Genome-wide association studies (GWAS) have identified thousands of novel genetic associations for complex genetic disorders, leading to the identification of potential pharmacological targets for novel drug development. In schizophrenia, 108 conservatively defined loci that meet genome-wide significance have been identified and hundreds of additional sub-threshold associations harbour information on the genetic aetiology of the disorder. In the present study, we used gene-set analysis based on the known binding targets of chemical compounds to identify the ‘drug pathways’ most strongly associated with schizophrenia-associated genes, with the aim of identifying potential drug repositioning opportunities and clues for novel treatment paradigms, especially in multi-target drug development. We compiled 9389 gene sets (2496 with unique gene content) and interrogated gene-based p-values from the PGC2-SCZ analysis. Although no single drug exceeded experiment wide significance (corrected p<0.05), highly ranked gene-sets reaching suggestive significance including the dopamine receptor antagonists metoclopramide and trifluoperazine and the tyrosine kinase inhibitor neratinib. This is a proof of principle analysis showing the potential utility of GWAS data of schizophrenia for the direct identification of candidate drugs and molecules that show polypharmacy.

Many antipsychotics promote weight gain, which can lead to non-compliance and relapse of psychosis. By developing models that accurately identify individuals at greater risk of weight gain, clinicians can make informed treatment decisions and target intervention measures. We examined clinical, genetic and expression data for 284 individuals with psychosis derived from a previously published randomised controlled trial (IMPACT). These data were used to develop regression and classification models predicting change in Body Mass Index (BMI) over one year. Clinical predictors included demographics, anthropometrics, cardiac and blood measures, diet and exercise, physical and mental health, medication and BMI outcome measures. We included genetic polygenic risk scores (PRS) for schizophrenia, bipolar disorder, BMI, waist-hip-ratio, insulin resistance and height, as well as gene co-expression modules generated by Weighted Gene Co-expression Network Analysis (WGCNA). The best performing predictive models for BMI and BMI gain after one year used clinical data only, which suggests expression and genetic data do not improve prediction in this cohort.

The active form of vitamin B6, pyridoxal phosphate (PLP), is essential for human metabolism. The brain is dependent on vitamin B6 for its neurotransmitter balance. To obtain insight into the genetic determinants of vitamin B6 homeostasis, we conducted a genome-wide association study (GWAS) of the B6 vitamers pyridoxal (PL), PLP and the degradation product of vitamin B6, pyridoxic acid (PA). We collected a unique sample set of cerebrospinal fluid (CSF) and plasma from the same healthy human subjects of Dutch ancestry (n = 493) and included concentrations and ratios in and between these body fluids in our analysis. Based on a multivariate joint analysis of all B6 vitamers and their ratios, we identified a genome-wide significant association at a locus on chromosome 1 containing the ALPL (alkaline phosphatase) gene (minimal p = 7.89 × 10⁻¹⁰, rs1106357, minor allele frequency (MAF) = 0.46), previously associated with vitamin B6 levels in blood. Subjects homozygous for the minor allele showed a 1.4-times-higher ratio between PLP and PL in plasma, and even a 1.6-times-higher ratio between PLP and PL in CSF than subjects homozygous for the major allele. In addition, we observed a suggestive association with the CSF:plasma ratio of PLP on chromosome 15 (minimal p = 7.93 × 10⁻⁷, and MAF = 0.06 for rs28789220). Even though this finding is not reaching genome-wide significance, it highlights the potential of our experimental setup for studying transport and metabolism across the blood–CSF barrier. This GWAS of B6 vitamers identifies alkaline phosphatase as a key regulator in human vitamin B6 metabolism in CSF as well as plasma. Furthermore, our results demonstrate the potential of genetic studies of metabolites in plasma and CSF to elucidate biological aspects underlying metabolite generation, transport and degradation.

Objectives Clozapine is an atypical antipsychotic primarily prescribed for treatment-resistant schizophrenia. We tested the specific effect of clozapine versus other drug treatments on whole-blood gene expression in a sample of patients with psychosis from the UK. Methods A total of 186 baseline whole-blood samples from individuals receiving treatment for established psychosis were analysed for gene expression on Illumina HumanHT-12.v4 BeadChips. After standard quality-control procedures, 152 samples remained, including 55 from individuals receiving clozapine. In a within-case study design, weighted gene correlation network analysis was used to identify modules of coexpressed genes. The influence of mood stabilizers, lithium carbonate/lithium citrate and sodium valproate was studied to identify their possible roles as confounders. Results Individuals receiving clozapine as their only antipsychotic (clozapine monotherapy) had a nominal association with one gene-expression module, whereas no significant change in gene expression was found for other drugs. Conclusion Overall, this study does not provide evidence that clozapine treatment induces medium to large different gene-expression patterns in human whole blood versus other antipsychotic treatments. This does not rule out the possibility of smaller effects as observed for other common antipsychotic treatments.

Both common and rare genetic variation play a role in the causes for mood disorders. Very large families pose unique opportunities and analytical challenges but may provide a way to identify regions and mutations associated with mood disorders. We identified a family with a high prevalence (~30%) of mood disorders in a rural village in Brazil, featuring decreasing age of onset over generations. The pattern of inheritance was complex with 32 Bipolar type I cases, 11 Bipolar type II and 59 recurrent and/or severe Depression cases in addition to other phenotypes. We enrolled 333 participants with DNA samples from a broader pedigree of 960 subjects for genotyping using the Affymetrix 10K array. Non-parametric linkage was carried out via MERLIN and parametric with both MERLIN and MCLINKAGE. We exome sequenced a subset of the family (n=27) in order to identify rare variation within the linkage regions shared by affected family members. We identified four genome wide significant and four suggestive linkage regions on chromosomes 1, 2, 3, 11 and 12 for different phenotype definitions. However, no region received strong joint support in both the parametric and non-parametric analyses. Exome sequencing revealed potential deleterious variants in 11p15.4 for MDD and 1q21.1-1q21.3 and 12p23.1-p22.3, implicated in cell signaling, adhesion, translation and neurogenesis processes. Overall, our results suggest promising, but not definitive or confirmed evidence, that rare genetic variation contributes to the high prevalence of mood disorders in this multi-generational family. We note that a substantial role for common genetic variation is likely given the strength of the linkage signals observed. The World Health Organisation reports depression and bipolar disorder as the second and seventh most important causes of years lost due to disability worldwide[1]. The heritability of bipolar disorder is between 60-90% with a lower but still substantial heritability for major depression (40-45%) [2]; [3]. First-degree relatives of bipolar disorder probands have a 5-10 fold increase in risk of developing the illness compared to relatives of controls but also show a three fold increase in unipolar depression, indicating that bipolar disorder does not “breed true” [4]. Large collaborative genome-wide association studies (GWAS) have uncovered several common genetic variants of small effect [5]. Genomewide estimates of heritability suggest that up to 60% of the genetic risk is contributed by common variants [6]. Overall, the current picture for bipolar disorder (and almost all complex traits) is a genetic architecture formed of both common and rare variants. Linkage studies have been pursued on the basis that there may be variants of greater effect shared between and within affected families. However these studies have usually focused on collections of comparatively small families or sib pairs and few consistent findings have emerged [7]. Large multigenerational families (e. g. of >30 affected individuals) theoretically offer a powerful means for mapping complex disease loci that are individually rare but common in a single family. These loci may be more highly penetrant and of larger effect than loci found with GWAS [8]. Here we report the results of the Brazilian Bipolar Family (BBF) study on a five-generation family of 639 members of which 333 were enrolled in the current analyses. Our objectives were to perform a linkage analysis with genome coverage and try to identify new genes/mutations related to bipolar and other mood disorders in the family. Here we report our findings and preliminary results of sequencing of linkage regions.