@article {433,
	title = {Genetic meta-analysis of twin birth weight shows high genetic correlation with singleton birth weight},
	journal = {Human Molecular Genetics},
	volume = {30},
	year = {2021},
	pages = {1894{\textendash}1905},
	abstract = {<p>Birth weight (BW) is an important predictor of newborn survival and health and has associations with many adult health outcomes, including cardiometabolic disorders, autoimmune diseases and mental health. On average, twins have a lower BW than singletons as a result of a different pattern of fetal growth and shorter gestational duration. Therefore, investigations into the genetics of BW often exclude data from twins, leading to a reduction in sample size and remaining ambiguities concerning the genetic contribution to BW in twins. In this study, we carried out a genome-wide association meta-analysis of BW in 42 212 twin individuals and found a positive correlation of beta values (Pearson\&$\#$39;s r = 0.66, 95\% confidence interval [CI]: 0.47-0.77) with 150 previously reported genome-wide significant variants for singleton BW. We identified strong positive genetic correlations between BW in twins and numerous anthropometric traits, most notably with BW in singletons (genetic correlation [rg] = 0.92, 95\% CI: 0.66-1.18). Genetic correlations of BW in twins with a series of health-related traits closely resembled those previously observed for BW in singletons. Polygenic scores constructed from a genome-wide association study on BW in the UK Biobank demonstrated strong predictive power in a target sample of Dutch twins and singletons. Together, our results indicate that a similar genetic architecture underlies BW in twins and singletons and that future genome-wide studies might benefit from including data from large twin registers.</p>
},
	doi = {10.1093/hmg/ddab121},
	author = {Beck, Jeffrey J and Pool, Ren{\'e} and van de Weijer, Margot and Chen, Xu and Krapohl, Eva and Gordon, Scott D and Nygaard, Marianne and Debrabant, Birgit and Palviainen, Teemu and van der Zee, Matthijs D and Baselmans, Bart and Finnicum, Casey T and Yi, Lu and Lundstr{\"o}m, Sebastian and van Beijsterveldt, Toos and Christiansen, Lene and Heikkil{\"a}, Kauko and Kittelsrud, Julie and Loukola, Anu and Ollikainen, Miina and Christensen, Kaare and Martin, Nicholas G and Plomin, Robert and Nivard, Michel and Bartels, Meike and Dolan, Conor and Willemsen, Gonneke and de Geus, Eco and Almqvist, Catarina and Magnusson, Patrik K E and Mbarek, Hamdi and Ehli, Erik A and Boomsma, Dorret I and Hottenga, Jouke-Jan}
}
@article {424,
	title = {Genetics and not shared environment explains familial resemblance in adult metabolomics data},
	journal = {Human Genetics},
	volume = {23},
	year = {2020},
	pages = {145{\textendash}155},
	abstract = {<p>Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term \&$\#$39;metabolomics\&$\#$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.</p>
},
	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}
}
