@article {424, title = {Genetics and not shared environment explains familial resemblance in adult metabolomics data}, journal = {Human Genetics}, volume = {23}, year = {2020}, pages = {145{\textendash}155}, abstract = {

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term \&$\#$39;metabolomics\&$\#$39; refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.

}, keywords = {classical twin design, enrichment analysis, heritability, metabolite classes, shared environment}, doi = {DOI: 10.1017/thg.2020.53}, author = {Pool, Ren{\'e} and Hagenbeek, Fiona A and Hendriks, Anne M and van Dongen, Jenny and Willemsen, Gonneke and de Geus, Eco and BBMRI Metabolomics Consortium and Willems van Dijk, Ko and Verhoeven, Aswin and Suchiman, H Eka and Beekman, Marian and Slagboom, P Eline and Harms, Amy C and Hankemeier, Thomas and Boomsma, Dorret I} } @article {427, title = {Heritability estimates for 361 blood metabolites across 40 genome-wide association studies}, journal = {Nature Communications}, volume = {11}, year = {2020}, pages = {39}, abstract = {

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. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify \>800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are 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 reveals significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2Metabolite-hits estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.

}, doi = {DOI: 10.1038/s41467-019-13770-6}, author = {Hagenbeek, Fiona A and Pool, Ren{\'e} and van Dongen, Jenny and Draisma, Harmen H M and Jan Hottenga, Jouke and Willemsen, Gonneke and Abdellaoui, Abdel and Fedko, Iryna O and den Braber, Anouk and Visser, Pieter Jelle and de Geus, Eco J C N and Willems van Dijk, Ko and Verhoeven, Aswin and Suchiman, H Eka and Beekman, Marian and Slagboom, P Eline and van Duijn, Cornelia M and BBMRI Metabolomics Consortium and Harms, Amy C and Hankemeier, Thomas and Bartels, Meike and Nivard, Michel G and Boomsma, Dorret I} } @article {227, title = {DNA methylation signatures of educational attainment}, volume = {3}, year = {2018}, month = {2018/03/23}, pages = {7}, abstract = {

Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. We measured DNA methylation at 410,746 CpGs (N\ =\ 4152) and identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28\% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62\% smaller in never smokers. We examined sources and biological implications of education-related methylation differences, demonstrating correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain. Our findings show that the methylome of lower-educated people resembles that of smokers beyond effects of their own smoking behaviour and shows traces of various other exposures.

}, isbn = {2056-7936}, url = {https://doi.org/10.1038/s41539-018-0020-2}, author = {Jenny van Dongen and Bonder, Marc Jan and Dekkers, Koen F. and Michel G. Nivard and van Iterson, Maarten and Gonneke Willemsen and Beekman, Marian and van der Spek, Ashley and Joyce B.J. Van Meurs and Franke, Lude and Bastiaan T. Heijmans and van Duijn, Cornelia M. and Slagboom, P. Eline and Dorret I. Boomsma} }