Genetic profiling of young and aged endothelial progenitor cells in hypoxia

<div><p>Age is a major risk factor for diseases caused by ischemic hypoxia, such as stroke and coronary artery disease. Endothelial progenitor cells (EPCs) are the major cells respond to ischemic hypoxia through angiogenesis and vascular remodeling. However, the effect of aging on EPCs and their responses to hypoxia are not well understood. CD34⁺ EPCs were isolated from healthy volunteers and aged by replicative senescence, which was to passage cells until their doubling time was twice as long as the original cells. Young and aged CD34⁺ EPCs were exposed to a hypoxic environment (1% oxygen for 48hrs) and their gene expression profiles were evaluated using gene expression array. Gene array results were confirmed using quantitative polymerase chain reaction, Western blotting, and BALB/c female athymic nude mice hindlimb ischemia model. We identified 115 differentially expressed genes in young CD34⁺ EPCs, 54 differentially expressed genes in aged CD34⁺ EPCs, and 25 common genes between normoxia and hypoxia groups. Among them, the expression of solute carrier family 2 (facilitated glucose transporter), member 1 (SLC2A1) increased the most by hypoxia in young cells. Gene set enrichment analysis indicated the pathways affected by aging and hypoxia most, including genes “response to oxygen levels” in young EPCs and genes involved “chondroitin sulfate metabolic process” in aged cells. Our study results indicate the key factors that contribute to the effects of aging on response to hypoxia in CD34⁺ EPCs. With the potential applications of EPCs in cardiovascular and other diseases, our study also provides insight on the impact of ex vivo expansion might have on EPCs.</p></div

GSEA results in differentially expressed genes (old only).

<p>GSEA results in differentially expressed genes (old only).</p

All differentially expressed genes.

<p>All differentially expressed genes.</p

Quantitative PCR for control genes.

<p>(A) SLC2A1 was significantly up-regulated by hypoxia. No significant difference was found in 18S (B) and HPRT (C) expression. (D) ADM was significantly upregulated and (E) HMOX1 was downregulated by hypoxia which was consistent with microarray results. N = 6 * P < .05 compared to normoxia cells of the same passage. Y: young; A: aged; N: normoxia; H: hypoxia.</p

Isolation and aging of CD34⁺ EPC.

<p>Isolated CD34⁺ EPC were subcultured in vitro and signs of senescence showed after around 10 passages. Replicative senescence resulted in (A) morphological changes (Bar = 10μm), (B) up-regulation of senescence marker (P < .01).</p

Determination of hypoxia time.

<p>(A) VEGF Western blot time course showed that VEGF was upregulated within 24 hours and reached a plateau in 48 hours. N = 3; * P< .01; # P< .05 (B) VEGF upregulation was confirmed by expression microarray in 3 EPC clones.</p

GSEA results in differentially expressed genes (young only).

<p>GSEA results in differentially expressed genes (young only).</p

Validation of SLC2A1 expression in response to hypoxia.

<p>(A) Western blots showing a significant rise of the SLC2A1 protein level in young EPCs. Representative Western blots and normalized quantification of band density were shown. * p < .05 compared to young CD34⁺ EPCs in normoxia, N = 3, Bars represent mean ± SEM. (B) Hypoxia-induced membrane translocation of SLC2A1 (Bar = 10mm). (C) EPCs (labeled with HNA) injected into ischemic hindlimb (Left) expressed more SLC2A1 that EPCs injected into the contralateral tissue (Right). Y: young; A: aged; N: normoxia; H: hypoxia; HNA: human nuclear antigen.</p

The Normal Limits, Subclinical Significance, Related Metabolic Derangements and Distinct Biological Effects of Body Site-Specific Adiposity in Relatively Healthy Population

<div><p>Background</p><p>The accumulation of visceral adipose tissue that occurs with normal aging is associated with increased cardiovascular risks. However, the clinical significance, biological effects, and related cardiometabolic derangements of body-site specific adiposity in a relatively healthy population have not been well characterized.</p><p>Materials and Methods</p><p>In this cross-sectional study, we consecutively enrolled 608 asymptomatic subjects (mean age: 47.3 years, 27% female) from 2050 subjects undergoing an annual health survey in Taiwan. We measured pericardial (PCF) and thoracic peri-aortic (TAT) adipose tissue volumes by 16-slice multi-detector computed tomography (MDCT) (Aquarius 3D Workstation, TeraRecon, San Mateo, CA, USA) and related these to clinical characteristics, body fat composition (Tanita 305 Corporation, Tokyo, Japan), coronary calcium score (CCS), serum insulin, high-sensitivity C-reactive protein (Hs-CRP) level and circulating leukocytes count. Metabolic risk was scored by Adult Treatment Panel III guidelines.</p><p>Results</p><p>TAT, PCF, and total body fat composition all increased with aging and higher metabolic scores (all p<0.05). Only TAT, however, was associated with higher circulating leukocyte counts (ß-coef.:0.24, p<0.05), serum insulin (ß-coef.:0.17, p<0.05) and high sensitivity C-reactive protein (ß-coef.:0.24, p<0.05). These relationships persisted after adjustment in multivariable models (all p<0.05). A TAT volume of 8.29 ml yielded the largest area under the receiver operating characteristic curve (AUROC: 0.79, 95%CI: 0.74–0.83) to identify metabolic syndrome. TAT but not PCF correlated with higher coronary calcium score after adjustment for clinical variables (all p<0.05).</p><p>Conclusion</p><p>In our study, we observe that age-related body-site specific accumulation of adipose tissue may have distinct biological effects. Compared to other adiposity measures, peri-aortic adiposity is more tightly associated with cardiometabolic risk profiles and subclinical atherosclerosis in a relatively healthy population.</p></div

Baseline characteristics of the study population by age quartiles.

<p>BMI: body mass index; BSA: body surface area; DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; HbA1c: glycosylated hemoglobin level; HDL: high-density lipoprotein; HOMA-IR: homeostasis model assessment-estimated insulin resistance; LDL: low-density lipoprotein; SBP: systolic blood pressure; TG: Triglycerides.</p