scholarly journals Atlas of functional connectivity relationships across rare and common genetic variants, traits, and psychiatric conditions

2021 ◽  
Author(s):  
Clara A Moreau ◽  
Kuldeep Kumar ◽  
Annabelle Harvey ◽  
Guillaume Huguet ◽  
Sebastian Urchs ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Large Scale ◽  
Brain Connectivity ◽  
Copy Number Variants ◽  
Effect Sizes ◽  
Genomic Variants ◽  
Common Genetic Variants ◽  
Polygenic Scores ◽  
Genetic Risks ◽  
Psychiatric Conditions

Polygenicity and pleiotropy are key properties of the genomic architecture of psychiatric disorders. An optimistic interpretation of polygenicity is that genomic variants converge on a limited set of mechanisms at some level from genes to behavior. Alternatively, convergence may be minimal or absent. We took advantage of brain connectivity, measured by resting-state functional MRI (rs-fMRI), as well as rare and common genomic variants to understand the effects of polygenicity and pleiotropy on large-scale brain networks, a distal step from genes to behavior. We processed ten rs-fMRI datasets including 32,988 individuals, to examine connectome-wide effects of 16 copy number variants (CNVs), 10 polygenic scores, 6 cognitive and brain morphometry traits, and 4 idiopathic psychiatric conditions. Although effect sizes of CNVs on connectivity were correlated to cognition and number of genes, increasing polygenicity was associated with decreasing effect sizes on connectivity. Accordingly, the effect sizes of polygenic scores on connectivity were 6-fold lower compared to CNVs. Despite this heterogeneity of connectivity profiles, multivariate analysis identified convergence of genetic risks and psychiatric disorders on the thalamus and the somatomotor network. Based on spatial correlations with transcriptomic data, we hypothesize that excitatory thalamic neurons may be primary contributors to brain alteration profiles shared across genetic risks and conditions. Finally, pleiotropy measured by genetic and transcriptomic correlations between 38 pairs of conditions/traits showed significant concordance with connectomic correlations, suggesting a substantial causal genetic component for shared connectivity. Such findings open avenues to delineate general mechanisms - amenable to intervention - across conditions and genetic risks.

scholarly journals The general impact of haploinsufficiency on brain connectivity underlies the pleiotropic effect of neuropsychiatric CNVs

2020 ◽  
Author(s):  
Clara Moreau ◽  
Guillaume Huguet ◽  
Sebastian Urchs ◽  
Elise Douard ◽  
Hanad Sharmarke ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Copy Number Variants ◽  
Neuropsychiatric Disorders ◽  
Pleiotropic Effect ◽  
Autism Spectrum ◽  
Hyperactivity Disorder ◽  
Severity Scores ◽  
Psychiatric Conditions ◽  
The Mean ◽  
Neutral Effect

AbstractCopy number variants (CNVs) are among the most highly penetrant genetic risk factors for neuropsychiatric disorders. Their impact on brain connectivity remains mostly unstudied. Because they confer risk for overlapping conditions, we hypothesized that they may converge on shared connectivity patterns.We performed connectome-wide analyses using resting-state functional MRI data from 436 carriers of neuropsychiatric CNVs at the 1q21.1, 15q11.2, 16p11.2, 22q11.2 loci, 4 “neutral effect” CNVs, 66 carriers of scarcer neuropsychiatric CNVs, 756 individuals with idiopathic autism spectrum disorder (ASD), schizophrenia, attention deficit hyperactivity disorder, and 5,377 controls. Neuropsychiatric CNVs showed global shifts of mean connectivity. The effect size of CNVs on relative connectivity (adjusted for the mean) was correlated with the known level of neuropsychiatric risk conferred by CNVs. Individuals with idiopathic schizophrenia and ASD had similarities in connectivity with neuropsychiatric CNVs. We reported a linear relationship between connectivity and intolerance to haploinsufficiency measured for all genes encompassed by CNVs across 18 loci. This profile involved the thalamus, the basal ganglia, somatomotor and frontoparietal networks and was correlated with lower general intelligence and higher autism severity scores. An exploratory factor analysis confirmed the contribution of these regions to three latent components shared across CNVs and neuropsychiatric disorders.We posit that deleting genes intolerant to haploinsufficiency reorganize connectivity along general dimensions irrespective of where deletions occur in the genome. This haploinsufficiency brain signature opens new avenues to understand polygenicity in psychiatric conditions and the pleiotropic effect of CNVs on cognition and risk for neuropsychiatric disorders.One sentence summaryNeuropsychiatric CNVs across the genome reorganize brain connectivity architecture along dominant patterns contributing to complex idiopathic conditions.

Functional MRI in Psychiatric Disorders

2018 ◽  
pp. 91-118
Author(s):  
Jie Lisa Ji ◽  
Alan Anticevic
Keyword(s):  
Magnetic Resonance Imaging ◽  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Large Scale ◽  
Neural Substrates ◽  
Behavioral Symptoms ◽  
Neural Systems ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Psychiatric Conditions

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.

Shared genetic etiology between anxiety disorders and psychiatric and related intermediate phenotypes

2019 ◽  
Vol 50 (4) ◽  
pp. 692-704 ◽  
Author(s):  
Kazutaka Ohi ◽  
Takeshi Otowa ◽  
Mihoko Shimada ◽  
Tsukasa Sasaki ◽  
Hisashi Tanii
Keyword(s):  
Anxiety Disorders ◽  
Psychiatric Disorders ◽  
Genetic Variants ◽  
Large Scale ◽  
Genetic Correlations ◽  
Well Being ◽  
Subjective Well Being ◽  
Intermediate Phenotypes ◽  
Genome Wide ◽  
Common Genetic Variants

AbstractBackgroundPsychiatric disorders and related intermediate phenotypes are highly heritable and have a complex, overlapping polygenic architecture. A large-scale genome-wide association study (GWAS) of anxiety disorders identified genetic variants that are significant on a genome-wide. The current study investigated the genetic etiological overlaps between anxiety disorders and frequently cooccurring psychiatric disorders and intermediate phenotypes.MethodsUsing case–control and factor score models, we investigated the genetic correlations of anxiety disorders with eight psychiatric disorders and intermediate phenotypes [the volumes of seven subcortical brain regions, childhood cognition, general cognitive ability and personality traits (subjective well-being, loneliness, neuroticism and extraversion)] from large-scale GWASs (n= 7556–298 420) by linkage disequilibrium score regression.ResultsAmong psychiatric disorders, the risk of anxiety disorders was positively genetically correlated with the risks of major depressive disorder (MDD) (rg± standard error = 0.83 ± 0.16,p= 1.97 × 10−7), schizophrenia (SCZ) (0.28 ± 0.09,p= 1.10 × 10−3) and attention-deficit/hyperactivity disorder (ADHD) (0.34 ± 0.13,p= 8.40 × 10−3). Among intermediate phenotypes, significant genetic correlations existed between the risk of anxiety disorders and neuroticism (0.81 ± 0.17,p= 1.30 × 10−6), subjective well-being (−0.73 ± 0.18,p= 4.89 × 10−5), general cognitive ability (−0.23 ± 0.08,p= 4.70 × 10−3) and putamen volume (−0.50 ± 0.18,p= 5.00 × 10−3). No other significant genetic correlations between anxiety disorders and psychiatric or intermediate phenotypes were observed (p> 0.05). The case–control model yielded stronger genetic effect sizes than the factor score model.ConclusionsOur findings suggest that common genetic variants underlying the risk of anxiety disorders contribute to elevated risks of MDD, SCZ, ADHD and neuroticism and reduced quality of life, putamen volume and cognitive performance. We suggest that the comorbidity of anxiety disorders is partly explained by common genetic variants.

0306 Exploring the feasibility of using copy number variants as genetic markers through large-scale whole genome sequencing experiments

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 146-146
Author(s):  
D. M. Bickhart ◽  
L. Xu ◽  
J. L. Hutchison ◽  
J. B. Cole ◽  
D. J. Null ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genetic Markers ◽  
Genome Sequencing ◽  
Copy Number ◽  
Large Scale ◽  
Copy Number Variants ◽  
Whole Genome

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

scholarly journals Large-scale study of Toxoplasma and Cytomegalovirus shows an association between infection and serious psychiatric disorders

2019 ◽  
Vol 79 ◽  
pp. 152-158 ◽  
Author(s):  
Kristoffer Sølvsten Burgdorf ◽  
Betina B. Trabjerg ◽  
Marianne Giørtz Pedersen ◽  
Janna Nissen ◽  
Karina Banasik ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Large Scale ◽  
Large Scale Study

scholarly journals Psychiatric disorders in China: strengths and challenges of contemporary research and clinical services

2021 ◽  
pp. 1-14
Author(s):  
Xiao Chang ◽  
Qiyong Gong ◽  
Chunbo Li ◽  
Weihua Yue ◽  
Xin Yu ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Disease Burden ◽  
Large Scale ◽  
Well Being ◽  
Research Quality ◽  
Psychiatric Research ◽  
Clinical Services ◽  
Contributing Factors ◽  
Brain Functions ◽  
Neuroscience Research

Abstract China accounts for 17% of the global disease burden attributable to mental, neurological and substance use disorders. As a country undergoing profound societal change, China faces growing challenges to reduce the disease burden caused by psychiatric disorders. In this review, we aim to present an overview of progress in neuroscience research and clinical services for psychiatric disorders in China during the past three decades, analysing contributing factors and potential challenges to the field development. We first review studies in the epidemiological, genetic and neuroimaging fields as examples to illustrate a growing contribution of studies from China to the neuroscience research. Next, we introduce large-scale, open-access imaging genetic cohorts and recently initiated brain banks in China as platforms to study healthy brain functions and brain disorders. Then, we show progress in clinical services, including an integration of hospital and community-based healthcare systems and early intervention schemes. We finally discuss opportunities and existing challenges: achievements in research and clinical services are indispensable to the growing funding investment and continued engagement in international collaborations. The unique aspect of traditional Chinese medicine may provide insights to develop a novel treatment for psychiatric disorders. Yet obstacles still remain to promote research quality and to provide ubiquitous clinical services to vulnerable populations. Taken together, we expect to see a sustained advancement in psychiatric research and healthcare system in China. These achievements will contribute to the global efforts to realize good physical, mental and social well-being for all individuals.

scholarly journals Nebula: ultra-efficient mapping-free structural variant genotyper

2021 ◽  
Author(s):  
Parsoa Khorsand ◽  
Fereydoun Hormozdiari
Keyword(s):  
Large Scale ◽  
Structural Variants ◽  
Sequencing Technologies ◽  
Generic Framework ◽  
Common Genetic Variants ◽  
Order Of Magnitude ◽  
Complex Events ◽  
Comparable Accuracy ◽  
Using Data ◽  
Computational Resources

Abstract Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at https://github.com/Parsoa/Nebula.

scholarly journals Effects of eight neuropsychiatric copy number variants on human brain structure

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Claudia Modenato ◽  
Kuldeep Kumar ◽  
Clara Moreau ◽  
Sandra Martin-Brevet ◽  
Guillaume Huguet ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Principal Component ◽  
Brain Morphology ◽  
Brain Anatomy ◽  
Brain Morphometry ◽  
Supplementary Motor Cortex ◽  
Psychiatric Conditions ◽  
Latent Dimension ◽  
Mirror Effects

AbstractMany copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions.

scholarly journals A large-scale investigation into the role of classical HLA loci in multiple types of severe infections, with a focus on overlaps with autoimmune and mental disorders

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Ron Nudel ◽  
Rosa Lundbye Allesøe ◽  
Wesley K. Thompson ◽  
Thomas Werge ◽  
Simon Rasmussen ◽  
...  
Keyword(s):  
Autoimmune Disease ◽  
Psychiatric Disorders ◽  
Large Scale ◽  
Viral Infections ◽  
Human Leukocyte ◽  
Severe Infection ◽  
Small Sample ◽  
Disease Etiology ◽  
Hla Alleles ◽  
Severe Infections

Abstract Background Infections are a major disease burden worldwide. While they are caused by external pathogens, host genetics also plays a part in susceptibility to infections. Past studies have reported diverse associations between human leukocyte antigen (HLA) alleles and infections, but many were limited by small sample sizes and/or focused on only one infection. Methods We performed an immunogenetic association study examining 13 categories of severe infection (bacterial, viral, central nervous system, gastrointestinal, genital, hepatitis, otitis, pregnancy-related, respiratory, sepsis, skin infection, urological and other infections), as well as a phenotype for having any infection, and seven classical HLA loci (HLA-A, B, C, DPB1, DQA1, DQB1 and DRB1). Additionally, we examined associations between infections and specific alleles highlighted in our previous studies of psychiatric disorders and autoimmune disease, as these conditions are known to be linked to infections. Results Associations between HLA loci and infections were generally not strong. Highlighted associations included associations between DQB1*0302 and DQB1*0604 and viral infections (P = 0.002835 and P = 0.014332, respectively), DQB1*0503 and sepsis (P = 0.006053), and DQA1*0301 with “other” infections (a category which includes infections not included in our main categories e.g. protozoan infections) (P = 0.000369). Some HLA alleles implicated in autoimmune diseases showed association with susceptibility to infections, but the latter associations were generally weaker, or with opposite trends (in the case of HLA-C alleles, but not with alleles of HLA class II genes). HLA alleles associated with psychiatric disorders did not show association with susceptibility to infections. Conclusions Our results suggest that classical HLA alleles do not play a large role in the etiology of severe infections. The discordant association trends with autoimmune disease for some alleles could contribute to mechanistic theories of disease etiology.

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