the wide variety of pesticides used and the inherent complexity of the matrices. In this study, different sample preparation methods including SPE, matrix solid‐phase dispersion, the quick, easy, cheap, efficient, rugged, and safe method, and a one‐step completion method were compared and evaluated for extracting pesticides from lotus seeds. Analysis was carried out using GC with electron‐capture detection. The results showed that good recoveries for tested pesticides were obtained by using Florisil in the four methods, and the extraction efficiency of the one‐step completion method was superior to the other three methods. The one‐step completion method was confirmed to have good linearity, reproducibility, stability, and recovery for the detection of 36 pesticides in lotus seed samples. The data collected from this study are expected to prove useful in regulating the concentration of the residues in lotus seeds, as well as in protecting human health from the hazards posed by these residues.     

Fingerprint and multicomponent quantitative analysis for the quality evaluation of Sibiraea angustata leaves by HPLC-DAD and HPLC-ESI-MS/MS combined with chemometrics

Sibiraea angustata leaves, known as a traditional Tibetan medicine, have been specially used in the treatment of indigestion and obesity. In the study, a simple and sensitive high-performance liquid chromatography (HPLC) method with a diode array detector (DAD) was established to solve the problem of lacking quality standard of S. angustata leaves, including the fingerprint analysis and quantification of six characteristic components. The analytical method was validated for linearity, repeatability, stability, recovery, and specificity. Seventeen raw samples and 1 processed sample of S. angustata leaves were collected from different locations of China to establish the fingerprint. The chemometric methods, including similarity analysis (SA), principal component analysis (PCA), and hierarchical clustering analysis (HCA), were applied to distinguish the 18 batches of S. angustata samples. The results successfully sorted these samples into five clusters and kept in line with each other. According to the result of the fingerprint analysis, 21 peaks were extracted to be the common peaks and most of them were identified by mass spectrometry (MS) with electron-spray ionization (ESI) in the negative mode. Meanwhile, the loading plot of PCA further indicated that the peaks of neochlorogenic acid, chlorogenic acid, ferulic acid, rutin, hyperin, and isoquercitrin played a greater role in the discrimination among the 21 peaks. So the six components mentioned above were investigated as index constituents to evaluate the quality of S. angustata leaves from different locations. The study demonstrated that the developed new method was a beneficial approach for authentication and quality evaluation of S. angustata leaves.     

Simultaneous determination of 20 bioactive components in Chuanxiong Rhizoma from different production origins in Sichuan province by ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry combined with multivariate statistical analysis

Chuanxiong Rhizoma is a commonly used in traditional Chinese medicine. Chuanxiong Rhizoma is widely distributed in Sichuan province, China, including the cities of Dujiangyan, Pengzhou, Meishan, Qionglai, and Shifang. However, reports on the comparisons of quality of Chuanxiong Rhizoma of different production origins are limited. Therefore, an ultra-HPLC with triple quadrupole MS method was developed for the determination of 20 bioactive components (12 aromatic acids and eight phthalides) in 36 samples from different production origins and further assessed its quality. The contents of these 20 constituents of samples were analyzed by hierarchical cluster analysis and orthogonal partial least squares discrimination analysis; the result indicated that Chuanxiong Rhizoma of different production origins had some differences. Thirteen constituents of quality difference markers were acquired by variable importance for the project. Furthermore, the sum of the contents of these quality difference markers was different from various production origins of Chuanxiong Rhizoma. Meanwhile, Z-ligustilide and senkyunolide A as main constituents of quality difference markers, the rate of various production origins of Chuanxiong Rhizoma was different. This study provides a foundation for the quality assessment of Chuanxiong Rhizoma.     

Accurate discrimination of Gastrodia elata from different geographical origins using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis

Gastrodia elata from different geographical origins varies in quality and pharmacological activity. This study focused on the classification and identification of Gastrodia elata from six producing areas using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis. Before recognition analysis, a principal component analysis was applied to ascertain the discrimination possibility with high‐performance liquid chromatography fingerprints. And then, boosting partial least‐squares discriminant analysis and conventional partial least‐squares discriminant analysis were applied in this study. Experimental results indicated that the adaptive iteratively reweighted penalized least‐squares algorithm could eliminate the baseline drift of high‐performance liquid chromatography chromatograms effectively. And compared with partial least‐squares discriminant analysis, the total recognition rates using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis for the calibration sets and prediction sets were improved from 94 to 100% and 86 to 97%, respectively. In conclusion, high‐performance liquid chromatography combined with boosting partial least‐squares discriminant analysis, which has such advantages as effective, specific, accurate, non‐polluting, has an edge for discrimination of traditional Chinese medicine from different geographical origins. And the proposed methodology is a useful tool to classify and identify Gastrodia elata from different geographical origins.     

Quality evaluation of Eucommiae Cortex processed by different methods and “sweating” conditions based on simultaneous determination of multiple bioactive constituents combined with gray relational analysis

Eucommiae Cortex is a classical traditional Chinese medicine, which needs to be processed by “sweating” methods. To select the suitable processing method and “sweating” processing condition for Eucommiae Cortex, in this study, the quality of Eucommiae Cortex was evaluated based on simultaneous determination of multiple bioactive constituents combined with gray relational analysis. The contents of lignans, iridoids, penylpropanoids, flavonoids, and phenols in samples were simultaneously determined using ultra‐fast performance liquid chromatography coupled with triple quadrupole‐linear ion trap tandem mass spectrometry. The chromatographic separation was performed on a Synergiۛ Hydro‐RP 100 Å column (100 mm × 2.0 mm, 2.5 μm) at 30°C with a gradient elution of acetonitrile with 0.1% formic acid/0.1% aqueous formic acid as the mobile phase. Furthermore, gray relational analysis was performed to evaluate and sort the samples according to the contents of 14 constituents by calculating the relative correlation degree of each sample. The results demonstrated that the quality of Eucommiae Cortex “sweating” at source area was better and the better “sweating” condition was to scrape off the cork layer before “sweating” with straw covering and sun drying. The developed method could provide the foundation and support for “sweating” processing method of Eucommiae Cortex in normalization and standardization.     

An integrated strategy for the geographical origin traceability of Goji berries by antioxidants characteristic fingerprint based online ultra-performance liquid chromatography-2,2-diphenyl-1-picrylhydrazyl- photodiode array detector-mass spectrometry combined with multivariate statistics analysis

Goji berries are now becoming increasingly popular in the human diet due to their potential health benefits. Unscrupulous traders deliberately mislabel with certain origins to gain illegal profits, which seriously affected the consumers’ benefits. In this study, an online ultra-performance liquid chromatography-2,2-diphenyl-1 -picrylhydrazyl-photodiode array detector-electrospray ionization-quadrupole time of flight mass was developed for rapid screening and identification of the antioxidants from Goji berry; then, the antioxidants characteristic fingerprint was established and explored in the origins discrimination of Goji berries from China combined with multivariate statistics analysis. As a result, twenty-eight compounds were screened from Goji berry extract, 19 of which were identified by accurate molecular and ultraviolet information according to references. Principal components analysis and partial least squares discrimination analysis achieved the accurate classification from the four regions, eight compounds were selected as origin-related antioxidant markers with variable importance in projection >1 and one-way analysis of variance (P<0.05), including rutin, rutin di-hexose, P-coumaric acid tri-hexose, dicaffeoylquinic acid isomer, Quercetin-rhamno-di-hexoside, peak14, peak16, and peak27. This study provides a feasible strategy for the geographical origins discrimination of Goji berries based on antioxidant ingredients difference and will be helpful for improving the quality control level of Goji berries.