@article {456, title = {Integrative multi-omics analysis of childhood aggressive behavior}, journal = {Behavior Genetics}, volume = {53}, year = {2023}, pages = {101{\textendash}117}, abstract = {

This study introduces and illustrates the potential of an integrated multi-omics approach in investigating the underlying biology of complex traits such as childhood aggressive behavior. In 645 twins (cases\ =\ 42\%), we trained single- and integrative multi-omics models to identify biomarkers for subclinical aggression and investigated the connections among these biomarkers. Our data comprised transmitted and two non-transmitted polygenic scores (PGSs) for 15 traits, 78,772 CpGs, and 90 metabolites. The single-omics models selected 31 PGSs, 1614 CpGs, and 90 metabolites, and the multi-omics model comprised 44 PGSs, 746 CpGs, and 90 metabolites. The predictive accuracy for these models in the test (N\ =\ 277, cases\ =\ 42\%) and independent clinical data (N\ =\ 142, cases\ =\ 45\%) ranged from 43 to 57\%. We observed strong connections between DNA methylation, amino acids, and parental non-transmitted PGSs for ADHD, Autism Spectrum Disorder, intelligence, smoking initiation, and self-reported health. Aggression-related omics traits link to known and novel risk factors, including inflammation, carcinogens, and smoking.

}, keywords = {childhood aggression, DNA methylation, Genetic nurturing, metabolomics, Multi-omics, polygenic scores}, doi = {10.1007/s10519-022-10126-7}, author = {Hagenbeek, Fiona A and van Dongen, Jenny and Pool, Ren{\'e} and Roetman, Peter J and Harms, Amy C and Hottenga, Jouke Jan and Kluft, Cornelis and Colins, Olivier F and van Beijsterveldt, Catharina E M and Fanos, Vassilios and Ehli, Erik A and Hankemeier, Thomas and Vermeiren, Robert R J M and Bartels, Meike and D{\'e}jean, S{\'e}bastien and Boomsma, Dorret I} } @article {471, title = {Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder}, journal = {American Journal of Medical Genetics Part B: Neuropsychiatric Genetics}, year = {2023}, pages = {e32955}, abstract = {

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases\ =\ 14.8\%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N\ =\ 258, cases\ =\ 14.3\%) and in a clinical sample (N\ =\ 145, cases\ =\ 51\%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.

}, keywords = {ADHD, DNA methylation, genetic nurture, metabolites, Multi-omics, polygenic scores}, doi = {10.1002/ajmg.b.32955}, author = {Hubers, Nikki and Hagenbeek, Fiona A and Pool, Ren{\'e} and D{\'e}jean, S{\'e}bastien and Harms, Amy C and Roetman, Peter J and van Beijsterveldt, Catharina E M and Fanos, Vassilios and Ehli, Erik A and Vermeiren, Robert R J M and Bartels, Meike and Hottenga, Jouke Jan and Hankemeier, Thomas and van Dongen, Jenny and Boomsma, Dorret I} } @article {457, title = {Heritability of urinary amines, organic acids, and steroid hormones in children}, journal = {Metabolites}, volume = {12}, year = {2022}, pages = {474}, abstract = {

Variation in metabolite levels reflects individual differences in genetic and environmental factors. Here, we investigated the role of these factors in urinary metabolomics data in children. We examined the effects of sex and age on 86 metabolites, as measured on three metabolomics platforms that target amines, organic acids, and steroid hormones. Next, we estimated their heritability in a twin cohort of 1300 twins (age range: 5.7-12.9 years). We observed associations between age and 50 metabolites and between sex and 21 metabolites. The monozygotic (MZ) and dizygotic (DZ) correlations for the urinary metabolites indicated a role for non-additive genetic factors for 50 amines, 13 organic acids, and 6 steroids. The average broad-sense heritability for these amines, organic acids, and steroids was 0.49 (range: 0.25-0.64), 0.50 (range: 0.33-0.62), and 0.64 (range: 0.43-0.81), respectively. For 6 amines, 7 organic acids, and 4 steroids the twin correlations indicated a role for shared environmental factors and the average narrow-sense heritability was 0.50 (range: 0.37-0.68), 0.50 (range; 0.23-0.61), and 0.47 (range: 0.32-0.70) for these amines, organic acids, and steroids. We conclude that urinary metabolites in children have substantial heritability, with similar estimates for amines and organic acids, and higher estimates for steroid hormones.

}, keywords = {amines, children, classical twin design, heritability, metabolites, organic acids, steroid hormones, urine}, doi = {10.3390/metabo12060474}, author = {Hagenbeek, Fiona A and van Dongen, Jenny and Pool, Ren{\'e} and Harms, Amy C and Roetman, Peter J and Fanos, Vassilios and van Keulen, Britt J and Walker, Brian R and Karu, Naama and Hulshoff Pol, Hilleke E and Rotteveel, Joost and Finken, Martijn J J and Vermeiren, Robert R J M and Kluft, Cornelis and Bartels, Meike and Hankemeier, Thomas and Boomsma, Dorret I} } @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 {426, title = {Urinary Amine and organic acid metabolites evaluated as markers for childhood aggression: The ACTION biomarker study}, journal = {Frontiers in Psychiatry}, volume = {11}, year = {2020}, pages = {165}, abstract = {

Biomarkers are of interest as potential diagnostic and predictive instruments in personalized medicine. We present the first urinary metabolomics biomarker study of childhood aggression. We aim to examine the association of urinary metabolites and neurotransmitter ratios involved in key metabolic and neurotransmitter pathways in a large cohort of twins (N = 1,347) and clinic-referred children (N = 183) with an average age of 9.7 years. This study is part of ACTION (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies), in which we developed a standardized protocol for large-scale collection of urine samples in children. Our analytical design consisted of three phases: a discovery phase in twins scoring low or high on aggression (N = 783); a replication phase in twin pairs discordant for aggression (N = 378); and a validation phase in clinical cases and matched twin controls (N = 367). In the discovery phase, 6 biomarkers were significantly associated with childhood aggression, of which the association of O-phosphoserine ($\beta$ = 0.36; SE = 0.09; p = 0.004), and gamma-L-glutamyl-L-alanine ($\beta$ = 0.32; SE = 0.09; p = 0.01) remained significant after multiple testing. Although non-significant, the directions of effect were congruent between the discovery and replication analyses for six biomarkers and two neurotransmitter ratios and the concentrations of 6 amines differed between low and high aggressive twins. In the validation analyses, the top biomarkers and neurotransmitter ratios, with congruent directions of effect, showed no significant associations with childhood aggression. We find suggestive evidence for associations of childhood aggression with metabolic dysregulation of neurotransmission, oxidative stress, and energy metabolism. Although replication is required, our findings provide starting points to investigate causal and pleiotropic effects of these dysregulations on childhood aggression.

}, keywords = {amines, biomarkers, childhood aggression, metabolites, metabolomics, neurotransmitters, organic acids, oxidative stress}, doi = {10.3389/fpsyt.2020.00165}, author = {Hagenbeek, Fiona A and Roetman, Peter J and Pool, Ren{\'e} and Kluft, Cornelis and Harms, Amy C and van Dongen, Jenny and Colins, Olivier F and Talens, Simone and van Beijsterveldt, Catharina E M and Vandenbosch, Marjolein M L J Z and de Zeeuw, Eveline L and D{\'e}jean, S{\'e}bastien and Fanos, Vassilios and Ehli, Erik A and Davies, Gareth E and Hottenga, Jouke Jan and Hankemeier, Thomas and Bartels, Meike and Vermeiren, Robert R J M and Boomsma, Dorret I} }