Biology subjects

Willemsen, G.

Publications and source records attributed to Willemsen, G..

6 recordsLinked to original sources

bioRxiv2023

Linking the gut microbiome to host DNA methylation by a discovery and replication epigenome-wide association study

Both gene methylation and the gut microbiome are partially determined by host genetics and partially by environment. We investigated the relations between gene methylation in blood and the abundance of common gut bacteria profiled by 16s rRNA gene sequencing in two population-based Dutch cohorts: LifeLines-Deep (LLD, n = 616, discovery) and the Netherlands Twin Register (NTR, n = 296, replication). In LLD, we also explored microbiome composition using data generated by shotgun metagenomic sequencing (n = 683). We then investigated if genetic and environmental factors can explain the methylation-microbiota associations in a set of 78 associated CpG-taxa pairs from the EWAS meta-analysis. In both cohorts, blood and stool samples were collected within 2 weeks of each other. Methylation was profiled in blood samples using the Illumina 450K array. Methylation and microbiome analysis pipelines were harmonized across cohorts. Epigenome-wide association study (EWAS) of microbial features were analysed using linear regression with adjustment for technical covariates. Discovery and replication analysis using 16s data identified two independent CpGs associated with the genus Eggerthella: cg16586104 (Pmeta-analysis = 3.21 x 10-11) and cg12234533 (Pmeta-analysis = 4.29 x 10-10). While we did not find human genetic variants that could explain the associated CpG-taxa/pathway pairs, we show that microbiome can mediate the effect of environmental factors on epigenetics. In this first association study linking epigenome to microbiome, we found and replicated the associations of two CpGs to the abundance of genus Eggerthella and identified microbiome as a mediator of the exposome.

genomics↗

bioRxiv2022

Genome-wide DNA methylation profiles in smoking discordant and concordant monozygotic twin pairs

Smoking-associated DNA methylation levels identified through epigenome-wide association studies (EWAS) are generally ascribed to smoking-reactive mechanisms, but the contribution of a shared genetic predisposition to smoking and DNA methylation levels is typically not accounted for. We exploited a strong within-family design, i.e., the discordant monozygotic twin design, to study reactiveness of DNA methylation in blood cells to smoking and reversibility of methylation patterns upon quitting smoking. Illumina HumanMethylation450 BeadChip data were available for 769 monozygotic twin pairs (mean age=36 years,range=18-78, 70% female), including pairs discordant or concordant for current or former smoking. In pairs discordant for current smoking, 13 differentially methylated CpGs were found between current smoking twins and their genetically identical co-twin who never smoked. Top sites include multiple CpGs in CACNA1D and GNG12, which encode subunits of a calcium voltage-gated channel and G protein, respectively. These proteins interact with the nicotinic acetylcholine receptor, suggesting that methylation levels at these CpGs might be reactive to nicotine exposure. All 13 CpGs have been previously associated with smoking in unrelated individuals and data from monozygotic pairs discordant for former smoking indicated that methylation patterns are to a large extent reversible upon smoking cessation. We further showed that differences in smoking level exposure for monozygotic twins who are both current smokers but differ in the number of cigarettes they smoke are reflected in their DNA methylation profiles. In conclusion, by analysing data from monozygotic twins, we robustly demonstrate that DNA methylation level in human blood cells is reactive to cigarette smoking.

genomics↗

bioRxiv2020

Safe linkage of cohort and population-based register data in a genome-wide association study on health care expenditure

BackgroundThere are research questions whose answers require record linkage of multiple databases which may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run analyses in a high performance computing (HPC) environment. MethodsAfter successful record linkage genome-wide association (GWA) analyses were carried out on expenditure for total health, mental health, primary and hospital care and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and SNP-based heritability. ResultsThe total heritability of expenditure ranged between 29.4 (SE 0.8) and 37.5 (SE 0.8) per cent, but GWA analyses did not identify single SNPs or genes that were genome-wide significantly associated with health care expenditure. SNP-based heritability was between 0.0 (SE 3.5) and 5.4 (SE 4.0) per cent and was different from zero for mental health care and primary care expenditure. ConclusionsWe successfully linked genotype data to administrative health care expenditure data from Statistics Netherlands and performed a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analysing linked data in large-scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions. Key messagesO_LICohort data of the Netherlands Twin Register were safely linked to population-based register data of Statistics Netherlands C_LIO_LIOn the ODISSEI Secure Supercomputer (OSSC) platform genome-wide association analyses were carried out on linked genotype and health care expenditure data C_LIO_LIVariation in health care expenditure was for approximately one third explained by family-based heritability, but SNP-heritability based on genetic similarity across unrelated individuals explained only a very small proportion of variance C_LIO_LIThe newly developed platform can serve as a prototype for realizing genome-wide association studies with sensitive data C_LI

genetics↗

bioRxiv2019

The genomic architecture of blood metabolites based on a decade of genome-wide analyses

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes and lipid species. We performed a review of all genetic association studies, and identified > 800 class-specific metabolite loci that influence metabolite levels. In a twin-family cohort (N = 5,117), these metabolite loci were leveraged to simultaneously estimate total heritability (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study revealed significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation had higher h2Metabolite-hits estimates than phosphatidylcholines with a low degree of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes and lipid species.

genetics↗

bioRxiv2018

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

AO_SCPLOWBSTRACTC_SCPLOWHumans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. While the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. While it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition towards loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we conducted a genome-wide association (GWAS) meta-analysis of loneliness (N=475,661), report 12 associated loci (two novel) and significant genetic correlations with 34 other complex traits. The polygenic basis for loneliness was significantly enriched for evolutionary constrained genes and genes expressed in specific brain tissues: (frontal) cortex, cerebellum, anterior cingulate cortex, and substantia nigra. We built polygenic scores based on this GWAS meta-analysis to explore the genetic association between loneliness and health outcomes in an independent sample of 18,498 individuals for whom electronic health records were available. A genetic predisposition towards loneliness predicted cardiovascular, psychiatric, and metabolic disorders, and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, effect of body fat on loneliness, and a similar weaker causal effect of BMI. Our results provide a framework for ongoing studies of the genetic basis of loneliness and its role in mental and physical health.

genetics↗

bioRxiv2017

Multivariate Genome-Wide and Integrated Transcriptome and Epigenome-Wide Analyses of the Well-being Spectrum.

Phenotypes related to well-being (life satisfaction, positive affect, neuroticism, and depressive symptoms), are genetically highly correlated (| rg | > .75). Multivariate genome-wide analyses (Nobs = 958,149) of these traits, collectively referred to as the well-being spectrum, reveals 63 significant independent signals, of which 29 were not previously identified. Transcriptome and epigenome analyses implicate variation in gene expression at 8 additional loci and CpG methylation at 6 additional loci in the etiology of well-being. We leverage an anatomically comprehensive survey of gene expression in the brain to annotate our findings, showing that SNPs within genes excessively expressed in the cortex and part of the hippocampal formation are enriched in their effect on well-being.

genetics↗