In-Silico Study of Immune System Associated Genes in Case of Type-2 Diabetes With Insulin Action and Resistance, and/or Obesity

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA Collapse

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Grants

• R01 HL143885 NHLBI NIH HHS
• R01 HL163262 NHLBI NIH HHS
• R01 HL142302 NHLBI NIH HHS
• R01 HL151152 NHLBI NIH HHS
• N01HC25195 NHLBI NIH HHS
• R01 HG010297 NHGRI NIH HHS
• R01 HL092577 NHLBI NIH HHS
• P20 MD000170 NIMHD NIH HHS
• 75N92019D00031 NHLBI NIH HHS
• R01 HD057194 NICHD NIH HHS
• UL1 TR000371 NCATS NIH HHS
• R01 DK122503 NIDDK NIH HHS

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Affiliation(s)

Hanfei Xu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Shreyash Gupta Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ian Dinsmore Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Abbey Kollu Department of Psychology and Neuroscience, University of North Carolina, 235 E. Cameron Avenue, Chapel Hill, NC, 27599, USA
Anne Marie Cawley Marsico Lung Institute, University of North Carolina, 125 Mason Farm Rd, Chapel Hill, NC, 27599, USA
Mohammad Y. Anwar Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Hung-Hsin Chen Institute of Biomedical Sciences, Academia Sinica, No. 128, Section 2, Academia Rd., Taipei, Nangang District, 115201, Taiwan Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Lauren E. Petty Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Sudha Seshadri Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio, 8300 Floyd Curl Drive, San Antonio, TX, 78229, USA
Misa Graff Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Piper Below Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Jennifer A. Brody Department of Medicine, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Seattle, WA, 98101, USA
Geetha Chittoor Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Susan P. Fisher-Hoch Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Nancy L. Heard-Costa Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA, 01702, USA Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, 72 E Concord St, Boston, MA, 02118, USA
Daniel Levy Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD, 20892, USA
Honghuang Lin Department of Medicine, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, USA
Ruth JF. Loos Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, 2200, Copenhagen, Denmark
Joseph B. Mccormick Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Jerome I. Rotter Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90502, USA
Tooraj Mirshahi Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Christopher D. Still Center for Obesity and Metabolic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Anita Destefano Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
L. Adrienne Cupples Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Karen L Mohlke Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
Kari E. North Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Anne E. Justice Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ching-Ti Liu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA

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Deficiency of spns1 exacerbates per- and polyfluoroalkyl substances mediated hepatic toxicity and steatosis in zebrafish (Danio rerio)

Per- and polyfluoroalkyl substances (PFAS) are man-made long-lasting chemical compounds that are found in everyday household items. Today they occur in the environment as a major group of pollutants. These compounds are broadly used in commercial product preparation such as, for food packaging, nonstick coatings, and firefighting foam. In humans, PFAS can cause immune disorders, impaired fetal development, abnormal skeletal tissue development, osteoarthritis, thyroid dysfunctions, cholesterol changes, affect insulin regulation and lipid metabolism, and are also involved in the development of fatty liver disease. In the current study, we investigated the effect of low, but physiologically relevant, concentrations of perfluorooctanoic acid (PFOA), heptafluorobutyric acid (HFBA), and perfluorotetradecanoic acid (PFTA) on gene expression markers of an inflammatory response (tnfa, il-1b, il-6, rplp0, edem1, and dnajc3a), unfolded protein response (UPR) (bip, atf4a, atf6, xbp1, and ddit3), senescence (p21, pai1, smp30, mdm2, and baxa), lipogenesis (scd1, acc, srebp1, pparγ, and fasn) and autophagy (p62, atg3, atg7, rab7, lc3b, and becn1) in AB wild-type (+/+), spns1-wt sibling (+/+), (+/-) and spns1 homozygous mutant (-/-) zebrafish embryos. Exposure to PFOA and HFBA (50 and 100 nM) specifically modulated inflammatory, UPR, senescence, lipogenic, and autophagy signaling in spns1-wt (+/+), (+/-), and spns1-mutant (-/-) zebrafish embryos. Furthermore, PFOA, but not HFBA, upregulated lipogenic-related gene expression and enhanced hepatic steatosis in spns1-wt (+/+), (+/-) zebrafish embryos. Combined exposure to PFOA, HFBA, and PFTA differentially expressed inflammatory, senescence, lipogenic, and autophagy-associated gene expression in spns1-mutant (-/-) zebrafish embryos compared with spns1-wt (+/+), (+/-) and AB-wt (+/+) zebrafish embryos. In addition, chronic exposure (∼2 months) to PFOA (120-600 nM) upregulated the expression of hepatic lipogenic and steatosis biomarkers in AB-wt (+/+) zebrafish. Collectively, our data suggest that acute/chronic physiologically relevant concentrations of PFOA upregulate inflammatory, UPR, senescence, and lipogenic signaling in spns1-wt (+/+), (+/-) and spns1-mutant (-/-) zebrafish embryos as well as in two-month-old AB-wt zebrafish, by targeting autophagy and hence induces toxicity that could promote nonalcoholic fatty liver disease.

Genome-Wide Identification of lncRNA and mRNA for Diagnosing Type 2 Diabetes in Saudi Arabia

Purpose

According to the World Health Organization, Saudi Arabia ranks seventh worldwide in the number of patients with diabetes mellitus. To our knowledge, no research has addressed the potential of noncoding RNA as a diagnostic and/or management biomarker for patients with type 2 diabetes mellitus (T2DM) living in high-altitude areas. This study aimed to identify molecular biomarkers influencing patients with T2DM living in high-altitude areas by analyzing lncRNA and mRNA.

Patients and Methods

RNA sequencing and bioinformatics analyses were used to identify significantly expressed lncRNAs and mRNAs in T2DM and healthy control groups. Coding potential was analyzed using coding-noncoding indices, the coding potential calculator, and PFAM, and the lncRNA function was predicted using Pearson's correlation. Differentially expressed transcripts between the groups were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify the biological functions of both lncRNAs and mRNAs.

Results

We assembled 1766 lncRNAs in the T2DM group, of which 582 were novel. This study identified three lncRNA target genes (KLF2, CREBBP, and REL) and seven mRNAs (PIK3CD, PIK3R5, IL6R, TYK2, ZAP70, LAMTOR4, and SSH2) significantly enriched in important pathways, playing a role in the progression of T2DM.

Conclusion

To the best of our knowledge, this comprehensive study is the first to explore the applicability of certain lncRNAs as diagnostic or management biomarkers for T2DM in females in Taif City, Saudi Arabia through the genome-wide identification of lncRNA and mRNA profiling using RNA seq and bioinformatics analysis. Our findings could help in the early diagnosis of T2DM and in designing effective therapeutic targets.

Molecular Genetics of Abnormal Redox Homeostasis in Type 2 Diabetes Mellitus

Numerous studies have shown that oxidative stress resulting from an imbalance between the production of free radicals and their neutralization by antioxidant enzymes is one of the major pathological disorders underlying the development and progression of type 2 diabetes (T2D). The present review summarizes the current state of the art advances in understanding the role of abnormal redox homeostasis in the molecular mechanisms of T2D and provides comprehensive information on the characteristics and biological functions of antioxidant and oxidative enzymes, as well as discusses genetic studies conducted so far in order to investigate the contribution of polymorphisms in genes encoding redox state-regulating enzymes to the disease pathogenesis.

Role of ZNF143 and Its Association with Gene Expression Patterns, Noncoding Mutations, and the Immune System in Human Breast Cancer

The function of noncoding sequence variations at ZNF143 binding sites in breast cancer cells is currently not well understood. Distal elements and promoters, also known as cis-regulatory elements, control the expression of genes. They may be identified by functional genomic techniques and sequence conservation, and they frequently show cell- and tissue-type specificity. The creation, destruction, or modulation of TF binding and function may be influenced by genetic modifications at TF binding sites that affect the binding affinity. Therefore, noncoding mutations that affect the ZNF143 binding site may be able to alter the expression of some genes in breast cancer. In order to understand the relationship among ZNF143, gene expression patterns, and noncoding mutations, we adopted an integrative strategy in this study and paid close attention to putative immunological signaling pathways. The immune system-related pathways ErbB, HIF1a, NF-kB, FoxO, JAK-STAT, Wnt, Notch, cell cycle, PI3K-AKT, RAP1, calcium signaling, cell junctions and adhesion, actin cytoskeleton regulation, and cancer pathways are among those that may be significant, according to the overall analysis.

An Approach for Systems-Level Understanding of Prostate Cancer from High-Throughput Data Integration to Pathway Modeling and Simulation

To understand complex diseases, high-throughput data are generated at large and multiple levels. However, extracting meaningful information from large datasets for comprehensive understanding of cell phenotypes and disease pathophysiology remains a major challenge. Despite tremendous advances in understanding molecular mechanisms of cancer and its progression, current knowledge appears discrete and fragmented. In order to render this wealth of data more integrated and thus informative, we have developed a GECIP toolbox to investigate the crosstalk and the responsible genes'/proteins' connectivity of enriched pathways from gene expression data. To implement this toolbox, we used mainly gene expression datasets of prostate cancer, and the three datasets were GSE17951, GSE8218, and GSE1431. The raw samples were processed for normalization, prediction of differentially expressed genes, and the prediction of enriched pathways for the differentially expressed genes. The enriched pathways have been processed for crosstalk degree calculations for which number connections per gene, the frequency of genes in the pathways, sharing frequency, and the connectivity have been used. For network prediction, protein-protein interaction network database FunCoup2.0 was used, and cytoscape software was used for the network visualization. In our results, we found that there were enriched pathways 27, 45, and 22 for GSE17951, GSE8218, and GSE1431, respectively, and 11 pathways in common between all of them. From the crosstalk results, we observe that focal adhesion and PI3K pathways, both experimentally proven central for cellular output upon perturbation of numerous individual/distinct signaling pathways, displayed highest crosstalk degree. Moreover, we also observe that there were more critical pathways which appear to be highly significant, and these pathways are HIF1a, hippo, AMPK, and Ras. In terms of the pathways' components, GSK3B, YWHAE, HIF1A, ATP1A3, and PRKCA are shared between the aforementioned pathways and have higher connectivity with the pathways and the other pathway components. Finally, we conclude that the focal adhesion and PI3K pathways are the most critical pathways, and since for many other pathways, high-rank enrichment did not translate to high crosstalk degree, the global impact of one pathway on others appears distinct from enrichment.

COVID-19 Candidate Genes and Pathways Potentially Share the Association with Lung Cancer

COVID-19 is considered as the most challenging in the current situation but lung cancer is also the leading cause of death in the global population. These two malignancies are among the leading human diseases and are highly complex in terms of diagnostic and therapeutic approaches as well as the most frequent and highly complex and heterogeneous in nature. Based on the latest update, it is known that the patients suffering from lung cancer, are considered to be significantly at higher risk of COVID-19 infection in terms of survival and there are a number of evidences which support the hypothesis that these diseases may share the same functions and functional components. Multi-level unwanted alterations such as (epi-)genetic alterations, changes at the transcriptional level, and altered signaling pathways (receptor, cytoplasmic, and nuclear level) are the major sources which promote a number of complex diseases and such heterogeneous level of complexities are considered as the major barrier in the development of therapeutics. With so many challenges, it is critical to understand the relationships and the common shared aberrations between them which is difficult to unravel and understand. A simple approach has been applied for this study where differential gene expression analysis, pathway enrichment, and network level understanding are carried out. Since, gene expression changes and genomic alterations are related to the COVID-19 and lung cancer but their pattern varies significantly. Based on the recent studies, it appears that the patients suffering from lung cancer and and simultaneously infected with COVID-19, then survival chance is lessened. So, we have designed our goal to understand the genes commonly overexpressed and commonly enriched pathways in case of COVID-19 and lung cancer. For this purpose, we have presented the summarized review of the previous works where the pathogenesis of lung cancer and COVID-19 infection have been focused and we have also presented the new finding of our analysis. So, this work not only presents the review work but also the research work. This review and research study leads to the conclusion that growth promoting pathways (EGFR, Ras, and PI3K), growth inhibitory pathways (p53 and STK11), apoptotic pathways (Bcl- 2/Bax/Fas), and DDR pathways and genes are commonly and dominantly altered in both the cases COVID-19 and lung cancer.

Genomic profiling and network-level understanding uncover the potential genes and the pathways in hepatocellular carcinoma

Data integration with phenotypes such as gene expression, pathways or function, and protein-protein interactions data has proven to be a highly promising technique for improving human complex diseases, particularly cancer patient outcome prediction. Hepatocellular carcinoma is one of the most prevalent cancers, and the most common cause is chronic HBV and HCV infection, which is linked to the majority of cases, and HBV and HCV play a role in multistep carcinogenesis progression. We examined the list of known hepatocellular carcinoma biomarkers with the publicly available expression profile dataset of hepatocellular carcinoma infected with HCV from day 1 to day 10 in this study. The study covers an overexpression pattern for the selected biomarkers in clinical hepatocellular carcinoma patients, a combined investigation of these biomarkers with the gathered temporal dataset, temporal expression profiling changes, and temporal pathway enrichment following HCV infection. Following a temporal analysis, it was discovered that the early stages of HCV infection tend to be more harmful in terms of expression shifting patterns, and that there is no significant change after that, followed by a set of genes that are consistently altered. PI3K, cAMP, TGF, TNF, Rap1, NF-kB, Apoptosis, Longevity regulating pathway, signaling pathways regulating pluripotency of stem cells, Cytokine-cytokine receptor interaction, p53 signaling, Wnt signaling, Toll-like receptor signaling, and Hippo signaling pathways are just a few of the most commonly enriched pathways. The majority of these pathways are well-known for their roles in the immune system, infection and inflammation, and human illnesses like cancer. We also find that ADCY8, MYC, PTK2, CTNNB1, TP53, RB1, PRKCA, TCF7L2, PAK1, ITPR2, CYP3A4, UGT1A6, GCK, and FGFR2/3 appear to be among the prominent genes based on the networks of genes and pathways based on the copy number alterations, mutations, and structural variants study.

The effectiveness of patient-centered care vs. usual care in type 2 diabetes self-management: A systematic review and meta-analysis

Background

Patient-centered care in diabetes self-management might be a significant factor in improving health outcomes of adults with type 2 diabetes, yet the supporting evidence is inadequate. This review aimed at assessing the effectiveness of patient-centered self-management care interventions on glycemic control (HbA1c) and self-care behaviors compared with usual care.

Methods

CINAHL, PubMed, Cochrane Library, Google Scholar, and the HEC Digital Library were searched for studies in English language that assessed patient-centered self-management educational and/or behavioral interventions in adults aged 18 years or older with type 2 diabetes from 2005 to 2020. Interventional studies with at least 3 months of follow-up and reporting on self-care outcomes such as glycemic control (HbA1c) and self-care behaviors including diet control, physical activity, foot care, and medication adherence were included.

Results

Of 168 identified records, 24 were found eligible comprising 20 RCTs and four QESs with total 4,083 participants. The meta-analysis involved 19 RCTs that provided enough information for a pooled estimate of HbA1c. Compared with the control group, patient-centered self-management interventions significantly lowered HbA1c, -0.56 (95% CI -0.79, -0.32). Stratified analysis for HbA1c with respect to various aspects of intervention showed larger effects in interventions employing both educational and behavioral components, -0.66 (95% CI -0.97, -0.34); spanned over shorter (<03 months) duration, -0.85 (95% CI -1.28, -0.43); administered by nurses, -0.80 (95% CI -1.44, -0.16); and delivered in community settings -0.70 (95% CI -1.14, -0.26).

Conclusion

This systematic review provided evidence supporting the effectiveness of patient-centered self-management care interventions in improving glycemic control and self-care behaviors in adults with type 2 diabetes and identified key features of intervention contributing toward success.

Synthesis of Silver Nano Particles Using Myricetin and the In-Vitro Assessment of Anti-Colorectal Cancer Activity: In-Silico Integration

The creation of novel anticancer treatments for a variety of human illnesses, including different malignancies and dangerous microbes, also potentially depends on nanoparticles including silver. Recently, it has been successful to biologically synthesize metal nanoparticles using plant extracts. The natural flavonoid 3,3′, 4′, 5,5′, and 7 hexahydroxyflavon (myricetin) has anticancer properties. There is not much known about the regulatory effects of myricetin on the possible cell fate-determination mechanisms (such as apoptosis/proliferation) in colorectal cancer. Because the majority of investigations related to the anticancer activity of myricetin have dominantly focused on the enhancement of tumor cell uncontrolled growth (i.e., apoptosis). Thus, we have decided to explore the potential myricetin interactors and the associated biological functions by using an in-silico approach. Then, we focused on the main goal of the work which involved the synthesis of silver nanoparticles and the labeling of myricetin with it. The synthesized silver nanoparticles were examined using UV-visible spectroscopy, dynamic light scattering spectroscopy, Fourier transform infrared spectroscopy, and scanning electron microscopy. In this study, we have investigated the effects of myricetin on colorectal cancer where numerous techniques were used to show myricetin’s effect on colon cancer cells. Transmission Electron Microscopy was employed to monitor morphological changes. Furthermore, we have combined the results of the colorectal cancer gene expression dataset with those of the myricetin interactors and pathways. Based on the results, we conclude that myricetin is able to efficiently kill human colorectal cancer cell lines. Since, it shares important biological roles and possible route components and this myricetin may be a promising herbal treatment for colorectal cancer as per an in-silico analysis of the TCGA dataset.

Novel insight into the aetiology of rheumatoid arthritis gained by a cross-tissue transcriptome-wide association study

BACKGROUND

Although genome-wide association studies (GWASs) have identified more than 100 loci associated with rheumatoid arthritis (RA) susceptibility, the causal genes and biological mechanisms remain largely unknown.

METHODS

A cross-tissue transcriptome-wide association study (TWAS) using the unified test for molecular signaturestool was performed to integrate GWAS summary statistics from 58 284 individuals (14 361 RA cases and 43 923 controls) with gene-expression matrix in the Genotype-Tissue Expression project. Subsequently, a single tissue by using FUSION software was conducted to validate the significant associations. We also compared the TWAS with different gene-based methodologies, including Summary Data Based Mendelian Randomization (SMR) and Multimarker Analysis of Genomic Annotation (MAGMA). Further in silico analyses (conditional and joint analysis, differential expression analysis and gene-set enrichment analysis) were used to deepen our understanding of genetic architecture and comorbidity aetiology of RA.

RESULTS

We identified a total of 47 significant candidate genes for RA in both cross-tissue and single-tissue test after multiple testing correction, of which 40 TWAS-identified genes were verified by SMR or MAGMA. Among them, 13 genes were situated outside of previously reported significant loci by RA GWAS. Both TWAS-based and MAGMA-based enrichment analyses illustrated the shared genetic determinants among autoimmune thyroid disease, asthma, type I diabetes mellitus and RA.

CONCLUSION

Our study unveils 13 new candidate genes whose predicted expression is associated with risk of RA, providing new insights into the underlying genetic architecture of RA.

Potential and Therapeutic Roles of Diosmin in Human Diseases

Because of their medicinal characteristics, effectiveness, and importance, plant-derived flavonoids have been a possible subject of research for many years, particularly in the last decade. Plants contain a huge number of flavonoids, and Diosmin, a flavone glycoside, is one of them. Numerous in-vitro and in-vivo studies have validated Diosmin’s extensive range of biological capabilities which present antioxidative, antihyperglycemic, anti-inflammatory, antimutagenic, and antiulcer properties. We have presented this review work because of the greater biological properties and influences of Diosmin. We have provided a brief overview of Diosmin, its pharmacology, major biological properties, such as anti-cancer, anti-diabetic, antibacterial, anticardiovascular, liver protection, and neuroprotection, therapeutic approach, potential Diosmin targets, and pathways that are known to be associated with it.

Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancer

Cancer is among the highly complex disease and renal cell carcinoma is the sixth-leading cause of cancer death. In order to understand complex diseases such as cancer, diabetes and kidney diseases, high-throughput data are generated at large scale and it has helped in the research and diagnostic advancement. However, to unravel the meaningful information from such large datasets for comprehensive and minute understanding of cell phenotypes and disease pathophysiology remains a trivial challenge and also the molecular events leading to disease onset and progression are not well understood. With this goal, we have collected gene expression datasets from publicly available dataset which are for two different stages (I and II) for renal cell carcinoma and furthermore, the TCGA and cBioPortal database have been utilized for clinical relevance understanding. In this work, we have applied computational approach to unravel the differentially expressed genes, their networks for the enriched pathways. Based on our results, we conclude that among the most dominantly altered pathways for renal cell carcinoma, are PI3K-Akt, Foxo, endocytosis, MAPK, Tight junction, cytokine-cytokine receptor interaction pathways and the major source of alteration for these pathways are MAP3K13, CHAF1A, FDX1, ARHGAP26, ITGBL1, C10orf118, MTO1, LAMP2, STAMBP, DLC1, NSMAF, YY1, TPGS2, SCARB2, PRSS23, SYNJ1, CNPPD1, PPP2R5E. In terms of clinical significance, there are large number of differentially expressed genes which appears to be playing critical roles in survival.

Thymoquinone (TQ) Inhibits Inflammation and Migration of THP-1 Macrophages: Mechanistic Insights into the Prevention of Atherosclerosis Using In-Vitro and In-Silico Analysis

Atherosclerosis is an inflammatory disease mediated by interferon (IFN-γ) in concert with cell adhesion molecules and chemokines. Thymoquinone (TQ), a flavonoid derived from Nigella sativa, is reported to have anti-inflammatory, antioxidant, and cardiovascular protective properties. We evaluated the effects of TQ on the key pathogenic stages of atherosclerosis, including cell viability, inflammatory gene expression, cell migration, and cholesterol efflux, on human THP-1 macrophages in-vitro. Moreover, in-silico analysis was performed to predict the molecular targets and signaling mechanisms. We demonstrated that TQ treatment had no effect on cell viability and decreased the expression of monocyte chemoattractant protein (MCP-1) and intercellular adhesion molecule (ICAM-1) in response to IFN-γ. In addition, we have also demonstrated that the THP-1 cell migration was inhibited by TQ in the absence or presence of MCP-1. Thymoquinone had no effect on cholesterol efflux from monocytes. In-silico analysis also identified several putative targets for TQ that are associated with inflammatory diseases and associated signaling pathways. Collectively, these results suggest that TQ has anti-inflammatory effects and may be a potential nutraceutical candidate for the prevention and treatment of atherosclerosis.

Gene Expression Profiling of Early Acute Febrile Stage of Dengue Infection and Its Comparative Analysis With Streptococcus pneumoniae Infection

Infectious diseases are the disorders caused by organisms such as bacteria, viruses, fungi, or parasites. Although many of them are permentantly hazardous, a number of them live in and on our bodies and they are normally harmless or even helpful. Under certain circumstances, some organisms may cause diseases and these infectious diseases may be passed directly from person to person or via intermediate vectors including insects and other animals. Dengue virus and Streptococcus pneumoniae are the critical and common sources of infectious diseases. So, it is critical to understand the gene expression profiling and their inferred functions in comparison to the normal and virus infected conditions. Here, we have analyzed the gene expression profiling for dengue hemorrhagic fever, dengue fever, and normal human dataset. Similar to it, streptococcus pneumoniae infectious data were analyzed and both the outcomes were compared. Our study leads to the conclusion that the dengue hemorrhagic fever arises in result to potential change in the gene expression pattern, and the inferred functions obviously belong to the immune system, but also there are some additional potential pathways which are critical signaling pathways. In the case of pneumoniae infection, 19 pathways were enriched, almost all these pathways are associated with the immune system and 17 of the enriched pathways were common with dengue infection except platelet activation and antigen processing and presentation. In terms of the comparative study between dengue virus and Streptococcus pneumoniae infection, we conclude that cell adhesion molecules (CAMs), MAPK signaling pathway, natural killer cell mediated cytotoxicity, regulation of actin cytoskeleton, and cytokine-cytokine receptor interaction are commonly enriched in all the three cases of dengue infection and Streptococcus pneumoniae infection, focal adhesion was enriched between classical dengue fever — dengue hemorrhagic fever, dengue hemorrhagic fever—normal samples, and SP, and antigen processing and presentation and Leukocyte transendothelial migration were enriched in classical dengue fever —normal samples, dengue hemorrhagic fever—normal samples, and Streptococcus pneumoniae infection.