Analysis of non-synonymous single-nucleotide polymorphisms and population variability of PLD2 gene associated with hypertension

Kundu, Arpita; Ramakrishnan, Parvathy; Rajendran, Ambika; Dharwar, Nivedita V.; Anbarasu, Anand

doi:10.1504/ijbra.2013.053604

Cited by 5 publications

(3 citation statements)

References 53 publications

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“…PLD2 function has also been linked to endocytosis of the angiotensin II type 1 receptor (AT1R) 19 , which promotes increased vascular tone and blood pressure via intracellular signaling, and to the production and secretion of aldosterone 20 , 21 , which increases blood pressure by stimulating renal water and salt retention. Taken together, these reports provided multiple rationales for the observation that a polymorphism that could affect PLD2 function correlates with decreased blood pressure 12 , 22 .…”

Section: Introductionmentioning

confidence: 85%

Phospholipase D2 loss results in increased blood pressure via inhibition of the endothelial nitric oxide synthase pathway

Nelson

Jiang

Gadbery

et al. 2017

Sci Rep

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The Phospholipase D (PLD) superfamily is linked to neurological disease, cancer, and fertility, and a recent report correlated a potential loss-of-function PLD2 polymorphism with hypotension. Surprisingly, PLD2 −/− mice exhibit elevated blood pressure accompanied by associated changes in cardiac performance and molecular markers, but do not have findings consistent with the metabolic syndrome. Instead, expression of endothelial nitric oxide synthase (eNOS), which generates the potent vasodilator nitric oxide (NO), is decreased. An eNOS inhibitor phenocopied PLD2 loss and had no further effect on PLD2 −/− mice, confirming the functional relationship. Using a human endothelial cell line, PLD2 loss of function was shown to lower intracellular free cholesterol, causing upregulation of HMG Co-A reductase, the rate-limiting enzyme in cholesterol synthesis. HMG Co-A reductase negatively regulates eNOS, and the PLD2-deficiency phenotype of decreased eNOS expression and activity could be rescued by cholesterol supplementation and HMG Co-A reductase inhibition. Together, these findings identify a novel pathway through which the lipid signaling enzyme PLD2 regulates blood pressure, creating implications for on-going therapeutic development of PLD small molecule inhibitors. Finally, we show that the human PLD2 polymorphism does not trigger eNOS loss, but rather creates another effect, suggesting altered functioning for the allele.

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Section: Introductionmentioning

confidence: 85%

Phospholipase D2 loss results in increased blood pressure via inhibition of the endothelial nitric oxide synthase pathway

Nelson

Jiang

Gadbery

et al. 2017

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Findings were implied by Richter et al [ 98 ], Suchkova et al [ 99 ], Qureshi et al [ 100 ], Wang et al [ 101 ], Wang et al [ 102 ], Aoki-Suzuki et al [ 103 ], Ohno et al [ 104 ], Richter et al [ 98 ], Rahman and Copeland [ 105 ], Congiu et al [ 106 ], Ji et al [ 107 ], Wollmer et al [ 108 ], Yamazaki et al [ 109 ], Bardien et al [ 110 ], Comella Bolla et al [ 111 ], Horvath et al [ 112 ], Watanabe et al [ 113 ], Kushima et al [ 114 ], Grünblatt et al [ 115 ], and Sato and Kawata [ 116 ] when they found that TAOK2 , ACAP3 , PLXNA3 , PLXNA4 , DCTN1 , NTNG2 , LRP4 , AGRN (agrin), TAOK2 , POLG (DNA polymerase gamma, catalytic subunit), KCNK2 , OPRK1 , ABCA2 , ABCA7 , LRRK2 , CD200 , PAK3 , PADI2 , EPHB1 , CHAT (choline O-acetyltransferase) and SLC18A1 plays a substantial role in the patients with neurological and neuropsychiatric disorders. Studies showed that biomarkers include PLD2 [ 117 ], FLNA (filamin A) [ 118 ], SMURF1 [ 119 ], LINGO1 [ 120 ], CACNA1H [ 121 ], NLRP6 [ 122 ], NLRC3 [ 123 ], CXCR2 [ 124 ] and C5AR1 [ 125 ] plays an important role in progression of hypertension. Sauzeau et al [ 126 ], Xu et al [ 127 ], Hirota et al [ 128 ], Alharatani et al [ 129 ], Beitelshees et al [ 130 ], Zhu et al [ 131 ], Gil-Cayuela et al [ 132 ], Liu et al […”

Section: Discussionmentioning

confidence: 99%

Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity

Ganekal

Vastrad²,

Kavatagimath

et al. 2023

Medicina

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Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein–protein interactions network, module analysis, target gene–miRNA regulatory network and target gene–TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity.The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.

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“…Richter et al [97], Suchkova et al [98], Qureshi et al [99], Wang et al [100], Wang et al [101], Aoki-Suzuki et al [102], Ohno et al [103], Richter et al [104], Rahman and Copeland [105], Congiu et al [106], Ji et al [107], Wollmer et al [108], Yamazaki et al [109], Bardien et al [110], Comella Bolla et al [111], Horvath et al [112], Watanabe et al [113], Kushima et al [114], Grünblatt et al [115] and Sato and Kawata [116] have shown that TAOK2, ACAP3, PLXNA3, PLXNA4, DCTN1, NTNG2, LRP4, AGRN (agrin), TAOK2, POLG (DNA polymerase gamma, catalytic subunit), KCNK2, OPRK1, ABCA2, ABCA7, LRRK2, CD200, PAK3, PADI2, EPHB1, CHAT (choline O-acetyltransferase) and SLC18A1 key for progression of neurological and neuropsychiatric disorders, but these genes might be liable for obesity associated type 2 diabetes mellitus. PLD2 [117], FLNA (filamin A) [118], SMURF1 [119], LINGO1 [120], CACNA1H [121], NLRP6 [122], NLRC3 [123], CXCR2 [124] and C5AR1 [125] are involved in hypertension, but these genes might be essential for progression of obesity associated type 2 diabetes mellitus. Studies conducted by Sauzeau et al [126], Xu et al [127], Hirota et al [128], Alharatani et al [129], Beitelshees et al [130], Zhu et al [131], Gil-Cayuela et al [132], Liu et al [133], Xie et al [134], Kroupis et al [135], López-Mejías et al [136], Gremmel et al [137], Yamada and Guo [138], Petri et al [139], DeFilippis et al [140], Rocca et al [141] and Tur et al [142] indicated that of VAV2, RASAL1, LIF (LIF interleukin 6 family cytokine), CTNND1, CACNA1C, MAP3K10, NRBP2, TRPM4, LILRB2, FCGR2A, PIK3CG, SELPLG (selectin P ligand), PRDX4, FPR2, PLG (plasminogen), SELENOM (selenoprotein M) and NCAM1were associated with cardiovascular diseases, but these genes might be responsible for progression of obesity associated type 2 diabetes mellitus.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics Analysis of Key Genes and Pathways for Obesity Associated Type 2 Diabetes Mellitus as a Therapeutic Target

Vastrad¹,

Tengli

Vastrad³

et al. 2020

Preprint

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Obesity associated type 2 diabetes mellitus is one of the most common metabolic disorder worldwide. The prognosis of obesity associated type 2 diabetes mellitus patients has remained poor, though considerable efforts have been made to improve the treatment of this metabolic disorder. Therefore, identifying significant differentially expressed genes (DEGs) associated in metabolic disorder advancement and exploiting them as new biomarkers or potential therapeutic targets for metabolic disorder is highly valuable. Differentially expressed genes (DEGs) were screened out from gene expression omnibus (GEO) dataset (GSE132831) and subjected to GO and REACTOME pathway enrichment analyses. The protein - protein interactions network, module analysis, target gene - miRNA regulatory network and target gene - TF regulatory network were constructed, and the top ten hub genes were selected. The relative expression of hub genes was detected in RT-PCR. Furthermore, diagnostic value of hub genes in obesity associated type 2 diabetes mellitus patients was investigated using the receiver operating characteristic (ROC) analysis. Small molecules were predicted for obesity associated type 2 diabetes mellitus by using molecular docking studies. A total of 872 DEGs, including 439 up regulated genes and 432 down regulated genes were observed. Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for obesity associated type 2 diabetes mellitus. The hub genes were validated in obesity associated type 2 diabetes mellitus. This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for obesity associated type 2 diabetes mellitus.

show abstract

Analysis of non-synonymous single-nucleotide polymorphisms and population variability of PLD2 gene associated with hypertension

Cited by 5 publications

References 53 publications

Phospholipase D2 loss results in increased blood pressure via inhibition of the endothelial nitric oxide synthase pathway

Phospholipase D2 loss results in increased blood pressure via inhibition of the endothelial nitric oxide synthase pathway

Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity

Bioinformatics Analysis of Key Genes and Pathways for Obesity Associated Type 2 Diabetes Mellitus as a Therapeutic Target

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