8 research outputs found
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)
Cytotoxicity-related gene expression and chromatin accessibility define a subset of CD4+ T cells that mark progression to type 1 diabetes.
This article contains supplementary material online at https://doi.org/10.2337/figshare.17185898.Type 1 diabetes in children is heralded by a preclinical phase defined by circulating autoantibodies to pancreatic islet antigens. How islet autoimmunity is initiated and then progresses to clinical diabetes remains poorly understood. Only one study has reported gene expression in specific immune cells of children at risk associated with progression to islet autoimmunity. We analyzed gene expression with RNA sequencing in CD4+ and CD8+ T cells, natural killer (NK) cells, and B cells, and chromatin accessibility by assay for transposase-accessible chromatin sequencing (ATAC-seq) in CD4+ T cells, in five genetically at risk children with islet autoantibodies who progressed to diabetes over a median of 3 years (“progressors”) compared with five children matched for sex, age, and HLA-DR who had not progressed (“nonprogressors”). In progressors, differentially expressed genes (DEGs) were largely confined to CD4+ T cells and enriched for cytotoxicity-related genes/pathways. Several top-ranked DEGs were validated in a semi-independent cohort of 13 progressors and 11 nonprogressors. Flow cytometry confirmed that progression was associated with expansion of CD4+ cells with a cytotoxic phenotype. By ATAC-seq, progression was associated with reconfiguration of regulatory chromatin regions in CD4+ cells, some linked to differentially expressed cytotoxicity-related genes. Our findings suggest that cytotoxic CD4+ T cells play a role in promoting progression to type 1 diabetes.Naiara G. Bediaga, Alexandra L. Garnham, Gaetano Naselli, Esther Bandala-Sanchez, Natalie L. Stone, Joanna Cobb, Jessica E. Harbison, John M. Wentworth, Annette-G. Ziegler, Jennifer J. Couper, Gordon K. Smyth, and Leonard C. Harriso
The Validity of Tri Hita Karana (THK) Oriented Blended Learning Tools to Improve Student’s Critical Thinking Ability
Genetic Overlap Between Alzheimer's Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes.
Background: Alzheimer's disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits. Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer's Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework. Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR = 0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR = 0.022, opposite direction of effect). Conclusion: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP
Sotakarjut : Roolipelin visuaalinen taide ja ammatillinen vuorovaikutus projektityöympäristössä.
Opinnäytetyöni pohjautuu vuonna 2012 julkaistavaan roolipelikirjaan nimeltä Sotakarjut. TAMKista valmistuvana visuaalisena suunnittelijana olin mukana piirtämässä sekä konseptitaiteidetta, että kuvituskuvia kyseistä teosta varten. Kyseisen projektin aikana työskentelin sekä taiteellisen johdon alaisuudessa, että osana useamman kuvittajan/konseptitaiteilijan muodostamaa työryhmää, jolloin taiteellisesta ja ammatillisesta vuorovaikutuksesta tuli selkeä osa projektin kulkua. Näistä lähtökohdista päätin myös kirjoittaa opinnäytetyöni kirjallisen osuuden.
Opinnäytetyöni tarkoitus on valaista monin tavoin vuorovaikutteiseksi muodostuvien projektityöympäristöjen vaikutusta taiteilijaan niin kuvittajan, kuin konseptitaiteilijan ammattissa. Valitsemaani aihetta lähestyn tekemäni projektin rajaaman kontekstin sisällä käymällä aluksi läpi nämä kaksi visuaalisen suunnittelun ammattihaaraa kartoittamalla taiteilijan roolia osana laajempaa projektityöympäristöä, ja tarjoamalla käytännön kautta lähestyvää näkökantaa esittelemilleni asioille. Tutkin sekä ulkoisen, että sisäisen vuorovaikutuksen merkitystä ja niiden luomia mahdollisuuksia luovalla alalla toimivan taiteilijan näkökulmasta. Esitän myös käytännön tapoja siitä, miten nämä vuorovaikutukselliset elementit voidaan valjastaa palvelemaan yksilön omaa ammatillista ja taiteellista kehitystä.My thesis work is based on a traditional role-playing-game that is set to be published in the year 2012, a book titled Sotakarjut. About to graduate from TAMK, Tampere University of Applied Sciences, as a visual designer I took part in this project, in a role that covered two distinct fields of profession: concept art and a illustration. As an single artist I worked under a artistic supervision and within a project that had several illustrators/consept artist in its ranks, thus making it essential to work as a singular creative team.
In this thesis I will try to shed some light on how project-related work enviroments involves a specific kind of artististic approach from professional consept artists and illustrators. Having my project part work as my general context, I will start by making a general introduction on both of these creative professions, giving an overview on the subject of artististic work within project enviroments. I will also present a practical approach by adding examples from my actual project to support the theory based information I am presenting. In addition I will write about the many effects that professional interaction has within a working eviroment, from the artist view-point. Through this I will also explain how it is possible to assert yourself as a professional artist, so that this interaction can be made beneficial to the indivudual, both artistically and professional
Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc