Endocrine disruptors project

door bhrw | mrt 1, 2024 | diabetes, gezondheidszorg, wetenschap

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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Questionnaire-based prediction for type 2 diabetes

door bhrw | dec 4, 2023 | diabetes, gezondheidszorg, wetenschap

Background
Type 2 diabetes disproportionately affects individuals of non-White ethnicity through a complex interaction of multiple factors. Therefore, early disease detection and prediction are essential and require tools that can be deployed on a large scale. We aimed to tackle this problem by developing questionnaire-based prediction models for type 2 diabetes prevalence and incidence for multiple ethnicities.

Methods
In this proof of principle analysis, logistic regression models to predict type 2 diabetes prevalence and incidence, using questionnaire-only variables reflecting health state and lifestyle, were trained on the White population of the UK Biobank (n = 472,696 total, aged 37–73 years, data collected 2006–2010) and validated in five other ethnicities (n = 29,811 total) and externally in Lifelines (n = 168,205 total, aged 0–93 years, collected between 2006 and 2013). In total, 631,748 individuals were included for prevalence prediction and 67,083 individuals for the eight-year incidence prediction. Type 2 diabetes prevalence in the UK Biobank ranged between 6% in the White population to 23.3% in the South Asian population, while in Lifelines, the prevalence was 1.9%. Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUC), and a detailed sensitivity analysis was conducted to assess potential clinical utility. We compared the questionnaire-only models to models containing physical measurements and biomarkers as well as to clinical non-laboratory type 2 diabetes risk tools and conducted a reclassification analysis.

Findings
Our algorithms accurately predicted type 2 diabetes prevalence (AUC = 0.901) and eight-year incidence (AUC = 0.873) in the White UK Biobank population. Both models replicated well in the Lifelines external validation, with AUCs of 0.917 and 0.817 for prevalence and incidence, respectively. Both models performed consistently well across different ethnicities, with AUCs of 0.855–0.894 for prevalence and 0.819–0.883 for incidence. These models generally outperformed two clinically validated non-laboratory tools and correctly reclassified >3,000 additional cases. Model performance improved with the addition of blood biomarkers but not with the addition of physical measurements.

Interpretation
Our findings suggest that easy-to-implement, questionnaire-based models could be used to predict prevalent and incident type 2 diabetes with high accuracy across several ethnicities, providing a highly scalable solution for population-wide risk stratification. Future work should determine the effectiveness of these models in identifying undiagnosed type 2 diabetes, validated in cohorts of different populations and ethnic representation.

You can download the full article HERE.