a-fabp and its association with atherogenic risk profile and insulin resistance in young overweight...

723ISSN 1752-036310.2217/BMM.13.61 © 2013 Future Medicine Ltd Biomarkers Med. (2013) 7(5), 723–730

Research Article Research Article

A-FABP and its association with atherogenic risk profile and insulin resistance in young overweight and obese women

Aim: We evaluated the association of A-FABP with proatherogenic risk profile and insulin resistance (IR) in young, nondiabetic, overweight/obese women. Materials & methods: Serum A-FABP, high-sensitivity CRP, adiponectin, glucose, insulin, lipids and apolipoproteins were measured in 104 women (aged 20–45 years; BMI ≥25 kg/m2) and age-matched healthy controls (n = 76; BMI <25 kg/m2). All patients underwent blood pressure and anthropometric measurements. Results: A-FABP concentration was related to IR, and anthropometric and atherogenic indices. A-FABP was an independent predictor of triglyceride:high-density lipoprotein cholesterol, explaining 42% of its variation in overweight/obese women. At a cutoff level of 16 ng/ml, A-FABP discriminated between controls and overweight/obese (area under curve = 0.96) with high sensitivity and specificity. A-FABP predicted atherogenic risk, with an odds ratio of 11.2 (95% CI: 3.7–34.2), 7.1 (1.9–27.2) and 6.7 (2.6–17.2) for having elevated triglyceride:high-density lipoprotein cholesterol, apoB and CRP, respectively, and IR with an odds ratio 5.6 (1.8–17.2). Conclusion: A-FABP seems to be a valuable predictor of atherogenic risk profile; if elevated it contributes to cardiovascular disease beyond its effect on IR.

KEYWORDS: adipocyte n adiponectin n cardiovascular risk n fatty acid-binding protein n inflammatory factors n overweight/obesity

Obesity, characterized by excess accumulation of adipose tissue, is the most common risk fac-tor for metabolic syndrome (MS), a cluster of abnormalities that includes dyslipidemia, insulin resistance (IR), Type 2 diabetes and hyperten-sion. Adipose tissue plays a central role in the management of systemic energy stores, as well as in many other processes [1]. Obese subjects are more likely to develop glucose intolerance and diabetes, in part owing to the ability of adipose tissue to secrete adipokines, chemokines and free fatty acids into the bloodstream, having a major impact on energy homeostasis and progression from obesity to atherosclerotic diseases, in par-ticular leading to induction of IR and athero-sclerosis [1–3]. Recently, an important molecular pathway that integrates metabolic and inflam-matory responses was suggested that involves the fatty acid-binding proteins (FABPs), which are present in adipocytes and macrophages [3,4]. FABPs belong to a family of cytosolic chaperones that are involved in systemic regulation of lipid and glucose metabolism. A-FABP, also known as aP2 or FABP4, is expressed predominantly in adipose tissue and macrophages. Earlier animal studies showed that mice with A-FABP deficiency are protected from the development of hyperin-sulinemia, hyperglycemia, IR, dyslipidemia and fatty liver disease, in the context of both genetic and dietary obesity [3,5,6]. Some findings suggest

that A-FABP may also play a role in the devel-opment of atherosclerotic diseases in humans and that lifestyle changes lower A-FABP plasma concentration in patients with cardiovascular risk [6]. A-FABP has been proposed as a clinical biomarker for atherogenic dyslipidemia, indepen-dent of obesity and IR, in Type 2 diabetics and nonobese patients with familial combined hyper-lipidemia [7,8], and associated with inflammatory factors related to obesity and MS in nondiabetic morbidly obese women [9].

We aimed to assess the relationship of A-FABP with atherogenic dyslipidemia, adipose tissue-derived inflammatory factors and IR, as well as the accuracy of A-FABP for predicting athero-genic risk profile in young nondiabetic women with overweight/obesity.

Materials & methods�n Study design & conduction

The study group consisted of 104 young pre-menopausal women aged 20–45 years with over-weight/obesity, recruited from the Outpatient Clinic of the City Hospital (Poland). The rea-son they attend the clinic was to decrease weight. None of them were on a weight loss diet at the time of blood collection.

The study group was divided into two sub-groups according to BMI: overweight (n = 48; BMI = 25–29.9 kg/m2) and obese women

Aneta Mankowska-Cyl*1, Magdalena Krintus1, Pawel Rajewski2 & Grazyna Sypniewska1

1Department of Laboratory Medicine, Nicolaus Copernicus University in Torun Ludwik Rydygier Collegium Medicum in Bydgoszcz, Poland 2Department of Internal Diseases, E. Warminski City Hospital, Bydgoszcz, Poland *Author for correspondence: Tel.: +48 52 585 40 46 Fax: +48 52 585 36 03 [email protected]

part of

A-FABP, atherogenic risk profile & insulin resistance in overweight & obese women Research ArticleResearch Article Mankowska-Cyl, Krintus, Rajewski & Sypniewska

Biomarkers Med. (2013) 7(5)724 future science group

(n = 56; BMI ≥30 kg/m2). The control group (BMI <25 kg/m2) included 76 age-matched women (20–45 years) recruited on a volun-tary basis. Both control and study groups were characterized by normoglycemia (<5.6 mmol/l; fasting glucose was measured twice within a week). We accepted the following cutoff values for normal lipids, apoB, atherogenic indices and high-sensitivity CRP (hsCRP): total cholesterol (TC) <5.17 mmol/l; high-density lipoprotein (HDL) cholesterol (HDL-C) ≥1.29 mmol/l; low-density lipoprotein (LDL)-C <3.36 mmol/l; triglyceride (TG) <1.69 mmol/l; TC:HDL-C <4 [10]; apoB <0.9 g/l [11]; TG:HDL-C <1.3 [12]; and hsCRP <1 mg/l [13]. The study group was characterized by mild dyslipidemia: TC ≥5.17 mmol/l (found in 25% of subjects), HDL-C <1.29 mmol/l (found in 73% of sub-jects) and TG ≥1.69 mmol/l (found in 10% of subjects) were found in 25, 73 and 10% of sub-jects, with maximal concentrations of TC and TG of 6.3 and 1.98 mmol/l, respectively, and a minimal value of HDL-C of 0.95 mmol/l. In each subject, bodyweight, height and waist cir-cumference were measured, and BMI was calcu-lated (kg/m2); blood pressure was also examined in a standard manner. Women included in the study had not taken any contraceptives, anti- inflammatories or other medicines known to affect lipid or carbohydrate metabolism. Other exclusion criteria were diagnosis of polycystic ovary syndrome, thyroid disorders or Cushing’s syndrome. The written informed consent from each participant was obtained and the study was approved by the Bioethics Committee at Nico-laus Copernicus University in Torun Collegium Medicum in Bydgoszcz (Poland).

�n Blood sampling & laboratory analysesFasting blood was drawn in the early morning (7.00–9.00 am) on the third day of the menstrual cycle. Serum was obtained within less than 1 h to avoid proteolysis, and stored deep-frozen (-80°C) in small aliquots until assayed for no longer than 8 months.

Serum was assayed for HDL-C, TGs, TC, apoA-I and apoB, glucose and insulin (ARCHI-TECT ci8200, Abbott Diagnostics, IL, USA). LDL-C, TG:HDL-C (the index of LDL par-ticle size and surrogate for IR), TC:HDL-C, apoB:apoA-I and Homeostasis Model of Assess-ment–Insulin Resistance (HOMA–IR) val-ues were calculated. Cutoff values for elevated apoB:apoA-I ≥0.6 [14] and HOMA–IR ≥2.75 were accepted. hsCRP concentration was

measured using the BN II System nephelometer (N High Sensitivity CRP; Siemens Healthcare Diagnostics, IL, USA), which provides excel-lent precision with the coefficient of variation reported by the manufacturer of less than 10%. Coefficients of variation for hsCRP estimated in our laboratory were <3.5 and <4.5% for hsCRP concentrations <1 mg/l and >3 mg/l, respectively. Human A-FABP was determined by a sandwich ELISA method for the quantitative measurement of human A-FABP (BioVendor Laboratory Medi-cine Inc., NC, USA). Coefficients of variation for A-FABP were below 2.6 and <5.1% for A-FABP concentrations <12.5 and >31.1 mg/l, respec-tively. Total adiponectin was assayed by a sand-wich ELISA (DRG MedTek, R&D, Germany) providing excellent precision with the coefficient of variation reported by the manufacturer of less than 7%.

The height (cm), weight (kg), and waist and hip circumferences (cm) were measured using standard methods. Waist circumference was measured in a horizontal plane midway between the distance of the superior iliac crest and the lower margin of the last rib. Hip circumference was taken around the pelvis at the point of maxi-mal protrusion of the buttocks. The systolic and diastolic blood pressures were measured twice according to the standard procedures, in the sit-ting position after at least 5 min rest, by trained personnel with the use of an automatic blood pressure monitor M6 Comfort (HEM-7223-E, OMRON, Poland). Three consecutive readings were performed, and the average was recorded. The cutoff value of systolic blood pressure was <130 mmHg and <85 mmHg for diastolic blood pressure [15,16].

�n Statistical methodsAll data were presented as mean ± standard deviation (Gaussian distribution of results) or median and the 25th and 75th percentile (non-Gaussian distribution). The Student’s t-test and Mann–Whitney U-test were used to compare dif-ferences. Comparison of mean values between the groups was performed by the analysis of vari-ance or Kruskal–Wallis tests. Pearson’s or Spear-man’s correlation tests were used and multiple regression ana lysis was performed. Using Pear-son’s or Spearman’s correlation, the R2-coefficient value within the range of 0.4–0.7 was accepted as moderate [17]. In multiple linear regression ana lysis, some models were created based on the assumption that atherogenic indices or athero-genic factors as the dependent variables corre-late with the independent variables. For multiple


www.futuremedicine.com 725future science group

regression ana lysis, the Snedecor F-test was used. Logistic regression was performed to determine associations between baseline parameters and the occurrence of overweight and obesity. To com-pare the diagnostic utility of adiponectin and A-FABP, receiver-operating characteristic (ROC) curves were constructed (area under the curve [AUC]) and 95% CI, sensitivity and specificity calculated. Odds ratio with 95% CI were also calculated. p < 0.05 was considered statistically significant. Statistical ana lysis was performed using Statistica 10.0 for Windows (StatSoft, OK, USA).

Results�n Baseline characteristics & results of

basic statisticsBaseline characteristics of the obese, overweight and control groups, including anthropo metric and lipid parameters, HOMA–IR, insulin, hsCRP, A-FABP, adiponectin and apolipo protein concentrations, and values of blood pressure

constituting major cardiovascular risk factors, are shown in Table 1. Women with obesity, compared with controls, had higher values of anthropo-metric parameters, concentrations of hsCRP and TG, but lower levels of HDL-C. They also presented significantly higher values of athero-genic indices such as TC:HDL-C, apoB:apoA-I and TG:HDL-C, as well as a nearly threefold higher median concentration of A-FABP in com-parison with the control group. Out of biochemi-cal variables, only median A-FABP and hsCRP concentrations as well as TG:HDL-C were sig-nificantly higher in overweight women. On the contrary, median serum adiponectin was signifi-cantly lower only in the obese compared with the control group.

In the study group a moderate positive cor-relation between serum A-FABP concentration, BMI and waist circumference was found (Table 2). The present study also showed weak but highly significant positive correlation of A-FABP with hsCRP compared with the anti-inflammatory

Table 1. Baseline characteristics of the obese, overweight and control group.

Parameter Group p-value

Control (BMI <25; n = 76)

Overweight (BMI = 25–29.9; n = 48)

Obese (BMI ≥30; n = 56)

Control vs overweight

Control vs obese

Overweight vs obese

Age (years) 28 (25–32) 29 (25–36) 30 (27–37) NS NS NS

WC (cm) 71 (69–74) 88 (84–90) 108 (100–119) 0.0001 0.0001 0.0001

BMI (kg/m2) 21.4 (19.6–22.3) 27.6 (26.3–28.5) 35.2 (32.3–38.4) 0.0001 0.0001 0.0001

WHR 0.75 (0.73–0.80) 0.81 (0.79–0.85) 0.87 (0.85–0.91) 0.0001 0.0001 0.0003

A-FABP (ng/ml) 10.1 (7.9–13.1) 17.5 (14.9–21.7) 28 (22.9–42.5) 0.0007 0.0001 0.03

hsCRP (mg/l) 0.7 (0.3–1.0) 1.4 (0.8–2.5) 3.3 (1.9–6.9) 0.005 0.0001 0.02

Adiponectin (µg/ml) 15.5 (9.7–17.9) 11.6 (8.5–16.2) 10.1 (6.5–13.3) NS 0.02 NS

TC (mmol/l) 4.24 (4–4.78) 4.11 (3.51–5.01) 4.75 (4.16–5.32) NS NS NS

LDL-C (mmol/l) 2.56 (2.17–2.97) 2.4 (1.86–2.76) 2.94 (2.43–3.49) NS NS 0.02

HDL-C (mmol/l) 1.39 (1.29–1.57) 1.29 (1.11–1.57) 1.16 (1–1.29) NS 0.0001 0.03

TG (mmol/l) 0.72 (0.57–0.82) 0.87 (0.65–1.2) 1.13 (0.96–1.4) NS 0.0001 0.03

TC:HDL-C 2.9 (2.7–3.5) 3.1 (2.6–3.6) 4.4 (3.5–4.9) NS 0.0001 0.0007

TG:HDL-C 0.48 (0.39–0.57) 0.57 (0.52–0.87) 1.05 (0.78–1.27) 0.01 0.0001 0.008

apoA-I (g/l) 1.5 (1.39–1.6) 1.46 (1.22–1.65) 1.32 (1.26–1.5) NS NS NS

apoB (g/l) 0.61 (0.54–0.75) 0.64 (0.49–0.76) 0.84 (0.7–0.96) NS 0.0002 0.0001

apoB:apoA-I 0.42 (0.35–0.48) 0.43 (0.36–0.53) 0.64 (0.49–0.75) NS 0.0001 0.0003

Systolic BP (mmHg) 120 (114–120) 120 (113–128) 135 (130–149) NS 0.0001 0.0005

Diastolic BP (mmHg) 77 (70–80) 80 (70–85) 90 ( 85–101) NS 0.0001 0.0004

Insulin (µIU/ml) 5.9 (4.4–7.1) 6.0 (4.9–10.7) 13.3 (7.8–17.9) NS 0.0001 0.008

HOMA–IR 1.22 (0.9–1.5) 1.32 (0.9–2.4) 2.9 (1.8–4.4) NS 0.0001 0.004

Values are presented as median (25th–75th quartile). BP: Blood pressure; HDL‑C: High‑density lipoprotein cholesterol; HOMA–IR: Homeostasis Model of Assessment–Insulin Resistance; hsCRP: High‑sensitivity CRP; LDL‑C: Low‑density lipoprotein cholesterol; NS: Not statistically significant; TC: Total cholesterol; TG: Triglyceride; WC: Waist circumference; WHR: Waist‑to‑hip ratio.



indicators adiponectin, HDL-C and apoA-I (neg-ative correlation). Moderate positive correlations were found with HOMA–IR, insulin and indi-ces of atherogenic profile, especially TC:HDL-C, TG:HDL-C and apoB:apoA-I.

�n Multiple linear & logistic regression ana lysisFurthermore, we performed a multiple linear regression ana lysis. First, we have presented only the results of the best model with two variables explaining changes in TG:HDL-C (the index of LDL particle size) in relation to A-FABP and adiponectin within the study group. This model explained 47% of TG:HDL-C varia-tion (R2 = 0.47; p = 0.00001); however, only A-FABP contributed significantly and its impact accounted for 42%.

Another four-variable model with A-FABP as a dependent variable and TG:HDL, HOMA–IR, apoB:apoA1 and hsCRP as independent variables explained 51% of A-FABP variation (R2 = 0.51; p = 0.00001); however, only TG:HDL and hsCRP contributed significantly.

The probability of overweight and obe-sity occurrence, depending on the measured

laboratory parameters and calculated atherogenic ratios, was presented using logistic regression after adjustment for age and hypertension. We decided to exclude the BMI from the regression model because of its high colinearity with A-FABP. The designed model was highly significant (p = 0.001) and, based on the result of a pseudomeasure of quality of the fit-R2 Nagelkerke, explained 86% of the variation for overweight and obesity occur-rence. In this model, TC:HDL-C, TG:HDL-C, apoB:apoA-I, HOMA–IR, hsCRP and adipo-nectin did not facilitate the risk stratification for overweight/obesity. Only A-FABP significantly increased the risk of occurrence of overweight and obesity in women by approximately 83% (adjusted odds ratio: 1.83; 95% CI: 1.16–2.89).

�n Diagnostic utility of investigated markersFinally, we evaluated the ROC curves to assess diagnostic accuracies of investigated variables for the prediction of overweight/obesity occur-rence. The higher level of discrimination of overweight/obesity was found for A-FABP (AUC = 0.96) compared with adiponectin (AUC = 0.67). The best cutoff value of A-FABP for discrimination between normal weight and overweight/obese women was considered to be 16.0 ng/ml (AUC = 0.96; 95% CI: 0.88–0.99; sensitivity 80%; specificity 100%).

ROC ana lysis performed to compare A-FABP and adiponectin discriminating power for pre-dicting an atherogenic risk profile has shown better accuracy for A-FABP (Table 3). The diag-nostic accuracy of A-FABP for predicting elevated TG:HDL-C in overweight/obese women was bet-ter compared with that of adiponectin. Similarly, significantly higher diagnostic accuracy was found for A-FABP as a predictor of increased hsCRP concentration in overweight/obese women than for adiponectin. For all parameters, sensitivity and specificity were calculated as shown in Table 3.

Serum A-FABP concentration over 16 ng/ml was associated with an odds ratio of 11.2 (p = 0.0001), 7.1 (p = 0.004), 6.7 (p = 0.0001) and 5.1 (p = 0.002) for elevated TG:HDL-C, apoB, hsCRP or apoB:apoA-I, respectively (Table 4). Moreover, A-FABP concentrations over the cutoff predicted IR (HOMA–IR) with an odds ratio of 5.6 (p = 0.002).

Discussion Subjects with obesity and diabetes mellitus are at increased risk for cardiovascular diseases. Cur-rently, the diagnosis of cardiovascular diseases in these asymptomatic patients is not adequate, and

Table 2. Spearman’s correlation coefficients between A-FABP and the measured parameters in the study group.

Parameter A-FABP

R2 p-value

hsCRP 0.34 0.001

Adiponectin -0.31 0.03

TG 0.29 0.03

LDL-C NS NS

HDL-C -0.30 0.04

TC:HDL-C 0.43 0.004

TG:HDL-C 0.41 0.003

apoA-I -0.34 0.02

apoB 0.30 0.04

apoB:apoA-I 0.40 0.007

Systolic BP 0.28 0.05

Diastolic BP NS NS

Insulin 0.41 0.005

HOMA–IR 0.43 0.003

Glucose 0.32 0.03

BMI 0.62 0.0007

WC 0.47 0.001

BP: Blood pressure; HDL‑C: High‑density lipoprotein cholesterol; HOMA–IR: Homeostasis Model of Assessment–Insulin Resistance; hsCRP: High‑sensitivity CRP; LDL‑C: Low‑density lipoprotein cholesterol; NS: Not statistically significant; TC: Total cholesterol; TG: Triglyceride; WC: Waist circumference.



searching for new potential biomarkers is of great importance. In the present study, we have investi-gated the relationship of serum A-FABP, the adi-pose tissue-derived molecule, with atherogenic risk profile and insulin sensitivity in non diabetic young women with overweight/obesity. The asso-ciation of A-FABP with HOMA–IR and proin-flammatory cytokines was found very recently in nondiabetic, morbidly obese Spanish women [9]. We have found that in overweight and mildly obese young women, A-FABP correlated with pro-inflammatory and anti-inflammatory factors and IR indices. A-FABP was an independent predictor of TG:HDL-C (the index of LDL particle size), whereas neither BMI nor adiponectin have shown a predictive power in this setting. Serum A-FABP was found to explain 42% of TG:HDL-C varia-tion in overweight/obese women, which indicates its association with the LDL particle size and possibly their number, as well as reflecting IR [18].

According to the previous data, of two main adipose tissue-derived molecules, adiponectin was considered an inhibitor of atherosclerosis, preventing the onset and progression of cardio-vascular diseases, especially in cases with MS [2,19–21], whereas A-FABP was associated with carotid atherosclerosis in humans. In contrast to adiponectin, A-FABP promotes inflammation [5,6] and is proposed to contribute to dyslipidemia and foam cell formation [22,23]. A-FABP might

serve as a significant mediator that links obesity with its related metabolic and cardiovascular diseases [6,24–27]. A-FABP-deficient mice are pro-tected from IR, hyperglycemia and atherosclerosis [28,29]. In humans, it has been demonstrated that the circulating A-FABP level has been associ-ated with central adiposity, IR and subclinical athero sclerosis [3,9,28]. Despite the observation that A-FABP seems to be closely associated to adiposity and fat distribution, it was postulated that lifestyle changes lower plasma A-FABP con-centration in patients with cardiovascular risk [6]. However, data on the impact of lifestyle changes on A-FABP level are scarce.

Good positive association between serum A-FABP concentration and indicators of adipos-ity (BMI and waist circumference) suggests that adipose tissue might be the major contributor of A-FABP secreted into the circulation. In fact, A-FABP mRNA expression in visceral adipose tissue was related to its circulating concentrations in morbidly obese women [9]. Data of Tuncman et al. have provided support to the recently pub-lished study, demonstrating that a genetically determined reduction in the A-FABP mRNA level in human adipose tissue is associated with a reduced risk of cardiovascular disease and sug-gest a pathogenetic role of A-FABP in cardiovas-cular risk in humans, as seen in experimental animals [30].

Table 3. Diagnostic utility of A-FABP and adiponectin for predicting atherogenic risk profile.

Atherogenic risk profile Parameter AUC (95% CI) p-value Sensitivity/specificity (%)

LDL-C ≥3.36 mmol/l A-FABP 0.63 (0.52–0.74) NS 100/27

Adiponectin 0.63 (0.51–0.73) 65/63

apoB ≥0.9 g/l A-FABP 0.73 (0.62–0.83) NS 87/58

Adiponectin 0.65 (0.53–0.75) 47/80

apoB:apoA1 ≥0.6 A-FABP 0.74 (0.63–0.83) NS 75/67

Adiponectin 0.69 (0.59–0.79) 65/72

TG:HDL-C ≥1.3 A-FABP 0.88 (0.79–0.94) 0.08 78/70

Adiponectin 0.73 (0.62–0.83) 85/62

TC:HDL-C ≥4 A-FABP 0.77 (0.66–0.86) NS 75/70

Adiponectin 0.70 (0.59–0.79) 83/59

hsCRP ≥1 mg/l A-FABP 0.80 (0.70–0.88) 0.003 84/65

Adiponectin 0.59 (0.48–0.70) 55/66

HOMA–IR ≥2.75 A-FABP 0.78 (0.67–0.86) NS 83/72

Adiponectin 0.79 (0.69–0.87) 63/92

AUC: Area under the curve; HDL‑C: High‑density lipoprotein cholesterol; HOMA–IR: Homeostasis Model of Assessment–Insulin Resistance; hsCRP: High‑sensitivity CRP; LDL‑C: Low‑density lipoprotein cholesterol; NS: Not statistically significant; TC: Total cholesterol; TG: Triglyceride.



We have found that serum A-FABP was signif-icantly higher already in women with overweight compared with normal-weight women. In logis-tic regression analysis we determined associations between A-FABP and the occurrence of over-weight and obesity. Only A-FABP significantly increased the risk of occurrence of overweight and obesity in women by approximately 83%. Moreover, our results clearly demonstrated the high discrimination power of A-FABP between controls and women with overweight/obesity with high sensitivity and very high specificity at a cutoff level of 16 ng/ml. However, as BMI is easy to measure without blood testing, our find-ings of A-FABP for prediction of atherogenic risk profiles seem to be more clinically relevant. The diagnostic accuracy for predicting atherogenic risk profile was very good for A-FABP compared with that of adiponectin. Our results are in line with the very recent report of Roos et al., indi-cating that adiponectin has been inversely cor-related with the risk of cardiovascular diseases in men but not in women [31].

High A-FABP and low adiponectin levels were reported as independent predictors of atherogenic dyslipidemia. As suggested by oth-ers, elevated plasma A-FABP concentrations should be considered as a potential marker of metabolic derangement, which may predict the development of atherogenic dyslipidemia [7]. Although the mechanisms involved in this effect are unknown, a link to the hyperlipolytic state of this condition is likely to contribute. A-FABP is considered a good plasma marker of adipose tissue dysfunction in these metabolic situations, being associated with central adipos-ity, MS and IR [3,5,32,33]. A-FABP plasma lev-els are clearly high in obesity, Type 2 diabetes and MS [3,5,32], and Cabré et al. have previously reported that they are associated with TG-rich lipoprotein components leading to atherogenic

dyslipidemia [8]. Our study group with over-weight/obesity had no diabetes, but was char-acterized by mild dyslipidemia. However, 52% of women had MS and in only 38% was MS with IR diagnosed. Altogether, this could have influenced the obtained results. At first glance, the impact of A-FABP on atherogenic profile in young nondiabetic women with overweight/obe-sity seems to be more pronounced than on IR. The relationship of A-FABP with atherogenic profile/apolipoproteins in our study was con-firmed by correlations with some lipid parame-ters such as positive correlation with atherogenic indices, especially the TG:HDL-C ratio. This ratio was shown to be useful in assessing the presence of small, dense atherogenic LDL par-ticles in nondiabetic subjects without prominent hyperlipidemia [10,34]. On the other hand, the TG:HDL-C may also be used as a predictor of IR and our findings indicated the possible con-tribution of A-FABP to IR. In the present study, calculated odds ratio for elevated TG:HDL-C, apoB, hsCRP and HOMA–IR clearly indicated the important association of increased serum A-FABP with increased atherogenic risk and IR.

The study has some limitations. We did not focus more on the comparison between A-FABP and adiponectin as this was not the main scope of the study. Instead of a direct measure of the small, dense LDL particle number, we have used the TG:HDL-C index; however, this index was found to be useful in several earlier studies. Our conclusion is valid only for women aged 20–45 years. Owing to the relatively small sam-ple size, our findings require further extended studies.

ConclusionIn summary, serum A-FABP in young non-diabetic women with overweight or obesity was closely associated with atherogenic risk. Our findings suggest that elevated A-FABP contrib-utes to cardiovascular diseases beyond its effect on IR.

Future perspectiveRecently, an important molecular pathway inte-grating metabolic and inflammatory responses was suggested that involves the FABPs, which are present in adipocytes and macrophages. However, prospective studies linking circulat-ing A-FABP levels with cardiovascular disease outcomes in the general population are still lacking.

To evaluate whether the circulating levels of A-FABPs are independent risk factors that

Table 4. Odds ratio and 95% CI values for atherogenic profile and insulin resistance in women with serum A-FABP concentrations over the cutoff level (16 ng/ml).

Parameter OR 95% CI p-value

apoB 7.1 1.9–27.2 0.004

apoB:apoA-I 5.1 1.8–14.6 0.002

TG:HDL-C 11.2 3.7–34.2 0.0001

TC:HDL-C 4.9 1.8–12.9 0.001

hsCRP 6.7 2.6–17.2 0.0001

HOMA–IR 5.6 1.8–17.2 0.002

HDL‑C: High‑density lipoprotein cholesterol; HOMA–IR: Homeostasis Model of Assessment–Insulin Resistance; hsCRP: High‑sensitivity CRP; OR: Odds ratio; TC: Total cholesterol; TG: Triglyceride.



predict atherogenic risk profile and IR, it is necessary to perform further studies. Elevated A-FABP concentration could possibly repre-sent an important pathophysiological mediator of atherosclerosis, indicating a new target for treatment. Perhaps in the future, this research will contribute to the introduction of A-FABP as a new marker in routine laboratory diagnos-tics, which seems to be a valuable predictor of atherogenic risk profile overweight or obese patients, and suggests that elevated A-FABP contributes to atherosclerosis/cardiovascular diseases. Patients could also potentially be iden-tified based on specific biomarkers expressed by adipose tissue and therapies individualized and tailored to maximize effect.

Author contributionsAll authors contributed to the creation of the article. This work was initiated by the idea of A Mankowska-Cyl, who also performed all the laboratory determinations. G Sypniewska was responsible for the scientific merit of the manuscript and proper drafting of the work. M Krintus dealt with the statistical ana lysis and graphical editing. P Rajewski has been involved in contact with patients.

AcknowledgementsThe authors would like to thank the staff at the Depart-ment of Laboratory Medicine of University Hospital for help in performing the determinations of lipid parameters.

Financial & competing interests disclosureThis study was supported by a grant number 14/2008 from the Nicolaus Copernicus University in Torun Ludwik Rydygier Collegium Medicum, Bydgoszcz, Poland. The authors have no other relevant affiliations or financial involvement with any organization or entity with a finan-cial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research The authors state that they have obtained appropriate insti-tutional review board approval or have followed the princi-ples outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investi gations involving human subjects, informed consent has been obtained from the participants involved.

Executive summary

Background

� It was recently suggested that fatty acid-binding proteins are involved in important molecular pathways that integrate metabolic and inflammatory responses.

Baseline characteristics & results of basic statistics

� Circulating A-FABP levels were increased in obese and overweight subjects compared with lean subjects; moreover, median A-FABP was significantly higher in overweight women compared with the control group.

Multiple linear & logistic regression analysis

� Serum A-FABP was found to explain 42% of triglyceride:high-density lipoprotein cholesterol variation in overweight/obese women, which indicates its association with the low-density lipoprotein particle size and possibly their number, as well as reflecting insulin resistance.

� A-FABP significantly increased the risk of occurrence of overweight and obesity in women by approximately 83%.

Diagnostic utilities of investigated markers

� Results clearly demonstrated the high discrimination power of A-FABP between controls and women with overweight/obesity, with a high sensitivity and very high specificity at a cutoff of 16 ng/ml.

� Calculated odds ratio for elevated triglyceride:high-density lipoprotein cholesterol, apoB, high-sensitivity CRP and Homeostasis Model of Assessment–Insulin Resistance clearly indicated the important association of increased serum A-FABP with increased atherogenic risk and insulin resistance.

Conclusion

� A-FABP seems to be a valuable predictor of atherogenic risk profile in young nondiabetic overweight/obese women, suggesting that elevated A-FABP contributes to cardiovascular diseases beyond its effect on insulin resistance.

ReferencesPapers of special note have been highlighted as:n of interestnn of considerable interest

1 Zahorska-Markiewicz B. Metabolic effects associated with adipose tissue distribution. Adv. Med. Sci. 51, 111–114 (2006).

2 Shibata R, Ouchi N, Murohara T. Adiponectin and cardiovascular disease. Circ. J. 73, 608–614 (2009).

3 Xu A, Wang Y, Xu JY et al. Adipocyte fatty acid-binding protein is a plasma biomarker closely associated with obesity and metabolic syndrome. Clin. Chem. 52, 405–413 (2006).

4 Makowski L, Hotamisligil GS. Fatty acid binding proteins – the evolutionary crossroads of inflammatory and metabolic responses. J. Nutr. 134, 2464–2468 (2004).

5 Tso AW, Lam TK, Xu A et al. Serum adipocyte fatty acid-binding protein associated with ischemic stroke and early death. Neurology 76(23), 1968–1975 (2011).

Research Article Mankowska-Cyl, Krintus, Rajewski & SypniewskaResearch Article


6 Lázaro I, Ferré R, Plana N et al. Lifestyle changes lower FABP4 plasma concentration in patients with cardiovascular risk. Rev. Esp. Cardiol. 65(2),152–157 (2012).

nn� Establishes that A-FABP may also play a role in the development of atherosclerotic diseases in humans and that lifestyle changes lower A-FABP plasma concentration in patients with cardiovascular risk.

7 Cabré A, Babio N, Lázaro I et al. FABP4 predicts atherogenic dyslipidemia development. The PREDIMED study. Atherosclerosis 222(1), 229–234 (2012).

nn� Suggests that elevated plasma A-FABP concentrations should be considered as a potential marker of metabolic derangement, which may predict the development of atherogenic dyslipidemia.

8 Cabré A, Lázaro I, Cofán M et al. FABP4 plasma levels are increased in familial combined hyperlipidemia. Lipid Res. 51, 1173–1178 (2010).

nn� A-FABP was proposed as a clinical biomarker for atherogenic dyslipidemia, independent of obesity and insulin resistance, in Type 2 diabetics and nonobese patients with familial combined hyperlipidemia.

9 Terra X, Quintero Y, Auguet T et al. FABP 4 is associated with inflammatory markers and metabolic syndrome in morbidly obese women. Eur. J. Endocrinol. 164, 539–547 (2011).

10 Third Report of the National Cholesterol Education Program (NCEP) National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 106(25), 3143–3421 (2002).

11 Brunzell JD, Davidson M, Furberg CD et al. Lipoprotein management in patients with cardiometabolic risk: consensus conference report from the American Diabetes Association and the American College of Cardiology Foundation. J. Am. Coll. Cardiol. 51, 1512–1524 (2008).

12 Maruyama C, Imamura K, Teramoto T. Assessment of LDL particle size by triglyceride/HDL-cholesterol ratio in non-diabetic, healthy subjects without prominent hyperlipidemia. J. Atheroscler. Thromb. 10, 186–191 (2003).

13 Pearson TA, Mensah GA, Alexander RW et al. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 107(3), 499–511 (2003).

14 Walldius G, Jungner I. The apoB/apoA-I ratio: a strong new risk factor for cardiovascular disease and target for lipid-lowering therapy – a review of the evidence. J. Intern. Med. 259, 493–519 (2006).

15 Mancia G, De Backer G, Dominiczak A et al. 2007 ESH–ESC guidelines for the management of arterial hypertension: the task force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Blood Press. 16, 135–232 (2007).

16 Hypertension. The Clinical Management of Primary Hypertension in Adults (NICE clinical guideline 127). National Institute for Health and Clinical Excellence, UK (2011).

17 Cohen J. Statistical Power Analysis for the Behavioral Sciences (2nd Edition). Lawrence Erlbaum Associates, NJ, USA (1988).

18 Chiang JK, Lai NS, Chang JK et al. Predicting insulin resistance using the triglyceride-to-high-density lipoprotein cholesterol ratio in Taiwanese adults. Cardiovasc. Diabetol. 17, 10–93 (2011).

n� The triglyceride:high-density lipoprotein cholesterol ratio was shown to be useful in assessing the presence of small dense atherogenic low-density lipoprotein particles in nondiabetic subjects without prominent hyperlipidemia, and may also be used as a predictor of insulin resistance.

19 Matsubara M, Maruoka S, Katayose S. Inverse relationship between plasma adiponectin and leptin concentrations in normal-weight and obese women. Eur. J. Endocrinol. 147, 173–180 (2002).

20 Hopkins TA, Ouchi N, Shibata R, Walsh K. Adiponectin actions in the cardiovascular system. Cardiovasc. Res. 74, 11–18 (2007).

21 Nakamura Y, Shimada K, Fukuda D et al. Implications of plasma concentrations of adiponectin in patients with coronary artery disease. Heart 90, 528–533 (2004).

22 Coe NR, Simpson MA, Bernlohr DA. Targeted disruption of the adipocytes lipid-binding protein (aP2 protein) gene impairs fat cell lipolysis and increases cellular fatty acid levels. J. Lipid Res. 40, 967–972 (1999).

23 Tian L, Luo N, Klein RL, Chung BH, Garvey WT, Fu Y. Adiponectin reduces lipid accumulation in macrophage foam cells. Atherosclerosis 202, 152–161 (2009).

24 Peeters W, de Kleijn DP, Vink A et al. Adipocyte fatty acid binding protein in atherosclerotic plaques is associated with local vulnerability and is predictive for the occurrence of adverse cardiovascular events. Eur. Heart J. 32, 1758–1768 (2011).

25 Yoo HJ, Kim S, Park MS et al. Serum adipocyte fatty acid-binding protein is associated independently with vascular inflammation: ana lysis with (18)F-fluorodeoxyglucose positron emission tomography. J. Clin. Endocrinol. Metab. 96, 488–492 (2011).

26 Doi M, Miyoshi T, Hirohata S et al. Association of increased plasma adipocyte fatty acid-binding protein with coronary artery disease in non-elderly men. Cardiovasc. Diabetol. 10, 44 (2011).

27 Miyoshi T, Onoue G, Hirohata A et al. Serum adipocyte fatty acid-binding protein is independently associated with coronary atherosclerotic burden measured by intravascular ultrasound. Atherosclerosis 21, 164–169 (2010).

28 Boord JB, Maeda K, Makowski L et al. Combined adipocyte-macrophage fatty acid-binding protein deficiency improves metabolism, atherosclerosis, and survival in apolipoprotein E-deficient mice. Circulation 110, 1492–1498 (2004).

29 Makowski L, Boord JB, Maeda K et al. Lack of macrophage fatty-acid-binding protein aP2 protects mice deficient in apolipoprotein E against atherosclerosis. Nat. Med. 7, 699–705 (2001).

30 Tuncman G, Erbay E, Hom X et al. A genetic variant at the fatty acid-binding protein aP2 locus reduces the risk for hypertriglyceridemia, Type 2 diabetes, and cardiovascular disease. Proc. Natl Acad. Sci. USA 103, 6970–6975 (2006).

31 Roos CJ, Quax PH, Jukema JW. Cardiovascular metabolic syndrome: mediators involved in the pathophysiology from obesity to coronary heart disease. Biomark. Med. 6, 35–52 (2012).

32 Cabré A, Lázaro I, Girona J et al. Fatty acid binding protein 4 is increased in metabolic syndrome and with thiazolidinedione treatment in diabetic patients. Atherosclerosis 195, 150–158 (2007).

33 Bergmann K, Sypniewska G. Diabetes as a complication of adipose tissue dysfunction. Is there a role for potential new biomarkers? Clin. Chem. Lab. Med. 51, 177–185 (2013).

34 Kimm H, Lee SW, Lee HS et al. Associations between lipid measures and metabolic syndrome, insulin resistance and adiponectin. Circ. J. 74, 931–937 (2010).

n� The triglyceride:high-density lipoprotein cholesterol ratio was shown to be useful in assessing the presence of small dense atherogenic low-density lipoprotein particles in nondiabetic subjects without prominent hyperlipidemia, and may also be used as a predictor of insulin resistance.

a-fabp and its association with atherogenic risk profile and insulin resistance in young overweight...

Documents