@article {467, title = {Genetic ancestry estimates within dutch family units and across genotyping arrays: insights from empirical analysis using two estimation methods}, journal = {Genes (Basel)}, volume = {14}, year = {2023}, pages = {1497}, abstract = {

Accurate inference of genetic ancestry is crucial for population-based association studies, accounting for population heterogeneity and structure. This study analyzes genome-wide SNP data from the Netherlands Twin Register to compare genetic ancestry estimates. The focus is on the comparison of ancestry estimates between family members and individuals genotyped on multiple arrays (Affymetrix 6.0, Affymetrix Axiom, and Illumina GSA). Two conventional methods, principal component analysis and ADMIXTURE, were implemented to estimate ancestry, each serving its specific purpose, rather than for direct comparison. The results reveal that as the degree of genetic relatedness decreases, the Euclidean distances of genetic ancestry estimates between family members significantly increase (empirical p \< 0.001), regardless of the estimation method and genotyping array. Ancestry estimates among individuals genotyped on multiple arrays also show statistically significant differences (empirical p \< 0.001). Additionally, this study investigates the relationship between the ancestry estimates of non-identical twin offspring with ancestrally diverse parents and those with ancestrally similar parents. The results indicate a statistically significant weak correlation between the variation in ancestry estimates among offspring and differences in ancestry estimates among parents (Spearman\’s rho: 0.07, p = 0.005). This study highlights the utility of current methods in inferring genetic ancestry, emphasizing the importance of reference population composition in determining ancestry estimates.

}, keywords = {ADMIXTURE, genetic ancestry estimation, population structure, principal components analysis (PCA), within-family analysis}, doi = {10.3390/genes14071497}, author = {Beck, Jeffrey J and Ahmed, Talitha and Finnicum, Casey T and Zwinderman, Koos and Ehli, Erik A and Boomsma, Dorret I and Hottenga, Jouke Jan} } @article {463, title = {DNA methylation in peripheral tissues and left-handedness}, journal = {Scientific Reports}, volume = {12}, year = {2022}, pages = {5606}, abstract = {

Handedness has low heritability and epigenetic mechanisms have been proposed as an etiological mechanism. To examine this hypothesis, we performed an epigenome-wide association study of left-handedness. In a meta-analysis of 3914 adults of whole-blood DNA methylation, we observed that CpG sites located in proximity of handedness-associated genetic variants were more strongly associated with left-handedness than other CpG sites (P = 0.04), but did not identify any differentially methylated positions. In longitudinal analyses of DNA methylation in peripheral blood and buccal cells from children (N = 1737), we observed moderately stable associations across age (correlation range [0.355-0.578]), but inconsistent across tissues (correlation range [- 0.384 to 0.318]). We conclude that DNA methylation in peripheral tissues captures little of the variance in handedness. Future investigations should consider other more targeted sources of tissue, such as the brain.

}, doi = {10.1038/s41598-022-08998-0}, author = {Odintsova, Veronika V and Suderman, Matthew and Hagenbeek, Fiona A and Caramaschi, Doretta and Hottenga, Jouke-Jan and Pool, Ren{\'e} and BIOS Consortium and Dolan, Conor V and Ligthart, Lannie and van Beijsterveldt, Catharina E M and Willemsen, Gonneke and de Geus, Eco J C and Beck, Jeffrey J and Ehli, Erik A and Cuellar-Partida, Gabriel and Evans, David M and Medland, Sarah E and Relton, Caroline L and Boomsma, Dorret I and van Dongen, Jenny} } @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 = {

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.

}, 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 {446, title = {Predicting complex traits and exposures from polygenic scores and blood and buccal DNA methylation profiles}, journal = {Frontiers in Psychiatry}, volume = {12}, year = {2021}, pages = {688464}, abstract = {

We examined the performance of methylation scores (MS) and polygenic scores (PGS) for birth weight, BMI, prenatal maternal smoking exposure, and smoking status to assess the extent to which MS could predict these traits and exposures over and above the PGS in a multi-omics prediction model. MS may be seen as the epigenetic equivalent of PGS, but because of their dynamic nature and sensitivity of non-genetic exposures may add to complex trait prediction independently of PGS. MS and PGS were calculated based on genotype data and DNA-methylation data in blood samples from adults (Illumina 450 K; N = 2,431; mean age 35.6) and in buccal samples from children (Illumina EPIC; N = 1,128; mean age 9.6) from the Netherlands Twin Register. Weights to construct the scores were obtained from results of large epigenome-wide association studies (EWASs) based on whole blood or cord blood methylation data and genome-wide association studies (GWASs). In adults, MSs in blood predicted independently from PGSs, and outperformed PGSs for BMI, prenatal maternal smoking, and smoking status, but not for birth weight. The largest amount of variance explained by the multi-omics prediction model was for current vs. never smoking (54.6\%) of which 54.4\% was captured by the MS. The two predictors captured 16\% of former vs. never smoking initiation variance (MS:15.5\%, PGS: 0.5\%), 17.7\% of prenatal maternal smoking variance (MS:16.9\%, PGS: 0.8\%), 11.9\% of BMI variance (MS: 6.4\%, PGS 5.5\%), and 1.9\% of birth weight variance (MS: 0.4\%, PGS: 1.5\%). In children, MSs in buccal samples did not show independent predictive value. The largest amount of variance explained by the two predictors was for prenatal maternal smoking (2.6\%), where the MSs contributed 1.5\%. These results demonstrate that blood DNA MS in adults explain substantial variance in current smoking, large variance in former smoking, prenatal smoking, and BMI, but not in birth weight. Buccal cell DNA methylation scores have lower predictive value, which could be due to different tissues in the EWAS discovery studies and target sample, as well as to different ages. This study illustrates the value of combining polygenic scores with information from methylation data for complex traits and exposure prediction.

}, keywords = {birth weight, BMI, DNA methylation, maternal smoking, methylation scores, multi-omics prediction, polygenic scores, smoking}, doi = {10.3389/fpsyt.2021.688464}, author = {Odintsova, Veronika V and Rebattu, Valerie and Hagenbeek, Fiona A and Pool, Ren{\'e} and Beck, Jeffrey J and Ehli, Erik A and van Beijsterveldt, Catharina E M and Ligthart, Lannie and Willemsen, Gonneke and de Geus, Eco J C and Hottenga, Jouke-Jan and Boomsma, Dorret I and van Dongen, Jenny} } @article {412, title = {Biological insights into multiple birth: genetic findings from UK Biobank}, journal = {European Journal of Human Genetics}, volume = {27}, year = {2019}, pages = {970{\textendash}979}, abstract = {

The tendency to conceive spontaneous dizygotic (DZ) twins is a complex trait with important contributions from both environmental factors and genetic disposition. In earlier work, we identified the first two genes as maternal susceptibility loci for DZ twinning. The aim of this study was to identify genetic variants influencing multiple births and to genetically correlate the findings across a broad range of traits. We performed a genome-wide association study (GWAS) in 8962 participants with Caucasian ancestry from UK Biobank who reported being part of a multiple birth, and 409,591 singleton controls. We replicated the association between FSHB, SMAD3 and twinning in the gene-based (but not SNP-based) test, which had been established in previous genome-wide association analyses in mothers with dizygotic twin offspring. Additionally, we report a novel genetic variant associated with multiple birth, rs428022 at 15q23 (p = 2.84 $\times$ 10-8) close to two genes: PIAS1 and SKOR1. Finally, we identified meaningful genetic correlations between being part of a multiple birth and other phenotypes (anthropometric traits, health-related traits, and fertility-related measures). The outcomes of this study provide important new insights into the genetic aetiology of multiple births and fertility, and open up novel directions for fertility and reproduction research.

}, doi = {10.1038/s41431-019-0355-z}, author = {Mbarek, Hamdi and van de Weijer, Margot P and van der Zee, Mathijs D and Ip, Hill F and Beck, Jeffrey J and Abdellaoui, Abdel and Ehli, Erik A and Davies, Gareth E and Baselmans, Bart M L and Nivard, Michel G and Bartels, Meike and de Geus, Eco J and Boomsma, Dorret I} }