Tsaokoflavanols A1-J1: Flavanol-fatty alcohol hybrids with HPL inhibitory activity from Amomum tsao-ko.

Ten previously undescribed compounds were isolated from the fruits of Amomum tsao-ko (Zingiberaceae), including nine undescribed flavanol-fatty alcohol hybrids (1-6, 10-11, 13), and a flavanol-monoterpenoid hybrid (14), along with seven known flavanol hybrids (7-9, 12, 15-17). The structures of these compounds were determined using various analyses, such as HRESIMS, 1D/2D NMR, and ECD calculations. In terms of biological activity, compounds 1, 2, 5, and 6 exhibited inhibitions of human pancreatic lipase (HPL), with IC50 values ranging from 0.017 to 0.193 mM. Some of these values were found to be stronger than that of the positive control, orlistat (IC50, 0.067 mM). Molecular docking studies were also conducted to investigate the interactions between these compounds and HPL. The docking simulations revealed the importance of the orientation of the 3,4-dihydroxyphenyl in binding with HPL. Additionally, compound 9 demonstrated cytotoxicity against HepG2, with a CC50 value of 14.96 ± 0.62 µM as determined by the MTT assay. Flow cytometry analysis indicated that compound 9 induced apoptosis in HepG2 cells. Western blot results showed an up-regulation of apoptosis-related proteins, such as p53 protein, Bax and Caspase-3 proteins, while the expression of Bcl-2 protein was down-regulated.

Comparative Analysis of Active Ingredients and Potential Bioactivities of Essential Oils from Artemisia argyi and A. verlotorum.

Artemisia argyi H. Lév. and Vaniot is a variety of Chinese mugwort widely cultured in central China. A. verlotorum Lamotte, another variety of Chinese mugwort, has been used in the southern region of China since ancient times. Despite their similar uses in traditional medicine, little is known about the differences in their active ingredients and potential benefits. Herein, the chemical compositions of the essential oils (EOs) from both varieties were analyzed using chromatography-mass spectrometry (GC-MS). A series of databases, such as the Traditional Chinese Medicine Systems Pharmacology database (TCMSP), SuperPred database and R tool, were applied to build a networking of the EOs. Our results revealed significant differences in the chemical compositions of the two Artemisia EOs. However, we found that they shared similar ingredient-target-pathway networking with diverse bioactivities, such as neuroprotective, anti-cancer and anti-inflammatory. Furthermore, our protein connection networking analysis showed that transcription factor p65 (RELA), phosphatidylinositol 3-kinase regulatory subunit alpha (PIK3R1) and mitogen-activated protein kinase 1 (MAPK1) are crucial for the biological activity of Artemisia EOs. Our findings provided evidence for the use of A. verlotorum as Chinese mugwort in southern China.

Essential oil of lemon myrtle (Backhousia citriodora) induces S-phase cell cycle arrest and apoptosis in HepG2 cells.

ETHNOPHARMACOLOGICAL RELEVANCE: Lemon myrtle (Backhousia citriodora F.Muell.) leaves, whether fresh or dried, are used traditionally in folk medicine to treat wounds, cancers, skin infections, and other infectious conditions. However, the targets and mechanisms related to anti-cancer effect of lemon myrtle are unavailable. In our study, we found that the essential oil of lemon myrtle (LMEO) showed anti-cancer activity in vitro, and we initially explored its mechanism of action. MATERIALS AND METHODS: We analyzed the chemical compositions of LMEO by GC-MS. We tested the cytotoxicity of LMEO on various cancer cell lines using the MTT assay. Network pharmacology was used also to analyze the targets of LMEO. Moreover, the mechanisms of LMEO were investigated through scratch assay, flow cytometry analysis, and western blot in the HepG2 liver cancer cell line. RESULTS: LMEO showed cytotoxicity on various cancer cell lines with values of IC50 40.90 ± 2.23 (liver cancer HepG2 cell line), 58.60 ± 6.76 (human neuroblastoma SH-SY5Y cell line), 68.91 ± 4.62 (human colon cancer HT-29 cell line) and 57.57 ± 7.61 µg/mL (human non-small cell lung cancer A549 cell line), respectively. The major cytotoxic chemical constituent in LMEO was identified as citrals, which accounted for 74.9% of the content. Network pharmacological analysis suggested that apurinic/apyrimidinic endodeoxyribonuclease 1 (APEX1), androgen receptor (AR), cyclin-dependent kinases 1 (CDK1), nuclear factor erythroid 2-related factor 2 (Nrf-2), fatty acid synthase (FASN), epithelial growth factor receptor (EGFR), estrogen receptor 1 (ERα) and cyclin-dependent kinases 4 (CDK4) are potential cytotoxic targets of LMEO. These targets are closely related to cell migration, cycle and apoptosis. Notley, the p53 protein had the highest confidence to co-associate with the eight common targets, which was further confirmed by scratch assay, flow cytometry analysis, and western blot in the HepG2 liver cancer cell line. LMEO significantly inhibited the migration of HepG2 cells in time-dependent and dose-dependent manner. Moreover, LMEO caused a S-phase blocking on HepG2 cells and promoted apoptosis in the meanwhile. Western blot results indicated that p53 protein, Cyclin A2 and Bax proteins were up-regulated, while Cyclin E1 and Bcl-2 proteins were down-regulated. CONCLUSION: LMEO showed cytotoxicity in various cancer cell lines in vitro. Pharmacological networks showed LMEO to have multi-component and multi-targeting effects that are related to inhibit migration of HepG2 cells, and affect cell cycle S-phase arrest and apoptosis through modulation of p53 protein.

A hnRNPA2B1 agonist effectively inhibits HBV and SARS-CoV-2 omicron in vivo.

The twenty-first century has already recorded more than ten major epidemics or pandemics of viral disease, including the devastating COVID-19. Novel effective antivirals with broad-spectrum coverage are urgently needed. Herein, we reported a novel broad-spectrum antiviral compound PAC5. Oral administration of PAC5 eliminated HBV cccDNA and reduced the large antigen load in distinct mouse models of HBV infection. Strikingly, oral administration of PAC5 in a hamster model of SARS-CoV-2 omicron (BA.1) infection significantly decreases viral loads and attenuates lung inflammation. Mechanistically, PAC5 binds to a pocket near Asp49 in the RNA recognition motif of hnRNPA2B1. PAC5-bound hnRNPA2B1 is extensively activated and translocated to the cytoplasm where it initiates the TBK1-IRF3 pathway, leading to the production of type I IFNs with antiviral activity. Our results indicate that PAC5 is a novel small-molecule agonist of hnRNPA2B1, which may have a role in dealing with emerging infectious diseases now and in the future.

Two different aging paths in human blood revealed by integrated analysis of gene Expression, mutation and alternative splicing.

Aging is a complex life process that human organs and tissues steadily and continuously decline. Aging has huge heterogeneity, which shows different aging rates among different individuals and in different tissues of the same individual. Many studies of aging are often contradictory and show little common signature. The integrated analysis of these transcriptome datasets will provide an unbiased global view of the aging process. Here, we integrated 8 transcriptome datasets including 757 samples from healthy human blood to study aging from three aspects of gene expression, mutations, and alternative splicing. Surprisingly, we found that transcriptome changes in blood are relatively independent of the chronological age. Further pseudotime analysis revealed two different aging paths (AgingPath1 and AgingPath2) in human blood. The differentially expressed genes (DEGs) along the two paths showed a limited overlap and are enriched in different biological processes. The mutations of DEGs in AgingPath1 are significantly increased in the aging process, while the opposite trend was observed in AgingPath2. Expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) analysis identified 304 important mutations that can affect both gene expression and alternative splicing during aging. Finally, by comparison between aging and Alzheimer's disease, we identified 37 common DEGs in AgingPath1, AgingPath2 and Alzheimer's disease. These genes may contribute to the shift from aging state to Alzheimer's disease. In summary, this study revealed the two aging paths and the related genes and mutations, which provides a new insight into aging and aging-related disease.

Screening of antibacterial compounds with novel structure from the FDA approved drugs using machine learning methods.

Bacterial infection is one of the most important factors affecting the human life span. Elderly people are more harmed by bacterial infections due to their deficits in immunity. Because of the lack of new antibiotics in recent years, bacterial resistance has increasingly become a serious problem globally. In this study, an antibacterial compound predictor was constructed using the support vector machines and random forest methods and the data of the active and inactive antibacterial compounds from the ChEMBL database. The results showed that both models have excellent prediction performance (mean accuracy >0.9 and mean AUC >0.9 for the two models). We used the predictor to screen potential antibacterial compounds from FDA-approved drugs in the DrugBank database. The screening results showed that 1087 small-molecule drugs have potential antibacterial activity and 154 of them are FDA-approved antibacterial drugs, which accounts for 76.2% of the approved antibacterial drugs collected in this study. Through molecular fingerprint similarity analysis and common substructure analysis, we screened 8 predicted antibacterial small-molecule compounds with novel structures compared with known antibacterial drugs, and 5 of them are widely used in the treatment of various tumors. This study provides a new insight for predicting antibacterial compounds by using approved drugs, the predicted compounds might be used to treat bacterial infections and extend lifespan.

The genome of medicinal leech (Whitmania pigra) and comparative genomic study for exploration of bioactive ingredients.

BACKGROUND: Leeches are classic annelids that have a huge diversity and are closely related to people, especially medicinal leeches. Medicinal leeches have been widely utilized in medicine based on the pharmacological activities of their bioactive ingredients. Comparative genomic study of these leeches enables us to understand the difference among medicinal leeches and other leeches and facilitates the discovery of bioactive ingredients. RESULTS: In this study, we reported the genome of Whitmania pigra and compared it with Hirudo medicinalis and Helobdella robusta. The assembled genome size of W. pigra is 177 Mbp, close to the estimated genome size. Approximately about 23% of the genome was repetitive. A total of 26,743 protein-coding genes were subsequently predicted. W. pigra have 12346 (46%) and 10295 (38%) orthologous genes with H. medicinalis and H. robusta, respectively. About 20 and 24% genes in W. pigra showed syntenic arrangement with H. medicinalis and H. robusta, respectively, revealed by gene synteny analysis. Furthermore, W. pigra, H. medicinalis and H. robusta expanded different gene families enriched in different biological processes. By inspecting genome distribution and gene structure of hirudin, we identified a new hirudin gene g17108 (hirudin_2) with different cysteine patterns. Finally, we systematically explored and compared the active substances in the genomes of three leech species. The results showed that W. pigra and H. medicinalis exceed H. robusta in both kinds and gene number of active molecules. CONCLUSIONS: This study reported the genome of W. pigra and compared it with other two leeches, which provides an important genome resource and new insight into the exploration and development of bioactive molecules of medicinal leeches.

Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma.

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.

Identification of hub ubiquitin ligase genes affecting Alzheimer's disease by analyzing transcriptome data from multiple brain regions.

The ubiquitin-proteasome system (UPS) plays crucial roles in numerous cellular functions. Dysfunction of the UPS shows certain correlations with the pathological changes in Alzheimer's disease (AD). This study aimed to explore the different impairments of the UPS in multiple brain regions and identify hub ubiquitin ligase (E3) genes in AD. The brain transcriptome, blood transcriptome and proteome data of AD were downloaded from a public database. The UPS genes were collected from the Ubiquitin and Ubiquitin-like Conjugation Database. The hub E3 genes were defined as the differentially expressed E3 genes shared by more than three brain regions. E3Miner and UbiBrowser were used to predict the substrate of hub E3. This study shows varied impairment of the UPS in different brain regions in AD. Furthermore, we identify seven hub E3 genes (CUL1, CUL3, EIF3I, NSMCE1, PAFAH1B1, RNF175, and UCHL1) that are downregulated in more than three brain regions. Three of these genes (CUL1, EIF3I, and NSMCE1) showed consistent low expression in blood. Most of these genes have been reported to promote AD, whereas the impact of RNF175 on AD is not yet reported. Further analysis revealed a potential regulatory mechanism by which hub E3 and its substrate genes may affect transcription functions and then exacerbate AD. This study identified seven hub E3 genes and their substrate genes affect transcription functions and then exacerbate AD. These findings may be helpful for the development of diagnostic biomarkers and therapeutic targets for AD.

Systematic metabolic analysis of potential target, therapeutic drug, diagnostic method and animal model applicability in three neurodegenerative diseases.

Considerable evidence suggests that metabolic abnormalities are associated with neurodegenerative diseases. This study aimed to conduct a systematic metabolic analysis of Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD). Human and mouse model microarray datasets were downloaded from the Gene Expression Omnibus database. The metabolic genes and pathways were collected from the Recon 3D human metabolic model. Drug and target information was obtained from the DrugBank database. This study identified ATP1A1, ATP6V1G2, GOT1, HPRT1, MAP2K1, PCMT1 and PLK2 as key metabolic genes that were downregulated in AD, PD and HD. We screened 57 drugs that target these genes, such as digoxin, ouabain and diazoxide. This study constructed multigene diagnostic models for AD, PD and HD by using metabolic gene expression profiles in blood, all models showed high accuracy (AUC > 0.8) both in the experimental and validation sets. Furthermore, analysis of animal models showed that there was almost no consistency among the metabolic changes between mouse models and human diseases. This study systematically revealed the metabolic damage among AD, PD, and HD and uncovered the differences between animal models and human diseases. This information may be helpful for understanding the metabolic mechanisms and drug development for neurodegenerative diseases.

Novel pathways of HIV latency reactivation revealed by integrated analysis of transcriptome and target profile of bryostatin.

The reactivation of HIV latency cell will be necessary to curing HIV infection. Although many latency-reversal agents (LRAs) have proven effective to reactivate the latency cell, there is a lack of any systematic analysis of the molecular targets of these LRAs and related pathways in the context of transcriptome. In this study, we performed an integrated analysis of the target profile of bryostatin and transcriptome of the reactivated CD4+ T cells after exposing to bryostatin. The result showed a distinct gene expression profile between latency cells and bryostatin reactivated cells. We found bryostatin can target multiple types of protein other than only protein kinase C. Functional network analysis of the target profile and differential expressed genes suggested that bryostatin may activate a few novel pathways such as pyrimidine metabolism, purine metabolism and p53 signaling pathway, besides commonly known pathways DNA replication, cell cycle and so on. The results suggest that bryostatin may reactivate the HIV-latent cells through up-regulation of pyrimidine and purine metabolism or through starting the cell-cycle arrest and apoptosis induced by up-regulation of p53 signaling pathway. Our study provides some novel insights into the role of bryostatin and its affected pathways in controlling HIV latency and reactivation.

Gain and loss events in the evolution of the apolipoprotein family in vertebrata.

BACKGROUND: Various apolipoproteins widely distributed among vertebrata play key roles in lipid metabolism and have a direct correlation with human diseases as diagnostic markers. However, the evolutionary progress of apolipoproteins in species remains unclear. Nine human apolipoproteins and well-annotated genome data of 30 species were used to identify 210 apolipoprotein family members distributed among species from fish to humans. Our study focused on the evolution of nine exchangeable apolipoproteins (ApoA-I/II/IV/V, ApoC-I~IV and ApoE) from Chondrichthyes, Holostei, Teleostei, Amphibia, Sauria (including Aves), Prototheria, Marsupialia and Eutheria. RESULTS: In this study, we reported the overall distribution and the frequent gain and loss evolutionary events of apolipoprotein family members in vertebrata. Phylogenetic trees of orthologous apolipoproteins indicated evident divergence between species evolution and apolipoprotein phylogeny. Successive gain and loss events were found by evaluating the presence and absence of apolipoproteins in the context of species evolution. For example, only ApoA-I and ApoA-IV occurred in cartilaginous fish as ancient apolipoproteins. ApoA-II, ApoE, and ApoC-I/ApoC-II were found in Holostei, Coelacanthiformes, and Teleostei, respectively, but the latter three apolipoproteins were absent from Aves. ApoC-I was also absent from Cetartiodactyla. The apolipoprotein ApoC-III emerged in terrestrial animals, and ApoC-IV first arose in Eutheria. The results indicate that the order of the emergence of apolipoproteins is most likely ApoA-I/ApoA-IV, ApoE, ApoA-II, ApoC-I/ApoC-II, ApoA-V, ApoC-III, and ApoC-IV. CONCLUSIONS: This study reveals not only the phylogeny of apolipoprotein family members in species from Chondrichthyes to Eutheria but also the occurrence and origin of new apolipoproteins. The broad perspective of gain and loss events and the evolutionary scenario of apolipoproteins across vertebrata provide a significant reference for the research of apolipoprotein function and related diseases.

Interactome Analyses implicated CAMK2A in the genetic predisposition and pharmacological mechanism of Bipolar Disorder.

Bipolar disorder (BPD) is a severe mental illness characterized by fluctuations in mood states, behaviors and energy levels. Growing evidence suggests that genes associated with specific illnesses tend to interact together and encode a tight protein-protein interaction (PPI) network, providing valuable information for understanding their pathogenesis. To gain insights into the genetic and physiological foundation of BPD, we conduct the physical PPI analysis of 184 BPD risk genes distilled from genome-wide association studies and exome sequencing studies. We have identified several hub genes (CAMK2A, HSP90AA1 and PLCG1) among those risk genes, and observed significant enrichment of the BPD risk genes in certain pathways such as calcium signaling, oxytocin signaling and circadian entrainment. Furthermore, while none of the 184 genetic risk genes are "well established" BPD drug targets, our PPI analysis showed that αCaMKII (encoded by CAMK2A) had direct physical PPIs with targets (HRH1, SCN5A and CACNA1E) of clinically used anti-manic BPD drugs, such as carbamazepine. We thus speculated that αCaMKII might be involved in the cellular pharmacological actions of those drugs. Using cultured rat primary cortical neurons, we found that carbamazepine treatment induced phosphorylation of αCaMKII in dose-dependent manners. Intriguingly, previous study showed that CAMK2A heterozygous knockout (CAMK2A+/-) mice exhibited infradian oscillation of locomotor activities that can be rescued by carbamazepine. Our data, in combination with previous studies, provide convergent evidence for the involvement of CAMK2A in the risk of BPD.

Low expression of aging-related NRXN3 is associated with Alzheimer disease: A systematic review and meta-analysis.

BACKGROUND: Alzheimer disease (AD) is a common neurodegenerative disorder with distinct pathological features, with aging considered the greatest risk factor. We explored how aging contributes to increased AD risk, and determined concurrent and coordinate changes (including genetic and phenotypic modifications) commonly exhibited in both normal aging and AD. METHODS: Using the Gene Expression Omnibus (GEO) database, we collected 1 healthy aging-related and 3 AD-related datasets of the hippocampal region. The normal aging dataset was divided into 3 age groups: young (20-40 years old), middle-aged (40-60 years old), and elderly (>60 years old). These datasets were used to analyze the differentially expressed genes (DEGs). The Gene Ontology (GO) terms, pathways, and function network analysis of these DEGs were analyzed. RESULTS: One thousand two hundred ninety-one DEGs were found to be shared in the natural aging groups and AD patients. Among the shared DEGs, ATP6V1E1, GNG3, NDUFV2, GOT1, USP14, and NAV2 have been previously found in both normal aging individuals and AD patients. Furthermore, using Java Enrichment of Pathways Extended to Topology (JEPETTO) analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we determined that changes in aging-related KEGG annotations may contribute to the aging-dependence of AD risk. Interestingly, NRXN3, the second most commonly deregulated gene identified in the present study, is known to carry a mutation in AD patients. According to functional network analysis, NRXN3 plays a critical role in synaptic functions involved in the cognitive decline associated with normal aging and AD. CONCLUSION: Our results indicate that the low expression of aging-related NRXN3 may increase AD risk, though the potential mechanism requires further clarification.

A strategy to find novel candidate anti-Alzheimer's disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants.

BACKGROUND: Alzheimer' disease (AD) is an ultimately fatal degenerative brain disorder that has an increasingly large burden on health and social care systems. There are only five drugs for AD on the market, and no new effective medicines have been discovered for many years. Chinese medicinal plants have been used to treat diseases for thousands of years, and screening herbal remedies is a way to develop new drugs. METHODS: We used molecular docking to screen 30,438 compounds from Traditional Chinese Medicine (TCM) against a comprehensive list of AD target proteins. TCM compounds in the top 0.5% of binding affinity scores for each target protein were selected as our research objects. Structural similarities between existing drugs from DrugBank database and selected TCM compounds as well as the druggability of our candidate compounds were studied. Finally, we searched the CNKI database to obtain studies on anti-AD Chinese plants from 2007 to 2017, and only clinical studies were included. RESULTS: A total of 1,476 compounds (top 0.5%) were selected as drug candidates. Most of these compounds are abundantly found in plants used for treating AD in China, especially the plants from two genera Panax and Morus. We classified the compounds by single target and multiple targets and analyzed the interactions between target proteins and compounds. Analysis of structural similarity revealed that 17 candidate anti-AD compounds were structurally identical to 14 existing approved drugs. Most of them have been reported to have a positive effect in AD. After filtering for compound druggability, we identified 11 anti-AD compounds with favorable properties, seven of which are found in anti-AD Chinese plants. Of 11 anti-AD compounds, four compounds 5,862, 5,863, 5,868, 5,869 have anti-inflammatory activity. The compound 28,814 mainly has immunoregulatory activity. The other six compounds have not yet been reported for any biology activity at present. DISCUSSION: Natural compounds from TCM provide a broad prospect for the screening of anti-AD drugs. In this work, we established networks to systematically study the connections among natural compounds, approved drugs, TCM plants and AD target proteins with the goal of identifying promising drug candidates. We hope that our study will facilitate in-depth research for the treatment of AD in Chinese medicine.

Identification of metabolism-associated genes and pathways involved in different stages of clear cell renal cell carcinoma.

The lack of early diagnostic markers and novel therapeutic targets for clear cell renal cell carcinoma (ccRCC) negatively affects patient prognosis. Cancer metabolism is an attractive area for the understanding of the molecular mechanism of carcinogenesis. The present study attempted to identify metabolic changes from the view of the expression of metabolism-associated genes between control samples and those of ccRCC at different disease stages. Data concerning ccRCC gene expression obtained by RNA-sequencing was obtained from The Cancer Genome Atlas and data on metabolism-associated genes were extracted using the Recon2 model. Following analysis of differential gene expression, multiple differentially expressed metabolic genes at each tumor-node-metastasis disease stage were identified, compared with control non-disease samples: Metabolic genes (305) were differentially expressed in stage I disease, 323 in stage II disease, 355 in stage III disease and 363 in stage IV disease. Following enrichment analysis for differential metabolic genes, 22 metabolic pathways were identified to be dysregulated in multiple stages of ccRCC. Abnormalities in hormone, vitamin, glucose and lipid metabolism were present in the early stages of the disease, with dysregulation to reactive oxygen species detoxification and amino acid metabolism pathways occurring with advanced disease stages, particularly to valine, leucine, and isoleucine metabolism, which was substantially dysregulated in stage IV disease. The xenobiotic metabolism pathway, associated with multiple cytochrome P450 family genes, was dysregulated in each stage of the disease. This pathway is worthy of substantial attention since it may aid understanding of drug resistance in ccRCC. The results of the present study offer information to aid further research into early diagnostic biomarkers and therapeutic targets of ccRCC.

Folate Deficiency and Gene Polymorphisms of MTHFR, MTR and MTRR Elevate the Hyperhomocysteinemia Risk.

BACKGROUND: Hyperhomocysteinemia (HHcy) is an independent risk factor for cardiovascular diseases (CVDs). We aimed to investigate the joint effect of homocysteine metabolism gene polymorphisms, as well as the folate deficiency on the risk of HHcy in a Chinese hypertensive population. METHODS: This study enrolled 480 hypertensive patients aged 28 - 75 from six hospitals in different Chinese regions from 9/2005 - 12/2005. Known genotypes of methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, methionine synthase (MTR) A2756G, and methionine synthase reductase (MTRR) A66G were detected by PCRRFLP methods. Serum Hcy was measured by high-performance liquid chromatography and serum folate was measured by chemiluminescent immunoassay. RESULTS: MTHFR C677T and MTR A2756G can independently elevate the risk of HHcy (TT vs. CC + CT, p < 0.001 and AG + GG vs. AA, p = 0.026, respectively), whereas MTHFR A1298C decreased HHcy risk (AC + CC vs. AA, p < 0.001) and showed a protective effect against HHcy risk. Importantly, the joint effect of these risk genotypes showed significantly higher odds of HHcy than non-risk genotypes, especially the patients with four risk genotypes. It is noteworthy that this deleterious effect was aggravated by folate deficiency. These findings were verified by generalized multifactor dimensionality reduction model (p = 0.001) and a cumulative effects model (p < 0.001). CONCLUSIONS: We have first demonstrated that the joint effect of homocysteine metabolism gene polymorphisms and folate deficiency lead to dramatic elevations in the HHcy risk.

Different impairment of immune and inflammation functions in short and long-term after ischemic stroke.

Ischemic stroke therapy and prognosis outcomes largely depend on the time periods after symptom onset. This study aims to explore the difference of global gene expression profiles and impairment of biological functions between short-term and long-term after stroke onset. We compared three short-term (3 h, 5 h and 24 h) and a long-term (6-month) gene expression levels by a multi-platform microarray data integration method. RankProd was used to calculate the differentially expressed genes between stroke patients and controls. DAVID Bioinformatics Resources was utilized to determine affected biological functions. Consensus cluster and hierarchical cluster methods were employed to compare the gene expression patterns of the commonly biological functions among these four time course groups. The results showed that severe impairment of inflammation and immune related functions in 5 h and 24 h after symptom onset. However, these functions were less affected in the 3 h and the 6-month groups. In addition, several key genes (CCL20, THBS1, EREG, and IL6 et al.) were dramatically down-regulated in 5 h and 24 h groups, whereas these genes showed no change or even a slight contrary expression in 3 h or 6-month groups. This study has identified the large differences of altered immune and inflammation functions based on gene levels between short and long-term after stroke onset. The findings provide valuable insight into the clinical practice and prognosis evaluation of ischemic stroke.

Meta-Analysis of Parkinson's Disease and Alzheimer's Disease Revealed Commonly Impaired Pathways and Dysregulation of NRF2-Dependent Genes.

Many lines of evidence suggest that Parkinson's disease (PD) and Alzheimer's disease (AD) have common characteristics, such as mitochondrial dysfunction and oxidative stress. As the underlying molecular mechanisms are unclear, we perform a meta-analysis with 9 microarray datasets of PD studies and 7 of AD studies to explore it. Functional enrichment analysis revealed that PD and AD both showed dysfunction in the synaptic vesicle cycle, GABAergic synapses, phagosomes, oxidative phosphorylation, and TCA cycle pathways, and AD had more enriched genes. Comparing the differentially expressed genes between AD and PD, we identified 54 common genes shared by more than six tissues. Among them, 31 downregulated genes contained the antioxidant response element (ARE) consensus sequence bound by NRF2. NRF2 is a transcription factor, which protects cells against oxidative stress through coordinated upregulation of ARE-driven genes. To our surprise, although NRF2 was upregulated, its target genes were all downregulated. Further exploration found that MAFF was upregulated in all tissues and significantly negatively correlated with the 31 NRF2-dependent genes in diseased conditions. Previous studies have demonstrated over-expressed small MAFs can form homodimers and act as transcriptional repressors. Therefore, MAFF might play an important role in dysfunction of NRF2 regulatory network in PD and AD.

The identification and molecular mechanism of anti-stroke traditional Chinese medicinal compounds.

Stroke is a worldwide epidemic disease with high morbidity and mortality. The continuously exploration of anti-stroke medicines and molecular mechanism has a long way to go. In this study, in order to screen candidate anti-stroke compounds, more than 60000 compounds from traditional Chinese medicine (TCM) database were computationally analyzed then docked to the 15 known anti-stroke targets. 192 anti-stroke plants for clinical therapy and 51 current anti-stroke drugs were used to validate docking results. Totally 2355 candidate anti-stroke compounds were obtained. Among these compounds, 19 compounds are structurally identical with 16 existing drugs in which part of them have been used for anti-stroke treatment. Furthermore, these candidate compounds were significantly enriched in anti-stroke plants. Based on the above results, the compound-target-plant network was constructed. The network reveals the potential molecular mechanism of anti-stroke for these compounds. Most of candidate compounds and anti-stroke plants are tended to interact with target NOS3, PSD-95 and PDE5A. Finally, using ADMET filter, we identified 35 anti-stroke compounds with favorable properties. The 35 candidate anti-stroke compounds offer an opportunity to develop new anti-stroke drugs and will improve the research on molecular mechanism of anti-stroke.