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 ◽  
...  

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.

2020 ◽  
Author(s):  
Claudia Modenato ◽  
Kuldeep Kumar ◽  
Clara Moreau ◽  
Sandra Martin-Brevet ◽  
Guillaume Huguet ◽  
...  

AbstractBackgroundCopy Number Variants (CNVs) associated with autism and schizophrenia have large effects on brain anatomy. Yet, neuroimaging studies have been conducted one mutation at a time. We hypothesize that neuropsychiatric CNVs may exert general effects on brain morphometry because they confer risk for overlapping psychiatric conditions.MethodsWe analyzed T1-weighted MRIs and characterized shared patterns on brain anatomy across 8 neuropsychiatric CNVs. Clinically ascertained samples included 1q21.1 (n=48), 16p11.2 (n=156), or 22q11.2 (n=96) and 331 non-carriers. Non-clinically ascertained samples from the UK Biobank included 1q21.1 (n=19), 16p11.2 (n=8), 22q11.2 (n=9), 15q11.2 (n=148) and 965 non-carriers. Canonical correlation analysis (CCA) and univariate models were used to interrogate brain morphometry changes across 8 CNVs.ResultsEight CNVs affect regional brain volumes along two main gene-morphometry dimensions identified by CCA. While fronto-temporal regions contributed to dimension 1, dimension 2 was driven by subcortical, parietal and occipital regions. Consistently, voxel-wise whole-brain analyses identified the same regions involved in patterns of alteration present across the 4 deletions and duplications. These neuroanatomical patterns are similar to those observed in cross-psychiatric disorder meta-analyses. Deletions and duplications at all 4 loci show mirror effects at either the global and/or the regional level.ConclusionNeuropsychiatric CNVs share neuroanatomical signatures characterized by a parsimonious set of brain dimensions. The latter may underlie the risk conferred by CNVs for a similar spectrum of neuropsychiatric conditions.


2019 ◽  
Vol 29 ◽  
pp. S196-S197
Author(s):  
Claudia Modenato ◽  
Kuldeep Kumar ◽  
Clara Moreau ◽  
Eloi Gagnon ◽  
Catherine Schramm ◽  
...  

2019 ◽  
Vol 29 ◽  
pp. S441-S442
Author(s):  
C. Modenato ◽  
A. Pain ◽  
S. Martin-Brevet ◽  
A. Maillard ◽  
B. Rodriguez-Herreros ◽  
...  

2020 ◽  
pp. 1-8
Author(s):  
Xavier Caseras ◽  
George Kirov ◽  
Kimberley M. Kendall ◽  
Elliott Rees ◽  
Sophie E. Legge ◽  
...  

Background Schizophrenia is a highly heritable disorder with undetermined neurobiological causes. Understanding the impact on brain anatomy of carrying genetic risk for the disorder will contribute to uncovering its neurobiological underpinnings. Aims To examine the effect of rare copy number variants (CNVs) associated with schizophrenia on brain cortical anatomy in a sample of unaffected participants from the UK Biobank. Method We used regression analyses to compare cortical thickness and surface area (total and across gyri) between 120 unaffected carriers of rare CNVs associated with schizophrenia and 16 670 participants without any pathogenic CNV. A measure of cortical thickness and surface area covariance across gyri was also compared between groups. Results Carrier status was associated with reduced surface area (β = −0.020 mm2, P < 0.001) and less robustly with increased cortical thickness (β = 0.015 mm, P = 0.035), and with increased covariance in thickness (carriers z = 0.31 v. non-carriers z = 0.22, P < 0.0005). Associations were mainly present in frontal and parietal areas and driven by a limited number of rare risk alleles included in our analyses (mainly 15q11.2 deletion for surface area and 16p13.11 duplication for thickness covariance). Conclusions Results for surface area conformed with previous clinical findings, supporting surface area reductions as an indicator of genetic liability for schizophrenia. Results for cortical thickness, though, argued against its validity as a potential risk marker. Increased structural thickness covariance across gyri also appears related to risk for schizophrenia. The heterogeneity found across the effects of rare risk alleles suggests potential different neurobiological gateways into schizophrenia's phenotype.


2019 ◽  
Vol 1 (1) ◽  
pp. 6-12
Author(s):  
Fatima Javeria ◽  
Shazma Altaf ◽  
Alishah Zair ◽  
Rana Khalid Iqbal

Schizophrenia is a severe mental disease. The word schizophrenia literally means split mind. There are three major categories of symptoms which include positive, negative and cognitive symptoms. The disease is characterized by symptoms of hallucination, delusions, disorganized thinking and speech. Schizophrenia is related to many other mental and psychological problems like suicide, depression, hallucinations. Including these, it is also a problem for the patient’s family and the caregiver. There is no clear reason for the disease, but with the advances in molecular genetics; certain epigenetic mechanisms are involved in the pathophysiology of the disease. Epigenetic mechanisms that are mainly involved are the DNA methylation, copy number variants. With the advent of GWAS, a wide range of SNPs is found linked with the etiology of schizophrenia. These SNPs serve as ‘hubs’; because these all are integrating with each other in causing of schizophrenia risk. Until recently, there is no treatment available to cure the disease; but anti-psychotics can reduce the disease risk by minimizing its symptoms. Dopamine, serotonin, gamma-aminobutyric acid, are the neurotransmitters which serve as drug targets in the treatment of schizophrenia. Due to the involvement of genetic and epigenetic mechanisms, drugs available are already targeting certain genes involved in the etiology of the disease.


2020 ◽  
Author(s):  
◽  
Evelina Siavrienė

A Molecular and Functional Evaluation of Coding and Non-Coding Genome Sequence Variants and Copy Number Variants


2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 146-146
Author(s):  
D. M. Bickhart ◽  
L. Xu ◽  
J. L. Hutchison ◽  
J. B. Cole ◽  
D. J. Null ◽  
...  

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