The association between the food environment and adherence to healthy diet quality: the Maastricht Study

Abstract Objective: The purpose of this study is to determine if healthier neighbourhood food environments are associated with healthier diet quality. Design: This was a cross-sectional study using linear regression models to analyse data from the Maastricht Study. Diet quality was assessed using data collected with a FFQ to calculate the Dutch Healthy Diet (DHD). A buffer zone encompassing a 1000 m radius was created around each participant home address. The Food Environment Healthiness Index (FEHI) was calculated using a Kernel density analysis within the buffers of available food outlets. The association between the FEHI and the DHD score was analysed and adjusted for socio-economic variables. Setting: The region of Maastricht including the surrounding food retailers in the Netherlands. Participants: 7367 subjects aged 40–75 years in the south of the Netherlands. Results: No relationship was identified between either the FEHI (B = 0·62; 95 % CI = –2·54, 3·78) or individual food outlets, such as fast food (B = –0·07; 95 % CI = –0·20, 0·07) and diet quality. Similar null findings using the FEHI were identified at the 500 m (B = 0·95; 95 % CI = –0·85, 2·75) and 1500 m (B = 1·57; 95 % CI = –3·30, 6·44) buffer. There was also no association between the food environment and individual items of the DHD including fruits, vegetables and sugar-sweetened beverages. Conclusion: The food environment in the Maastricht area appeared marginally unhealthy, but the differences in the food environment were not related to the quality of food that participants reported as intake

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2x)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted

Effects of interacting networks of cardiovascular risk genes on the risk of type 2 diabetes mellitus (the CODAM study)

Background: Genetic dissection of complex diseases requires innovative approaches for identification of disease-predisposing genes. A well-known example of a human complex disease with a strong genetic component is Type 2 Diabetes Mellitus (T2DM). Methods: We genotyped normal-glucose-tolerant subjects (NGT; n = 54), subjects with an impaired glucose metabolism (IGM; n = 111) and T2DM (n = 142) subjects, in an assay (designed by Roche Molecular Systems) for detection of 68 polymorphisms in 36 cardiovascular risk genes. Using the single-locus logistic regression and the so-called haplotype entropy, we explored the possibility that (1) common pathways underlie development of T2DM and cardiovascular disease which would imply enrichment of cardiovascular risk polymorphisms in "pre-diabetic" (IGM) and diabetic (T2DM) populations- and (2) that gene-gene interactions are relevant for the effects of risk polymorphisms. Results: In single-locus analyses, we showed suggestive association with disturbed glucose metabolism (i.e. subjects who were either IGM or had T2DM), or with T2DM only. Moreover, in the haplotype entropy analysis, we identified a total of 14 pairs of polymorphisms (with a false discovery rate of 0.125) that may confer risk of disturbed glucose metabolism, or T2DM only, as members of interacting networks of genes. We substantiated gene-gene interactions by showing that these interacting networks can indeed identify potential "disease-predisposing allele-combinations". Conclusion: Gene-gene interactions of cardiovascular risk polymorphisms can be detected in prediabetes and T2DM, supporting the hypothesis that common pathways may underlie development of T2DM and cardiovascular disease. Thus, a specific set of risk polymorphisms, when simultaneously present, increases the risk of disease and hence is indeed relevant in the transfer of risk

Genetically defined elevated homocysteine levels do not result in widespread changes of DNA methylation in leukocytes

BACKGROUND:DNA methylation is affected by the activities of the key enzymes and intermediate metabolites of the one-carbon pathway, one of which involves homocysteine. We investigated the effect of the well-known genetic variant associated with mildly elevated homocysteine: MTHFR 677C>T independently and in combination with other homocysteine-associated variants, on genome-wide leukocyte DNA-methylation. METHODS:Methylation levels were assessed using Illumina 450k arrays on 9,894 individuals of European ancestry from 12 cohort studies. Linear-mixed-models were used to study the association of additive MTHFR 677C>T and genetic-risk score (GRS) based on 18 homocysteine-associated SNPs, with genome-wide methylation. RESULTS:Meta-analysis revealed that the MTHFR 677C>T variant was associated with 35 CpG sites in cis, and the GRS showed association with 113 CpG sites near the homocysteine-associated variants. Genome-wide analysis revealed that the MTHFR 677C>T variant was associated with 1 trans-CpG (nearest gene ZNF184), while the GRS model showed association with 5 significant trans-CpGs annotated to nearest genes PTF1A, MRPL55, CTDSP2, CRYM and FKBP5. CONCLUSIONS:Our results do not show widespread changes in DNA-methylation across the genome, and therefore do not support the hypothesis that mildly elevated homocysteine is associated with widespread methylation changes in leukocytes

Refining Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Genetic Loci by Integrating Summary Data From Genome-wide Association, Gene Expression, and DNA Methylation Studies

Background: Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels. Methods: We applied summary-data–based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data–based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels. Results: We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before. Conclusions: Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies

Skewed X-inactivation is common in the general female population

X-inactivation is a well-established dosage compensation mechanism ensuring that X-chromosomal genes are expressed at comparable levels in males and females. Skewed X-inactivation is often explained by negative selection of one of the alleles. We demonstrate that imbalanced expression of the paternal and maternal X-chromosomes is common in the general population and that the random nature of the X-inactivation mechanism can be sufficient to explain the imbalance. To this end, we analyzed blood-derived RNA and whole-genome sequencing data from 79 female children and their parents from the Genome of the Netherlands project. We calculated the median ratio of the paternal over total counts at all X-chromosomal heterozygous single-nucleotide variants with coverage ≥10. We identified two individuals where the same X-chromosome was inactivated in all cells. Imbalanced expression of the two X-chromosomes (ratios ≤0.35 or ≥0.65) was observed in nearly 50% of the population. The empirically observed skewing is explained by a theoretical model where X-inactivation takes place in an embryonic stage in which eight cells give rise to the hematopoietic compartment. Genes escaping X-inactivation are expressed from both alleles and therefore demonstrate less skewing than inactivated genes. Using this characteristic, we identified three novel escapee genes (SSR4, REPS2, and SEPT6), but did not find support for many previously reported escapee genes in blood. Our collective data suggest that skewed X-inactivation is common in the general population. This may contribute to manifestation of symptoms in carriers of recessive X-linked disorders. We recommend that X-inactivation results should not be used lightly in the interpretation of X-linked variants

Selection bias in follow-up studies of stem cell transplantation survivors: an experience within the Maastricht Observational study of late effects after Stem cell trAnsplantation (MOSA)

Hematopoietic stem cell transplantation is an important treatment for many malignant hematological and non-hematological diseases. Survivors of hematopoietic stem cell transplantation (HCT) are at risk of long-term health problems and reduced quality of life related to previous treatments. Many studies about these long-term effects have been conducted over the last decades. However, selection bias is a concern in long-term follow-up studies and little is known about the non-participating group. As part of the Maastricht Observational study of late effects after Stem cell trAnsplantation (MOSA), investigating long-term health effects by extensively phenotyping HCT survivors, we conducted a survey to characterise the non-participating group. This survey mostly focused on quality of life and physical complaints. The survey responders were generally older than the MOSA group, had more history of relapsed disease, and described their general health as bad or mediocre significantly more often than the MOSA group. Also, more deaths occurred in the group of non-participants between the start of study inclusion in 2015 and analysis of the survey results in 2021. This study suggests that a selection of higher functioning HCT survivors with a relatively better quality of life participated in this long-term follow-up study of stem cell transplantation survivors. These results could also impact the results of other long-term follow-up studies in cancer survivors, knowing that possibly an unhealthier population is missed in these studies and some long-term negative effects of treatments might be underestimated.Trial registration number: NL-48599

Long-term effects after stem cell transplantation identified:design of the MOSA study

OBJECTIVE: The MOSA study (Maastricht Observational study of late effects after Stem cell trAnsplantation) aims to study the prevalence of adverse health effects in hematopoietic stem cell transplantation (HCT) survivors compared to a matched cohort, representing the general population. STUDY DESIGN AND SETTING: The MOSA study is a matched cohort study, nested within a large prospective cohort, The Maastricht Study. Participants of The Maastricht Study serve as a reference group matched on age, sex and education to compare MOSA participants to the general population. In both studies, the same study protocol and extensive phenotyping measurements are used. RESULTS: HCT survivors: 539 survivors were invited of which, so far 123 (23%) participants completed the study assessments. Data will be analyzed and published separately. REFERENCE GROUP: For each MOSA participant, four reference cases were matched. After matching, both groups are comparable with respect to age, sex and education. CONCLUSION: To our knowledge, this is the first study conducting such detailed phenotyping in HCT survivors. Comparison with a large reference group provides essential information about late effects of HCT and associated risk factors. This may improve screening and prevention strategies, potentially leading to a positive impact on morbidity, mortality and quality of life

Lower heart rate variability, an index of worse autonomic function, is associated with worse beta cell response to a glycemic load in vivo—The Maastricht Study

Abstract Objective We investigated, using population-based data, whether worse autonomic function, estimated from lower 24-hour heart rate variability (HRV), was associated with beta cell function, assessed from beta cell response during an oral glucose tolerance test (OGTT). Research design and methods We used cross-sectional data from The Maastricht Study, a population-based cohort study (N = 2,007; age, mean ± SD:60 ± 8 years; 52% men; and 24% with type 2 diabetes). We used linear regression analyses with adjustment for potential confounders (demographic, cardiovascular, and lifestyle factors) to study the associations of time- and frequency-domain HRV (composite scores) with overall beta cell response (estimated from a composite score calculated from: C-peptidogenic index, overall insulin secretion, beta cell glucose sensitivity, beta cell potentiation factor, and beta cell rate sensitivity). In addition, we tested for interaction by sex and glucose metabolism status. Results After full adjustment, lower time- and frequency-domain HRV was significantly associated with lower overall beta cell response composite score (standardized beta, -0.055 [-0.098; -0.011] and − 0.051 [-0.095; -0.007], respectively). These associations were not modified by sex and there was no consistent pattern of interaction by glucose metabolism status. Conclusion The present etiological study found that worse autonomic function, estimated from lower HRV, was associated with worse beta cell function, estimated from a composite score in a population-based sample which covered the entire spectrum of glucose metabolism. Hence, autonomic dysfunction may contribute to beta cell dysfunction and, ultimately, to the alteration of glucose metabolism status from normal glucose metabolism to prediabetes and type 2 diabetes