Association Between Single Nucleotide Polymorphisms (SNPs) in the Promoter of Adiponectin Gene, Hypoadiponectinemia, and Diabetes

Tianxin Sheng^1,2, Yunhe Lu³, Kangjuan Yang^1*, Yan Jin¹, Yinghua Wu³, Zibo Zhang¹, YanhuaJin¹, XiongjiJin¹

¹Yanbian University Medical College, Yanji, Jilin 133002 China

²Department of Medicine, Leshan Vocational and Technical College, Leshan, Sichuan 614000 China

³Yanbian University Hospital, Yanji, Jilin 133000 China

*Corresponding Author E-mail: yangkj@ybu.edu.cn

Abstract:

Objective: This study was going to investigate: 1. Environmental and genetic factors leading to hypoadiponectinemia; 2. Mechanism from hypoadiponectinemia to diabetes; 3. Diagnosis and treatment of hypoadiponectinemia-derived diabetes.

Methods: A total of 186 Yanbian Han-Chinese individuals were involved in this study, including 81 men and 105 women. Total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), Fasting plasma glucose (FPG), fasting plasma insulin (FPI), and plasma adiponectin (PA) were measured. PCR and sequencing were used for screening SNPs. ANOVA and linear regressions were used for analyzingthe relations of data.

Results: No significant difference of PA between genotypes or haplotypes of SNPs of -11426A>G and -11377C>G which are in the promoter of adiponectin gene. PA is inversely proportional to BMI (b=-0.17). FPI is directly proportional to PA (b=1.19). HDL-C is directly proportional to PA (b=0.03). 60% of hypoadiponectinemia patients suffered from diabetes and 69% of diabetic patients were hypoadiponectinemia-derived diabetic patients. FPI in simple hypoadiponectinemia group and in hypoadiponectinemia-derived diabetic group is significantly lower than that in normal group (p=0.021 and p<0.001, respectively). Homeostasis model assessment of insulin resistance (HOMA-IR) in other-cause-derived diabetic group is significantly higher than that in normal group (p<0.001). But there is no significant difference of HOMA-IR between hypoadiponectinemia-derived diabetic group and normal group (p=0.093).

Conclusions: 1. Obesity would decrease adiponectin level. 2. Adiponectin could stimulate HDL and insulin secretion, and the hypoinsulinemiamight be the direct cause of hypoadiponectinemia-derived diabetes.

KEY WORDS: Adiponectin; hypoadiponectinemia; diabetes

Introduction:

Adiponectin is an adipokine which is expressedin and secreted from adipocytes[1].In previous studies, adiponectin was also named with ACRP30,adipoQ, orGBP28[2–4]. Adiponectinis composed of 4 domains formed by244 amino acids with a molecular weight of 30 kDa[5,6]. A series of previous studies had shown that the body mass index (BMI) related with adiponectinemia in Japanese, American, and Norwegian populations[7–9].

Adiponectin gene was located on chromosome 3q27[10], including a total of 15,790 base pairs of genomic sequence (NC_000003:188043157-188058946, FASTA, Nucleotide, NCBI). In the adiponectin gene, 12 single nucleotide polymorphisms (SNPs) and 8 mutations had been identified[11–15]. Some studies had shown that the SNPs of -11391G>A (rs17300539) and -11377C>G (rs266729) in the promoter of adiponectin gene have relationship with adiponectinemia in American and German populations[16,17].

Hypoadiponectinemia had been reported to correlate with insulin resistance, and it was also reported to be associated with a higher incidence of development of diabetes and other metabolic syndromes[18–26]. This study is based on Han-Chinese population in Yanbian, China, and going to investigate: 1. Environmental and genetic factors leading to hypoadiponectinemia; 2. Mechanism from hypoadiponectinemia to diabetes; 3. Diagnosis and treatment of hypoadiponectinemia-derived diabetes.

MATERIALS AND METHODS:

Subjects:

A total of 186 Chinese individuals who lived in Yanbian, China were involved in this study, including 81 men and 105 women.

Measurements of Clinical Data:

Clinical data include total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), Fasting plasma glucose (FPG), which were measured on 7600 Clinical Analyzer (Hitachi High-Technologies Corporation, Tokyo, Japan) by Yanbian University Hospital (Yanji, China), and fasting plasma insulin (FPI), plasma adiponectin (PA), which were measured with Human Insulin ELISA Development Kit (Pepro Tech Inc., Rocky Hill, USA) and Human Adiponectin/Acrp30 Quantikine ELISA Kit (R&D Systems Inc., Minneapolis, USA) by Shanghai Westang Bio-Tech Co., Ltd. (Shanghai, China). The estimate of insulin resistance by homeostasis model assessment of insulin resistance (HOMA-IR) calculated by using the following mathematical formula: HOMA-IR = PFI×FPG/22.5

Extraction of Genomic DNA:

Genomic DNA was extracted with AxyPrep Blood Genomic DNA Miniprep Kit (AxygenBiosciences, Union City, USA).

PCR Amplification:

PCR amplification was performed on Techne TC-412 (Techne Inc., Burlington, USA) with GoTaq Green Master Mix (Promega Corp., Madison, USA). The primers were: F: 5’-GCACCTGACCTGAAGTTTAT-3’ and R: 5’-TGACCTGGACCCTGGATTTA-3’, which are synthesized by Beijing AuGCT biotechnology Co., Ltd. (Beijing, China). Reaction system of 25µl involved 12.5µl of GoTaq Green Master Mix, 2X, 7.5µl of Primers Mix, 1µM, and 5µl of DNA template. PCR program is: denaturation at 94℃, annealing at 55 - 53 ℃, polymerization at 72℃, 35 cycles. The amplification product is a DNA fragment of 993 bp.

Sequencing:

All amplification products were sequenced on Applied Biosystems 3730xl DNA Analyzer (Life Technologies Corporation, Foster City, USA)by Shanghai Sunsoon Bio-Technology Co., Ltd. (Shanghai, China).

Screening SNPs:

SNPs were screened with Chromas Lite 2.01 (Technelysium Pty., Ltd., Tewantin, Australia).

Statistical Analysis:

Mean, standard deviation (SD), standard error (SE), 95% confidence interval (CI), ANOVA, χ² test, and regression were calculated with SPSS Statistics 17.0 (SPSS Inc., Chicago, USA). Hardy-Weinberg equilibrium was determined with Hardy-Weinerg equilibrium calculator (http://www.genes.org.uk/software/hardy-weinberg.shtml), Linkage disequilibrium and haplotype frequencies were calculated with Cube X (http://www.oege.org/software/cubex/).

RESULTS:

Clinical Data:

According to the criterion of diagnosis for diabetes proposed by American Diabetes Association (ADA) [27],Individuals whose FPG≥7.0mmol/l were diagnosed with diabetes. Thus all individuals were divided into 2 groups: nondiabetic group and diabetic group (Table 1).

Table 1 Clinical data in nondiabetic and diabetic groups

Nondiabetic group Mean±SD (95% CI)

Diabetic group Mean±SD (95% CI)

n (Male/Female)

Age (years)

BMI (kg/m²)

TC (mmol/l)

TG (mmol/l)

HDL-C (mmol/l)

LDL-C (mmol/l)

FPG (mmol/l)

FPI (ng/ml)

HOMA-IR

PA (µg/ml)

91 (41/50)

53.90±12.23 (51.35-56.45)

24.52±3.48 (23.79-25.25)

4.82±1.17 (4.58-5.07)

2.03±1.71 (1.68-2.39)

1.42±0.34 (1.35-1.49)

2.60 ± 0.81 (2.43-2.77)

5.45±0.68 (5.31-5.59)

18.19±9.81 (16.15-20.23)

4.35±2.27 (3.87-4.82)

5.32±3.11 (4.68-5.97)

95 (40/55)

54.57±9.95 (52.54-56.45)

26.11±3.38 (25.42-26.80)

5.10±1.19 (4.86-5.35))

2.26±1.74 (1.91-2.62)

1.32±0.30 (1.26-1.38)

2.62±0.77 (2.47-2.78)

10.47±4.05 (9.65-11.30)

14.89±11.45 (12.56-17.22)

6.75±4.97 (5.73-7.76)

3.90±2.26 (3.44-4.36)

0.685

0.683

0.002

0.105

0.365

0.040

0.850

< 0.001

0.037

< 0.001

The p values were calculated withχ² test and one-way ANOVA.

Table 2Clinical data in nonhypoadiponectinemia and hypoadiponectinemia groups

Nonhypoadiponectinemia group Mean±SD (95% CI)

Hypoadiponectinemia group Mean±SD (95% CI)

n (Male/Female)

Age (years)

BMI (kg/m²)

TC (mmol/l)

TG (mmol/l)

HDL-C (mmol/l)

LDL-C (mmol/l)

FPG (mmol/l)

FPI (ng/ml)

HOMA-IR

PA (µg/ml)

76 (33/43)

54.53±12.62 (51.64-57.41)

24.24±3.37 (23.47-25.01)

5.12±1.48 (4.78-5.46)

1.89±1.30 (1.60-2.19)

1.48±0.32 (1.41-1.56)

2.73±0.94 (2.52-2.95)

7.09±3.07 (6.39-7.79)

19.85±12.21 (17.06-22.64)

6.14±4.73 (5.06-7.23)

7.19±2.46 (6.62-7.75)

110 (48/62)

54.05±9.97 (52.16-55.93)

26.09±3.43 (25.44-26.73)

4.86±0.93 (4.69-5.04)

2.33±1.95 (1.96-2.70)

1.29±0.30 (1.24-1.35)

2.53±0.66 (2.41-2.65)

8.65±4.22 (7.85-9.45)

14.19±9.01 (12.49-15.89)

5.18±3.50 (4.52-5.84)

2.81±1.09 (2.60-3.01)

0.977

0.772

< 0.001

0.146

0.094

< 0.001

0.081

0.006

< 0.001

0.111

< 0.001

The p values were calculated withχ² test and one-way ANOVA.

The age in nonhypoadiponectinemia group was not significantly different from that in hypoadiponectinemia group (p=0.772). So there was no interference from age while comparing clinical data between groups. FPI in hypoadiponectinemia group is significantly lower than that in nonadiponectinemia group (p<0.001), while HDL-C in hypoadiponectinemia group is significantly lower than that in nonadiponectinemia group (p<0.001), and BMI in hypoadiponectinemia group is significantly larger thanthat in nonadiponectinemia group (p<0.001). Frequencies of genotypes, alleles, and haplotypes of the SNPs in the promoter of adiponectin gene 3 SNPs in the promoter of adiponectin gene were screened: -11426A>G, -11377C>G, and -11156insCA. They were all determined to be in Hardy-Weinberg equilibrium (p>0.05) and complete linkage disequilibrium (|D’|=1.0). SNPs of -11426A and -11156N (no insert of CA) or -11426G and -11156I (an insert of CA) are always exist together on the same chromosome. So the -11156insCA could be ignored when analyzing the genotypes and haplotypes of these loci. For finding the genetic factors leading to hypoadiponectinemia, we examined the difference of frequencies of genotypes, alleles, and haplotypes of SNPs of -11426A>G and -11377C>G between nonhypoadiponectinemia and hypoadiponectinemia groups(Table 3).

Table 3 Frequencies of genotypes, alleles, and haplotypes of SNPs of -11426A>G and -11377C>G in nonhypoadiponectinemia and hypoadiponectinemia groups

Genotype (freq.)

Allele (freq.)

-11426A>G

Nonhypoadiponectinemia group

Hypoadiponectinemia group

-11377C>G

Nonhypoadiponectinemia group

Hypoadiponectinemia group

55 (0.72)

75 (0.68)

0.745

41 (0.54)

75 (0.68)

0.119

17 (0.22)

30 (0.27)

29 (0.38)

27 (0.25)

4 (0.06)

5 (0.05)

6 (0.08)

8 (0.07)

127 (0.84)

180 (0.82)

0.665

111 (0.73)

177 (0.80)

0.092

25 (0.16)

40 (0.18)

41 (0.27)

43 (0.20)

Haplotype (freq.)

-11426 -11377

Nonhypoadiponectinemia group

Hypoadiponectinemia group

A C

87 (0.57)

136 (0.62)

1.000

A G

41 (0.27)

44 (0.20)

G C

24 (0.16)

40 (0.18)

Based on the figure above, PA is inversely proportional to BMI. FPI is directly proportional to PA. HDL-C is directly proportional to PA.

Analysis of the 4 Groups:

According to the criteria of diabetes and hypoadiponectinemia suggested, all individuals can be divided into 4 groups: normal group (A), hypoadiponectinemia and nondiabetic group (B), hypoadiponectinemia and diabetic group (C), and nonhypoadiponectinemia and diabetic group (D) (Fig. 2).

Fig. 2Allindividualswere divided into 4 groups: A, normal group; B, simple hypoadiponectinemia group; C, hypoadiponectinemia-derived diabetic group; D, other-cause-derived diabetic group. The number indicates the amount in every group. 60% of hypoadiponectinemia patients suffered from diabetes and 69% of diabetic patients were hypoadiponectinemia-derived diabetic patients. The PA, FPI, FPG, and HOMA-IR4 in 4 groups were examined (Fig. 3).

Fig. 3 PA, FPI, FPG, and HOMA-IR in the 4 groups. Data were expressed as mean±SE. A, normal group; B, simple hypoadiponectinemia group; C,hypoadiponectinemia-derived diabetic group; D, other-cause-derived diabetic group. ANOVA was used for comparing groups B, C, and D with group A. *, p<0.05, ***, p<0.001.

FPI in simple hypoadiponectinemia group and in hypoadiponectinemia-derived diabetic group was significantly lower than that in normal group (p=0.021 and p<0.001 respectively). HOMA-IR in other-cause-derived diabetic group was significantly higher than that in normal group (p<0.001). But there was no significant difference of HOMA-IR between hypoadiponectinemia-derived diabetic group and normal group (p=0.093).

DISCUSSION:

Environmental and genetic factors leading to hypoadiponectinemia:

Being different from previous studies[16,17], we did not find any genetic factor leading to hypoadiponectinemia in the promoter of adiponectin gene in the population. But that the adiponectin level can be affected by BMI has been demonstrated in this study. This is consistent with previous studies[7–9]. As a factor leading to hypoadiponectinemia, BMI>25.01kg/m² (P_97.5 of BMI in nonhypoadiponectinemia group) would be a criterion suggesting hypoadiponectinemia in Yanbian Han-Chinese population. But this was not absolute. We have found that some lean individuals could have lower adiponectin level, while some obese subjects could have higher adiponectin level. Comparing with BMI, HDL-C might be a better criterion suggestinghypoadiponectinemia. HDL-C is positively correlated with PA (p<0.001). Since HDL-C was an item of blood routine, it was convenient getting the data. We would suggest that HDL-C<1.41mmol/l (P_2.5 of HDL-C in nonhypoadiponectinemia group) may be a criterion suggesting hypoadiponectinemia in Yanbian Han-Chinese population.

Mechanism from Hypoadiponectinemia to Diabetes:

In addition to HDL-C, FPI is also positively correlated with PA (p<0.001). Adiponectin might directly or indirectly stimulate HDL and insulin secretion. Hypoadiponectinemia could cause hypoinsulinemia and then cause a higher FPG. In Fig. 3, FPI was relatively deficient in simple hypoadiponectinemia group (p=0.021), and was absolutely deficient in hypoadiponectinemia-derived diabetic group (p<0.001). This may be caused by different individual’s adiponectin sensitivity. But the HOMA-IR in hypoadiponectinemia-derived diabetic group was not significant different with the HOMA-IR in normal group (p=0.093), but significantly lower than that in other-cause-derived diabetic group (p=0.014). This indicated that hypoinsulinemia would the direct cause of hypoadiponectinemia-derived diabetes other than insulin resistance.

Diagnosis and Treatment of Hypoadiponectinemia-Derived Diabetes:

A diabetic patient with obesity, low HDL-C, low FPI, and low PA should be suspected to be a hypoadiponectnemia-derived diabetic patient. For the treatment of the hypoadiponectinmia-derived diabetes, we would like to suggest the following ways:

1. Diet. Since adiponectin level is negatively correlated with BMI, we may increase patients’ adiponectin level by decreasing their BMI. And then their plasma insulin could be increased and plasma glucose could be decreased. This method had already been demonstrated[28,29].

2. Adiponectin. Since the hypoadiponectinemia-derived diabetes was caused by hypoadiponectinemia, making up adiponectin for instance injection of adiponectin or adipocytes transplantation may be a way for treatment. But the method still needs further studies.

3. Insulin. Absolute deficiency of insulin was the direct cause of hypoadiponectinemia-derived diabetes. So increasing plasma insulin is the direct method for treatment. And this is the most common used method presently.

4. Drug. Thiazolidinediones (TZDs) could upregulate adiponectin level by generating small adipocytes that abundantly express and secrete adiponectin and/or directly activating adiponectin gene transcription[30,31].

ACKNOWLEDGMENTS:

This study is funded by National Natural Science Foundation of China (No. 31060154 and No. 81460158).

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Received on 19.11.2015 Modified on 08.12.2015

Research J. Science and Tech. 8(1): Jan.– Mar. 2016; Page 34-40

DOI: 10.5958/2349-2988.2016.00004.8