Schizophrenia is a highly polygenic brain disorder. The main hypothesis for disease etiology in schizophrenia primarily focuses on the role of dysfunctional synaptic transmission. Previous studies ...have therefore directed their investigations toward the role of neuronal dysfunction. However, recent studies have shown that apart from neurons, glial cells also play a major role in synaptic transmission. Therefore, we investigated the potential causal involvement of the 3 principle glial cell lineages in risk to schizophrenia. We performed a functional gene set analysis to test for the combined effects of genetic variants in glial type-specific genes for association with schizophrenia. We used genome-wide association data from the largest schizophrenia sample to date, including 13 689 cases and 18 226 healthy controls. Our results show that astrocyte and oligodendrocyte gene sets, but not microglia gene sets, are associated with an increased risk for schizophrenia. The astrocyte and oligodendrocyte findings are related to astrocyte signaling at the synapse, myelin membrane integrity, glial development, and epigenetic control. Together, these results show that genetic alterations underlying specific glial cell type functions increase susceptibility to schizophrenia and provide evidence that the neuronal hypothesis of schizophrenia should be extended to include the role of glia.
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.
Abstract
To prevent the electromagnetic (EM) wakefields excitation, protect detectors from damage at a range of installations and facilities including particle accelerators the EM field control is ...required. Conductive foils or wires providing EM protection and required thermal and mechanical properties are normally used. We suggest novel composite materials with uniquely designed frequency selective conductivity enabling them to overcome the properties of the conventional materials, protect from EM fields and supress undesirable phenomena. Theoretical and experimental investigations are carried out and the conductivity of designed and composite (dual-layer) aluminium/graphene metamaterials as well as graphene and aluminium foils is studied. The EM properties of these materials are compared, and conditions of full and partial electromagnetic transparency are discussed. Results observed allow engineering materials capable of EM field control, instability suppression including those observed in high-intensity particle accelerators and enabling control of an EM field generating media including relativistic charge particle beams.
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.
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.
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.
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.
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.
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.
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.
Although common sense suggests that environmental influences increasingly account for individual differences in behavior as experiences accumulate during the course of life, this hypothesis has not ...previously been tested, in part because of the large sample sizes needed for an adequately powered analysis. Here we show for general cognitive ability that, to the contrary, genetic influence increases with age. The heritability of general cognitive ability increases significantly and linearly from 41% in childhood (9 years) to 55% in adolescence (12 years) and to 66% in young adulthood (17 years) in a sample of 11 000 pairs of twins from four countries, a larger sample than all previous studies combined. In addition to its far-reaching implications for neuroscience and molecular genetics, this finding suggests new ways of thinking about the interface between nature and nurture during the school years. Why, despite life's 'slings and arrows of outrageous fortune', do genetically driven differences increasingly account for differences in general cognitive ability? We suggest that the answer lies with genotype-environment correlation: as children grow up, they increasingly select, modify and even create their own experiences in part based on their genetic propensities.
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.
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