A TOR2A Gene Product: Salusin-β Contributes to Attenuated Vasodilatation of Spontaneously Hypertensive Rats

Sun, Shuhong; Zhang, Feng; Yan, Pan; Xu, Yu; Chen, Aidong; Wang, Jian; Tang, Haiyang; Han, Ying

doi:10.1007/s10557-020-06983-1

Cited by 16 publications

(15 citation statements)

References 46 publications

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“…Some have been previously involved in regulating longevity-related pathways. For example, TOR2A is a gene involved in cardiovascular diseases ( Sun et al 2021 ), which is included in a CNV region in chromosome 9 correlating with longevity ( Zhao et al 2018 ). Interestingly, TOR2A gene codifies for the protein Prosalusin, which is cleaved into two gene products (salusin-alpha and salusin-beta), both important vasoactive peptides that play a pivotal role in the maintenance of blood pressure homeostasis regulating cell proliferation and apoptosis ( Shichiri et al 2003 ; Fujie et al 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Comparative Analysis of Mammal Genomes Unveils Key Genomic Variability for Human Life Span

Farré

Molina

Barteri

et al. 2021

Molecular Biology and Evolution

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The enormous mammal’s lifespan variation is the result of each species' adaptations to their own biological trade-offs and ecological conditions. Comparative genomics have demonstrated that genomic factors underlying both, species lifespans and longevity of individuals, are in part shared across the tree of life. Here, we compared protein-coding regions across the mammalian phylogeny to detect individual amino-acid (AA) changes shared by the most long-lived mammals and genes whose rates of protein evolution correlate with longevity. We discovered a total of 2,737 AA in 2,004 genes that distinguish long- and short-lived mammals, significantly more than expected by chance (p = 0.003). These genes belong to pathways involved in regulating lifespan, such as inflammatory response and hemostasis. Among them, a total 1,157 AA showed a significant association with maximum lifespan in a phylogenetic test. Interestingly, most of the detected AA positions do not vary in extant human populations (81.2%) or have allele frequencies below 1% (99.78%). Consequently, almost none of these putatively important variants could have been detected by Genome-Wide Association Studies (GWAS). Additionally, we identified four more genes whose rate of protein evolution correlated with longevity in mammals. Crucially, SNPs located in the detected genes explain a larger fraction of human lifespan heritability than expected, successfully demonstrating for the first time that comparative genomics can be used to enhance interpretation of human GWAS. Finally, we show that the human longevity-associated proteins are significantly more stable than the orthologous proteins from short-lived mammals, strongly suggesting that general protein stability is linked to increased lifespan.

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Section: Discussionmentioning

confidence: 99%

Comparative Analysis of Mammal Genomes Unveils Key Genomic Variability for Human Life Span

Farré

Molina

Barteri

et al. 2021

Molecular Biology and Evolution

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“…Some have been previously involved in regulating longevity-related pathways. For example, TOR2A is a gene involved in cardiovascular diseases (Sun et al 2020) included in a CNV region in chromosome 9, correlating with longevity in a GWAS of Han Chinese individuals (Zhao et al 2018). ADCY7 is a key gene in the longevity regulating pathway and was recently associated with cancer mortality in dog breeds (Doherty et al 2020).…”

Section: Discussionmentioning

confidence: 99%

Comparative analysis of mammal genomes unveils key genomic variability for human lifespan

Farré

Molina

Barteri

et al. 2021

Preprint

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Mammals vary 100-fold in their maximum lifespan. This enormous variation is the result of the adaptations of each species to their own biological trade-offs and ecological conditions. Comparative genomics studies have demonstrated that the genomic factors underlying the lifespans of species and the longevity of individuals are shared across the tree of life. Here, we set out to compare protein-coding regions across the mammalian phylogeny, aiming to detect individual amino acid changes shared by the most long-lived mammal species and genes whose rates of protein evolution correlate with longevity. We discovered a total of 2,737 amino acid changes in 2,004 genes that distinguish long- and short-lived mammals, significantly more than expected by chance (p=0.003). The detected genes belong to pathways involved in regulating lifespan, such as inflammatory response and hemostasis. Among them, a total 1,157 amino acids, located in 996 different genes, showed a significant association with maximum lifespan in a phylogenetically controlled test. Interestingly, most of the detected amino acids positions do not vary in extant human populations (>81.2%) or have allele frequencies below 1% (99.78%), Consequently, almost none could have been detected by Genome-Wide Association Studies (GWAS). Additionally, we identified four more genes whose rate of protein evolution correlated with longevity in mammals. Crucially, SNPs located in the detected genes explain a larger fraction of human lifespan heritability than expected by chance, successfully demonstrating for the first time that comparative genomics can be used to enhance the interpretation of human GWAS. Finally, we show that the human longevity-associated proteins coded by the detected genes are significantly more stable than the orthologous proteins from short-lived mammals, strongly suggesting that general protein stability is linked to increased lifespan.

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“…A previous study reported that FAP (fibroblast activation protein alpha) [205], EYA4 [206], BCL9 [207], IRF2BP2 [208], EGR3 [209], GADD45B [210], DMD (dystrophin) [211], LSR (lipolysis stimulated lipoprotein receptor) [212], DLL4 [213], SUN2 [214], SOS1 [215], PIK3CA [216], GAMT (guanidinoacetate N-methyltransferase) [217], RBM47 [218], HSP90AA1 [219], GAB1 [220], S1PR1 [221], EDNRB (endothelin receptor type B) [222], NFKBIA (NFKB inhibitor alpha) [223], GJA1 [224], GADD45G [225], PHLDA1 [226], CMPK2 [227], FIGN (fidgetin, microtubule severing factor) [228], KCNJ2 [229], ABCC9 [230], DIRAS3 [231], EPHX1 [232], RAB4A [233], UBIAD1 [234], CASQ2 [235], TTN (titin) [236], KCNH1 [237], JPH2 [238], OXGR1 [239], UCHL1 [240], SERPINA3 [241], MMP28 [242], ADAMTS2 [243], P2RY1 [244], CSF2RA [245], MYO1F [246], SELPLG (selectin P ligand) [247] and SAMHD1 [248] are expressed in cardiovascular disease, but these genes might be novel target for T1DM. MAOB (monoamine oxidase B) [249], VEGFC (vascular endothelial growth factor C) [250], DBP (D-box binding PAR bZIP transcription factor) [251], MYADM (myeloid associated differentiation marker) [252], NES (nestin) [253], SMURF1 [254], EDNRB (endothelin receptor type B) [255], MUC6 [256], TOR2A [257], TNKS (tankyrase) [258], NEDD9 [259], ASIC1 [260], ADAMTS8 [261], DYSF (dysferlin) [262], SLC26A9 [263], SLC45A3 [264] and KCNQ2 [265] contributes to the progression of hypertension, but these genes might be novel target for T1DM. Yang et al [266], Zhang et al [267] and Wang et al [268] demonstrated that SYVN1, BTG1 and CFB (complement factor B) were associated with diabetic retinopathy, but these genes mi...…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Bm¹,

Cm²

2021

Preprint

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Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis and RT-PCR confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

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A TOR2A Gene Product: Salusin-β Contributes to Attenuated Vasodilatation of Spontaneously Hypertensive Rats

Cited by 16 publications

References 46 publications

Comparative Analysis of Mammal Genomes Unveils Key Genomic Variability for Human Life Span

Comparative Analysis of Mammal Genomes Unveils Key Genomic Variability for Human Life Span

Comparative analysis of mammal genomes unveils key genomic variability for human lifespan

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

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