Endocrine-Disrupting Chemicals and type 2 diabetes: what  is their relationship?

Summary of all research performed in the Department of Endocrinology of the UMCG, on endocrine disruptors, obesity and type 2 diabetes through a personal researcher grant awarded by DiabetesFonds Nederland to dr Jana van Vliet-Ostaptchouk.


Endocrine disrupting chemicals (EDCs) are exogenous compounds with the potential to disturb hormonal regulation and the endocrine system, consequently affecting health and reproduction in animals and humans (1). EDCs can interfere with the production, release, metabolism, and elimination of or can mimic the occurrence of natural hormones. Parabens, bisphenols and phthalates are EDCs which have in common that even though having lipophilic properties, they are quickly metabolized into more water-soluble chemicals. These chemicals in turn are easily excreted via the kidneys from the body. Due to their short half-lives of less than 24 hour, these chemicals are considered to be non-persistent (2-4). In contrast, persistent EDCs are often more resilient to metabolic degradation, making it harder to excrete these chemicals. For example, polychlorinated biphenyls (PCBs) contain chlorine atoms, which make hydroxylation by the liver much harder and leads to half-live times of months to decades. As a result, PCBs are still widely detected in blood regardless of the fact that they have been banned at least in part in Europe in 1985. Even though non-persistent EDCs are easily metabolized and excreted, their use in a wide variety of daily used consumer products has led to an ubiquitous exposure around the world.

For example, bisphenol A (BPA), 2,2-bis(4-hydroxyphenyl)propane, is a synthetic compound that is widely used as a monomer in polycarbonate plastics and epoxy resins, being one of the world’s highest production volumechemicals (Source: paper #13, Environ Int 2015). This means that humans are widely exposed to chlorinated derivatives and structural analogs of bisphenol A.

Exposure to EDCs may play an important role in the global escalating incidence of type 2 diabetes observed in the last few decades (5). Based on the observations that EDCs interfere with the body’s endocrine system, a connection between EDC and altered glucose metabolism and increased risk for T2D is proposed. This project aimed to investigate how EDC determine the risk of T2D and to pinpoint the underlying pathophysiological mechanisms. Our hypothesis was that chronic daily exposure to EDC increases the risk of developing T2D through a cascade of adverse metabolic changes. We performed systematic analysis of EDC-related changes (single and multiple EDC effects) in metabolic functioning, epigenetics and gene expression patterns, combined with an analysis of individual genetic profiles and lifestyle. This strategy aimed to uncover mechanisms underlying EDC-induced metabolic dysregulation. Our main objectives were:

  1. To investigate whether exposures to EDC as measured in urine increase the risk of T2D and how this risk is modified by lifestyle and genetic predisposition
  2. To examine the effects of EDC on metabolism and to establish EDC-related alterations in gene function (i.e. DNA methylation and gene expression)


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Preparing the laboratory methodology

As parabens, bisphenols and phthalates have been receiving a growing amount of attention over the decades, the need to quantify these EDCs has resulted in the development of different analytical methods. ELISA techniques are unable to reliably measure low concentrations and is easily affected by irregular noise (6), and only allow to measure one EDC at a time. Gas chromatography combined with mass spectrometry (GC–MS) does enable the quantification of multiple EDCs at low concentrations, but often requires a time intensive derivatization steps. In contrast, liquid chromatography tandem mass spectrometry (LC-MS/MS) does not require derivatization while this technique is able to measure multiple compounds simultaneously. Therefore, we developed two ultra-performance LC-MS/MS methods for the measurement in urine of 21 different EDCs with lower runtimes compared to methods described in literature (7–13). Our newly developed method (source: paper #7, J Anal Toxicol. 2019) showed high levels of agreement with a previous European project in this area, which thus allows to reliably measure parabens, bisphenols and phthalates in urine samples. Currently our group is the only center where these EDCs can be measured reliably.


Table 1. EDCs assessed with LCMS-MS technique















As the EDCs of interest are largely excreted within 24 hours after administration (14–16), we chose to use 24 hour urine samples for the determination of recent exposure to EDCs. This approach has shown less variation in EDC concentrations and fewer samples had high exposure outliers (17), without need for additional adjustments such as creatinine (18-20).








Figure. Representative LC–MS-MS extracted ion chromatograms of a human urine sample fortified with phenols or phthalates.



Epidemiologic studies on EDCs

Several countries use surveillance programs for exposure to EDC such as the National Health and Nutrition Examination Survey (NHANES; US), the Canadian Health Measures Survey (CHMS), the Korean National Environmental Health Survey (KoNEHS) and the German Environmental Specimen Bank (ESB) to monitor exposure (21,22), or through active research programs (23,24). Only few studies have examined EDC exposure in the Netherlands (25–27).  We investigated change in indicators of EDC exposure between 2009 and 2016 and assessed its consistency between and within individuals over a median follow-up time of 47 months in a sample of Dutch individuals (source: paper #3, Environ Res. 2021). Of 500 Dutch individuals, two 24 h urine samples were analyzed for 5 parabens, 3 bisphenols and 13 metabolites of in total 8 different phthalates. We calculated per-year differences using meta-analysis and assessed temporal correlations between and within individuals using Spearman correlation coefficients, intra-class correlation coefficients (ICC) and kappa-statistics.


Figure. Correlations between endocrine disrupting chemicals at different timepoints.




Figure. Consistency of endocrine disrupting chemicals over different timeframes


We found a secular decrease in concentrations of methyl, ethyl, propyl and n-butyl paraben, bisphenol A, and metabolites of di-ethyl phthalate (DEP), di-butyl phthalate (DBP), di-(2-ethyl-hexyl) phthalate (DEHP), and butylbenzyl phthalate (DBzP) which varied from 8 to 96% (ethyl paraben, propyl paraben) between 2009 and 2016. Within-person temporal correlations were highest for parabens (ICC: 0.34 to 0.40) and poorest for bisphenols (ICC: 0.15 to 0.23). For phthalate metabolites, correlations decreased most between time periods (ICC < 48 months: 0.22 to 0.39; ≥48 months: 0.05 to 0.32). When categorizing EDC concentrations, 33–54% of individuals remained in the lowest or highest category and temporal correlations were similar to continuous measurements. Overall, we found EDC concentrations in this general Dutch population to be in line with concentrations reported in other countries (21–23,25,26). Moreover, concentrations of most EDCs within individuals decreased over time between 2009 and 2016, an effect also observed in populations from the US, Denmark and Germany (21,24). A number of paraben and bisphenol concentrations showed strong decreases from one year to another, which coincides with the introduction of specific European legislation to restrict EDCs in consumer products (28,29). Concentrations of analogues such as bisphenol F were stable over time, a trend also reported in literature (24,30). As some legislation has recently (i.e. January and July 2020) become active (31,32) and the deadline of others is due the following year (33), exposure is expected to further change in the future. As chemicals such as bisphenol F and bisphenol S have been proved to possess similar hormonal activity and endocrine disrupting effects as bisphenol A (34), they should be included in future biomonitoring studies.


Figure. Associations between change in adiposity-related traits within and between individuals and change in EDC excretions during a diet-induced weight loss program.


In a post-hoc analysis of the Lifestyle, OverWeight, Energy Restriction (LOWER) study from the Netherlands, we investigated the effect of a dietary intervention driven reduction in adipose tissue on the magnitude of urinary EDC exposure and mobilization, and whether higher EDC exposure leads to impaired weight loss in 218 obese individuals (source: paper #2, Environ Res. 2021). Five parabens, three bisphenols and thirteen metabolites of eight phthalates were measured in 24-h urine using LC-MS/MS, before and after three-months of a calorie-restricted weight reduction intervention program. Associations between adiposity-related traits and EDCs were tested using multivariable linear regression and linear mixed effects models. A multiple testing correction based on the false discovery rate (FDR) was applied. After the 3-month intervention, urinary paraben and bisphenol excretions remained similar. Excretions of mono-butyl phthalates and most high-molecular-weight phthalates decreased, whereas mono-ethyl phthalate increased (all FDR<0.05). A reduction in adipose tissue was not associated with higher urinary EDC excretions. Higher baseline EDC excretions were associated with higher post-intervention body-mass index (methyl-, propylparaben), waist circumference (propylparaben, mono-n-butyl phthalate, mono-benzyl phthalate), and body fat percentage (mono-ethyl phthalate, mono-benzyl phthalate). Associations between parabens and body-mass index, and mono-benzyl phthalate and waist circumference and body fat percentage remained after multiple testing correction (all FDR<0.05).

We found the exposure to parabens to be independent of food products, which is in line with their main use in personal care and cosmetic products, and the literature pointing towards the main route of exposure to be transdermal (35,36). On the other hand, bisphenol A is used in a wide variety of food products (37), and concentrations have been shown to decline during a short period of fasting (38). We observed that exposure to bisphenol A concentrations remained similar over a period of dietary weight loss. As the median bisphenol A concentration at baseline was nearly half of that reported in a general Dutch population, a change in type of food products rather than a quantitative restriction could have led to a decrease in exposure. Indeed, exposure to bisphenol A can be substantially reduced by avoiding specific nutritional products (39). The decrease which we observed in exposure to high molecular weight phthalates as a result of the dietary intervention is in line with food products being the main source of exposure (40,41). Most low molecular weight phthalates remained stable during the dietary intervention, further confirming their non-dietary routes of exposure (36,42). Yet, MEP concentrations showed a strong increase, suggesting that specific food products play an important role in its exposure. A similar effect has been reported in a weight loss study, in which the absolute concentration of MEP decreased, but its proportion compared to other phthalates increased (43). Two studies have shown associations between high MEP concentrations and vegetable consumption (44,45), which may explain the source of increased exposure. Given its purported obesogenic properties (46), this increase is alarming and future research should further elicit its source of exposure in relation to weight reduction.



Figure. Multivariate associations between lipid-related traits and urinary paraben, bisphenol and phthalate concentrations in the Lifelines population (n = 662).


High exposure to EDCs has been associated with adverse metabolic outcomes such as obesity and type 2 diabetes (50-53). As few studies have investigated the exposure to EDCs and cardiometabolic health taking lifestyle into account. We aimed to assess exposure to five parabens, three bisphenols and thirteen metabolites of in total eight phthalates in a general Dutch population and to investigate their association with cardiometabolic traits (Source: paper #5: Sci Rep. 2020). In 662 adult subjects from the population-based Lifelines cohort, 21 EDC compounds were measured in 24-hour urine collected in 2012, using LC-MS/MS. Association analyses between cardiometabolic traits and EDC concentrations were performed using multivariate linear models adjusting for age, sex, education, smoking, diabetes, physical activity and caloric intake. Quartile analyses were performed to assess linearity. BPA, four parabens and eight phthalate metabolites were detected in 84-100% of the samples. Adjusted associations for MiBP and MBzP and adiposity-related traits were robust for multiple testing (Beta’s, BMI: 1.12, 2.52; waist circumference: 0.64, 1.56, respectively; FDR < 0.009). Associations for triglyceride, HDL-cholesterol, glucose and blood pressure were not. Linearity was confirmed for significant associations. Exposure to EDCs in the Dutch population is ubiquitous. We found direct associations between phthalates and adiposity-related traits.

Of the three EDC groups of our interest, the obesogenic evidence of parabens in humans is weakest. Although some studies show significant associations between high paraben concentrations and increased adiposity-related traits (54,55), NHANES data suggest an opposite effect (56). We did not find a significant association between parabens and obesity-related traits, but did find that high paraben concentrations impair weight loss during the dietary intervention of the LOWER study, which was the first prospective study focusing on parabens so far. High concentrations of bisphenol A have been associated with obesity-related traits (4,57-59). We could not replicate these findings, and this could be population-specific. A number of reports based on NHANES data showed that high concentrations of phthalates were associated with higher body weight (60–62). Moreover, prospective studies link high baseline exposure to weight gain over time (4,46). Our results add to this growing body of evidence. Further, we found that high phthalate concentrations are associated with impaired weight reduction, suggesting obesogenic properties in a dynamic setting of weight loss.



Figure. Associations between type 2 diabetes and endocrine disrupting chemicals in middle-aged and older women


We also investigated associations between EDC concentrations and glycaemic traits (i.e. glucose, HbA1c), as well as the 5-year development of type 2 diabetes (Source: paper #1, currently under review). Several prospective studies have tested the association for parabens, bisphenols and phthalates with the development of type 2 diabetes (50–53,63), with conflicting results. Exposure to high EDC concentrations was not significantly associated with higher glucose and HbA1c levels in a cross-sectional setting. Moreover, higher EDCs were not significantly associated with the development of type 2 diabetes over time. When stratifying for age and sex, we did find significant inverse associations in middle-aged women. Direct associations between EDCs and type 2 diabetes have been previously described specifically in middle-aged and not older women (50), suggesting that this subpopulation is especially susceptible for the endocrine disrupting effects of these chemicals. This may be explained by the fact that concentrations of natural hormones are very different between males and females, but also between premenopausal and postmenopausal women. As EDCs interact with the same system, co-exposure and susceptibility from natural hormones may lead to different effects.

The limited consistency of EDCs over the course of multiple years as mentioned previously could only be partly ascribed to the decreasing temporal trend. The intra-individual consistency has been modest to poor (47) and this consistency further declined after a follow-up beyond the scope of previous studies (48,49). The impact of this is huge. The majority of studies base exposure to EDCs on a single baseline measurement (4,50–52), thereby incorrectly assuming that this single measurement is representative for the exposure during the development of the disease. In our study on associations between EDCs and the development of type 2 diabetes we found that the inclusion of a repeated measurement at follow-up impacted the associations. This underlines the importance of repeated measurements in EDC-focused research. Although many studies evaluate low with high exposure to EDCs (51–53), our studies do not show that the categorization of EDCs improves the reproducibility compared to continuous variables.




In addition to EDCs like bisphenols and phthalates, other chemical compounds may be associated with incidence of type 2 diabetes. These may be environmental chemicals like disinfection byproducts (trihalomethanes, THM composed of chloroform, TCM and brominated trihalomethanes, BrTHM). In order to assess the association between THM and incident type 2 diabetes, we explored alterations in metabolic profiles due to THM exposures or type 2 diabetes status in both the HUNT cohort (Norway) and the Lifelines cohort (Netherlands) (Source: paper #8, Metabolomics). Urinary biomarkers of THM exposure and mass spectrometry-based serum metabolomics were performed.

The data revealed that low median THM exposures were found in both cohorts (cases and controls of HUNT and Lifelines, respectively). Neither compounds BrTHM nor TCM were associated with previously diagnosed or newly developed type 2 diabetes. Untargeted metabolomics analysis using Ultra High Performance Liquid Chromatography tandem Mass Spectrometry (UHPLC-MS/MS) showed that 48 metabolites associated with incident type 2 diabetes, which remained statistically robust after adjusting for sex, age and BMI, whereas a total of 244 metabolites were associated with prevalent type 2 diabetes. A total of 34 metabolites were associated with the progression of type 2 diabetes. These metabolic markers included -amongst others- HDL, glycosylceramide, cholesterol, hydrocinnamate, mannose (see the table and the full paper for more details). The study also identified that some metabolites, such as cinnamoylglycine and 1-methylurate, were protective of type 2 diabetes. The conclusion of this study was that so-called exposome-based approaches in cohort studies are warranted to better understand the environmental origins in the pathogenesis of diabetes. However, the specific compounds of interest BrTHM and TCM were not associated with the risk to develop type 2 diabetes.


Brain tissue studies

In two separate studies we assessed the possibility that EDCs may accumulate in the brain and exert their effect through influencing specific brain regions, for instance the hypothalamus. In the first study, we aimed to explore the presence of bisphenol A (BPA), bisphenol F (BPF) and chlorinated BPA (ClBPA), collectively called the bisphenols, in different brain regions and their association with obesity using post-mortem hypothalamic and white matter brain material from twelve pairs of obese (body mass index (BMI) >30 kg/m2) and normal-weight individuals (BMI <25 kg/m2) (Source: paper #9, Sci Rep. 2018). Mean ratios of hypothalamus vs. white matter for BPA, BPF and ClBPA were 1.5, 0.92, 0.95, respectively, suggesting no preferential accumulation of the bisphenols in the grey matter (hypothalamic) or white matter-enriched brain areas. We observed differences in hypothalamic concentrations among the bisphenols, with highest median level detected for ClBPA (median: 2.4 ng/g), followed by BPF (2.2 ng/g) and BPA (1.2 ng/g); similar ranking was observed for the white matter samples (median for: ClBPA-2.5 ng/g, BPF-2.3 ng/g, and BPA-1.0 ng/g). Furthermore, all bisphenol concentrations, except for white-matter BPF were associated with obesity (p < 0.05). As this was the first study reporting the presence of bisphenols in two distinct regions of the human brain, we can not compare our data with those of other groups. The fact that bisphenols accumulate in the brain implies that they indeed are able to cross the blood-brain barrier.


Figure. Concentrations (mean ± SD) of bisphenol A (BPA) in hypothalamus and white‐matter brain tissue in all paired samples combined, controls, and obese cases.

Figure. Concentrations (mean ± SD) of bisphenol A (BPA) (A) and methyl paraben (MeP) (B) in paired hypothalamus tissues from controls (n = 12) and obese individuals (n = 12). *‐ p < 0.05.


In a follow-up study we found a higher quantity of EDCs in human hypothalamus compared to white matter brain tissue (Source: paper #12, Int J Environ Res Public Health. 2017). This may be explained by the central role the hypothalamus plays in hormonal signaling pathways, making it more susceptible to hormones due to a more permeable blood-brain-barrier and relatively high vascularity (64). Further, we found higher methyl paraben concentrations in the hypothalamus of obese compared to normal-weight individuals. As the hypothalamus plays a central role in energy homeostasis, methyl paraben may induce adiposity via a local disrupting effect in the hypothalamus.


For persistent EDCs, weight loss has been shown to lead to mobilization of EDCs from adipose tissue (65–67), increasing circulating concentrations and therewith potential hazardous effects. In case of obesogenic EDCs, this release in turn could lead to increased weight gain, creating a so-called yo-yo effect (65). Although non-persistent EDCs have been widely detected in human adipose tissue (68–71), we found that increased weight loss was not significantly associated with an increase in urinary EDC concentrations. Although a number of factors (e.g. fixed EDC intake, blood serum and adipose tissue measurements, more frequent urinary EDC measurements) should be controlled for to confirm our results, this yo-yo effect does not seem to be the consequence of non-persistent EDCs.

Although earlier studies also suggested a role for TUB gene expression, studies in rodents indicate that TUB is involved in the hypothalamic pathways regulating food intake and adiposity. Aside from the function in central nervous system, TUB has also been implicated in energy metabolism in adipose tissue.

In a similar setting in postmortem material, we used in situ hybridization to specifically localize the hypothalamic regions and cells expressing TUB mRNA (Source: paper #11, Int J Obesity). Expression of both TUB transcripts – a short and a long transcript variant – was detected in the hypothalamus, whereas only the short TUB isoform was found in both visceral and subcutaneous adipose tissue. TUB mRNA was detected in several hypothalamic regions which have previously been shown to be involved in body weight regulation, including the nucleus basalis of Meynert and the paraventricular, supraoptic and tuberomamillary nuclei. There was no difference in the hypothalamic TUB expression between brain tissue obtained from obese and non-obese individuals, whereas the level of TUB mRNA was significantly lower in adipose tissue of obese vs control subjects. Also, TUB expression was negatively correlated with indices of body weight and obesity in a fat-depot-specific manner. From these in vitro experiments we concluded that there is high expression of TUB in the hypothalamus, especially in those areas which regulate body weight, and also the inverse correlation between TUB expression in adipose tissue and obesity. As other studies in blood mononuclear cells have suggested that EDCs may alter gene expression of – amongst others – the TUB gene. These results may suggest a direct connection between EDC exposure and TUB gene expression in other tissues as well, for instance in the hypothalamus. This connection can however not be uncovered in postmortem tissue, and should direct us to future studies – for instance in rodents- to assess these relationships further.


DNA methylation / epigenetics

In the research on EDCs, the epigenome has thus far been unexplored territory. Recent epigenome-wide association studies (EWASs) identified several DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels. Therefore, we postulated that epigenetic alterations may functionally link EDCs with gene expression and metabolic traits and thus shed light on the role of EDCs in the development of obesity and/or type 2 diabetes.

We performed a systematic literature search for EWASs to test the association between DNA methylation and type 2 diabetes and/or glycaemic traits (Source: paper #10, Diabetologia). Using our own methylation data (produced with the Illumina 450K array) in whole blood from 100 Lifelines participants with type 2 diabetes and 100 control individuals, we aimed to replicate 100 unique CpGs identified in peripheral blood, pancreas, adipose tissue and liver from 15 EWASs. From the 52 CpGs identified in blood and selected for replication, 15 CpGs showed significant associations with type 2 diabetes in the Lifelines sample (p<0.05). The results for five CpGs (in ABCG1, LOXL2, TXNIP, SLC1A5 and SREBF1) remained significant after a stringent multiple-testing correction. These genes are respectively involved in complex metabolic pathways such as lipid homeostasis, especially promoting cholesterol efflux into HDL, related to diabetic retinopathy (LOCL2), glucose uptake via enhanced endocytosis of glucose-transporter 1 (TXNIP), participate in the synthesis of cholesterol, fatty acids and triglycerides (SREBF1), and glutamine uptake (SLC1A5).



All associations were directionally consistent with the original EWAS results. However, we could not replicate any of the selected CpGs from the tissue-specific EWASs, and we could also not replicate any of the CpGs associated with HbA1c levels in the healthy control individuals of our sample, while two CpGs (inABCG1andCCDC57) for fasting glucose were replicated at a nominal significance level (p<0.05). From this study we concluded that it was possible to replicate a number of differentially methylated CpGs reported to be associated with type 2 diabetes. These signals show promise for clinical use as disease biomarkers. However, it should be noted that epigenetic changes can be either a cause or a consequence of disease or an indirect contributing factor through environmental exposures that can affect both epigenome and type 2 diabetes risk. Multiple factors can affect DNA methylation patterns, which include a broad spectrum of environmental exposures (nutrition, physical activity, smoking, stress), as well as psychosocial and genetic factors, together explaining the variance in DNA methylation levels between individuals. Even so, new evidence suggests that even more complex interactions between both genetic determinants and epigenetic alterations may influence how genes are expressed and can influence various metabolic traits and lead to the development of complex disease like type 2 diabetes.



To elucidate our concepts further, we evaluated metabolic-related effects of the exposure to endocrine disruptors on epigenome-wide DNA methylation (Source: paper #6, Environ Int. 2020). For this purpose, a blood-based epigenome-wide association study was performed in 622 participants from the Lifelines DEEP cohort using Illumina Infinium HumanMethylation450 methylation data and EDC excretions in 24-hour urine. Out of the 21 EDCs, 13 compounds were detected in >75% of the samples and, together with bisphenol F, were included in these analyses. Furthermore, we explored the putative function of identified methylation markers and their correlations with metabolic traits, which yielded exciting results. We could identify 20 differentially methylated cytosine-phosphate-guanines (CpGs) which were significantly associated with 10 EDCs, especially with MEHP and MEHHP concentrations. Nine out of these 20 CpGs were significantly associated with at least one of the tested metabolic traits, such as fasting glucose, HbA1c, lipid levels, and/or blood pressure. It should be noted that 18 out of these 20 EDC-associated CpGs involved genes which have been shown to be functionally related to metabolic syndrome, hypertension, obesity, type 2 diabetes and insulin resistance. This is –to our knowledge- the first study that identified DNA methylation markers for exposure to the most common EDCs, and it provides several clues for mechanisms underlying the contributions of EDCs to metabolic health and diabetes.


Bioinformatics / machine learning approaches

One of our objectives was to use a novel bioinformatical environment-wide approach to investigate complex lifestyle-gene interactions including the role of EDCs in the development of type 2 diabetes. This approach is called a data-driven risk variable wide association study methodology (RV-WAS). As reported above, exposure to high EDC concentrations was not significantly associated with higher glucose and HbA1c levels in a cross-sectional setting, and also higher EDCs were not significantly associated with the development of type 2 diabetes over time. This may be a consequence of both the indirect ways by which EDCs may influence adiposity-related traits and type 2 diabetes, as well as the changes over time we have observed in exposure to EDCs in the general Dutch population, a phenomenon that until that publication remained a bit underexposed. Nevertheless, as better prediction of incident type 2 diabetes may be of importance for both diabetes care and better aiming of lifestyle intervention studies, we proceeded to replicate a wide variety of risk variables for the development of type 2 diabetes (Source: paper #4, Diabetologia. 2021). The RV-WAS methodology has placed the hazard ratios of the discovered risk variables into perspective. For a large number of risk variables, the impact was modest to weak. For EDCs, we did not observe a significant association with incident type 2 diabetes, so for the further analyses these variables were not incorporated.

In Lifelines participants without type 2 diabetes at baseline, we were able to identify a total number of 63 risk variables, and found novel associations for quality-of-life indicators and (surprisingly) non-cardiovascular medications (i.e., proton-pump inhibitors, anti-asthmatics) for incident type 2 diabetes. For continuous variables, the increase of 1 standard-deviation (SD) of HbA1c, i.e. 0.31% absolute), was equivalent in risk to an increase of diabetes risk of 0.53 mmol/l of glucose, 19.8 cm of waist circumference, 8.34 kg/m2 of BMI, 0.67 mmol/l of HDL-cholesterol, and 0.14 mmol/l of uric acid. Other variables required an increase of >3 SD, which is not physiologically realistic or a rare occurrence in the population. So, in addition to HbA1c, only a limited number of adiposity-related and biochemical variables were able to predict disease risk to a comparable extent. Although moderately correlated, the inclusion of four variables satiated prediction models. Invasive variables, except for glucose and HbA1c, contributed little compared with non-invasive variables. Glucose, HbA1cand family history of diabetes explained a unique part of disease risk. Adding risk variables to a satiated model can impact the hazard ratios of variables already in the model. For daily practice, glucose, HbA1c, and family history of diabetes explained a unique part of disease risk. The machine learning approach yielded modest to poor correlations between risk variables and outcome (type 2 diabetes). Most of these variables predicted the same part of disease risk and thus only a limited number of variables were able to contribute to risk prediction. Earlier publications have clearly indicated that most risk prediction models have comparable performance (72,73). Thus, existing risk prediction models could be simplified very easily without losing performance and should be reevaluated. Further, our findings show that measurements in blood or serum (triglycerides, HDL-C) , with the exception of glucose and HbA1c, do not further contribute to the prediction of type 2 diabetes development. Glucose and HbA1c measurements are readily available in GP practices, and even HbA1c can be measured reliably with in-office point-of-care equipment like DCA2000 or the Ac1Now InView device, and can therefore be easily implemented in screening methods for the development of type 2 diabetes.


The short summary above highlights the most important findings in the 13 papers brought forward by this project. For additional details, we refer to the full papers (see below).



Value and sustainability
This project has created enormous value to the body of evidence regarding endocrine disrupting chemicals and its link to type 2 diabetes. First of all, our multidisciplinary group headed by the grant recipient has developed an LC-MS/MS methodology that quantifies a clinically relevant set of important EDCs in a accurate, precise and reproducible way. The paper that describes this methodology provides an important ‘technical’ reference for the entire set-up of our LC-MS/MS system. Further, the methodology is available for and is offered as a service to other researchers who are active in this challenging field of research which bears huge importance for society and health. For example, a paper using our methodology in a longitudinal follow-up study of 13-15 year old children (part of two Dutch birth cohorts) has been submitted for review, with the title: “Urinary levels of bisphenols and parabens and their association with attention and concentration at adolescence”.
Second, the entire dataset with measurements, evaluations and spin-off variables has been added to the already extensive dataset of the Lifelines Cohort Study, allowing for in-depth follow-up research by other groups interested in this field of research. For example, next to information on exposure to EDCs, there is a large amount of genotypic and phenotypic information available in the dataset of the individuals with impaired fasting glucose, the participants to the LOWER study, and the individuals from the Lifelines DEEP study. This can be used to further investigate the link between exposure and diabetes-associated disease. As Lifelines aims to assess long-term health of its participants for a period of at least 30 years, future research can take profit of an even longer follow-up of the Lifelines participants. This way, research can explore the links between EDCs and not only the incidence of type 2 diabetes, but also the complications of this disease.
Third, the extensive series of scientific publications has not gone unnoticed by other researchers and authorities, and the importance of EDCs for health has been in center stage during the recent years. This is exemplified by the regulation of parabens, bisphenols and phthalates by the European Union in the past decade. Moreover, the European Society for Endocrinology (ESE) input to the Chemicals Strategy primarily focused around Endocrine Disrupting Chemicals (EDCs). Also, this response was coordinated by the ESE EDC Working Group, chaired by Prof Josef Köhrle (Charité, Berlin, Germany). This input is very relevant also in times of COVID 19. There is increasing evidence that EDCs increase the prevalence of diseases that cause underlying conditions like obesity and diabetes, that result in higher susceptibility to COVID 19. Source/citation: https://www.ese-hormones.org/advocacy/endocrine-disrupting-chemicals/


Conclusions and lessons learned
We have developed an innovative method to measure multiple EDCs reliably and reproducibly in a short period of time with state-of-the-art LC-MS/MS techniques..
There is a relationship between the concentration of EDC and measures of adiposity, while exposure to certain phthalate EDCs negatively influences reduction of body weight in obese people who participate in a dedicated weight loss program.
Exposure to EDCs affects changes in DNA methylation at sites which are specifically related to glucose metabolism and metabolic syndrome, thus supporting the role of EDCs in the pathogenesis of long-term metabolic disorders like type 2 diabetes.
EDCs can penetrate into and accumulate in brain tissue, including the hypothalamus, which is the specific part of the brain that regulates appetite and energy metabolism. We can however due to the nature of our experiments not yet conclude that this is the specific mechanism of action of EDCs. This finding supports the need for more mechanistic studies to evaluate this further.
We were unable to demonstrate a direct relationship between EDCs and the development of type 2 diabetes in participants to the Lifelines Cohort Study with pre-diabetes, who were followed for an average of almost 4 years. Despite this, based on the other mechanisms of action of EDCs (see above) it may well be that they play a causal role in an earlier phase in triggering important metabolic derangements and changes in DNA methylation, e.g. in the development of metabolic syndrome and pre-diabetes.
There are literally dozens of risk factors associated with the development of type 2 diabetes. However, from a viewpoint of future health, only a limited number of risk variables, including glucose and HbA1c, are needed to optimally predict the development of type 2 diabetes.
Repeated measurements of EDCs are required to monitor exposure and assess associations with diseases like obesity and type 2 diabetes.
Repeated measurements in our studies clearly indicate that exposure to EDCs has declined in recent years, probably due to legislation restricting the use of these types of chemicals. This is also part of the good news of our studies.

The list of literature is available on https://www.gmed.nl/ReferencesDFNGrant.pdf




Van der Meer TP. PhD Thesis. Risk variables for the development of obesity and type 2 diabetes. Promotor Prof. dr. B.H.R. Wolffenbuttel, Copromotor Dr. J.V. van Vliet-Ostaptchouk. Thesis defense May 12,2021.

Under review:

  1. van der Meer TP, van Faassen M, Makris KCN, van Beek AP, Kema IP, Wolffenbuttel BHR, van Vliet-Ostaptchouk J, Patel CJ. Associations between Endocrine Disrupting Chemicals and Type 2 Diabetes in a pre-diabetic population.

In general, we found higher EDC concentrations to be non-significantly associated with lower diabetes risk. Associations became significant after stratification for sex and were driven by middle-aged women for phthalates and older women for parabens. The time at which exposure is assessed affects the association, further stressing the need for repeated measurements.

Published (support of DF has been acknowledged)

  1. van der Meer TP, Thio CHL, van Faassen M, van Beek AP, Snieder H, van Berkum FNR, Kema IP, Makris KC, Wolffenbuttel BHR, van Vliet-Ostaptchouk JV. Endocrine disrupting chemicals during diet-induced weight loss – A post-hoc analysis of the LOWER study. Environ Res. 2021 Jan;192:110262. doi: 10.1016/j.envres.2020.110262. Epub 2020 Oct 10. PMID: 33045228.

In a study of obese participants, we observed a reduction in most phthalates after a weight reduction intervention. A reduction in adipose tissue may not lead to mobilization and successively  to higher urinary EDC excretions. Higher baseline paraben and phthalate exposures were associated with reduced weight loss, suggesting obesogenic properties

  1. van der Meer TP, Chung MK, van Faassen M, Makris KC, van Beek AP, Kema IP, Wolffenbuttel BHR, van Vliet-Ostaptchouk JV, Patel CJ. Temporal exposure and consistency of endocrine disrupting chemicals in a longitudinal study of individuals with impaired fasting glucose. Environ Res. 2021 Feb 20;197:110901. doi: 10.1016/j.envres.2021.110901. Epub ahead of print. PMID: 33617867.

Exposure to most EDCs decreased between 2009 and 2016 in a sample of individuals with impaired fasting glucose from the Dutch population. Temporal consistency was generally poor. The inconsistency in disease associations may be influenced by individual-level or temporal variation exhibited by EDCs. Our findings call for the need for repeated measurements of EDCs in observational studies before and during at-risk temporal windows for the disease.

  1. van der Meer TP, Wolffenbuttel BHR, Patel CJ. Data-driven assessment, contextualisation and implementation of 134 variables in the risk for type 2 diabetes: an analysis of Lifelines, a prospective cohort study in the Netherlands. Diabetologia. 2021 Mar 12. doi: 10.1007/s00125-021-05419-1. Epub ahead of print. PMID: 33710397 (indirectly supported).

Many variables show weak or inconsistent associations with the development of type 2 diabetes, and only a handful can reliably explain disease risk. Newly discovered risk variables will yield little over established factors, and existing prediction models can be simplified. A systematic, data-driven approach to identify risk variables for the prediction of type 2 diabetes is necessary for the practice of precision medicine.

  1. van der Meer TP, van Faassen M, van Beek AP, Snieder H, Kema IP, Wolffenbuttel BHR, van Vliet-Ostaptchouk JV. Exposure to Endocrine Disrupting Chemicals in the Dutch general population is associated with adiposity-related traits. Sci Rep. 2020 Jun 9;10(1):9311. doi: 10.1038/s41598-020-66284-3. PMID: 32518352; PMCID: PMC7283255.

Exposure to EDCs in the Dutch population is ubiquitous. We found direct associations between phthalates and adiposity-related traits. Prospective studies are needed to confirm these findings.

  1. Lu X, Fraszczyk E, van der Meer TP, van Faassen M, Bloks VW, Kema IP, van Beek AP, Li S, Franke L, Westra HJ; BIOS Consortium, Xu X, Huo X, Snieder H, Wolffenbuttel BHR, van Vliet-Ostaptchouk JV. An epigenome-wide association study identifies multiple DNA methylation markers of exposure to endocrine disruptors. Environ Int. 2020 Nov;144:106016. doi: 10.1016/j.envint.2020.106016. Epub 2020 Sep 9. PMID: 32916427.

The identified DNA methylation markers for exposure to the most common EDCs provide suggestive mechanism underlying the contributions of EDCs to metabolic health. Follow-up studies are needed to unravel the causality of EDC-induced methylation changes in metabolic alterations.

  1. 7. van der Meer TP, van Faassen M, Frederiksen H, van Beek AP, Wolffenbuttel BHR, Kema IP, van Vliet-Ostaptchouk JV. Development and Interlaboratory Validation of Two Fast UPLC-MS-MS Methods Determining Urinary Bisphenols, Parabens and Phthalates. J Anal Toxicol. 2019 Jul 24;43(6):452-464.

We set up and validated two high-throughput methods with very short runtime capable of measuring 5 parabens, 3 bisphenols and 13 different metabolites of 8 phthalates. Sensitivity of the phenol method was increased by using ammonium fluoride in the mobile phase.

  1. Gängler S, Waldenberger M, Artati A, Adamski J, van Bolhuis JN, Sørgjerd EP, van Vliet-Ostaptchouk J, Makris KC. Exposure to disinfection byproducts and risk of type 2 diabetes: a nested case-control study in the HUNT and Lifelines cohorts. Metabolomics. 2019 Apr 8;15(4):60.

Such exposome-based approaches in cohort-nested studies are warranted to better understand the environmental origins of diabetogenesis.

  1. Charisiadis P, Andrianou XD, van der Meer TP, den Dunnen WFA, Swaab DF, Wolffenbuttel BHR, Makris KC, van Vliet-Ostaptchouk JV. Possible Obesogenic Effects of Bisphenols Accumulation in the Human Brain. Sci Rep. 2018 May 29;8(1):8186.

This is the first study reporting the presence of bisphenols in two distinct regions of the human brain. Bisphenols accumulation in the white matter-enriched brain tissue could signify that they are able to cross the blood-brain barrier.

  1. Walaszczyk E, Luijten M, Spijkerman AMW, Bonder MJ, Lutgers HL, Snieder H, Wolffenbuttel BHR, van Vliet-Ostaptchouk JV. DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA(1c) levels: a systematic review and replication in a case-control sample of the Lifelines study. Diabetologia. 2018 Feb;61(2):354-368.

A number of differentially methylated CpGs reported to be associated with type 2 diabetes in the EWAS literature were replicated in blood and show promise for clinical use as disease biomarkers. However, more prospective studies are needed to support the robustness of these findings.

  1. V Nies, D Struik, M Wolfs, S Rensen, E Szalowska, U Unmehopa, K Fluiter, T van der Meer, G Hajmousa, W Buurman, JW Greve, F Rezaee, R Shiri-Sverdlov, R Vonk, D Swaab, B Wolffenbuttel, J Jonker, JV Van Vliet-Ostaptchouk. TUB gene expression in hypothalamus and adipose tissue and its association with obesity in humans. Int Journal of Obesity, 2018 Mar; 42(3):376-383.

Our results indicate high expression of TUB in the hypothalamus, especially in areas involved in body weight regulation, and the correlation between TUB expression in adipose tissue and obesity. These findings suggest a role for TUB in human obesity. 

  1. van der Meer TP, Artacho-Cordón F, Swaab DF, Struik D, Makris KC, Wolffenbuttel BHR, Frederiksen H, van Vliet-Ostaptchouk JV. Distribution of Non-Persistent Endocrine Disruptors in Two Different Regions of the Human Brain. Int J Environ Res Public Health. 2017 Sep 13;14(9).

Our findings indicate that some suspected npEDCs are able to cross the blood–brain barrier. Whether the presence of npEDCs can adversely affect brain function and to which extent the detected concentrations are physiologically relevant needs to be further investigated.

  1. Andra SS, Charisiadis P, Arora M, van Vliet-Ostaptchouk JV, Makris KC. Biomonitoring of human exposures to chlorinated derivatives and structural analogs of bisphenol A. Environ Int. 2015 Dec;85:352-79

The primary objective of this review was to survey all available studies reporting biomonitoring protocols of ClxBPA and structural BPA analogs (BPS, BPF, BPB, etc.) in human matrices. Focus was paid on describing the analytical methodologies practiced for the analysis of ClxBPA and BPA analogs using hyphenated chromatography and mass spectrometry techniques, because current methodologies for human matrices are complex. During the last decade, an increasing number of ecotoxicological, cell-culture and animal-based and human studies dealing with ClxBPA exposure sources and routes of exposure, metabolism and toxicity have been published. Up to date findings indicated the association of ClxBPA with metabolic conditions, such as obesity, lipid accumulation, and type 2 diabetes mellitus, particularly in in-vitro and in-vivo studies. We critically discuss the limitations, research needs and future opportunities linked with the inclusion of ClxBPA and BPA analogs into exposure assessment protocols of relevant epidemiological studies.



Nederlandse samenvatting

De algemene Nederlandse bevolking wordt dagelijks blootgesteld aan een breed scala aan stoffen die het endocriene systeem en de stofwisseling beïnvloeden, de zgn endocriene disruptors (EDCs). Dit zijn chemische stoffen als parabenen, bisfenolen en ftalaten, die voorkomen in voedselproducten, cosmetica, plastic, etc. In onze studies hebben wij getracht te onderzoeken op welke wijze deze stoffen het krijgen van overgewicht en type 2 diabetes beïnvloeden.

Allereerst hebben wij een nieuwe techniek ontwikkeld, die we voor onze metingen hebben gebruikt, op basis van zgn vloeistofchromatografie gekoppeld aan een dubbele massa spectometrie (LC-MS/MS). Met deze methode is het mogelijk om de diverse EDCs (vijf verschillende parabenen, drie bisphenolen , en dertien metabolieten van in totaal acht ftalaten) betrouwbaar te bepalen, waarbij enkele technische aanpassingen maakten dat we een grote hoeveelheid bepalingen konden laten doen in relatief korte tijd.

In onze studies hebben wij een aantal bevindingen gedaan. EDCs hopen op in hersenweefsel, met name in dat deel van de hersenen, de hypothalamus, van waaruit eetlust en verzadiging worden gereguleerd. Mensen met obesitas hadden hogere concentraties van de stof methylparabeen in de hypothalamus in vergelijking met mensen met een normaal gewicht. Er is mogelijk een directe relatie tussen blootstelling aan EDCs en de activiteit van het TUB enzym in de hypothalamus en het vetweefsel. Er is in de Nederlandse bevolking een duidelijk verband tussen blootstelling aan EDCs en bepaalde maten voor overgewicht. We detecteerden bisphenol A, vier parabenen en acht ftalaat metabolieten in 84-100% van de urinemonsters van mensen die deelnamen aan de Lifelines Cohort Studie. Dit laat zien dat blootstelling aan deze chemicaliën wijdverspreid en alomvattend is. Nadat we onze analyses gecorrigeerd hadden voor onder andere voeding en lichamelijke beweging, vonden we dat hoge concentraties van bisphenol A en de ftalaat metabolieten MiBP, MECPP en MBzP geassocieerd waren met een toename in obesitas-gerelateerde variabelen zoals body mass index en buikomvang. Uit een andere studie bleek verhoogde blootstelling aan ftalaten maakte dat mensen tijdens een afvalprogramma minder gewicht verloren.

Eén van de mogelijke manieren waarop EDCs hun effect op overgewicht en diabetes uitoefenen is beïnvloeding van DNA methylering. Dat bepaalt hoe en hoe vaak bepaalde genen worden gekopieerd en gebruikt. Wij vonden een duidelijk verband tussen bepaalde EDCs en veranderingen in DNA methylering, juist op die plekken in het DNA die duidelijk verband houden met variabelen als glucose, HbA1c, en het hebben van het metabool syndroom, een combinatie van risicofactoren voor het ontwikkelen van type 2 diabetes en hart- en vaatziekten. Deze unieke studie is één van de eerste die dit verband heeft aangetoond. Tevens bestudeerden wij mogelijke verbanden tussen blootstelling aan EDCs en de ontwikkeling van type 2 diabetes. Dit deden we in een groep mensen met pre-diabetes, wat betekent dat hun nuchtere glucosewaarden al licht verhoogd waren, maar nog niet hoog genoeg voor de diagnose diabetes. Omdat we naar een tijdsperiode van vijf jaar kijken, hebben we de EDC concentraties aan het begin en aan het einde van de studieperiode bepaald. We vonden dat er geen significant verband was tussen blootstelling aan EDCs en het ontwikkelen van type 2 diabetes. Integendeel, blootstelling aan hoge concentraties van ftalaat metabolieten was geassocieerd met een afname in het krijgen van type 2 diabetes, maar alleen in vrouwen van middelbare leeftijd. Tevens stelden wij vast dat er in de loop van de afgelopen jaren een afname is van de blootstelling aan EDCs. Veranderingen in de wetgeving in Nederland en Europa speelt hierbij mede een rol: het gebruik van een aantal van deze chemicaliën voor specifieke producten is al bij Europese wet verboden, en zal daardoor blootstelling verder voorkomen. Toekomstig onderzoek moet dieper ingaan op deze geslachts- en leeftijdsspecifieke effecten, en zich richten op de onderliggende reden achter deze verschillen.

Het verband tussen EDCs, overgewicht en type 2 diabetes is erg complex. Waarschijnlijk oefenen EDCs hun negatieve effect uit vroeg in het ontstaan van type 2 diabetes, nl in de fase van ontwikkelen van overgewicht en metabool syndroom. De chemische bais is eveneens complex: vaak is er niet zomaar een rechtlijnig verband tussen blootstelling aan EDC en hun ongunstige effect, maar kunnen zowel lage en hoge concentraties van een stof een negatief effect hebben, bv op de bloeddruk, terwijl een gemiddelde concentratie weinig effect heeft. Er zijn daarnaast grote verschillen in blootstelling tussen individuen. Dit benadrukt dat het noodzakelijk is om herhaalde metingen van EDCs uit te voeren om een betrouwbaar beeld te krijgen in welke mate mensen aan EDCs worden blootgesteld.  We onderzochten tevens de blootstellingsroutes van verschillende EDC’s verder door te onderscheiden of blootstelling werd beïnvloed door een beperking van voedsel-gerelateerde producten. Onze bevindingen suggereren bijvoorbeeld dat blootstelling aan hoge concentraties van de ftalaatmetaboliet MEP afkomstig is van voedingsproducten met een lage calorische waarde zoals groenten, mogelijk als gevolg van een combinatie van verpakking en de oplosbaarheid in water in vergelijking met andere ftalaten. Deze resultaten bieden de mogelijkheid voor toekomstig onderzoek om de bron van EDC-blootstelling aan een specifieke reeks producten vast te stellen.



Wij hebben een innovatieve methode ontwikkeld om meerdere EDCs waaronder bisphenolen, parabenen en phtalaten in korte tijd betrouwbaar en reproduceerbaar te meten. Deze methode kan relatief eenvoudig ingezet worden in andere laboratoria maar onderzoekers met weinig ervaring in de gebruikte technieken kunnen analyse van hun urinemonsters in ons laboratorium laten meten.

Er is een relatie tussen de concentratie van EDCs in de urine (een goede maat voor blootstelling aan deze chemische stoffen) en bepaalde aan overgewicht verbonden metingen, zoals een hogere body mass index en toegenomen buikomvang.

Blootstelling aan bepaalde EDCs belemmert de daling van het lichaamsgewicht bij mensen die aan een programma meedoen om af te vallen.

Bloostelling aan EDCs beïnvloedt chemische veranderingen in ons DNA, de zgn DNA methylering, en deze veranderingen in specifieke genen houden verband met de afwijkingen in de glucose stofwisseling en het metabool syndroom, obergewicht, en hoge bloeddruk..

EDCs kunnen doordringen in het hersenweefsel, onder andere de hypothalamus, dat deel van de hersenen dat eetlust en energiestofwisseling reguleert.

Wij konden geen relatie aantonen tussen EDCs en het ontstaan van type 2 diabetes bij mensen met pre-diabetes, die gemiddeld 4 jaar werden gevolgd. Mogelijk spelen EDCs al in een vroegere fase een rol, via bovengenoemde mechanismen, o.a. bij het ontstaan van metabool syndroom en pre-diabetes.

Er zijn heel veel factoren die een verband hebben met het toekomstig ontstaan van type 2 diabetes. Voor een meer exacte inschatting van dit risico is slechts een beperkt aantal metingen, waaronder dat van bloed glucose en HbA1c, in staat om het ontstaan van type 2 diabetes te voorspellen.

De blootstelling aan EDCs is de afgelopen jaren afgenomen, waarschijnlijk onder invloed van wetgeving die gebruik van dit soort chemische stoffen beperkt. Toch is de blootstelling nog niet uitgebannen, en kunnen via verdere maatregelen onnodige blootstelling en effecten op metabool syndroom en pre-diabetes mogelijk worden voorkomen. Vele organisaties waaronder de Europese Wetenschappelijke Vereniging voor Endocrinologie, zijn actief om dit te bewerkstelligen.