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

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.

2020 ◽  
Author(s):  
Judit Cabana-Domínguez ◽  
Bàrbara Torrico ◽  
Andreas Reif ◽  
Noèlia Fernàndez-Castillo ◽  
Bru Cormand

ABSTRACTPsychiatric disorders are highly prevalent and display considerable clinical and genetic overlap. Dopaminergic and serotonergic neurotransmission have been shown to have an important role in many psychiatric disorders. Here we aim to assess the genetic contribution of these systems to eight psychiatric disorders (ADHD, ANO, ASD, BIP, MD, OCD, SCZ and TS) using publicly available GWAS analyses performed by the Psychiatric Genomics Consortium. To do so, we elaborated four different gene sets using the Gene Ontology and KEGG pathways tools: two ‘wide’ selections for dopamine (DA) and for serotonin (SERT), and two ‘core’ selections for the same systems. 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 both the core DA set and the core SERT set. Interestingly, interrogation of the cross-disorder GWAS meta-analysis displayed association with the wide DA gene set. To our knowledge, this is the first time that these two neurotransmitter systems have systematically been inspected in these disorders. Our results support a cross-disorder contribution of dopaminergic and serotonergic systems in several psychiatric conditions.


2018 ◽  
Vol 49 (07) ◽  
pp. 1166-1173 ◽  
Author(s):  
E. Pettersson ◽  
P. Lichtenstein ◽  
H. Larsson ◽  
J. Song ◽  
A. Agrawal ◽  
...  

AbstractBackgroundMost studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders.MethodsWe assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia.ResultsHeritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50.ConclusionsGiven the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.


2019 ◽  
Author(s):  
◽  
Phil H. Lee ◽  
Verneri Anttila ◽  
Hyejung Won ◽  
Yen-Chen A. Feng ◽  
...  

SummaryGenetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.


2016 ◽  
Vol 33 (S1) ◽  
pp. s225-s225 ◽  
Author(s):  
X. Sun ◽  
S.H.W. So ◽  
C. Zhu ◽  
P.W.L. Leung

IntroductionIt is assumed that dysfunctional meta-cognitive beliefs about one's thoughts increase problematic appraisals and coping behaviors, which further contribute to the development of mental disorders (Wells and Matthews, 1994; Wells, 2000). Although this research interest originated around generalized anxiety disorder (GAD), recent studies have begun to examine similar meta-cognitive processes in other disorders. The majority of studies using Meta-cognitions Questionnaire (MCQ; Cartwright-Hatton & Wells, 1997) and its variants to assess meta-cognitive beliefs.ObjectivesWe conducted a meta-analysis to integrate empirical findings on group differences in meta-cognitive beliefs between healthy individuals and patients with various psychiatric disorders.MethodsWe followed the PRISMA guideline (Liberati et al., 2009). A systematic literature search was conducted. We included studies that involved a diagnosed psychiatric group and healthy controls (aged 18 or above), reported group comparisons of metacognition, and were published during the period of 1990–27 August 2015. Effect sizes were computed.ResultsA final set of 43 studies was included. Large combined effect sizes were found on each subdomain of the MCQ, indicating increased levels of dysfunctional meta-cognitive beliefs in patients. Subgroup analyses were carried out based on psychiatric diagnosis (i.e. psychosis, n = 10; GAD, n = 7; obsessive-compulsive disorder, OCD, n = 15; anorexia nervosa, n = 5). All patient groups were more dysfunctional on each subtype of meta-cognitive beliefs than controls. Effect size of U/D was particularly large for GAD, and that of CSC was particularly large for OCD.ConclusionsDysfunctional meta-cognitive beliefs are evident across several psychiatric disorders, with specific types of beliefs being more marked in certain diagnoses.Disclosure of interestThe authors have not supplied their declaration of competing interest.


2021 ◽  
Author(s):  
Bo-yong Park ◽  
Valeria Kebets ◽  
Sara Lariviere ◽  
Meike D. Hettwer ◽  
Casey Paquola ◽  
...  

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we assessed i) shared dimensions of alterations in cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression, obsessive-compulsive disorder, bipolar disorder, schizophrenia) and ii) carried out a multiscale neural contextualization, by cross-referencing shared anomalies against cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we computed a shared disease dimension on cortical morphology using principal component analysis that described a sensory-fugal pattern with paralimbic regions showing the most consistent abnormalities across conditions. The shared disease dimension was closely related to cortical gradients of microstructure and intrinsic connectivity, as well as neurotransmitter systems, specifically serotonin and dopamine. Our findings embed the shared effects of major psychiatric conditions on brain structure in multiple scales of brain organization and may provide novel insights into neural mechanisms into transdiagnostic vulnerability.


2019 ◽  
Author(s):  
William R. Reay ◽  
Murray J. Cairns

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.


2021 ◽  
Vol 36 (6) ◽  
pp. 1137-1137
Author(s):  
Kathleen Torsney

Abstract Objective The assessment of personality and psychopathology in an individual who has symptoms of autism spectrum disorder (ASD) can be a challenging task due to the overlap of characteristic behaviors associated with ASD and markers of psychopathology. Through the examination of key factors in 3 case studies of neuropsychological assessments, this poster outlines steps to facilitate the correct diagnosis of psychiatric disorders in persons with autism spectrum disorder. Method This poster explores 3 case studies in which an individual exhibited signs of a psychiatric disorder as well as ASD. The author describes how the personality tests such as the MMPI-2 and MMPI-RF were administered and interpreted and how case history and test taking behavior affected the understanding of the results. Results The poster highlights critical factors in differentiating psychiatric disorders and symptoms that are part of the ASD. For example, in all 3 case studies, the individuals had significant difficulty with the computerized version of the test and needed to take it with paper and pencil. The author also outlines examples where the symptoms are manifestations of the ASD, such as perseveration and rigid thinking and when they are attributable to an obsessive–compulsive disorder. Further, the author differentiates signs of psychosis in a person with ASD from the typical tangential and circumstantial speech associated with ASD. Conclusion The author offers suggestions for administering personality tests to persons with ASD, for interpreting the results of the tests, and for conducting future research to facilitate the differentiation between symptoms consistent with ASD and with psychopathology.


2018 ◽  
pp. 91-118
Author(s):  
Jie Lisa Ji ◽  
Alan Anticevic

sSince its introduction to clinical research, functional magnetic resonance imaging (fMRI) has had a pivotal role in understanding the systems-level neural substrates of psychiatric disorders. fMRI is a powerful tool for the field of psychiatry because it is well suited to studying large-scale neural systems and distributed neuropathology, which are thought to underlie many of the behavioral symptoms in psychiatric conditions. This chapter highlights key fMRI findings in four major types of psychiatric disorders: schizophrenia, mood disorders (including major depressive disorder and bipolar disorder), obsessive-compulsive disorder, and posttraumatic stress disorder.


Author(s):  
M. Pilar Trelles ◽  
Paige M. Siper ◽  
Dorothy E. Grice

Many psychiatric disorders of childhood have a chronic course. As such, they impact multiple developmental epochs and negatively influence developmental trajectories. While early identification and intervention may minimize, or even prevent, symptoms being carried into adulthood, the availability of evidence-based treatments is sparse in children and adolescents compared to adult populations. Establishing effective interventions for psychiatric symptoms presenting in childhood is critical given the chronic course of most psychiatric disorders. This chapter describes psychopharmacological and psychosocial interventions used for the treatment of childhood psychiatric conditions, with an emphasis on empirically supported treatments. Both symptom- and diagnosis-specific approaches are described as well as the use of combined interventions for the following childhood psychiatric conditions: autism spectrum disorder (ASD), intellectual disability (ID), attention-deficit/hyperactivity disorder (ADHD), anxiety, depression, obsessive compulsive disorder (OCD), chronic tic disorders, eating disorders, and conduct problems.


F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 356
Author(s):  
Euclides José de Mendonça Filho ◽  
Márcio Bonesso Alves ◽  
Patricia Pelufo Silveira

Common brain abnormalities are a possible explanation for comorbidities in psychiatric disorders. Challenges in understanding these conditions are likely due to the paucity of studies able to analyze the extent and regional distribution of shared morphometric abnormalities between disorders. Recently, Opeal et al. presented an elegant rationale to investigate shared and specific morphometric measures of cortical thickness and subcortical gray matter volume between healthy individuals and subjects across six major psychiatric disorders. Although their approach has the potential to systematically portrait shared brain alterations, the chosen principal component analysis solution may not address the central question of the observed shared versus specific brain alterations due to misspecification of the number of components. Given how this misspecification can lead to different conclusions, we reanalyzed Opel et al. data to thoroughly determine the number of factors to be considered, explore the alternative solution, and visualize the patterns of shared brain matter correlations using network analysis. Our approach suggests that a unidimensional solution was appropriate in this situation. The unidimensional solution indicated that brain alterations in autism spectrum disorder (ASD) had a significant negative component loading, suggesting that brain abnormalities found in ASD carry more similarities with major depressive disorder (MDD), bipolar disorder (BD), schizophrenia (SCZ), and obsessive-compulsive disorder (OCD) than demonstrated by the original work. Network analysis indicated that SCZ had the highest strength, BD the highest closeness, and BD and MDD had the highest betweenness in the network. This work highlights how different component solutions can lead to different conclusions, with important implications for the understanding of overlapped patterns of symptoms among six major psychiatric diseases. The network approach is complementary in indicating central markers of specific psychopathology domains. Investigations using shared-variation and network perspectives are promising for the study of pathophysiological patterns of common brain alterations.


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