In Silico Preliminary Association of Ammonia Metabolism Genes GLS, CPS1, and GLUL with Risk of Alzheimer’s Disease, Major Depressive Disorder, and Type 2 Diabetes

Griffin, Jeddidiah W. D.; Liu, Ying; Bradshaw, Patrick C.; Wang, Kesheng

doi:10.1007/s12031-018-1035-0

Cited by 27 publications

(22 citation statements)

References 79 publications

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“…Hou et al [ 53 ] and Olesen et al [ 54 ] demonstrated that DACT2 and KCND3 were found to be substantially related to atrial fibrillation. Ge and Concannon [ 55 ], Ferjeni et al [ 56 ], Anquetil et al [ 57 ], Glawe et al [ 58 ], Kawabata et al [ 59 ], Li et al [ 60 ], Buraczynska et al [ 61 ], Amini et al [ 62 ], Yang et al [ 63 ], Du Toit et al [ 64 ], Hirose et al [ 65 ], Zhang et al [ 66 ], Griffin et al [ 67 ], Zouidi et al [ 68 ], Trombetta et al [ 69 ], Alharbi et al [ 70 ], Ikarashi et al [ 71 ], Dharmadhikari et al [ 72 ], Sutton et al [ 73 ] and Deng et al [ 74 ] reported that UBASH3A, ZAP70, IDO1, ITGAL (integrin subunit alpha L). ITGB7, RASGRP1, CNR1, SLC2A1, SLC11A1, GPR84, SSTR5, KCNB1, GLUL (glutamate-ammonia ligase), BANK1, CACNA1E, LGR5, AQP3, SIGLEC7, SSTR2 and DNER (delta/notch like EGF repeat containing) could be an index for diabetes, but these genes might be responsible for progression of HF.…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Kolur¹,

Vastrad²,

Vastrad

et al. 2021

BMC Cardiovasc Disord

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Introduction Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules. Methods The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein–protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene—miRNA regulatory network and target gene—TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed. Results A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene—miRNA regulatory network and target gene—TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed. Conclusion The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

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Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Kolur¹,

Vastrad²,

Vastrad

et al. 2021

BMC Cardiovasc Disord

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“…With the recent identification of CPS1 variants correlating with increased plasma glycine and protective effects against atherosclerosis, in addition to the role of CPS1 in vascular signaling, this new model may also serve as a useful tool for the in‐depth study of the relationship of short‐ and long‐term cardiovascular effects and CPS1 enzymatic activity. Additional preliminary findings implicate CPS1 in Alzheimer's disease and other neurological disorders . These new studies, combined with the more established studies of CPS1 in cancer initiation and progression, make the murine model described here more broadly applicable beyond the field of urea cycle disorders.…”

Section: Discussionmentioning

confidence: 75%

A constitutive knockout of murine carbamoyl phosphate synthetase 1 results in death with marked hyperglutaminemia and hyperammonemia

Khoja

Nitzahn²,

Truong

et al. 2019

J of Inher Metab Disea

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The enzyme carbamoyl phosphate synthetase 1 (CPS1; EC 6.3.4.16) forms carbamoyl phosphate from bicarbonate, ammonia, and adenosine triphosphate (ATP) and is activated allosterically by N-acetylglutamate. The neonatal presentation of bi-allelic mutations of CPS1 results in hyperammonemia with reduced citrulline and is reported as the most challenging nitrogen metabolism disorder to treat. As therapeutic interventions are limited, patients often develop neurological injury or die from hyperammonemia. Survivors remain vulnerable to nitrogen overload, being at risk for repetitive neurological injury. With transgenic technology, our lab developed a constitutive Cps1 mutant mouse and reports its characterization herein. Within 24 hours of birth, all Cps1 −/− mice developed hyperammonemia and expired. No CPS1 protein by Western blot or immunostaining was detected in livers nor was Cps1 mRNA present. CPS1 enzymatic activity was markedly decreased in knockout livers and reduced in Cps1 +/− mice. Plasma analysis found markedly reduced citrulline and arginine and markedly increased glutamine and alanine, both intermolecular carriers of nitrogen, along with elevated ammonia, taurine, and lysine. Derangements in multiple other amino acids were also detected. While hepatic amino acids also demonstrated markedly reduced citrulline, arginine, while decreased, was not statistically significant; alanine and lysine were markedly increased while glutamine was trending towards significance. In conclusion we have determined that this constitutive neonatal mouse model of CPS1 deficiency replicates the neonatal human phenotype and demonstrates the key biochemical features of the disorder. These mice will be integral for addressing the challenges of developing new therapeutic approaches for this, at present, poorly treated disorder. K E Y W O R D S carbamoyl phosphate synthetase (CPS1) deficiency, citrulline, glutamine, hyperammonemia, murine model Suhail Khoja and Matthew Nitzahn contributed equally to this study.

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“…Hou et al [44] and Olesen et al [45] demonstrated that DACT2 and KCND3 were found to be substantially related to atrial fibrillation. Ge and Concannon [46], Ferjeni et al [47], Anquetil et al [48], Glawe et al [49], Kawabata et al [50], Li et al [51], Buraczynska et al [52], Amini et al [53], Yang et al [54], Du Toit et al [55], Hirose et al [56], Zhang et al [57], Griffin et al [58], Zouidi et al [59], Trombetta et al [60], Alharbi et al [61], Ikarashi et al [62], Dharmadhikari et al [63], Sutton et al [64] and Deng et al [65] reported that UBASH3A, ZAP70, IDO1, ITGAL (integrin subunit alpha L). ITGB7, RASGRP1, CNR1, SLC2A1, SLC11A1, GPR84, SSTR5, KCNB1, GLUL (glutamate-ammonia ligase), BANK1, CACNA1E, LGR5, AQP3, SIGLEC7, SSTR2 and DNER (delta/notch like EGF repeat containing) could be an index for diabetes, but these genes might be responsible for progression of HF.…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Vastrad¹,

Tengli

Vastrad³

2021

Preprint

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Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules. The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein-protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene - miRNA regulatory network and target gene - TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed. A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene - miRNA regulatory network and target gene - TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed. The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

show abstract

In Silico Preliminary Association of Ammonia Metabolism Genes GLS, CPS1, and GLUL with Risk of Alzheimer’s Disease, Major Depressive Disorder, and Type 2 Diabetes

Cited by 27 publications

References 79 publications

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

A constitutive knockout of murine carbamoyl phosphate synthetase 1 results in death with marked hyperglutaminemia and hyperammonemia

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

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