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J Intern Med. Author manuscript; available in PMC 2011 March 1.
Published in final edited form as:
PMCID: PMC2833228
NIHMSID: NIHMS135410
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Circulating HMW adiponectin isoform is heritable and shares a common genetic background with insulin resistance in non diabetic White Caucasians from Italy: evidence from a family-based study
Claudia Menzaghi,1 Lucia Salvemini,1 Giulia Paroni,1 Concetta De Bonis,1 Davide Mangiacotti,1 Grazia Fini,1 Alessandro Doria,2 Rosa Di Paola,1 and Vincenzo Trischitta1,3,4
1Research Unit of Diabetes and Endocrine Diseases, IRCCS “Casa Sollievo della Sofferenza”, San Giovanni Rotondo (FG), Italy
2Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, MA
3Department of Medical Pathophysiology, “Sapienza” University, Rome, Italy
4IRCCS Casa Sollievo della Sofferenza-Mendel Institute, Rome, Italy
Correspondence: Claudia Menzaghi, PhD, Research Unit of Diabetes and Endocrine Diseases, IRCC “Casa Sollievo della Sofferenza”, Viale Padre Pio, 71013 San Giovanni Rotondo (FG), Italy, Tel ++39 0882 416276, FAX ++39 0882 416266, c.menzaghi/at/operapadrepio.it
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Abstract
Objective
Reduced circulating adiponectin levels contribute to the etiology of insulin-resistance. Adiponectin circulates in three different isoforms: high (HMW), medium (MMW), and low (LMW) molecular weight. The genetics of adiponectin isoforms is mostly unknown. Our aim was to investigate whether and to which extent circulating adiponectin isoforms are heritable and whether they share common genetic backgrounds with insulin resistance-related traits.
Methods
In a family based sample of 640 non diabetic White Caucasians from Italy, serum adiponectin isoforms concentrations were measured by ELISA. Three SNPs in the ADIPOQ gene previously reported to affect total adiponectin levels (rs17300539, rs1501299 and rs677395) were genotyped. The heritability of adiponectin isoform levels was assessed by variance component analysis. A linear mixed effects model was used to test association between SNPs and adiponectin isoforms. Bivariate analyses were conducted to study genetic correlations between adiponectin isoforms levels and other insulin resistance-related traits.
Results
All isoforms were highly heritable (h2=0.60−0.80, p=1×10−13–1×10−23). SNPs rs17300539, rs1501299 and rs6773957 explained a significant proportion of HMW variance (2–9%, p=1×10−3–1×10−5). In a multiple-SNP model, only rs17300539 and rs1501299 remained associated with HMW adiponectin (p=3×10−4 and 2.0×10−2). Significant genetic correlations (p=1×10−2–1×10−5) were observed between HMW adiponectin and fasting insulin, HOMAIR, HDL-cholesterol and the metabolic syndrome score. Only rs1501299 partly accounted for these genetic correlations.
Conclusion
Circulating levels of adiponectin isoforms are highly heritable. The genetic control of HMW adiponectin is shared in part with insulin resistance-related traits and involves, but is not limited to the ADIPOQ locus.
Keywords: ADIPOQ gene, Adiponectin isoforms, insulin resistance
Adiponectin, a hormone exclusively secreted from adipose tissue, has insulin enhancing and anti-inflammatory actions and may therefore be involved in the etiology of insulin-resistance and related abnormalities [1–3]. Circulating adiponectin levels and insulin resistance traits have been reported to be both heritable and to share, at least in part, a common genetic background [4]. Recent evidences have shown that adiponectin circulates in three different higher order complexes: high (HMW), medium (MMW), and low (LMW) molecular weight isoforms [5, 6]. Whether and to which extent circulating adiponectin isoforms are heritable and, if so, whether they share a common genetic background with insulin resistance-related traits has not been thus far investigated.
We addressed these questions in a family based sample of 640 non-diabetic White Caucasians from Italy. In addition, we investigated whether SNPs rs17300539, rs1501299 and rs6773957 in the ADIPOQ gene play a role in the genetic regulation of adiponectin isoforms. These SNPs were selected because of their previously reported association with total adiponectin levels [7–9].
Subjects
A total of 640 non-diabetic individuals from 235 families were recruited in the Gargano area (an homogeneous geographical area in Center-East Italy [10]) and examined as previously described [11, 12]. All study subjects were not treated with medications known to interfere with glucose homeostasis, lipid profile and blood pressure. The study and the informed consent procedures were approved by the local research committee.
Serum total adiponectin, HMW and MMW+HMW adiponectin concentrations were measured by enzyme-linked immunosorbant assay ELISA (ALPCO, NH) [13]. MMW values were obtained by subtracting the concentrations of HMW from the combined concentrations of MMW+HMW. LMW adiponectin fractions were obtained by subtracting the combined concentrations of MMW+HMW from the total adiponectin concentrations.
The intra-assay coefficient of variation (CV), calculated by measuring 4 samples in 6 replicates in a single assay and the inter-assay CV, calculated by measuring replicates of the same samples in 20 consecutive assays, were 5.4% and 5.0%, 5.2% and 4.9%, 5.0% and 4.8% for total adiponectin, MMW+HMW adiponectin and HMW adiponectin, respectively.
The metabolic syndrome score was calculated for each study subject summing the number of individual components of the syndrome, according to ATP III criteria, as follows: waist circumference >102 cm for men and >88 cm for women; systolic blood pressure ≥130 mm Hg or diastolic blood pressure ≥85 mm Hg; serum HDL-cholesterol <40 mg/dl for men and <50 mg/dl for women; serum TG levels ≥150 mg/dl; and venous plasma glucose ≥110 mg/dl [12]. Smoking habit was recorded as smoker (i.e. an individual who had regularly smoked one or more cigarette a day for >1 year) or never smoker. Physical exercise was assessed as follows: no physical activity = equal or less than 2 hr weekly exercise, including walking; physical activity = more than 2 hours weekly exercise.
SNP genotyping
SNPs rs17300539, rs1501299, and rs6773957 in the ADIPOQ gene were genotyped by Taqman SNP allelic discrimination technique, by means of an ABI 7000 (Applied Biosystems, CA). Call rate and concordance rate were ≥96% (average 98%) and >99% respectively. Out of 640 study individuals, genotypes were available for 623 study subjects for rs17300539, for 625 study subject for rs1501299 and for 612 study subjects for rs6773957. All the SNPs were in Hardy-Weinberg Equilibrium (HWE) (P>0.05).
Data Analysis
Data are summarized as means ± SD. If the data were not normally distributed (kurtosis >1.9), a log transformation was performed before further analyses. Some residual kurtosis, slightly above the threshold (i.e. 2.0), was present only for the HMW. A χ2 test was used to assess whether genotypes prevalence were in HWE.
To determine the contribution of genetic factors to serum adiponectin isoforms, the SOLAR software package (Version 4.1.7) was utilized [14]. SOLAR performs a variance components analysis of family data that decomposes the total variance of the phenotypes (adiponectin isoforms) into components that are due to genetic effects (i.e. polygenic, additive genetic variance), measured covariates, and random environmental effects (i.e. measured environmental factors and random unmeasured factors). The relative contribution of genetic factors to serum adiponectin isoforms is then estimated by heritability (h2), defined as the ratio of the genetic variance component to the residual (after removal of covariates) phenotypic variance. Heritability estimates, so obtained, also include any environmental contributions to similarities in adjusted values between relatives. To assess phenotypic correlations between adiponectin isoforms and insulin resistance related traits we used a mixed effects model by SOLAR that includes fixed covariate effects. This method could account for the dependence of the family data and provide a more stringent p value. To evaluate the contribution of the ADIPOQ genotypes to adiponectin isoforms variance, and test the associations between each trait and each SNP, a linear mixed effects model implemented in SOLAR, to account for within-family correlations, was performed. Each SNP was included in a model as a fixed effect with additive coding. All analyses were performed first with sex, age, age2, smoking habits, and physical exercise and then with sex, age, age2 smoking habits, physical exercise and BMI as covariates in the model, to examine the strength of the SNP associations after accounting for the portion of variance due to BMI. Bivariate analyses were conducted to partition the phenotypic correlation between two traits (ρp) into genetic (ρg) and environmental (ρe) correlations [14]. Evidence of pleiotropy (i.e. a common set of genes influencing more than one trait) is indicated by a genetic correlation significantly different from zero.
The clinical characteristics of study participants are shown in Table 1. This study comprises 140 nuclear families, 75 sibships and 20 extended sibships (ranging 3–5 individuals).
Table 1
Table 1
Clinical characteristics of 640 non-diabetic individuals from 235 nuclear families
Among the 640 individuals, mean HMW, MMW and LMW adiponectin levels were 4.3 ± 2.9 µg/ml (median 3.6, range 0.02 – 24.1), 1.6 ± 1.5 µg/ml (median 1.2, range 0.01–11.6) and 2.1 ± 1.8 µg/ml (median 1.7, range (0.01 – 13.5), respectively (Table 1).
HMW adiponectin was inversely associated with several traits related to insulin resistance, including BMI, waist circumference, fasting glucose, insulin and HOMAIR levels (Table 2). Correlations were also evident with triglycerides, HDL-cholesterol and the metabolic syndrome score (Table 2). MMW and LMW isoforms were associated, in a much weaker manner, only with HDL-cholesterol and the metabolic syndrome score and with HDL-cholesterol, respectively (Table 2). No association was found between any adiponectin isoform and C-reactive protein (CRP) (Table 2).
Table 2
Table 2
Association of serum adiponectin isoforms levels and insulin resistance-related traits in 640 non-diabetic individuals from 235 nuclear families
The overall effect of genetic factors on serum adiponectin isoforms was investigated by variance component analysis. After adjusting for age, age2, gender, smoking habits, and physical exercise, all the different isoforms were found to be highly heritable, with HMW showing a somewhat higher heritability (0.79 ± 0.06, p = 1.0×10−13) than MMW and LMW (0.58 ± 0.06, p = 2.4×10−23 and 0.58 ± 0.09, p = 6.5×10−13, respectively) (Table 3). ADIPOQ SNPs rs17300539, rs1501299 and rs6773957 explained a highly significant proportion of HMW, but not MMW and LMW adiponectin variance (Table 3). Further adjustment for BMI did not significantly change the observed associations (Table 3). Adjustment for CRP also did not affect the observed associations (data not shown). When the two SNPs in the 3’ UTR block (which are in moderate LD, r2 = 0.64) were simultaneously considered into the model, rs1501299 (p = 2.0×10−2), but not rs6773957 (p = 0.51) remained significantly associated with HMW isoform levels. When all the three SNPs were included into the same model only the promoter rs17300539 and rs1501299 remained significantly associated with HMW adiponectin (p = 3×10−4 and 2.0×10−2, respectively).
Table 3
Table 3
Serum adiponectin isoforms levels according to ADIPOQ SNPs in nuclear families
Table 4 shows the genetic (ρg) correlations between serum adiponectin isoforms levels and insulin resistance-related traits. Significant genetic correlations were observed between HMW isoform and fasting insulin (ρg = −0.37, p = 1.1×10−5), HOMAIR (ρg = −0.32, p = 4.9×10−3), HDL-cholesterol (ρg = 0.22, p = 1.6×10−2) and the metabolic syndrome score (ρg = −0.32, p = 4.2×10−2). In contrast, no genetic correlations were observed between MMW and LMW isoforms and any trait (Table 4). After the inclusion into the model of SNP rs1501299, genetic correlations of HMW adiponectin with insulin (p=0.06), HOMAIR (p=0.12) and metabolic syndrome score (p=0.11) were no longer significant. No effect of the promoter rs17300539 and the 3’ UTR rs6773957 was observed on these genetic correlations (data not shown).
Table 4
Table 4
Genetic (ρg) correlations between adiponectin isoforms levels and insulin resistance-related traits in 640 non-diabetic individuals from 235 nuclear families
Environmental, and phenotypic correlations between serum adiponectin isoforms levels and insulin resistance-related traits are summarized in Supplemental Table 1. Significant environmental correlations (ρe) were observed only between LMW and waist circumference, insulin and HOMAIR (Supplemental Table 1).
Several studies have clearly established the important role of adiponectin in the pathogenesis of insulin resistance-related disorders [2, 3, 15, 16]. More recently, it has been shown that adiponectin is secreted, and then circulates, in several multimeric forms [5, 6, 17, 18], of which the HMW isoform is the most biologically active in peripheral target tissues [19, 20].
In the present study, we investigated for the first time several aspects of the genetics of adiponectin isoforms. Our findings show that these isoforms are highly heritable and are therefore likely to be under a strong genetic control. Heritability estimates observed in our population are consistent with those of total adiponectin levels previously reported in studies with similar family structures [9, 21], although we acknowledge that under these circumstances (i.e. family structures prevalently composed by nuclear families and sib pairs rather than extended pedigrees) heritability is usually overestimated and different from that estimated by twin studies [22, 23]. In addition, HMW, but not MMW or LMW adiponectin levels are genetically correlated with fasting insulin, HOMAIR, HDL-cholesterol and the metabolic syndrome score. This implies that a common set of genes that controls some of the insulin-resistance traits also controls HMW adiponectin. ADIPOQ SNPs rs17300539 and rs1501299 were strongly and independently associated with HMW adiponectin levels and explained a proportion of its variance. In addition, ADIPOQ rs1501299 partly accounted for the common genetic background shared by HMW and insulin resistance traits. Taken together, these data indicate an impact of ADIPOQ gene variability on HMW, but not on MMW and LMW isoforms. The presentation of circulating adiponectin under each different isoform is entirely due to a post-translational modification process [5]. However, the production of HMW isoform is more likely to be affected by reduced gene expression, as compared to that of MMW and LMW [18]. This makes possible that the observed associations between ADIPOQ SNPs and HMW, but not MMW and LMW, is a consequence of an impact of these SNPs on gene expression. In this context it is of note that, while rare gene variants harbored in the ADIPOQ coding region (i.e. G84R and G90S) may influence the ability to form HMW oligomer and consequently adiponectin isoforms levels [17], no common variants in the coding sequence have been so far described with the potential to influence circulating adiponectin at a post transcriptional level.
A recent comprehensive analysis of the evidence published thus far on the role of ADIPOQ gene common variants on adiponectin circulating levels and insulin resistance traits has clearly indicated the existence of two distinct signals, corresponding to the two linkage disequilibrium blocks in the ADIPOQ gene [7]. SNP rs17300539 in the promoter region and SNPs rs1501299 in the 3’UTR block are the variants that best capture these associations [7]. More recently rs6773957 in the 3’UTR has been associated to total adiponectin levels [8, 9]. Our present data on adiponectin isoforms confirm the association of rs17300539 and rs1501299 with adiponectin levels and indicate that this is due exclusively to an effect on the HMW fraction. On the other hand, a clear functional role has been shown for rs17300539 [24], but not for rs1501299 [24]. Thus, additional fine-mapping and functional studies are needed to pin point the causal variant(s) responsible for this association. Given the lack of association between ADIPOQ SNPs and MMW and LMW levels, as well as the large proportion of unexplained variability of HMW levels, after taking into account ADIPOQ SNPs, other yet unidentified genetic determinants are certainly playing a role in modulating adiponectin isoforms levels.
Although not a primary aim of this study, we also confirmed previous observations [25, 26] indicating that, of the three adiponectin isoforms, HMW is the one showing the best correlation with insulin resistance traits.
The main strength of our findings relates to the novelty of studying all circulating adiponectin isoforms in a family based cohort. In addition, our sample of non-diabetic White Caucasians comes from a genetically homogeneous population [10], further minimizing the risk of false results due to population stratification. Nonetheless, our study has some limitations. Our genotyping was limited to the three SNPs reported to be associated with total adiponectin levels in previous studies and we cannot exclude that other ADIPOQ SNPs play also a role on the genetics of adiponectin isoforms. In addition, whether our data can be generalized to other populations with different study design (i.e. sample with extended pedigrees where genetic heritability can be more accurately estimated), and with different environmental and/or genetic background is not known and deserves further investigation.
In conclusion, our data indicate that circulating levels of adiponectin isoforms are under a strong additive genetic control which, as far as HMW is concerned, is shared with other traits related to insulin resistance. Our results also point to a role of the ADIPOQ locus in influencing both HMW adiponectin and insulin resistance. Taken together, these data reinforce the hypothesis that differences in HMW isoform levels play a pathogenic role in the development of insulin resistance-related abnormalities.
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Acknowledgments
Part of the research described in this paper was supported by Accordo Programma Quadro in Materia di Ricerca Scientifica nella Regione Puglia-PST 2006 and Italian Ministry of Health grants Ricerca Corrente 2007, 2008 and 2009 (C.M.) and NIH grant HL073168 (A.D.).
Footnotes
Conflict of interest statement
No conflicts of interest to declare.
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