subcutaneous adipose tissue FABP4 expression and coronary atherosclerosis in patients with metabolic syndrome

Journal Pre-proof Relationships between visceral/subcutaneous adipose tissue FABP4 expression and coronary atherosclerosis in patients with metabolic syndrome Selcuk Gormez, Refik Erdim, Gokce Akan, Barıs Caynak, Cihan Duran, Demet Gunay, Volkan Sozer, Fatmahan Atalar PII:

S1054-8807(19)30357-6

DOI:

https://doi.org/10.1016/j.carpath.2019.107192

Reference:

CVP 107192

To appear in:

Cardiovascular Pathology

Received Date: 6 August 2019 Revised Date:

17 October 2019

Accepted Date: 28 November 2019

Please cite this article as: Gormez S, Erdim R, Akan G, Caynak B, Duran C, Gunay D, Sozer V, Atalar F, Relationships between visceral/subcutaneous adipose tissue FABP4 expression and coronary atherosclerosis in patients with metabolic syndrome, Cardiovascular Pathology, https://doi.org/10.1016/ j.carpath.2019.107192. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc.

ORIGINAL ARTICLE Title: Relationships between visceral/subcutaneous adipose tissue FABP4 expression and coronary atherosclerosis in patients with metabolic syndrome Running title: Relationships between visceral/subcutaneous adipose tissue FABP4 expression and coronary atherosclerosis Selcuk Gormez1, Refik Erdim2, Gokce Akan3, Barıs Caynak4, Cihan Duran5, Demet Gunay6, Volkan Sozer7 and Fatmahan Atalar8 1

Department of Cardiology, Acibadem Mehmet Ali Aydinlar University, Faculty of Medicine,

Istanbul, Turkey 2

Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

3

MUHAS Genetics Laboratory, MUHAS, Muhimbili University of Health and Allied Sciences, Dar

Es Salaam, Tanzania 4

Department of Cardiovascular Surgery, Istanbul Bilim University, Istanbul, Turkey

5

Department of Radiology, Istanbul Bilim University, Istanbul, Turkey

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Sisli Florence Nightingale Hospital, Department of Biochemistry, Istanbul, Turkey

7

Department of Biochemistry, Yildiz Technical University, Istanbul, Turkey

8

Department of Medical Genetics, Child Health Institute, Istanbul University, Istanbul, Turkey

Correspondence: Assoc. Prof. Dr. Fatmahan ATALAR Department of Medical Genetics, Child Health Institute, Istanbul University, Istanbul, Turkey E-mail: [email protected]

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Highlights

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FABP4 EAT expression is associated with the extent of coronary atherosclerosis.

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EAT FABP4 expression and EATV are independent risk factors of MS CAD.

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rs1054135 increases mRNA expression of FABP4 EAT.

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rs1054135 is associated with the extent of atherosclerosis.

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rs778782271 is associated with decreased levels of FABP4 EAT expression.

Abstract Background: Cytoplasmic fatty acid-binding proteins facilitate the transport of lipids to specific compartments in cells. Fatty acid-binding protein 4 (FABP4), also known as aP2 or A-FABP, plays a key role in the development of atherosclerosis, insulin resistance, obesity, and metabolic syndrome (MS). The FABP4 polymorphisms are associated with protein expression changes in vitro and metabolic and vascular alterations in vivo. The aim of this study was to investigate the association between FABP4 messenger ribonucleic acid (mRNA) expression levels in epicardial (EAT), pericardial (PAT), and subcutaneous adipose tissues (SAT) and the extent of coronary atherosclerosis in coronary artery disease (CAD) patients with MS. Furthermore, the relationship between the extent of coronary atherosclerosis and epicardial adipose tissue volume (EATV) and FABP4 gene variations was evaluated. Patients and Methods: A total of 37 patients undergoing coronary artery bypass grafting due to CAD (MS CAD group) and 23 non-MS patients undergoing heart valve surgery (control group) were included. Coronary angiography was performed for all patients and the extent of coronary atherosclerosis was assessed using the Sullivan’s scoring system. The mRNA expression levels of FABP4 gene in EAT, PAT, and SAT and FABP4 polymorphisms were analyzed using the quantitative real-time polymerase chain reaction (qRT-PCR). Results: An increased FABP4 expression was observed in EAT and PAT of MS CAD group compared to controls. In the MS CAD group, FABP4 mRNA expression levels in EAT was 2.8-fold higher, compared to PAT. The expression of FABP4 in EAT was positively correlated with the extent of atherosclerosis and EATV in MS CAD group (r=0.588, p=0.001, r=0.174, p=0.001, respectively). There were no correlations between PAT and SAT versus the extent of atherosclerosis and EATV. The FABP4 EAT mRNA expression levels were found to significantly increase in mutant allele carriers of rs1054135, while they significantly decreased in mutant allele carriers of rs77878271(T-87C) in MS CAD group (p<0.05). The extent of atherosclerosis was also found to be significantly associated with rs1054135 (p<0.05). A cut-off point of 57.5 cm3 EATV was used indicating the presence of CAD with a significant area under the curve of 0.783%, 98% sensitivity, and 100% specificity (95% CI 0.620–0.880; p<0.05). Conclusions: Our study results suggest that FABP4 expression in EAT is strongly associated with the extent of atherosclerosis and EATV in MS CAD patients. Keywords: Coronary atherosclerosis, Fatty acid-binding protein 4, Epicardial adipose tissue, Epicardial adipose tissue volume, Metabolic syndrome, Single nucleotide polymorphism.

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List of Abbreviations: PAT, pericardial adipose tissue; EAT, epicardial adipose tissue; SAT, subcutaneous adipose tissue; VAT, visceral adipose tissue; EATV, epicardial adipose tissue volume; MS, metabolic syndrome; CAD, coronary artery disease; CABG, coronary artery bypass grafting; FABP4, fatty acid-binding protein 4; FFA, free fatty acid; TNF-α, tumor necrosis factor-α;, IL, interleukin; PAI-1, plasminogen activator inhibitor-1; ADIPOQ, adiponectin; BMI, body mass index; TC, total cholesterol; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TG, triglycerides; qRTPCR, quantitative real-time polymerase chain reaction; HWE, Hardy-Weinberg equilibrium; AUC, area under the curve; ROC, receiver operating characteristics; mRNA, messenger ribonucleic acid.

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1. Introduction Metabolic syndrome (MS) is defined as a clustering of at least three of the five following conditions: central obesity, high blood pressure, elevated fasting plasma glucose, and abnormal cholesterol and triglyceride (TG) levels and is a well-established risk factor for coronary artery disease (CAD). The landmark sign of MS is central obesity which is also known as visceral adiposity characterized by adipose tissue accumulation, particularly around the waist and trunk due to excess calorie intake. Energy surplus leads to adipose tissue expansion, adipocyte hypertrophy, hypoxia, and eventually death and macrophage infiltration, leading to adipose tissue inflammation which adversely affects adipose tissue functioning, namely adipocytokine dysregulation, thereby resulting in promotion of systemic insulin resistance, dyslipidemia, and inflammation [1]. Visceral adiposity is characterized by altered cellular composition, increased lipid storage and impaired insulin sensitivity in adipocytes, and a proinflammatory, atherogenic, and diabetogenic adipokine pattern [2]. In recent years, epicardial adipose tissue (EAT) as an important component of visceral adipose tissue (VAT) has gained an increasing attention due to its proximity to the coronary arteries, and its direct endocrine and paracrine effects result in the development of coronary atherosclerosis, while EAT volume (EATV) is associated with the severity of atherosclerosis [3,4]. Pro-inflammatory markers associated with the development of MS and CAD include an increased production of leptin, tumor necrosis factor-α (TNF-α), interleukin 1 (IL-1), interleukin 6 (IL-6), free fatty acids (FFA), and plasminogen activator inhibitor-1 (PAI-1), and a decreased secretion of adiponectin (ADIPOQ) [5,6]. Fatty acid-binding proteins (FABP) are a group of cytosolic lipid carriers which coordinate inflammatory and metabolic pathways in cells. Among these adipokine family, fatty acid binding protein-4 (FABP4), also known as adipocyte P2 or adipocyte FABP, is highly secreted by adipocytes and macrophages [7]. Elevated serum circulating FABP4 levels and FABP4 messenger ribonucleic acid (mRNA) expressions in various tissues show a strong pathophysiological association with obesity, insulin resistance, hypertension, inflammation, atherosclerosis, MS, and cardiac dysfunction [7-9]. Therefore, the FABP4 has been proposed as an independent predictor for metabolic and cardiovascular diseases [10]. Recent studies have demonstrated that FABP4 gene variations resulted in a decreased mRNA expression of FABP4 in certain tissues, speculating their protective effect. However, the number of these studies is scarce. In the present study, therefore, we aimed to investigate the association between FABP4 mRNA expression levels in EAT, pericardial adipose tissues (PAT), and subcutaneous adipose tissues (SAT) and the extent of coronary atherosclerosis in patients with MS 5

and to evaluate the impact of EATV and FABP4 polymorphisms on FABP4 expression in MS CAD patients. 2. Methods 2.1 Study population This single-center, prospective study included a total of 37 metabolic syndrome patients undergoing coronary artery bypass grafting (CABG) due to CAD (MS CAD group) and 23 patients without CAD undergoing heart valve surgery (control group). All patients were evaluated by a multidisciplinary team and met the eligibility criteria for the operation. All patients with CAD had an angiographic evidence of critical coronary atherosclerosis involving three vessels deemed necessary for an elective CABG surgery. Those with any history of human immunodeficiency virus (HIV) and/or viral hepatitis, malignancies, collagen diseases, endocrinopathies, secondary hypertension, or diabetic microangiopathic complications were excluded from the study. None of the female patients were on birth control pills or postmenopausal hormone replacement. No atherosclerotic lesions were seen on coronary angiographies in the control group. A detailed history was obtained, and physical examination was performed for each subject. Blood pressure, height, weight, hip and waist circumference were recorded. The body mass index (BMI) was calculated for each patient as weight in kilograms divided by the square of height in meters. Obesity was diagnosed according to the BMI using the National Institutes of Health criteria. The mean BMI of our study group, which comprised of MS CAD group and controls, was 30.2 kg/cm2. The cut-off points of waist circumference for cardiovascular disease risk were 87 cm for men and 83 cm for women, as defined by the criteria of Turkish Adults Heart Disease and Risk Factors (TEKHARF) study [11]. The diagnosis of hypertension was based on a resting systolic or diastolic blood pressure of >140 or >90 mmHg, respectively, or current use of antihypertensive therapy. Dyslipidemia was defined as a low-density lipoprotein (LDL) cholesterol of ≥130 mg/dL or the use of hypolipidemic agents. All patients had normal dietary regimes at least three days before taking blood samples. Plasma and tissue samples were obtained after 10 h (overnight) fasting. Fasting venous blood samples were separated as serum, plasma, and cellular portions and stored at -80ºC for biochemical analyses. The EAT, PAT, and SAT biopsy samples were collected during CABG and heart valve surgeries. Fat samples (300 mg) were obtained from three different locations during surgery for all patients: (1) SAT from thoracoscopic ports or sternal wall; (2) PAT from the parietal pericardium; (3) EAT harvested adjacent to the left-interventricular groove. The tissue samples were, then, immediately frozen in liquid nitrogen and stored at -80ºC prior to total RNA preparation. Oral antidiabetics, including metformin, and lipid-lowering drugs which may interfere with 6

adipocytokine gene expression were discontinued three days before blood and tissue sample collection. None of the patients were treated with thiazolidinediones. A written informed consent was obtained from each participant. The study protocol was approved by the local Ethics Committee of Istanbul Bilim University. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. 2.2 Biochemical measurements Serum total cholesterol (TC) and high-density lipoprotein (HDL) cholesterol, LDL cholesterol, TG, fasting glucose, fasting insulin, and morning plasma cortisol levels were measured by routine assays in the hospital laboratory. All analyses were performed using the Cobas 6000 instrument (Roche Diagnostics GmbH, Mannheim, Germany). Plasma levels of adiponectin (LINCO Research, USA), IL-18, IL-6, and TNF-α (BioSource International Inc., CA, USA) were measured through immunoassay using the commercial enzyme-linked immunosorbent assay (ELISA) kit. Insulin resistance was evaluated using the homeostatic model assessment of insulin resistance (HOMA-IR= fasting glucose [mmol/L]x fasting insulin[uU/mL]/22.5). A HOMA-IR value higher than 2.24 as suggested by the TEKHARF study was taken as the cut-off point for insulin resistance for the study group [12]. The body fat amount was assessed using the bioelectrical impedance technique (MC 180, TANITA Corp., Tokyo, Japan). Volumetric measurement of epicardial and subcutaneous fat were obtained by multislice computed tomography (LightSpeed VCT 64, GE Healthcare or Aquillon 16, Toshiba Medical Systems, Tokyo, Japan). 2.3 Angiographic scoring system (The Sullivan Score) Coronary angiograms were assessed and scored according to the system of Sullivan et al. [13] by an expert. Extension score refers to the proportion of the coronary artery tree showing an angiographically detectable atheroma. The observed proportion in each vessel is multiplied by a factor which varies according to the artery involved: left main stem, 5; left anterior descending coronary artery, 20; main diagonal branch, 10; first septal perforator, 5; left circumflex artery, 20; obtuse marginal and posterolateral vessels, 10; right coronary artery, 20; and main posterior descending branch, 10. When the major lateral wall branch was a large obtuse marginal or intermediate vessel, this was given a factor of 20, and the left circumflex artery, a factor of 10. When a vessel was occluded and the distal bed was not fully visualized by collateral flow, the proportion of vessel not visualized was given the mean extent score of the remaining vessels. The scores for each vessel or branch were added to give a total score of 100 and the total score represents the percentage of the coronary luminal surface area involved by the atheroma [13]. 2.4 Adipose tissue volumes by Computed Tomography 7

The adipose tissue volume was expressed in cm3 using computed tomography (Figure 1). The multidetector computed tomographic data were acquired by a 16-slice multidetector computed tomographic scanner (SOMATOM Sensation 16, Siemens Medical Solutions; Erlangen, Germany) with a 16×0.75-mm detector collimation, a Gantry rotation time of 420 msec, tube current of 550 mA-s, and tube voltage of 120 kV. The computed tomography scan of 60 participants was performed at three levels, at the right ventricular level of the heart to evaluate the epicardial fat volume, at the level of the umbilicus (L4-L5) to evaluate the subcutaneous and abdominal fat depots. We used the density of fat tissue (from −50 to −250 Hounsfield units) as upper and lower limits of density for this semi-automatic volume program, respectively. The EAT volume was defined as the total amount of adipose tissue between the myocardium and pericardium and was calculated multiplying the slice thickness and cross-sectional area by an experienced reader. 2.5 Total RNA extraction and quantitation The EAT, PAT, and SAT were disrupted with a homogenizer in the reaction tube. Total RNA from EAT, PAT, and SAT was extracted using the Allprep kit (Qiagen, GmbH, Germany). The RNA quantity was determined using the NanoDrop™ 1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). After DNase I treatment, 1 µg of RNA was reverse transcribed in 20 µL total volume using random hexamers and poly(dt) as primers and SuperScript II reverse transcriptase (Invitrogen; Thermo Scientific, Wilmington, DE, USA). Following complementary DNA (cDNA) synthesis, the quality of cDNA was assessed using the PCR amplification of the housekeeping gene beta-globin. The cDNA was stored at -80ºC until analysis. 2.6 Gene expression analysis of FABP-4 The mRNA expression levels of FABP4 were determined using the SYBR green-based qRT-PCR via a LightCycler® (Roche Diagnostics GmbH, Mannheim, Germany) instrument. Ten-fold dilutions of cDNA synthesized from total RNA were used. All samples were amplified in duplicate and the mean was obtained for further calculations. Primers were designed using the software Primer3 v.0.4.0 (http://frodo.wi.mit.edu/primer3/) and synthesized by TIB-MOLBIOL GmbH (Berlin, Germany).

2.7 Deoxyribonucleic acid (DNA) Extraction and Genotyping From both groups, approximately 5 mL of blood samples were collected in Falcon™ tubes containing 0.5 mg of ethylenediaminetetraacetic acid per mL as anticoagulant. Genomic DNA was obtained from 400 µL peripheral blood leukocytes with MagNA Pure DNA Isolation device (Roche Diagnostics GmbH, Mannheim, Germany). The DNA quantities were determined using the 8

NanoDrop™ 1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). The extracted DNA was stored at -20ºC until molecular analysis. We selected and genotyped a total of 4 single nucleotide polymorphisms spanning 41.3kb across FABP4 in all subjects. We surveyed common genetic variation using the National Center for Biotechnology Information database SNP supplemented by HapMap database. We aimed to choose SNPs with high SNP density covering the FABP4 gene as well as its 30-kbp 5′-upstream and 30kbp 3′-downstream regions. Our selection was based on the functionality priority; nonsynonymous coding SNPs (cSNPs) and splicing-site SNPs (ssSNPs) were kept in the following order: cSNPs > ssSNPs > 5′-upstream SNPs > 3′-downstream SNPs > intronic SNPs. Genotyping of the rs1054135, rs77878271, rs2303519, and rs16909233 SNPs was performed using the quantitative real-time polymerase chain reaction (qRT-PCR). Genotyping was carried out using the LightSNiP typing assay (TIBMolBiol, Berlin, Germany) with the LightCycler® 480 system instrument (Roche Diagnostics GmbH, Mannheim, Germany).

2.8 Statistical analysis Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 25.0 software (IBM Corp., Armonk, NY, USA). The allelic frequency distributions of polymorphisms between the control and patient groups were compared using the chi-square (χ2) test. The Hardy-Weinberg equilibrium (HWE) was assessed by the Fisher’s exact test. For the comparison of differences between the mean values between two groups, unpaired Student t-test was used. To evaluate differences between the groups, the data were log transformed to satisfy analysis of variance (ANOVA) criteria and, then, subjected to one-way ANOVA with the Tukey’s post-hoc analysis. A p value of <0.05 was considered statistically significant. Gene expression data were obtained as Ct values (Ct=the cycle number at which logarithmic PCR plots cross a calculated threshold line). The Ct values were used to calculate ∆CT values (∆CT=Ct of the target gene minus Ct of the housekeeping gene). The expression of each gene was compared between depots using the ∆∆Ct method. All statistical analyses were performed at the ∆Ct stage to exclude potential bias due to averaging of data transformed through the equation 2-∆∆Ct. Target gene expression was calculated using the expression of a housekeeping gene (cyclophilin) as an internal standard. The presence of specific gene products was also confirmed with the melting curve analysis. Data were expressed in mean ± standard deviation (SD) for continuous variables and in number and frequency for discrete variables. Baseline differences between the MS CAD group

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and control group were examined by the Kruskal-Wallis and Mann-Whitney U test. Variables were compared using the Spearman’s correlation analysis to eliminate the effect of outliers. To obtain the cut-off point of EAT volume for predicting MS CAD in this population, the receptor operating curve (ROC) curve was constructed, for which subjects were categorized into groups with and without MS CAD. An area under the curve (AUC) of 1 was considered to have little validity, and the power of the test for this sample size was calculated. The Youden index was to determine the optimum cut-off point from the ROC curve, calculated with the formula YI(sensitivity+specifity) -1. The risk (odds ratio) of having MS CAD was determined using the epicardial fat value obtained. The MedCalc statistical software package (MedCalc Software, Mariakerke, Belgium) was used for statistical analyses. A p value of <0.05 was considered statistically significant. 3. Results 3.1 Patients’ data The anthropometric, clinical, and metabolic characteristics of MS CAD and control group are shown in Table 1. Accordingly, there were no significant differences in age, SBP, DBP, insulin, HDL, cholesterol, triglycerides, Hs-CRP, body adiposity and SAT volume while there were statistically significant differences in BMI, waist circumference, HOMA-IR, glucose, LDL, EATV and proinflammatory markers between the MS CAD group and controls. There was also a significant difference in the presence of MS risk factors, including family history of MS, between the groups (p<0.05). 3.2 FABP4 expression in EAT, PAT, and SAT The EAT, PAT, and SAT depots were assessed for the expression of FABP4 using the qRTPCR in the study group (Figure 2). We found that the FABP4 mRNA levels of MS CAD group were significantly higher in the EAT and PAT, compared to SAT (p<0.05). In addition, the expression levels of FABP4 were further evaluated in both sexes. The male patients with MS CAD had significantly higher expression levels of FABP4 in EAT, PAT, and SAT compared to female MS CAD patients (p<0.05 for both). Also, the FABP4 gene expression in EAT and PAT of female controls was no significantly different than males (data not shown). 3.3 Correlations between gene expression levels and anthropometric parameters and fat volumes A positive correlation was found between the EAT FABP4 mRNA levels and BMI (r=0.309; p=0.016) and glucose (r=0444; p=0.001). Interestingly, we determined positive

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correlations between the FABP4 mRNA levels in EAT and EATV (r=0418; p=0.002) and Sullivan score (r=0.588; p=0.001). We also analyzed the correlation of inflammatory markers and FABP4 mRNA expression levels in EAT, PAT, and SAT depots with the study variables for MS CAD group. Accordingly, the FABP4 EAT mRNA levels were positively correlated with C-reactive protein (CRP), IL-18, IL-6, and TNF-α, while it was found to be negatively correlated with the ADIPOQ (r=0.422; p=0.02, r=0.559; p=0.001, r=0.367; p=0.024, r=0.602; p=0.001, r=-0.521; p=0.001, respectively). 3.4 EATV measurements There was a statistically significant difference in the EATV between the groups with a mean volume of 79 ± 14.5 cm3 (range, 40 cm3 to 96 cm3) for the patient group and a mean volume of 42.2 ± 22.2 cm3 (range, 22 cm3 to 68 cm3) for the control group (p<0.001). Using the ROC curve analysis, we found that the cut-off point of 57.5 cm3 obtained the highest Youden index ((Youden Index J=0.773, with 87.3% sensitivity (95% CI: 78.5-93.9) and 79.6% specificity (95% CI: 65.282.6)), indicating the presence of CAD with a significant AUC of 0.783, 98% sensitivity, and 100% specificity (95% CI 0.620–0.880; p<0.05) (Figure 3). In addition, the merged output probabilities of each fold for leave-one-out cross-validation was used to build ROC curves of the model built for the clinical importance of the risk factors collected in this study. The FABP4 mRNA expression levels and SNPs were also added in the built model. The model included BMI, EATV, and FABP4 mRNA expression levels in EAT and rs1054135. We observed that our model was significantly predictive of MS CAD (Table 2). Furthermore, we used binary logistic regression model to test the independent correlates of the CAD presence. In this model, we included age, BMI, EATV, EAT expression of FABP4, and FABP4 rs1054135 polymorphism. Age (p<0.001), EATV (p<0.001), EAT expression of FABP4 and FABP4 rs1054135 (p<0.05, respectively) were independent correlates of the presence of CAD. Whereas, BMI was not CAD independent risk factors (Table 3). 3.5 Single nucleotide polymorphisms (SNP) The χ2 goodness-of-fit test showed that the four SNPs genotyped were within the distribution expected according to HWE in both the patient and control groups. The genotype and allele frequencies of the individual SNPs and the results of the correlation analyses between the patients and controls are summarized in Table 4. The minor allele frequencies were more than 5%. Neither the genotype nor the allele frequencies of rs77878271, rs2303519, and rs16909233 showed a significant difference between the patients and controls. However, both the genotype and allele frequencies of rs1054135 were significantly different between the groups (p<0.05 for both). The GG genotype was found to be less frequent and the GA and AA genotypes more frequent, whereas 11

the frequency of the G allele was lower and the frequency of the A allele was higher in patients than controls (p<0.05 for both). As shown in Table 5, in MS CAD patients, glucose, abdominal fat, subcutaneous fat, Sullivan scores, and FABP4 mRNA expression levels in EAT were statistically different between the rs1054135 genotypes (p<0.05).

Furthermore, we found a statistically

significant difference in the GA and AA genotypes showing increased levels of FABP4 expression in EAT, compared to GG (wild type) genotypes (p<0.05). On the other hand, the analysis of rs77878271 revealed no significant difference in genotype and allele frequencies between the patients and controls. Although there was a significant difference in the FABP4 EAT expression and Sullivan score between genotypes, FABP4 EAT expression of the patients with TT and TC genotypes was almost two-fold higher, compared to the patients with CC genotype (p<0.05), and the Sullivan score of the patients with CC genotype showed a significant decrease, compared to the other genotypes (p<0.05), indicating the possible protective role of C allele against the formation of epicardial fat and the extent of coronary atherosclerosis in MS patients.

4. Discussion Both visceral obesity and ectopic fat accumulation in non-adipose tissues, including the heart, have been associated with cardiac structure abnormalities and an increased cardiometabolic risk [14]. In recent studies, cardiac fat has been recognized as a new cardiometabolic risk marker, as its association has been shown with an increased insulin resistance, cardiovascular risk factors, VAT and, in general, with the MS [15]. The localized VAT, compared to systemic fat, plays a major role in progression and diseases of cardiovascular lesions. The EAT refers to the fat tissues depositing outside the pericardial sac and covers more than 80% of the heart, accounting for 1% of the systemic fat, while EATV accounts for 15 to 20% of the heart volume and, anatomically and functionally, the adipose tissues are closely related to the myocardium and supplied by the coronary artery [16]. Previous studies have demonstrated that EATV increases with an increased number of affected coronary arteries and, along with EAT, it is one of the independent risk factors for the development of coronary heart disease [17-20]. Large-scale studies have also reported that an increased EATV promotes early development of atherosclerosis and is positively associated with the coronary artery calcium score and an adverse CAD prognosis [21,22]. The mechanism underlying these associations may be linked to a dysregulated secretory profile of EAT, with substantial accumulation of inflammatory cytokines, and by mediators secreted by infiltrating macrophages

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[23-25]. The accumulated inflammatory cytokines can easily induce and exacerbate the interstitial fibrosis in adipose tissue, which is one of the most important driving factors and a hallmark of the metabolic dysfunction of adipose tissue [26]. Recent studies have also shown that those cytokines secreted by the adipose tissues may act on nearby coronary artery and myocardium via paracrine or supporting vessels, which may be involved in the occurrence and development of cardiovascular disease [27]. As a new emerging adipokine, the FABP4 is involved in the development of metabolic disease and CAD. Apart from adipocytes, FABP4 is also highly expressed in macrophages and dendritic cells, further contributing to inflammation-related alterations, such as MS and cardiovascular disease [28, 29]. At the crossroads of MS and cardiovascular diseases, the crucial role of human FABP4 has been demonstrated in genetic models in the in vitro setting [30-32]. However, the data on FABP4 in human MS and atherosclerosis are still scarce. In our study, expression analyses revealed the presence of FABP4 mRNA expression in EAT, PAT, and SAT. According to the analysis of FABP4 mRNA expression in three different adipose tissues in and around the heart, we found depot-specific differences in the expression of FABP4 in MS CAD patients. The FABP4 mRNA expression in VAT was higher, compared to SAT, in MS CAD patients and, among VAT, the FABP4 gene expression was found to be 2.8-fold higher in EAT, compared to PAT. These expression differences can be attributed to the different embryonic origins, pattern of adipokine production and regional/anatomical features of EAT, PAT, and SAT. Our study showed two statistically significant correlations between the EAT expression of FABP4 and the extent of coronary atherosclerosis and between the EAT expression of FABP4 and EATV in MS CAD patients (p<0.05). Consistent with previous studies, these findings suggest an existing relationship between the EAT, EATV, and FABP-4 and coronary atherosclerosis. Furthermore, we evaluated the impact of FABP4 genetic variants on FABP4 mRNA expression levels in EAT, PAT, and SAT in our study group and, then, evaluated their association with MS CAD. Our results suggested that rs1054135 was significantly associated with the extent of atherosclerosis (~2 fold) and higher FABP4 mRNA expression levels (~1.91 fold) in EAT and metabolic conditions (p<0.05, respectively). Although no significant difference was found between the groups, genetic variability at the FABP4 as evidenced by rs77878271 (T-87C), decreased dramatically EAT FABP4 mRNA expression levels in homozygous mutant genotype and Sullivan score (2.09-fold and 1.84-fold, respectively) (p<0.05, respectively) confirmed its protective role, as previously described [33].

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Our results are also in consistent with two population studies showing rs77878271 CC homozygotes having lower levels of serum TC, apoB, reduced expression of FABP4, and apoptosis within the carotid atheroma and also a lower risk for developing large artery atherosclerosis in metabolically strained obese individuals [34,35]. Interestingly, the reduction in serum TC and apoB levels were determined to be prominent in the highest BMI quartile among CC genotypes; therefore, based on previous mouse models, one may suggest that the body weight and the lipidlowering effect may be mechanistically linked also in human [31,34,36]. This inference may possibly explain the underlying pathophysiology of metabolically healthy individuals with obesity. In the present study, the rs2303519 and rs16909233 allelic variants were not differentially present in MS CAD patients and controls, and did not show any significant association with the FABP4 mRNA expression levels in EAT, PAT, and SAT. Taken together, these initial findings in MS CAD patients and controls group suggest that the FABP4 mRNA expression levels in EAT and FABP4 genomic variants may be important determinants for cardiometabolic risk, particularly among MS CAD patients. In addition, our ROC analysis revealed FABP4 with BMI, EATV, and rs1054135 as independent risk factors of MS CAD. It has been well-established that the development from early lesions to vulnerable plaque formation is driven by numerous cellular and molecular inflammatory components. In evolving lesions, there is an accumulation of dendritic cells, T-lymphocytes, and monocyte-derived macrophages which are known to produce a wide array of soluble inflammatory mediators (i.e., cytokines, chemokines) which are involved in the initiation and perpetuation of CAD [29]. Therefore, we examined possible associations between MS CAD and CRP, IL-6, IL-18, TNF-α, and adiponectin that have recently been suggested to affect the development and progression of atherosclerosis. Based on several population-based studies [37,38], we found a strong and positive correlation between FABP4 mRNA expression in EAT and CRP, IL-18, IL-6, and TNF-α and a negative correlation with the ADIPOQ. This finding suggests a potential role of FABP4 by inflammatory proteins in the generation of the atherosclerotic lesions. In conclusion, to the best of our knowledge, this is the first study showing the association between the EAT FABP4 mRNA expression levels and the extent of coronary atherosclerosis in MS patients with CAD. In addition, the volume of EAT and FABP4 mRNA expression in EAT were found to be strongly associated. Nonetheless, further large-scale studies are needed to investigate the adipokines secreted from EAT and their interrelation to elucidate the underlying pathophysiology of coronary atherosclerosis. Nevertheless, we believe that our study results provide an insight into the biology of EAT and its potential implication.

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Acknowledgements We would like to thank to the late Prof. Ahmet Sevim Buyukdevrim for his valuable support and advice to the manuscript. Funding This study was financially supported by the Turkish Diabetes Foundation. Conflict of Interests The authors declare no conflict of interests. Authors’ Contributions S.G. and F.A. conceived the experiment. All authors contributed to the final design of the study. B.C. did cardiac surgeries. S.G. consulted the patients. F.A. and G.A. performed the molecular analysis. C.D. performed and analyzed computed tomography scans of the study group. D.G. performed the biochemical analysis. F.A. drafted the manuscript. All authors contributed to the final version of the manuscript.

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Tables and Figures

Figure 1: Epicardial adipose tissue quantification by computed tomography in control and MS CAD patients. On an axial view, the pericardial sac is easily identified as a thin band enveloping the heart. EAT is the adipose tissue between the pericardium and the myocardium. A: EAT quantification of a control patient. B: EAT quantification of a MS CAD patient.

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Figure 2: The mRNA expression levels of FABP4 in EAT, PAT, and SAT of MS CAD patients and controls. Data are given in mean ± standard deviation (SD). MS: Metabolic Syndrome, CAD: Coronary Artery Disease, EAT: Epicardial Adipose Tissue, PAT: Pericardial Adipose Tissue, SAT: Subcutaneous Adipose Tissue, AU: Arbitrary Unit. mRNA levels of FABP4 between the groups were compared using the one-way ANOVA test. A p value <0.05 statistically significant.

Figure 3: ROC curve analysis for of Epicardial Adipose Tissue Volume (EATV) association with MS CAD. The figure gives a significant area under the curve (AUC) of 0.783%, 98% sensitivity, 100% specificity (95%CI, 0.620-0880; p<0.05) ROC: Receiver Operating Characteristics.

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Table 1: Anthropometric, clinical and metabolic parameters of the study group

MS (n=37)

Controls (n=23)

P value

Age (years)

60.6± 8.99

55.1± 6.98

0.254

BMI (kg/m2)

35.38± 3.91

28± 5.35

0.014

Waist circumference (cm)

106.4± 9.65

89.4± 14.1

0.0003

SBP (mmHg)

135.9± 18.4

129± 31.4

0.227

DBP (mmHg)

75.8± 8.4

77.3± 7.8

0.515

HOMA-IR (µ µU/ml x G)

3.8 ± 2.36

1.36± 0.93

0.0001

Glucose (mg/dL)

157.36 ± 51.5

106.91± 11.54

0.0001

Insulin (µ µLU/mL)

9.88 ± 4.67

7.76± 5.85

0.129

LDL (mg/dL)

130.23± 39.7

109.49± 36.1

0.044

HDL (mg/dL)

41.68 ± 9.5

44.91± 10.4

0.242

Total Cholesterol (mg/dL)

199.05± 49.24

178.05± 38.1

0.072

Triglycerides (mg/dL)

160.25 ± 72.4

139.1± 66.07

0.267

Adiponectin (mg/L)

5.29± 1.56

7.13± 1.03

0.0009

IL-18 (ng/mL)

287.03± 64.87

232.52± 77.61

0.005

IL-6 (ng/mL)

5.2 ± 2.97

3.9± 3.4

0.016

TNF-α (ng/mL)

2.1 ± 1.47

1.46± 0.62

0.032

Hs-CRP (ng/mL)

1.48± 3.66

1.81± 3.89

0.241

Body adiposity (kg)

30.11 ± 8.46

25± 10.6

0.151

Epicardial Adipose Tissue Volume (cm3)

88.8± 5.1

25.5± 2.5

0.001

Subcutaneous Adipose Tissue Volume (cm3)

138.4± 44.46

130± 38.4

0.119

Values are given in mean ± SD. SD: Standard deviation, BMI: Body mass index, SBP: Systolic blood pressure, DBP: Diastolic blood pressure, HDL: High density lipoprotein, LDL: Low density lipoprotein, HOMA-IR: Homeostasis Model of Assessment - Insulin Resistance. Groups were compared using the Mann-Whitney U test for the variables. Remained significant after adjusting by age.

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Table 2: AUC of the model

Test Result Variables

95% CI

Epicardial Adipose Tissue Volume (EATV)

0.622-0880

BMI

0.507-0.820

EAT FABP4 mRNA

0.888-0.998

rs1054135

0.593-0.869

AUC model composed of EATV, BMI, EAT FABP4 mRNA and rs1054135 was significantly predictive of MS CAD. AUC: Area Under the Curve. A p value <0.05 statistically significant.

Table 3: Binary logistic regression analysis to identify the independent determinants of CAD Variables Age,year BMI (kg/m2) EATV EAT expression of FABP4 rs1054135 (G/A) GA+AA

Beta-coefficient 0.119 0.662 1.301 0.802

SE 0.19 0.359 0.363 0.372

P <0.001 0.055 <0.001 0.031

OR (95% CI) 1.11(1.07-1.15) 1.010(0.963-1.076) 1.200(1.080-1.320) 2.231(1.076-4.626)

-1.580

0.715

0.025

0.77(0.05-0.89)

BMI, body mass index; EATV, epicardial adipose tissue volume; CAD, coronary artery disease; CI, confidence interval; GA - heterozygotes; OR - odds ratio; SE - standard error; AA - homozygotes for the A allele

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Table 4: Association of SNPs between MS CAD patients and controls

NP

Genotype Frequencies n (%)

X2

OR/CI (95%)

*P-Value

Genotype MS(n=37) Controls(n=23)

1054135

77878271

2303519

16909233

GG

12(32.4)

16(69.6)

GA

18(48.6)

6(26.1)

AA

7(18.9)

1(4.3)

TT

32(89)

19(82.6)

TC

3(8.1)

3(13)

CC

2(2.7)

1(4.4)

CC

24(64.9)

19(82.6)

CT

12(32.4)

3(13)

TT

1(2.7)

1(4.4)

GG

29(78.4)

15(65.2)

AG

6(16.2)

6(26.1)

AA

2(5.4)

2(8.7)

Allele Frequencies Allele

7.86

4.76/1.54-14.64

MS(n=37)

X2

OR/CI (95%)

* P-Value

Controls(n=23)

0.005

G/A

0.57/0.43

0.83/0.17

8.53

T/C

0.93/0.07

0.96/0.04

0.06

3.61/1.48-8.81

0.86/0.25-2.87

0.003

0.17

0.74/0.17-3.11

>0.05

>0.05

2.20

2.57/0.72-9.18

>0.05

C/T

0.81/0.19

0.89/0.11

1.38

1.91/0.64-5.72

>0.05

1.26

0.51/0.16-1.65

>0.05

G/A

0.86/0.14

0.78/0.22

1.38

0.56/0.21-1.47

>0.05

MS: Metabolic Syndrome, CAD: Coronary Artery Disese, OR: Odds Ratio, CI: Confidence Interval, x2: Chi square. *The genotype and allelic frequency distribution of polymorphisms between the groups was compared using the chisquare and HWE tests. A p value <0.05 statistically significant.

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Table 5: Association of SNPs with clinical and metabolic parameters, scores, and FABP4 expression of the study group rs1054135

rs77878271 (T-87C)

GG

GA

AA

P value

TT

TC

CC

BMI (kg/m2)

29.6±4.0

31.6±3.4

32.5±4.7

0.134

35.7±2.7

35.4±2.1

30.9±3.8

Total Cholesterol (mg/dL)

164.5±29.5

180.5±43.6

182±30.3

0.457

177.7±39.1

190.33±36.1

153±22.1

Triglycerides (mg/dL)

134.3±63.5

174.5±64.8

198.5±100.3

0.068

166.1±74.5

121.6±24.3

110.6±28.1

Glucose (mg/dL)

129±34.4

139.6±47.5

165.5±49.8

0.02

170.6±31.1

156.8±53.8

133.1±13.4

LDL (mg/dL)

89.9±27.5

114.5±39.9

116.8±38.78

0.284

118.0±29.5

109.5±37.0

83±36.9

HDL (mg/dL)

43.3±9.3

42±9.5

39±10.7

0.485

40.4±9.1

45±5.9

53.6±7.3

Insulin (µLU/mL)

7.9±4.0

10.1±5.4

12.8±5.2

0.091

18.5±6.4

13.6±8.0

9.2±4.0

Cortisol (mg/L)

10.8±6.9

11.6±5.7

13.6±7.5

0.438

11.5±6.8

11.8±3.8

10.4±5.8

Omental Adipose Tissue Volume (cm3)

96.3±45.4

107.3±37.9

122.7±43.7

0.403

169±21.1

103.7±17.8

103.2±43.3

Abdominal Adipose Tissue Volume (cm3)

211.5±50.2

246.8±63.8

296.2±94.4

0.036

353.5±3.5

315.7±30.5

237.5±68.4

Subcutaneous Adipose Tissue Volume (cm3)

104.1±24.2

153.9±57.3

175.7±73.6

0.024

256.3±30.1

168.7±10.7

135.7±53.6

Epicardial Adipose Tissue Volume (cm3)

66.4±28 .1

82.7±26.7

83.9±31.8

0.695

78.85±24.1

76.56±26.2

67±29.3

Adiponectin (mg/L)

5.3±1.8

5.2±1.4

5.3±1.6

0.982

5.1±1.5

6.1±0.3

7.2±1.4

EAT FABP4 mRNA

37.09±22.5

49.35±16.7

71.8±17.5

0.001

73.7±15.7

74.9±13.8

35.1±16.4

PAT FABP4 mRNA

53.1±21.2

38.8±17.9

53.1±16.6

0.085

46.2±19.4

46.0±30.3

44.9±15.7

SAT FABP4 mRNA

41.1±25.4

34.7±22.5

32.4±22.2

0.358

38.1±23.5

16.4±10.3

39.7±5.1

Sullivan Score

33.1±5.04

50.6±17.6

75.8±16.6

0.001

55.2±19.1

47.7±20.3

30±6.9

Values are given in mean ± SD. SD: Standard deviation, BMI: Body mass index. Groups were compared with MannWhitney U test for the variables. A p value <0.05 statistically significant.

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Title: Relationships between visceral/subcutaneous adipose tissue FABP4 expression and coronary atherosclerosis in patients with metabolic syndrome Selcuk Gormez1, Refik Erdim2, Gokce Akan3, Barıs Caynak4, Cihan Duran5, Demet Gunay6, Volkan Sozer7 and Fatmahan Atalar8

Highlights

•

FABP4 EAT expression is associated with the extent of coronary atherosclerosis.

•

EAT FABP4 expression and EATV are independent risk factors of MS CAD.

•

rs1054135 increases mRNA expression of FABP4 EAT.

•

rs1054135 is associated with the extent of atherosclerosis.

•

rs778782271 is associated with decreased levels of FABP4 EAT expression.