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DNA pooling is a practical way to reduce the cost of large-scale association studies to identify susceptibility loci for common diseases. Pooling allows allele frequencies in groups of individuals to be measured using far fewer PCR reactions and genotyping assays than are used when genotyping individuals. Here, we discuss recent developments in quantitative genotyping assays and in the design and analysis of pooling studies. Sophisticated pooling designs are being developed that can take account of hidden population stratification, confounders and inter-loci interactions, and that allow the analysis of haplotypes. [ABSTRACT FROM AUTHOR]

This report describes locomotor-like activity generated by the neonatal mouse spinal cord in vitro. We demonstrate that locomotor-like activity can be produced either spontaneously or by a train of stimuli applied to the dorsal roots or in the presence of bath-applied drugs. Calcium imaging of the motoneuron activity generated by a train of dorsal root stimuli revealed a rostrocaudally propagating component of the optical signal in the anterior lumbar (L1–L3) and in the caudal segments (S1–S4). We hypothesize that this spatio-temporal pattern arises from a rostrocaudal gradient of excitability in the relevant segments. Our experiments suggest that left/right reciprocal inhibition and NMDA-mediated oscillations are not essential mechanisms underlying rhythmogenesis in the neonatal mouse cord. Finally, our data are discussed in the context of other models of locomotion in lower and higher vertebrates. [Copyright &y& Elsevier]

Emphasizes the importance of genetic factors in determining susceptibility to bipolar disorder (BPD) in the United States. Analysis of the hKCa3 gene in BPD disease; Use of extended transmission/disequilibrium test; Contribution of the hKCa3 gene to the susceptibility of BPD.

Darier disease (DD) is an autosomal-dominant skin disorder characterized by loss of adhesion between epidermal cells (acantholysis) and abnormal keratinization. Recently we constructed a 2.4-Mb, P1-derived artificial chromosome contig spanning the DD candidate region on chromosome 12q23-24.1. After screening several genes that mapped to this region, we identified mutations in the ATP2A2 gene, which encodes the sarco/endoplasmic reticulum Ca2+-ATPase type 2 isoform (SERCA2) and is highly expressed in keratinocytes. Thirteen mutations were identified, including frameshift deletions, in-frame deletions or insertions, splice-site mutations and non-conservative missense mutations in functional domains. Our results demonstrate that mutations in ATP2A2 cause DD and disclose a role for this pump in a Ca2+-signalling pathway regulating cell-to-cell adhesion and differentiation of the epidermis. [ABSTRACT FROM AUTHOR]

Heat shock induces in cells the synthesis of specific proteins called heat-shock proteins. We have compared the induction of these proteins in human keratinocytes, skin fibroblasts, and a human epithelial tumor cell line following exposure to weak and strong inducing agents (heat, cadmium sulphate, and sodium arsenite). The induction of heat shock proteins was measured in cells by one-dimensional gel electrophoresis of [35S] methionine-labeled proteins and by immunofluorescence using a specific HSP72 monoclonal antibody. Both HSP90 and HSP116 were constitutively expressed in these cell types. Exposure of these cells to weak inducing agents such as heat or cadmium sulphate resulted in the synthesis of HSP72 and HSP90, whereas HSP28 and HSP116 synthesis was detected in keratinocytes and fibroblasts following exposure to the strong inducing agent sodium arsenite. In addition, sodium arsenite induced the synthesis of HSP46 in human keratinocytes. Immunofluorescence demonstrated a rapid and reversible accumulation of the 72-kD heat shock protein within the nucleolus of heat-stressed human keratinocytes and fibroblasts. [ABSTRACT FROM AUTHOR]

People born in winter and early spring are at an elevated risk for schizophrenia [1 – 4]. Although the effect is small, with an increase in risk of about around 10%, this season of birth effect is one of the most robust findings in schizophrenia epidemiology [5]. It has also been influential in developing hypotheses of schizophrenia pathogenesis, forming one of the central planks of the viral infection hypothesis of the disorder [6] as well as other less intensively investigated putative mechanisms including vitamin D deficiency during fetal development [7]. However, at present, the mechanisms underpinning this season of birth effect are unknown. We implement PRS analysis of the UK Biobank (UKBB) to determine whether season of birth is associated with genetic risk for schizophrenia. We generated schizophrenia PRS for every participant in the UKBB (June 2015 release, N=136,538) and tested whether this score is associated with month or season of birth. As a secondary test of the plausibility of season of birth being a genetically correlated confound, we also conducted a GWAS of season of birth as a binary phenotype, comparing winter/spring births with summer/autumn. Our aim was to estimate heritability of season of birth as a phenotype. We found no association between schizophrenia PRS and season of birth in the UK Biobank sample and no differences in schizophrenia risk scores with respect to month of birth. No SNPs were associated with season of birth at genome-wide significance, there was no evidence for inflation in the test statistics indicative of polygenic inheritance and no evidence that SNP heritability contributed to this trait (total liability scale h2=-0.002 SE=0.0052 as estimated by LD-Score regression). In this study, we examined seasonality in regard to genetic risk to schizophrenia within UK Biobank. We used the largest schizophrenia dataset to date for identification of genetic risk loci and one of the largest available population cohorts to generate schizophrenia PRS and test for seasonal differences in genetic liability to schizophrenia. We found no trends of elevated schizophrenia polygenic risk scores in people born in winter or spring. These results were further supported by a lack of evidence that seasonality is a heritable trait. Since the PRS analysis and heritability estimates were based upon common SNPs, we don't exclude a possible role for rare SNPs, however the frequencies of rare CNVs, linked to neurodevelopmental disorders, also did not differ by season of birth. [ABSTRACT FROM AUTHOR]

Success in the identification of genetic variants associated with neuropsychiatric disorders is one of the major achievements in contemporary biomedical research. Most genetic variants identified in Genome-Wide Association Studies (GWAS) of complex traits are thought to act via effects on gene regulation rather than directly altering the protein product. As a consequence, the actual genes involved in disease are not necessarily the most proximal to the associated variants. By integrating data from GWAS analyses with that from genetic studies of regulatory variation, it is possible to identify variants pleiotropically-associated with both a complex trait and measures of gene regulation. In this study, we use Summary data–based Mendelian Randomization (SMR), a method developed to identify variants pleiotropically associated with both complex traits and gene expression, to identify associations between neuropsychiatric disorders and DNA methylation. Building on our previous efforts, we increased our catalogue of DNA Methylation Quantitative Trait Loci (mQTL) in whole blood using the Illumina EPIC HumanMethylation array that interrogates over 800,000 genomic loci. These data along with mQTL data identified previously in human fetal brain were used to prioritize genes for psychiatric disorders using GWAS data from the Psychiatric Genomics Consortium (PGC). In this study, we apply the SMR approach to test 129,469 DNA methylation sites against five psychiatric phenotypes (schizophrenia, bipolar disorder, major depressive disorder, autism, ADHD) with robust GWAS data available from the PGC using mQTLs identified in whole blood (n=1,175; mQTL P < 1×10-10) to identify novel associations with psychiatric traits. In addition, we tested 9,261 DNA methylation sites using mQTL identified in fetal brain (n=166; mQTL P < 1×10-8). In total, we identified 107 associations with 37 satisfied addition criteria to be defined as pleiotropic and not an artefact of linkage disequilibrium. We identify multiple examples of variable DNA methylation associated with GWAS variants across the five psychiatric disorders, demonstrating the utility of the SMR approach for refining genetic association signals. [ABSTRACT FROM AUTHOR]

Risk-taking is a key component of several psychiatric disorders and could influence lifestyle choices such as smoking, alcohol use and diet. Risk-taking behaviour therefore fits within the Research Domain Criteria (RDoC) approach, whereby elucidation of the genetic determinants of this trait has the potential to improve our understanding of behaviours that span a number of psychiatric disorders. A genome wide association study was conducted in 116 255 UK Biobank participants who responded yes/no to the question "would you consider yourself a risk-taker?". Genetic correlations were calculated between risk-taking and phenotypes relevant to psychiatric disorders. Expression quantitative trait loci analyses in the brain were conducted for significant loci. Risk-takers (compared to controls) were more likely to be men, smokers and have a history of mental illness. Significant loci associated with risk-taking behaviour were identified on chromosomes 3 (rs13084531) and 6 (rs9379971). The effect of rs13084531 was comparable between men and women, whilst rs9379971 showed stronger effects in women than men. Rs13084531 on chromosome 3 demonstrated significant effects on CADM2 mRNA expression levels. CADM2 has previously been implicated in cognition, including executive function. The chromosome 6 locus remains challenging to interpret due to the complexity of the HLA region, although a number of testis-specific genes were observed in this locus. Genetic susceptibility for risk-taking behaviour was significantly correlated with schizophrenia (rg 0.27 p= 4.54⁎10–11), bipolar disorder (rg 0.26 p= 1.73⁎10-4), attention-deficit hyperactivity disorder (rg 0.31 p= 0.0132) and post-traumatic stress disorder (rg 0.51 p= 0.0018), as well as with smoking (rg 0.17 p= 0.0102)and total obesity (rg 0.10 p= 0.0028). Despite being based on only a single question, this study identified genetic determinants of risk-taking behaviour and further demonstrated genetic correlation with psychiatric disorders where this trait is a feature. Although it is not clear which subtypes of risk-taking behaviour are being assessed, these findings further our understanding of the biology of risk-taking behaviour, a trait which has a major impact on a broad spectrum of physical and mental disorders. [ABSTRACT FROM AUTHOR]

Schizophrenia is a highly heritable disorder and is known to have a substantial common polygenetic component [1]. The polygenic risk score approach [1] allows common genetic liability to the disorder to be directly estimated in individuals regardless of their affected status. In addition to weakly predicting schizophrenia affected status in independent case-control datasets, polygenic risk score approaches have revealed significant shared SNP heritability between schizophrenia and multiple psychiatric and behavioural traits [2 , 3]. We therefore postulated that combining risk score profiles derived from several traits might improve the prediction of schizophrenia risk. Polygenic risk score profiles were calculated for the CLOZUK schizophrenia GWAS study [4] (11260 cases, 24542 controls) by training on six recent GWAS datasets: schizophrenia (independent of the CLOZUK set), bipolar disorder, bipolar vs schizophrenia [5] , major depression disorder, educational attainment [6] and neuroticism [7]. Principal component analysis (PCA) was employed to generate factor loadings for the six polygenic risk score profiles. The advantage of PCA is that it converts a set of possibly correlated variables (e.g. due to shared genetic liability) into a set of uncorrelated variables, with the first principal component accounting for the greatest degree of variance in the dataset outcome. We investigated the prediction accuracy of the first principal component compared to the schizophrenia polygenic risk score by means of area under the curve (AUC) analysis. Our analysis indicates that schizophrenia case prediction accuracy of the combined schizophrenia and neuropsychiatric-related first principal component is increased as compared to the AUC of schizophrenia polygenic risk scores alone. The first principal component also visually separates cases and controls in the CLOZUK individuals based upon their combined (schizophrenia and neuropsychiatric-related traits) profiles. We have proposed an approach to combine genetic evidence for schizophrenia and neuropsychiatric-related traits into one score and tested its prediction accuracy. This approach takes advantage of the shared genetic risk between schizophrenia, psychiatric disorders and behavioural traits, and at present, can improve the prediction of schizophrenia risk. [ABSTRACT FROM AUTHOR]

There is strong evidence for partial overlap of genetic influence on Schizophrenia (SCZ), Schizoaffective Disorder (SAD) and Bipolar Affective Disorder (BAD). Part of this is due to common genetic variants, detected by GWAS, with a small individual effect on risk. Recent studies using next generation sequencing reveal growing evidence of the role of rare genetic variants in both diseases. We performed targeted NGS on 187 candidate genes to further investigate the genetic architecture of Bulgarian patients with bipolar disorder and schizophrenia. A total of 300 individuals with BAD, 151 with SCZ, 15 SAD according to DSMIV and ICD-10, as well as 85 healthy population controls and 40 healthy relatives were recruited. The samples were sequenced on the Ion PROTON platform. The sequencing panel comprised of 187 preselected strong candidate genes, based on the results from GWAS and previous NGS studies. Only samples with coverage of at least 95% of the target region at 20x were included in the analyses. Case-control association testing was done using PLINK. The rare variants have been evaluated and divided into groups based on their functional relevance: LOF variants (frameshift and nonsense); with potentially damaging effect on protein function (splice site, missense variants, 3'-UTR/5'-UTR variants); and with no known effect on function (synonymous and intron variants). Genes were prioritized by mutation burden analysis based on the average number of functional occurrences per 1000 bp of the gene CDS. The RVIS scoring system for assessing the intolerance of individual genes to protein-altering variants (Petrovski et al., 2013) was used in conjunction with the burden score for the final ordering. 5373 variants were detected, of which 2826 were found in affecteds (1831 singletons and 995 recurrent). No significant associations between cases and controls could be detected, that survived the correction for multiple testing. In total we found in patients 14 rare LOF variants; 889 non-synonymous variants (243 of which were potentially damaging); 109 splice site variants and 32 in regulatory regions. We could find no significant association of common or rare variants in the analyzed samples, most likely due to small sample size. However, we could identify both recurrent and singleton rare variants with potential functional relevance in genes associated with ion channels, postsynaptic plasticity, neurogenesis and signalling cascade pathways. [ABSTRACT FROM AUTHOR]

The aetiology of Bipolar Disorder (BD) and Schizophrenia (SZ) involves a complex gene-environment interplay and this involves common risk alleles that are shared across the disorders. Bipolar disorder is heterogeneous in presentation and we and others have postulated that the particular clinical presentation is in part determined by the particular risk alleles carried. To investigate this, we have employed sparse Canonical Correlation Analysis (sCCA), to seek patterns of correlation between psychotic symptoms and schizophrenia risk alleles in a large (N=3903) deeply phenotyped sample of subjects with BD. Canonical Correlation Analysis (CCA) seeks linear relationships between two sets of multi-dimensional variables. In the psychiatric genetics field, this approach can be adapted to enable the analysis of both phenotype and genetic variables in one framework. This has the advantage of minimizing the number of statistical tests required. A recent extension of CCA to sparse canonical correlation analysis (sCCA) allows application of the general approach to high dimensional genomic data (Witten et al., 2009). sCCA has advantages compared to CCA in terms of precision of parameter estimates and statistical power. We employed sCCA to analyse 30 psychotic symptoms assessed with the OPerational CRITeria checklist (OPCRIT) and 82 independent genome-wide significant SNPs that were identified by the SZ PGC2 study (The Psychiatric Genomics Consortium, 2014) for which we had data in our BD sample. We applied the sCCA as a purely data driven approach to individual OPCRIT psychotic symptoms and also to groups of OPCRIT psychotic symptoms ("positive", "negative", "disorganised") defined by a previously published factor analysis study of schizophrenia. sCCA analysis of the individual OPCRIT items with the set of significantly associated with SZ 82 sCCA analysis based on individual psychotic symptoms revealed a significant association (p=0.045) with the largest weights attributed to delusions of influence, bizarre behaviour and grandiose delusions and an indel SNP on chromosome 3 (3:180594593, build 37). sCCA analysis on the same set of SNPs and OPCRIT symptom groups confirmed association with the same SNP and the "disorganised" group of OPCRIT symptoms (p=0.01). The results also show significant association when we use less stringent p-value thresholds in SZ. In this case the most heavily weighted SNP remains 3:180594593, but other SNPs also contribute to the analysis. Our results suggest the CCA canonical correlation approach might be a useful tool to explore phenotype-genotype relationships. It can be applied to generate data-driven hypotheses with the potential to provide further insights into the complex architecture of psychiatric disorders. To the best of our knowledge, this is the first study to apply this approach in analysing phenotypes and genotypes together. sCCA offers the potential to be extended to include a larger number of fine grained systematic descriptors of BD, and for testing for correlation with genetic profiles from other co-morbid disorders. [ABSTRACT FROM AUTHOR]

Knowledge of the genetic basis of schizophrenia has markedly improved in the past five years with the discovery of more than 140 significantly associated loci. Several gene sets have been implicated in schizophrenia (e.g. RBFOX, FMRP, synaptic genes). Precise experimental modelling remains difficult as gene sets consist of hundreds of genes and the functional effect of perturbations are likely to be cell type dependent. One key that would allow to model schizophrenia and better understand the disorder is to identify the relevant brain cell types. Applying knowledge of the cellular taxonomy of the brain from single-cell RNA-sequencing, we evaluated whether specifically expressed genes from 24 brain cell types (identified from the sequencing of 9970 single cells from 5 different brain regions) were enriched in schizophrenia heritability using two methods (LDSC and MAGMA). We also evaluated whether gene sets previously associated with schizophrenia were specifically expressed in specific cell types. The common variant genomic results for schizophrenia consistently mapped to pyramidal cells, medium spiny neurons, and certain interneurons but far less consistently to embryonic, progenitor, or glial cells. These results broadly replicated in external datasets. The key results were supported by multiple statistical methods. In addition, many of the diverse gene sets associated with schizophrenia (including pharmacologically defined antipsychotic targets) implicated the same brain cell types. Furthermore, our results indicate that these enrichments were due to distinct sets of genes specifically expressed in each of these cell types. A comparative analysis with other brain related traits (e.g. education years, IQ, MDD, Alzheimer) and one non-brain trait (Height) results in distinct patterns of relevant cell types. Our results provide a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. [ABSTRACT FROM AUTHOR]

NRXN1 deletions are a confirmed risk factor for schizophrenia and ASD. The full phenotypic spectrum of consequences of these deletions has not been established. We tested 140,187 white British or Irish participants in the UK Biobank (aged 40–70) for the presence of deletions that intersect at least one exon of the NRXN1 gene 48 people (30 women and 18 men) carried such deletions (0.03%). Carriers had subtle cognitive deficits: on seven tests they showed differences of between 0 and 1 SD (Z-scores, corrected for age and gender), with only two of these reaching significance: Digit Symbol and Reaction Time tests. Carriers did not differ on their educational qualifications (e.g., 15 carriers went to college or university), their occupational attainment, income or subjective happiness and satisfaction with their health and financial situation. We tested over 30 health outcomes, such as heart attacks, diabetes, cancer or number of hospital admissions. There was no increase in any adverse health outcomes. There was no increase in major psychiatric disorders, and no carrier had developed schizophrenia or mania. There were slight reductions of some measures of physical fitness: carriers had slight increases in hip and waist circumference, and lower peak expiratory volume. Despite the only subtle differences and the lack of adverse health outcomes, NRXN1 deletion carriers had on average 0.7 fewer children than the rest of the participants (on average women in the Biobank had 1.82 children and men had 1.78 children). Nine of the 18 men and 13 of the 30 women had no children. The differences in both men and women were significant, confirming previous suggestions that carriers have reduced fecundity (Rees et al., 2011; Stefansson et al., 2014). Reduced fecundity appears to be present even among overall healthy middle-aged people who have escaped early neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

Epigenetic processes play a key role in orchestrating transcriptional regulation during the development of the human central nervous system. We have quantified dynamic changes in DNA methylation (5mC) and DNA hydroxymethylation (5hmC) occurring during human fetal brain development, using a unique collection of human fetal brain samples spanning 23 to 184 days post-conception. We identify widespread changes in both modifications occurring during human brain development, notable sex-differences, and interactions between 5mC and 5hmC at specific sites. We also identify loci where DNA modifications in the fetal brain are associated with genetic variation, highlighting the utility of mQTLs and hmQTLs for fine-mapping GWAS loci of neurodevelopmental phenotypes. Finally, we have examined variation in both 5mC and 5hmC across multiple regions of the adult brain in neurodevelopmental phenotypes including schizophrenia and autism, identifying disease-associated DNA modifications and relating these to neurodevelopmental trajectories of gene regulation. A searchable database of our fetal brain regulatory genomic data is available as a resource to the research community at http://epigenetics.essex.ac.uk/fetalbrain2/. [ABSTRACT FROM AUTHOR]

Most psychiatric disorders are thought to have their origins at least in part in childhood, even if early manifestations of liability are quite different from the later full-blown clinical picture. This work aims to identify traits relevant to risk for psychiatric disorders early in development by investigating which "neurodevelopmental domains" are associated with psychiatric disorder risk alleles during childhood. Findings will be presented testing the hypothesis that psychiatric disorder risk alleles, as measured by polygenic risk scores, affect normative, dimensional childhood characteristics in the general population. Specifically, this work investigates associations between polygenic risk scores for schizophrenia, bipolar disorder, major depressive disorder and Attention Deficit Hyperactivity Disorder and primarily pre-pubertal neurodevelopmental traits using longitudinal general population samples. [ABSTRACT FROM AUTHOR]

Variants at microRNA-137 (MIR137), one of the most strongly associated schizophrenia risk loci identified to date, are associated with poorer cognitive performance. As microRNA-137 is known to regulate the expression of ~1900 other genes, including several that are independently associated with schizophrenia, we tested whether this gene set was also associated with variation in cognition, brain structure and brain function. Our analysis was based on an empirically derived list of genes whose expression was altered by manipulation of MIR137 expression. This list was cross-referenced with genome-wide schizophrenia association data to construct individual polygenic scores. In a sample of 808 patients and 192 controls, we tested whether these risk scores were associated with altered performance on cognitive functions known to be affected in schizophrenia. A subgroup of healthy participants also underwent functional imaging during memory performance, and brain volume and cortical thickness and shape analysis was carried out in n=216 patients and healthy participants. Increased polygenic risk within the empirically derived miR-137 regulated gene score was associated with significantly lower performance measures of IQ, working memory and episodic memory. Analysis of the spatial working memory fMRI task further suggested that increased risk score (thresholded at P=10-5) was significantly associated with increased activation of the right inferior occipital gyrus. Finally, the MiR137 gene network was not associated with variation in cortical thickness or shape, nor was it associated with variation in hippocampal volume. While polygenic risk scores were associated with reduced whole brain volume, this finding did not survive correction for multiple testing. In conclusion, these data are consistent with emerging evidence that MIR137 associated risk for schizophrenia may relate, in part, to its broader downstream genetic effects on neurocognitive function. [ABSTRACT FROM AUTHOR]

• Low-field static gradient DEXSY methods are developed. • Water exchanging across lipid membranes is measured rapidly. • Diffusion, T 1 and exchange weightings are explained. • T 1 weighting is removed from AXR. • Most rapid method measures AXR in 80 s. Diffusion exchange spectroscopy (DEXSY) provides a means to isolate the signal attenuation associated with exchange from other sources of signal loss. With the total diffusion weighting b 1 + b 2 = b s held constant, DEXSY signals acquired with b 1 = 0 or b 2 = 0 have no exchange weighting, while a DEXSY signal acquired with b 1 = b 2 has maximal exchange weighting. The exchange rate can be estimated by fitting a diffusion exchange model to signals acquired with variable mixing times. Conventionally, acquired signals are normalized by a signal with b 1 = 0 and b 2 = 0 to remove the decay due to spin–lattice relaxation. Instead, division by a signal with equal b s but b 1 = 0 or b 2 = 0 reduces spin–lattice relaxation weighting of the apparent exchange rate (AXR). Furthermore, apparent diffusion-weighted R 1 relaxation rates can be estimated from non-exchange-weighted DEXSY signals. Estimated R 1 values are utilized to remove signal decay due to spin–lattice relaxation from exchange-weighted signals, permitting a more precise estimate of AXR with less data. Data reduction methods are proposed and tested with regards to statistical accuracy and precision of AXR estimates on simulated and experimental data. Simulations show that the methods are capable of accurately measuring the ground-truth exchange rate. The methods remain accurate even when the assumption that DEXSY signals attenuate with b is violated, as occurs for restricted diffusion. Experimental data was collected from fixed neonatal mouse spinal cord samples at 25 and 7 ° C using the strong static magnetic field gradient produced by a single-sided permanent magnet (i.e., an NMR MOUSE). The most rapid method for exchange measurements requires only five data points (an 80 s experiment as implemented) and achieves a similar level of accuracy and precision to the baseline method using 44 data points. This represents a significant improvement in acquisition speed, overcoming a barrier which has limited the use of DEXSY on living specimen. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to an article on structural variations in children with attention-deficit hyperactivity disorder (ADHD) by Nigel Williams and colleagues in the October 23, 2010 issue.

Alzheimer's disease (AD) is a devastating neurodegeneration with a characteristic deficit in cholinergic neurotransmission. Treatment with acetylcholinesterase (AChE) inhibitors aims to reverse this deficit and does ameliorate the decline in cognition in some AD patients, although response is variable.To examine whether sequence variation in the gene encoding choline acetyltransferase (CHAT), which encodes the major catalytic enzyme of the cholinergic pathway, predicts response to AChE inhibitors.Alzheimer's disease patients (121) were treated with cholinesterase inhibitors and the effect of treatment on cognition was measured using the Mini Mental State Examination (MMSE). Six polymorphisms in CHAT were analysed for association with change in MMSE score.After correction for multiple testing, we found one SNP, rs733722, in a promoter region of CHAT, is associated with response of AD patients to cholinesterase inhibitors (P=0.03) and accounts for 6% of the variance in response to AChE inhibitors.Rs733722 represents a putative marker of response to AChE inhibitors in AD patients. [ABSTRACT FROM AUTHOR]

Highlights from the article: Su93the contribution of psychiatric risk alleles to a general liability to psychopathology in early life: investigating one explanation for pleiotropy In this study we examine the structure of psychopathology in childhood and early adolescence in a population-based birth cohort, including autistic and ADHD symptoms as well as emotional and behavioral items that have been used in previous studies. PRS were derived from the largest available published genome-wide association studies of schizophrenia, major depressive disorder (MDD), autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD).

Highlights from the article: Su38early onset depression: characterising developmental trajectories and the role of neuropsychiatric genetic risk variants B Results: b Latent class growth analysis identified three distinct trajectory classes - a persistently low class (73.7%), a late-adolescent-onset class (17.3%), and an early-adolescent-onset class (9.0%). The late-adolescent class, which had features of a "typical" post-pubertal-onset depression trajectory, was associated with an elevated genetic risk for depression as indexed by MDD PRS, but not with liability to neurodevelopmental disorders.

Highlights from the article: Identification of association-enriched gene-sets in each training set was derived from 134 central nervous system (CNS)-related gene-sets shown to capture the excess burden in schizophrenia for copy number variants [6]. The FMRP targets [1] gene-set preferentially captured variance in cognition in schizophrenia over other previously associated schizophrenia gene-sets when the GWAS of IQ was used to define risk alleles. One important observation was in marked contrast to genome wide polygenic risk score analyses, many gene-set polygenic risk scores capture maximal variance when risk alleles are defined at the genome wide significant threshold.

Highlights from the article: B Background: b Cognitive impairment is a clinically important feature of schizophrenia but is not significantly impacted by current treatments. We were interested in establishing the relative contributions to variance in cognition in schizophrenia of schizophrenia risk alleles and alleles that influence cognitive ability in the general population. We examined the relationship between g and PRS for EA, population IQ, schizophrenia, bipolar disorder and major depressive disorder in 2825 schizophrenia case samples from the Psychiatric Genomics Consortium (PGC).

Highlights from the article: B Background: b Findings from genome-wide association studies have been extremely successful and we now have an embarrassment of riches of potential disease loci for psychiatric disorders such as schizophrenia. Chromatin conformation capture methods shed light on the three-dimensional organization of chromatin. B Methods: b We have generated the most detailed 3D chromatin interactome of adult brain cortex and fetal cerebra to date using easy Hi-C (eHi-C), a variation of Hi-C that yields high quality libraries using a much lower input.

Highlights from the article: Sa61can dna methylation profiling shed light on the biology of cannabis associated psychosis? B Results: b Our preliminary analyses revealed regular cannabis use-associated dysregulation of DNA methylation at multiple loci across the epigenome that also include CpGs previously associated with Schizophrenia. B Discussion: b This epigenome-wide study of first episode psychosis patients and healthy controls represents the largest and most comprehensive study of methylomic variation in regular cannabis users compared to never users performed to date.

Highlights from the article: F29investigating supervised machine learning methods for prediction of schizophrenia in uk biobank B Background: b Supervised machine learning encompasses a range of methods for learning patterns from labelled data. This study has developed and tested a machine learning framework for analysis of UK Biobank data and investigated several approaches using genetic variants for prediction.

Highlights from the article: B Background: b Large, rare copy number variants (CNVs) are associated with neurodevelopmental disorders but it is unclear whether such CNVs also contribute to the risk of depression. Exploratory analyses found neurodevelopmental CNVs to have a stronger effect on risk of depression in females (OR 1.48, 95% CI 1.30 - 1.69, p 3.07 × 10-9) compared to males (OR 1.16, 95% CI 0.96 - 1.39, p 0.12) for the primary depression phenotype. B Discussion: b We report the largest study of CNVs in depression to date and the first to robustly demonstrate association between CNVs and depression.

Highlights from the article: The impact of the duffy-null genotype in clozapine-associated neutropenia: a genome-wide association study in individuals of african ancestry The antipsychotic clozapine, the only licensed medication for treatment-resistant schizophrenia, is under-prescribed and has high rates of discontinuation in individuals of African ancestry, due in part to increased rates of neutropenia. In the first genetic association study of neutrophil counts during clozapine treatment in 552 individuals with robustly inferred African genetic ancestry, we identify two genome-wide significant loci.

Objective: A valine/methionine polymorphism in the catechol O-methyltransferase (COMT) gene has been proposed to influence susceptibility to schizophrenia, as has a COMT haplotype in Ashkenazi Jewish and Irish subjects. The authors examined these hypotheses.Method: They reviewed data from more than 2,800 individuals, including almost 1,200 with schizophrenia, from case-control and family-based European association samples.Results: The authors found no support for the hypothesis that a valine/methionine polymorphism in the COMT gene influences susceptibility to schizophrenia or the hypothesis that a COMT haplotype influences susceptibility to schizophrenia in Ashkenazi Jewish and Irish subjects.Conclusions: The data suggest that the valine allele of COMT does not increase susceptibility to schizophrenia in Europeans and that the Ashkenazi or Irish haplotype does not increase susceptibility. Ethnic variation in the linkage disequilibrium structure at COMT means that the haplotype data may not generalize across populations. However, the authors' examination of the hypothesis that the valine allele confers susceptibility, with a particularly strong effect in Europeans, reveals that no such caveat applies. [ABSTRACT FROM AUTHOR]

Objective: Association has been reported between the C allele of a -759C/T polymorphism in the promoter of the 5-HT2c receptor gene (HTR2C) and antipsychotic-induced weight gain, suggesting that polymorphic HTR2C expression influences this phenotype. The authors tested this polymorphism, and other promoter variants, for effects on HTR2C transcription. Method: Six HTR2C promoter haplotypes constructed from four polymorphisms were cloned into a luciferase reporter gene plasmid. Their transcriptional activities were then com- pared in two human cell lines. Results: All haplotypes containing the -759C allele showed less transcriptional activity than haplotypes containing the -759T allele. The A allele of a -997G/A polymorphism was also associated with reduced expression. Conclusions: These findings suggest that the -759C allele is functional and results in relative underexpression of HTR2C Reduced expression of HTR2CmRNA may underlie vulnerability to weight gain following antipsychotic treatment. [ABSTRACT FROM AUTHOR]

Previous studies find that both schizophrenia and mood disorder risk alleles contribute to adult anxiety and depression. Emotional problems (depression or anxiety) begin in childhood and show strong continuities into adult-life; this suggests that symptoms are the manifestation of the same underlying liability across different ages. However, other findings suggest there are developmental differences in the etiology of emotional problems at different ages. These include (a) differences in treatment responsiveness and gender ratios in child/adolescence compared to adulthood, (b) recent genetic findings that schizophrenia risk alleles were specifically associated with "earlier-onset" (<27 years) rather than "later-onset" depression. To our knowledge, no study has prospectively examined the impact of psychiatric risk alleles on emotional problems at different ages in the same individuals. Data were analyzed using regression-based analyses in two UK, prospective, population-based cohorts (NCDS and ALSPAC). Schizophrenia and Major Depressive Disorder (MDD) Polygenic Risk Scores (PRS), were derived from published Psychiatric Genomics Consortium genome-wide association studies. Emotional problems were assessed prospectively from age 7 to 44 years in NCDS and from age 7 to 18 years in ALSPAC. Schizophrenia PRS were associated with emotional problems from childhood (β=0.044, p=0.005) to mid-life (β=0.033, p=0.023), while MDD PRS were associated with emotional problems only in adulthood (β=0.035, p=0.011; childhood β=0.014, p=0.372). Associations between schizophrenia PRS and early emotional problems appear to be driven by anxiety rather than depression. Our prospective investigations suggests that early (childhood) emotional problems in the general population share more genetic risk with schizophrenia, while later (adult life) emotional problems also shared genetic risk with MDD. This is consistent with findings from cross-sectional clinical studies of MDD. The results suggest that the genetic architecture of depression/anxiety is not static across development. [ABSTRACT FROM AUTHOR]

Psychotic symptoms can be conceptualised as dimensions of psychopathology cutting across diagnostic boundaries. Thus, they might be considered enhanced quantitative phenotypes to relate to genetic variants as summarised by Polygenic Risk Scores (PRSs) for Major Mental Disorders (MMDs), including Schizophrenia (SZ), Bipolar Disorder (BP), and Major Depressive Disorder (MDD). The objectives of this study were to: 1) identify the dimensional structure of symptoms at First Episode Psychosis (FEP), testing whether a bi-factor model statistically fits the conceptualization of psychosis as a single common construct (general psychosis factor) while also recognising multidimensionality (positive, negative, disorganized, manic, and depressive symptom factors); 2) examine the extent to which MMD PRSs indexed the phenotypic variance due to the general psychosis construct and to the specific symptom dimensions. The sample included 1182 FEP patients recruited as part of the EUGEI study. The MRC Sociodemographic Schedule and the OPerational CRITeria (OPCRIT) were used to collect sociodemographic information and assess psychopathology. DNA was extracted from blood or saliva samples collected from 940 participants. The following analysis steps were performed: 1) OPCRIT psychopathology items were analysed using multidimensional item response modelling in Mplus to estimate unidimensional, multidimensional, and bi-factor models of psychosis. Models' fit statistics were compared using Log-Likelihood, and Akaike and Bayesian Information Criteria. 2) SZ, BP, and MDD PRSs were built using the results from large mega-analyses from Working Groups of the Psychiatric Genomics Consortium. In PRSice, individuals' number of risk alleles in the target sample was weighted by the log odds ratio from the discovery samples, and summed into the three PRSs. 3) For the best data fitting psychosis model, linear regressions were estimated to predict symptom dimensions as a continuous outcome from the three PRSs, accounting for population stratification. The best model fit statistics was observed for the bi-factor model including one general and five specific symptom factors compared with the other models. This indicated that there was a broad latent structure underlying the whole range of psychosis symptoms among five latent specific symptom dimensions. PRSs for SZ, BP, and MDD were calculated at the best model fitting P-value threshold. As expected, there was a substantial difference in discrimination of case-control status between SZ PRS and BP and MDD PRSs. A significant positive linear regression equation was observed for BP PRS and mania dimension severity (t(864)=2.74, p<0.01), explaining 5% of the variance; whereas a significant negative linear regression equation was found for MDD PRS and the negative dimension severity (t(864)=-1.75, p=0.05), explaining 3% of the variance. No significant association was found for SZ, BP, or MDD PRSs and the general psychosis trait score. These results suggest that a) psychosis at illness onset can be conceptualised as being composed of one general factor and five specific symptom dimensions, b) there is an association between mania dimension score and BP PRS. Despite the need to both replicate these findings also using PGC new released GWAS to build better powered PRSs, psychosis symptom dimensions have clearly been shown to be a valid and a useful continuous quantitative phenotype across categorical disorders. [ABSTRACT FROM AUTHOR]

Recent sequencing studies have shown a small fraction of SZ risk comes from rare mutations. They have also advanced our understanding of SZ pathophysiology, with multiple studies implicating post-synaptic proteins, including the activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-d-aspartate receptor (NMDAR) complexes. Thus far, only one gene, SETD1A, has been associated with SZ at genome-wide levels of significance. We aimed to identify novel SZ genes by sequencing 187 genes in 5,207 cases and 4,991 controls. Included among these genes are members of ARC and NMDAR complexes, as well as Voltage-Gated Sodium (VGSC) and Calcium Channels (VGCC), all of which have been previously implicated in SZ. A total of 5,724 cases, 5,769 controls were selected for Ion Torrent sequencing of 187 candidate SZ genes. None of these samples have been included in previous SZ sequencing studies. After stringent quality control (low sequence quality, relatedness and ancestry), our sample consisted 5,207 cases and 4,991 controls. Gene-set and single-gene association statistics were generated using a Firth's penalised-likelihood logistic regression model. Cases had a significant excess of Loss-of-Function (LoF) mutations (< 0.1%) in all 187 genes after correction for multiple testing (P=0.0023, OR=1.33). No other class of mutation was enriched in cases after correction for multiple testing. For gene-sets previously implicated in SZ, cases had higher rates of LoF mutations in ARC (P=0.047, OR=2.7), NMDAR (P=0.024, OR=1.7), and VGSCs (P=0.015, OR=1.98). No support was found for association with VGCCs (P=0.22, OR=0.72). We observed strong enrichment of LoF alleles in genes previously associated with Developmental Disorders (DD) (P=0.0025, OR=8.21). No single gene was significantly associated with SZ after correction for multiple testing. In a new, independent sequencing study of SZ, we found an excess of LoF alleles in cases in all 187 targeted genes, and provide independent support for the involvement of ARC and NMDAR post-synaptic protein complexes, and voltage-gated sodium channels, in SZ pathogenesis. We also provide further evidence for a shared genetic risk between SZ and DD. However, our study was underpowered to identify specific risk genes. [ABSTRACT FROM AUTHOR]

Several neuropsychiatric disorders are thought to have an early developmental component, which could be partly conferred by individual differences in gene expression. In order to explore sex and genotypic effects on gene expression in the human prenatal brain, we have performed whole transcriptome sequencing and genome-wide genotyping on a large collection (N > 120) of human fetal brain samples from the second trimester of gestation. Strand-specific whole transcriptome RNA-seq libraries were prepared from total RNA following ribosomal RNA depletion and deeply sequenced on an Illumina HiSeq. Genomic DNA from each sample was genotyped using Illumina arrays followed by SNP and indel imputation. Sex effects on gene expression were assessed by likelihood ratio tests. Expression quantitative trait loci (eQTL) in the human fetal brain will be identified using measures of total and allele-specific gene expression. We have identified hundreds of autosomal as well sex-linked genes exhibiting sex differences in expression or splicing in the prenatal human brain. Details of fetal brain eQTL and their association with neuropsychiatric disorders will also be presented. Our findings of sex differences in gene expression highlight an early stage of sexual differentiation of the human brain, which could have relevance to sex-biased neurodevelopmental disorders. Identification of fetal brain eQTL associated with neuropsychiatric disorders will help elucidate neurodevelopmental mechanisms contributing to these conditions. [ABSTRACT FROM AUTHOR]

Schizophrenia is a chronic and disabling psychiatric disorder affecting about 1% of the world population. While the biological mechanisms of schizophrenia remain largely elusive, much progress has been made in schizophrenia genetics in the past few years, with over 100 genomic loci associated with schizophrenia reported by the recent large-scale genome-wide association study. However, to date, almost all large schizophrenia genetics studies are derived from primarily European descent population, severely limiting our understanding of schizophrenia biology. Here we present a large-scale schizophrenia genetic study, comprising of 12 schizophrenia case-control cohorts from Singapore, Hong Kong, Taiwan, mainland China, Japan, and Indonesia. After quality control, there are 13,760 cases and 16,883 controls available for genome-wide association. A fixed effect meta-analysis across Asian and Caucasian populations was conducted resulting in a combined sample of 46,945 cases and 59,800 controls. A novel fine-mapping algorithm was designed and conducted to identify potential causal variants between Caucasian and Asian samples. Twelve loci (p<5e-8) were found associated with schizophrenia in the Asian sample. Six were previously associated with schizophrenia, and four are novel. An example is a new locus (Caucasians 0.7%; Asians 45%), which may have been previously missed, implicates CACNA2D2, a calcium channel auxiliary subunit associated with early infantile epileptic encephalopathy. Meta-analysis across Asian and Caucasian populations identified 40 new loci implicated in schizophrenia. Genetic effects are consistent in both populations. Using a published fine-mapping method and a European-only dataset, we mapped 11 schizophrenia associations to a credible set of ≤5 variants. The number increased to 18 associations when we used the novel fine-mapping algorithm on a combined European and Asian dataset, demonstrating a significantly improved association resolution. The reported results consist of amongst the largest collection of Asian GWAS samples to date. Evidence indicates shared biology across major world populations in schizophrenia. Specifically, across the two populations, all known schizophrenia associations were congruent in effect directions, and effect sizes show no significant heterogeneity. Our approach not only serve to improve detection of common variant loci that implicates two major populations in the world, the approach we have undertaken, improved GWA resolution which in turn allows us to better isolate the causal alleles and facilitate the functional interpretation of schizophrenia associations. [ABSTRACT FROM AUTHOR]

Schizophrenia is a debilitating psychiatric condition that manifests itself in the early adult life and is often associated with poor quality of life and decreased life expectancy. It is both highly heritable and polygenic, with risk variants spanning the full spectrum of population frequencies. There has been a long-standing debate, from an evolutionary perspective, as to how risk alleles persist in the human gene pool, particularly given the decreased fecundity associated with schizophrenia. It has been repeatedly show that rare risk alleles of strong effect persist due to mutation-selection balance, a mechanism which implies that they are removed from the population by natural selection at the same rate that they appear by mutation. However, an explanation for the persistence of common risk alleles of small effect has not been explicitly given, though this is often attributed to various evolutionary scenarios. One of the most popular hypotheses links this persistence to positive selection, arguing that current common risk alleles for schizophrenia might have been beneficial at some point during human evolution, and these benefits resulted in the allele frequencies we observe today. While detecting selection signals in genomic data has been traditionally challenging, recent advances in the statistical and population genetics communities have made possible to systematically test for the presence of selected alleles in GWAS summary statistics. To demonstrate the possibilities of such a procedure, this work uses a large-scale meta-analysis of schizophrenia GWAS data (40,675 cases and 64,643 controls) to test four different metrics of positive selection, each tailored to a particular timeframe of human evolution. The LD-Score framework shows that none of these metrics are significantly associated with common genetic variation, raising doubts into the validity of positive selection as a driver for the persistence of schizophrenia risk alleles. Furthermore, strong association is shown for a metric of negative selection, background selection (h2 enrichment = 1.801; p=0.001), which recurrently affects regions of low recombination and reduces genetic diversity. An examination of the mechanism of action of background selection, coupled with a simulation analysis, allows us to establish that regions with reduced genetic diversity are more likely to harbour common risk alleles in schizophrenia, and that this is compatible with our current knowledge about the epidemiology of the disorder. This also suggests a genetic model for the action of natural selection in schizophrenia, which relates our findings to the nearly-neutral theory of molecular evolution (Ohta 1973) and could be extended to other psychiatric complex traits. [ABSTRACT FROM AUTHOR]

The article focuses on the effect of pasture versus indoor feeding systems on raw milk composition and the quality over an entire lactation and fatty acids, α-linolenic acid and eicosenoic acid were labelled in reverse order, as were behenic acid and each are correlated with same feeding system.

Background Schizophrenia (SZ) and Bipolar disorder (BD) show evidence for partial overlap in phenotypic and genetic influences based on family, twins, adoption and Psychiatric Genetic Consortium (PGC) studies. They have lifetime prevalence of about 1% and 2.4%, and heritability estimates of 60-80% and 40-70%, respectively. In the last decade BD has been investigated using dimensional structuring of psychoses based on symptomatic-functional checklists that provides reliable approach to phenotypic assessment. Recent research suggests moving towards developing Phenotype-based Genetic Association Studies. In this approach, patients will only be put into groups consisting of others with symptoms similar to their own. Canonical Correlation Analysis (CCA) is statistical technique designed to identify relationships (usually hidden) between two sets of variables. We use CCA to combine genotypic and phenotypic variables and measure correlation between those sets. This analysis estimates canonical correlation between psychotic symptoms measured using validated item check list (OPCRIT), and genome-wide significant (GWS) loci from PGC2 schizophrenia. Methods For our analysis we used phenotype and genetic data for 5,507 BD cases. Imputation of genetic data was performed with 1000Genomes (Phase 3, 2014) then quality control was applied (INFO>0.8, HWE>1e-6, MAF>0.01). Additional quality control was performed on phenotypic symptom coverage. CCA was employed as implemented in R, using package “CCA” with GWS loci from PGC2 SZ and OPCRIT items. SNPs were standardised and adjusted for 10 population covariates calculated from imputed data using principal component approach prior to CCA. Results Canonical correlation analysis was run on 4422 cases on 89 available GWS PGC2 SZ SNPs or their proxies (with r2>0.6). 60 phenotypic variables were taken from OPCRIT measurements including mood disturbance, biological indices, atypical depression, substance use, psychosis and social functioning. We found no significant canonical correlations indicating absence of hidden sub-clusters at individual symptom level of BD associated with SZ GWS loci. Discussion Our analysis was focused to find correlation from bipolar phenotype by using OPCRIT questionnaire and GWS SZ loci from PGC2. We have shown that there were no significant canonical correlation coefficients suggesting that there is no direct association between SZ associated genetic loci and BP at individual symptom level. CCA is canonical correlation analysis is one of potential of data-driven approaches to identify hidden genotype-phenotype relationships. It provides opportunities to generate and test different hypotheses and understand more about complex architecture of psychiatric disorders. In the next stage we plan to extend our analysis to more fine grained systematic descriptors of BD and test for correlation with genetic profiles from a number of co-morbid disorders, as well as the full range of phenotypic and genetic data that are available. [ABSTRACT FROM AUTHOR]

Background The UK Biobank is a unique resource for biomedical research, with extensive phenotypic and genetic data on half a million adults. We wanted to call all pathogenic CNVs in the first 150,000 participants and examine the cognitive performance and phenotypic characteristics of their carriers. Methods We used Affymetrix Power Tools and PennCNV-Affy software to analyse 152,728 Affymetrix microarrays in batches of ~4,600 from the first data release. We annotated a list of 93 CNVs that have been proposed to be pathogenic. Results The frequencies of the 93 CNVs were remarkably similar to those among 26,628 controls from other datasets. Carriers of neurodevelopmental CNVs performed worse on cognitive tests and had lower educational and occupational attainment. Carriers of CNVs with known phenotypes displayed the expected characteristics, e.g. increased or reduced BMI in 16p11.2 deletions and duplications carriers. Discussion The UK Biobank is the largest population study that allows the study of the effect of CNVs on cognitive and physical phenotypes. The set of CNVs will be made available for use by the scientific community. [ABSTRACT FROM AUTHOR]

Background Bipolar disorder (BD) includes a broad range of phenotypic features – most research examining its genetic underpinning focuses on the overall syndrome rather than its subphenotypic components. BD is a highly heritable disorder and while its genetic architecture is not fully elucidated there is increasingly strong support for a very polygenic component with partial polygenic overlap with schizophrenia (SZ). Here we present preliminary results from an analysis examining the association of SZ derived polygenic risk scores (PRS) across different BD subtypes (Bipolar Type 1(BPI), Bipolar Type 2 (BPII) and Schizoaffective disorder (SAD), and subphenotypes defined by the presence of psychosis and its associated level of mood incongruence. Methods We used a UK sample of 3101 BP cases, collected using a consistently administrated interview protocol with OPCRIT confirmed lifetime diagnosis of Research Diagnostic Criteria (RDC - BPI, BPII or SAD). PRS were generated using 1000 genomes (phase3, 2014) imputed genetic data (INFO score>0.8, HWE>1e-6, MAF>0.01) trained on the results from Psychiatric Genetic Consortium (PGC2) SZ GWAS, pruned r2 <0.25, and computed across different SZ association p-value thresholds (range 0.0001 - 0.5). PRS were standardised and analysed with nominal logistic regression with RDC subtypes as dependant variables. To test whether psychosis mediated the association across subtypes, we repeated the analyses fitting psychosis together with PRS in the model and comparing it with the PRS only model. We also examined SZ-PRS association with psychosis in the whole sample and level of mood incongruent psychotic features in the subset of cases with psychosis (n =1352). All regression models were adjusted for age, sex and 1st 10 principal components derived from genetic data. Above analyses was run using DSM and ICD Results PRS with the SZ association p-value cut-off of 0.5, have shown significant association across the BD subtypes with relative risk ratios RRR = 1.28 (95%CI: 1.18-1.39, p<0.0001) and RRR = 1.18 (95%CI: 1.01–1.38, p=0.03) for BP1 and SAD, respectively, compared to BP2 as the baseline. Entering psychosis into the model attenuated the effect of PRS in the BP1 group but still remained significant (RRR = 1.19, 95%CI: 1.08-1.31, p<0.0001). In contrast the effect in the SAD group has become insignificant (RRR= 1.05, 95%CI: 0.89-1.24, p=0.6). In the whole sample of BD cases, PRS has shown association with presence of psychosis RRR=1.23 (95%CI: 1.15-1.34, p<0.0001). Examining cases with psychosis, we found PRS was associated with increasing level of mood incongruence (OR=1.15, 95%CI: 1.04-1.27, p=0.005). The results are ostensibly the same when PRS are generated using p-value thresholds from the range 0.05 - 0.5 , indicating these results are mostly driven by SNPs identified at p<0.05. Analyses using DSM and ICD show similar results. Discussion Preliminary analyses show a genetic - phenotypic association, between polygenic features of schizophrenia and BP characterised by the presence of psychosis, suggesting the phenotypic overlap between SZ and BD may in part be driven by polygenic overlap. This finding is further supported by the association of PRS and level of mood incongruence in the content of psychotic symptoms. These results suggest the PRS effect is not solely mediated though the psychosis subphenotype, at least in the BPI group. Our analyses show promise for the strategy of examining polygenic/phenotypic associations based on fine grained clinical characterisations [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article on the link between rs498055 with Alzheimer's disease, published in the July 2006 issue.

Abstract: Progressive supranuclear palsy (PSP) is the most common atypical parkinsonian disorder. Abnormal tau inclusions, in selected regions of the brain, are a hallmark of the disease and the H1 haplotype of MAPT, the gene encoding tau, is the major risk factor in PSP. A 3-repeat and 4-repeat (4R) tau isoform ratio imbalance has been strongly implicated as a cause of disease. Thus, understanding tau isoform regional expression in disease and pathology-free states is crucial to elucidating the mechanisms involved in PSP and other tauopathies. We used a tau isoform-specific fluorescent assay to investigate relative 4R-tau expression in 6 different brain regions in PSP cases and healthy control samples. We identified a marked difference in 4R-tau relative expression, across brain regions and between MAPT haplotypes. Highest 4R-tau expression levels were identified in the globus pallidus compared with pons, cerebellum, and frontal cortex. 4R-tau expression levels were related to the MAPT H1 and H1c haplotypes. Similar regional variation was seen in PSP case and in control samples. [Copyright &y& Elsevier]