A Meta-analysis of ADIPOQ rs2241766 polymorphism association with type 2 diabetes

Abstract

Objective

There is extensive research on the association between polymorphisms in the adiponectin gene (ADIPOQ) and type 2 diabetes (T2D). The present meta-analytic study explored the association between ADIPOQ rs2241766 polymorphisms and T2D.

Metolds

Articles were collected by searching Google Scholar, Scopus, and PubMed electronic databases until 2021. They were searched using a systematic search of original and sensitive English keywords and their equivalent keywords based on the keywords “type 2 diabetes”, “ADIPOQ”, and “rs2241766”. The article selection criteria were based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram.

Results

The results revealed that there was no bias in this study. Some studies, such as Joshaghani et al. (odds ratio [OR] = 2.18), Hussain et al. (OR = 2.12), Momin (OR = 4.45), and Amal et al. (OR = 1.84), showed an increasing effect of ADIPOQ rs266729 polymorphism on T2D with 95% CI (P ˂ 0.01), while some have shown no significant association between them.

Conclusion

The results of this meta-analytic study showed the relationship between ADIPOQ and rs2241766. Also, it was found that Rs2241766 polymorphism and allele increase the risk, and rs2241766 increases the risk of developing T2D (OR = 1.29).

Introduction

According to the World Health Organization (WHO), type 2 diabetes (T2D) is a group of metabolic disorders caused by insulin resistance and insulin deficiency and characterized by chronic hyperglycemia and metabolism disorders of carbohydrates, fats, and proteins [1]. It is the most common metabolic disease accounting for 90% of patients with diabetes [1, 2]. Also, T2D is a specific type of insulin resistance in patients. According to WHO, the number of diabetic patients in 2017 was 451 million worldwide. This value is predicted to increase to more than 695 million by 2045 [1, 2]. T2D is a complex disease caused by environmental and genetic factors [3]. Since genes are involved in the causes of cancer, the ADIPOQ gene is also effective in diabetes [4–9].

ADIPOQ is a 30-kDa protein and indicator for estimating adipose tissue dysfunction and systemic inflammation in diabetic patients [4, 10] ADIPOQ is the most abundant cytokine derived from adipose tissue. This protein is present in plasma in 3 forms with low, medium, and high molecular weight, with the third type being biologically active. ADIPOQ binds to 2 receptor subtypes (AdipoR and AdipoR2) and is involved in AMPK metabolism, lipid activation, and insulin action [11, 12]. Many studies have also shown that ADIPOQ polymorphisms are significantly associated with diabetes [13–15]. Besides, research has shown that SNP rs2241766 is directly related to the ADIPOQ protein level [12, 15].

Van et al. found that rs2241766 polymorphisms significantly increased the risk of T2D in an Asian population [16]. Eaton et al. also reported that the rs2241766 allele was significantly associated with a sensitive gene in T2D patients in a Chinese population [17]. However, Han et al. found no association between SNP45 and SNP276 polymorphisms and T2D [18]. Despite considerable findings regarding the association of ADIPOQ polymorphisms with T2D [13, 15], the results of some studies in this area are disappointing [19, 20]. To the best of our knowledge, there are no definite reports and evidence on the relationship between ADIPOQ rs2241766 polymorphisms and T2D in humans or animals. Accordingly, we investigated the relationship between ADIPOQ rs2241766 polymorphisms and T2D. The results of this study can be used in designing treatment methods for diabetes in humans.

Materials and methods

Search strategy

We collected the required data by searching Google Scholar, Scopus, and PubMed databases. To this end, we started with a systematic search of English keywords with all possible compounds, important, main, and sensitive words, and their equivalent keywords. Articles were searched based on the keywords “Diabetes Mellitus, Noninsulin-Dependent” OR “Diabetes Mellitus, Types” AND “adiponectin” OR “ADIPOQ” AND “Polymorphism, Genetic” OR “Polymorphism, Single Nucleotide/genetics” [Mesh] OR “SNP” OR “rs2241766.”

Criteria for selecting articles

After studying all abstracts of the articles, unrelated articles were excluded, possible related articles were identified, and their full texts were extracted. Inclusion criteria were studies in which the intervention was the effect of the rs2241766 polymorphism gene on T2D, studies with a T2D patient group and control group (non-diabetic individuals), and related articles in English. Finally, animal and in vitro studies, meta-analysis and review articles, and clinical articles were excluded from the study.

Statistical analysis

As the selected studies were heterogeneous, a random-effects model was applied to combine them. The Cochran test and I² index were used to evaluate the heterogeneity of the studies. Also, the collected data were analyzed using STATA software.

Results

Data extraction

Initially, 145 articles published by 2021 were reviewed. Next, the first 1976 articles were imported to EndNote, and 1204 articles remained after removing the duplicate ones. Then, the titles of articles were screened, 500 articles were entered into the study, and 704 articles were removed. After screening the abstracts of the articles, 319 unrelated articles were removed. Finally, 18 articles that met the inclusion criteria were meta-analyzed (Fig. 1). The article selection criterion was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram.

Fig. 1.

The process of selecting eligible articles

The number of cases, number of controls, and number of homozygous (AA), heterozygous (GA), and wild (GG) genotypes of the rs2241766 polymorphism gene were examined in cases and controls in each study. The article publication year and the study population were extracted and entered into the form. OR and 95% CI were calculated in each study.

In the heterogeneity test, P values less than 15 were considered statistically significant.

Results

Figure 1 shows the characteristics of 16 identified case studies on ADIPOQ rs2241766 levels and the risk of T2D. The studies conducted by 2020 in Iran, India, Venezuela, South Korea, Iraq, China, Bangladesh, Bahrain, Brazil, and Japan (Fig. 1) were included in this analysis. The results revealed that the studies of Sánchez et al., Joshaghani et al., Hussain et al., Momin, and Amal et al. had a significant difference with a P value less than 0.01. In contrast, other studies did not show a significant difference. The results of Sánchez et al. (OR = 0.31) indicated a decreasing effect on T2D, while the studies of Joshaghani et al. (OR = 2.18), Hussain et al. (OR = 2.12), Momin (OR = 4.45), and Amal et al. (OR = 1.84)) showed an increasing effect on T2D. However, the final overall OR was reported to be 1.29 [1.05; 1.58], which indicates that SNP rs2241766 has an increasing effect on T2D (Fig. 2).

Fig. 2.

Association between rs2241766 gene polymorphism and the risk of T2D

Based on the entered data and the obtained OR values, the chart is stretched to the right, and the overall OR was found to be 1.24 with 95%CI. Therefore, the results showed that SNP rs2241766 increased the risk of T2D. In fact, this gene not only does not reduce the chances of developing the disease but also increases the risk of developing it (Fig. 3).

Fig. 3.

The association of rs2241766 polymorphism with the risk of T2D

The results showed that bias had no effect in this study (P = 0.79), which is shown symmetrically in the funnel chart. The size of the circles indicates the weight of the studies. In other words, the larger circles show greater samples. This chart also shows several cases outside the scope of the study. There was also some evidence of heterogeneity among the studies (I² = 79%; P = 0.79; Fig. 4).

Fig. 4.

The funnel chart shows publication bias; the rate ratio is shown against the standard error. It is a symmetrical distribution, which indicates a lack of bias

Discussion

Although many studies have shown that ADIPOQ polymorphisms are associated with T2D [13–15], the association of ADIPOQ rs2241766 polymorphisms with T2D is still one of the most challenging issues. Therefore, the present study sought to explore the relationship between ADIPOQ rs2241766 polymorphism and T2D using database search methods. Many basic mechanisms in ADIPOQ polymorphisms are associated with T2D. Several studies have shown significant differences in the risk of developing T2D among individuals with the ADIPOQ genotype [13–15]. In addition, many studies have reported that SNP rs2241766 is directly associated with the ADIPOQ protein level [12, 13, 15]. Previous studies have also reported conflicting results on the association of the ADIPOQ gene with rs2241766 polymorphism and the risk of T2D [18].

Therefore, this meta-analytic study was designed to determine whether the ADIPOQ gene is associated with the risk of T2D in studied populations. Overall, the studies of Sánchez et al., Joshaghani et al., Hussain et al., Momin, and Amal et al. showed an increasing effect between ADIPOQ polymorphism genotypes and T2D. This finding was consistent with the one reported by Amal et al. (2014), which used the PCR-RFLP method to investigate the association of ADIPOQ polymorphism genotypes with T2D. This study showed that both TG and GG genotypes increased significantly in diabetic patients, and the mean OR was reported to be 1.5 [21]. In another effort, Eaton et al. also conducted a study using the PCR method. According to this research, the rs2241766 allele was significantly associated with a sensitive gene in T2D patients in a Chinese population [17]. Hussain et al. (2018) used the PCR-RFLP method to investigate the association between ADIPOQ polymorphism genotypes and T2D. They found that the genotypic distribution of rs2241766 had a significant increase in homozygous GG (OR = 5.04) and heterozygous TG carriers (OR = 1.7). It was also reported that the rs2241766T > G SNP of the ADIPOQ gene was a risk factor for developing T2D in an Iraqi population [22]. Joshaghani et al. (2020) also conducted a study using the PCR-RFLP method to investigate the association between the ADIPOQ polymorphism genotypes and T2D in an Iranian population. They found that the G allele and GG and TG genotypes were more abundant than the T allele and TT genotype in T2D patients compared with the control group. G/T SNP was also shown to be associated with T2D. Furthermore, there was also a statistically significant difference in the frequency of the G/T allele and genotype between the control group and diabetic patients [23]. Saxena et al. (2012) investigated the association between ADIPOQ polymorphism genotypes and T2D in an Indian population using the PCR-RFLP method. They found a significant relationship between the G allele of the ADIPOQ gene and T2D patients compared with the control group [24]. Elsewhere, using the PCR-RFLP method, Sánchez et al. (2019) investigated the relationship between ADIPOQ polymorphisms and T2D in a Venezuelan population. They found that genotypes with heterozygous T/G and G/G homozygous polymorphism were more frequent in the diabetic group than in the control group [25]. However, Hannan et al. found that SNP45 and SNP276 polymorphisms are not associated with T2D [18] (Table 1).

Table 1.

Characteristics of included studies selected for meta-analysis

Author.	Year of Publication	Population	Method	Cases (n)	Controls (n)	Overall Sample Size	Count (Genotype)
							Diabetic			Nondiabetic (Control)
							GG	TG	TT	GG	TG	TT
Joshaghani et al.	2020	Iranian	PCR-RFLP	211	202	413	18	77	116	5	48	149
Sánchez et al.	2019	Venezuelan	PCR-RFLP	46	44	90	1	4	41	2	12	30
Nam JS	2018	Korean	PCR	249	131	380	119	108	22	61	60	10
Hussain et al.	2018	Iraqi	PCR-RFLP	400	400	800	33	110	257	8	78	314
Momin AA	2017	Indian	PCR	150	150	300	2	21	127	0	6	144
Sheng T	2016	Korean Chinese	PCR	191	138	329	13	81	97	9	63	66
Saleh R	2016	Bangladeshi	PCR-RFLP	55	40	95	3	19	33	1	12	27
Farooq,R	2018	Indian	PCR-RFLP	400	300	700	40	168	192	24	123	153
Vendramini, M.F.	2010	Japanese Brazilians	PCR	200	200	400	12	95	93	15	85	100
Potapov,V.A.	2008	Russian	PCR	129	117	246	2	10	117	1	8	108
Lee,Y.Y.	2005	Korean	PCR	493	427	920	39	202	252	45	181	201
Al Hannan, F.A.	2016	Bahraini	PCR-RFLP	140	66	206	8	32	100	10	0	56
Ming-Kai Tsa	2014	Taiwan’s Chinese Han	PCR	149	139	288	9	69	71	12	57	70
Amal et al.	2014	Egyptian	PCR-RFLP	296	209	505	34	145	117	10	78	121
Saxena et al.	2012	North Indian	PCR-RFLP	221	205	426	23	55	143	11	46	148
Fatemeh Namvaran	2012	Iranian	PCR	101	128	229	3	31	67	6	21	101

A limitation of this meta-analytic study was that our search was restricted to studies published in English. Thus, it may potentially lead to publication bias. Given the significant heterogeneity among the studies, the present study’s findings should be interpreted cautiously. Finally, the number of studies for subgroup analysis was relatively small. Therefore, further studies are needed to identify the exact association between SNP rs2241766 and the increased risk of developing T2D.

Conclusion

The results of this meta-analysis show the association between ADIPOQ and rs2241766. Rs2241766 polymorphism and allele increase the risk of T2D. Also, rs2241766 with an OR of 1.29 has an increasing effect on T2D and increases the risk of developing it.

Author contributions

Dr. Elham Afraz, Dr. Sanaz Pashapour, Yeganeh Hamidi, and Sahar Saki conducted the research, collected the data, and performed the statistical analysis. Dr. Sanaz Pashapour collaborated in writing and reviewing the processes.

Data availability

The raw/processed data required to reproduce these findings cannot be shared at this time due to legal or ethical reasons.

Declarations

Conflict of interest

The authors state that there is no conflict of interests regarding the publication of this article.