Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study.

Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.

Genetic influences on eight psychiatric disorders based on family data of 4 408 646 full and half-siblings, and genetic data of 333 748 cases and controls.

BACKGROUND: Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders. METHODS: We assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia. RESULTS: Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50. CONCLUSIONS: Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.

Author Correction: Susceptible genes and disease mechanisms identified in frontotemporal dementia and frontotemporal dementia with Amyotrophic Lateral Sclerosis by DNA-methylation and GWAS.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Susceptible genes and disease mechanisms identified in frontotemporal dementia and frontotemporal dementia with Amyotrophic Lateral Sclerosis by DNA-methylation and GWAS.

Frontotemporal dementia (FTD) is a neurodegenerative disorder predominantly affecting the frontal and temporal lobes. Genome-wide association studies (GWAS) on FTD identified only a few risk loci. One of the possible explanations is that FTD is clinically, pathologically, and genetically heterogeneous. An important open question is to what extent epigenetic factors contribute to FTD and whether these factors vary between FTD clinical subgroup. We compared the DNA-methylation levels of FTD cases (n = 128), and of FTD cases with Amyotrophic Lateral Sclerosis (FTD-ALS; n = 7) to those of unaffected controls (n = 193), which resulted in 14 and 224 candidate genes, respectively. Cluster analysis revealed significant class separation of FTD-ALS from controls. We could further specify genes with increased susceptibility for abnormal gene-transcript behavior by jointly analyzing DNA-methylation levels with the presence of mutations in a GWAS FTD-cohort. For FTD-ALS, this resulted in 9 potential candidate genes, whereas for FTD we detected 1 candidate gene (ELP2). Independent validation-sets confirmed the genes DLG1, METTL7A, KIAA1147, IGHMBP2, PCNX, UBTD2, WDR35, and ELP2/SLC39A6 among others. We could furthermore demonstrate that genes harboring mutations and/or displaying differential DNA-methylation, are involved in common pathways, and may therefore be critical for neurodegeneration in both FTD and FTD-ALS.

Modeling psychiatric disorders: from genomic findings to cellular phenotypes.

Major programs in psychiatric genetics have identified >150 risk loci for psychiatric disorders. These loci converge on a small number of functional pathways, which span conventional diagnostic criteria, suggesting a partly common biology underlying schizophrenia, autism and other psychiatric disorders. Nevertheless, the cellular phenotypes that capture the fundamental features of psychiatric disorders have not yet been determined. Recent advances in genetics and stem cell biology offer new prospects for cell-based modeling of psychiatric disorders. The advent of cell reprogramming and induced pluripotent stem cells (iPSC) provides an opportunity to translate genetic findings into patient-specific in vitro models. iPSC technology is less than a decade old but holds great promise for bridging the gaps between patients, genetics and biology. Despite many obvious advantages, iPSC studies still present multiple challenges. In this expert review, we critically review the challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes.

Gene expression in major depressive disorder.

The search for genetic variants underlying major depressive disorder (MDD) has not yet provided firm leads to its underlying molecular biology. A complementary approach is to study gene expression in relation to MDD. We measured gene expression in peripheral blood from 1848 subjects from The Netherlands Study of Depression and Anxiety. Subjects were divided into current MDD (N=882), remitted MDD (N=635) and control (N=331) groups. MDD status and gene expression were measured again 2 years later in 414 subjects. The strongest gene expression differences were between the current MDD and control groups (129 genes at false-discovery rate, FDR<0.1). Gene expression differences across MDD status were largely unrelated to antidepressant use, inflammatory status and blood cell counts. Genes associated with MDD were enriched for interleukin-6 (IL-6)-signaling and natural killer (NK) cell pathways. We identified 13 gene expression clusters with specific clusters enriched for genes involved in NK cell activation (downregulated in current MDD, FDR=5.8 × 10(-5)) and IL-6 pathways (upregulated in current MDD, FDR=3.2 × 10(-3)). Longitudinal analyses largely confirmed results observed in the cross-sectional data. Comparisons of gene expression results to the Psychiatric Genomics Consortium (PGC) MDD genome-wide association study results revealed overlap with DVL3. In conclusion, multiple gene expression associations with MDD were identified and suggest a measurable impact of current MDD state on gene expression. Identified genes and gene clusters are enriched with immune pathways previously associated with the etiology of MDD, in line with the immune suppression and immune activation hypothesis of MDD.

Functional characterization of the PCLO p.Ser4814Ala variant associated with major depressive disorder reveals cellular but not behavioral differences.

Genome-wide association studies have suggested a role for a genetic variation in the presynaptic gene PCLO in major depressive disorder (MDD). As with many complex traits, the PCLO variant has a small contribution to the overall heritability and the association does not always replicate. One variant (rs2522833, p.Ser4814Ala) is of particular interest given that it is a common, nonsynonymous exon variant near a calcium-sensing part of PCLO. It has been suggested that the molecular effects of such variations penetrate to a variable extent in the population due to phenotypic and genotypic heterogeneity at the population level. More robust effects may be exposed by studying such variations in isolation, in a more homogeneous context. We tested this idea by modeling PCLO variation in a mouse knock-in model expressing the Pclo(SA)(/)(SA) variant. In the highly homogeneous background of inbred mice, two functional effects of the SA-variation were observed at the cellular level: increased synaptic Piccolo levels, and 30% increased excitatory synaptic transmission in cultured neurons. Other aspects of Piccolo function were unaltered: calcium-dependent phospholipid binding, synapse formation in vitro, and synaptic accumulation of synaptic vesicles. Moreover, anxiety, cognition and depressive-like behavior were normal in Pclo(SA)(/)(SA) mice. We conclude that the PCLO p.Ser4814Ala missense variant produces mild cellular phenotypes, which do not translate into behavioral phenotypes. We propose a model explaining how (subtle) cellular phenotypes do not penetrate to the mouse behavioral level but, due to genetic and phenotypic heterogeneity and non-linearity, can produce association signals in human population studies.

The co-occurrence of autistic and ADHD dimensions in adults: an etiological study in 17,770 twins.

Autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) often occur together. To obtain more insight in potential causes for the co-occurrence, this study examined the genetic and environmental etiology of the association between specific ASD and ADHD disorder dimensions. Self-reported data on ASD dimensions social and communication difficulties (ASDsc), and repetitive and restricted behavior and interests (ASDr), and ADHD dimensions inattention (IA), and hyperactivity/impulsivity (HI) were assessed in a community sample of 17,770 adult Swedish twins. Phenotypic, genetic and environmental associations between disorder dimensions were examined in a multivariate model, accounting for sex differences. ASDr showed the strongest associations with IA and HI in both sexes (r(p) 0.33 to 0.40). ASDsc also correlated moderately with IA (females r(p) 0.29 and males r(p) 0.35) but only modestly with HI (females r(p) 0.17 and males r(p) 0.20). Genetic correlations ranged from 0.22 to 0.64 and were strongest between ASDr and IA and HI. Sex differences were virtually absent. The ASDr dimension (reflecting restricted, repetitive and stereotyped patterns of behavior, interests and activities) showed the strongest association with dimensions of ADHD, on a phenotypic, genetic and environmental level. This study opens new avenues for molecular genetic research. As our findings demonstrated that genetic overlap between disorders is dimension-specific, future gene-finding studies on psychiatric comorbidity should focus on carefully selected genetically related dimensions of disorders.

Cortical thickness and inattention/hyperactivity symptoms in young children: a population-based study.

BACKGROUND: While many neuroimaging studies have investigated the neurobiological basis of attention deficit hyperactivity disorder (ADHD), few have studied the neurobiology of attention problems in the general population. The ability to pay attention falls along a continuum within the population, with children with ADHD at one extreme of the spectrum and, therefore, a dimensional perspective of evaluating attention problems has an added value to the existing literature. Our goal was to investigate the relationship between cortical thickness and inattention and hyperactivity symptoms in a large population of young children. METHOD: This study is embedded within the Generation R Study and includes 6- to 8-year-old children (n = 444) with parent-reported attention and hyperactivity measures and high-resolution structural imaging data. We investigated the relationship between cortical thickness across the entire brain and the Child Behavior Checklist Attention Deficit Hyperactivity Problems score. RESULTS: We found that greater attention problems and hyperactivity were associated with a thinner right and left postcentral gyrus. When correcting for potential confounding factors and multiple testing, these associations remained significant. CONCLUSIONS: In a large, population-based sample we showed that young (6- to 8-year-old) children who show more attention problems and hyperactivity have a thinner cortex in the region of the right and left postcentral gyrus. The postcentral gyrus, being the primary somatosensory cortex, reaches its peak growth early in development. Therefore, the thinner cortex in this region may reflect either a deviation in cortical maturation or a failure to reach the same peak cortical thickness compared with children without attention or hyperactivity problems.

Childhood intelligence is heritable, highly polygenic and associated with FNBP1L.

Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17,989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.

Attentional switching forms a genetic link between attention problems and autistic traits in adults.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) symptoms and autistic traits often occur together. The pattern and etiology of co-occurrence are largely unknown, particularly in adults. This study investigated the co-occurrence between both traits in detail, and subsequently examined the etiology of the co-occurrence, using two independent adult population samples. Method Data on ADHD traits (Inattention and Hyperactivity/Impulsivity) were collected in a population sample (S1, n = 559) of unrelated individuals. Data on Attention Problems (AP) were collected in a population-based family sample of twins and siblings (S2, n = 560). In both samples five dimensions of autistic traits were assessed (social skills, routine, attentional switching, imagination, patterns). RESULTS: Hyperactive traits (S1) did not correlate substantially with the autistic trait dimensions. For Inattention (S1) and AP (S2), the correlations with the autistic trait dimensions were low, apart from a prominent correlation with the attentional switching scale (0.47 and 0.32 respectively). Analyses in the genetically informative S2 revealed that this association could be explained by a shared genetic factor. CONCLUSIONS: Our findings suggest that the co-occurrence of ADHD traits and autistic traits in adults is not determined by problems with hyperactivity, social skills, imagination or routine preferences. Instead, the association between those traits is due primarily to shared attention-related problems (inattention and attentional switching capacity). As the etiology of this association is purely genetic, biological pathways involving attentional control could be a promising focus of future studies aimed at unraveling the genetic causes of these disorders.

Supporting the generalist genes hypothesis for intellectual ability/disability: the case of SNAP25.

Intellectual disability (ID) is an unresolved health care problem with a worldwide prevalence rate of 2-3%. For many years, research into the genetic causes of ID and related disorders has mainly focused on chromosomal abnormalities or X-linked genetic deficits. Only a handful of autosomal genes are known to cause ID. At the same time it has been suggested that at least some cases of ID represent an extreme form of normal intellectual ability and therefore that genes important for intellectual ability in the normal range may also play a role in ID. In this study, we tested whether the autosomal SNAP25 gene, which was previously associated with variation in intellectual ability in the normal range, is also associated with ID. The gene product of SNAP25 is an important presynaptic plasma membrane protein, is known to be involved in regulating neurotransmitter release, and has been linked to memory and learning by its effect on long term potentiation in the hippocampus. Allele frequencies of two genetic variants in SNAP25 previously associated with intellectual ability were compared between a group of 636 ID cases (IQ < 70) and a control group of 361 persons of higher than average intellectual ability. We observed a higher frequency of the putative risk allele of rs363050 (P = 0.02; OR = 1.24) in cases as compared to controls. These results are consistent with a role of SNAP25 in ID, and also support the notion that ID reflects the lower extreme of the quantitative distribution of intellectual ability.

Functional gene group analysis identifies synaptic gene groups as risk factor for schizophrenia.

Schizophrenia is a highly heritable disorder with a polygenic pattern of inheritance and a population prevalence of ~1%. Previous studies have implicated synaptic dysfunction in schizophrenia. We tested the accumulated association of genetic variants in expert-curated synaptic gene groups with schizophrenia in 4673 cases and 4965 healthy controls, using functional gene group analysis. Identifying groups of genes with similar cellular function rather than genes in isolation may have clinical implications for finding additional drug targets. We found that a group of 1026 synaptic genes was significantly associated with the risk of schizophrenia (P=7.6 × 10(-11)) and more strongly associated than 100 randomly drawn, matched control groups of genetic variants (P<0.01). Subsequent analysis of synaptic subgroups suggested that the strongest association signals are derived from three synaptic gene groups: intracellular signal transduction (P=2.0 × 10(-4)), excitability (P=9.0 × 10(-4)) and cell adhesion and trans-synaptic signaling (P=2.4 × 10(-3)). These results are consistent with a role of synaptic dysfunction in schizophrenia and imply that impaired intracellular signal transduction in synapses, synaptic excitability and cell adhesion and trans-synaptic signaling play a role in the pathology of schizophrenia.

Poor replication of candidate genes for major depressive disorder using genome-wide association data.

Data from the Genetic Association Information Network (GAIN) genome-wide association study (GWAS) in major depressive disorder (MDD) were used to explore previously reported candidate gene and single-nucleotide polymorphism (SNP) associations in MDD. A systematic literature search of candidate genes associated with MDD in case-control studies was performed before the results of the GAIN MDD study became available. Measured and imputed candidate SNPs and genes were tested in the GAIN MDD study encompassing 1738 cases and 1802 controls. Imputation was used to increase the number of SNPs from the GWAS and to improve coverage of SNPs in the candidate genes selected. Tests were carried out for individual SNPs and the entire gene using different statistical approaches, with permutation analysis as the final arbiter. In all, 78 papers reporting on 57 genes were identified, from which 92 SNPs could be mapped. In the GAIN MDD study, two SNPs were associated with MDD: C5orf20 (rs12520799; P=0.038; odds ratio (OR) AT=1.10, 95% CI 0.95-1.29; OR TT=1.21, 95% confidence interval (CI) 1.01-1.47) and NPY (rs16139; P=0.034; OR C allele=0.73, 95% CI 0.55-0.97), constituting a direct replication of previously identified SNPs. At the gene level, TNF (rs76917; OR T=1.35, 95% CI 1.13-1.63; P=0.0034) was identified as the only gene for which the association with MDD remained significant after correction for multiple testing. For SLC6A2 (norepinephrine transporter (NET)) significantly more SNPs (19 out of 100; P=0.039) than expected were associated while accounting for the linkage disequilibrium (LD) structure. Thus, we found support for involvement in MDD for only four genes. However, given the number of candidate SNPs and genes that were tested, even these significant may well be false positives. The poor replication may point to publication bias and false-positive findings in previous candidate gene studies, and may also be related to heterogeneity of the MDD phenotype as well as contextual genetic or environmental factors.