M57 THE IMPACT OF COPY NUMBER VARIANTS ON BRAIN MORPHOMETRY

AbstractCopy number variants (CNVs) are associated with syndromic and severe neurological and psychiatric disorders (SNPDs), such as intellectual disability, epilepsy, schizophrenia, and bipolar disorder. Although considered high-impact, CNVs are also observed in the general population. This presents a diagnostic challenge in evaluating their clinical significance. To estimate the phenotypic differences between CNV carriers and non-carriers regarding general health and well-being, we compared the impact of SNPD-associated CNVs on health, cognition, and socioeconomic phenotypes to the impact of three genome-wide polygenic risk score (PRS) in two Finnish cohorts (FINRISK, n = 23,053 and NFBC1966, n = 4895). The focus was on CNV carriers and PRS extremes who do not have an SNPD diagnosis. We identified high-risk CNVs (DECIPHER CNVs, risk gene deletions, or large [>1 Mb] CNVs) in 744 study participants (2.66%), 36 (4.8%) of whom had a diagnosed SNPD. In the remaining 708 unaffected carriers, we observed lower educational attainment (EA; OR = 0.77 [95% CI 0.66–0.89]) and lower household income (OR = 0.77 [0.66–0.89]). Income-associated CNVs also lowered household income (OR = 0.50 [0.38–0.66]), and CNVs with medical consequences lowered subjective health (OR = 0.48 [0.32–0.72]). The impact of PRSs was broader. At the lowest extreme of PRS for EA, we observed lower EA (OR = 0.31 [0.26–0.37]), lower-income (OR = 0.66 [0.57–0.77]), lower subjective health (OR = 0.72 [0.61–0.83]), and increased mortality (Cox’s HR = 1.55 [1.21–1.98]). PRS for intelligence had a similar impact, whereas PRS for schizophrenia did not affect these traits. We conclude that the majority of working-age individuals carrying high-risk CNVs without SNPD diagnosis have a modest impact on morbidity and mortality, as well as the limited impact on income and educational attainment, compared to individuals at the extreme end of common genetic variation. Our findings highlight that the contribution of traditional high-risk variants such as CNVs should be analyzed in a broader genetic context, rather than evaluated in isolation.

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Effects of eight neuropsychiatric copy number variants on human brain structure

Translational Psychiatry ◽

10.1038/s41398-021-01490-9 ◽

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.

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Genotype-Phenotype correlation in Dravet Syndrome with SCN1A mutation increase efficiency of molecular diagnosis

Journal of Epilepsy and Clinical Neurophysiology ◽

10.1590/s1676-26492012000200009 ◽

2012 ◽

Vol 18 (2) ◽

pp. 60-62

Author(s):

MC Gonsales ◽

P Preto ◽

MA Montenegro ◽

MM Guerreiro ◽

I Lopes-Cendes

Keyword(s):

Protein Function ◽

Copy Number ◽

Mutation Screening ◽

Copy Number Variants ◽

Febrile Seizures ◽

Copy Number Variations ◽

Dravet Syndrome ◽

Missense Mutations ◽

The Impact ◽

Doose Syndrome

OBJECTIVES: The purpose of this study was to advance the knowledge on the clinical use of SCN1A testing for severe epilepsies within the spectrum of generalized epilepsy with febrile seizures plus by performing genetic screening in patients with Dravet and Doose syndromes and establishing genotype-phenotype correlations. METHODS: Mutation screening in SCN1A was performed in 15 patients with Dravet syndrome and 13 with Doose syndrome. Eight prediction algorithms were used to analyze the impact of the mutations in putative protein function. Furthermore, all SCN1A mutations previously published were compiled and analyzed. In addition, Multiplex Ligation-Dependent Probe Amplification (MLPA) technique was used to detect possible copy number variations within SCN1A. RESULTS: Twelve mutations were identified in patients with Dravet syndrome, while patients with Doose syndrome showed no mutations. Our results show that the most common type of mutation found is missense, and that they are mostly located in the pore region and the N- and C-terminal of the protein. No copy number variants in SCN1A were identified in our cohort. CONCLUSIONS: SCN1A testing is clinically useful for patients with Dravet syndrome, but not for those with Doose syndrome, since both syndromes do not seem to share the same genetic basis. Our results indicate that indeed missense mutations can cause severe phenotypes depending on its location and the type of amino-acid substitution. Moreover, our strategy for predicting deleterious effect of mutations using multiple computation algorithms was efficient for most of the mutations identified.

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Neuropsychiatric copy number variants exert shared effects on human brain structure

10.1101/2020.04.15.20056531 ◽

2020 ◽

Author(s):

Claudia Modenato ◽

Kuldeep Kumar ◽

Clara Moreau ◽

Sandra Martin-Brevet ◽

Guillaume Huguet ◽

...

Keyword(s):

Copy Number ◽

Copy Number Variants ◽

Brain Anatomy ◽

Brain Volumes ◽

Brain Morphometry ◽

Main Gene ◽

Psychiatric Conditions ◽

Mirror Effects ◽

The Uk ◽

Meta Analyses

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.

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Whole‐genome re‐sequencing reveals the impact of the interaction of copy number variants of the rhg1 and Rhg4 genes on broad‐based resistance to soybean cyst nematode

Plant Biotechnology Journal ◽

10.1111/pbi.13086 ◽

2019 ◽

Vol 17 (8) ◽

pp. 1595-1611 ◽

Cited By ~ 19

Author(s):

Gunvant B. Patil ◽

Naoufal Lakhssassi ◽

Jinrong Wan ◽

Li Song ◽

Zhou Zhou ◽

...

Keyword(s):

Copy Number ◽

Soybean Cyst Nematode ◽

Copy Number Variants ◽

Cyst Nematode ◽

Whole Genome ◽

The Impact

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Copy Number Variants Account for a Tiny Fraction of Undiagnosed Myopathic Patients

Genes ◽

10.3390/genes9110524 ◽

2018 ◽

Vol 9 (11) ◽

pp. 524 ◽

Cited By ~ 2

Author(s):

Teresa Giugliano ◽

Marco Savarese ◽

Arcomaria Garofalo ◽

Esther Picillo ◽

Chiara Fiorillo ◽

...

Keyword(s):

Copy Number ◽

Neuromuscular Disorders ◽

Copy Number Variants ◽

Dystrophin Gene ◽

Muscle Disease ◽

Comparative Genomic ◽

Disease Genes ◽

Inherited Disease ◽

Multicenter Cohort Study ◽

The Impact

Next-generation sequencing (NGS) technologies have led to an increase in the diagnosis of heterogeneous genetic conditions. However, over 50% of patients with a genetically inherited disease are still without a diagnosis. In these cases, different hypotheses are usually postulated, including variants in novel genes or elusive mutations. Although the impact of copy number variants (CNVs) in neuromuscular disorders has been largely ignored to date, missed CNVs are predicted to have a major role in disease causation as some very large genes, such as the dystrophin gene, have prone-to-deletion regions. Since muscle tissues express several large disease genes, the presence of elusive CNVs needs to be comprehensively assessed following an accurate and systematic approach. In this multicenter cohort study, we analyzed 234 undiagnosed myopathy patients using a custom array comparative genomic hybridization (CGH) that covers all muscle disease genes at high resolution. Twenty-two patients (9.4%) showed non-polymorphic CNVs. In 12 patients (5.1%), the identified CNVs were considered responsible for the observed phenotype. An additional ten patients (4.3%) presented candidate CNVs not yet proven to be causative. Our study indicates that deletions and duplications may account for 5–9% of genetically unsolved patients. This strongly suggests that other mechanisms of disease are yet to be discovered.

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MONTAGE: a new tool for high-throughput detection of mosaic copy number variation

BMC Genomics ◽

10.1186/s12864-021-07395-7 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Joseph T. Glessner ◽

Xiao Chang ◽

Yichuan Liu ◽

Jin Li ◽

Munir Khan ◽

...

Keyword(s):

Copy Number Variation ◽

High Throughput ◽

Copy Number ◽

Copy Number Variants ◽

Cell Types ◽

Disease Phenotype ◽

Multiple Phenotypes ◽

Genome Wide ◽

Number Variation ◽

The Impact

Abstract Background Not all cells in a given individual are identical in their genomic makeup. Mosaicism describes such a phenomenon where a mixture of genotypic states in certain genomic segments exists within the same individual. Mosaicism is a prevalent and impactful class of non-integer state copy number variation (CNV). Mosaicism implies that certain cell types or subset of cells contain a CNV in a segment of the genome while other cells in the same individual do not. Several studies have investigated the impact of mosaicism in single patients or small cohorts but no comprehensive scan of mosaic CNVs has been undertaken to accurately detect such variants and interpret their impact on human health and disease. Results We developed a tool called Montage to improve the accuracy of detection of mosaic copy number variants in a high throughput fashion. Montage directly interfaces with ParseCNV2 algorithm to establish disease phenotype genome-wide association and determine which genomic ranges had more or less than expected frequency of mosaic events. We screened for mosaic events in over 350,000 samples using 1% allele frequency as the detection limit. Additionally, we uncovered disease associations of multiple phenotypes with mosaic CNVs at several genomic loci. We additionally investigated the allele imbalance observations genome-wide to define non-diploid and non-integer copy number states. Conclusions Our novel algorithm presents an efficient tool with fast computational runtime and high levels of accuracy of mosaic CNV detection. A curated mosaic CNV callset of 3716 events in 2269 samples is presented with comparability to previous reports and disease phenotype associations. The new algorithm can be freely accessed via: https://github.com/CAG-CNV/MONTAGE.

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