Angiotensinogen precursor (Serpin A8) [Contains: Angiotensin-1 (Angiotensin 1-10) (Angiotensin I) (Ang I); Angiotensin-2 (Angiotensin 1-8) (Angiotensin II) (Ang II); Angiotensin-3 (Angiotensin 2-8) (Angiotensin III) (Ang III) (Des-Asp[1]-angiotensin II); Angiotensin-4 (Angiotensin 3-8) (Angiotensin IV) (Ang IV); Angiotensin 1-9; Angiotensin 1-7; Angiotensin 1-5; Angiotensin 1-4] [SERPINA8]

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SQSTM1/p62 and PPARGC1A/PGC-1alpha at the interface of autophagy and vascular senescence.

Defective macroautophagy/autophagy and mitochondrial dysfunction are known to stimulate senescence. The mitochondrial regulator PPARGC1A (peroxisome proliferator activated receptor gamma, coactivator 1 alpha) regulates mitochondrial biogenesis, reducing senescence of vascular smooth muscle cells (VSMCs); however, it is unknown whether autophagy mediates PPARGC1A-protective effects on senescence. Using [i]ppargc1a [/i] VSMCs, we identified the autophagy receptor SQSTM1/p62 (sequestosome 1) as a major regulator of autophagy and senescence of VSMCs. Abnormal autophagosomes were observed in VSMCs in aortas of [i]ppargc1a [/i] mice. [i]ppargc1a [/i] VSMCs in culture presented reductions in LC3-II levels; in autophagosome number; and in the expression of SQSTM1 (protein and mRNA), LAMP2 (lysosomal-associated membrane protein 2), CTSD (cathepsin D), and TFRC (transferrin receptor). Reduced SQSTM1 protein expression was also observed in aortas of [i]ppargc1a [/i] mice and was upregulated by PPARGC1A overexpression, suggesting that SQSTM1 is a direct target of PPARGC1A. Inhibition of autophagy by 3-MA (3 methyladenine), spautin-1 or [i]Atg5[/i] (autophagy related 5) siRNA stimulated senescence. Rapamycin rescued the effect of [i]Atg5[/i] siRNA in [i]Ppargc1a [/i] , but not in [i]ppargc1a [/i] VSMCs, suggesting that other targets of MTOR (mechanistic target of rapamycin kinase), in addition to autophagy, also contribute to senescence. [i]Sqstm1[/i] siRNA increased senescence basally and in response to AGT II (angiotensin II) and zinc overload, two known inducers of senescence. Furthermore, [i]Sqstm1 [/i]gene deficiency mimicked the phenotype of [i]Ppargc1a[/i] depletion by presenting reduced autophagy and increased senescence [i]in vitro[/i] and [i]in vivo[/i]. Thus, PPARGC1A upregulates autophagy reducing senescence by a SQSTM1-dependent mechanism. We propose SQSTM1 as a novel target in therapeutic interventions reducing senescence. 3-MA: 3 methyladenine; ACTA2/SM-actin: actin, alpha 2, smooth muscle, aorta; ACTB/β-actin: actin beta; AGT II: angiotensin II; ATG5: autophagy related 5; BECN1: beclin 1; CAT: catalase; CDKN1A: cyclin-dependent kinase inhibitor 1A (P21); Chl: chloroquine; CTSD: cathepsin D; CYCS: cytochrome C, somatic; DHE: dihydroethidium; DPBS: Dulbecco's phosphate-buffered saline; EL: elastic lamina; EM: extracellular matrix; FDG: fluorescein-di-β-D-galactopyranoside; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; γH2AFX: phosphorylated H2A histone family, member X, H DCFDA: 2',7'-dichlorodihydrofluorescein diacetate; LAMP2: lysosomal-associated membrane protein 2; MASMs: mouse vascular smooth muscle cells; MEF: mouse embryonic fibroblast; NBR1: NBR1, autophagy cargo receptor; NFKB/NF-κB: nuclear factor of kappa light polypeptide gene enhancer in B cells; MTOR: mechanistic target of rapamycin kinase; NFE2L2: nuclear factor, erythroid derived 2, like 2; NOX1: NADPH oxidase 1; OPTN: optineurin; PFA: paraformaldehyde; PFU: plaque-forming units; PPARGC1A/PGC-1α: peroxisome proliferator activated receptor, gamma, coactivator 1 alpha; Ptdln3K: phosphatidylinositol 3-kinase; RASMs: rat vascular smooth muscle cells; ROS: reactive oxygen species; SA-GLB1/β-gal: senescence-associated galactosidase, beta 1; SASP: senescence-associated secretory phenotype; SIRT1: sirtuin 1; Spautin 1: specific and potent autophagy inhibitor 1; SQSTM1/p62: sequestosome 1; SOD: superoxide dismutase; TEM: transmission electron microscopy; TFEB: transcription factor EB; TFRC: transferrin receptor; TRP53/p53: transformation related protein 53; TUBG1: tubulin gamma 1; VSMCs: vascular smooth muscle cells; WT: wild type.


Keywords

  • Aging
  • SQSTM1
  • autophagy
  • oxidative stress
  • senescence
  • vascular biology


Towards frailty biomarkers: Candidates from genes and pathways regulated in aging and age-related diseases.

Use of the frailty index to measure an accumulation of deficits has been proven a valuable method for identifying elderly people at risk for increased vulnerability, disease, injury, and mortality. However, complementary molecular frailty biomarkers or ideally biomarker panels have not yet been identified. We conducted a systematic search to identify biomarker candidates for a frailty biomarker panel. Gene expression databases were searched (http://genomics.senescence.info/genes including GenAge, AnAge, LongevityMap, CellAge, DrugAge, Digital Aging Atlas) to identify genes regulated in aging, longevity, and age-related diseases with a focus on secreted factors or molecules detectable in body fluids as potential frailty biomarkers. Factors broadly expressed, related to several "hallmark of aging" pathways as well as used or predicted as biomarkers in other disease settings, particularly age-related pathologies, were identified. This set of biomarkers was further expanded according to the expertise and experience of the authors. In the next step, biomarkers were assigned to six "hallmark of aging" pathways, namely (1) inflammation, (2) mitochondria and apoptosis, (3) calcium homeostasis, (4) fibrosis, (5) NMJ (neuromuscular junction) and neurons, (6) cytoskeleton and hormones, or (7) other principles and an extensive literature search was performed for each candidate to explore their potential and priority as frailty biomarkers. A total of 44 markers were evaluated in the seven categories listed above, and 19 were awarded a high priority score, 22 identified as medium priority and three were low priority. In each category high and medium priority markers were identified. Biomarker panels for frailty would be of high value and better than single markers. Based on our search we would propose a core panel of frailty biomarkers consisting of (1) CXCL10 (C-X-C motif chemokine ligand 10), IL-6 (interleukin 6), CX3CL1 (C-X3-C motif chemokine ligand 1), (2) GDF15 (growth differentiation factor 15), FNDC5 (fibronectin type III domain containing 5), vimentin (VIM), (3) regucalcin (RGN/SMP30), calreticulin, (4) PLAU (plasminogen activator, urokinase), AGT (angiotensinogen), (5) BDNF (brain derived neurotrophic factor), progranulin (PGRN), (6) α-klotho (KL), FGF23 (fibroblast growth factor 23), FGF21, leptin (LEP), (7) miRNA (micro Ribonucleic acid) panel (to be further defined), AHCY (adenosylhomocysteinase) and KRT18 (keratin 18). An expanded panel would also include (1) pentraxin (PTX3), sVCAM/ICAM (soluble vascular cell adhesion molecule 1/Intercellular adhesion molecule 1), defensin α, (2) APP (amyloid beta precursor protein), LDH (lactate dehydrogenase), (3) S100B (S100 calcium binding protein B), (4) TGFβ (transforming growth factor beta), PAI-1 (plasminogen activator inhibitor 1), TGM2 (transglutaminase 2), (5) sRAGE (soluble receptor for advanced glycosylation end products), HMGB1 (high mobility group box 1), C3/C1Q (complement factor 3/1Q), ST2 (Interleukin 1 receptor like 1), agrin (AGRN), (6) IGF-1 (insulin-like growth factor 1), resistin (RETN), adiponectin (ADIPOQ), ghrelin (GHRL), growth hormone (GH), (7) microparticle panel (to be further defined), GpnmB (glycoprotein nonmetastatic melanoma protein B) and lactoferrin (LTF). We believe that these predicted panels need to be experimentally explored in animal models and frail cohorts in order to ascertain their diagnostic, prognostic and therapeutic potential.

MeSH Terms

  • Aged
  • Aging
  • Amyloid beta-Peptides
  • Amyloid beta-Protein Precursor
  • Animals
  • Apoptosis
  • Biomarkers
  • Fibronectins
  • Frailty
  • Genetic Association Studies
  • Growth Differentiation Factor 15
  • Humans
  • Insulin-Like Growth Factor I
  • Interleukin-1 Receptor-Like 1 Protein
  • Membrane Glycoproteins
  • MicroRNAs
  • Signal Transduction

Keywords

  • Age-related diseases
  • Biomarker panel
  • Frailty
  • Hallmark of aging pathways


Lead-Related Genetic Loci, Cumulative Lead Exposure and Incident Coronary Heart Disease: The Normative Aging Study.

Cumulative exposure to lead is associated with cardiovascular outcomes. Polymorphisms in the δ-aminolevulinic acid dehydratase (ALAD), hemochromatosis (HFE), heme oxygenase-1 (HMOX1), vitamin D receptor (VDR), glutathione S-transferase (GST) supergene family (GSTP1, GSTT1, GSTM1), apolipoprotein E (APOE),angiotensin II receptor-1 (AGTR1) and angiotensinogen (AGT) genes, are believed to alter toxicokinetics and/or toxicodynamics of lead. We assessed possible effect modification by genetic polymorphisms in ALAD, HFE, HMOX1, VDR, GSTP1, GSTT1, GSTM1, APOE, AGTR1 and AGT individually and as the genetic risk score (GRS) on the association between cumulative lead exposure and incident coronary heart disease (CHD) events. We used K-shell-X-ray fluorescence to measure bone lead levels. GRS was calculated on the basis of 22 lead-related loci. We constructed Cox proportional hazard models to compute adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CHD. We applied inverse probability weighting to account for potential selection bias due to recruitment into the bone lead sub-study. Significant effect modification was found by VDR, HMOX1, GSTP1, APOE, and AGT genetic polymorphisms when evaluated individually. Further, the bone lead-CHD associations became larger as GRS increases. After adjusting for potential confounders, a HR of CHD was 2.27 (95%CI: 1.50-3.42) with 2-fold increase in patella lead levels, among participants in the top tertile of GRS. We also detected an increasing trend in HRs across tertiles of GRS (p-trend = 0.0063). Our findings suggest that lead-related loci as a whole may play an important role in susceptibility to lead-related CHD risk. These findings need to be validated in a separate cohort containing bone lead, lead-related genetic loci and incident CHD data.

MeSH Terms

  • Aged
  • Aging
  • Bone and Bones
  • Coronary Disease
  • Environmental Exposure
  • Female
  • Genetic Predisposition to Disease
  • Humans
  • Lead
  • Male
  • Middle Aged
  • Polymorphism, Genetic


Identification of RAS genotypes that modulate blood pressure change by outdoor temperature.

The aim of this study was to evaluate the role of polymorphisms of renin-angiotensin system (RAS) genes in modulating outdoor temperature-related blood pressure (BP) responses. Data for RAS gene polymorphisms, BP and outdoor temperature were collected from 4903 subjects from February 2003 to August 2004. Generalized additive and linear models were used to determine whether genetic variants of RAS affected the interplay between outdoor temperature and BP. Outdoor temperature (°C) was inversely associated with systolic BP and diastolic BP. These inverse relationships were stronger in subjects with ACE DD, AGT TT and AGTR1 AA genotypes. In contrast, significant positive temperature-dependent BP responses were found at temperatures above 21.4 °C in subjects with the AGTR1 C allele, but not at temperatures below 21.4 °C. Our findings suggest that subjects with ACE DD, AGT TT or AGTR1 AA genotypes are susceptible to cold temperature-induced BP increase, whereas subjects with AGTR1 C allele have a high risk of BP elevation when exposed to hot temperatures.

MeSH Terms

  • Aging
  • Angiotensinogen
  • Blood Pressure
  • DNA
  • Female
  • Genotype
  • Humans
  • Male
  • Middle Aged
  • Peptidyl-Dipeptidase A
  • Polymorphism, Genetic
  • Receptor, Angiotensin, Type 1
  • Renin-Angiotensin System
  • Sex Characteristics
  • Sex Factors
  • Temperature

{{medline-entry |title=Involvement of the skeletal renin-angiotensin system in age-related osteoporosis of ageing mice. |pubmed-url=https://pubmed.ncbi.nlm.nih.gov/22785482 |abstract=The local tissue-specific renin-angiotensin system (RAS) was identified. The aim of this study was to investigate the role of local bone RAS in the osteoporosis of aging mice. Twelve-month-old and two-month-old male mice were respectively assigned to the ageing and young groups. The tibias and femurs were collected for an analysis of histomorphology, bone mass, and gene and protein expression. H