Skip to main content
Download PDF

The role of angiotensin I-converting enzyme gene polymorphism and global DNA methylation in the negative associations between urine di-(2-ethylhexyl) phthalate metabolites and serum adiponectin in a young Taiwanese population

Clinical Epigenetics volume 15, Article number: 87 (2023) Cite this article

Abstract

Background

Adiponectin is a key protein produced in adipose tissue, with crucial involvement in multiple metabolic processes. Di-(2-ethylhexyl) phthalate (DEHP), one of the phthalate compounds used as a plasticizer, has been shown to decrease adiponectin levels in vitro and in vivo studies. However, the role of angiotensin I-converting enzyme (ACE) gene polymorphism and epigenetic changes in the relationship between DEHP exposure and adiponectin levels is not well understood.

Methods

This study examined the correlation between urine levels of DEHP metabolite, epigenetic marker 5mdC/dG, ACE gene phenotypes, and adiponectin levels in a sample of 699 individuals aged 12–30 from Taiwan.

Results

Results showed a positive relationship between mono-2-ethylhexyl phthalate (MEHP) and 5mdC/dG, and a negative association between both MEHP and 5mdC/dG with adiponectin. The study found that the inverse relationship between MEHP and adiponectin was stronger when levels of 5mdC/dG were above the median. This was supported by differential unstandardized regression coefficients (− 0.095 vs. − 0.049, P value for interaction = 0.038)). Subgroup analysis also showed a negative correlation between MEHP and adiponectin in individuals with the I/I ACE genotype, but not in those with other genotypes, although the P value for interaction was borderline significant (0.06). The structural equation model analysis indicated that MEHP has a direct inverse effect on adiponectin and an indirect effect via 5mdC/dG.

Conclusions

In this young Taiwanese population, our findings suggest that urine MEHP levels are negatively correlated with serum adiponectin levels, and epigenetic modifications may play a role in this association. Further study is needed to validate these results and determine causality.

Background

Adiponectin is a protein consisting of 244 amino acids that is produced by fat cells. It plays a role in regulating various metabolic processes, including improving insulin sensitivity. [1]. Adiponectin has been reported to play protective roles against diabetes mellitus, cancer, and cardiovascular disease (CVD) [2]. A number of factors can influence the amount of adiponectin present in the body, such as peroxisome proliferator-activated receptor (PPAR) γ, insulin, insulin-like growth factor, leptin, and various inflammatory cytokines [3, 4]. The renin–angiotensin–aldosterone system (RAAS), a series of peptide hormones that regulates body fluid, also plays a role in regulating adiponectin homeostasis [4, 5]. It has been shown that aldosterone may downregulate the gene expression of adiponectin [6]. Additionally, research has revealed that epigenetic modifications, which do not involve changes to the DNA sequence but can affect gene expression, can alter the expression of adiponectin-related genes [7, 8].

Di-(2-ethylhexyl) phthalate (DEHP), a commonly used plasticizer, is a type of phthalate compound that can be easily released into the ecosystem due to its lack of covalent bonding with plastics [9]. DEHP exposure has been linked to various adverse health effects, such as endocrine and metabolic diseases [9]. According to experimental studies, DEHP treatment may reduce adiponectin levels [10,11,12]. The exact mechanism through which DEHP leads to a decrease in adiponectin concentration is still being studied. Possible mechanisms include decreasing expression of PPARγ, increasing inflammatory cytokines and oxidative stress [10,11,12].

Animal studies have also shown that DEHP exposure is linked to the stimulation of the RAAS. Possible mechanisms for this effect include the elevation of angiotensin I-converting enzyme (ACE) levels and the suppression of 11β hydroxysteroid dehydrogenase type 2 (11β-HSD-2) enzyme activity [13, 14]. ACE is an enzyme that cleaves angiotensin 1 into angiotensin II and inactivates bradykinin [15]. It has been observed that different ACE genotypes may be associated with varying risks for CVD [15, 16]. While we know that DEHP can affect the RAAS and that RAAS can in turn influence adiponectin secretion, it is currently unclear what role ACE genotypes may play in the relationship between DEHP exposure and adiponectin levels.

Studies have also demonstrated that DEHP exposure can lead to epigenetic regulation in experimental settings [17, 18]. Past research has suggested that DNA methylation, a well-studied form of epigenetic regulation, may be involved in the link between DEHP and health outcomes [19, 20]. Although it is known that epigenetic modifications can also affect adiponectin levels [7, 8], the potential impact of these changes on the relationship between DEHP and adiponectin has yet to be explored.

Epidemiological studies exploring the correlation between DEHP exposure and adiponectin levels are limited, and the findings are conflicting. While some research has identified a positive correlation between DEHP exposure and adiponectin levels [21, 22], others have found a negative relationship [23]. Furthermore, these studies have primarily focused on children, women, and patients with diabetes mellitus, leaving a gap in knowledge about the effects in adolescents and young adults. In an effort to address this gap and better understand the relationship between DEHP exposure, serum adiponectin levels, and ACE gene polymorphism/epigenetic modification, we conducted a cross-sectional study among Taiwanese adolescents and young adults using 5mdC/dG, a marker of global DNA methylation, as a marker of epigenetic modification. The aim of this study was to examine the relationship between DEHP exposure and serum adiponectin levels in young people, as well as the role that ACE gene polymorphism/epigenetic modification may play in this association.

Materials and methods

Study population and data collection

Between 2006 and 2008, we conducted a cohort study (YOTA, Young TAiwanese Cohort Study) of 886 young Taiwanese individuals (aged 12–30) selected from a nationwide urine screening program [24]. The study received approval from the National Taiwan University Hospital Research Ethics Committee, and participants were enrolled after providing informed consent. We excluded 17 individuals with diabetes because their medications could potentially affect adiponectin levels [25]. Another 17 participants were excluded due to a lack of data on urine DEHP metabolites, and an additional 153 subjects were excluded due to a lack of data on global DNA methylation or serum adiponectin. A total of 699 participants were included in the final analysis. More detailed information can be found in Additional file 1.

Anthropometric and biochemical data

In this study, we conducted a comprehensive analysis of various demographic, lifestyle, and medical factors among a group of study participants. We collected data on age, gender, household income, smoking status, alcohol consumption, and past medical history, including hypertension and diabetes mellitus. We also measured body measures such as the z-score of body mass index (BMI) and systolic blood pressure (SBP). Blood samples were taken from all participants after an overnight fast, and commercially available kits were used to measure serum levels of insulin (Immulite 2000; RRID: AB_2750939; Siemens Healthcare Diagnostics;) and adiponectin (Human Adiponectin/Acrp30 Immunoassay; RRID: AB_2783020; R&D Systems, Minneapolis, MN). In addition, we measured a range of other biochemistry parameters, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, and the homeostasis model assessment of insulin resistance index (HOMA-IR) and β-cell function (HOMA-β), were also measured. The complete details of our methods are provided in Additional file 1.

Measurements of urine DEHP concentrations

Once inside the human body, DEHP is catalyzed into MEHP by lipases and esterases. A range of byproducts are subsequently generated, including mono(ethyl-5-hydroxyhexyl) phthalate (MEHHP) and mono(2-ethly-5-oxoheyl) phthalate (MEOHP)). Our previous research study introduced the detailed methods [26]. The lower limit of detection (LOD) for this study was 0.5 ng/mL. For concentrations that fell below this threshold, we used a value equal to the LOD divided by the square root of 2 in our analyses. Additional information on this method can be found in Additional file 1.

Analysis of leukocyte global DNA methylation levels

In this study, we measured 5mdC/dG and adjusted for the corresponding 15N-labeled internal standards. The detailed method for this measurement has been previously described in our studies [27]. Additional information on this method can be found in Additional file 1.

Genotyping of ACE gene alleles

DNA was extracted from peripheral leukocytes of volunteers using saline–EDTA extraction. Genotyping of the ACE alleles (D/D, I/D, I/I) was conducted using real-time polymerase chain reaction with fluorescently labeled primers [28, 29]. The complete details are provided in Additional file 1: Methods section.

Statistical analysis

DEHP metabolites, adiponectin, and 5mdC/dG were expressed as geometric means with standard error, and their levels were compared using Student's two-tailed t-test or one-way analysis of variance in different subgroups. We also examined the relationship between and DEHP metabolites, adiponectin, 5mdC/dG, and markers of glucose homeostasis using multiple linear regression analysis. The model was adjusted for age, gender, BMI z score, smoking status, drinking status, and family income. Due to deviation from normal distribution in the levels of DEHP metabolites, 5mdC/dG, and adiponectin, we employed a natural logarithm transformation (ln) for these three values. In the analysis, unstandardized regression coefficients were utilized to indicate the degree of change in the dependent variable that is related to a one-unit alteration in the independent variable. To evaluate the dose response relationship, DEHP metabolites were also stratified across the population into quartiles. To gain further insights, we analyzed the data to examine the connection between ln-adiponectin and ln-MEHP levels at different levels of 5mdC/dG (cut at the 50th percentile) and at different ACE genotypes. We calculated cross product terms to estimate the interaction in these analyses. We also used a structural equation model (SEM) to explore the relationships between MEHP, 5mdC/dG, and adiponectin. In the SEM, we posited that adiponectin was modified by MEHP both directly and indirectly through 5mdC/dG, and used the same covariates as in the multiple linear regression analysis. We analyzed the data using IBM SPSS Amos version 23, and considered a P-value of less than 0.05 to be statistically significant.

Results

In this study, 286 male and 413 female participants aged 21.45 years old (between the ages of 12 and 30) were included. The detection rate of urine DEHP metabolites was 78.4%. The geometric means (S.E.) of the DEHP metabolites, adiponectin, and 5mdC/dG in the different subgroups are presented in Table 1. Urine MEHP concentrations were found to be higher among participants aged 12–19, whereas urine MEOHP levels were elevated in females and individuals with lower BMI z scores. Serum adiponectin levels were higher in females, lower BMI z scores, and subjects without hypertension. Higher 5mdC/dG percentage was found in subjects with current alcohol consumption and higher BMI z scores. In the other subgroups, no significant association was found. Multiple linear regression models were used to examine the relationship between CVD risk factors and a one-unit increase in natural ln-DEHP metabolites, ln-adiponectin, and ln-5mdC/dG. The results are presented in Additional file 1: Table S1. A one-unit increase in ln-MEHP and ln-5mdC/dG was positively correlated with BMI z scores. Ln-adiponectin levels were negatively associated with BMI z scores and LDL-C, while positively associated with HDL-C. The mean of CVD risk factors across ACE gene alleles is demonstrated in Additional file 1: Table S2. Between CVD risk factors and ACE gene alleles, no significant associations were found.

Table 1 Geometric means (S.E.) of the urine DEHP metabolites, serum adiponectin, and 5mdC/dG in different subgroups
Full size table

Multiple linear regression models were used to examine the relationship between markers of glucose homeostasis, adiponectin, and 5mdC/dG and a one-unit increase in ln-urine phthalates metabolites, adiponectin, and 5mdC/dG. The results are presented in Table 2. Our findings indicate that MEHP concentrations negatively affect adiponectin levels and positively influence insulin, HOMA-IR, HOMA-β, and 5mdC/dG. Adiponectin levels were inversely related to insulin, HOMA-IR, HOMA-β, and 5mdC/dG while 5mdC/dG was positively associated with insulin, HOMA-IR, HOMA-β, and negatively linked to adiponectin. The geometric mean of adiponectin and 5mdC/dG levels across quartiles of MEHP levels is demonstrated in Table 3. The mean levels of adiponectin significantly decreased with increasing quartiles of MEHP (P for trend < 0.001) while the mean 5mdC/dG percentage rose with quartiles of MEHP (P for trend < 0.001).

Table 2 Unstandardized regression coefficients (standard error) of markers of glucose homeostasis, ln-adiponectin, and ln-5mdC/dG with a one-unit increase in ln-urine DEHP metabolites, ln-adiponectin, and ln-5mdC/dG in multiple linear regression models
Full size table
Table 3 Geometric mean (SE) of adiponectin and 5mdC/dG across quartiles of MEHP in multiple linear regression models
Full size table

Table 4 shows the unstandardized regression coefficients of the ln-adiponection with a one-unit increase in the ln-MEHP level for different categories of the 5mdC/dG levels and ACE gene categories. The study found that when the 5mdC/dG level was above the 50th percentile (Adjusted β (SE), P value = 0.002), the ln-MEHP level was negatively correlated with adiponectin. Additionally, when the 5mdC/dG level was above the 50th percentile, the unstandardized regression coefficient was lower than below the 50th percentile (− 0.095 vs. -0.049) and a statistically significant P value of interaction (0.038). MEHP levels were found to be negatively correlated with adiponectin levels when the ACE genotype was I/I. However, the P value for this interaction was borderline significant (0.060). The SEM for MEHP, 5mdC/dG, and adiponectin is shown in Fig. 1. It was discovered that ln-MEHP levels were positively correlated with ln-5mdC/dG levels, and negatively correlated with ln-adiponectin levels. Additionally, ln-5mdC/dG levels were found to be negatively correlated with ln-adiponectin levels. The goodness of fit index, which was greater than 0.9, the normed fit index, which was also greater than 0.9, and the root mean square, which was lower than 0.05, all indicated that the model fit well.

Table 4 Unstandardized regression coefficients (standard error) of ln-adiponectin levels with a one-unit increase in ln-MEHP concentration by different categories of 5mdC/dG and ACE gene polymorphism and their cross product in analysis
Full size table
Fig. 1
figure 1

Relationship between MEHP, 5mdC/dG, and adiponectin in the structural equation model. *Unstandardized regression coefficients

Full size image

Discussion

In this study, we found that MEHP concentrations were negatively correlated with adiponectin and positively correlated with markers of glucose homeostasis, including insulin, HOMA-IR, and HOMA-β. We also discovered that MEHP had a direct negative association with adiponectin and an indirect negative impact on adiponectin via its relationship with 5mdC/dG in the SEM. In subgroup analysis, we observed a negative correlation between MEHP and adiponectin in individuals with the I/I ACE genotype, but not in others, although the P value for this interaction was borderline significant. This study is the first to examine the relationship between DEHP exposure, epigenetic modifications, ACE gene polymorphism, and adiponectin levels. Our findings suggest that epigenetic changes may be involved in the mechanism of DEHP-induced decreases in adiponectin concentrations.

Increased levels of MEHP in urine were found to be associated with indicators of glucose regulation, including insulin, HOMA-IR, and HOMA-β in this study. The balance between increased insulin resistance and β-cell function has no impact on blood glucose. Earlier research has demonstrated that DEHP exposure can alter glucose homeostasis in animal models [30, 31]. Some epidemiological studies have identified a relationship between DEHP exposure and insulin resistance and the prevalence of diabetes mellitus [32, 33]. In contrast, a different study did not find a relationship in an elderly population [34]. The differences in these studies might be a result of the diverse demographics of the study participants.

Several endocrine disruptors, such as bisphenol A and polyfluoroalkyl substances, have been associated with adiponectin levels [35, 36]. DEHP treatment has been shown to decrease adiponectin levels in experimental studies. In a human cell culture model, a low dose of DEHP resulted in decreased adiponectin levels and increased generation of oxygen-derived free radicals in the supernatant of treated adipocytes [10]. In rats, high-dose DEHP led to the secretion of inflammatory cytokines, disturbed lipid metabolism, and decreased adiponectin levels [11]. Additionally, high-dose DEHP has been reported to impair fertility and decrease the expression of PPARγ mRNA and adiponectin in female mice [12]. Besides mechanisms mentioned above, DEHP exposure may activate RAAS, in which aldosterone may downregulate serum levels of adiponectin [6]. The mechanisms by which DEHP affects RAAS include increasing ACE levels [13], inhibiting 11β-HSD-2 activity [14]. Furthermore, DEHP exposure could potentially increase the likelihood of obesity [37], and adipocytes are capable of producing and releasing aldosterone, which has direct negative effect on adiponectin [6, 38]. Previous research has indicated that inhibiting the RAAS can boost adiponectin levels in individuals with metabolic syndrome, and also improves expression of adiponectin in human preadipocyte cell lines [4].

The RAAS is a hormone system that is crucial for maintaining cardiovascular homeostasis and electrolyte balance. One of the components of RAAS is ACE, which is a type of enzyme called a zinc metallopeptidase. The main function of ACE is to convert angiotensin 1 into angiotensin II, a hormone that constricts blood vessels and elevates blood pressure. ACE also inactivates bradykinin, a molecule that promotes the dilation of blood vessels and lowers blood pressure. [15]. The ACE gene is located on chromosome 17q23 and is made up of 21 kilobases of DNA. The gene contains a polymorphism in the sequence of its intron 16. There are three genotypes that result from this polymorphism: those with two copies of the insertion (I/I), those with one copy of the insertion and one copy of the deletion (I/D), and those with two copies of the deletion (D/D). Individuals with the DD genotype have the highest serum ACE levels, followed by those with the I/D genotype, and finally those with the I/I genotype [39]. The ID and DD genotypes have been linked to a greater risk of CVD in several studies [15, 16]. While previous studies have looked at the relationship between DEHP exposure and adiponectin, none have specifically explored the role of ACE polymorphism in this association. Our study found that the inverse relationship between MEHP and adiponectin was only evident in individuals with the I/I ACE genotype. However, the P-value for interaction was only borderline significant, and there are two possible explanations for these results. Firstly, the ACE genotype may modify the negative association between MEHP and adiponectin levels, and the insignificant P-value for interaction might be due to inadequate power or sample size to detect a significant effect. Specifically, the effect of MEHP on adiponectin concentration may be more pronounced in individuals with the I/I genotype who have low baseline ACE levels. Additionally, MEHP might influence the expression of the ACE gene through epigenetic mechanisms. Secondly, it is also possible that the significant correlation observed in the I/I genotype group is due to chance or random error, while the lack of correlation in the other genotype groups is simply due to data variability. There is no evidence of differential effects by ACE genotype. In summary, further research with larger sample sizes is necessary to confirm the results of our study.

Gene expression can be modified by epigenetic changes, which do not alter the DNA sequence [8]. The attachment of methyl groups to cytosine rings within guanine residues, a process called DNA methylation, is the most extensively investigated epigenetic modification due to its relative ease of measurement [7]. DNA methylation has been shown to predict the likelihood of developing diabetes, even when traditional risk factors are taken into account. It is also thought to be involved in the biological pathways connecting traditional risk factors to diabetes [40]. In this study, we found that higher levels of 5mdC/dG were associated with higher insulin levels, HOMA-IR, and β cell function. This aligns with recent research suggesting that changes in DNA methylation may impact glucose homeostasis [40].

We observed that lower levels of 5mdC/dG were related to higher levels of serum adiponectin. Previous studies have shown that epigenetic modifications can affect genes expression related to adiponectin [7, 8]. A Japanese study involving 232 pairs of monozygotic twins conducted an epigenetic variation association study to identify epigenetic regulators influencing adiponectin levels. The researchers found that methylation levels at 38 specific CpG sites were consistently linked to adiponectin levels. Additionally, they discovered that epigenetic modifications affecting adiponectin may be influenced by genes with diverse functions, such as glucose and lipid metabolism, rather than genes with a specific function [8]. Given that there are numerous genes that influence adiponectin levels, it is likely that global DNA methylation markers would be found to be related to adiponectin levels in this study.

The exact way underlying DEHP's disruption of DNA methylation is not yet understood. However, previous studies have shown that MEHP can cause oxidative DNA damage in human tissue cultures [41, 42]. DNA damage caused by oxidative stress may potentially disrupt proteins that bind to methylated cytosine and guanine residues and alter the function of DNA methyltransferases, leading to epigenetic modifications [43]. A majority of the studies examining the relationship between DEHP exposure, DNA methylation, and health outcomes have centered on investigating the impact on fertility and child development [44, 45] or atherosclerosis [19, 20]. Given the lack of understanding about the role of epigenetic modifications in the development of DEHP-related health issues, this study is the first to suggest that DNA methylation may be involved in the link between DEHP exposure and adiponectin levels.

Epidemiological study reports on the relationship between DEHP exposure and serum adiponectin levels are scarce and conflicting. One study showed the total levels of DEHP metabolites in urine (∑DEHP) were positively associated with serum adiponectin levels in 459 Korean women of reproductive age [22]. Furthermore, a study involving 167 Japanese mother–child pairs examined the relationship between maternal MEHP levels and cord blood adiponectin. The results showed that maternal blood MEHP levels measured during the third trimester were positively associated with cord blood adiponectin levels in boys [21]. On the other hand, a study found that urine levels of ∑DEHP were positively associated with tumor necrosis factor-α and negatively associated with serum adiponectin levels in subgroup of 329 Chinese adults who were diagnosed with diabetes mellitus and had higher BMI [23]. In our current study, we found that there is a negative correlation between urine levels of MEHP and serum adiponectin levels in a young population. The varied ethnicity, age, and gender of the research subjects may be the main reasons for the differing results.

The limitations of this study include the lack of causal inference in a cross-sectional cohort, the limited study population consisting of young Taiwanese individuals, the lack of consideration for other environmental pollutants, and the absence of measurements of methylation levels at specific gene loci.

Conclusions

In the YOTA cohort, we observed a positive correlation between urine levels of MEHP and 5mdC/dG and markers of glucose homeostasis, as well as a negative correlation between MEHP and serum adiponectin levels. Additionally, we found that there is a direct negative relationship between MEHP and adiponectin, meaning that higher levels of MEHP are associated with lower levels of adiponectin. We also observed an indirect negative association between MEHP and adiponectin through 5mdC/dG. These findings suggest that epigenetic changes may play a role in the pathological mechanism by which DEHP reduces adiponectin production. Our results provide new insight into the ways in which DEHP affects serum adiponectin levels and highlight the need for further research to better understand the health effects of DEHP.

Availability of data and materials

The raw datasets used in the current study are available from the corresponding author and with permission of National Taiwan University Hospital on reasonable request.

Abbreviations

11β-HSD-2:

11β Hydroxysteroid dehydrogenase type 2

ACE:

Angiotensin I-converting enzyme

BMI:

Body mass index

CVD:

Cardiovascular disease

DEHP:

Di-(2-ethylhexyl) phthalate

HDL-C:

High-density lipoprotein cholesterol

HOMA-IR:

Homeostasis model assessment of insulin resistance index

HOMA-β:

Homeostasis model assessment of β-cell function

LOD:

Lower limit of detection

LDL-C:

Low-density lipoprotein cholesterol

PPAR:

Peroxisome proliferator-activated receptor

MEHHP:

Mono(ethyl-5-hydroxyhexyl) phthalate

MEOHP:

Mono(2-ethly-5-oxoheyl) phthalate

RAAS:

Renin–angiotensin–aldosterone system

SEM:

Structural equation model

SBP:

Systolic blood pressure

YOTA:

Young TAiwanese Cohort Study

References

  1. Nguyen TMD. Adiponectin: role in physiology and pathophysiology. Int J Prev Med. 2020;11:136.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Khoramipour K, Chamari K, Hekmatikar AA, Ziyaiyan A, Taherkhani S, Elguindy NM, Bragazzi NL. Adiponectin: structure physiological functions role in diseases and effects of nutrition. Nutrients. 2021;13:1180.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Fang H, Judd RL. Adiponectin regulation and function. Compr Physiol. 2018;8:1031–63.

    Article  PubMed  Google Scholar 

  4. Tian F, Luo R, Zhao Z, Wu Y, Ban D. Blockade of the RAS increases plasma adiponectin in subjects with metabolic syndrome and enhances differentiation and adiponectin expression of human preadipocytes. Exp Clin Endocrinol Diabetes. 2010;118:258–65.

    Article  CAS  PubMed  Google Scholar 

  5. Furuhashi M, Ura N, Higashiura K, Murakami H, Tanaka M, Moniwa N, Yoshida D, Shimamoto K. Blockade of the renin-angiotensin system increases adiponectin concentrations in patients with essential hypertension. Hypertension. 2003;42:76–81.

    Article  CAS  PubMed  Google Scholar 

  6. Flynn C, Bakris GL. Interaction between adiponectin and aldosterone. Cardiorenal Med. 2011;1:96–101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Un Nisa K, Reza MI. Key relevance of epigenetic programming of adiponectin gene in pathogenesis of metabolic disorders. Endocr Metab Immune Disord Drug Targets. 2020;20:506–17.

    Article  PubMed  Google Scholar 

  8. Hasegawa M, Taniguchi J, Ueda H, Watanabe M. Twin study: genetic and epigenetic factors affecting circulating adiponectin levels. J Clin Endocrinol Metab. 2022;108:144–54.

    Article  PubMed  Google Scholar 

  9. Chang WH, Herianto S, Lee CC, Hung H, Chen HL. The effects of phthalate ester exposure on human health: a review. Sci Total Environ. 2021;786: 147371.

    Article  CAS  PubMed  Google Scholar 

  10. Schaedlich K, Gebauer S, Hunger L, Beier LS, Koch HM, Wabitsch M, Fischer B, Ernst J. DEHP deregulates adipokine levels and impairs fatty acid storage in human SGBS-adipocytes. Sci Rep. 2018;8:3447.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Zhou L, Chen H, Xu Q, Han X, Zhao Y, Song X, Zhao T, Ye L. The effect of di-2-ethylhexyl phthalate on inflammation and lipid metabolic disorder in rats. Ecotoxicol Environ Saf. 2019;170:391–8.

    Article  CAS  PubMed  Google Scholar 

  12. Schmidt JS, Schaedlich K, Fiandanese N, Pocar P, Fischer B. Effects of di(2-ethylhexyl) phthalate (DEHP) on female fertility and adipogenesis in C3H/N mice. Environ Health Perspect. 2012;120:1123–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Deng T, Xie X, Duan J, Chen M. Di-(2-ethylhexyl) phthalate induced an increase in blood pressure via activation of ACE and inhibition of the bradykinin-NO pathway. Environ Pollut. 2019;247:927–34.

    Article  CAS  PubMed  Google Scholar 

  14. Kirkley AG, Sargis RM. Environmental endocrine disruption of energy metabolism and cardiovascular risk. Curr Diab Rep. 2014;14:494.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Dhar S, Ray S, Dutta A, Sengupta B, Chakrabarti S. Polymorphism of ACE gene as the genetic predisposition of coronary artery disease in Eastern India. Indian Heart J. 2012;64:576–81.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Cambien F, Poirier O, Lecerf L, Evans A, Cambou JP, Arveiler D, Luc G, Bard JM, Bara L, Ricard S, et al. Deletion polymorphism in the gene for angiotensin-converting enzyme is a potent risk factor for myocardial infarction. Nature. 1992;359:641–4.

    Article  CAS  PubMed  Google Scholar 

  17. Liu S, Wang K, Svoboda LK, Rygiel CA, Neier K, Jones TR, Cavalcante RG, Colacino JA, Dolinoy DC, Sartor MA. Perinatal DEHP exposure induces sex- and tissue-specific DNA methylation changes in both juvenile and adult mice. Environ Epigenet. 2021;7:dvab004.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Chou CK, Huang HW, Yang CF, Dahms HU, Liang SS, Wang TN, Kuo PL, Hsi E, Tsai EM, Chiu CC. Reduced camptothecin sensitivity of estrogen receptor-positive human breast cancer cells following exposure to di(2-ethylhexyl)phthalate (DEHP) is associated with DNA methylation changes. Environ Toxicol. 2019;34:401–14.

    CAS  PubMed  Google Scholar 

  19. Lin CY, Lee HL, Hwang YT, Wang C, Hsieh CJ, Wu C, Sung FC, Su TC. The association between urine di-(2-ethylhexyl) phthalate metabolites, global DNA methylation, and subclinical atherosclerosis in a young Taiwanese population. Environ Pollut. 2020;265: 114912.

    Article  CAS  PubMed  Google Scholar 

  20. Lin CY, Chen CW, Lee HL, Wu C, Wang C, Sung FC, Su TC. Global DNA methylation mediates the association between urine mono-2-ethylhexyl phthalate and serum apoptotic microparticles in a young Taiwanese population. Sci Total Environ. 2022;808: 152054.

    Article  CAS  PubMed  Google Scholar 

  21. Minatoya M, Araki A, Miyashita C, Sasaki S, Goto Y, Nakajima T, Kishi R. Prenatal di-2-ethylhexyl phthalate exposure and cord blood adipokine levels and birth size: the Hokkaido study on environment and children’s health. Sci Total Environ. 2017;579:606–11.

    Article  CAS  PubMed  Google Scholar 

  22. Lee I, Kim S, Park S, Mok S, Jeong Y, Moon HB, Lee J, Kim S, Kim HJ, Choi G, et al. Association of urinary phthalate metabolites and phenolics with adipokines and insulin resistance related markers among women of reproductive age. Sci Total Environ. 2019;688:1319–26.

    Article  CAS  PubMed  Google Scholar 

  23. Duan Y, Wang L, Han L, Wang B, Sun H, Chen L, Zhu L, Luo Y. Exposure to phthalates in patients with diabetes and its association with oxidative stress, adiponectin, and inflammatory cytokines. Environ Int. 2017;109:53–63.

    Article  CAS  PubMed  Google Scholar 

  24. Lin CY, Wen LL, Lin LY, Wen TW, Lien GW, Hsu SH, Chien KL, Liao CC, Sung FC, Chen PC, Su TC. The associations between serum perfluorinated chemicals and thyroid function in adolescents and young adults. J Hazard Mater. 2013;244–245:637–44.

    Article  PubMed  Google Scholar 

  25. Katsiki N, Mikhailidis DP, Gotzamani-Psarrakou A, Yovos JG, Karamitsos D. Effect of various treatments on leptin, adiponectin, ghrelin and neuropeptide Y in patients with type 2 diabetes mellitus. Expert Opin Ther Targets. 2011;15:401–20.

    Article  CAS  PubMed  Google Scholar 

  26. Lin CY, Hsieh CJ, Lo SC, Chen PC, Torng PL, Hu A, Sung FC, Su TC. Positive association between concentration of phthalate metabolites in urine and microparticles in adolescents and young adults. Environ Int. 2016;92–93:157–64.

    Article  PubMed  Google Scholar 

  27. Liou SH, Wu WT, Liao HY, Chen CY, Tsai CY, Jung WT, Lee HL. Global DNA methylation and oxidative stress biomarkers in workers exposed to metal oxide nanoparticles. J Hazard Mater. 2017;331:329–35.

    Article  CAS  PubMed  Google Scholar 

  28. Chen S, Hao Q, Yang M, Yue J, Cao L, Liu G, Zou C, Ding X, Pu H, Dong B. Association between angiotensin-converting enzyme insertion/deletion polymorphisms and frailty among Chinese older people. J Am Med Dir Assoc. 2015;16(438):e431-436.

    Google Scholar 

  29. Seripa D, Paroni G, Matera MG, Gravina C, Scarcelli C, Corritore M, D’Ambrosio LP, Urbano M, D’Onofrio G, Copetti M, et al. Angiotensin-converting enzyme (ACE) genotypes and disability in hospitalized older patients. Age (Dordr). 2011;33:409–19.

    Article  CAS  PubMed  Google Scholar 

  30. Zhang W, Shen XY, Zhang WW, Chen H, Xu WP, Wei W. Di-(2-ethylhexyl) phthalate could disrupt the insulin signaling pathway in liver of SD rats and L02 cells via PPARγ. Toxicol Appl Pharmacol. 2017;316:17–26.

    Article  CAS  PubMed  Google Scholar 

  31. Xu J, Zhou L, Wang S, Zhu J, Liu T, Jia Y, Sun D, Chen H, Wang Q, Xu F, et al. Di-(2-ethylhexyl)-phthalate induces glucose metabolic disorder in adolescent rats. Environ Sci Pollut Res Int. 2018;25:3596–607.

    Article  CAS  PubMed  Google Scholar 

  32. Zhang H, Ben Y, Han Y, Zhang Y, Li Y, Chen X. Phthalate exposure and risk of diabetes mellitus: implications from a systematic review and meta-analysis. Environ Res. 2022;204: 112109.

    Article  CAS  PubMed  Google Scholar 

  33. Gao H, Chen D, Zang M. Association between phthalate exposure and insulin resistance: a systematic review and meta-analysis update. Environ Sci Pollut Res Int. 2021;28:55967–80.

    Article  CAS  PubMed  Google Scholar 

  34. Lind PM, Zethelius B, Lind L. Circulating levels of phthalate metabolites are associated with prevalent diabetes in the elderly. Diabetes Care. 2012;35:1519–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Lin CY, Wen LL, Lin LY, Wen TW, Lien GW, Chen CY, Hsu SH, Chien KL, Sung FC, Chen PC, Su TC. Associations between levels of serum perfluorinated chemicals and adiponectin in a young hypertension cohort in Taiwan. Environ Sci Technol. 2011;45:10691–8.

    Article  CAS  PubMed  Google Scholar 

  36. Menale C, Grandone A, Nicolucci C, Cirillo G, Crispi S, Di Sessa A, Marzuillo P, Rossi S, Mita DG, Perrone L, et al. Bisphenol A is associated with insulin resistance and modulates adiponectin and resistin gene expression in obese children. Pediatr Obes. 2017;12:380–7.

    Article  PubMed  Google Scholar 

  37. Ribeiro C, Mendes V, Peleteiro B, Delgado I, Araújo J, Aggerbeck M, Annesi-Maesano I, Sarigiannis D, Ramos E. Association between the exposure to phthalates and adiposity: a meta-analysis in children and adults. Environ Res. 2019;179: 108780.

    Article  CAS  PubMed  Google Scholar 

  38. Briones AM, Nguyen Dinh Cat A, Callera GE, Yogi A, Burger D, He Y, Corrêa JW, Gagnon AM, Gomez-Sanchez CE, Gomez-Sanchez EP, et al. Adipocytes produce aldosterone through calcineurin-dependent signaling pathways: implications in diabetes mellitus-associated obesity and vascular dysfunction. Hypertension. 2012;59:1069–78.

    Article  CAS  PubMed  Google Scholar 

  39. Rigat B, Hubert C, Alhenc-Gelas F, Cambien F, Corvol P, Soubrier F. An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J Clin Invest. 1990;86:1343–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kaimala S, Kumar CA, Allouh MZ, Ansari SA, Emerald BS. Epigenetic modifications in pancreas development, diabetes, and therapeutics. Med Res Rev. 2022;42:1343–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wang X, Jiang L, Ge L, Chen M, Yang G, Ji F, Zhong L, Guan Y, Liu X. Oxidative DNA damage induced by di-(2-ethylhexyl) phthalate in HEK-293 cell line. Environ Toxicol Pharmacol. 2015;39:1099–106.

    Article  CAS  PubMed  Google Scholar 

  42. Ozkemahli G, Erkekoglu P, Ercan A, Zeybek ND, Yersal N, Kocer-Gumusel B. Effects of single or combined exposure to bisphenol A and mono(2-ethylhexyl)phthalate on oxidant/antioxidant status, endoplasmic reticulum stress, and apoptosis in HepG2 cell line. Environ Sci Pollut Res Int. 2022;30:12189–206.

    Article  PubMed  Google Scholar 

  43. Valinluck V, Tsai HH, Rogstad DK, Burdzy A, Bird A, Sowers LC. Oxidative damage to methyl-CpG sequences inhibits the binding of the methyl-CpG binding domain (MBD) of methyl-CpG binding protein 2 (MeCP2). Nucleic Acids Res. 2004;32:4100–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Tian M, Liu L, Zhang J, Huang Q, Shen H. Positive association of low-level environmental phthalate exposure with sperm motility was mediated by DNA methylation: a pilot study. Chemosphere. 2019;220:459–67.

    Article  CAS  PubMed  Google Scholar 

  45. Huang LL, Zhou B, Ai SH, Yang P, Chen YJ, Liu C, Deng YL, Lu Q, Miao XP, Lu WQ, et al. Prenatal phthalate exposure, birth outcomes and DNA methylation of Alu and LINE-1 repetitive elements: a pilot study in China. Chemosphere. 2018;206:759–65.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank all of the subjects who participated in this study.

Funding

This study was funded by grants from the Ministry of Science and Technology of Taiwan NSC 106–2314-B-385–001 and NSC 110–2314-B-385–001-MY3.

Author information

Authors and Affiliations

  1. Department of Internal Medicine, En Chu Kong Hospital, New Taipei City, 237, Taiwan

    Chien-Yu Lin

  2. School of Medicine, Fu Jen Catholic University, New Taipei City, 242, Taiwan

    Chien-Yu Lin

  3. Department of Environmental Engineering and Health, Yuanpei University of Medical Technology, Hsinchu, 300, Taiwan

    Chien-Yu Lin & Chikang Wang

  4. Department of Chemistry, Fu Jen Catholic University, New Taipei City, 242, Taiwan

    Hui-Ling Lee

  5. Department of Cardiology, National Taiwan University Hospital Yunlin Branch, Yunlin, 640, Taiwan

    Ching-Way Chen

  6. Department of Health Services Administration, College of Public Health, China Medical University, Taichung, 404, Taiwan

    Fung-Chang Sung

  7. Department of Environmental and Occupational Medicine, National Taiwan University Hospital, Taipei, 10002, Taiwan

    Ta-Chen Su

  8. Department of Internal Medicine and Cardiovascular Center, National Taiwan University Hospital, Taipei, 100, Taiwan

    Ta-Chen Su

  9. Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, 100, Taiwan

    Ta-Chen Su

  10. The Experimental Forest, National Taiwan University, Nantou, 558, Taiwan

    Ta-Chen Su

Authors
  1. Chien-Yu Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hui-Ling Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ching-Way Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chikang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fung-Chang Sung
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ta-Chen Su
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CL was responsible for developing the theoretical concept, manuscript drafting, and performing the analytic calculations. HL provided expertise in the analysis of global DNA methylation and contributed to the development of the analytic method. CC assisted with the analytic calculations. CW played a key role in the analysis of phthalate metabolites and helped to write the analytic method. FS was instrumental in the recruitment of study participants, designed the data collection instruments and collected data. TS contributed to the development of the theoretical concept, recruitment of study participants, and analysis of covariates, and provided valuable input in the critical discussion of the manuscript. The final version of the manuscript was a collaborative effort, with all authors contributing to its development. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ta-Chen Su.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the National Taiwan University Hospital Research Ethics Committee (NTUH-9561705054).

Competing interest

The authors declare that there are no competing financial interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

Materials and Methods and Tables.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, CY., Lee, HL., Chen, CW. et al. The role of angiotensin I-converting enzyme gene polymorphism and global DNA methylation in the negative associations between urine di-(2-ethylhexyl) phthalate metabolites and serum adiponectin in a young Taiwanese population. Clin Epigenet 15, 87 (2023). https://doi.org/10.1186/s13148-023-01502-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13148-023-01502-z

Keywords

Clinical Epigenetics

ISSN: 1868-7083

Contact us