The presence of subclinical levels of psychosis in the general population may imply that schizophrenia is the extreme expression of more or less continuously distributed traits in the population. In a previous study, we identified five quantitative measures of schizophrenia (positive, negative, disorganisation, mania, and depression scores). The aim of this study is to examine the association between a direct measure of genetic risk of schizophrenia and the five quantitative measures of psychosis. Estimates of the log of the odds ratios of case/control allelic association tests were obtained from the Psychiatric GWAS Consortium (PGC) (minus our sample) which included genome-wide genotype data of 8,690 schizophrenia cases and 11,831 controls. These data were used to calculate genetic risk scores in 314 schizophrenia cases and 148 controls from the Netherlands for whom genotype data and quantitative symptom scores were available. The genetic risk score of schizophrenia was significantly associated with case-control status (p<0.0001). In the case-control sample, the five psychosis dimensions were found to be significantly associated with genetic risk scores; the correlations ranged between.15 and.27 (all p<.001). However, these correlations were not significant in schizophrenia cases or controls separately. While this study confirms the presence of a genetic risk for schizophrenia as categorical diagnostic trait, we did not find evidence for the genetic risk underlying quantitative schizophrenia symptom dimensions. This does not necessarily imply that a genetic basis is nonexistent, but does suggest that it is distinct from the polygenic risk score for schizophrenia.

Recent studies have provided new data on the teratogenicity of lithium. Less is known about the risk of miscarriage after lithium use during pregnancy. The aim of this study was to investigate the association between lithium use during pregnancy and miscarriage. Participants were women with bipolar I disorder and one or more pregnancies, of which information on medication use and pregnancy outcome was available (n = 443). The unadjusted odds ratios for miscarriage after lithium use during pregnancy was calculated. Multilevel logistic regression was used to calculate the odds ratio, adjusted for the age at conception and the clustering of pregnancies per woman. Miscarriages occurred in 20.8% of the lithium-exposed pregnancies (16/77), compared with 10.9% of the unexposed pregnancies (40/366) (OR = 2.14; 95% CI: 1.13-4.06). The adjusted odds ratio of miscarriage after lithium use during pregnancy was 2.94 (95% CI: 1.39-6.22). Lithium use during pregnancy may increase the risk of miscarriage.

Bipolar disorder (BD) patients show aberrant white matter microstructure compared to healthy controls but little is known about the relation with clinical characteristics. We therefore investigated the relation of white matter microstructure with the main pharmacological treatments as well its relation with IQ. Patients with BD (N = 257) and controls (N = 167) underwent diffusion tensor imaging (DTI) and comprehensive clinically assessments including IQ estimates. DTI images were analyzed using tract-based spatial statistics. Fractional anisotropy (FA) and Mean Diffusivity (MD) were determined. Patients had significantly lower FA and higher MD values throughout the white matter skeleton compared to controls. Within the BD patients, lithium use was associated with higher FA and lower MD. Antipsychotic medication use in the BD patients was not associated with FA but, in contrast to lithium, was associated with higher MD. IQ was significantly positively correlated with FA and negatively with MD in patients as well as in controls. In this large DTI study we found evidence for marked differences in FA and MD particularly in (but not restricted to) corpus callosum, between BD patients and controls. This effect was most pronounced in lithium-free patients, implicating that lithium affects white matter microstructure and attenuates differences associated with bipolar disorder. Effects of antipsychotic medication intake were absent in FA and only subtle in MD relative to those of lithium. The abnormal white matter microstructure was associated with IQ but not specifically for either group.

Cerebral dominance of language function and hand preference are suggested to be heritable traits with possible shared genetic background. However, joined genetic studies of these traits have never been conducted. We performed a genetic linkage study in 37 multigenerational human pedigrees of both sexes (consisting of 355 subjects) enriched with left-handedness in which we also measured language lateralization. Hand preference was measured with the Edinburgh Handedness Inventory, and language lateralization was measured with functional transcranial Doppler during language production. The estimated heritability of left-handedness and language lateralization in these pedigrees is 0.24 and 0.31, respectively. A parametric major gene model was tested for left-handedness. Nonparametric analyses were performed for left-handedness, atypical lateralization, and degree of language lateralization. We did not observe genome-wide evidence for linkage in the parametric or nonparametric analyses for any of the phenotypes tested. However, multiple regions showed suggestive evidence of linkage. The parametric model showed suggestive linkage for left-handedness in the 22q13 region [heterogeneity logarithm of odds (HLOD) = 2.18]. Nonparametric multipoint analysis of left-handedness showed suggestive linkage in the same region [logarithm of odds (LOD) = 2.80]. Atypical language lateralization showed suggestive linkage in the 7q34 region (LODMax = 2.35). For strength of language lateralization, we observed suggestive linkage in the 6p22 (LODMax = 2.54), 7q32 (LODMax = 1.93), and 9q33 (LODMax = 2.10) regions. We did not observe any overlap of suggestive genetic signal between handedness and the extent of language lateralization. The absence of significant linkage argues against the presence of a major gene coding for both traits; rather, our results are suggestive of these traits being two independent polygenic complex traits.

Abstract Background Several recent studies reported aging effects on DNA methylation levels of individual CpG dinucleotides. But it is not yet known whether aging-related consensus modules, in the form of clusters of correlated CpG markers, can be found that are present in multiple human tissues. Such a module could facilitate the understanding of aging effects on multiple tissues. Results We therefore employed weighted correlation network analysis of 2,442 Illumina DNA methylation arrays from brain and blood tissues, which enabled the identification of an age-related co-methylation module. Module preservation analysis confirmed that this module can also be found in diverse independent data sets. Biological evaluation showed that module membership is associated with Polycomb group target occupancy counts, CpG island status and autosomal chromosome location. Functional enrichment analysis revealed that the aging-related consensus module comprises genes that are involved in nervous system development, neuron differentiation and neurogenesis, and that it contains promoter CpGs of genes known to be down-regulated in early Alzheimer's disease. A comparison with a standard, non-module based meta-analysis revealed that selecting CpGs based on module membership leads to significantly increased gene ontology enrichment, thus demonstrating that studying aging effects via consensus network analysis enhances the biological insights gained. Conclusions Overall, our analysis revealed a robustly defined age-related co-methylation module that is present in multiple human tissues, including blood and brain. We conclude that blood is a promising surrogate for brain tissue when studying the effects of age on DNA methylation profiles.

Emerging evidence suggests that schizophrenia (SZ) susceptibility involves variation at genetic, epigenetic and transcriptome levels. We describe an integrated approach that leverages DNA methylation and gene expression data to prioritize genetic variation involved in disease. DNA methylation levels were obtained from whole blood of 260 SZ patients and 250 unaffected controls of which a subset with gene expression data was available. By assessing DNA methylation and gene expression in cases and controls, we identified 432 CpG sites with differential methylation levels that are associated with differential gene expression. We hypothesized that genetic factors involved in these methylation levels may be associated with the genetic risk of SZ susceptibility. To test this hypothesis, we used results from the Psychiatric Genomics Consortium SZ genome-wide association study (GWAS). We observe an enrichment of SZ-associated SNPs in the mQTLs of which the associated CpG site is also correlated with differential gene expression in SZ. While this enrichment was already apparent when using nominal significant thresholds, enrichment was even more pronounced when applying more stringent significance levels. One locus, previously identified as susceptibility locus in a SZ GWAS, involves SNP rs11191514:C>T, which regulates DNA methylation of calcium homeostasis modulator 1 that is also associated with differential gene expression in patients. Overall, our results suggest that epigenetic variation plays an important role in SZ susceptibility and that the integration of analyses of genetic, epigenetic and gene expression profiles may be a biologically meaningful approach for identifying disease susceptibility loci, even when using whole blood data in studies of brain-related disorders.

We investigate how the sleep disruptions and irregular physical activity levels that are prominent features of bipolar disorder (BD) relate to white matter microstructure in patients and controls. Diffusion tension imaging (DTI) and 14-day actigraphy recordings were obtained in 51 BD I patients and 55 age-and-gender-matched healthy controls. Tract-based spatial statistics (TBSS) was used for voxelwise analysis of the association between fractional anisotropy (FA) and sleep and activity characteristics in the overall sample. Next, we investigated whether the relation between sleep and activity and DTI measures differed for patients and controls. Physical activity was related to increased integrity of white matter microstructure regardless of bipolar diagnosis. The relationship between sleep and white matter microstructure was more equivocal; we found an expected association between higher FA and effective sleep in controls but opposite patterns in bipolar patients. Confounding factors such as antipsychotic medication use are a likely explanation for these contrasting findings and highlight the need for further study of medication-related effects on white matter integrity.

The notion that healthy brain function emerges from coordinated neural activity constrained by the brain's network of anatomical connections--i.e., the connectome--suggests that alterations in the connectome's wiring pattern may underlie brain disorders. Corroborating this hypothesis, studies in schizophrenia are indicative of altered connectome architecture including reduced communication efficiency, disruptions of central brain hubs, and affected "rich club" organization. Whether similar deficits are present in bipolar disorder is currently unknown. This study examines structural connectome topology in 216 bipolar I disorder patients as compared to 144 healthy controls, focusing in particular on central regions (i.e., brain hubs) and connections (i.e., rich club connections, interhemispheric connections) of the brain's network. We find that bipolar I disorder patients exhibit reduced global efficiency (-4.4%, P =0.002) and that this deficit relates (r = 0.56, P < 0.001) to reduced connectivity strength of interhemispheric connections (-13.0%, P = 0.001). Bipolar disorder patients were found not to show predominant alterations in the strength of brain hub connections in general, or of connections spanning brain hubs (i.e., "rich club" connections) in particular (all P > 0.1). These findings highlight a role for aberrant brain network architecture in bipolar I disorder with reduced global efficiency in association with disruptions in interhemispheric connectivity, while the central "rich club" system appears not to be particularly affected.

Mapping genetic variants that regulate gene expression (eQTL mapping) in large-scale RNA sequencing (RNA-seq) studies is often employed to understand functional consequences of regulatory variants. However, the high cost of RNA-seq limits sample size, sequencing depth, and, therefore, discovery power in eQTL studies. In this work, we demonstrate that, given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample and increasing the number of individuals sequenced in the assay. We perform RNA-seq of whole-blood tissue across 1,490 individuals at low coverage (5.9 million reads/sample) and show that the effective power is higher than that of an RNA-seq study of 570 individuals at moderate coverage (13.9 million reads/sample). Next, we leverage synthetic datasets derived from real RNA-seq data (50 million reads/sample) to explore the interplay of coverage and number individuals in eQTL studies, and show that a 10-fold reduction in coverage leads to only a 2.5-fold reduction in statistical power to identify eQTLs. Our work suggests that lowering coverage while increasing the number of individuals in RNA-seq is an effective approach to increase discovery power in eQTL studies.

Objectives

Bipolar disorder type-I (BD-I) patients show a lower Intelligence Quotient (IQ) and smaller brain volumes as compared with healthy controls. Considering that in healthy individuals lower IQ is related to smaller total brain volume, it is of interest to investigate whether IQ deficits in BD-I patients are related to smaller brain volumes and to what extent smaller brain volumes can explain differences between premorbid IQ estimates and IQ after a diagnosis of BD-I.

Methods

Magnetic resonance imaging brain scans, IQ and premorbid IQ scores were obtained from 195 BDI patients and 160 controls. We studied the relationship of (global, cortical and subcortical) brain volumes with IQ and IQ change. Additionally, we investigated the relationship between childhood trauma, lithium- and antipsychotic use and IQ.

Results

Total brain volume and IQ were positively correlated in the entire sample. This correlation did not differ between patients and controls. Although brain volumes mediated the relationship between BD-I and IQ in part, the direct relationship between the diagnosis and IQ remained significant. Childhood trauma and use of lithium and antipsychotic medication did not affect the relationship between brain volumes and IQ. However, current lithium use was related to lower IQ in patients.

Conclusions

Our data suggest a similar relationship between brain volume and IQ in BD-I patients and controls. Smaller brain volumes only partially explain IQ deficits in patients. Therefore, our findings indicate that in addition to brain volumes and lithium use other disease factors play a role in IQ deficits in BD-I patients.