Auto-immune gastritis

Autoimmune gastritis (AIG) is characterized by the destruction of gastric parietal cells, resulting in hypochlorhydria and eventual achlorhydria, as oxyntic glands in the corpus are destroyed and become atrophic. The permanent loss of gastric acid has many impacts—both theoretical and documented. The most concerning of these are hypergastrinemia and increased N-nitroso compounds, both of which increase the risk of gastric cancers. While known deficiencies of B12 and iron are often replaced in AIG, acid is not. Moreover, patients with AIG are often prescribed acid suppression for a stomach that is decidedly no longer acidic, worsening the sequelae of gastric atrophy. Betaine hydrochloride (BHCL) is a short-acting acidifying agent, available over the counter in capsule form. Mealtime acid supplementation has an historic basis and could ameliorate many AIG-related gastrointestinal symptoms. Theoretically, acidification could also reduce the potential for hypergastrinemia and the production of N-nitroso compounds, consequently reducing the risk of gastric cancers. Supplemental vitamin C may also help in preventing gastric N-nitroso formation, regardless of the gastric pH. This narrative review describes the functions of gastric acid in gastrointestinal and immune health, documents the effects of hypochlorhydria in AIG, and proposes potential options for safely re-establishing the acid milieu of the stomach for patients with AIG.

You can download the article HERE.

 

 

Endocrine disruptors project

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)

 

Click on ‘meer’ to read further..

(meer…)

Questionnaire-based prediction for type 2 diabetes

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.

 

Genezen en toch klachten

Mijn recente column in het magazine Hypo Nieuws. Het mooie wetenschappelijke artikel van de collegae uit Leiden, waar ik in de column naar verwijs, heet: Smaller grey matter volumes in the anterior cingulate cortex and greater cerebellar volumes in patients with long-term remission of Cushing’s disease: a case–control study. De eerste auteur is Cornelie Andela. U vindt het HIER.

 

De link in de column verwijst naar een wikipedia pagina over DNA methylering.

 

Wanneer u als wetenschapper geïnteresseerd bent in de rol van DNA methylering bij endocriene of metabole aandoeningen, kijk dan ook eens naar de volgende publicaties:

DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels: a systematic review and replication in a case-control sample of the Lifelines study.

The effects of bariatric surgery on clinical profile, DNA methylation, and ageing in severely obese patients.

An epigenome-wide association study identifies multiple DNA methylation markers of exposure to endocrine disruptors.

 

Polygenic risk scores

The growing public interest in genetic risk scores for various health conditions can be harnessed to inspire preventive health action. However, current commercially available genetic risk scores can be deceiving as they do not consider other, easily attainable risk factors, such as sex, BMI, age, smoking habits, parental disease status and physical activity. Recent scientific literature shows that adding these factors can improve PGS based predictions significantly. However, implementation of existing PGS based models that also consider these factors requires reference data based on a specific genotyping chip, which is not always available. In this paper, we offer a method naïve to the genotyping chip used. We train these models using the UK Biobank data and test these externally in the Lifelines cohort. We show improved performance at identifying the 10% most at-risk individuals for type 2 diabetes (T2D) and coronary artery disease (CAD) by including common risk factors. Incidence in the highest risk group increases from 3.0- and 4.0-fold to 5.8 for T2D, when comparing the genetics-based model, common risk factor-based model and combined model, respectively. Similarly, we observe an increase from 2.4- and 3.0-fold to 4.7-fold risk for CAD. As such, we conclude that it is paramount that these additional variables are considered when reporting risk, unlike current practice with current available genetic tests.

 

 

You can read the full paper at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941118/pdf/41598_2023_Article_27637.pdf

 

 

 

Insuline secretie bij lang bestaande type 1 diabetes

In een recent onderzoek worden de resultaten gepresenteerd van de insuline afgifte na een test maaltijd bij mensen met langer bestaande type 1 diabetes.

Het abstract is als volgt:

Aims: This study aims to evaluate the stability of C-peptide over time and to compare fasting C-peptide and C-peptide response after Mixed-Meal Tolerance Test (MMTT) at T90 or T120 with C-peptide area under the curve (AUC) in long-standing type 1 diabetes.

Methods: We included 607 type 1 diabetes individuals with diabetes duration >5 years. C-peptide concentrations (ultrasensitive assay) were collected in the fasting state, and in a subpopulation after MMTT (T0, just prior to, T30-T60-T90-T120, 30-120 minutes after ingestion of Mixed-meal) (n=168). Fasting C-peptide concentrations (in n=535) at Year 0 and Year 1 were compared. The clinical determinants associated with residual C-peptide secretion and the correspondence of C-peptide at MMTT T90 / T120 and total AUC were assessed.

Results: 153 participants (25%) had detectable fasting serum C-peptide (i.e ≥ 3.8 pmol/L). Fasting C-peptide was significantly lower at Year 1 (P <0.001, effect size = -0.16). Participants with higher fasting C-peptide had a higher age at diagnosis, shorter disease duration and were less frequently insulin pump users. Overall, 109 of 168 (65%) participants had both non-detectable fasting and post-meal serum C-peptide concentrations. The T90 and T120 C-peptide values at MMTT were concordant with total AUC. In 17 (10%) individuals, C-peptide was only detectable at MMTT and not in the fasting state.

Conclusions: Stimulated C-peptide was detectable in an additional 10% of individuals compared with fasting in individuals with >5 years diabetes duration. T90 and T120 MMTT measurements showed good concordance with the MMTT total AUC. Overall there was a decrease of C-peptide at 1-year follow-up.

Het volledige artikel is hier te lezen: https://onlinelibrary.wiley.com/doi/10.1111/dme.15012

Het onderzoek werd mogelijk gemaakt door het JDRF (Juvenile Diabetes Research Foundation) en het DiabetesFonds Nederland.