@article {470, title = {Genetics and epigenetics of human aggression}, journal = {Handbook of Clinical Neurology, Brain and Crime}, volume = {197}, year = {2023}, pages = {13{\textendash}44}, abstract = {

There is substantial variation between humans in aggressive behavior, with its biological etiology and molecular genetic basis mostly unknown. This review chapter offers an overview of genomic and omics studies revealing the genetic contribution to aggression and first insights into associations with epigenetic and other omics (e.g., metabolomics) profiles. We allowed for a broad phenotype definition including studies on \"aggression\", \"aggressive behavior\" or \"aggression-related traits\", \"antisocial behavior\", \"conduct disorder\", and \"oppositional defiant disorder\". Heritability estimates based on family and twin studies in children and adults of this broadly defined phenotype of aggression are around 50\%, with relatively small fluctuations around this estimate. Next, we review the genome-wide association studies (GWAS) which search for associations with alleles and also allow for gene-based tests and epigenome-wide association studies (EWAS) which seek to identify associations with differently methylated regions across the genome. Both GWAS and EWAS allow for construction of Polygenic and DNA methylation scores at an individual level. Currently, these predict a small percentage of variance in aggression. We expect that increases in sample size will lead to additional discoveries in GWAS and EWAS, and that multiomics approaches will lead to a more comprehensive understanding of the molecular underpinnings of aggression.

}, keywords = {Epigenome-wide association studies, Epigenomics, genome-wide association studies, Genomics, heritability, Human aggression}, doi = {10.1016/B978-0-12-821375-9.00005-0}, author = {Odintsova, Veronika V and Hagenbeek, Fiona A and Van der Laan, Camiel M and van de Weijer, Steve and Boomsma, Dorret I} } @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 {434, title = {Genetically informed regression analysis: Application to aggression prediction by inattention and hyperactivity in children and adults}, journal = {Behavior Genetics}, volume = {51}, year = {2021}, pages = {250{\textendash}263}, abstract = {

We present a procedure to simultaneously fit a genetic covariance structure model and a regression model to multivariate data from mono- and dizygotic twin pairs to test for the prediction of a dependent trait by multiple correlated predictors. We applied the model to aggressive behavior as an outcome trait and investigated the prediction of aggression from inattention (InA) and hyperactivity (HA) in two age groups. Predictions were examined in twins with an average age of 10 years (11,345 pairs), and in adult twins with an average age of 30 years (7433 pairs). All phenotypes were assessed by the same, but age-appropriate, instruments in children and adults. Because of the different genetic architecture of aggression, InA and HA, a model was fitted to these data that specified additive and non-additive genetic factors (A and D) plus common and unique environmental (C and E) influences. Given appropriate identifying constraints, this ADCE model is identified in trivariate data. We obtained different results for the prediction of aggression in children, where HA was the more important predictor, and in adults, where InA was the more important predictor. In children, about 36\% of the total aggression variance was explained by the genetic and environmental components of HA and InA. Most of this was explained by the genetic components of HA and InA, i.e., 29.7\%, with 22.6\% due to the genetic component of HA. In adults, about 21\% of the aggression variance was explained. Most was this was again explained by the genetic components of InA and HA (16.2\%), with 8.6\% due to the genetic component of InA.

}, keywords = {Aggression, Genetic and environmental prediction, Hyperactivity, Inattention, Regression, Structural equation model}, doi = {10.1007/s10519-020-10025-9}, author = {Boomsma, Dorret I and van Beijsterveldt, Toos C E M and Odintsova, Veronika V and Neale, Michael C and Dolan, Conor V} } @article {440, title = {Identical twins carry a persistent epigenetic signature of early genome programming}, journal = {Nature Communications}, volume = {12}, year = {2021}, pages = {5618}, abstract = {

Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.

}, doi = {10.1038/s41467-021-25583-7}, author = {van Dongen, Jenny and Gordon, Scott D and McRae, Allan F and Odintsova, Veronika V and Mbarek, Hamdi and Breeze, Charles E and Sugden, Karen and Lundgren, Sara and Castillo-Fernandez, Juan E and Hannon, Eilis and Moffitt, Terrie E and Hagenbeek, Fiona A and van Beijsterveldt, Catharina E M and Jan Hottenga, Jouke and Tsai, Pei-Chien and BIOS Consortium and Genetics of DNA Methylation Consortium and Min, Josine L and Hemani, Gibran and Ehli, Erik A and Paul, Franziska and Stern, Claudio D and Heijmans, Bastiaan T and Slagboom, P Eline and Daxinger, Lucia and van der Maarel, Silv{\`e}re M and de Geus, Eco J C and Willemsen, Gonneke and Montgomery, Grant W and Reversade, Bruno and Ollikainen, Miina and Kaprio, Jaakko and Spector, Tim D and Bell, Jordana T and Mill, Jonathan and Caspi, Avshalom and Martin, Nicholas G and Boomsma, Dorret I} } @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 {417, title = {DNA methylation signatures of breastfeeding in buccal cells collected in mid-childhood}, journal = {Nutrients}, volume = {11}, year = {2019}, pages = {2804}, abstract = {

Breastfeeding has long-term benefits for children that may be mediated via the epigenome. This pathway has been hypothesized, but the number of empirical studies in humans is small and mostly done by using peripheral blood as the DNA source. We performed an epigenome-wide association study (EWAS) in buccal cells collected around age nine (mean = 9.5) from 1006 twins recruited by the Netherlands Twin Register (NTR). An age-stratified analysis examined if effects attenuate with age (median split at 10 years; n10 = 489, mean age = 11.2). We performed replication analyses in two independent cohorts from the NTR (buccal cells) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (peripheral blood), and we tested loci previously associated with breastfeeding in epigenetic studies. Genome-wide DNA methylation was assessed with the Illumina Infinium MethylationEPIC BeadChip (Illumina, San Diego, CA, USA) in the NTR and with the HumanMethylation450 Bead Chip in the ALSPAC. The duration of breastfeeding was dichotomized (\&$\#$39;never\&$\#$39; vs. \&$\#$39;ever\&$\#$39;). In the total sample, no robustly associated epigenome-wide significant CpGs were identified ($\alpha$ = 6.34 $\times$ 10-8). In the sub-group of children younger than 10 years, four significant CpGs were associated with breastfeeding after adjusting for child and maternal characteristics. In children older than 10 years, methylation differences at these CpGs were smaller and non-significant. The findings did not replicate in the NTR sample (n = 98; mean age = 7.5 years), and no nearby sites were associated with breastfeeding in the ALSPAC study (n = 938; mean age = 7.4). Of the CpG sites previously reported in the literature, three were associated with breastfeeding in children younger than 10 years, thus showing that these CpGs are associated with breastfeeding in buccal and blood cells. Our study is the first to show that breastfeeding is associated with epigenetic variation in buccal cells in children. Further studies are needed to investigate if methylation differences at these loci are caused by breastfeeding or by other unmeasured confounders, as well as what mechanism drives changes in associations with age.

}, keywords = {ALSPAC., breastfeeding, DNA methylation, EPIC, EWAS, NTR, twins}, doi = {10.3390/nu11112804}, author = {Odintsova, Veronika V and Hagenbeek, Fiona A and Suderman, Matthew and Caramaschi, Doretta and van Beijsterveldt, Catharina E M and Kallsen, Noah A and Ehli, Erik A and Davies, Gareth E and Sukhikh, Gennady T and Fanos, Vassilios and Relton, Caroline and Bartels, Meike and Boomsma, Dorret I and van Dongen, Jenny} } @article {413, title = {Genomics of human aggression: current state of genome-wide studies and an automated systematic review tool}, journal = {Psychiatric Genetics}, volume = {29}, year = {2019}, pages = {170{\textendash}190}, abstract = {

There are substantial differences, or variation, between humans in aggression, with its molecular genetic basis mostly unknown. This review summarizes knowledge on the genetic contribution to variation in aggression with the following three foci: (1) a comprehensive overview of reviews on the genetics of human aggression, (2) a systematic review of genome-wide association studies (GWASs), and (3) an automated tool for the selection of literature based on supervised machine learning. The phenotype definition \&$\#$39;aggression\&$\#$39; (or \&$\#$39;aggressive behaviour\&$\#$39;, or \&$\#$39;aggression-related traits\&$\#$39;) included anger, antisocial behaviour, conduct disorder, and oppositional defiant disorder. The literature search was performed in multiple databases, manually and using a novel automated selection tool, resulting in 18 reviews and 17 GWASs of aggression. Heritability estimates of aggression in children and adults are around 50\%, with relatively small fluctuations around this estimate. In 17 GWASs, 817 variants were reported as suggestive (P \≤ 1.0E), including 10 significant associations (P \≤ 5.0E). Nominal associations (P \≤ 1E) were found in gene-based tests for genes involved in immune, endocrine, and nervous systems. Associations were not replicated across GWASs. A complete list of variants and their position in genes and chromosomes are available online. The automated literature search tool produced literature not found by regular search strategies. Aggression in humans is heritable, but its genetic basis remains to be uncovered. No sufficiently large GWASs have been carried out yet. With increases in sample size, we expect aggression to behave like other complex human traits for which GWAS has been successful.

}, doi = {10.1097/YPG.0000000000000239}, author = {Odintsova, Veronika V and Roetman, Peter J and Ip, Hill F and Pool, Ren{\'e} and Van der Laan, Camiel M and Tona, Klodiana-Daphne and Vermeiren, Robert R J M and Boomsma, Dorret I} }