Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR-33a dysregulation in peripheral blood mononuclear cells

GENE-40570; No. of pages: 7; 4C: Gene xxx (2015) xxx–xxx

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Gene journal homepage: www.elsevier.com/locate/gene

Research paper

Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR-33a dysregulation in peripheral blood mononuclear cells D.Z. Scherrer a,1, V.H.S. Zago a,1,⁎, E.S. Parra a, S. Avansini b, N.B. Panzoldo a, F. Alexandre a, J. Baracat c, E.R. Nakandakare d, E.C.R. Quintão d, E.C. de Faria a a

Department of Clinical Pathology, Faculty of Medical Sciences, 126, Tessália Vieira de Camargo St., University of Campinas, Campinas, 13084-971 São Paulo, Brazil Department of Medical Genetics, Faculty of Medical Sciences, 126, Tessália Vieira de Camargo St., University of Campinas, Campinas, 13084-971 São Paulo, Brazil c Department of Radiology, Faculty of Medical Sciences, 126, Tessália Vieira de Camargo St., University of Campinas, Campinas, 13084-971 São Paulo, Brazil d Lipid Laboratory, Faculty of Medical Sciences, 455, Dr Arnaldo St., University of São Paulo, São Paulo, 01246-000 São Paulo, Brazil b

a r t i c l e

i n f o

Article history: Received 11 December 2014 Received in revised form 19 May 2015 Accepted 31 May 2015 Available online xxxx Keywords: ABCA1 ABCG1 MicroRNA HDL

a b s t r a c t Considering the growing knowledge and perspectives on microRNAs (miRNAs) that control high-density lipoprotein cholesterol (HDL-C) levels and metabolism, this study aimed at evaluating whether hsa-miR-33a and hsa-miR-128a are differentially expressed in peripheral blood mononuclear cells from asymptomatic individuals with low and high HDL-C, as well as at investigating the potential relationships with ATP binding cassete transporter A1 (ABCA1) expression, cholesterol efflux capacity and other parameters related with reverse cholesterol transport. In addition, the associations with cardiovascular risk were investigated by carotid-intima media thickness (cIMT). Asymptomatic volunteers of both genders (n = 51) were classified according to HDLC (mg/dL) in hypoalphalipoproteinemics (hypo, HDL-C ≤ 39), hyperalphalipoproteinemics (hyper, HDL-C ≥ 68) and controls (CTL, HDL-C ≥ 40 b 68). cIMT, lipids, lipoproteins, HDL size and volume, C reactive protein and insulin were determined, as well as the activities of several proteins and enzymes related to HDL metabolism. In a subgroup of 19 volunteers the cellular cholesterol efflux and HDL composition were determined. Total RNA was extracted from peripheral blood mononuclear cells for relative quantification experiments. Hypo volunteers presented significantly higher levels of triglycerides, VLDL-C and insulin; in addition, HDL size and volume decreased when compared with CTL and hyper. Regarding gene expression analysis, the hyper group presented a decrease of 72% in hsa-miR-33a and higher mRNA expression of ABCA1 and ABCG1 when compared with CTL. No significant differences in hsa-miR-128a expression, cholesterol efflux, cIMT or plaques were found. Further studies are necessary to elucidate the mechanisms underlying the complex miRNA network, regulating cellular cholesterol homeostasis in humans and its clinical repercussions. © 2015 Elsevier B.V. All rights reserved.

Abbreviations: ABCA1, ATP binding cassete transporter A1; ABCG1, ATP binding cassete transporter G1; ANCOVA, analysis of covariance; ANOVA, analysis of variance; Apo A-I, apolipoprotein A-I; Apo B, apolipoprotein B; BAI, body adiposity index; BMI, body mass index; cDNA, complementary DNA; CE, cholesteryl ester; CETP, cholesteryl ester transfer protein; cIMT, carotidintima media thickness; CRP, C reactive protein; CT, comparative threshold; CTL, controls; CVD, cardiovascular disease; DBP, diastolic blood pressure; DLS, dynamic light scattering; DMEM, Dulbecco's modified Eagle's medium; EDTA, ethylenediamine tetraacetic acid; ELISA, enzyme-linked immunosorbent assay; FAFA, fatty acid-free albumin; GAPDH, glyceraldehyde 3phosphate dehydrogenase; HDL, high-density lipoprotein; HDL-C, high-density lipoprotein cholesterol; HL, hepatic lipase; HOMA, homeostatic model assessment; HPRT1, hypoxanthine guanine phosphoribosyltransferase 1; Hyper, hyperalphalipoproteinemics; Hypo, hypoalphalipoproteinemics; LAP, lipid accumulation product; LCAT, lecithin-cholesterol acyltransferase; LDL, low-density lipoprotein; LDL-C, low-density lipoprotein cholesterol; Lp(a), lipoprotein (a); LPL, lipoprotein lipase; miRNA, microRNAs; mRNA, messenger RNA; N, number of individuals; PBS, phosphate-buffered saline; PCR, polymerase chain reaction; PEG, polyethylene glycol; PGK1, phosphoglycerate kinase 1; PLTP, phospholipid transfer protein; PON-1, paraoxonase-1; RCT, reverse cholesterol transport; RNA, ribonucleic acid; RPMI, Roswell Park Memorial Institute; SBP, systolic blood pressure; SCARB1, scavenger receptor class B type I; snRNA, small nuclear RNA; SREBF1, sterol regulatory element-binding transcription factor 1; SREBF2, sterol regulatory element-binding transcription factor 2; SREBP1, sterol regulatory element-binding protein 1; SREBP2, sterol regulatory element-binding protein 2; UTR, untranslated region; UV, ultraviolet; VLDL, very low-density lipoprotein; VLDL-C, very low-density lipoprotein cholesterol. ⁎ Corresponding author at: Department of Clinical Pathology, FCM-UNICAMP, 126 Tessália Vieira de Camargo Street, Campinas, 13084-971 SP, Brazil. E-mail address: [email protected] (V.H.S. Zago). 1 The authors equally contributed to the manuscript.

http://dx.doi.org/10.1016/j.gene.2015.05.074 0378-1119/© 2015 Elsevier B.V. All rights reserved.

Please cite this article as: Scherrer, D.Z., et al., Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR33a dysregulation in peripheral blood mononuclear cells..., Gene (2015), http://dx.doi.org/10.1016/j.gene.2015.05.074

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D.Z. Scherrer et al. / Gene xxx (2015) xxx–xxx

1. Introduction

2.2. Clinical and anthropometrical data

Plasma levels of high-density lipoprotein cholesterol (HDL-C) are considered a significant and independent predictor of cardiovascular disease (CVD) risk, according to evidences derived from clinical and epidemiological studies (Gordon et al., 1989; Amarenco et al., 2008). Furthermore, HDL-C levels are under strong genetic control, and despite monogenic disorders, most cases result from the interaction between multiple genes and environmental factors (Weissglas-Volkov and Pajukanta, 2010). The protective role of HDL particles is explained by their multiple properties, such as cholesterol efflux capacity, and antiinflammatory, antioxidant, antiapoptotic, vasodilatory, anti-thrombotic, as well as anti-infectious activities (Kontush and Chapman, 2006). However, reverse cholesterol transport (RCT), in which HDL particles remove cholesterol from peripheral tissues and macrophages from the liver for excretion, has a particular key role in the development of atherosclerosis. Recent discoveries of microRNAs (miRNAs) that control HDL levels and function expanded the knowledge of the mechanisms regulating its biogenesis, uptake and RCT (Rayner and Moore, 2014). In this regard, several miRNAs targets the ATP binding cassette transporter A1 (ABCA1), a transporter that controls the rate of cholesterol efflux to apolipoprotein A-I (apo A-I) and consequently HDL biogenesis (Yokoyama, 2006). In fact, ABCA1 has a long 3′ untranslated region (3′ UTR) as compared to other common genes involved in cholesterol and HDL metabolism, raising the probability of posttranscriptional regulation by miRNAs (Davalos and Fernandez-Hernando, 2013). The first to be identified as ABCA1 regulators were miR-33a and miR-33b (Rayner et al., 2010; Najafi-Shoushtari et al., 2010), which are embedded in intronic regions of sterol regulatory element-binding transcription factor 2 (SREBF2) and SREBF1, that code for sterol regulatory element-binding protein 2 (SREBP2) and SREBP1. In addition, miRNAs as miR-758, miR-106b, miR-26, miR-144, miR-10b, miR-145 and miR-128a were also experimentally validated for their importance to cholesterol efflux and RCT (Rayner and Moore, 2014). Since the cholesterol efflux from peripheral cells (first and key step in RCT pathway) represent the most clinically relevant atheroprotective function of HDL, probably forming the basis between HDL-C levels and CVD (von Eckardstein et al., 2001) and that ABCA1 has a fundamental role in this process, this study aimed at evaluating whether miRNAs hsa-miR-33a and hsa-miR-128a are differentially expressed in peripheral blood mononuclear cells from asymptomatic individuals with low and high HDL-C levels, as well as investigating their potential relationships with ABCA1 expression and other parameters related with reverse cholesterol transport, as cholesterol efflux. We also aimed at determining their relationships with carotid atherosclerosis.

Clinical and anthropometrical data as body weight, height, BMI, waist and hip circumference, as well as systolic and diastolic blood pressures (SBP and DBP, respectively) were obtained at admission. Moreover, waist-to-hip and waist-to-height ratios, body adiposity index (BAI = ((hip circumference) / ((height)1.5) − 18) and lipid accumulation product ((LAP, for males = (waist circumference − 65) × triglycertriglycerides), for females = (waist circumference − 58) × triglycerides)) (Bergman et al., 2011; Kahn, 2005) were calculated.

2. Materials and methods 2.1. Study subjects Volunteers of both genders were recruited from primary health care centers in Campinas (SP-Brazil). Nonsmokers, asymptomatic individuals with body mass index (BMI) lower than 30 kg/m2, without regular use of any medications that interfere with lipid metabolism and daily intake of alcohol lower than 14 g, as previously described, were included (Parra et al., 2013). Thus, 51 volunteers were selected and classified, according to plasma HDL-C levels (mg/dL), into three groups: hypoalphalipoproteinemics (hypo, HDL-C ≤ 39, n = 17), hyperalphalipoproteinemics (hyper, HDLC ≥ 68, n = 17) and controls (CTL, HDL-C ≥ 40 b 68, n = 17). They were invited to a blood collection for biochemical measurements and real-time PCR analysis. The study was approved by the Research Ethics Committee of the Faculty of Medical Sciences, University of Campinas and each participant provided written informed consent.

2.3. Biochemical analysis Venous blood samples were drawn after a 12-hour fasting period. Serum and EDTA plasma were separated by centrifugation (4 °C, 1000 ×g, 10 min) and stored at −80 °C until analysis. Total cholesterol, triglycerides and HDL-C were measured in an automated system Modular Analytics® EVO (Roche Diagnostics, Burgess Hill, West Sussex, UK), using Roche Diagnostics® reagents (Mannheim, Germany). Lowdensity lipoprotein cholesterol (LDL-C) was calculated by Friedwald equation and very low-density lipoprotein cholesterol (VLDL-C) by triglycerides / 5 (Friedewald et al., 1972). Apolipoproteins A-I, B (apo B) and lipoprotein (a) (Lp(a)) were determined by nephelometry in automated system BN II (Siemens Healthcare Diagnostics, Marburg, Germany), using commercially available assays (Dade-Boehringer®, Deerfield, Illinois, USA). C-reactive protein (CRP) was measured using the Tina-quant® CRP (latex) high sensitivity assay (Roche Diagnostics®, Mannheim, Germany) by immunoturbidimetry. Insulin was determined using an ELISA assay (Human Insulin ELISA kit, Millipore Corporation, MA, USA). Homeostasis Model Assessment (HOMA) Calculator 2.2.2 (University of Oxford, UK) was used to estimate the insulin sensitivity (HOMA-S) and β cell function (HOMA-β) (Caumo et al., 2006). 2.3.1. HDL particle size, volume and chemical composition For particle size and volume determinations, HDL was isolated by the precipitation of apo B containing lipoproteins with polyethylene glycol (PEG) 8000 (Sigma-Aldrich, St. Louis, USA), as previously reported (Dias et al., 1988). After PEG precipitation, HDL samples were maintained at 25 °C in a heat block and immediately analyzed by the dynamic light scattering (DLS) technique on Nanotrac Particle Size Analyzer (Microtrac, North Largo, Florida, USA) (Lima and Maranhao, 2004). The measurements were performed in triplicate and each sample was analyzed three times with 30 s of running time. A 100 nm polymeric nanoparticle was used as the standard and a control sample obtained from the same individual plasma was used in all determinations. HDL volume (nm3) was calculated using the Microtrac FLEX Software (Microtrac, USA). The measurements of HDL composition were performed in a subgroup of 19 volunteers (6 hypo, 6 controls and 7 hyper) and determined after the lipoprotein isolation from plasma through density gradient ultracentrifugation, using a SW41Ti rotor (Chapman et al., 1981). All assays were performed in freshly isolated lipoproteins, kept refrigerated for a maximum period of 7 days. In 96-well microplates the particle content of total protein (Pierce™ BCA Protein Assay Kit, Thermo Scientific, Rockford, USA), total cholesterol (CHOD-PAP, Roche Diagnostics® reagents, Mannheim, Germany), free cholesterol (Free Cholesterol E, Wako Chemicals, Richmond, USA), phospholipids (Phospholipids C, Wako Chemicals, Richmond, USA), triglycerides (GPO-PAP, Roche Diagnostics ® reagents, Mannheim, Germany) and apo A-I (TINA QUANT APO A1 V2, Roche Diagnostics® reagents, Mannheim, Germany) were measured using commercially available kits, in the microplate reader Power Wave XS (BioTek ®, Winooski, USA). Cholesteryl ester was calculated as the difference between total cholesterol and free cholesterol times 1.67 (Chapman et al., 1981).

Please cite this article as: Scherrer, D.Z., et al., Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR33a dysregulation in peripheral blood mononuclear cells..., Gene (2015), http://dx.doi.org/10.1016/j.gene.2015.05.074

D.Z. Scherrer et al. / Gene xxx (2015) xxx–xxx

2.3.2. Cellular cholesterol efflux Cellular cholesterol efflux was also measured in a subgroup of volunteers (6 hypo, 6 controls and 7 hyper); J774 macrophages enriched with acetylated LDL and 14C-cholesterol, using HDL as the cholesterol acceptor, as described earlier (Machado-Lima et al., 2013). Briefly, J774 macrophages were cultured in RPMI 1640 medium containing 10% fetal calf serum, penicillin and streptomycin and maintained in a 5% CO2 incubator at 37 °C. After reaching confluence, the cells were plated in a 96-well culture microplate (1.25 × 105 cells/mL), and enriched with acetylated LDL (50 μg/mL) and 14C-cholesterol (0.3 μCi/mL). After 48 h, cells were washed with PBS containing fatty acid-free albumin (FAFA), and incubated with Dulbecco's modified Eagle's medium (DMEM) containing FAFA for 24 h. The cells were, then, washed twice with PBS + FAFA, and incubated with HDL (50 μg apo A-I/mL) for 8 h. Media were collected, and the radioactivity measured in a beta-scintillation counter. Cells were rinsed twice with cold physiologic saline and the intracellular lipids extracted with hexane:isopropanol (3:2, v/v). Solvent was evaporated and radioactivity measured. The percentage of 14C-cholesterol efflux was calculated as (14Ccholesterol in the medium/14C-cholesterol in cells plus medium) × 100. 2.3.3. Components of reverse cholesterol transport and HDL metabolism Cholesteryl ester transfer protein (CETP) and phospholipid transfer protein (PLTP) activities were determined using exogenous radiometric assays, and PLTP mass was measured by ELISA, as previously described (Lagrost, 1998; Jauhiainen and Ehnholm, 2005). Lipoprotein lipase (LPL) and hepatic lipase (HL) activities were measured in post-heparin plasma samples on the basis of fatty acid release, using a radiolabeled triolein emulsion as substrate and NaCl (1 M) as LPL inhibitor (Ehnholm and Kuusi, 1986). Plasma exogenous lecithin: cholesterol acyltransferase (LCAT) activity (nmol/mL/h) was determined using a recombinant HDL3 and the endogenous activity (% CE) by the rate of esterification of 14C-free cholesterol by LCAT in the subject HDL (Jauhiainen and Dolphin, 1986; Dobiasova et al., 1992). Paraoxonase-1 (PON-1) activity was measured using paraoxon (diethyl-p-nitrophenylphosphate, Sigma, St. Louis, MO, USA) as substrate (Kleemola et al., 2002). 2.4. Real-time PCR analysis 2.4.1. RNA extraction Peripheral blood mononuclear cells were isolated by density gradient using Histopaque-1077 (Sigma-Aldrich, St. Louis, MO, USA), and total RNA (including miRNA) was isolated using TRIzol® (TRIzol Reagent — Life Technologies, Carlsbad, CA, USA), both following the manufacturer's protocol. Total RNA concentration was determined using the Qubit® Quantitation Platform with the Qubit® RNA BR Assay (Life Technologies, Carlsbad, CA, USA). The purity was determined by UV spectrophotometry at 260/280 nm and 260/230 nm with the Epoch (Bioteck, Winooski, Vermont, USA), and RNA integrity was analyzed by 1% agarose gel electrophoresis. 2.4.2. mRNA expression Complementary DNA (cDNA) was obtained by reverse transcription reaction, using a commercially available set of High Capacity cDNA Archive Kit (Applied Biosystems, Carlsbad, CA, USA) and random primers, according to standard protocol. Gene expression analysis of ABCA1, ABCG1 and SCARB1 were performed using quantitative real-time PCR with the Applied Biosystems 7500 Real-Time PCR System (Applied Biosystems, CA, USA), and the experiments were carried out using the human commercial available assays Hs01059118_ml, Hs00245154_ml and Hs00194092_m1, respectively. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), hypoxanthine guanine phosphoribosyltransferase 1 (HPRT1) and phosphoglycerate kinase 1 (PGK1) were used as endogenous controls.

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Reactions were performed using 6.25 μL of TaqMan® PCR MasterMix (Applied Biosystems, CA, USA), 0.625 μL of primers and probes, 1.625 μL of water, and 4 μL of cDNA. Cycle conditions were 50 °C for 2 min, 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s, and 60 °C for 1 min. All relative quantification experiments were performed in triplicate and the mRNA expression levels was calculated using the 2−ΔΔCT (comparative threshold cycle, or CT) method (Livak and Schmittgen, 2001). 2.4.3. miRNA expression To analyze the expression of hsa-miR-33a (MIMAT0004506, 2135) and hsa-miR-128a (MIMAT0000424, 2216), reverse transcription was performed using High Capacity cDNA Archive Kit (Applied Biosystems, Carlsbad, CA, USA) of each miRNA-specific cDNA, 10 ng of total RNA in a 15 μL reaction volume containing 1 × RT buffer, 0.15 μL of 100 mM dNTPs, 0.19 μL of RNase inhibitor (20 units/mL), 1 μL of MultiScribeTM Reverse Transcriptase (50 units/mL) and 3 μL of each of the miRNA specific stem-loop primers. Quantitative real-time PCR was performed after cDNA amplification, and the reactions were performed using 6.0 μL of TaqMan® Universal PCR MasterMix (Applied Biosystems), 0.625 μL of primers and probes, 1.625 μL of water and 4 μL of cDNA. The reaction conditions were as follows: 50 °C for 2 min, then 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min in the Applied Biosystems 7500 Real-Time PCR System (Applied Biosystems, Carlsbad, CA, USA). All relative quantification experiments were performed in triplicate and the results were normalized to the expression of the small nuclear RNAU6B (U6 snRNA, 1973). The hsa-miR-33a and hsa-miR-128a expressions were calculated by using the 2−ΔΔCT method (Livak and Schmittgen, 2001). 2.5. Carotid intima-media thickness measurements High resolution B-mode carotid ultrasonography was performed by a trained sonographer, who was blinded to the subject identity, using a 6–9 MHz linear array ultrasound imaging system (ATL HDI 1500 and 3500 Ultrasound System, Advanced Technology Laboratories Ultrasound, Bothell, EUA). The volunteers were examined in dorsal decubitus with the head elevated about 20° and rotated 45°, and the far wall of the distal 1 cm of the left and right common carotid arteries was scanned according to a standardized method (Simons et al., 1999). The mean cIMT was calculated as the average of five measurements on each side (right and left) and expressed in mm. Carotid atherosclerotic plaques were also accessed by carotid ultrasonography, and defined as an echogenic thickening of intimal reflection that encroaches in the arterial lumen with a minimal intimal-medial thickness of N 1.2 mm or a focal structure encroaching into the arterial lumen by at least 50% more of the surrounding intima-media thickness values. 2.6. Statistical analysis The analyses were performed using the software SPSS Statistics 16.0. A two-sided p-value ≤ 0.05 was considered as statistically significant, and p-values N 0.05 and ≤0.09 were considered borderline. The normal distribution of the studied variables was determined by the Kolmogorov–Smirnov test. Comparisons between HDL-C groups were performed using Kruskal–Wallis or ANOVA, followed by the Bonferroni's test for non-normal and normal data, respectively. Chisquare test was performed for categorical variables. When necessary, the analyses were controlled by ANCOVA for age, gender and BMI. 3. Results The study comprised non-obese and asymptomatic subjects, 51% of females and 49% of males aged 21–71 years. Clinical and anthropometric characteristics, along with biochemical profile of the studied groups are demonstrated in Table 1.

Please cite this article as: Scherrer, D.Z., et al., Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR33a dysregulation in peripheral blood mononuclear cells..., Gene (2015), http://dx.doi.org/10.1016/j.gene.2015.05.074

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D.Z. Scherrer et al. / Gene xxx (2015) xxx–xxx

No significant differences were observed between the groups regarding cIMT, atherosclerotic plaques or C-reactive protein. However, hypo volunteers presented significantly higher plasma levels of triglycerides, VLDL-C, insulin, HOMA-S and HOMA-β when compared with hyper individuals. Furthermore, several parameters related to HDL metabolism and reverse cholesterol transport were evaluated and compared, as shown in Table 2. HDL particle size was significantly increased by 16% and HDL volume by 54% in hyper when compared with hypo group; additionally, PLTP mass was 34% lower in hypo individuals. Despite the increase in HDL size and volume, no significant differences were observed regarding cellular cholesterol efflux and HDL chemical composition among the groups, but a tendency to higher cholesteryl ester content (p = 0.07) was observed between hyper and the other groups, as demonstrated in Table 3. ABCA1, ABCG1 and SCARB1 mRNA expression were also determined and compared among the groups, as shown by Fig. 1A. ABCA1 mRNA expression was 34% higher in hyper when compared with hypo group (hyper, 0.98 ± 0.43; hypo, 0.65 ± 0.27; p b 0.05). Moreover, in the analysis between hyper and CTL groups, hyper presented significant increases for mRNA expression of ABCA1 (hyper, 0.98 ± 0.43; CTL, 0.74 ± 0.27; p b 0.05) and ABCG1 (hyper, 1.43 ± 0.31; CTL, 1.20 ± 0.35; p b 0.05). In the comparisons of hsa-miR-33a expression among the three groups (Fig. 1B) hyper volunteers, when compared with CTL group, presented a significant decrease of 72% of hsa-miR-33a (hyper, 0.13 (0.27); CTL, 0.47 (0.81); p b 0.05). Regarding hsa-miR-128a expression, no significant differences were observed among the groups (hyper, 0.23 (0.20); CTL, 0.46 (0.39); hypo, 0.20 (0.19); p N 0.05).

Table 1 Clinical, anthropometric and biochemical characteristics of hypo, hyper and CTL volunteers. Parameters

Hypo (n = 17)

CTL (n = 17)

Gender, F/M 8/9 9/8 Age, years 39 ± 13 48 ± 16 BMI, kg/m2 23.7 ± 2.4 22.8 ± 2.0 Waist circumference, cm 76 ± 9 75 ± 8 Hip circumference, cm 93 (11) 92 (11) Waist-to-hip ratio 0.83 (0.08) 0.78 (0.11) Waist-to-height ratio 0.46 ± 0.06 0.45 ± 0.05 LAP, cm·mmol/L 19.34 ± 12.61 16.81 ± 9.64 BAI, % 26.16 ± 5.75 24.47 ± 7.49 SBP, mm Hg 120 (15) 120 (18) DBP, mm Hg 80 (3) 80 (12) Mean cIMT, mm 0.55 (0.31) 0.58 (0.41) Plaques, (Y/N) 4/12 6/10 Total cholesterol, mg/dL 158 ± 20 178 ± 19 HDL-C, mg/dL 36 (7) 48 (28) Non HDL-C, mg/dL 123 ± 19 128 ± 20 Triglycerides, mg/dL 105 ± 32 92 ± 37 LDL-C, mg/dL 102 ± 17 109 ± 16 VLDL-C, mg/dL 21 ± 6 19 ± 7 Apo A-I, mg/dL 115 ± 19 146 ± 31 Apo B, mg/dL 83 ± 20 87 ± 13 Lp(a), mg/dL 9.84 (23.74) 14.55 (22.07) hsCRP, mg/L 0.80 (1.80) 1.60 (3.50) Insulin, μU/mL 5.91 ± 3.55 4.85 ± 2.97 HOMA-S 1.22 ± 0.70 0.93 ± 0.58 HOMA-β 116.65 ± 79.69 82.70 ± 59.46

Hyper (n = 17) 9/8 50 ± 10 22.7 ± 2.1 72 ± 5 90 (10) 0.80 (0.06) 0.44 ± 0.03 8.70 ± 6.21 23.59 ± 6.81 120 (20) 80 (4) 0.70 (0.12) 3/13 201 ± 34 79 (18) 121 ± 29 66 ± 20 107 ± 27 13 ± 4 182 ± 27 81 ± 21 6.34 (22.75) 0.70 (0.80) 3.30 ± 1.35 0.69 ± 0.28 58.93 ± 34.07

p 0.734 0.037a 0.365 0.312 0.326 0.791 0.453 0.009a 0.542 0.549 0.693 0.184 0.478 b0.0001a,c – 0.689 0.002a,c 0.650 0.002a,c b0.0001a,b,c 0.694 0.653 0.201 0.030a 0.027a 0.027a

Hypo, hypoalphalipoproteinemia, HDL-C ≤ 39 mg/dL. Hyper, hyperalphalipoproteinemia, HDL-C ≥ 68 mg/dL. CTL, controls, HDL-C between 40–67 mg/dL. F, females. M, males. BMI, body mass index. LAP, lipid accumulation product. BAI, body adiposity index. SBP, systolic blood pressure. DBP, diastolic blood pressure. cIMT, carotid intima-media thickness. Y, yes. N, no. HDL-C, high-density lipoprotein cholesterol. LDL-C, low-density lipoprotein cholesterol. VLDL-C, very-low density lipoprotein cholesterol. Apo, apolipoprotein. Lp(a), lipoprotein (a). hsCRP, high sensitivity C-reactive protein. HOMA, Homeostasis Model Assessment. Normal and non-normal data are presented as mean ± standard deviation and median (interquartile range), respectively. P-values: ANOVA or Kruskal– Wallis. Significant differences (p ≤ 0.05) by Bonferroni were indicated by aHypo ≠ Hyper, b Hypo ≠ CTL and cHyper ≠ CTL. Comparisons adjusted by ANCOVA for age, gender and BMI.

Table 2 Differences among components of HDL metabolism in hypo, hyper and CTL volunteers. Parameters

Hypo (n = 17)

HDL particle size, nm 7.25 ± 0.46 HDL volume, nm3 117.16 ± 22.51 PON1, μmol/min 30.00 (63.25) CETP, % 12.00 ± 3.80 HL, nmol FFA/mL/h 6936 ± 3565 LPL, nmol FFA/mL/h 2692 (2694) LCAT, nmol/mL/h 15.98 ± 7.49 LCAT, % CE 3.61 ± 1.11 PLTP, nmol FC/mL/h 6099 ± 2407 PLTP mass, μg/mL 5.43 ± 0.97

CTL (n = 17)

Hyper (n = 17)

p

7.68 ± 0.50 139.84 ± 29.38 31.85 (41.68) 14.15 ± 6.13 5735 ± 4900 5882 (4210) 17.83 ± 7.93 3.60 ± 2.13 6082 ± 3555 7.05 ± 1.16

8.38 ± 0.32 b0.0001a,b,c 180.87 ± 28.26 b0.0001a,c 17.60 (38.80) 0.569 12.50 ± 4.59 0.438 5291 ± 3349 0.477 5038 (4739) 0.369 17.68 ± 7.09 0.788 2.29 ± 0.56 0.075 6266 ± 2824 0.981 7.30 ± 0.89 0.0001a,b

Hypo, hypoalphalipoproteinemia, HDL-C ≤ 39 mg/dL. Hyper, hyperalphalipoproteinemia, HDL-C ≥ 68 mg/dL. CTL, controls, HDL-C between 40–67 mg/dL. PON1, paraoxonase 1. CETP, cholesteryl ester transfer protein. HL, hepatic lipase. LPL, lipoprotein lipase. FFA, free fatty acids. LCAT, lecithin cholesterol acyl transferase. PLTP, phospholipid transfer protein. CE, cholesteryl ester. FC, free cholesterol. Normal and non-normal data are presented as mean ± standard deviation and median (interquartile range), respectively. p-Values: ANOVA or Kruskal–Wallis. Significant differences (p ≤ 0.05) by Bonferroni were indicated by aHypo ≠ Hyper, bHypo ≠ CTL and cHyper ≠ CTL. Comparisons adjusted by ANCOVA for age, gender and BMI.

4. Discussion The present study investigated the expression of hsa-miR-33a and hsa-miR-128a in peripheral blood mononuclear cells from asymptomatic individuals with low and high HDL-C levels. In fact, we demonstrated that hsa-miR-33a, but not hsa-miR-128a, is differentially expressed in high HDL-C individuals. Regarding HDL-C groups, it is important establish that hypo and hyper volunteers present several metabolic differences. The low HDLC phenotype is highly associated with metabolic disorders and cardiovascular risk, as well as an inflammatory and oxidative phenotype (Holven et al., 2013). Moreover, previous studies suggested that low HDL-C could represent a causative role in the development of insulin resistance (von Eckardstein and Sibler, 2011); epidemiologically, low HDL-C may lead to the development of diabetes mellitus (Rohrer et al., 2004). The dyslipidemia observed in insulin resistance states is usually associated with increased hepatic production of VLDL (Kissebah et al., 1982; Duvillard et al., 2000; Ouguerram et al., 2003; Cummings et al., 1995), leading to altered HDL composition through CETP and hepatic

Table 3 HDL chemical composition and cellular cholesterol efflux in hypo, hyper and CTL volunteers. Parameters

Hypo (n = 6)

CTL (n = 6)

Hyper (n = 7)

p

Cholesterol efflux, % HDL-TC, mg/dL HDL-TG, mg/dL HDL-FC, mg/dL HDL-CE, mg/dL HDL-PL, mg/dL HDL-apo A-I, mg/dL % TG % FC % CE % PL % Apo A-I

10.55 ± 4.31 25.93 ± 21.25 7.73 ± 1.74 4.92 ± 3.90 35.08 ± 29.25 25.67 ± 7.22 73.61 ± 38.37 3.96 ± 1.39 2.35 ± 1.48 16.72 ± 11.37 13.13 ± 4.68 35.19 ± 17.45

13.11 ± 1.64 39.81 ± 16.66 10.32 ± 4.80 7.15 ± 2.70 54.54 ± 24.30 33.21 ± 10.64 89.63 ± 13.98 4.61 ± 3.13 3.01 ± 1.06 22.71 ± 9.40 13.96 ± 4.38 37.67 ± 8.29

11.87 ± 3.47 57.07 ± 19.39 7.89 ± 3.89 7.85 ± 2.70 82.19 ± 29.60 35.03 ± 11.00 103.09 ± 27.27 2.63 ± 1.20 2.55 ± 0.67 26.31 ± 6.56 11.38 ± 2.44 33.43 ± 4.05

0.314 0.095 0.393 0.694 0.070 0.927 0.166 0.182 0.852 0.347 0.159 0.989

Hypo, hypoalphalipoproteinemia, HDL-C ≤ 39 mg/dL. Hyper, hyperalphalipoproteinemia, HDL-C ≥ 68 mg/dL. CTL, controls, HDL-C between 40–67 mg/dL. HDL, high-density lipoprotein. TC, total cholesterol. TG, triglycerides. FC, free cholesterol. CE, cholesteryl ester. PL, phospholipids. Apo, apolipoprotein. % of TG, FC, CE, PL and apo A-I were calculated according to HDL total mass. Normal and non-normal data are presented as mean ± standard deviation and median (interquartile range), respectively. p-Values: ANOVA or Kruskal–Wallis. Significant differences (p ≤ 0.05) by Bonferroni were indicated by aHypo ≠ Hyper, bHypo ≠ CTL and cHyper ≠ CTL. Comparisons adjusted by ANCOVA for age, gender and BMI.

Please cite this article as: Scherrer, D.Z., et al., Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR33a dysregulation in peripheral blood mononuclear cells..., Gene (2015), http://dx.doi.org/10.1016/j.gene.2015.05.074

D.Z. Scherrer et al. / Gene xxx (2015) xxx–xxx

Fig. 1. A, Gene expression of ABCA1, ABCG1 and SCARB1 in CTL, hyper and hypo volunteers. Significant differences (*p ≤ 0.05) were observed for ABCA1 in hypo × hyper (hypo, 0.65 ± 0.27; hyper, 0.98 ± 0.43) and hyper × CTL (hyper, 0.98 ± 0.43; CTL, 0.74 ± 0.27). ABCG1 significant differences were observed for hyper × CTL (hyper, 1.43 ± 0.31; CTL, 1.20 ± 0.35). B, hsa-miR-128a and hsa-miR-33a expressions in CTL, hyper and hypo volunteers. Significant differences (*p ≤ 0.05) were observed for hsa-miR-33a in hyper × CTL (hyper, 0.13 (0.27); CTL, 0.47 (0.81)).

lipase activities. Small, dense HDL particles produced are rapidly catabolized, and consequently HDL-C levels are decreased (Rashid et al., 2003). Similarly, asymptomatic individuals of the study, characterized by low plasma HDL-C levels, present a significant increase of insulin, HOMA indexes, VLDL-C and triglycerides. In addition, HDL particle size and volume were significantly lower, indicating a possible increase in HDL catabolism. Previous findings from our group in another cohort of healthy, normal weight individuals, demonstrated that plasma HDL-C variations are related to several parameters controlling plasma lipoprotein metabolism and to the degree of insulin sensitivity (Leanca et al., 2013). In fact, the isolated low HDL-C is commonly found with hyperinsulinism, without hypertriglyceridemia or other lipoprotein variations (Rashid et al., 2003; Karhapaa et al., 1994). Furthermore, differences in the main components involved with HDL metabolism and reverse cholesterol transport were expected; despite the lack of significant differences of CETP, hepatic lipase and lipoprotein lipase between hypo and hyper individuals, the PLTP mass diminished by 26% in hypo group. As previously demonstrated in 2002 by Oka et al. (2002), PLTP activity was similar between hypo and CTL individuals, while PLTP mass was significantly lower, probably due to the absence of inactive PLTP. In fact, low HDL-C phenotype and/or increased triglycerides alter the distribution of active and inactive PLTP (Huuskonen et al., 2000; Oka et al., 2000). Additionally, Yatsuya et al. (2004) demonstrated in a prospective study that serum PLTP mass is inversely associated with the risk of coronary heart disease, independently of HDL-C, triglycerides and other established risk factors. In addition, mRNA ABCA1 expression was significantly decreased in the hypo group in relation to hyper individuals. ABCA1 gene is primarily regulated by the liver X receptor (Venkateswaran et al., 2000); furthermore, SREBP2 in hepatocytes also contributes to ABCA1 expression to

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maintain cholesterol homeostasis (Tamehiro et al., 2007). Since ABCA1 plays an important role in the balance of cellular cholesterol in monocytes and macrophages, preventing the development/progression of atherosclerotic lesions, the posttranscriptional regulation of ABCA1 has received growing attention due to the discovery of several potential therapeutic targets, as reviewed by Lv et al. (2013). It is possible that ABCA1 mRNA levels were down-regulated in hypo individuals by the interaction of several factors, including ABCA1 regulation by insulin and miRNAs. Evidences indicated that insulin decreases ABCA1 specific activity by its phosphorylation at a specific site; still, insulin downregulates ABCA1 protein level in cultured cells, probably accelerating its degradation (Spartano et al., 2014; Nonomura et al., 2011). Conversely, a significant difference regarding the studied miRNAs would be expected, due to their emerging role in lipid metabolism (HDL biogenesis and cholesterol homeostasis, fatty acids, phospholipids and triglycerides, bile acid metabolism), inflammatory response, insulin signaling and glucose/energy homeostasis. Indeed, miRNAs are small (18–25 nucleotides) non-coding RNAs that alter gene expression through posttranscriptional silencing (Bartel, 2004). The first miRNAs were discovered in the early 1990s; however, they were not recognized as a distinct class of post-transcriptional biological regulators until the early 2000s (Lee et al., 1993; Wightman et al., 1993; O'Connell et al., 2010). Currently, miRNAs are described as biomarkers, prognostic indicators, and regulators of normal and abnormal cellular and physiologic functions (Kolfschoten et al., 2009). Interestingly, each miRNA is thought to have several targets, and more than one miRNA can converge on a single mRNA, suggesting the enormous regulatory role for these molecules and pointing the complexity of miRNA regulation at cellular level (Krek et al., 2005; Grimson et al., 2007). In addition to the other findings, in the study group characterized by high HDL-C levels, ABCA1 and ABCG1 mRNA expression were significantly increased when compared with normolipidemic individuals. Furthermore, hsa-miR-33a expression was 72% lower in this group. Many algorithms predict the presence of miR-33a binding sites in the 3′ UTRs of genes involved in cholesterol transport, as ABCA1, suggesting a regulatory role in maintaining cellular cholesterol homeostasis. In fact, several studies highlight the regulatory role of miR-33 in ABCA1 expression (Fernandez-Hernando et al., 2011; Moore et al., 2010; Chen et al., 2013; Canfran-Duque et al., 2014), leading to efforts to demonstrate the potential of miR-33 as a therapeutic target. The silencing of miR-33 in mice, using modified antisense oligonucleotides or viral delivery of hairpin inhibitors, increased hepatic ABCA1 expression and HDL-C levels by 35%; additionally, the antagonism of miR-33 in vivo enhanced the RCT (Rayner et al., 2010; Najafi-Shoushtari et al., 2010; Marquart et al., 2010; Allen et al., 2012). The anti-miR-33 therapy also resulted in increased plasma HDL-C in non-human primates (Rayner et al., 2011; Rottiers et al., 2013). Interestingly, in mouse cells miR-33 was also shown to target ABCG1, a transporter that also mobilizes free cholesterol from the cell but uses larger HDL particles as its acceptor. Despite that, miR-33 repression of ABCG1 is not conserved in human cells due to the loss of miR-33 binding sites in 3′ UTR of ABCG1 (Rayner et al., 2010; Tall, 2008; Tall et al., 2008). We hypothesized that decreased hsa-miR-33a in individuals with high HDL-C levels, plus the higher mRNA of ABCA1 could indicate an increased cholesterol efflux and reverse cholesterol transport in these individuals as compared to controls. However, no significant differences were observed, despite the increase of HDL size (6.2%, p b 0.05), volume (22.7%, p b 0.05) and a tendency to higher cholesteryl ester content (33.6%, p = 0.07) on HDL particles. Indeed, the absence of significant differences in HDL composition justifies the lack of differences regarding cholesterol efflux. Therefore, other mechanisms are involved, for instance the increased ABCG1 expression which directly contributes to higher HDL size and plasma levels. The relationship of miR-33 in the initiation and progression of atherosclerosis is still limited and conflicting in animal models (Marquart et al., 2013; Rotllan et al., 2013). In this study, hsa-mir-33a was not

Please cite this article as: Scherrer, D.Z., et al., Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR33a dysregulation in peripheral blood mononuclear cells..., Gene (2015), http://dx.doi.org/10.1016/j.gene.2015.05.074

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D.Z. Scherrer et al. / Gene xxx (2015) xxx–xxx

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Please cite this article as: Scherrer, D.Z., et al., Asymptomatic individuals with high HDL-C levels overexpress ABCA1 and ABCG1 and present miR33a dysregulation in peripheral blood mononuclear cells..., Gene (2015), http://dx.doi.org/10.1016/j.gene.2015.05.074