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STUDY QUESTION Does having a male co-twin, older brothers, or sons lead to an increased probability of persistent male microchimerism in female members of twin pedigrees? SUMMARY ANSWER The presence of a male co-twin did not increase risk of male microchimerism and the prevalence of male microchimerism was not explained by having male offspring or by having an older brother. WHAT IS KNOWN ALREADY Microchimerism describes the presence of cells within an organism that originate from another zygote and is commonly described as resulting from pregnancy in placental mammals. It is associated with diseases with a female predilection including autoimmune diseases and pregnancy-related complications. However, microchimerism also occurs in nulliparous women; signifying gaps in the understanding of risk factors contributing to persistent microchimerism and the origin of the minor cell population. STUDY DESIGN, SIZE, DURATION This cross-sectional study composed of 446 adult female participants of the Netherlands Twin Register (NTR). PARTICIPANTS/MATERIALS, SETTING, METHODS Participants included in the study were female monozygotic (MZ) twins, female dizygotic same-sex twins and females of dizygotic opposite-sex twin pairs, along with the mothers and sisters of these twins. Peripheral blood samples collected from adult female participants underwent DNA extraction and were biobanked prior to the study. To detect the presence of male-origin microchimerism, DNA samples were tested for the relative quantity of male specific Y chromosome gene DYS14 compared to a common β-globin gene using a highly sensitive quantitative PCR assay. MAIN RESULTS AND THE ROLE OF CHANCE We observed a large number of women (26.9%) having detectable male microchimerism in their peripheral blood samples. The presence of a male co-twin did not increase risk of male microchimerism (odds ratio (OR) = 1.23: SE 0.40, P = 0.61) and the prevalence of male microchimerism was not explained by having male offspring (OR 0.90: SE 0.19, P = 0.63) or by having an older brother (OR = 1.46: SE 0.32, P = 0.09). The resemblance (correlation) for the presence of microchimerism was similar (P = 0.66) in MZ pairs (0.27; SE 0.37) and in first-degree relatives (0.091; SE 0.092). However, age had a positive relationship with the presence of male microchimerism (P = 0.02). LIMITATIONS, REASONS FOR CAUTION After stratifying for variables of interest, some participant groups resulted in a low numbers of subjects. We investigated microchimerism in peripheral blood due to the proposed mechanism of cell acquisition via transplacental blood exchange; however, this does not represent global chimerism in the individual and microchimerism may localize to numerous other tissues. WIDER IMPLICATIONS OF THE FINDINGS Immune regulation during pregnancy is known to mitigate allosensitization and support tolerance to non-inherited antigens found on donor cells. While unable to identify a specific source that promotes microchimerism prevalence within pedigrees, this study points to the underlying complexities of natural microchimerism in the general population. These findings support previous studies which have identified the presence of male microchimerism among women with no history of pregnancy, suggesting alternative sources of microchimerism. The association of detectable male microchimerism with age is suggestive of additional factors including time, molecular characteristics and environment playing a critical role in the prevalence of persistent microchimerism. The present study necessitates investigation into the molecular underpinnings of natural chimerism to provide insight into women’s health, transplant medicine and immunology. STUDY FUNDING/COMPETING INTEREST(S) This work is funded by Royal Netherlands Academy of Science Professor Award (PAH/6635 to D.I.B.); The Netherlands Organisation for Health Research and Development (ZonMw)—Genotype/phenotype database for behavior genetic and genetic epidemiological studies (ZonMw 911-09-032); Biobanking and Biomolecular Research Infrastructure (BBMRI–NL, 184.021.007; 184.033.111); The Netherlands Organisation for Scientific Research (NWO)—Netherlands Twin Registry Repository (NWO-Groot 480-15-001/674); the National Institutes of Health—The Rutgers University Cell and DNA Repository cooperative agreement (NIMH U24 MH068457-06), Grand Opportunity grants Integration of genomics and transcriptomics in normal twins and major depression (NIMH 1RC2 MH089951-01), and Developmental trajectories of psychopathology (NIMH 1RC2 MH089995); and European Research Council—Genetics of Mental Illness (ERC 230374). C.B.L. declares a competing interest as editor-in-chief of Human Reproduction and his department receives unrestricted research grants from Ferring, Merck and Guerbet. All remaining authors have no conflict-of-interest to declare in regards to this work. TRIAL REGISTRATION NUMBER N/A.

The classical twin model can be reparametrized as an equivalent multilevel model. The multilevel parameterization has underexplored advantages, such as the possibility to include higher-level clustering variables in which lower levels are nested. When this higher-level clustering is not modeled, its variance is captured by the common environmental variance component. In this paper we illustrate the application of a 3-level multilevel model to twin data by analyzing the regional clustering of 7-year-old children’s height in the Netherlands. Our findings show that 1.8%, of the phenotypic variance in children’s height is attributable to regional clustering, which is 7% of the variance explained by between-family or common environmental components. Since regional clustering may represent ancestry, we also investigate the effect of region after correcting for genetic principal components, in a subsample of participants with genome-wide SNP data. After correction, region did no longer explain variation in height. Our results suggest that the phenotypic variance explained by region actually represent ancestry effects on height.

The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies. Here, we present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5-26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses). We identified a genome-wide significant association with word reading (rs11208009, p=1.098 × 10−8) independent of known loci associated with intelligence or educational attainment. All five reading-/language-related traits had robust SNP-heritability estimates (0.13–0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS was performed to jointly analyse word and nonword reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language. Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.

Variable preferences for different foods are among the main determinants of their intake and are influenced by many factors, including genetics. Despite considerable twins’ heritability, studies aimed at uncovering food-liking genetics have focused mostly on taste receptors. Here, we present the first results of a large-scale genome-wide association study of food liking conducted on 161,625 participants from UK Biobank. Liking was assessed over 139 specific foods using a 9-point hedonic scale. After performing GWAS, we used genetic correlations coupled with structural equation modelling to create a multi-level hierarchical map of food liking. We identified three main dimensions: high caloric foods defined as “Highly palatable”, strong-tasting foods ranging from alcohol to pungent vegetables, defined as “Learned” and finally “Low caloric” foods such as fruit and vegetables. The “Highly palatable” dimension was genetically uncorrelated from the other two, suggesting that two independent processes underlie liking high reward foods and the Learned/Low caloric ones. Genetic correlation analysis with the corresponding food consumption traits revealed a high correlation, while liking showed twice the heritability compared to consumption. For example, fresh fruit liking and consumption showed a genetic correlation of 0.7 with heritabilities of 0.1 and 0.05, respectively. GWAS analysis identified 1401 significant food-liking associations located in 173 genomic loci, with only 11 near taste or olfactory receptors. Genetic correlation with morphological and functional brain data (33,224 UKB participants) uncovers associations of the three food-liking dimensions with non-overlapping, distinct brain areas and networks, suggestive of separate neural mechanisms underlying the liking dimensions. In conclusion, we created a comprehensive and data-driven map of the genetic determinants and associated neurophysiological factors of food liking beyond taste receptor genes.

Background: Ill decisions and reckless behaviors due to low self-control are concurrently and longitudinally costly, and revealing possible factors contributing to individual differences in self-control is necessary. It is hypothesized that genetically sensitivity interacts with life stressors in the prediction of the development of low self-control (gene environment interaction), yet attempts to test this hypothesis mostly concern candidate gene studies yielding inconclusive results. The goal of this research was to bring findings from large scale gene identification studies into the developmental psychology framework, taking the polygenic nature of complex traits into account. Methods: Using data of a large population-based twin sample, we tested whether polygenic risk scores for self-control problems – based on the most recent ADHD GWAS – predict self-control problems in adults, and whether this polygenic risk scores interact with the presence of environmental stressors. Results: While polygenic scores and life stressors significantly predicted low self-control, we did not find a significant interaction effect. Conclusions: Empirically, finding statistical evidence for this hypothesis remains a challenge, and more research is needed to investigate how to better detect G x E.

IntroductionIt’s imperative to understand the specific and shared aetiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression.MethodsPolygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic aetiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in eleven data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank.ResultsAll cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression.ConclusionsThe phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic aetiology irrespective of the age depression first presents.

We aimed to detect Attention-deficit/hyperactivity (ADHD) risk-conferring genes in adults. In children, ADHD is characterized by age-inappropriate levels of inattention and/or hyperactivity-impulsivity and may persists into adulthood. Childhood and adulthood ADHD are heritable, and are thought to represent the clinical extreme of a continuous distribution of ADHD symptoms in the general population. We aimed to leverage the power of studies of quantitative ADHD symptoms in adults who were genotyped. Within the SAGA (Study of ADHD trait genetics in adults) consortium, we estimated the single nucleotide polymorphism (SNP)-based heritability of quantitative self-reported ADHD symptoms and carried out a genome-wide association meta-analysis in nine adult population-based and case-only cohorts of adults. A total of n = 14,689 individuals were included. In two of the SAGA cohorts we found a significant SNP-based heritability for self-rated ADHD symptom scores of respectively 15% (n = 3656) and 30% (n = 1841). The top hit of the genome-wide meta-analysis (SNP rs12661753; p-value = 3.02 × 10 −7 ) was present in the long non-coding RNA gene STXBP5-AS1. This association was also observed in a meta-analysis of childhood ADHD symptom scores in eight population-based pediatric cohorts from the Early Genetics and Lifecourse Epidemiology (EAGLE) ADHD consortium (n = 14,776). Genome-wide meta-analysis of the SAGA and EAGLE data (n = 29,465) increased the strength of the association with the SNP rs12661753. In human HEK293 cells, expression of STXBP5-AS1 enhanced the expression of a reporter construct of STXBP5, a gene known to be involved in “SNAP” (Soluble NSF attachment protein) Receptor” (SNARE) complex formation. In mouse strains featuring different levels of impulsivity, transcript levels in the prefrontal cortex of the mouse ortholog Gm28905 strongly correlated negatively with motor impulsivity as measured in the five choice serial reaction time task (r 2 = − 0.61; p = 0.004). Our results are consistent with an effect of the STXBP5-AS1 gene on ADHD symptom scores distribution and point to a possible biological mechanism, other than antisense RNA inhibition, involved in ADHD-related impulsivity levels.

The interrelations among well-being, neuroticism, and depression can be captured in a so-called well-being spectrum (3-phenotype well-being spectrum, 3-WBS). Several other human traits are likely linked to the 3-WBS. In the present study, we investigate how the 3-WBS can be expanded. First, we constructed polygenic risk scores for the 3-WBS and used this score to predict a series of traits that have been associated with well-being in the literature. We included information on loneliness, big five personality traits, self-rated health, and flourishing. The 3-WBS polygenic score predicted all the original 3-WBS traits and additionally loneliness, self-rated health, and extraversion (R2 between 0.62% and 1.58%). Next, using LD score regression, we calculated genetic correlations between the 3-WBS and the traits of interest. From all candidate traits, loneliness and self-rated health were found to have the strongest genetic correlations (rg = − 0.79, and rg= 0.64, respectively) with the 3-WBS. Lastly, we use Genomic SEM to investigate the factor structure of the proposed spectrum. The best model fit was obtained for a two-factor model including the 5-WBS traits, with two highly correlated factors representing the negative- and positive end of the spectrum. Based on these analyses we propose to include loneliness and self-rated health in the WBS and use a 5-phenotype well-being spectrum in future studies to gain more insight into the determinants of human well-being. Electronic supplementary material The online version of this article (10.1007/s10519-019-09951-0) contains supplementary material, which is available to authorized users.

Following publication of this article, the authors noticed an error in Supplementary Table 1. In the original Supplementary Table 1, one of the criteria for control participants was incorrectly given as ‘Report extensive recent symptoms of depression: less than 14 on summed response (where “not at all” = 1 and “nearly every day” = 4) to recent’. This has now been corrected to: ‘Report extensive recent symptoms of depression: less than 5 on summed response (where “not at all” = 1 and “nearly every day” = 4) to recent’.

This study was funded by grants from the Templeton World Charity Foundation, Inc., the Medical Research Council, the Wellcome Trust, the Autism Research Trust, the Institut Pasteur, the CNRS and the University Paris Diderot. VW is funded by St. John’s College, Cambridge, and Cambridge Commonwealth Trust. The research was carried out in association with the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care East of England at Cambridgeshire and Peterborough NHS Foundation Trust. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The research was supported by the National Human Genome Research Institute of the National Institutes of Health (grant number R44HG006981). The National Science Foundation (grant numbers 0729493 and 0721707) supported the research on the Brisbane Longitudinal Twin Study. FU was supported by the British Friends of Haifa University, the Israel Science Foundation (grant no. 449/14), the British Friends of Hebrew University, and the Joseph Levy Charitable Foundation. TB was supported by the Institut Pasteur and the Bettencourt-Schueller Foundation. We thank the research participants and employees of 23andMe for making this work possible. We also thank the volunteers of the Brisbane Longitudinal Twin Study and the NIHR Cambridge BioResource.

The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 data sets containing 38 802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis) with qualifying unpublished data, were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.Molecular Psychiatry advance online publication, 4 April 2017; doi:10.1038/mp.2017.44.

Item does not contain fulltext In the original version of this article, unfortunately, in the acknowledgement section "National Institutes of Health (NIH, R37 AG033590-08) to J Cacioppo" was omitted. This has been corrected by publishing this erratum. 1 p.

Various non-psychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the nature of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by shared genetic risk factors.Polygenic risk scores (PRS), reflecting an individual’s genetic risk for schizophrenia, were constructed for participants in two birth cohorts (2,588 children from the Netherlands Twin Register (NTR) and 6,127 from the Avon Longitudinal Study of Parents And Children (ALSPAC)). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/conduct disorder (ODD/CD) were estimated at age 7, 10, 12/13 and 15 years in the two cohorts. Results were then meta-analyzed, and age-effects and differences in the associations between disorders and PRS were formally tested in a meta-regression.The schizophrenia PRS was associated with childhood and adolescent psychopathology Where the association was weaker for ODD/CD at age 7. The associations increased with age this increase was steepest for ADHD and ODD/CD. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology.A multivariate meta-analysis of multiple and repeated observations enabled to optimally use the longitudinal data across diagnoses in order to provide knowledge on how childhood disorders develop into severe adult psychiatric disorders.

Variation in obsessive–compulsive symptoms (OCS) has a heritable basis, with genetic association studies starting to yield the first suggestive findings. We contribute to insights into the genetic basis of OCS by performing an extensive series of genetic analyses in a homogeneous, population-based sample from the Netherlands. First, phenotypic and genetic longitudinal correlations over a 6-year period were estimated by modeling OCS data from twins and siblings. Second, polygenic risk scores (PRS) for 6931 subjects with genotype and OCS data were calculated based on meta-analysis results from IOCDF-GC, to investigate their predictive value. Third, the contribution of measured single nucleotide polymorphisms (SNPs) to the heritability was estimated using random-effects modeling. Last, we performed an exploratory genome-wide association study (GWAS) of OCS, testing for SNP- and for gene-based associations. Stability in OCS (test–retest correlation 0.63) was mainly explained by genetic stability. The PRS based on clinical samples predicted OCS in our population-based twin-family sample. SNP-based heritability was estimated at 14%. GWAS revealed one SNP (rs8100480), located within the MEF2BNB gene, associated with OCS (P=2.56 × 10−8). Additional gene-based testing resulted in four significantly associated genes, which are located in the same chromosomal region on chromosome 19p13.11: MEF2BNB, RFXANK, MEF2BNB-MEF2B and MEF2B. Thus, common genetic variants explained a significant proportion of OCS trait variation. Genes significantly associated with OCS are expressed in the brain and involved in development and control of immune system functions (RFXANK) and regulation of gene expression of muscle-specific genes (MEF2BNB). MEF2BNB also showed a suggestive association with OCD in an independent case–control study, suggesting a role for this gene in the development of OCS.

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Correction to: Molecular Psychiatry (2015); advance online publication 12 January 2016; doi:10.1038/mp.2015.197 Following publication of the above article, the authors noticed that the fifteenth author’s name was presented incorrectly. The author’s name should have appeared as S Van der Auwera. The publisher regrets the error.

Correction to: Molecular Psychiatry advance online publication, 26 May 2015; doi:10.1038/mp.2015.57 Following publication of the above article, the authors noticed that the Supplementary Figure legends were not published with the paper. The legends accompany this erratum. In addition, the Supplementary Tables were originally presented as PDF files.