scholarly journals Pairwise common variant meta-analyses of schizophrenia with other psychiatric disorders reveals shared and distinct gene and gene-set associations

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
William R. Reay ◽  
Murray J. Cairns
Keyword(s):  
Psychiatric Disorders ◽  
Common Variant ◽  
Gene Set ◽  
Distinct Gene ◽  
Meta Analyses

scholarly journals Pairwise common variant meta-analyses of schizophrenia with other psychiatric disorders reveals shared and distinct gene and gene-set associations

2019 ◽  
Author(s):  
William R. Reay ◽  
Murray J. Cairns
Keyword(s):  
Psychiatric Disorders ◽  
Association Studies ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Common Variant ◽  
Joint Analysis ◽  
Genome Wide Association Studies ◽  
Gene Set ◽  
Common Variation ◽  
Meta Analyses

ABSTRACTThe complex aetiology of schizophrenia is postulated to share factors with other psychiatric disorders. Recently, this has been supported by genome-wide association studies, with several psychiatric phenotypes displaying high genomic correlation with schizophrenia. We sought to investigate pleiotropy amongst the common variant genomics of schizophrenia and seven other psychiatric disorders using a multimarker test of association. Gene-based analysis of common variation revealed over 50 schizophrenia-associated genes shared with other psychiatric phenotypes; including bipolar disorder, major depressive disorder, ADHD, and autism spectrum disorder. In addition, we uncovered 78 genes significantly enriched with common variant associations for schizophrenia that were not linked to any of these seven disorders (P > 0.05). Transcriptomic imputation was then leveraged to investigate the functional significance of variation mapped to these genes, prioritising several interesting functional candidates. Pairwise meta-analysis of schizophrenia and each psychiatric phenotype further revealed 330 significantly associated genes (PMeta < 2.7 × 10−6) that were only nominally associated with each disorder individually (P < 0.05). Multivariable gene-set association suggested that common variation enrichment within biologically constrained genes observed for schizophrenia also occurs across several psychiatric phenotypes. These analyses consolidate the overlap between the genomic architecture of schizophrenia and other psychiatric disorders and uncovered several pleiotropic genes which warrant further investigation.AUTHOR SUMMARYSchizophrenia and other psychiatric disorders have many similarities, and this includes features of their overall genetic risk. Here, we investigate genes which may play a role in schizophrenia as well one or more of seven other psychiatric phenotypes and demonstrate that a number of them are pleiotropic and influence at least one other disorder. We also identify genes amongst the psychiatric disorders studied here which only show association with schizophrenia. Furthermore, we find a number of genes which were only significant when combining genetic association data from schizophrenia and one of the other seven disorders, suggesting there are shared genetic influences that are revealed through the power of joint analysis. This study identifies interesting novel shared (pleiotropic) genes in psychiatry which warrant future study.

Update on hypnotherapy for psychiatrists

2021 ◽  
pp. 1-7
Author(s):  
Natalie A. Chan ◽  
Zhisong Zhang ◽  
Guoxing Yin ◽  
Zhimeng Li ◽  
Roger C. Ho
Keyword(s):  
Psychiatric Disorders ◽  
Practice Guidelines ◽  
Review Article ◽  
Outcome Studies ◽  
Evidence Based ◽  
High Quality ◽  
Long Time ◽  
Meta Analyses ◽  
Evidence Based Therapy

SUMMARY Although hypnosis has played a part in psychotherapy for a long time, it is not yet seen as an evidence-based therapy and is absent from many practice guidelines when it comes to the treatment of psychiatric disorders. At present, the applications and methods of hypnotherapy are poorly understood and other methods of psychotherapy tend to be favoured. This review article aims to introduce the role of hypnotherapy and its application for certain common psychiatric presentations, as well as examine its efficacy by summarising recent evidence from high-quality outcome studies and meta-analyses.

scholarly journals Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review (Preprint)

2019 ◽  
Author(s):  
Sigurd Melbye ◽  
Lars Vedel Kessing ◽  
Jakob Eyvind Bardram ◽  
Maria Faurholt-Jepsen
Keyword(s):  
Systematic Review ◽  
Young Adults ◽  
Psychiatric Disorders ◽  
Literature Search ◽  
Risk Of Bias ◽  
Smartphone App ◽  
Controlled Trials ◽  
Self Monitoring ◽  
Randomized Controlled ◽  
Meta Analyses

BACKGROUND Psychiatric disorders often have an onset at an early age, and early identification and intervention help improve prognosis. A fine-grained, unobtrusive, and effective way to monitor symptoms and level of function could help distinguish severe psychiatric health problems from normal behavior and potentially lead to a more efficient use of clinical resources in the current health care system. The use of smartphones to monitor and treat children, adolescents, and young adults with psychiatric disorders has been widely investigated. However, no systematic review concerning smartphone-based monitoring and treatment in this population has been published. OBJECTIVE This systematic review aims at describing the following 4 features of the eligible studies: (1) monitoring features such as self-assessment and automatically generated data, (2) treatment delivered by the app, (3) adherence to self-monitoring, and (4) results of the individual studies. METHODS We conducted a systematic literature search of the PubMed, Embase, and PsycInfo databases. We searched for studies that (1) included a smartphone app to collect self-monitoring data, a smartphone app to collect automatically generated smartphone-based data, or a smartphone-based system for treatment; (2) had participants who were diagnosed with psychiatric disorders or received treatment for a psychiatric disorder, which was verified by an external clinician; (3) had participants who were younger than 25 years; and (4) were published in a peer-reviewed journal. This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The risk of bias in each individual study was systematically assessed. RESULTS A total of 2546 unique studies were identified through literature search; 15 of these fulfilled the criteria for inclusion. These studies covered 8 different diagnostic groups: psychosis, eating disorders, depression, autism, self-harm, anxiety, substance abuse, and suicidal behavior. Smartphone-based self-monitoring was used in all but 1 study, and 11 of them reported on the participants’ adherence to self-monitoring. Most studies were feasibility/pilot studies, and all studies on feasibility reported positive attitudes toward the use of smartphones for self-monitoring. In 2 studies, automatically generated data were collected. Three studies were randomized controlled trials investigating the effectiveness of smartphone-based monitoring and treatment, with 2 of these showing a positive treatment effect. In 2 randomized controlled trials, the researchers were blinded for randomization, but the participants were not blinded in any of the studies. All studies were determined to be at high risk of bias in several areas. CONCLUSIONS Smartphones hold great potential as a modern, widely available technology platform to help diagnose, monitor, and treat psychiatric disorders in children and adolescents. However, a higher level of homogeneity and rigor among studies regarding their methodology and reporting of adherence would facilitate future reviews and meta-analyses.

scholarly journals Psychiatric Manifestations of Coeliac Disease, a Systematic Review and Meta-Analysis

Nutrients ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 142 ◽  
Author(s):  
Emma Clappison ◽  
Marios Hadjivassiliou ◽  
Panagiotis Zis
Keyword(s):  
Systematic Review ◽  
Eating Disorders ◽  
Coeliac Disease ◽  
Psychiatric Disorders ◽  
Meta Analysis ◽  
Hyperactivity Disorder ◽  
Increased Risk ◽  
Meta Analyses ◽  
Psychiatric Manifestations ◽  
The Relationship

Background: Coeliac disease (CD) is increasingly prevalent and is associated with both gastrointestinal (GI) and extra-intestinal manifestations. Psychiatric disorders are amongst extra-intestinal manifestations proposed. The relationship between CD and such psychiatric disorders is not well recognised or understood. Aim: The aim of this systematic review and meta-analysis was to provide a greater understanding of the existing evidence and theories surrounding psychiatric manifestations of CD. Methodology: An online literature search using PubMed was conducted, the prevalence data for both CD and psychiatric disorders was extracted from eligible articles. Meta analyses on odds ratios were also performed. Results: A total of 37 articles were included in this review. A significant increase in risk was detected for autistic spectrum disorder (OR 1.53, 95% CI 1.24–1.88, p < 0.0001), attention deficit hyperactivity disorder (OR 1.39, 95% CI 1.18–1.63, p < 0.0001), depression (OR 2.17, 95% CI 2.17–11.15, p < 0.0001), anxiety (OR 6.03, 95% CI 2.22–16.35, p < 0.0001), and eating disorders (OR 1.62, 95% CI 1.37–1.91, p < 0.00001) amongst the CD population compared to healthy controls. No significant differences were found for bipolar disorder (OR 2.35, 95% CI 2.29–19.21, p = 0.43) or schizophrenia (OR 0.46, 95% CI 0.02–10.18, p = 0.62). Conclusion: CD is associated with an increased risk of depression, anxiety, eating disorders as well as ASD and ADHD. More research is required to investigate specific biological explanations as well as any effect of gluten free diet.

Distinct gene set in two different lineages of ammonia-oxidizing archaea supports the phylum Thaumarchaeota

2010 ◽  
Vol 18 (8) ◽  
pp. 331-340 ◽  
Author(s):  
Anja Spang ◽  
Roland Hatzenpichler ◽  
Céline Brochier-Armanet ◽  
Thomas Rattei ◽  
Patrick Tischler ◽  
...  
Keyword(s):  
Gene Set ◽  
Distinct Gene ◽  
Ammonia Oxidizing Archaea

scholarly journals TWAS pathway method greatly enhances the number of leads for uncovering the molecular underpinnings of psychiatric disorders

2018 ◽  
Author(s):  
Chris Chatzinakos ◽  
Donghyung Lee ◽  
Na Cai ◽  
Vladimir I. Vladimirov ◽  
Anna Docherty ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Computational Burden ◽  
Gene Sets ◽  
Genome Wide ◽  
Genetic Signal ◽  
Meta Analyses ◽  
Combine Information ◽  
Or Genes

ABSTRACTGenetic signal detection in genome-wide association studies (GWAS) is enhanced by pooling small signals from multiple Single Nucleotide Polymorphism (SNP), e.g. across genes and pathways. Because genes are believed to influence traits via gene expression, it is of interest to combine information from expression Quantitative Trait Loci (eQTLs) in a gene or genes in the same pathway. Such methods, widely referred as transcriptomic wide association analysis (TWAS), already exist for gene analysis. Due to the possibility of eliminating most of the confounding effect of linkage disequilibrium (LD) from TWAS gene statistics, pathway TWAS methods would be very useful in uncovering the true molecular bases of psychiatric disorders. However, such methods are not yet available for arbitrarily large pathways/gene sets. This is possibly due to it quadratic (in the number of SNPs) computational burden for computing LD across large regions. To overcome this obstacle, we propose JEPEGMIX2-P, a novel TWAS pathway method that i) has a linear computational burden, ii) uses a large and diverse reference panel (33K subjects), iii) is competitive (adjusts for background enrichment in gene TWAS statistics) and iv) is applicable as-is to ethnically mixed cohorts. To underline its potential for increasing the power to uncover genetic signals over the state-of-the-art and commonly used non-transcriptomics methods, e.g. MAGMA, we applied JEPEGMIX2-P to summary statistics of most large meta-analyses from Psychiatric Genetics Consortium (PGC). While our work is just the very first step toward clinical translation of psychiatric disorders, PGC anorexia results suggest a possible avenue for treatment.

scholarly journals Comprehensive exploration of the genetic contribution of the dopaminergic and serotonergic pathways to psychiatric disorders

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Judit Cabana-Domínguez ◽  
Bàrbara Torrico ◽  
Andreas Reif ◽  
Noèlia Fernàndez-Castillo ◽  
Bru Cormand
Keyword(s):  
Psychiatric Disorders ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Genetic Contribution ◽  
Obsessive Compulsive ◽  
Gene Set ◽  
Compulsive Disorder ◽  
Kegg Pathways ◽  
Gene Sets ◽  
Psychiatric Conditions

AbstractPsychiatric disorders are highly prevalent and display considerable clinical and genetic overlap. Dopaminergic and serotonergic neurotransmission have been shown to play an important role in many psychiatric disorders. Here we aim to assess the genetic contribution of these systems to eight psychiatric disorders (attention-deficit hyperactivity disorder (ADHD), anorexia nervosa (ANO), autism spectrum disorder (ASD), bipolar disorder (BIP), major depression (MD), obsessive-compulsive disorder (OCD), schizophrenia (SCZ) and Tourette’s syndrome (TS)) using publicly available GWAS analyses performed by the Psychiatric Genomics Consortium that include more than 160,000 cases and 275,000 controls. To do so, we elaborated four different gene sets: two ‘wide’ selections for dopamine (DA) and for serotonin (SERT) using the Gene Ontology and KEGG pathways tools, and two’core’ selections for the same systems, manually curated. At the gene level, we found 67 genes from the DA and/or SERT gene sets significantly associated with one of the studied disorders, and 12 of them were associated with two different disorders. Gene-set analysis revealed significant associations for ADHD and ASD with the wide DA gene set, for BIP with the wide SERT gene set, and for MD with the core SERT set. Interestingly, interrogation of a cross-disorder GWAS meta-analysis of the eight psychiatric conditions displayed association with the wide DA gene set. To our knowledge, this is the first systematic examination of genes encoding proteins essential to the function of these two neurotransmitter systems in these disorders. Our results support a pleiotropic contribution of the dopaminergic and serotonergic systems in several psychiatric conditions.

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