The impact of copy number deletions on general cognitive ability and ventricle size in patients with schizophrenia and healthy control subjects

Copy Number Variations in Neuropsychiatric Disorders

Neuropsychiatric disorders are complex conditions that represent a significant global health burden with complex and multifactorial etiologies. Technological advances in recent years have improved our understanding of the genetic architecture of the major neuropsychiatric disorders and the genetic loci involved. Previous studies mainly investigated genome-wide significant SNPs to elucidate the cross-disorder and disorder-specific genetic basis of neuropsychiatric disorders. Although copy number variations represent a major source of genetic variations, they are known risk factors in developing a variety of human disorders, including certain neuropsychiatric diseases. In this review, we demonstrate the current understanding of CNVs contributing to liability for schizophrenia, bipolar disorder, and major depressive disorder.

A review of the cognitive impact of neurodevelopmental and neuropsychiatric associated copy number variants

The heritability of intelligence or general cognitive ability is estimated at 41% and 66% in children and adults respectively. Many rare copy number variants are associated with neurodevelopmental and neuropsychiatric conditions (ND-CNV), including schizophrenia and autism spectrum disorders, and may contribute to the observed variability in cognitive ability. Here, we reviewed studies of intelligence quotient or cognitive function in ND-CNV carriers, from both general population and clinical cohorts, to understand the cognitive impact of ND-CNV in both contexts and identify potential genotype-specific cognitive phenotypes. We reviewed aggregate studies of sets ND-CNV broadly linked to neurodevelopmental and neuropsychiatric conditions, and genotype-first studies of a subset of 12 ND-CNV robustly associated with schizophrenia and autism. Cognitive impacts were observed across ND-CNV in both general population and clinical cohorts, with reports of phenotypic heterogeneity. Evidence for ND-CNV-specific impacts were limited by a small number of studies and samples sizes. A comprehensive understanding of the cognitive impact of ND-CNVs would be clinically informative and could identify potential educational needs for ND-CNV carriers. This could improve genetic counselling for families impacted by ND-CNV, and clinical outcomes for those with complex needs.

The contribution of copy number variants to psychiatric symptoms and cognitive ability

Copy number variants (CNVs) are deletions and duplications of DNA sequence. The most frequently studied CNVs, which are described in this review, are recurrent CNVs that occur in the same locations on the genome. These CNVs have been strongly implicated in neurodevelopmental disorders, namely autism spectrum disorder (ASD), intellectual disability (ID), and developmental delay (DD), but also in schizophrenia. More recent work has also shown that CNVs increase risk for other psychiatric disorders, namely, depression, bipolar disorder, and post-traumatic stress disorder. Many of the same CNVs are implicated across all of these disorders, and these neuropsychiatric CNVs are also associated with cognitive ability in the general population, as well as with structural and functional brain alterations. Neuropsychiatric CNVs also show incomplete penetrance, such that carriers do not always develop any psychiatric disorder, and may show only mild symptoms, if any. Variable expressivity, whereby the same CNVs are associated with many different phenotypes of varied severity, also points to highly complex mechanisms underlying disease risk in CNV carriers. Comprehensive and longitudinal phenotyping studies of individual CNVs have provided initial insights into these mechanisms. However, more work is needed to estimate and predict the effect of non-recurrent, ultra-rare CNVs, which also contribute to psychiatric and cognitive outcomes. Moreover, delineating the broader phenotypic landscape of neuropsychiatric CNVs in both clinical and general population cohorts may also offer important mechanistic insights.

Rare Copy Number Variants Are Associated With Poorer Cognition in Schizophrenia

BACKGROUND

Cognitive impairment in schizophrenia is a major contributor to poor outcomes, yet its causes are poorly understood. Some rare copy number variants (CNVs) are associated with schizophrenia risk and affect cognition in healthy populations, but their contribution to cognitive impairment in schizophrenia has not been investigated. We examined the effect of 12 schizophrenia CNVs on cognition in those with schizophrenia.

METHODS

General cognitive ability was measured using the Measurement and Treatment Research to Improve Cognition in Schizophrenia composite z score in 875 patients with schizophrenia and in a replication sample of 519 patients with schizophrenia using Wechsler Adult Intelligence Scale Full Scale IQ. Using linear regression, we tested for association between cognition and schizophrenia CNV status, covarying for age and sex. In addition, we tested whether CNVs hitting genes in schizophrenia-enriched gene sets (loss-of-function intolerant and synaptic gene sets) were associated with cognitive impairment.

RESULTS

A total of 23 schizophrenia CNV carriers were identified. Schizophrenia CNV carriers had lower general cognitive ability than nonschizophrenia CNV carriers in discovery (β = -0.66, 95% confidence interval [CI] = -1.31 to -0.01) and replication samples (β = -0.91, 95% CI = -1.71 to -0.11) and after meta-analysis (β = -0.76, 95% CI = -1.26 to -0.25, p = .003). CNVs hitting loss-of-function intolerant genes were associated with lower cognition (β = -0.15, 95% CI = -0.29 to -0.001, p = .048).

CONCLUSIONS

In those with schizophrenia, cognitive ability in schizophrenia CNV carriers is 0.5-1.0 standard deviations below non-CNV carriers, which may have implications for clinical assessment and management. We also demonstrate that rare CNVs hitting genes intolerant to loss-of-function variation lead to more severe cognitive impairment, above and beyond the effect of known schizophrenia CNVs.

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.

Identifying schizophrenia patients who carry pathogenic genetic copy number variants using standard clinical assessment: retrospective cohort study

BACKGROUND

Copy number variants (CNVs) play a significant role in disease pathogenesis in a small subset of individuals with schizophrenia (~2.5%). Chromosomal microarray testing is a first-tier genetic test for many neurodevelopmental disorders. Similar testing could be useful in schizophrenia.

AIMS

To determine whether clinically identifiable phenotypic features could be used to successfully model schizophrenia-associated (SCZ-associated) CNV carrier status in a large schizophrenia cohort.

METHOD

Logistic regression and receiver operating characteristic (ROC) curves tested the accuracy of readily identifiable phenotypic features in modelling SCZ-associated CNV status in a discovery data-set of 1215 individuals with psychosis. A replication analysis was undertaken in a second psychosis data-set (n = 479).

RESULTS

In the discovery cohort, specific learning disorder (OR = 8.12; 95% CI 1.16-34.88, P = 0.012), developmental delay (OR = 5.19; 95% CI 1.58-14.76, P = 0.003) and comorbid neurodevelopmental disorder (OR = 5.87; 95% CI 1.28-19.69, P = 0.009) were significant independent variables in modelling positive carrier status for a SCZ-associated CNV, with an area under the ROC (AUROC) of 74.2% (95% CI 61.9-86.4%). A model constructed from the discovery cohort including developmental delay and comorbid neurodevelopmental disorder variables resulted in an AUROC of 83% (95% CI 52.0-100.0%) for the replication cohort.

CONCLUSIONS

These findings suggest that careful clinical history taking to document specific neurodevelopmental features may be informative in screening for individuals with schizophrenia who are at higher risk of carrying known SCZ-associated CNVs. Identification of genomic disorders in these individuals is likely to have clinical benefits similar to those demonstrated for other neurodevelopmental disorders.

Variation in fourteen brain structure volumes in schizophrenia: A comprehensive meta-analysis of 246 studies

Despite hundreds of structural MRI studies documenting smaller brain volumes on average in schizophrenia compared to controls, little attention has been paid to group differences in the variability of brain volumes. Examination of variability may help interpret mean group differences in brain volumes and aid in better understanding the heterogeneity of schizophrenia. Variability in 246 MRI studies was meta-analyzed for 13 structures that have shown medium to large mean effect sizes (Cohen's d≥0.4): intracranial volume, total brain volume, lateral ventricles, third ventricle, total gray matter, frontal gray matter, prefrontal gray matter, temporal gray matter, superior temporal gyrus gray matter, planum temporale, hippocampus, fusiform gyrus, insula; and a control structure, caudate nucleus. No significant differences in variability in cortical/subcortical volumes were detected in schizophrenia relative to controls. In contrast, increased variability was found in schizophrenia compared to controls for intracranial and especially lateral and third ventricle volumes. These findings highlight the need for more attention to ventricles and detailed analyses of brain volume distributions to better elucidate the pathophysiology of schizophrenia.

Treatment resistant schizophrenia: Clinical, biological, and therapeutic perspectives

Treatment resistant schizophrenia (TRS) refers to the significant proportion of schizophrenia patients who continue to have symptoms and poor outcomes despite treatment. While many definitions of TRS include failure of two different antipsychotics as a minimum criterion, the wide variability in inclusion criteria has challenged the consistency and reproducibility of results from studies of TRS. We begin by reviewing the clinical, neuroimaging, and neurobiological characteristics of TRS. We further review the current treatment strategies available, addressing clozapine, the first-line pharmacological agent for TRS, as well as pharmacological and non-pharmacological augmentation of clozapine including medication combinations, electroconvulsive therapy, repetitive transcranial magnetic stimulation, deep brain stimulation, and psychotherapies. We conclude by highlighting the most recent consensus for defining TRS proposed by the Treatment Response and Resistance in Psychosis Working Group, and provide our overview of future perspectives and directions that could help advance the field of TRS research, including the concept of TRS as a potential subtype of schizophrenia.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part II: Cognition, neuroimaging and genetics

OBJECTIVES

Schizophrenia is a group of severe psychiatric disorders with high heritability but only low odds ratios of risk genes. Despite progress in the identification of pathophysiological processes, valid biomarkers of the disease are still lacking.

METHODS

This comprehensive review summarises recent efforts to identify genetic underpinnings, clinical and cognitive endophenotypes and symptom dimensions of schizophrenia and presents findings from neuroimaging studies with structural, functional and spectroscopy magnetic resonance imaging and positron emission tomography. The potential of findings to be biomarkers of schizophrenia is discussed.

RESULTS

Recent findings have not resulted in clear biomarkers for schizophrenia. However, we identified several biomarkers that are potential candidates for future research. Among them, copy number variations and links between genetic polymorphisms derived from genome-wide analysis studies, clinical or cognitive phenotypes, multimodal neuroimaging findings including positron emission tomography and magnetic resonance imaging, and the application of multivariate pattern analyses are promising.

CONCLUSIONS

Future studies should address the effects of treatment and stage of the disease more precisely and apply combinations of biomarker candidates. Although biomarkers for schizophrenia await validation, knowledge on candidate genomic and neuroimaging biomarkers is growing rapidly and research on this topic has the potential to identify psychiatric endophenotypes and in the future increase insight on individual treatment response in schizophrenia.

Increased rare duplication burden genomewide in patients with treatment-resistant schizophrenia

BACKGROUND

A significant number of patients with schizophrenia fail to respond to antipsychotic medication. Although several studies have investigated associated patient characteristics, the emerging findings from genetic studies offer further scope for study.

METHOD

In 612 schizophrenia patients with detailed clinical information, common genetic variants indexed by polygenic risk scores, and rare variants indexed by deletion and duplication burden genomewide, we explored potential genetic predictors alongside other established risk factors for treatment resistance. Clinical outcomes of treatment resistance were also calculated using lifetime measures of positive, negative/disorganized and mood symptoms as well as number of hospitalizations and suicide attempts.

RESULTS

Logistic regression models identified a significant relationship between treatment resistance and total duplication burden genomewide, years of formal schooling and age at onset. Clinically, treatment-resistant patients were characterized by greater negative/disorganized and positive symptoms and greater number of hospitalizations.

CONCLUSIONS

Taken together, these findings suggest genetic information, specifically the genomewide burden of rare copy number variants, may increase our understanding and clinical management of patients with treatment-resistant schizophrenia.

Graph Metrics of Structural Brain Networks in Individuals with Schizophrenia and Healthy Controls: Group Differences, Relationships with Intelligence, and Genetics

OBJECTIVES

One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia.

METHODS

Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging.

RESULTS

The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity--connections among high degree "rich club" nodes, "feeder" connections to these rich club nodes, and "local" connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length.

CONCLUSIONS

Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA.

Clinical and parental age characteristics of rare copy number variant burden in patients with schizophrenia

Copy number variant (CNV) burden, especially for rare deletions, has been associated with risk for schizophrenia as well as phenotypic differences within cognitive and neuroimaging domains. The current study investigated clinical and parental age characteristics of rare CNV burden in patients with schizophrenia. Clinical data was collected for 629 patients with schizophrenia who formed part of a genomewide association study, which included CNV data. Parental age was available for 368 patients. Correlations were calculated between burden scores and positive, negative, and mood symptoms from the Lifetime Diagnostic Psychosis Scale as well as age at onset. Patients were grouped according to number of rare deletions, duplications, or total CNVs and MANOVAs used to investigate differences in clinical and parental age characteristics. Patients with the least number of CNVs had older fathers and larger parental age difference. Patients with no deletions had older mothers and those with five or more deletions had younger mothers. Total deletion, duplication, and CNV burden, as measured by number of base pairs, were not associated with clinical or parental age differences although total rare duplication burden had a negative correlation with positive symptoms that did not survive correction for multiple testing. Likewise, a positive correlation between age at onset and total CNV burden did not survive correction. Rare CNVs are associated with differences in parental age in patients with schizophrenia. No robust clinical differences were identified. However, duplication burden may have a small protective effect against positive symptoms and age at onset may be influenced by total CNV burden. No clinical differences were associated with deletion burden measures.

Cognitive and structural neuroimaging characteristics of schizophrenia patients with large, rare copy number deletions

Large (>500 Kb), rare (frequency <1%) deletions are associated with risk for schizophrenia. The aim of the study was to characterise patients with these deletions using measures of cognition, grey-matter volume and white-matter integrity. Patients with schizophrenia and large, rare deletions (SZ-del) (n=17) were assessed on a test of intelligence, the Wechsler Abbreviated Scale of Intelligence (WASI), and compared with age- and sex-matched schizophrenia patients without large, rare deletions (SZ-nodel) (n=65), and healthy controls (HCs) (n=50). Regional grey-matter differences were investigated using voxel-based morphometry (SZ-del=9; SZ-nodel=26; HC=19). White-matter integrity was assessed using fractional anisotropy (SZ-del=9; SZ-nodel=24; HC=15). Compared with schizophrenia patients without large, rare deletions, those with large, rare deletions had lower IQ; greater grey-matter volume in clusters with peaks in the left and right cerebellum, left hippocampus, and right rectal gyrus; and increased white-matter anisotropy in the body and genu of the corpus callosum. Compared with healthy controls, patients with large, rare deletions had reduced grey matter volume in the right calcarine gyrus. In sum, patients with large, rare deletions had structural profiles intermediate to those observed in healthy controls and schizophrenia patients without large, rare deletions, but had greater impairment in intelligence.

Genetic influences on cognitive endophenotypes in schizophrenia

BACKGROUND

Cognitive deficits are prominent in schizophrenia and represent promising endophenotypes for genetic research.

METHODS

The current study investigated the importance of two conceptually distinct genetic aggregates, one based on copy number variations (uncommon deletion burden), and one based on single nucleotide polymorphisms identified in recent risk studies (genetic risk score). The impact of these genetic factors, and their interaction, was examined on cognitive endophenotypes defined by principal component analysis (PCA) in a multi-center sample of 50 patients with schizophrenia and 86 controls. PCA was used to identify three different types of executive function (EF: planning, fluency, and inhibition), and in separate analyses, a measure general cognitive ability (GCA).

RESULTS

Cognitive deficits were prominent among individuals with schizophrenia, but no group differences were evident for either genetic factor. Among patients the deletion burden measures predicted cognitive deficits across the three EF components and GCA. Further, an interaction was noted between the two genetic factors for both EF and GCA and the observed patterns of interaction suggested antagonistic epistasis. In general, the set of genetic interactions examined predicted a substantial portion of variance in these cognitive endophenotypes.

LIMITATIONS

Though adequately powered, our sample size is small for a genetic study.

CONCLUSIONS

These results draw attention to genetic interactions and the possibility that genetic influences on cognition differ in patients and controls.