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DOI:10.4158/EP13173.OR Endocrine Practice © 2013

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ENDOCRINE PRACTICE Rapid Electronic Article in Press Rapid Electronic Articles in Press are preprinted manuscripts that have been reviewed and accepted for publication, but have yet to be edited, typeset and finalized. This version of the manuscript will be replaced with the final, published version after it has been published in the print edition of the journal. The final, published version may differ from this proof. DOI:10.4158/EP13173.OR © 2013 AACE. Original Article EP13173.OR

PRECLINICAL ATHEROSCLEROSIS IN PATIENTS WITH PROLACTINOMA

Running title: Prolactinoma and cardiovascular risk

Muyesser Sayki Arslan, MD1; Oya Topaloglu, MD1; Mustafa Sahin, MD2; Esra Tutal,

MD1; Askin Gungunes, MD1 ; Evrim Cakir, MD1; Ilknur Unsal Ozturk, MD1; Basak Karbek, MD1; Bekir Ucan, MD1 ;Zeynep Ginis, MD3; Erman Cakal, MD1; Mustafa Ozbek, MD1 ; Tuncay

Delibasi, MD1

From the 1Diskapi Yildirim Beyazit Training and Research Hospital, Department of Endocrinology and Metabolic Diseases, Ankara, Turkey, 2Ankara University, School of Medicine, Department of Endocrinology and Metabolic Diseases, Ankara, Turkey, 3Diskapi Yildirim Beyazit Training and Research Hospital, Department of Biochemistry, Ankara, Turkey. Address correspondence to Tuncay Delibasi, Prof., Diskapi Yildirim Beyazit Training and Research Hospital, Department of Endocrinology and Metabolic Diseases, Ankara, Turkey. E-mail: [email protected]


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ABSTRACT

Objective: The aim of this study was to evaluate the effect of hyperprolactinemia on body

fat, insulin sensitivity, inflammatory markers, and cardiovascular risk in patients with

prolactinoma.

Methods: The study included 35 untreated hyperprolactinemic patients with pituitary

adenomas, and 36 age-, gender-, and BMI-matched healthy controls without any known disease.

Serum glucose, insulin, homeostasis model assessment of insulin resistance, lipid profile, high

sensitive C-reactive protein, and heart-type fatty acid binding protein levels were measured. Waist

and hip circumference were measured in all the participants. The body fat percentage was

measured, and the visceral fat and abdominal fat percentage was measured via bioelectrical

impedance. In addition, carotid intima media thickness was measured using high-resolution B-

mode ultrasound.

Results: The serum glucose level, homeostasis model assessment of insulin resistance,

triglyceride level, and waist circumference were significantly higher in the patient group than in

the control group. The high sensitive C-reactive protein level and carotid intima media thickness

were significantly higher in the hyperprolactinemic patients. Visceral and truncal fat percentages

were significantly higher in the patients with prolactinoma. Heart-type fatty acid binding protein

levels were similar in the patient and control groups, and there was a positive correlation between

the prolactin and heart-type fatty acid binding protein levels.

Conclusions: Based on the present findings, hyperprolactinemia is associated with

preclinical atherosclerosis and metabolic abnormalities. Patients with hyperprolactinemia might

experience cardiovascular disease in the long-term. Metabolic control should be achieved in

addition to the control of hyperprolactinemia, in the clinical management of patients diagnosed

with prolactinoma.

Keywords: Hyperprolactinemia; atherosclerosis; cardiovascular risk; metabolic profile


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Abbreviations

BIA = bioelectrical impedance analysis; BMI = body mass index; CIMT = carotid artery intima

media thickness; H-FABP = heart type fatty acid binding protein; HDL = high density

lipoprotein; HOMA-IR = homeostasis model assessment of insulin resistance; hs-CRP = high

sensitive C-reactive protein; LDL = low density lipoprotein

INTRODUCTION

Prolactinoma has been associated with metabolic and inflammatory conditions that might

increase cardiovascular risk, including obesity, insulin resistance, dyslipidemia, low-grade

inflammation, and hypercoagulability (1-6). Furthermore, the supraphysiological prolactin (PRL)

level may play a role in accelerated arteriosclerosis and may be correlated with cardiovascular

mortality in early menopause (7). There is increasing evidence that suggests hyperprolactinemia

plays a role in various components of atherogenesis. PRL receptors were observed in coronary

artery plaques in patients without hyperprolactinemia (8). In vitro studies have demonstrated that

PRL can modulate inflammatory responses, stimulate vascular smooth muscle cell proliferation,

and play a role in adhesion of circulating mononuclear cells to endothelium, all of which might

alter vascular structure and function (9-11). In addition PRL might alter endothelial function via

modification of peripheral and central hemodynamics through its vasoconstrictive features (12).

There have been reports of impaired endothelial vasodilatory function, based on flow-mediated

dilatation of the brachial artery, in patients with hyperprolactinemia (6,13). Whereas

hyperprolactinemia is a common endocrine disorder, cardiovascular risk assessment is under

performed.

Heart-type fatty acid binding protein (H-FABP) is a soluble small cardiomyocyte protein

that may protect myocardial cells from oxidation of long fatty acids (14). It was proposed that H-

FABP is an early diagnostic biochemical marker of acute coronary syndrome (15). In addition, an


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elevated serum H-FABP level has been observed in such conditions as heart failure,

cardiomyopathy, pulmonary embolism, and metabolic syndrome (16-18). Carotid artery intima

media thickness (CIMT) is a validated non-invasive structural marker of preclinical atherosclerosis

with predictive value for cardiovascular outcome (19). The aim of the present study was to

evaluate the effect of hyperprolactinemia on H-FABP, high sensitive C-reactive protein (hs-CRP)

and CIMT and their relation with body fat and insulin sensitivity in addition to the CV risk in

patients diagnosed with prolactinoma and healthy controls.

METHODS

The study included 35 patients (27 female and 8 male) with active disease (both micro- and

macroprolactinoma) from our outpatient clinic. Prolactinoma was diagnosed based on an elevated

PRL level in 2 distinct samples and pituitary gland MRI findings indicative of prolactinoma.

Among the patients, 7 had macroprolactinoma and 28 had microprolactinoma. Patients with other

causes of hyperprolactinemia and hypopituitarism were excluded. None of the patients included in

the study had an endocrine diseases other than hyperprolactinoma. Only 1 of the female patients

was postmenopausal. Hyperprolactinemic patients were recruited to participate in the study prior

to beginning medical treatment. The control group included 36 healthy volunteers without any

known disease that were matched in terms of age, gender, and BMI. Participants with a history of

cardiovascular disease, cardiomyopathy, renal disease, and immunological disorders, or those that

were receiving any treatment that could affect cardiovascular and metabolic parameters were

excluded from the study. The Diskapi Training and Research Hospital Ethics Committee approved

the study protocol and all the participants provided written informed consent.

Serum glucose, high-density lipoprotein (HDL) cholesterol, and triglyceride levels were

measured using commercial enzymatic kits. PRL and insulin levels were measured via

chemiluminescence assay (Advia Centaur, Siemens Healthcare Diagnostics, USA). Intra-assay and

inter-assay variation coefficients for insulin levels of 14.68, 45.72, and 124.51 mUL–1 were 4.6%,


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3.2%, and 3.3%, respectively, and 5.9%, 2.6%, and 4.8%, respectively. Intra-assay and inter-assay

variation coefficients for PRL levels of 10.2 and 60.4 ngmL–1were 2.3% and 2.8%, respectively,

and 2.0% and 3.4%, respectively. The normal PRL level was 2.7-18.3 ngmL–1.

Measurement of H-FABP was performed using an EPOCH system (BioTek Instruments,

USA) anda commercially available ELISA kit (Hycult, Netherlands). The assay range of the H-

FABP ELISA kit was 102-25,000 pgmL–1. The samples were carried out together in the same

experiment. BMI and the homeostasis model assessment of insulin resistance (HOMA-IR) were

calculated (20). The total fat percentage (%), and abdominal and visceral fat composition of the

participants were assessed via bioelectrical impedance analysis (BIA) using a TBF-310GS™

(Tanita Corporation, Tokyo, Japan) (21). CIMT was measured via high-resolution B-Mode

ultrasonography using a 12-MHz linear probe (Hitachi EUB 7000 HV). Three arterial wall

segments of the carotid artery were measured bilaterally after imaging from a fixed lateral

transducer angle and designated as mean CIMT.

Descriptive data for the obtained measurements are presented as number, percentage, and

arithmetic mean±SD. The Kolmogorov-Smirnov test was used to test the normality of the

distribution of numerical data. Student’s T test, the chi-square test, and the Mann-Whitney U test

were used for between-group comparisons. Associations between parameters were determined via

Pearson’s correlation analysis. The backward elimination method was used to determine the

association between H-FABP and numerical measurements using multivariate multiple regression

analysis. The level of statistical significance was set at p<0.05. PASW v.18.0 for Windows was

used for all statistical calculations.

RESULTS

Serum fasting glucose, triglyceride, and waist circumference were significantly higher in

the patients with prolactinoma than in the controls (P<0.05). There wasn’t a significant difference

in HDL-C or LDL-C levels between the patients and controls (Table 1). The mean HOMA-IR


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value was significantly higher in the patient group than in the control group (2.6±1.6 vs. 1.9±0.9,

respectively, P <0.05). CIMT was significantly higher in the patient group than in the control

group (0.58±0.11 vs. 0.47±0, P <0.05), and the hs-CRP concentration was significantly higher in

the patients with prolactinoma than in the control group; however, there wasn’t a significant

difference in the H-FABP level between the patient and control groups (Table 2). Metabolic

variables and CIMT were adjusted for BMI (using BMI as a covariate by ANCOVA) because BMI

was higher in the patients than in the controls (P =0.075), which showed that fasting insulin (FI)

was significantly higher in the patients than in the controls (P =0.006), in addition to other

significant parameters. A relationship was observed between the serum H-FABP and PRL levels

(P <0.05, rho=0.365), based on correlation analysis. Additionally, there was a trend towards a

correlation between serum H-FABP and CIMT levels (P <0.05, rho=0.269); however, a positive

correlation was noted only between age and H-FABP, based on multiple regression analysis.

According to BIA, the total body fat percentage was higher in the patients with

prolactinoma than in the controls; however, the difference was not significant (30.3% ±8.8%

vs.26.2% ±10.8%, P =0.197). VIScan analysis showed that visceral and truncal fat percentages

were significantly higher in the patients with prolactinoma than in the control group (visceral fat:

13.4% ±5.5% vs. 9.4% ±5.3%, P =0.049; truncal fat: 41.4% ±6.1% vs. 34.7% ±10.3%, P =0.032);

however, there wasn’t a significant correlation between serum PRL or H-FABP levels, and the

body fat percentage, and visceral fat and truncal fat ratios. Moreover, thyroid-stimulating hormone

(TSH), free T4, and insulin growth factor-1 (IGF-1) levels were similar in the patient and control

groups (P >0.05) (Table 1).

DISCUSSION

The present study’s findings confirm that hyperprolactinemia is associated with features of

metabolic syndrome, including impaired insulin sensitivity, hypertriglyceridemia, and increased

waist circumference. The present findings also show that visceral and truncal fat percentages were


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higher in patients with prolactinoma. These metabolic abnormalities are a well-known precursor of

early atherosclerosis and cardiovascular disease; thus, patients diagnosed as prolactinoma with

increased insulin resistance or metabolic syndrome tend to have a higher cardiovascular risk.

Earlier studies have shown that PRL has a wide range of effects including immunoregulatory and

metabolic effects on multiple systems other than the reproductive and osmoregulatory systems

(2,22). PRL is also produced in extrapituitary tissues, including endothelial cells, and its receptor

belongs to the superfamily of hematopoietic cytokine receptors (23).

A growing body of data suggests that PRL can modulate inflammation due to its

immunostimulatory features (9).An animal study by Molinari et al. (12) reported that PRL induced

vasoconstriction, including constriction of coronary arteries, via inhibition of a vasodilatory β2-

adrenergic receptor-mediated effect related to the nitric oxide intracellular pathway. Reuwer et al.

(24) demonstrated that the PRL receptor is abundantly present in macrophages of atherosclerotic

plaques in the most prominent sites of inflammation and posited that the PRL receptor plays a role

in atherogenesis. In menopausal women physiological PRL levels have been correlated with a risk

score that predicts 10-year cardiovascular mortality (7). These data suggest that chronic

hyperprolactinemia might contribute to atherogenesis; however, adequate data regarding the effect

of PRL on cardiovascular circulation do not exist. Endothelial dysfunction is recognized as an

early atherogenic event (25). Yavuz et al. (13) and Serri et al. (6) reported that hyperprolactinemia

is associated with a high level of cardiovascular inflammatory markers, including hs-CRP,

homocysteine, interleukin-6 (IL-6), soluble E-selectin, and tumor necrosis factor-α (TNF-α) (6,13).

Serri et al. (6) observed that short-term dopamine agonist therapy can reduce the level of

inflammatory markers. Yavuz et al. (13) also showed that the hyperprolactinemic state is

associated with decreased endothelial function, based on the flow-mediated dilatation technique.

It was reported that CIMT is a widely used and validated early marker of cardiovascular

diseasecan accurately assess the structural components of the arterial wall (19). CIMT measured


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using ultrasonography correlates well with histological findings (26). Several longitudinal studies

have investigated the relationship between CIMT and cardiovascular events, and it is accepted as a

marker of preclinical atherosclerosis (27). In the present study preclinical atherosclerosis was

investigated via CIMT measurement. CIMT was significantly higher in the patients with

hyperprolactinemia than in the controls. It has been reported that H-FABP induces cardiac

myocyte hypertrophy, stimulating an increase in cell surface area, c-Jun expression, and protein

synthesis (28). H-FABP was recently proposed to be an early diagnostic marker of coronary events

(15). Moreover, elevated plasma levels of H-FABP have been associated with conditions of high

cardiovascular risk, such as metabolic syndrome (17); therefore, H-FABP was evaluated in the

present study’s patients with hyperprolactinemia, as they were expected to have higher levels than

the controls due to the vasoconstrictive, chronotropic, and metabolic effects of PRL hormones

(29); however, there wasn’t a significant difference in H-FABP between the patients and controls,

despite a significant difference in PRL and some metabolic syndrome components. As in earlier

studies, in the present study the patients had higher hs-CRP levels. It was reported that hs-CRP is

an independent prognostic marker of coronary artery disease, both in patients with acute coronary

events and in healthy males. In addition, hs-CRP is a marker of low-grade inflammation (30).

These data taken together suggest that inflammation accompanies hyperprolactinemia.

In addition to the effects of hyperprolactinemia on the cardiovascular system,

hyperprolactinemia effects body fat distribution. PRL receptors have been found in human adipose

tissue and PRL reduces lipoprotein lipase activity in fat cells in vitro (31). Nalioto et al. (32)

evaluated body fat in non-obese women with prolactinoma that were treated with dopamine

agonists, and reported that the body fat percentage was similar in the patients and controls. Body

fat was measured using dual energy X-ray absorptiometry, and arm, leg, truncal, android, gynoid,

and total body fat were positively associated with the PRL level. In the present study body fat was

measured via BIA and abdominal fat was measured using VIScan, a non-invasive validated


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technique. The body fat percentage in patients was higher than in controls, despite both groups

having a similar BMI. Obese patients were not excluded from the present study and the mean BMI

in the patient group was characterized as overweight. The effect of dopamine agonists on body fat

has been investigated in a few studies. Dopamine agonists were reported to improve the metabolic

profile; however; a significant reduction in body weight was not observed in prolactinoma patients

after 6 months of treatment (33).

The effect of hypothyroidism and growth hormone excess on metabolic parameters and

atherosclerosis was excluded in the present study by evaluating TSH, free T4, and IGF-1 levels.

Furthermore, the study participants were not receiving any type of treatment. Based on the present

findings, H-FABP is not a useful marker in prolactinoma patients. In consideration of the elevated

CIMT value observed in the present study’s patients and its link with cardiovascular risk, we think

that additional research is warranted in order to confirm the present findings and to further

investigate the underlying mechanisms associated with preclinical atherosclerosis. Nonetheless,

the present study has several limitations. Firstly, this study was cross-sectional in design.

Secondly, the study population was small and, therefore, the findings regarding H-FABP should be

re-evaluated in a larger population and, in particular, obese prolactinoma patients. Based on the

present findings, hyperprolactinemia is associated with an increase in atherogenesis and, therefore,

cardiovascular evaluation should be a consideration in the clinical management of patients

diagnosed with prolactinoma.


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REFERENCES

1. Creemers LB, Zelissen PM, Van’t Verlaat JW, Koppeschaar HP. Prolactinoma and

body weight: a retrospective study. Acta Endocrinol (Copenh). 1991125;392-396.

2. Shibli-Rahhal A, Schlechte J. The effects of hyperprolactinemia on bone and fat.

Pituitary. 2009;12:96-104.

3. Serri O, Beauregard H, Rasio E, Hardy J. Decreased sensitivity to insulin in women

with microprolactinomas. Fertil Steril.1986;45:572-574.

4. Pelkonen R, Nikkilä EA, Grahne B. Serum lipids, postheparin plasma lipase activities

and glucose tolerance in patients with prolactinoma. Clin Endocrinol (Oxf). 1982;16, 383-

390.

5. Erem C, Kocak M, Nuhoglu I, Yılmaz M, Ucuncu O. Blood coagulation, fibrinolysis

and lipid profile in patients with prolactinoma. Clin Endocrinol (Oxf). 2010;73;502-527.

6. Serri O, Li L, Mamputu JC, Beauchamp MC, Maingrette F, Renier G. The influences

of hyperprolactinemia and obesity on cardiovascular risk markers: effects of cabergoline

therapy. Clin Endocrinol (Oxf). 2006;64:366-370

7. Georgiopoulos GA, Stamatelopoulos KS, Lambrinoudaki I, et al. Prolactin and

preclinical atherosclerosis in menopausal women with cardiovascular risk factors.

Hypertension. 2009;54:98-105.

8. Reuwer AQ, Twickler MT, Hutten BA, et al. Prolactin levels and the risk of future

coronary artery disease in apparently healthy men and women. Circ Cardiovasc Genet.

2009;2:389-395.

9. Yu-Lee, L.Y.: Prolactin modulation of immune and inflammatory responses. Recent Prog

Horm Res. 2002;57:435-455.


11

10. Montes de Oca P, Macotela Y, Nava G, López-Barrera F, de la Escalera GM, Clapp

C. Prolactin stimulates integrin-mediated adhesion of circulating mononuclear cells to

endothelial cells. Lab Invest. 2005;85:633-642.

11. Sauro MD, Buckley AR, Russell DH, Fitzpatrick DF. Prolactin stimulation of protein

kinase C activity in rat aortic smooth muscle. Life Sci. 1989;44:1787-1792.

12. Molinari C, Grossini E, Mary DA, et al. Prolactin induces regional vasoconstriction

through the beta2-adrenergic and nitric oxide mechanisms. Endocrinology. 2007;148:4080-

4090.

13. Yavuz D, Deyneli O, Akpinar I. Endothelial function, insulin sensitivity and

inflammatory markers in hyperprolactinemic pre-menopausal women. Eur J Endocrinol.

2003;149:187-193.

14. Karaduman M, Sengul A, Oktenli C, et al. Tissue levels of adiponectin, tumour necrosis

factor-alpha, soluble intercellular adhesion molecule-1 and heart-type fatty acid-binding

protein in human coronary atherosclerotic plaques. Clin. Endocrinol. (Oxf). 2006;64:19-

202.

15. Ghani F, Wu AH, Graff L, Petry, et al. Role of heart-type fatty acid-binding protein in

early detection of acute myocardial infarction. Clin Chem. 2000;46;718-719.

16. Komamura K, Sasaki T, Hanatani A, et al. Heart-type fatty acid binding protein is a

novel prognostic marker in patients with non-ischaemic dilated cardiomyopathy. Heart.

2006;92:615-618.

17. Akbal E, Ozbek M, Günes F, Akyürek Ö, Üreten K, Delibaşı T. Serum heart type fatty

acid binding protein levels in metabolic syndrome. Endocrine. 2009;36:433-437.

18. Dellas C, Puls M, Lankeit M, et al. Elevated heart-type fatty acid-binding protein levels

on admission predict an adverse outcome in normotensive patients with acute pulmonary

embolism. J Am Coll Cardiol. 2010;55, 2150-2157.


12

19. Mancini GB, Dahlöf B, Díez J. Surrogate markers for cardiovascular disease: structural

markers. Circulation. 2004;109:IV22-30.

20. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC.

Homeostasis model assesment: insulin resistance and beta-cell function from fasting blood

glucoseand insuln concentrations in man. Diabetologia. 1985;28:412-419.

21. Thomas EL, Collins AL, McCarthy, et al. Estimation of abdominal fat compartments by

bioelectrical impedance: the validity of the ViScan measurement system in comparison

with MRI. Eur J Clin Nutr. 2010;64, 525533.

22. Shelly, S., Boaz, M., Orbach, H.: Prolactin and autoimmunity. Autoimmun Rev. 2012;11:

A465-470.

23. Clapp C, López-Gómez FJ, Nava G, et al. Expression of prolactin mRNA and of

prolactin-like proteins in endothelial cells: evidence for autocrine effects. J Endocrinol.

1998;158;137-144.

24. Reuwer AQ, van Eijk M, Houttuijn-Bloemendaal FM, et al. The prolactin receptor is

expressed in macrophages within human carotid atherosclerotic plaques: a role for

prolactin in atherogenesis?. J Endocrinol. 2011;208;107-117.

25. Zeiher AM, Drexler H, Wollschläger H, Just H. Endothelial dysfunction of the coronary

microvasculature is associated with coronary blood flow regulation in patients with early

atherosclerosis. Circulation. 1991;84:1984-1992.

26. Pignoli P, Tremoli E, Poli A, Oreste P, Paoletti R. Intimal plus medial thickness of the

arterial wall: a direct measurement with ultrasound imaging. Circulation. 1986;74:1399-

1406.

27. de Groot E, Hovingh GK, Wiegman A., et al. Measurement of arterial wall thickness as a

surrogate marker for atherosclerosis. Circulation. 2004;109:III33−38.


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28. Burton PB, Hogben CE, Joannou CL, et al. Heart fatty acid binding protein is a novel

regulator of cardiac myocyte hypertrophy. Burton. Biochem Biophys Res Commun.

1994;205:1822-1828.

29. Manku MS, Horrobin DF, Zinner H, et al. Dopamine enhances the action of prolactin on

rat blood vessels. Implications for dopamine effects on plasma prolactin. Endocrinology.

1977;101, 1343-1345.

30. Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers

of inflammation in the prediction of cardiovascular disease in women. N Engl J Med.

2000;342;836-843.

31. Ling C, Svensson L, Odén B, et al. Identification of functional prolactin (PRL) receptor

gene expression: PRL inhibits lipoprotein lipase activity in human white adipose tissue. J

Clin Endocrinol Metab. 2003;88, 1804−1808.

32. Naliato EC, Violante AH, Caldas D, et al. Body fat in nonobese women with

prolactinoma treated with dopamine agonists. Clin Endocrinol (Oxf). 2007;67:845-852.

33. dos Santos Silva CM, Barbosa FR, Lima GA, Warszawski L, et al. BMI and metabolic

profile in patients with prolactinoma before and after treatment with dopamine agonists.

Obesity (Silver Spring). 2011;19:800-805.

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Table 1. Demographic characteristics and biochemical data in the patient and control groups.

Patients

(n=35)

Controls

(n=35)

P

Male/female

Age (years)

PRL (ngmL–1)

BMI (kgm–²)

WC (cm)

HC (cm)

FBG (mgdL–1)

HDL-C (mgdL–1)

LDL-C (mgdL–1)

TG (mgdL–1)

FI (IU mL–1) HOMA-IR

TSH

fT4

IGF-1

8/27

40.1 ± 11.9

119.2 ± 116.0

28.6 ± 4.2

96.7 ± 12.8

104.4 ± 9.4

89.3 ± 9.7

50.8 ± 10.7

112.2 ± 32.8

144.2 ± 53.9

11.7 ± 6.3

2.6 ± 1.6

2.1 ± 1.0

1 ± 0.2

175.8 ± 68.4

9/26

39.0 ± 9.4

9.9 ± 5.6

26.7 ± 3.7

86.8 ± 8.0

92.2 ± 8.9

84.5 ± 7.2

49.1 ± 16.0

113.9 ± 24.6

108.0 ± 51.8

9.4 ± 4.3

1.9 ± 0.9

1.7 ± 0.9

1.1 ± 0.2

184.6 ± 42.3

0.634

0.682

0.0001

0.075

0.003

0.0001

0.021

0.612

0.812

0.008

0.093

0.026

0.11

0.08

0.8

*Data are presented as mean±SD.

PRL:Prolactin;BMI: body mass index; WC: waist circumference; HC: hip circumference; FBG: fasting blood glucose; HDL-C: high-density

cholesterol; LDL-C: low-density cholesterol; TG: triglyceride;FI: fasting insulin; HOMA-IR: homeostasis model assessment of insulin

resistance;TSH: thyroid-stimulating hormone; fT4: free T4; IGF-1: insulin like growth factor-1.

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Table 2.Cardiovascular risk parameters in the patient and control groups.

Patients (n=35) Controls (n=35) P

H-FABP (pg mL–1))

hs-CRP (IUmL–1)

CIMT (mm)

10.6±3.8

2.2±1.3

0.58±0.11

10.1±2.9

1.1±1.2

0.47±0

0.56

0.006

0.0001

H-FABP: Human-fatty acid binding protein; hs-CRP: high sensitive C-reactive protein;

CIMT: carotid intima media thickness.