Asprosin induces vascular endothelial-to-mesenchymal transition in diabetic lower extremity peripheral artery disease | Cardiovascular Diabetology

Study subjects

This cross-sectional single-center study was approved by the Ethics Committee of Army Medical Center of PLA. The experimental procedures were conducted according to the Declaration of Helsinki. Informed consent was obtained from each participant. The protocol was registered in ClinicalTrials.gov (Identifier: NCT05068895). PASS 15.0 software (NCSS, LLC) was used to calculate the sample size. The expected area under curve (AUC) of asprosin was about 0.7 [11, 19], and the calculated size is N = 82 for this study.

33 type 2 diabetes mellitus (T2DM) patients (DM) and 51 T2DM patients with PAD (DM + PAD) were recruited from the Department of Hypertension and Endocrinology, Daping Hospital, Army Medical University, Chongqing, China, from June to October 2021. All patients were confirmed to be diagnosed with T2DM on the basis of the American Diabetes Association criteria with fasting plasma glucose (FPG) ≥ 7.0 mmol/l, or hemoglobin A1c (HbA1c) ≥ 6.5% or oral glucose tolerance test (OGTT) 2 h post-load plasma glucose ≥ 11.1 mmol/l or self-reported medical history [20]. Besides, the diagnosis of T2DM with PAD was based on standard criteria recommended by American Heart Association [3] with a resting ABI ≤ 0.9 or imaging method including duplex ultrasound (DUS), computed tomography angiography (CTA) or digital subtraction angiography (DSA) showed stenosis or thrombosis existence in lower extremity peripheral arteries.

The following were the main exclusion criteria: (1) type 1 diabetes and other special types of diabetes, (2) type 2 diabetes with acute diabetic complications such as diabetic ketoacidosis, hyperosmolar hyperglycemic status and diabetic lactic acidosis, (3) acute infection at the time of evaluation, (4) cardiovascular or cerebrovascular disease, liver or renal dysfunction, tumors, autoimmune disease or mental disease, (5) a history of lower extremity amputations due to diabetes, (6) alcohol abuse or pregnancy. Additionally, we enrolled 30 additional age-, sex-, body mass index (BMI)- and waist circumference- matched healthy volunteers as normal controls (NC) with normal FPG and HbA1c.

Clinical and routine laboratory measurements

Demographic characteristics, previous history of smoking and medication history (including anti-diabetic medications, statins, antiplatelets treatment and anti-hypertensive drugs) were collected through the electronic medical record. Physical examination included measurements of height, weight and waist circumference, and BMI (kg/m2) was calculated as weight divided by the square of height in meters. Office blood pressure (BP) was measured on both arms in the setting position after 10 min of resting for three times and the average value was calculated. ABI and toe-brachial index (TBI) measurement was performed by trained assessors from both sides, and the lower one was shown in our study. ABI was obtained by comparing the higher brachial systolic pressure with the higher pressure at the ankle (either the dorsal pedal [DP] or posterior tibial [PT] artery). This can be performed with a hand-held Doppler probe (Huntleigh, Cardiff, CF24 5HN, UK). Toe pressures were obtained by placing cuffs around each toe with a digital flow sensor beyond the cuff. The same as ABI, TBI was obtained by comparing the higher brachial systolic blood pressure with the higher pressure from the toe artery [21]. Blood samples were obtained in the morning after an overnight fast, and some samples were used for the measurement of FPG, HbA1c, high-sensitivity C-reactive protein (hs-CRP) and lipid profiles, including total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) in the Endocrinology & Metabolism laboratory of Daping Hospital. Other samples were collected in a centrifuge tube and allowed to stand at room temperature for 1 h for coagulation and stratification. Then the samples were centrifuged at 3000 rpm for 10 min at room temperature and the supernatant was transferred to a clean centrifuge tube to centrifuge at 12000 rpm for 10 min at 4 ℃, and the plasma was aliquoted and stored at − 80 ℃ for further study. When the samples were collected enough (15 samples in each group), 200 μl of each sample were shipped by dry ice to the Shanghai Biotree biotech Company to perform liquid chromatography–mass spectrometry (LC–MS). When the recruitment of participant was stopped, serum asprosin concentrations were measured using a human Asprosin ELISA kit (ab275108, Abcam) following the instructions of the manufacturer.

LC–MS-based nontargeted metabolomic approach

For extraction of metabolites, 50 μl of sample was transferred to an EP tube. After the addition of 200 μl of extract solution (acetonitrile: methanol = 1: 1, containing isotopically-labelled internal standard mixture), the samples were vortexed for 30 s, sonicated for 10 min in ice-water bath, and incubated for 1 h at −40 ℃ to precipitate proteins. Then the sample was centrifuged at 12,000 rpm for 15 min at 4 ℃ The resulting supernatant was transferred to a fresh glass vial for analysis. The quality control (QC) sample was prepared by mixing an equal aliquot of the supernatants from all samples. And then, LC–MS/MS analyses were performed using an UHPLC system (Vanquish, Thermo Fisher Scientific) with a UPLC BEH Amide column (2.1 mm × 100 mm, 1.7 μm) coupled to Q Exactive HFX mass spectrometer (Orbitrap MS, Thermo). The mobile phase consisted of 25 mmol/l ammonium acetate and 25 ammonia hydroxides in water (pH 9.75) (A) and acetonitrile (B). The auto-sampler temperature was 4 ℃, and the injection volume was 3 μl. The QE HFX mass spectrometer was used for its ability to acquire MS/MS spectra on information-dependent acquisition (IDA) mode in the control of the acquisition software (Xcalibur, Thermo). The raw data were converted to the mzXML format using ProteoWizard and processed with an in-house program, which was developed using R and based on XCMS, for peak detection, extraction, alignment, and integration. Then an in-house MS2 database (BiotreeDB) was applied in metabolite annotation. The cutoff value for annotation was set at 0.3.

Animal experiments

All experimental procedures were performed in adherence to the NIH Guide for the Care and Use of Laboratory Animals and in accordance with protocols approved by the institutional animal care and research advisory committee at Daping hospital, Army Medical University. The db/db mice on C57BLKS/J background (000697), a model of type 2 diabetes in which leptin receptors are deficient, and their nondiabetic heterozygote littermates db/m mice, were purchased from Jackson Laboratory (Bar Harbor, ME). All mice were housed in cages at a controlled temperature (22 ± 1 °C) and relative humidity (55 ± 5%) in a 12-h light/12-h dark cycle. They were supplied with standard laboratory chow and tap water ad libitum. 12-week-old male mice were used to collect tissue samples. At the end of the treatment period, mice were sacrificed after fasting for 14 h. The aorta tissues were collected and quickly frozen in liquid nitrogen for further analysis.

RNA sequencing (RNA-seq)

Total RNA was extracted from the tissues using Trizol (Invitrogen, Carlsbad, CA, USA) according to manual instruction. Subsequently, total RNA was qualified and quantified using a Nano Drop and Agilent 2100 bioanalyzer (Thermo Fisher Scientific, MA, USA). The RNA library construction and subsequent RNA sequencing were performed by BGI-Shenzhen, China. First-strand cDNA was generated using random hexamer-primed reverse transcription, followed by a second-strand cDNA synthesis. afterwards, A-Tailing Mix and RNA Index Adapters were added by incubating to end repair. The cDNA fragments obtained from previous step were amplified by PCR, and products were purified by Ampure XP Beads, then dissolved in EB solution. The product was validated on the Agilent Technologies 2100 bioanalyzer for quality control. The double stranded PCR products from previous step were heated denatured and circularized by the splint oligo sequence to get the final library. The single strand circle DNA (ssCir DNA) was formatted as the final library. The final library was amplified with phi29 to make DNA nanoball (DNB) which had more than 300 copies of one molecular, DNBs were loaded into the patterned nanoarray and single end 50 bases reads were generated on BGIseq500 platform (BGI-Shenzhen, China).

The sequencing data was filtered with SOAPnuke (v1.5.2) by and the clean reads were mapped to the reference genome using HISAT2 (v2.0.4). Bowtie2 (v2.2.5) was applied to align the clean reads to the reference coding gene set, then expression level of gene was calculated by RSEM (v1.2.12). The heatmap was drawn by pheatmap (v1.0.8) according to the gene expression in different samples. Essentially, differential expression analysis was performed using the DESeq2(v1.4.5) with false discovery rate (FDR)-adjusted P-value (q-value) ≤ 0.05. To take insight to the change of phenotype, GO (http://www.geneontology.org/) and KEGG (https://www.kegg.jp/) enrichment analysis of annotated different expressed gene was performed by Phyper (https://en.wikipedia.org/wiki/Hypergeometric_distribution) based on Hypergeometric test. The significant levels of terms and pathways were corrected by FDR-adjusted P-value (q-value), with a rigorous threshold (q ≤ 0.05) by Bonferroni. All analysis were performed on the Dr. Tom analysis system constructed by BGI-Shenzhen, China.

Cell culture

Primary human umbilical vein endothelial cells (HUVECs) were purchased from Procell, China. Cells between four to seven passages were cultured in endothelial growth medium (CM-H082, Procell) containing 5% fetal bovine serum (FBS) and 1% penicillin/streptomycin with all the growth factor supplied at 37℃ with 5% CO2. At approximately 80% confluence, the culture medium was changed to a serum-free DMEM (GIBCO, Rockville, MD, USA) medium for 24 h before the cells were used for further experiments.

In vitro induction of EndMT

To examine the effect of asprosin on the phenotypic transition in HUVECs, cells were treated with PBS (vehicle) or 50 μmol/l asprosin (HY-P7612, MCE) for 24 h. In order to further examine the effect of TGF-β inhibition on asprosin-induced EndMT, cells were treated with DMSO (vehicle) or 10 μmol/l SB431542 (HY-10431, MCE), a specific TGF-β type I receptor inhibitor, for the last 8 h.

Immunofluorescent staining

For immunofluorescent microscopy, HUVECs were labeled with primary antibodies overnight, followed by incubation with a suitable fluorophore-conjugated secondary antibody for 1 h. Specifically, goat anti-mouse-CD31 antibody (MA3100, 1:200; Invitrogen), goat anti-rabbit-alpha smooth muscle actin (α-SMA) antibody (ab124964, 1:300; Abcam) were used to stain the makers of HUVECs and VSMCs, respectively. Immunofluorescent images were obtained using a confocal microscope (A1R HD25, Nikon, Tokyo, Japan) with NIS-Elements BR software (version 3.2. Nikon).

Quantitative PCR

Total RNA was isolated from HUVECs using TRIzol (15,596,026, Invitrogen™). First strand cDNA was synthesized using random primers and EvoScript Universal cDNA Master (Roche, Germany). PCR reactions were carried out with the manufacturer (Light Cycler 96, Roche), using the FastStart Essential DNA Green Master (Roche, Germany). Light Cycler analysis software (Life Technologies, Norwalk, CT) was used to determine crossing points using the second derivative method. Data were normalized to housekeeping genes (β-actin). Details of the primer sequences used are presented in Additional file 1: Table S1.

Western blot

First, HUVECs were lysed in RIPA lysis buffer (65 mM Tris–HCl pH 7.5, 150 mM NaCl, 1 mM EDTA, 1% Nonidet P-40, 0.5% sodium deoxycholate and 0.1% SDS), protease inhibitor cocktail tablets (04693132001; Roche) and phosphatase inhibitor tablets (4906837001; Roche). The protein concentration was determined using the BCA Protein Assay Kit (23225; Thermo Fisher Scientific). Proteins were separated on 10% SDS–PAGE gels and then transferred to PVDF membranes (IPVH00010; Millipore). The membranes were blocked for 1 h at room temperature in Tris-buffered saline and 0.1% Tween-20 (TBST) containing 5% skim milk and then were incubated with primary antibodies in the same buffer at 4 °C overnight as followed: Smad 2/3 (sc-133098, Santa Cruz), p-Smad2/3 (sc-11769, Santa Cruz), TGF-β1 (ab215715, Abcam), CD31 (sc-376764, Santa Cruz), VWF (sc-14014, Santa Cruz), NOS3 (sc-136977, Santa Cruz), α-SMA (ab7817, Abcam), TAGLN (ab14106, Abcam), collagen I (ab88147, Abcam), CTGF (sc-34772, Santa Cruz), β-actin (66009-1-Ig, Proteintech). After washes and incubation with the appropriate horse radish peroxidase-conjugated secondary antibody (Santa Cruz Biotechnology), the immune complexes were visualized using a chemiluminescence reagent. Western blot results were densitometrically quantified with Quantity One software (Bio-Rad), and the intensity values were normalized to β-actin.

Statistical analysis

The continuous variables were expressed as means (mean ± standard deviation [SD]), or as medians (interquartile range [IQR]) based on the distribution, which is determined by the Shapiro–Wilk test. The categorical variables were expressed as n (%). The differences between groups were analyzed by ANOVA test (continuous variables with normal distribution) or Kruskal–Wallis H test (continuous variables with skewed distribution) or chi-squared test (categorical variables). Spearman’s correlative analysis was used to analyze the correlations of circulating asprosin levels with ABI and TBI. Multiple linear regression analysis was conducted to further evaluate the relationship between circulating asprosin levels and ABI/TBI in different models. Multiple logistic regression analysis was used to determine the effect on circulating asprosin levels the risk of PAD. The area under the receiver operating characteristic (ROC) curve was calculated to test the discrimination of PAD. P < 0.05 was set as statistically significant. Graphs were created using Prism 8.0 (GraphPad Software). All the statistical analyses about clinical data were performed using SPSS 26.0 software (SPSS Inc., Chicago, USA), while all the statistical analyses about cells were performed with GraphPad Prism.

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