scholarly journals Association between polygenic propensity for psychiatric disorders and nutrient intake

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Avina K. Hunjan ◽  
Christopher Hübel ◽  
Yuhao Lin ◽  
Thalia C. Eley ◽  
Gerome Breen
Keyword(s):  
Psychiatric Disorders ◽  
Nutrient Intake ◽  
Autism Spectrum ◽  
Dietary Behaviour ◽  
Obsessive Compulsive ◽  
Higher Alcohol ◽  
Polygenic Score ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
Polygenic Scores

AbstractDespite the observed associations between psychiatric disorders and nutrient intake, genetic studies are limited. We examined whether polygenic scores for psychiatric disorders are associated with nutrient intake in UK Biobank (N = 163,619) using linear mixed models. We found polygenic scores for attention-deficit/hyperactivity disorder, bipolar disorder, and schizophrenia showed the highest number of associations, while a polygenic score for autism spectrum disorder showed no association. The relatively weaker obsessive-compulsive disorder polygenic score showed the greatest effect sizes suggesting its association with diet traits may become more apparent with larger genome-wide analyses. A higher alcohol dependence polygenic score was associated with higher alcohol intake and individuals with higher persistent thinness polygenic scores reported their food to weigh less, both independent of socioeconomic status. Our findings suggest that polygenic propensity for a psychiatric disorder is associated with dietary behaviour. Note, nutrient intake was self-reported and findings must therefore be interpreted mindfully.

scholarly journals Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders

2019 ◽  
Author(s):  
◽  
Phil H. Lee ◽  
Verneri Anttila ◽  
Hyejung Won ◽  
Yen-Chen A. Feng ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Pleiotropic Effects ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Hyperactivity Disorder ◽  
Genome Wide ◽  
Genomic Relationships ◽  
The Brain

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.

scholarly journals Association between polygenic propensity for a psychiatric disorder and nutrient intake

2021 ◽  
Author(s):  
Avina K. Hunjan ◽  
Christopher Hübel ◽  
Yuhao Lin ◽  
Thalia C. Eley ◽  
Gerome Breen
Keyword(s):  
Socioeconomic Status ◽  
Major Depressive Disorder ◽  
Anorexia Nervosa ◽  
Depressive Disorder ◽  
Psychiatric Disorders ◽  
Nutrient Intake ◽  
Major Depressive ◽  
Higher Alcohol ◽  
Polygenic Score ◽  
Polygenic Scores

AbstractBackgroundDespite the observed associations between psychiatric disorders and nutrient intake, genetic studies are limited.AimsWe examined whether polygenic scores for psychiatric disorders, including anorexia nervosa, major depressive disorder and schizophrenia, are associated with self-reported nutrient intake.MethodsWe used data obtained by the UK Biobank ‘Diet by 24-hour recall’ questionnaire (N=163,619). Association was assessed using linear mixed models for the analysis of data with repeated measures.ResultsWe find polygenic scores for psychiatric disorders are differentially associated with nutrient intake, with attention-deficit/hyperactivity disorder, bipolar disorder and schizophrenia showing the strongest associations, whilst autism spectrum disorder showed no association. Expressed as the effect of a one standard deviation higher polygenic score, anorexia nervosa polygenic score was associated with higher intake of fibre (0.06 g), folate (0.93 μg), iron (0.03 mg) and vitamin C (0.92 μg). Similarly, a higher major depressive disorder polygenic score was associated with 0.04 mg lower iron and 1.13 μg lower vitamin C intake per day, and a greater obsessive-compulsive disorder polygenic score with 0.06 g higher fibre intake. These associations were predominantly driven by socioeconomic status and educational attainment. However, a higher alcohol dependence polygenic score was associated with higher alcohol intake and individuals with higher persistent thinness polygenic scores reported their food to weigh 8.61 g less, both independent of socioeconomic status.ConclusionsOur findings suggest that polygenic propensity for a psychiatric disorder is associated with dietary behaviour. The nutrient intake is based on self-reported data and findings must therefore be interpreted mindfully.Declaration of interestNone.

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.

scholarly journals Genetic influences on eight psychiatric disorders based on family data of 4 408 646 full and half-siblings, and genetic data of 333 748 cases and controls

2018 ◽  
Vol 49 (07) ◽  
pp. 1166-1173 ◽  
Author(s):  
E. Pettersson ◽  
P. Lichtenstein ◽  
H. Larsson ◽  
J. Song ◽  
A. Agrawal ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Autism Spectrum ◽  
Psychiatric Research ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Hyperactivity Disorder ◽  
Unique Character ◽  
Psychiatric Conditions ◽  
Heritability Estimates ◽  
Study Designs

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.

scholarly journals Novel genome-wide associations for anhedonia, genetic correlation with psychiatric disorders, and polygenic association with brain structure

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Joey Ward ◽  
Laura M. Lyall ◽  
Richard A. I. Bethlehem ◽  
Amy Ferguson ◽  
Rona J. Strawbridge ◽  
...  
Keyword(s):  
White Matter ◽  
Psychiatric Disorders ◽  
Brain Structure ◽  
Genetic Correlations ◽  
Grey Matter Volume ◽  
Obsessive Compulsive ◽  
Major Depressive ◽  
Compulsive Disorder ◽  
Matter Volume ◽  
Genome Wide

AbstractAnhedonia is a core symptom of several psychiatric disorders but its biological underpinnings are poorly understood. We performed a genome-wide association study of state anhedonia in 375,275 UK Biobank participants and assessed for genetic correlation between anhedonia and neuropsychiatric conditions (major depressive disorder, schizophrenia, bipolar disorder, obsessive compulsive disorder and Parkinson’s Disease). We then used a polygenic risk score approach to test for association between genetic loading for anhedonia and both brain structure and brain function. This included: magnetic resonance imaging (MRI) assessments of total grey matter volume, white matter volume, cerebrospinal fluid volume, and 15 cortical/subcortical regions of interest; diffusion tensor imaging (DTI) measures of white matter tract integrity; and functional MRI activity during an emotion processing task. We identified 11 novel loci associated at genome-wide significance with anhedonia, with a SNP heritability estimate (h2SNP) of 5.6%. Strong positive genetic correlations were found between anhedonia and major depressive disorder, schizophrenia and bipolar disorder; but not with obsessive compulsive disorder or Parkinson’s Disease. Polygenic risk for anhedonia was associated with poorer brain white matter integrity, smaller total grey matter volume, and smaller volumes of brain regions linked to reward and pleasure processing, including orbito-frontal cortex. In summary, the identification of novel anhedonia-associated loci substantially expands our current understanding of the biological basis of state anhedonia and genetic correlations with several psychiatric disorders confirm the utility of this phenotype as a transdiagnostic marker of vulnerability to mental illness. We also provide the first evidence that genetic risk for state anhedonia influences brain structure, including in regions associated with reward and pleasure processing.

scholarly journals Genetic Association Study of Childhood Aggression across raters, instruments and age

2019 ◽  
Author(s):  
Hill F. Ip ◽  
Camiel M. van der Laan ◽  
Eva M. L. Krapohl ◽  
Isabell Brikell ◽  
Cristina Sánchez-Mora ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Genetic Correlations ◽  
Childhood Aggression ◽  
Age At First Birth ◽  
Nucleotide Polymorphisms ◽  
Obsessive Compulsive ◽  
Psychological Traits ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
Polygenic Scores

AbstractBackgroundHuman aggressive behavior (AGG) has a substantial genetic component. Here we present a large genome-wide association meta-analysis (GWAMA) of childhood AGG.MethodsWe analyzed assessments of AGG for a total of 328,935 observations from 87,485 children (aged 1.5 – 18 years), from multiple assessors, instruments, and ages, while accounting for sample overlap. We performed an overall analysis and meta-analyzed subsets of the data within rater, instrument, and age.ResultsHeritability based on the overall meta-analysis (AGGall) that could be attributed to Single Nucleotide Polymorphisms (SNPs) was 3.31% (SE=0.0038). No single SNP reached genome-wide significance, but gene-based analysis returned three significant genes: ST3GAL3 (P=1.6E-06), PCDH7 (P=2.0E-06) and IPO13 (P=2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children and in retrospectively assessed childhood aggression. We obtained moderate-to-strong genetic correlations (rg‘s) with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg|: 0.19 –.1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg =∼-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg|: 0.46 – 0.60). Genetic correlations between AGG and psychiatric disorders were strongest for mother- and self-reported AGG.ConclusionsThe current GWAMA of childhood aggression provides a powerful tool to interrogate the genetic etiology of AGG by creating individual polygenic scores and genetic correlations with psychiatric traits.

A-90 Personality Tests in Neuropsychological Assessment: Determining the Presence of Psychotic and Obsessive Compulsive Disorders in 3 Individuals with Autism Spectrum Disorder

2021 ◽  
Vol 36 (6) ◽  
pp. 1137-1137
Author(s):  
Kathleen Torsney
Keyword(s):  
Autism Spectrum Disorder ◽  
Psychiatric Disorders ◽  
Case Studies ◽  
Correct Diagnosis ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Future Research ◽  
Obsessive Compulsive ◽  
Personality Tests ◽  
Compulsive Disorder

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.

scholarly journals Novel genome-wide associations for anhedonia, genetic correlation with psychiatric disorders, and polygenic association with brain structure

2019 ◽  
Author(s):  
Joey Ward ◽  
Laura M. Lyall ◽  
Richard A. I. Bethlehem ◽  
Amy Ferguson ◽  
Rona J. Strawbridge ◽  
...  
Keyword(s):  
White Matter ◽  
Psychiatric Disorders ◽  
Brain Structure ◽  
Genetic Correlations ◽  
Grey Matter Volume ◽  
Obsessive Compulsive ◽  
Major Depressive ◽  
Compulsive Disorder ◽  
Matter Volume ◽  
Genome Wide

AbstractAnhedonia is a core feature of several psychiatric disorders but its biological underpinnings are poorly understood. We performed a genome-wide association study of anhedonia in 375,275 UK Biobank participants and assessed for genetic correlation between anhedonia and neuropsychiatric conditions (major depressive disorder, schizophrenia, bipolar disorder, obsessive compulsive disorder and Parkinson’s Disease). We then used a polygenic risk score approach to test for association between genetic loading for anhedonia and both brain structure and brain function. This included: magnetic resonance imaging (MRI) assessments of total grey matter volume, white matter volume, cerebrospinal fluid volume, and 15 cortical/subcortical regions of interest; diffusion tensor imaging (DTI) measures of white matter tract integrity; and functional MRI activity during an emotion processing task. We identified 11 novel loci associated at genome-wide significance with anhedonia, with a SNP heritability estimate (h2SNP) of 5.6%. Strong positive genetic correlations were found between anhedonia and major depressive disorder, schizophrenia and bipolar disorder; but not with obsessive compulsive disorder or Parkinson’s Disease. Polygenic risk for anhedonia was associated with poorer brain white matter integrity, smaller total grey matter volume, and smaller volumes of brain regions linked to reward and pleasure processing, including nucleus accumbens, caudate and medial frontal cortex. In summary, the identification of novel anhedonia-associated loci substantially expands our current understanding of the biological basis of anhedonia and genetic correlations with several psychiatric disorders confirm the utility of this trait as a transdiagnostic marker of vulnerability to mental illness. We also provide the first evidence that genetic risk for anhedonia influences brain structure, particularly in regions associated with reward and pleasure processing.

scholarly journals Genome-wide association study of suicide death and polygenic prediction of clinical antecedents

2017 ◽  
Author(s):  
Anna R. Docherty ◽  
Andrey A. Shabalin ◽  
Emily DiBlasi ◽  
Eric Monson ◽  
Niamh Mullins ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Case Control ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Behavioral Disinhibition ◽  
Suicide Death ◽  
Polygenic Score ◽  
Death Case ◽  
Genome Wide ◽  
Polygenic Scores

ABSTRACTObjectiveSuicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort.MethodsThe analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression.ResultsGWAS identified two genome-wide significant loci (6 SNPs, p<5×10−8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder.ConclusionsIn this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.

scholarly journals Brain structural abnormalities in six major psychiatric disorders: shared variation and network perspectives

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 356
Author(s):  
Euclides José de Mendonça Filho ◽  
Márcio Bonesso Alves ◽  
Patricia Pelufo Silveira
Keyword(s):  
Network Analysis ◽  
Psychiatric Disorders ◽  
Regional Distribution ◽  
Principal Component ◽  
Autism Spectrum ◽  
Brain Abnormalities ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Component Loading ◽  
Shared Variation

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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