Acta Diabetol (2014) 51:1025–1032 DOI 10.1007/s00592-014-0664-1

ORIGINAL ARTICLE

TNFRSF11B gene polymorphisms increased risk of peripheral arterial occlusive disease and critical limb ischemia in patients with type 2 diabetes Federico Biscetti • Carlo Filippo Porreca • Flavio Bertucci • Giuseppe Straface Angelo Santoliquido • Paolo Tondi • Flavia Angelini • Dario Pitocco • Luca Santoro • Antonio Gasbarrini • Raffaele Landolfi • Andrea Flex

•

Received: 26 July 2014 / Accepted: 3 October 2014 / Published online: 17 October 2014  Springer-Verlag Italia 2014

Abstract Aims Osteoprotegerin (OPG) is a secretory glycoprotein that belongs to the tumor necrosis factor receptor family and plays a role in atherosclerosis. OPG has been hypothesized to modulate vascular functions; however, its role in mediating atherosclerosis is controversial. Epidemiological data in patients with cardiovascular disease (CVD) indicate that OPG serum levels are associated with several inflammatory markers, myocardial infarction events, and calcium scores, suggesting that OPG may be causative for CVD. Federico Biscetti and Carlo Filippo Porreca have contributed equally to this study. Managed by Antonio Secchi. F. Biscetti Institute of Rheumatology and Affine Sciences, Catholic University School of Medicine, Rome, Italy F. Biscetti  C. F. Porreca  F. Bertucci  A. Santoliquido  P. Tondi  D. Pitocco  A. Gasbarrini  R. Landolfi  A. Flex (&) Department of Medicine, A. Gemelli University Hospital, Catholic University School of Medicine, Rome, Italy e-mail: [email protected] F. Biscetti  C. F. Porreca  F. Bertucci  F. Angelini  A. Gasbarrini  A. Flex Laboratory of Vascular Biology and Genetics, Catholic University School of Medicine, Rome, Italy G. Straface Vascular Medicine and Atherothrombosis Laboratory, Department of Experimental Medicine, Sapienza University of Rome, Polo Pontino, Italy L. Santoro Department of Internal Medicine, Complesso Integrato Columbus, School of Medicine, Rome, Italy

Methods The present study aimed to evaluate whether the OPG gene (TNFRSF11B) polymorphisms are involved in the development of peripheral arterial occlusive disease (PAOD) and critical limb ischemia (CLI) in patients with type 2 diabetes. This genetic association study included 402 diabetic patients (139 males and 263 females) with peripheral arterial occlusive disease and 567 diabetic subjects without peripheral arterial occlusive disease (208 males and 359 females). The T245G, T950C, and G1181C polymorphisms of the OPG gene were analyzed by polymerase chain reaction and restriction fragment length polymorphism. Results We found that the T245G, T950C, and G1181C gene polymorphisms of the OPG gene were significantly (27.9 vs. 12.2 %, P \ 0.01; 33.6 vs. 10.4 %, P \ 0.01 and 24.4 vs. 12.7 %, P \ 0.01, respectively) and independently (adjusted OR 4.97 (3.12–6.91), OR 7.02 (4.96–11.67), and OR 2.85 (1.95–4.02), respectively) associated with PAOD. We also found that these three polymorphisms act synergistically in patients with PAOD and are associated with different levels of risk for PAOD and CLI, depending on the number of high-risk genotypes carried concomitantly by a given individual. Conclusion The TNFRSF11B gene polymorphisms under study are associated with PAOD, and synergistic effects between these genotypes might be potential markers for the presence and severity of atherosclerotic disorders. Keywords TNFRSF11B gene polymorphisms  Atherosclerosis  PAOD  Type 2 diabetes

Introduction Atherosclerosis is a progressive process affecting multiple arteries. The pathophysiology process behind atherosclerosis

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is complex and involves the accumulation of plaque and remodeling of the arteries. The atherosclerotic process is characterized by the interaction between chronic inflammation and altered immune function, as well as between genetic and environmental factors [1, 2]. Its clinical consequences, which include coronary artery disease (CAD), cerebrovascular disease, and peripheral arterial occlusive disease (PAOD), are potentially life-threatening [3]. Indeed, PAOD, which is characterized by atherosclerotic lesions in large vessels and disturbances at the microcirculatory level, may lead to critical ischemia of lower limbs and is significantly associated with increased risk of cardiovascular events, such as myocardial infarction and stroke [4]. Now, the risk of atherosclerotic disease is independent of, and so additive to, other cardiovascular risk factors, and it is markedly increased among individuals with diabetes: In fact, it causes most of the death and disability in diabetic patients, especially in the ones affected by type 2 diabetes [5]. Patients with diabetes and non-diabetic glucose intolerance suffer from an increased risk of early carotid atherosclerosis compared with patients with normal glucose tolerance in both sexes [6]. Recently, Sesti et al. [7] show that irisin, a novel myokine, is inversely associated with insulin sensitivity and positively associated with carotid IMT in humans, suggesting either increased release by adipose/muscle tissue in response to deterioration of insulin sensitivity or a compensatory increase in irisin to overcome an underlying irisin resistance. Serum OPG levels were significantly correlated with coronary artery calcification in asymptomatic Korean patients with T2DM, suggesting that arterial stiffness, as determined by Brachial-ankle PWV, may predict the extent of coronary calcification by multidetector computed tomography [8]. Moreover, several clinical and basic science studies conducted in the last few years have demonstrated that a protein system, RANK/RANKL/OPG, involved in the metabolism of the bone tissue, plays an active role in vascular pathology, including atherogenesis and arterial calcification [9, 10]. Osteoprotegerin (OPG), also known as the osteoclastogenesis inhibitory factor, is a member of the tumor necrosis factor receptor superfamily of cytokines [11]. OPG inhibits the production of osteoclasts via blocking the differentiation of macrophages, and it also inhibits the function of differentiated osteoclasts, thereby preventing bone resorption. OPG is thought to represent a decoy receptor for RANKL, preventing binding of this factor to RANK [12]. Clinically, OPG may play a role in the formation of osteoporosis [13], inflammatory bone diseases [14], and also multiple myeloma and malignant bone resorption [15], while genetic mutations of OPG lead to forms of Paget’s disease [16]. In addition to its role in the skeletal system, OPG may have a role in the formation of vascular disease. OPG-deficient mice exhibit severe osteoporosis and vascular calcification of the aorta and renal

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arteries [17]. This phenotype can be prevented by delivery of recombinant OPG or transgenic overexpression of OPG [18]. Increased systemic and myocardial expression of members of the OPG/RANKL/RANK system has been observed in both clinical and experimental heart failure, suggesting a role for known mediators of bone homeostasis in the pathogenesis of heart failure [19]. Elevated serum OPG concentrations have been found to correlate with the severity of peripheral artery disease [10] and heart failure [19], as well as with symptomatic carotid stenosis [20], unstable angina [21], vulnerable carotid plaques [22], and acute myocardial infarction [23] compared with controls with stable atherosclerosis. Given the relevance of this finding, we focused on the genetic polymorphisms that have been identified in the OPG gene: The clinical relevance of these SNPs is based on the fact that plasma levels and/or functional activity may be strongly influenced by these gene variants. Recently, our group demonstrated that the T245G, T950C, and G1181C polymorphisms of the OPG gene were associated with a median OPG protein concentration that was statistically higher in patients with internal carotid artery stenosis than in controls [22]. Therefore, the purposes of the present study were to determine whether the T245G (rs 3134069), T950C (rs 2073617), and G1181C (rs 2073618) polymorphisms of the OPG gene are associated in the development of peripheral arterial occlusive disease and critical limb ischemia in patients with type 2 diabetes.

Subjects and methods Subjects Patients and controls were recruited among subjects consecutively admitted to the Department of Medicine of the A. Gemelli University Hospital of Rome, Italy, and to the Department of Medicine of the St M. Goretti Hospital, Latina (Italy), from January 1, 2011, to May 31, 2014. Diabetic subjects who had a past history of critical limb ischemia and have survived this event were enlisted in a retrospective study, in the group of patients with peripheral arterial disease (PAOD). Inclusion criteria for the PAOD group were Caucasian race and presence of PAOD at Fontaine’s stage II, III, or IV. Diagnosis of PAOD was performed in accordance with the criteria established by the Ad Hoc Committee on Reporting Standards of the Society for Vascular Surgery and the International Society for Cardiovascular Surgery [24]. All patients had an ankle/ arm pressure index lower than 0.8 and underwent bilateral high-resolution B-mode ultrasonography evaluation (EcocolorDoppler Acuson 128XP/10, Acuson, Mountain View,

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CA, USA, with an 4 MHz transducer). Severity of PAOD was defined according to the Fontaine’s staging system: Patients were considered affected by stage II when they presented intermittent claudication, by stage III when they presented rest pain, and by stage IV when ischemic trophic lesions of the lower limbs were present. According to recommendations of the TransAtlantic Inter-Society Consensus on the Management of Peripheral Arterial Disease, patients with chronic ischemic rest pain, ulcers, or gangrene attributable to objectively proven PAOD were considered affected by critical limb ischemia (CLI) [25]. Diabetic individuals (n = 567), attending the same Departments of Medicine, matched for age and gender, with an ankle/arm pressure index C1 and normal findings at bilateral high-resolution B-mode ultrasonography evaluation were recruited as controls. Subjects without peripheral occlusive disease (WPAOD) had no relationship with cases and no family history of PAOD. Exclusion criteria from the study were atrial fibrillation, other major sources of cardio-embolism, coagulation disorders, cancer (current or previous), chronic inflammatory and infectious diseases, and autoimmune diseases. All subjects were of European descent, coming from central and southern Italy. Diabetes mellitus was determined by the presence of an existing diagnosis, fasting blood glucose [126 mg/dL, glycohemoglobin A1c [5.8 %, or use of antidiabetic medication or insulin. For all individuals enrolled in the study, a complete medical history was collected and included smoking habits, coronary artery disease, hypertension, hypercholesterolemia, diabetes duration, and drug treatment. Hypertension was defined as a systolic blood pressure [130 mm Hg, a diastolic blood pressure [85 mm Hg, or current treatment with an antihypertensive drug. Hypercholesterolemia was defined as either a need for hypolipidemic drugs or total plasma cholesterol level [5.18 mmol/L. Approval for this study was provided by the ethics committees of the A. Gemelli University Hospital of Rome and St M. Goretti Hospital, Latina (Italy). Informed consent was obtained from participating patients. SNP genotyping Samples of DNA were extracted from peripheral blood by standard procedures and assayed by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) for the detection of OPG T950C, T245G, and G1181C gene polymorphisms, as previously described. Genotyping of the 950 T ? C OPG promoter polymorphism was performed by PCR amplification of the OPG promoter sequence with oligonucleotide primers 50 TGCGTCCGGATCTTGGCTGGATCGG-30 (sense) and 50 -GGGCGCGGCGGGCGCGCCCAGGGACTTACCAC

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GAGCGCGCAGCACAGCAA-30 (antisense); PCR amplifications were carried out in a total volume of 30 ll with a reaction mixture containing 1.5 ng genomic DNA, 10 mM Tris–HCl (pH 8.3), 2 mM MgCl2, 50 mM KCl, 200 lM of each deoxy-NTP, 10 pmol of each primer, and 1 U Platinum Taq DNA polymerase (Invitrogen Life Technologies, Karlsruhe, Germany). The PCR amplification conditions included an initial denaturation at 94 C for 3 min, followed by 30 cycles with denaturation at 94 C for 30 s, annealing at 62 C for 30 s, and extension at 72 C for 2 min, followed by a final extension step at 72 C for 10 min. Afterward, a short denaturation/renaturation program was performed that consisted of 5 min at 95 C, 5 min at 65 C, 5 min at 37 C, and final cooling to 4 C. After PCR amplification, 5 ll of PCR product was digested by restriction endonuclease with 3 U HincII (New England Biolabs, Frankfurt, Germany) for 16 h at 37 C and subsequently analyzed on a 3 % agarose gel and visualized by ethidium bromide staining. The 570-bp PCR product is cleaved into 288- and 282-bp fragments only in the presence of a C nucleotide at position 950. Genotyping of the G1181C OPG exon 1 polymorphism was performed using a mis-matched oligonucleotide approach. A 570-bp fragment was amplified with primers 50 -TGCGTCCGGATCTTGGCTGG-ATCGG-30 (sense) and 50 -GGGCGCGG-CGGGCGCGCCCAGGGACTTACCACGA-GCGCGCAGCACAGCTA-30 (antisense), containing a T instead of an A nucleotide two bases before the 30 end that corresponds to the third base of codon 3 that encodes lysine in exon 1 of the OPG gene, thereby introducing an artificial XspI restriction site in the presence of the mutant allele. The PCR mixture (30 ll) contained genomic DNA (100 ng), 1 9 PCR buffer, 0.2 mmol/l each of the four deoxyribonucleotides, 1.0–2.5 mmol/l MgCl2, 0.42 lmol/l each of the two oligonucleotide primers, and 0.6 unit of AmpliTaq Gold polymerase (Applied Biosystems, Foster City, CA). Cycling conditions consisted of an initial 12 min at 95 C, followed by 35 cycles of 60 s at 94 C, 30 s at 56 C, and 60 s at 72 C, and finally 7 min at 72 C. After PCR amplification, 5 ll of PCR product was digested with 3 units XspI (Cambrex Bio Science, Apen, Germany) for 16 h and subsequently analyzed on a 3 % agarose gel and visualized by ethidium bromide staining. In the presence of a C nucleotide at position 1181, the 570-bp PCR product was cleaved into 522- and 48-bp fragments, respectively. Genotyping of the T245G OPG promoter polymorphism was performed by amplification of a 271-bp fragment with oligonucleotide primers 50 -CGA ACC CTA GAG CAA AGT GC-30 (sense) and 50 -TGT CTG ATT GGC CCT AAA GC-30 (antisense). The PCR mixture (30 ll) contained genomic DNA (100 ng), 1 9 PCR buffer, 0.2 mmol/l each of the four deoxyribonucleotides, 1.0–2.5 mmol/l MgCl2,

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0.42 lmol/l each of the two oligonucleotide primers, and 0.6 unit of AmpliTaq Gold polymerase (Applied Biosystems). Cycling conditions consisted of an initial 12 min at 95 C, followed by 35 cycles of 60 s at 94 C, 30 s at 56 C, and 60 s at 72 C, and finally, 7 min at 72 C. After PCR amplification, 5 ll of PCR product was digested with 3 units HinfI restriction endonuclease (New England Biolabs, Beverly, MA) for 16 h and subsequently analyzed on a 3 % agarose gel and visualized by ethidium bromide staining [26]. Statistical analysis Demographic and clinical data between groups were compared by chi-squared test and by the t test. Genotype frequency was compared by the chi-squared test. Hardy– Weinberg equilibrium was assessed, in PAOD patients and in controls, by a chi-squared test or Fisher’s exact test as appropriate, and statistical significance was established at P \ 0.05. Linkage disequilibrium calculation was performed using the software Haploview 4.1 for all pairwise SNP combinations. In order to evaluate the best genetic model, the following approach was chosen. First of all OR1 and OR2 were computed for the three SNPs: • • •

OPG T245G, TG versus TT (OR1); GG versus TT (OR2) OPG T950C, TC versus TT (OR1); CC versus TT (OR2) OPG G1181C, GC versus GG (OR1); CC versus GG (OR2)

According to the following criteria, the best genetic model was identified for each SNPs [27]: • •

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duration (P = 0.082), hypercholesterolemia (P = 0.164), and CAD (P = 0.374). In contrast, hypertension (P = 0.029) and current smoking (P = 0.023) were significantly more frequent in diabetic patients with PAOD than in diabetic subjects WPAOD. Table 2 shows the genotypic distribution of the T245G, T950C, and G1181C gene polymorphisms. Genetic distribution of all SNPs was in Hardy–Weinberg equilibrium. These SNPs are not in linkage disequilibrium. Of the 402 patients with PAOD, the genotype distribution of the T245G gene polymorphism was 112 GG, 189 TG, and 101 TT, which was significantly different to what observed in the 567 subjects WPAOD (69 GG, 265 TG, and 233 TT). The frequency of the GG genotype in patients with PAOD (27.9 %) was significantly higher than in those WPAOD (12.2 %; P \ 0.001). Similarly, the genotype distribution of the T950C polymorphism was 135 CC, 196 TC, and 71 TT in patients with PAOD, which was significantly different to that observed in the patients WPAOD (59 CC, 253 TC, and 255 TT), and the frequency of the CC genotype in patients with PAOD (33.6 %) was significantly higher than in those WPAOD (10.4 %; P \ 0.001). In addition, the genotype distribution of the G1181C polymorphism was 98 CC, 198 GC, and 106 GG in patients with PAOD, which was significantly different to that observed in the subjects WPAOD (72 CC, 241 GC, and 254 GG). The frequency of the CC genotype in patients with PAOD (24.4 %) was significantly higher than in those WPAOD (12.7 %; P \ 0.001; Table 2).

Table 1 Demographic and clinical data in subjects with PAOD and in subjects WPAOD

Recessive model: if OR2 = 1 and OR1 = 1 Dominant model: if OR2 = OR1 = 1,

A multivariate analysis was carried out in order to investigate the role of each of the three SNPs using the best genetic model and a backward stepwise approach; adjusted ORs with 95 %CI were reported in the tables. All analyses were performed by using STATA version 11.0 for Windows (Statistics/Data Analysis, Stata Corporation, College Station, Texas, USA). Statistical significance was established at P \ 0.05. Bonferroni correction was used to adjust P values for multiple testing.

PAOD (n = 402)

WPAOD (n = 567)

P

Age (years ± SD)

70.4 ± 3.9

71.1 ± 4.4

0.854a

Male:female ratio

139:263

208:359

0.327b

Diabetes duration (years ± SD)

12.4 ± 4.8

11.9 ± 3.9

0.082a

Hypertension, n (%)

245 (60.9)

305 (53.8)

0.029b

Hypercholesterolemia, n (%)

223 (55.5)

306 (54.0)

0.164b

CAD, n (%)

177 (44.0)

239 (42.1)

0.374b

Smoking (current), n (%)

151 (37.6)

177 (31.2)

0.023b

Diet only, n (%)

45 (11.2)

62 (10.9)

0.897b

Oral agents, n (%)

219 (54.5)

314 (55.4)

0.287b

Incidence of insulin therapy

138 (34.3)

191 (33.7)

0.246b

Treatment

Results Table 1 shows the demographic and clinical data of patients with and without PAOD. In univariate correlations, there was no significant difference between the groups in terms of age (P = 0.854), sex (P = 0.327), diabetes

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SD standard deviation, CAD coronary artery diseases a

Statistical test performed with Student’s t test

b

Chi-squared test for categorical values

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Table 2 Genotype distribution in patients with PAOD and WPAOD

PAOD (n = 402)

WPAOD (n = 567)

Pa

Adjusted ORb (95 % CI)

\0.001

5.15 (3.19–7.01)

\0.001

7.36 (5.12–11.88)

\0.001

3.07 (2.76–4.46)

OPG Genotypes SNP of T245G (rs 3134069) GG

112 (27.9 %)

69 (12.2 %)

TG

189 (47.0 %)

265 (46.7 %)

TT

101 (25.1 %)

233 (41.1 %)

SNP of T950C (rs 2073617)

a

Chi-squared test for categorical values

b

Odds ratios (ORs) adjusted for age, sex, presence of hypertension, and smoke

CC

135 (33.6 %)

59 (10.4 %)

TC

196 (48.7 %)

253 (44.6 %)

TT

71 (17.7 %)

255 (45.0 %)

CC

98 (24.4 %)

72 (12.7 %)

GC

198 (49.2 %)

241 (42.5 %)

GG

106 (26.4 %)

254 (44.8 %)

SNP of G1181C (rs 2073618)

Following these observations, we used a logistic regression analysis to evaluate whether these gene variations were independent variables associated with PAOD and we found, after adjusting for relevant confounding variables (age, sex, hypertension, and smoking), that the GG, CC, and CC genotypes of the T245G, T950C, and G1181C gene polymorphisms were independently associated with PAOD (adjusted OR 5.15 [3.19–7.01], OR 7.36 [5.12–11.88], and OR 3.07 [2.76–4.46], respectively; Table 2). Another step of our study was to evaluate whether the combined effects of these gene variations influenced the risk of PAOD: The studied population was stratified according to the number of high-risk gene polymorphisms carried concomitantly by a given individual, as shown in Table 3. Group 0 was composed of individuals with no high-risk genotypes (n = 675) and served as the reference group; group 1 was composed of individuals carrying one high-risk genotype (n = 159); group 2 consisted of subjects with two high-risk genotypes (n = 108); and group 3 was composed of subjects concomitantly carrying three high-risk genotypes (n = 27). Among group 0 subjects, the frequency of PAOD was 34.1 %. Interestingly, the frequency of PAOD progressively increased in groups 1, 2, and 3 (40.9, 77.8, and 85.2 %, respectively). These frequencies were significantly higher than those in the referent group (group 1 vs. group 0, P = 0.093; group 2 vs. group 0, P \ 0.001; and group 3 vs. group 0, P \ 0.001; Table 3). Further, the OR for PAOD, calculated after adjusting for age, sex, presence of hypertension, and smoking, increased progressively with the increasing number of pro-inflammatory high-risk genotypes: The risk of PAOD was 10.56 (95 % CI 5.7–17.1) in individuals with

two high-risk genotypes and increased to 45.65 (95 % CI 13.4–167.2) in individuals with three high-risk genotypes (Table 3). The final step of our study was to investigate whether the concomitant presence of multiple high-risk genotypes was associated with the severity of PAOD. Therefore, the frequency of CLI among PAOD patients was evaluated according to the number of high-risk genotypes (Table 4). Also in this case, the frequency of CLI increased progressively from subjects with 0 gene variation (32.6 %) to individuals with 1 (46.2 %), 2 (54.8 %), or 3 (87.0 %) proinflammatory mutations. Adjusted ORs for CLI were 2.98 (95 % CI 1.4–4.6), 9.79 (95 % CI 5.5–16.1), and 40.89 (95 % CI 11.9–169.9) in PAOD patients with 1, 2, and 3 high-risk genotypes, respectively.

Discussion The current study is the first report showing that rs 3134069, rs 2073617, and rs 2073618 variant genotypes of the OPG gene are significantly and independently associated with the increased risk of peripheral arterial occlusive disease in diabetic patients. A major finding of this study is the discovery that these three gene polymorphisms act synergistically in patients with peripheral arterial occlusive disease and determine the genetic profiles that are associated with different levels of risk for PAOD (10.56 and 45.65 in diabetic subjects with two or three high-risk genotypes; Table 3) and CLI (2.98, 9.79 and 40.89 in diabetic subjects with PAOD with one, two, or three highrisk genotypes; Table 4), depending on the number of highrisk genotypes concomitantly carried by a given individual.

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Table 3 Risk of PAOD according to the high-risk genotype numbers Number of high-risk genotypes

PAOD (n = 402)

WPAOD (n = 567)

Pa

OR (95 % CI)b

0 (n = 675)

230 (34.1 %)

445 (65.9 %)

Referent

Reference

1 (n = 159)

65 (40.9 %)

94 (59.1 %)

0.093

2.01 (1.1–3.6)

2 (n = 108)

84 (77.8 %)

24 (22.2 %)

\0.001

10.56 (5.7–17.1)

3 (n = 27)

23 (85.2 %)

4 (14.8 %)

\0.001

45.65 (13.4–167.2)

a

Chi-squared test for categorical values

b

Odds ratios (ORs) adjusted for age, sex, presence of hypertension, and smoke

Table 4 Severity of PAOD according to the high-risk genotypes numbers Number of high-risk genotypes

Fontaine’s II (n = 231)

CLI (n = 171)

Pa

OR (95 % CI)b

0 (n = 230)

155 (67.4 %)

75 (32.6 %)

Referent

Reference

1 (n = 65)

35 (53.8 %)

30 (46.2 %)

0.03

2.98 (1.4–4.6)

2 (n = 84)

38 (45.2 %)

46 (54.8 %)

\0.001

9.79 (5.5–16.1)

3 (n = 23)

3 (13.0 %)

20 (87.0 %)

\0.001

40.89 (11.9–169.9)

a

Chi-squared test for categorical values

b

Odds ratios (ORs) adjusted for age, sex, presence of hypertension, and smoke

This is consistent with the concept that the individual chances of presenting an atherosclerotic-related disease might be affected by a susceptibility profile that results from functional interactions between a number of different genes. The biological significance of the associations presented in this study is based on the fact that the gene mutations that we investigated are functionally important [22]. Vascular calcification, a type of ectopic soft tissue mineralization, increases the risk of cardiovascular mortality. Recent studies suggest pro-atherosclerotic roles of OPG including anti-calcification function [28, 29]. Vascular calcification is not only pro-atherosclerotic, but also a physiologic defense mechanism against active, progressive atherosclerotic disease [30]. The regulatory mechanism of OPG on vascular calcification could promote the progression and instability of atherosclerosis [29]. OPG also could contribute to the development and progression of atherosclerosis by promoting inflammatory responses in T cells and dendritic cells, promoting endothelial cell adhesion, impairing cell proliferation and apoptosis of smooth muscle cells, inducing chemotactic properties in monocytes, and via MMP and interleukin-6 production [28], [29–32]. Arterial wall mineralization is estimated to be present in the vast majority of patients affected by cardiovascular disease (CVD) [33]. In particular, patients with type II diabetes mellitus are an additional population affected by elevated vascular calcification [34]. Given the dramatic rise in diabetes mellitus and metabolic syndrome in the world, increased frequencies of vascular calcification and CVD are expected in the coming decades. In the aorta, intimal

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and medial calcification promotes congestive heart failure by compromising vessel compliance and elasticity. Intimal calcification is positively correlated with atherosclerotic plaque burden, increased risk of myocardial infarction [35], plaque instability [36], and stroke [25] and is an independent risk factor for cardiovascular mortality in the general population [37, 38]. Functional studies in vitro, as well as in vivo, indicate that osteoprotegerin (OPG) is a major regulator of bone remodeling by blocking receptor activator NF-jB ligand (RANKL) binding to its own cell surface receptor RANK, resulting in the inhibition of RANKL-dependent osteoclast formation [39]. More recently, OPG has been hypothesized to modulate vascular functions; however, its role in mediating atherosclerosis is controversial. Epidemiological data in CVD patients indicate that OPG serum levels are associated with several inflammatory markers, MI events, and calcium scores, suggesting that OPG may be causative for CVD. An opposite interpretation is that the rise in OPG levels may be an adaptive response to curb the harmful effects of RANKL and tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL), the other known ligands for OPG [40, 41]. Up to the best of our knowledge, there are no studies about the genetic variants and the RNA stability. In one of our previous studies, we found, for the first time, that the GG genotype of the T245G gene polymorphism, the CC genotype of the T950C gene polymorphism, and the CC variant genotype of the G1181C gene polymorphism were correlated with higher serum OPG levels [22]. Further studies are needed to understand the effects of these

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polymorphisms on either OPG mRNA or protein to prove that they interfere with the protein expression or function. This study has some potential limitations. It was a case– control study; therefore, a recruitment and survival bias cannot be excluded. Our data were obtained from a cohort of diabetics of European descent and includes subjects with other cardiovascular diseases; therefore, comorbidity might represent a confounding factor, and the generalization of our findings to other age groups or ethnicities is unclear. The size of the studied population is relatively small and could lead to false positive results; then, our findings need to be confirmed in larger samples and should also be tested in groups of different ethnic origins. Some of the genes investigated in this study present more than one single nucleotide polymorphisms, and it might be interesting to evaluate whether other genetic haplotypes play a role in subjects with PAOD. In conclusion, the present study identifies genetic variants of OPG as an independent risk factor for peripheral arterial occlusive disease. These data further suggest a role for OPG as a reliable biomarker in cardiac and vascular disease. Although the mechanisms linking OPG and vascular disease require further studies, the associations between OPG and PAOD demonstrated in this study support further investigation to clarify a possible role of OPG as a biomarker to identify patients with, or at risk of, peripheral arterial disease. Conflict of interest Federico Biscetti, Carlo Filippo Porreca, Flavio Bertucci, Giuseppe Straface, Angelo Santoliquido, Paolo Tondi, Flavia Angelini, Dario Pitocco, Luca Santoro, Antonio Gasbarrini, Raffaele Landolfi, and Andrea Flex declare that they have no conflict of interest. Human and Animal Rights disclosure All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Informed consent disclosure Informed consent was obtained from all patients for being included in the study.

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