A natural genetic variation screen identifies insulin signaling, neuronal communication, and innate immunity as modifiers of hyperglycemia in the absence of Sirt1

Physical Interaction ◽

Genetic Modifiers ◽

Natural Genetic Variation ◽

Neuronal Communication ◽

Risk Patients ◽

Genetic And Environmental Factors

ABSTRACTVariation in the onset, progression, and severity of symptoms associated with metabolic disorders such as diabetes impairs the diagnosis and treatment of at-risk patients. Diabetes symptoms, and patient variation in these symptoms, is attributed to a combination of genetic and environmental factors, but identifying the genes and pathways that modify diabetes in humans has proven difficult. A greater understanding of genetic modifiers and the ways in which they interact with metabolic pathways could improve the ability to predict a patient’s risk for severe symptoms, as well as enhance the development of individualized therapeutic approaches. In this study we use the Drosophila Genetic Reference Panel (DGRP) to identify genetic variation influencing hyperglycemia associated with loss of Sirt1 function. Through analysis of individual candidate functions, physical interaction networks, and Gene Set Enrichment Analysis (GSEA) we identify not only modifiers involved in canonical glucose metabolism and insulin signaling, but also genes important for neuronal signaling and the innate immune response. Furthermore, reducing the expression of several of these candidates suppressed hyperglycemia, making them ideal candidate therapeutic targets. These analyses showcase the diverse processes contributing to glucose homeostasis and open up several avenues of future investigation.

Natural genetic variation screen in Drosophila identifies Wnt signaling, mitochondrial metabolism, and redox homeostasis genes as modifiers of apoptosis

10.1101/670075 ◽

2019 ◽

Author(s):

Rebecca A.S. Palu ◽

Elaine Ong ◽

Kaitlyn Stevens ◽

Shani Chung ◽

Katie G. Owings ◽

...

Keyword(s):

Genetic Variation ◽

Wnt Signaling ◽

Redox Homeostasis ◽

Enrichment Analysis ◽

Mitochondrial Metabolism ◽

Gene Set Enrichment ◽

Natural Genetic Variation ◽

Effective Diagnosis ◽

The Impact

ABSTRACTApoptosis is the primary cause of degeneration in a number of neuronal, muscular, and metabolic disorders. These diseases are subject to a great deal of phenotypic heterogeneity in patient populations, primarily due to differences in genetic variation between individuals. This creates a barrier to effective diagnosis and treatment. Understanding how genetic variation influences apoptosis could lead to the development of new therapeutics and better personalized treatment approaches. In this study, we examine the impact of the natural genetic variation in the Drosophila Genetic Reference Panel (DGRP) on two models of apoptosis-induced retinal degeneration: overexpression of p53 or reaper (rpr). We identify a number of known apoptotic, neural, and developmental genes as candidate modifiers of degeneration. We also use Gene Set Enrichment Analysis (GSEA) to identify pathways that harbor genetic variation that impact these apoptosis models, including Wnt signaling, mitochondrial metabolism, and redox homeostasis. Finally, we demonstrate that many of these candidates have a functional effect on apoptosis and degeneration. These studies provide a number of avenues for modifying genes and pathways of apoptosis-related disease.

Bioinformatics Analysis of Autophagy-related LncRNAs in Esophageal Carcinoma

10.21203/rs.3.rs-60567/v1 ◽

2020 ◽

Author(s):

junbai fan ◽

Dan Wu ◽

Yi Ding

Keyword(s):

High Risk ◽

Esophageal Carcinoma ◽

Cox Regression ◽

Expression Profiles ◽

Enrichment Analysis ◽

Diagnostic Value ◽

The Cancer Genome Atlas ◽

High Risk Patients ◽

Abstract Background: Esophageal carcinoma (ESCA) is a malignant tumor with high invasiveness and mortality. Autophagy has multiple roles in the development of cancer; however, there are limited data on autophagy genes associated with long non-coding RNAs (lncRNAs) in ESCA. The purpose of this study was to screen potential diagnostic and prognostic molecules, and to identify gene co-expression networks associated with autophagy in ESCA. Methods: We downloaded transcriptome expression profiles from The Cancer Genome Atlas and autophagy-related gene data from the Human Autophagy Database, and analyzed the co-expression of mRNAs and lncRNAs. In addition, the diagnostic and prognostic value of autophagy-related lncRNAs was analyzed by multivariate Cox regression. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis was carried out for high-risk patients, and enriched pathways were analyzed by gene set enrichment analysis. Results: The results showed that genes of high-risk patients were enriched in protein export and spliceosome. Based on Cox stepwise regression and survival analysis, we identified seven autophagy-related lncRNAs with prognostic and diagnostic value, with the potential to be used as a combination to predict the prognosis of patients with ESCA. Finally, a co-expression network related to autophagy was constructed. Conclusion: These results suggest that autophagy-related lncRNAs and the spliceosome play important parts in the pathogenesis of ESCA. Our findings provide new insight into the molecular mechanism of ESCA and suggest a new method for improving its treatment.

Bioinformatics Analysis of Autophagy-related lncRNAs in Esophageal Carcinoma

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207324666210624143452 ◽

2021 ◽

Vol 24 ◽

Author(s):

Dan Wu ◽

Yi Ding ◽

JunBai Fan

Keyword(s):

High Risk ◽

Esophageal Carcinoma ◽

Cox Regression ◽

Expression Profiles ◽

Enrichment Analysis ◽

Diagnostic Value ◽

The Cancer Genome Atlas ◽

High Risk Patients ◽

Background: Esophageal carcinoma (ESCA) is a malignant tumor with high invasiveness and mortality. Autophagy has multiple roles in the development of cancer; however, there are limited data on autophagy genes associated with long non-coding RNAs (lncRNAs) in ESCA. The purpose of this study was to screen potential diagnostic and prognostic molecules and to identify gene co-expression networks associated with autophagy in ESCA. Methods: We downloaded transcriptome expression profiles from The Cancer Genome Atlas and autophagy-related gene data from the Human Autophagy Database and analyzed the co-expression of mRNAs and lncRNAs. In addition, the diagnostic and prognostic value of autophagy-related lncRNAs was analyzed by multivariate Cox regression. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis was carried out for high-risk patients, and enriched pathways were analyzed by gene set enrichment analysis. Results: The results showed that genes of high-risk patients were enriched in protein export and spliceosome. Based on Cox stepwise regression and survival analysis, we identified seven autophagy-related lncRNAs with prognostic and diagnostic value, with the potential to be used as a combination to predict the prognosis of patients with ESCA. Finally, a co-expression network related to autophagy was constructed. Conclusion: These results suggest that autophagy-related lncRNAs and the spliceosome play important parts in the pathogenesis of ESCA. Our findings provide new insight into the molecular mechanism of ESCA and suggest a new method for improving its treatment.

Pathway-Driven Approaches of Interaction between Oxidative Balance and Genetic Polymorphism on Metabolic Syndrome

Oxidative Medicine and Cellular Longevity ◽

10.1155/2017/6873197 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9 ◽

Cited By ~ 8

Author(s):

Ho-Sun Lee ◽

Taesung Park

Keyword(s):

Oxidative Stress ◽

Metabolic Syndrome ◽

Genetic Variation ◽

Enrichment Analysis ◽

Biological Pathways ◽

Glutathione Metabolism ◽

Redox Biology ◽

Reactive Protein ◽

Oxidative Balance

Despite evidences of association between basic redox biology and metabolic syndrome (MetS), few studies have evaluated indices that account for multiple oxidative effectors for MetS. Oxidative balance score (OBS) has indicated the role of oxidative stress in chronic disease pathophysiology. In this study, we evaluated OBS as an oxidative balance indicator for estimating risk of MetS with 6414 study participants. OBS is a multiple exogenous factor score for development of disease; therefore, we investigated interplay between oxidative balance and genetic variation for development of MetS focusing on biological pathways by using gene-set-enrichment analysis. As a result, participants in the highest quartile of OBS were less likely to be at risk for MetS than those in the lowest quartile. In addition, persons in the highest quartile of OBS had the lowest level of inflammatory markers including C-reactive protein and WBC. With GWAS-based pathway analysis, we found that VEGF signaling pathway, glutathione metabolism, and Rac-1 pathway were significantly enriched biological pathways involved with OBS on MetS. These findings suggested that mechanism of angiogenesis, oxidative stress, and inflammation can be involved in interaction between OBS and genetic variation on risk of MetS.

Natural genetic variation drives microbiome selection in the Caenorhabditis elegans gut

10.1101/2021.03.12.435148 ◽

2021 ◽

Author(s):

Fan Zhang ◽

Jessica L. Weckhorst ◽

Adrien Assié ◽

Ciara Hosea ◽

Christopher A. Ayoub ◽

...

Keyword(s):

Genetic Variation ◽

Caenorhabditis Elegans ◽

Signaling Pathways ◽

Insulin Signaling ◽

Natural Genetic Variation ◽

Microbiome Composition ◽

C Elegans ◽

Free Living Nematode ◽

Wild Strains ◽

The Stability

Host genetic landscapes can shape microbiome assembly in the animal gut by contributing to the establishment of distinct physiological environments. However, the genetic determinants contributing to the stability and variation of these microbiome types remain largely undefined. Here, we use the free-living nematode Caenorhabditis elegans to identify natural genetic variation among wild strains of C. elegans strains that drives assembly of distinct microbiomes. To achieve this, we first established a diverse model microbiome that represents the phylogenetic and functional diversity naturally found in the C. elegans microbiome. Using this community, we show that C. elegans utilizes immune, xenobiotic and metabolic signaling pathways to favor the assembly of different microbiome types. Variations in these pathways were associated with the enrichment for specific commensals, including the Alphaproteobacteria Ochrobactrum. Using RNAi and mutant strains, we showed that host selection for Ochrobactrum is mediated specifically by host insulin signaling pathways. Ochrobactrum recruitment is blunted in the absence of daf-2/IGFR and requires the insulin signaling transcription factors daf-16/FOXO and pqm-1/SALL2. Further, the ability of C. elegans to enrich for Ochrobactrum is correlated positively with host outcomes, as animals that develop faster are larger and have higher gut Ochrobactrum colonization as adults. These results highlight a new role for the highly conserved insulin signaling pathways in the regulation of microbiome composition in C. elegans.

Identification of biomarkers and pathways in hypertensive nephropathy based on the ceRNA regulatory network

10.21203/rs.2.16949/v1 ◽

2019 ◽

Author(s):

lei kang ◽

Zhen Wang ◽

Zhongjie Liu ◽

Yingxia Liu

Keyword(s):

Signaling Pathway ◽

Insulin Signaling ◽

Regulatory Network ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Insulin Signaling Pathway ◽

Chronic Hypertension ◽

Hypertensive Nephropathy ◽

Kegg Pathways

Abstract Background Hypertensive nephropathy (HTN) is a kind of renal injury caused by chronic hypertension, which seriously affect people’s life. The purpose of this study was to identify the potential biomarkers of HTN and understand its possible mechanisms.Methods The dataset numbered GSE28260 related to hypertensive and normotensive was downloaded from NCBI Gene Expression Omnibus. Then, the differentially expressed RNAs (DERs) were screened using R limma package, and functional analyses of DE-mRNA were performed by DAVID. Afterwards, a ceRNA network was established and KEGG pathway was analyzed based on the Gene Set Enrichment Analysis (GSEA) database. Finally, a ceRNA regulatory network directly associated with HTN was proposed.Results A total of 947 DERs were identified, including 900 DE-mRNAs, 20 DE-lncRNAs and 27 DE-miRNAs. Based on these DE-mRNAs, they were involved in biological processes such as fatty acid beta-oxidation, IRE1-mediated unfolded protein response, and transmembrane transport, and many KEGG pathways like glycine, serine and threonine metabolism, carbon metabolism. Subsequently, lncRNAs KCTD21-AS1, LINC00470 and SNHG14 were found to be hub nodes in the ceRNA regulatory network. KEGG analysis showed that insulin signaling pathway, glycine, serine and threonine metabolism, pathways in cancer, lysosome, and apoptosis was associated with hypertensive. Finally, insulin signaling pathway was screened to directly associate with HTN and was regulated by mRNAs PPP1R3C, PPKAR2B and AKT3, miRNA has-miR-107, and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG.Conclusions Insulin signaling pathway was directly associated with HTN, and miRNA has-miR-107 and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG were the biomarkers of HTN. These results would improve our understanding of the occurrence and development of HTN.

A Novel Prognostic Index Based on the Analysis of Glycolysis-Related Genes in Head and Neck Squamous Cell Carcinomas

Journal of Oncology ◽

10.1155/2020/7353874 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Yuchao Liu ◽

Shihua Yin

Keyword(s):

Head And Neck ◽

Squamous Cell ◽

Prognostic Significance ◽

Prognostic Index ◽

Enrichment Analysis ◽

Prognostic Indicator ◽

Low Risk ◽

The Cancer Genome Atlas ◽

Aims. The preferential dependence on glycolysis as a pathway of energy metabolism is a hallmark of cancer cells. However, the prognostic significance of glycolysis-related genes in head and neck squamous cell carcinoma (HNSCC) remains obscure. The purpose of this study was to identify glycolysis-related genes of prognostic value in HNSCC. Results. Transcriptional and clinical data of 544 HNSCC samples were obtained from The Cancer Genome Atlas (TCGA) dataset. By gene set enrichment analysis (GSEA) and by employing a univariate and subsequently a stepwise multivariate Cox proportional regression model, eight glycolysis-related genes of prognostic significance in HNSCC (KIF2A, JMJD8, HMMR, STC2, HK1, EXT2, GPR8, and STC1) were identified. The patients were clustered into two groups (high and low risk) based on the expression of these genes. High-risk patients had significantly a shorter overall survival than low-risk patients. Furthermore, a new prognostic indicator based on selected glycolysis-related genes was developed by multivariate Cox analysis that proved to be a better predictor of patient outcome compared to other clinical factors. Conclusion. Our findings provide new insights into the role of glycolysis in HNSCC. The identified genes predict the patient prognosis and might substantially contribute to the development of individualized treatments.

Identification of biomarkers and pathways in hypertensive nephropathy based on the ceRNA regulatory network

10.21203/rs.2.16949/v2 ◽

2020 ◽

Author(s):

Zhen Wang ◽

Zhongjie Liu ◽

Yingxia Liu ◽

Lei Kang

Keyword(s):

Signaling Pathway ◽

Insulin Signaling ◽

Regulatory Network ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Insulin Signaling Pathway ◽

Chronic Hypertension ◽

Hypertensive Nephropathy ◽

Kegg Pathways

Abstract Background Hypertensive nephropathy (HTN) is a kind of renal injury caused by chronic hypertension, which seriously affect people’s life. The purpose of this study was to identify the potential biomarkers of HTN and understand its possible mechanisms. Methods The dataset numbered GSE28260 related to hypertensive and normotensive was downloaded from NCBI Gene Expression Omnibus. Then, the differentially expressed RNAs (DERs) were screened using R limma package, and functional analyses of DE-mRNA were performed by DAVID. Afterwards, a ceRNA network was established and KEGG pathway was analyzed based on the Gene Set Enrichment Analysis (GSEA) database. Finally, a ceRNA regulatory network directly associated with HTN was proposed. Results A total of 947 DERs were identified, including 900 DE-mRNAs, 20 DE-lncRNAs and 27 DE-miRNAs. Based on these DE-mRNAs, they were involved in biological processes such as fatty acid beta-oxidation, IRE1-mediated unfolded protein response, and transmembrane transport, and many KEGG pathways like glycine, serine and threonine metabolism, carbon metabolism. Subsequently, lncRNAs KCTD21-AS1 , LINC00470 and SNHG14 were found to be hub nodes in the ceRNA regulatory network. KEGG analysis showed that insulin signaling pathway, glycine, serine and threonine metabolism, pathways in cancer, lysosome, and apoptosis was associated with hypertensive. Finally, insulin signaling pathway was screened to directly associate with HTN and was regulated by mRNAs PPP1R3C , PPKAR2B and AKT3 , miRNA has-miR-107, and lncRNAs SNHG14 , TUG1 , ZNF252P-AS1 and MIR503HG . Conclusions Insulin signaling pathway was directly associated with HTN, and miRNA has-miR-107 and lncRNAs SNHG14 , TUG1 , ZNF252P-AS1 and MIR503HG were the biomarkers of HTN. These results would improve our understanding of the occurrence and development of HTN.

Bioinformatics analysis of autophagy-related lncRNAs in esophageal carcinoma

10.21203/rs.3.rs-60567/v2 ◽

2020 ◽

Author(s):

Dan Wu ◽

Yi Ding ◽

junbai fan

Keyword(s):

High Risk ◽

Esophageal Carcinoma ◽

Cox Regression ◽

Expression Profiles ◽

Enrichment Analysis ◽

Diagnostic Value ◽

The Cancer Genome Atlas ◽

High Risk Patients ◽

Identification of biomarkers and pathways in hypertensive nephropathy based on the ceRNA regulatory network

BMC Nephrology ◽

10.1186/s12882-020-02142-8 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Zhen Wang ◽

Zhongjie Liu ◽

Yingxia Yang ◽

Lei Kang

Keyword(s):

Signaling Pathway ◽

Insulin Signaling ◽

Regulatory Network ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Insulin Signaling Pathway ◽

Chronic Hypertension ◽

Hypertensive Nephropathy ◽

Kegg Pathways

Abstract Background Hypertensive nephropathy (HTN) is a kind of renal injury caused by chronic hypertension, which seriously affect people’s life. The purpose of this study was to identify the potential biomarkers of HTN and understand its possible mechanisms. Methods The dataset numbered GSE28260 related to hypertensive and normotensive was downloaded from NCBI Gene Expression Omnibus. Then, the differentially expressed RNAs (DERs) were screened using R limma package, and functional analyses of DE-mRNA were performed by DAVID. Afterwards, a ceRNA network was established and KEGG pathway was analyzed based on the Gene Set Enrichment Analysis (GSEA) database. Finally, a ceRNA regulatory network directly associated with HTN was proposed. Results A total of 947 DERs were identified, including 900 DE-mRNAs, 20 DE-lncRNAs and 27 DE-miRNAs. Based on these DE-mRNAs, they were involved in biological processes such as fatty acid beta-oxidation, IRE1-mediated unfolded protein response, and transmembrane transport, and many KEGG pathways like glycine, serine and threonine metabolism, carbon metabolism. Subsequently, lncRNAs KCTD21-AS1, LINC00470 and SNHG14 were found to be hub nodes in the ceRNA regulatory network. KEGG analysis showed that insulin signaling pathway, glycine, serine and threonine metabolism, pathways in cancer, lysosome, and apoptosis was associated with hypertensive. Finally, insulin signaling pathway was screened to directly associate with HTN and was regulated by mRNAs PPP1R3C, PPKAR2B and AKT3, miRNA has-miR-107, and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG. Conclusions Insulin signaling pathway was directly associated with HTN, and miRNA has-miR-107 and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG were the biomarkers of HTN. These results would improve our understanding of the occurrence and development of HTN.