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Abstract

Objectives:

Adiponectin has insulin-sensitizing, anti-inflammatory and anti-atherogenic properties. There are few and controversial data on the role of ADIPOQ variants in heart failure (HF) pathogenesis. We planned this large association study to investigate the potential association of four selected ADIPOQ polymorphisms with HF in a population of Italian origin.

Methods:

We genotyped 1173 cases with symptomatic HF and 1136 controls for alleles rs17300539, rs266729, rs1501299 and rs2241766. Cases were patients enrolled in the GISSI-Heart Failure genetic sub-study, with a long-term follow up (median 3.9 years). Controls were blood donors with no history of diabetes or cardiovascular disease (CVD). Genotype and allele frequencies of the four single nucleotide polymorphisms (SNPs) were compared between the two groups.

Results:

Clinical characteristics were significantly different between HF patients and controls. No significant differences were reported in the allelic and genotypic distribution, with the exception of rs266729 G allele, which showed a significant association with an increased risk of HF [odds ratio (OR) = 1.26; 95% confidence interval (CI) = 1.07–1.48; p = 0.006). We divided the GISSI-HF population according to HF etiology (ischemic and nonischemic) and presence of diabetes. For rs266729 G allele, a significant association with HF was confirmed in both ischemic (OR = 1.29; 95% CI = 1.06–1.56; p = 0.009) and nonischemic patients (OR = 1.2; 95% CI = 1.02–1.42; p = 0.03) as well as in nondiabetic patients (OR = 1.25; 95% CI = 1.05–1.49; p = 0.012). rs2241766 G allele showed a significant reduction of risk of HF in nonischemic (OR = 0.77; 95% CI = 0.62–0.95; p = 0.02) and diabetic patients (OR = 0.62; 95% CI = 0.45–0.84; p = 0.0025).

Conclusions:

We confirm the association between rs266729 G allele and an increased risk of HF and between rs2241766 G allele and decreased risk of HF. Our study extends the knowledge on the influence of ADIPOQ variants on CVD.

Keywords

adiponectin chronic heart failure diabetes etiology single nucleotide polymorphisms

Introduction

Adiponectin is a cytokine characterized by an adipose tissue-specific expression. It is mainly produced by adipocytes [Maeda et al. 1996] and secreted in the blood serum, where it circulates abundantly in two forms: a high molecular weight (HMW) complex of 12–18 subunits and a low molecular weight (LMW) dimer of trimers. The HMW isoform seems to bind the AdipoR1, which is mainly expressed in skeletal muscle, and to AdipoR2, expressed in the liver to act the insulin-sensitizing and vasoprotective roles [Fruebis et al. 2001].

Adiponectin, also known as ApM1 (adipose most abundant transcript 1), Acrp30 (adipocyte complement-related protein 30), Gbp28 (gelatin-binding protein 28) or AdipoQ, consists of 244 amino acids organized in three different domains: a signal sequence with a variable region domain; a collagen triple helix; and a globular head domain. This protein is encoded by ADIPOQ gene (Gene ID 9370), which consists of three exons spanning 16 kb and mapped on chromosome 3q27 in a region linked to type 2 diabetes (T2D) and metabolic syndrome [Takahashi et al. 2002]. In Europeans, this gene is organized in two linkage disequilibrium (LD) blocks [D′ >0.8 for pairs of consecutive single nucleotide polymorphisms (SNPs)] with a boundary point in intron 1 [Heid et al. 2006].

Few and controversial data have been reported about the role of ADIPOQ gene variants in heart failure (HF) pathogenesis. Several studies correlate serum adiponectin levels with the presence of potentially regulatory SNPs within the ADIPOQ gene. These variants probably influence the functional role played by the circulating protein in the pathogenesis of the major metabolic disorders related to insulin resistance, such as T2D and/or obesity and conventional risk factors, including total cholesterol (TC), low density lipoprotein (LDL), triglycerides (TG), high density lipoprotein (HDL) and LDL particle size [Gable et al. 2006].

The ADIPOQ gene is polymorphic and in particular two promoter SNPs, rs17300539 (-11391 G/A) and rs266729 (-11377 C/G), have been reported to be significantly related to serum adiponectin levels [Vasseur et al. 2005; Bouatia-Naji et al. 2006]. Other two SNPs show a minor correlation: rs2241766 in exon 2 (G/T, G45G) and rs1501299 in intron 2 (+276 A/C) [Zacharova et al. 2005; Schwarz et al. 2006]. rs17300539 (-11391) and rs266729 (-11377) lie in the first LD block, whereas rs2241766 (+45) and rs1501299 (+276) map in the second one [Heid et al. 2006].

Reduction of adiponectin levels is commonly observed in patients with coronary artery disease (CAD) and increases the risk of developing myocardial infarction and T2D [Hotta et al. 2000; Kumada et al. 2003]. However, subjects with chronic heart failure (CHF) show high concentrations of circulating protein and functional resistance to adiponectin in skeletal muscles [van Berendoncks et al. 2010].

To clarify the reported issue, we planned a large case-control study in a population of 1173 HF patients and 1136 matched controls with the aim of investigating the association of the selected SNPs in the ADIPOQ gene (rs17300539, rs266729, rs1501299 and rs2241766) with the occurrence of HF. We also explored the association of genotypes with HF in different subgroups of patients.

Methods

Study population

The GISSI Heart Failure Study (GISSI-HF) is a randomized, large-scale, double-blind, placebo-controlled trial with a long-term follow up (median 3.9 years), designed to assess the efficacy of two pharmacological agents never formally assessed in symptomatic HF in addition to recommended treatments [GISSI-HF Investigators 2008]. GISSI-HF study has a clinical database with detailed phenotype information, treatment history and genomic DNA bank.

The population recruited for this study is a subset of 1173 (with available blood samples) out of 6975 Italian subjects of the main study with symptomatic HF already assessed in our previous work [Masson et al. 2011]. It consisted of: men and women (men: 78.9%); 18 years old or older (>70 years: 47.7%); with symptomatic HF, classified as New York Heart Association (NYHA) functional classes II–IV (NYHA II: 68.7%; NYHA III: 29.6%; NYHA IV: 1.7%); and left ventricular ejection fraction (LVEF) measured within 3 months before enrolment (<40%: 89.3%). The etiology, nonischemic and ischemic, of HF was also evaluated (nonischemic: 50.3%). This population is homogeneous for the genetic background with European ancestry.

The control population consisted of a group of 1136 Italian controls matched by sex, without history of CAD or T2D recruited among blood donors who have regular, routine checkups of their state of health.

All subjects provided written informed consent before the enrolment. The study was approved by the ethics committees of the hospitals participating in the GISSI-HF study and conforms with the principle expressed in the Declaration of Helsinki.

Genotyping

DNA was extracted from lymphocytes of peripheral anticoagulated blood (EDTA) samples using the salting out procedure, which exploits dehydration and precipitation with saturated NaCl solution. Polymerase chain reactions (PCRs) were carried out using the TaqMan Universal PCR Master Mix (Applied Biosystems, Foster City, CA, USA) and 10 ng of genomic DNA, according to the manufacturer’s instructions. All samples were genotyped for the investigated SNPs by allelic discrimination assay using an ABI 7900 sequence detection system. The fluorescent data files for each plate were analyzed using Sequence Detection System version 3.2 (Applied Biosystems). To ensure the quality of automatic allele calling, all samples were analyzed in two replicates.

Statistical methods

Continuous variables were compared among HF cases and controls using Student’s t-test, analysis of variance (ANOVA) or Kruskall–Wallis rank test as appropriate. Differences in percentages were assessed by the χ² test. For each SNP, a χ² test was performed to assess whether the observed genotype frequencies were in Hardy–Weinberg equilibrium among controls. Genotype and allele frequency distributions were compared between HF patients and controls. To quantify the association between each SNP genotype and the risk of HF, a logistic regression model was fitted including age, sex and BMI as covariates. An additive genetic model was tested and adopted in the analyses.

A p-value <0.013 was considered statistically significant to adjust for multiple testing across the four SNPs.

Haplotype frequencies for rs1501299, rs17300539, rs266729 and rs2241766 SNPs were estimated by the EM algorithm using UNPHASED 3.1 [Dudbridge, 2008]. Rare haplotypes (frequency <0.05) were ignored. Haplotype frequency distribution was tested for association with risk of HF.

As adiponectin has been found to correlate with insulin resistance, T2D and risk of CAD, the same approach was carried out considering two subgroups: the etiology of HF and diabetes.

For all comparisons of subgroup analyses, the actual p-value is reported. This avoids having to declare whether the difference is ‘statistically significant’ or not according to a prespecified cutoff value due to the explorative and hypothesis-generating nature of the subgroups analysis.

Results

Study population

Two populations, consisting of 1136 controls and 1173 HF patients were recruited. Age, sex, body mass index (BMI), TC, systolic and diastolic blood pressure (BP) are reported in Table 1 for cases and controls. The HF patients are older than the controls (mean: 67 versus 55.8 years) and are more represented in the category of BMI <22 (10.6% versus 7.2%) and ≥30 (21.6% versus 17%). TC levels, systolic and diastolic BP are lower in the cases, probably because the HF patients underwent pharmacological treatment.

Table 1.

Main clinical characteristics of HF patients and controls.

		HF patients (n = 1173)	Controls (n = 1136)	p-value
Sex	% male	80.5	83.3	0.08*
Age (years)	Mean (SD)	67 (10.8)	55.8 (7.6)	<0.0001**
BMI <22 (kg/m²)	%	10.6	7.2	0.0003*
BMI ≥22 to <25 (kg/m²)	%	24.4	27.4
BMI ≥25 to <30 (kg/m²)	%	43.5	48.4
BMI ≥30 (kg/m²)	%	21.6	17
TC (mg/dl)	Mean (SD)	189.3 (41.7)	212.2 (34.6)	<0.0001**
Systolic BP (mmHg)	Mean (SD)	124.4 (19.5)	130.3 (14)	<0.0001**
Diastolic BP (mmHg)	Mean (SD)	75.9 (10.9)	82.7 (7.6)	<0.0001**

χ² test: Sex and BMI; **t-test: age, TC, systolic BP and diastolic BP.

BMI, body mass index; BP, blood pressure; HF, heart failure; SD, standard deviation; TC, total cholesterol.

Polymorphisms description in cases and controls

The characteristics of the selected SNPs and allelic frequencies are reported in Table 2. Among the control group, rs17300539, rs266729 and rs2241766 are in Hardy–Weinberg equilibrium, while only rs1501299 does not meet Hardy–Weinberg equilibrium (χ² = 4.38; p = 0.04). Genotyping was complete for all subjects. Genotypic and allelic frequencies between the two groups are reported in Table 3.

Table 2.

The four SNPs in the study population.

SNP ID number and position	Localization	Hardy–Weinberg equilibrium X² test, p value	Minor allele	Major allele	Minor allele frequency	Minor allele frequency (HapMap-CEU)
rs17300539 (-11391)	5’ UTR	0.46	A	G	0.099	0.08
rs266729 (-11377)	5’UTR	0.86	G	C	0.21	0.3
rs1501299 (+276)	Intron 2	0.04	T	G	0.32	0.26
rs2241766 (+45)	Exon 2	0.07	G	T	0.17	0.13

ID, identifier; SNP, single nucleotide polymorphism HapMap-CEU: http://hapmap.ncbi.nlm.nih.gov.

Table 3.

Genotypic and allelic frequencies distribution in HF cases and controls.

		HF cases (n = 1173)		Controls (n = 1136)
		No. subjects	(%)	No. subjects	(%)
rs17300539 (-11391)	AAAG	13200	1.1117.05	9207	0.7918.22
	GG	960	81.84	920	80.99
	Minor allele (A)	226	9.6	225	9.9
rs266729 (-11377)	GGGC	74436	6.3137.17	51384	4.4933.8
	CC	663	56.52	701	61.71
	Minor allele (G)	584	24.9	486	21.4
rs1501299 (+276)	TTGT	130499	11.0842.54	132464	11.6240.85
	GG	544	46.38	540	47.54
	Minor allele (T)	759	32.3	728	32.0
rs2241766 (+45)	GGGT	26294	2.2225.06	41301	3.6126.5
	TT	853	72.72	794	69.89
	Minor allele (G)	346	14.7	383	16.8

HF, heart failure.

Association of adiponectin polymorphisms and HF

Univariate and multivariable analyses of the SNPs in cases and controls are reported in Table 4: rs266729 G allele is associated with an increased risk of HF (OR 1.22; 95% CI = 1.06–1.40, p = 0.005). The association is confirmed in the multivariable analysis (OR 1.26: 95% CI = (1.07–1.48), p = 0.006). rs17300539, rs2241766 and rs1501299 did not show association with HF.

Table 4.

Association between ADIPOQ SNPs and HF.

SNP	Unadjusted OR (95% CI)	p value	Adjusted OR (95% CI)*	p value
rs17300539 ( -11391)	0.97 (0.80–1.18)	0.75	0.93 (0.74–1.17)	0.53
rs266729 (-11377)	1.22 (1.06–1.40)	0.005	1.26 (1.07–1.48)	0.006
rs2241766 (+45)	0.86 (0.733–1.002)	0.053	0.84 (0.70–1.01)	0.06
rs1501299 (+276)	1.01 (0.90–1.14)	0.83	1.002 (0.87–1.16)	0.98

Adjustment for age, sex and body mass index by logistic regression analysis.

CI, confidence interval; HF, heart failure; OR, odds ratio; SNP, single nucleotide polymorphism.

Haplotype analysis

We performed a haplotype association analysis with HF (1173 cases and 1136 controls). The two SNPs rs266729 and rs2241766 in Hardy–Weinberg equilibrium among controls, with the lowest correlation coefficients (r² = 0.0081) and most likely not in LD, were tested for haplotype association. Haplotypes frequencies above the threshold of 0.05 in either cases or controls were considered. No statistically significant association was detected comparing low risk haplotypes with the higher risk haplotype (Table 5).

Table 5.

Haplotypes analysis for SNP rs266729 and rs2241766.

Haplotype	Case	Control	freq-Cases	freq-Controls	OR	95% Low	95% High
GG	54.67	52.03	0.0233	0.0229	1	1	1
GT	529.3	434	0.2256	0.191	1.161	0.6589	2.045
CG	291.3	331	0.1242	0.1457	0.8377	0.4642	1.512
CT	1471	1455	0.6269	0.6404	0.9619	0.572	1.618

Test of overall association p-value = 0.01.

OR, odds ratio.

Etiology: ischemic and nonischemic

The population recruited for this study consists of patients with clinical evidence of HF of any cause, categorized in two main classes of etiology: 603 HF patients had an ischemic etiology (51.4%) and 570 HF patients presented HF of nonischemic origin (that is, dilated or hypertrophic cardiomyopathy, hypertensive, alcoholic and so on).

Table 6 reports univariate and multivariable analysis of the SNPs in both cases groups of different etiology compared with controls. The association observed for rs266729 G allele and HF is confirmed, consistent in both subgroups (ischemic adjusted OR = 1.29, 95% CI = 1.06–1.56; p = 0.009; non ischemic adjusted OR = 1.2, 95% CI = 1.02–1.42; p = 0.03); whereas a trend of association of rs2241766 G allele was seen only in the nonischemic group (OR = 0.77, 95% CI = 0.62–0.95; p = 0.02). Both G alleles for rs266729 and rs2241766 were present in 9.47% of the nonischemic HF patients and 9.5% of the controls.

Table 6.

Association of adiponectin polymorphisms in subgroups of patients: ischemic, nonischemic aetiology of HF; diabetic and nondiabetic HF patients.

		Ischemic etiology versus controls	Nonischemic etiology versus controls	Diabetic versus controls	Nondiabetic versus controls
		(n = 603)	(n = 570)	(n = 306)	(n = 867)
rs17300539 (-11391)	unadjusted	0.99	0.95	0.99	0.96
	OR (95% CI)	(0.78–1.25)	(0.75–1.21)	(0.73–1.34)	(0.78–1.19)
	p value	0.91	0.69	0.94	0.73
	adjusted	0.95	0.91	0.99	0.92
	OR (95% CI)*	(0.73–1.25)	(0.70–1.18)	(0.69–1.42)	(0.72–1.18)
	p value	0.73	0.47	0.96	0.50
rs266729 (-11377)	unadjusted	1.23	1.2	1.31	1.18
	OR (95% CI)	(1.05–1.45)	(1.02–1.42)	(1.06–1.62)	(1.02–1.37)
	p value	0.01	0.03	0.01	0.002
	adjusted	1.29	1.2	1.27	1.25
	OR (95% CI)*	(1.06–1.56)	(1.02–1.42)	(0.99–1.64)	(1.05–1.49)
	p value	0.009	0.03	0.06	0.012
rs2241766 +45)	unadjusted	0.93	0.78	0.66	0.93
	OR (95% CI)	(0.77–1.12)	(0.64–0.95)	(0.5–0.86)	(0.79–1.10)
	p value	0.45	0.02	0.0021	0.41
	adjusted	0.93	0.77	0.62	0.92
	OR (95% CI)*	(0.75–1.15)	(0.62–0.95)	(0.45–0.84)	(0.76–1.12)
	p value	0.48	0.02	0.0025	0.41
rs1501299 (+276)	unadjusted	0.97	1.06	1.08	0.99
	OR (95% CI)	(0.84–1.12)	(0.92–1.23)	(0.90–1.30)	(0.87–1.13)
	p value	0.68	0.43	0.42	0.89
	adjusted	0.94	1.06	1.08	0.99
	OR (95% CI)*	(0.80–1.12)	(0.90–1.25)	(0.87–1.34)	(0.84–1.15)
	p value	0.50	0.51	0.49	0.86

Adjustment for age, sex and body mass index by logistic regression analysis

CI, confidence interval; HF, heart failure; OR, odds ratio.

Diabetes

Among the HF patients, 306 patients were diabetic (26% of HF cases) and 867 nondiabetic (74% of HF cases) patients. The presence of the four SNPs in these two groups was evaluated.

Univariate and multivariable analyses testing the association of the four SNPs in diabetic and nondiabetic HF patients were compared with controls (Table 6). In diabetics, univariate analysis confirms the association for rs266729 G allele (OR = 1.31, 95% CI = 1.06–1.62, p = 0.01) and rs2241766 G allele (OR = 0.66, 95% CI = 0.05–0.86, p = 0.0021). After adjustment for age, sex and BMI only rs2241766 confirms the univariate results (OR = 0.62, 95% CI = 0.45–0.84, p = 0.0025) and the presence of the G allele seems to have a protective effect on HF.

For the nondiabetic group, only rs266729 G allele shows a significant association both in univariate (OR = 1.18, 95% CI = 1.02–1.49, p = 0.002) and in multivariable (OR = 1.25, 95% CI = 1.05–1.49, p = 0.012) analysis.

To explain the protective role of rs2241766 in diabetic and nonischemic patients, considering that the ischemic etiology is more common (62.5%) in diabetics, we investigated whether the association was still present in the diabetic nonischemic as well as in the nondiabetic nonischemic patients. We confirmed a strong association only for the diabetic nonischemic patients (n = 115, OR = 0.48, 95%CI = 0.30–0.76, p = 0.002).

Discussion

Adiponectin is an adipocytes-derived protein with insulin-sensitizing, anti-inflammatory and anti-atherogenic properties. Several studies have reported the association between adiponectin levels and risk of CVD. The cardioprotection of adiponectin and the influence of its plasma concentration on obesity, T2D, dyslipidemia and metabolic syndrome have been widely investigated. Hotta and colleagues reported a relatively low adiponectin plasma concentration in subjects affected by these kinds of disorders [Hotta et al. 2000].

The ADIPOQ gene has been considered a candidate gene in many genome-wide association studies [Ling et al. 2009; Heid et al. 2010; Jee et al. 2010], in which SNPs have been reported to correlate with different circulating adiponectin levels. Among these variants, rs17300539 (-11391 G>A), rs266729 (-11377 C>G), rs2241766 (+45 T>G) and rs1501299 (+276 G>T) have been extensively investigated.

In a previous study conducted by our group in a CHF population [Masson et al. 2011], we investigated the influence of the four SNPs and diabetes on circulating adiponectin levels and on their association with mortality. We demonstrated that diabetes and ADIPOQ genetic variants influence plasma levels. Nevertheless, only circulating levels, not genetic variants, were associated with a poor prognosis.

In the present case-control study we investigated in the same large HF cohort and in a randomly selected general population free of disease, the presence of rs17300539 (-11391 G>A), rs266729 (-11377 C>G), rs2241766 (+45 T>G) and rs1501299 (+276 G>T) and their potential role in the occurrence of HF disease. Significant differences were observed between the HF and control subjects in terms of age, BMI, TC and BP (both systolic and diastolic).

Concerning the association between ADIPOQ gene variants and the HF, rs266729 (-11377 C>G) G allele showed a statistical significance both in univariate and multivariable analysis (adjusted for age, sex and BMI).

The haplotype analysis, which considered the only significant SNPs (rs266729 and rs2241766) and compared low risk haplotypes with the higher risk haplotype, did not show statistically significant association with HF.

We performed a subgroup analysis on the basis of HF etiology (ischemic and nonischemic) and on the basis of diabetic status (HF diabetic and HF nondiabetic). rs266729 G allele correlates with HF in both classes of etiology as well as in nondiabetic patients. It shows a significant univariate association in the diabetics group that was lost after adjustment: these results suggest that association of rs266729 G allele with HF is independent from the etiology as well as from diabetic status. Among the other three SNPs, only rs2241766 (+45 T>G) G allele showed a statistical significance in the nonischemic and diabetic groups in univariate and multivariable analysis (Table 6).

Two recent meta-analyses focused on the role of ADIPOQ polymorphisms in CVD [Zhang et al. 2012; Yang et al. 2012], and both did not consider rs17300539. Zhang and colleagues reported a clear association between rs2241766G, rs266729G alleles and an increased CVD risk. For rs1501299, they showed that the T allele associates with a reduced risk. In the second meta-analysis, Yang and colleagues confirmed these results with the exception of the rs2241766 variant. They found an increased and reduced CAD risk association for rs266729 and rs1501299, respectively. Our results are partly consistent with the study by the Zhang group, even if we did not find any association between rs1501299 and HF.

The authors of the two aforementioned meta-analyses suggested the necessity of other studies to improve the inconclusive data about these genetic variations and CVD association. Taken together the results and the sample size of the present study, we could give an answer to the open question. In our study the strongest results concerned rs266729, associated with an increased risk of HF, consistently confirmed across the subgroups investigated. We observed an association between rs2241766 and the reduced risk of HF, which was confirmed only in the nonischemic etiology of HF and T2D subgroups. Although ischemic etiology is more represented (62.5%) in our diabetic patients, we found association only for the diabetic and not for the ischemic patients suggesting that the protective role of our SNP could be related to T2D.

In the nonischemic subgroup, only 9.5% of patients presented both G alleles for rs266729 and rs2241766. As expected, the compound effect of the two SNPs when together nullified each other. Our results suggest that the association between rs266729G allele and HF is not different across different aetiologies of HF.

We did not find any correlation for rs17300539 (-11391 G>A) in the promoter region and for rs1501299 in intron 2.

Given the exploratory nature of the subgroups analysis, the results reported should be treated with caution.

The promoter region is rich in CpG which presents a large number of methylation and demethylation processes. Further studies of this sequence could clarify the potential role in HF pathogenesis of rs266729 (-11377 C>G) observed in our HF population.

Footnotes

Acknowledgements

GISSI is endorsed by: Associazione Nazionale Medici Cardiologi Ospedalieri (ANMCO), Firenze, Italy; Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy; and Consorzio Mario Negri Sud, Santa Maria Imbaro, Italy. Silvana Pileggi is a Fellow of Associazione Amici dell’Istituto Mario Negri, Milan, Italy.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Conflict of interest statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Association of ADIPOQ variants and heart failure in an Italian population

Abstract

Objectives:

Methods:

Results:

Conclusions:

Keywords

Introduction

Methods

Study population

Genotyping

Statistical methods

Results

Study population

Polymorphisms description in cases and controls

Association of adiponectin polymorphisms and HF

Haplotype analysis

Etiology: ischemic and nonischemic

Diabetes

Discussion

Footnotes

Acknowledgements

Funding

Conflict of interest statement

References