[What can genetic research teach us about the overlap and differences between psychiatric disorders?] / Wat kan genetisch onderzoek ons leren over de overeenkomsten en verschillen tussen psychiatrische aandoeningen?

BACKGROUND: Genetic research has made continuous progress in the past years, as a results of the rapidly growing sample sizes and development of novel analytical tools.
AIM: To present the latest developments in research into the genetic overlap and differences between psychiatric disorders.
METHOD: Description of findings from recent literature.
RESULTS: First of all, psychiatric disorders differ in their heritability, and consequently impact of environmental factors. Second, some disorders show high concordance in direction of genetic effects, while other disorders have rather different effects. Using these genetic (dis)similarities, subgroups of psychiatric disorders can also be defined.
CONCLUSION: Genetic research is developing at rapid pace, and much more will be learned about the genetic overlap and differences between psychiatric disorders in the next years. The big promise -and challenge- will be to integrate genetic research with research of environmental factors, other biological measures and more detailed phenotypic information.
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Comparing the genetic architecture of childhood behavioral problems across socioeconomic strata in the Netherlands and the United Kingdom.

Socioeconomic status (SES) affects the development of childhood behavioral problems. It has been frequently observed that children from low SES background tend to show more behavioral problems. There also is some evidence that SES has a moderating effect on the causes of individual differences in childhood behavioral problems, with lower heritability estimates and a stronger contribution of environmental factors in low SES groups. The aim of the present study was to examine whether the genetic architecture of childhood behavioral problems suggests the presence of protective and/or harmful effects across socioeconomic strata, in two countries with different levels of socioeconomic disparity: the Netherlands and the United Kingdom. We analyzed data from 7-year-old twins from the Netherlands Twin Register (N = 24,112 twins) and the Twins Early Development Study (N = 19,644 twins). The results revealed a nonlinear moderation effect of SES on the contribution of genetic and environmental factors to individual differences in childhood behavioral problems. The heritability was higher, the contribution of the shared environment was lower, and the contribution of the nonshared environment was higher, for children from high SES families, compared to children from low or medium SES families. The pattern was similar for Dutch and UK families. We discuss the importance of these findings for prevention and intervention goals.

A Genetic Investigation of the Well-Being Spectrum.

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.

Correction to: A Genetic Investigation of the Well-Being Spectrum.

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.

A Potential Role for the STXBP5-AS1 Gene in Adult ADHD Symptoms.

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 (r2 = - 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.

Meta-analysis of genome-wide association studies of anxiety disorders.

Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat-response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18 000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case-control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P=1.65 × 10(-8)); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 10(-9)). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.

Stability in symptoms of anxiety and depression as a function of genotype and environment: a longitudinal twin study from ages 3 to 63 years.

BACKGROUND: The influence of genetic factors on major depressive disorder is lower than on other psychiatric disorders. Heritability estimates mainly derive from cross-sectional studies, and knowledge on the longitudinal aetiology of symptoms of anxiety and depression (SxAnxDep) across the lifespan is limited. We aimed to assess phenotypic, genetic and environmental stability in SxAnxDep between ages 3 and 63 years. METHOD: We used a cohort-sequential design combining data from 49 524 twins followed from birth to age ⩾20 years, and from adolescence into adulthood. SxAnxDep were assessed repeatedly with a maximum of eight assessments over a 25-year period. Data were ordered in 30 age groups and analysed with longitudinal genetic models. RESULTS: Over age, there was a significant increase during adolescence in mean scores with sex differences (women>men) emerging. Heritability was high in childhood and decreased to 30-40% during adulthood. This decrease in heritability was due to an increase in environmental variance. Phenotypic stability was moderate in children (correlations across ages ~0.5) and high in adolescents (r = 0.6), young adults (r = 0.7), and adults (r = 0.8). Longitudinal stability was mostly attributable to genetic factors. During childhood and adolescence there was also significant genetic innovation, which was absent in adults. Environmental effects contributed to short-term stability. CONCLUSIONS: The substantial stability in SxAnxDep is mainly due to genetic effects. The importance of environmental effects increases with age and explains the relatively low heritability of depression in adults. The environmental effects are transient, but the contribution to stability increases with age.

Predicting loneliness with polygenic scores of social, psychological and psychiatric traits.

Loneliness is a heritable trait that accompanies multiple disorders. The association between loneliness and mental health indices may partly be due to inherited biological factors. We constructed polygenic scores for 27 traits related to behavior, cognition and mental health and tested their prediction for self-reported loneliness in a population-based sample of 8798 Dutch individuals. Polygenic scores for major depressive disorder (MDD), schizophrenia and bipolar disorder were significantly associated with loneliness. Of the Big Five personality dimensions, polygenic scores for neuroticism and conscientiousness also significantly predicted loneliness, as did the polygenic scores for subjective well-being, tiredness and self-rated health. When including all polygenic scores simultaneously into one model, only 2 major depression polygenic scores remained as significant predictors of loneliness. When controlling only for these 2 MDD polygenic scores, only neuroticism and schizophrenia remain significant. The total variation explained by all polygenic scores collectively was 1.7%. The association between the propensity to feel lonely and the susceptibility to psychiatric disorders thus pointed to a shared genetic etiology. The predictive power of polygenic scores will increase as the power of the genome-wide association studies on which they are based increases and may lead to clinically useful polygenic scores that can inform on the genetic predisposition to loneliness and mental health.

Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia.

Higher educational attainment (EA) is negatively associated with schizophrenia (SZ). However, recent studies found a positive genetic correlation between EA and SZ. We investigate possible causes of this counterintuitive finding using genome-wide association study results for EA and SZ (N = 443,581) and a replication cohort (1169 controls; 1067 cases) with deeply phenotyped SZ patients. We find strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Using EA as a proxy phenotype, we isolate FOXO6 and SLITRK1 as novel candidate genes for SZ. Our results reveal that current SZ diagnoses aggregate over at least two disease subtypes: one part resembles high intelligence and bipolar disorder (BIP), while the other part is a cognitive disorder that is independent of BIP.

Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32 330 subjects from the International Cannabis Consortium.

Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10(-8)) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.

Further confirmation of the association between anxiety and CTNND2: replication in humans.

The rat genome sequencing and mapping consortium found evidence for an association between the catenin-δ2 gene (CTNND2) and anxious behaviour. We replicated these results in humans by carrying out a genetic association test in patients with panic disorder, social phobia, generalized anxiety disorder and/or agoraphobia (N = 1714) and controls (N = 4125). We further explored the association between CTNND2 and other psychiatric disorders based on publicly available genome-wide association results. A gene-based test showed that single nucleotide polymorphisms (SNPs) in CTNND2 have a significantly increased signal (P < 1e(-5) ) and decreased P-values. Single nucleotide polymorphism rs1012176 showed the strongest association with any anxiety disorder (odds ratio: 0.8128, SE = 0.063, P = 0.00099), but this effect was not significant after correction for multiple testing. In available genome-wide association results from the Psychiatric Genomics Consortium we found that SNPs in CTNND2 collectively showed an increased signal for schizophrenia (P < 1e(-5) ) and major depressive disorder (P < 1e(-5) ), but not for bipolar disorder. These signals remained significant after correction for potential confounders. The association between CTNND2 and anxiety was not strong enough to be picked up in the current generation of human genome-wide analyses, indicating the usefulness of and need for animal genetic studies to identify candidate genes for further study in human samples.