Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Relevant Logic and Paraconsistency

Abstract. This is an account of the approach to paraconsistency as-sociated with relevant logic. The logic fde of first degree entailments is shown to arise naturally out of the deeper concerns of relevant logic. The relationship between relevant logic and resolution, and especially the disjunctive syllogism, is then examined. The relevant refusal to validate these inferences is defended, and finally it is suggested that more needs to be done towards a satisfactory theory of when they may nonetheless safely be used. 1 Why Paraconsistency? The core business of logic is to underpin reasoning. The distinction is important: a logic is a theory; reasoning is a process. The activities of a reasoner are not dictated by logic, but are described by it in the sense that logic issues permissions—assurances that certain forms of inference will never lead into error—and restrictions. The restrictions are not on inferences, for the reasoner may of course reason invalidly if it so wishes

Nuclear targeting of Porphyromonas gingivalis W50 protease in epithelial cells

Porphyromonas gingivalis is an important pathogen associated with destructive periodontal disease and is able to invade the epithelial cell barrier. Its cysteine proteases are recognized as major virulence factors, and in this study, we examined the interaction of the arginine-specific protease with epithelial cells in culture. Three cell lines (KB, HeLa, and SCC4) were incubated with strain W50 culture supernatant; stained with monoclonal antibody 1A1, which recognizes an epitope on the adhesin (ß) component of the cysteine protease-adhesin ({alpha}/ß) heterodimer; and viewed using immunofluorescence microscopy. Within 1 h, the protease traversed the plasma membrane and was localized around the nucleus before becoming concentrated in the cytoplasm after 24 to 48 h. In contrast, the purified arginine-specific heterodimeric protease (HRgpA) rapidly entered the nucleus within 15 to 30 min. This nuclear targeting (i) was seen with active and N{alpha}-p-tosyl-L-lysine chloromethyl ketone (TLCK)-inactivated HRgpA, indicating it was independent of the proteolytic activity; (ii) occurred at both 4 and 37°C; and (iii) failed to occur with the monomeric protease (RgpAcat), indicating the importance of the adhesin chain of the HRgpA protease to this process. Rapid cell entry was also observed with recombinant catalytic ({alpha}) and adhesin (ß) chains, with the latter again targeting the nuclear area. After 48 h of incubation with HRgpA, significant dose-dependent stimulation of metabolic activity was observed (measured by reduction of 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide), and a doubling of mitotic activity combined with the presence of apoptotic cells indicated that HRgpA may interfere with cell cycle control mechanisms. These effects were seen with both active and TLCK-inactivated protease, confirming that they were not dependent on proteolytic activity, and thus provide new insights into the functioning of this P. gingivalis protease

Recognition of the carbohydrate modifications to the RgpA protease of Porphyromonas gingivalis by periodontal patient serum lgG

Periodontal infections by Porphyromonas gingivalis are associated with a sustained systemic IgG antibody response and elevations in local antibody synthesis to this organism. One of the targets of this response is a protease, RgpAcat, which is an important virulence determinant of this organism. Recently, we demonstrated that this molecule is glycosylated and that the glycan chains are immunologically related to P. gingivalis lipopolysaccharide (LPS) (Curtis et al., Infect Immun 1999;62:3816-3823). In the present study, we examined the role of these glycan additions in the immune recognition of RgpAcat, by sera from adult periodontal patients (n = 25). Serum IgG antibody levels to P. gingivalis W50, RgpAcat and LPS and to recombinant RgpA were determined by enzyme-linked immunosorbant assay (ELISA). No correlation was observed between the antibody levels to RgpAcat from P. gingivalis and the recombinant form of this enzyme expressed in Escherichia coli. However, a strong association was found between the recognition of LPS and the wild-type enzyme (R = 0.8926; p = 0.0005). Incorporation of LPS into the ELISA led to a significant reduction (mean 25%; range 0.8-43%, SD = 15; p &#60; 0.05) in the recognition of RgpAcat, but had no effect on the recognition of control antigens. Deglycosylation of RgpAcat led to the abolition of immune recognition by patient serum IgG, which suggests that the glycan additions to this molecule are the principal targets of the immune response. Therefore, glycosylation of the RgpAcat protease may play an important role in immune evasion by shielding the primary structure from immune recognition