Rare genomic deletions and duplications and their role in neurodevelopmental disorders

Rare recurrent copy number variations in metabotropic glutamate receptor interacting genes in children with neurodevelopmental disorders

BACKGROUND

Neurodevelopmental disorders (NDDs), such as attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), are examples of complex and partially overlapping phenotypes that often lack definitive corroborating genetic information. ADHD and ASD have complex genetic associations implicated by rare recurrent copy number variations (CNVs). Both of these NDDs have been shown to share similar biological etiologies as well as genetic pleiotropy.

METHODS

Platforms aimed at investigating genetic-based associations, such as high-density microarray technologies, have been groundbreaking techniques in the field of complex diseases, aimed at elucidating the underlying disease biology. Previous studies have uncovered CNVs associated with genes within shared candidate genomic networks, including glutamate receptor genes, across multiple different NDDs. To examine shared biological pathways across two of the most common NDDs, we investigated CNVs across 15,689 individuals with ADHD (n = 7920), ASD (n = 4318), or both (n = 3,416), as well as 19,993 controls. Cases and controls were matched by genotype array (i.e., Illumina array versions). Three case-control association studies each calculated and compared the observed vs. expected frequency of CNVs across individual genes, loci, pathways, and gene networks. Quality control measures of confidence in CNV-calling, prior to association analyses, included visual inspection of genotype and hybridization intensity.

RESULTS

Here, we report results from CNV analysis in search for individual genes, loci, pathways, and gene networks. To extend our previous observations implicating a key role of the metabotropic glutamate receptor (mGluR) network in both ADHD and autism, we exhaustively queried patients with ASD and/or ADHD for CNVs associated with the 273 genomic regions of interest within the mGluR gene network (genes with one or two degrees protein-protein interaction with mGluR 1-8 genes). Among CNVs in mGluR network genes, we uncovered CNTN4 deletions enriched in NDD cases (P = 3.22E - 26, OR = 2.49). Additionally, we uncovered PRLHR deletions in 40 ADHD cases and 12 controls (P = 5.26E - 13, OR = 8.45) as well as clinically diagnostic relevant 22q11.2 duplications and 16p11.2 duplications in 23 ADHD + ASD cases and 9 controls (P = 4.08E - 13, OR = 15.05) and 22q11.2 duplications in 34 ADHD + ASD cases and 51 controls (P = 9.21E - 9, OR = 3.93); those control samples were not with previous 22qDS diagnosis in their EHR records.

CONCLUSION

Together, these results suggest that disruption in neuronal cell-adhesion pathways confers significant risk to NDDs and showcase that rare recurrent CNVs in CNTN4, 22q11.2, and 16p11.2 are overrepresented in NDDs that constitute patients predominantly suffering from ADHD and ASD.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02286817 First Posted: 10 November 14, ClinicalTrials.gov Identifier: NCT02777931 first posted: 19 May 2016, ClinicalTrials.gov Identifier: NCT03006367 first posted: 30 December 2016, ClinicalTrials.gov Identifier: NCT02895906 first posted: 12 September 2016.

Non-coding structural variation differentially impacts attention-deficit hyperactivity disorder (ADHD) gene networks in African American vs Caucasian children

Previous studies of attention-deficit hyperactivity disorder (ADHD) have suggested that structural variants (SVs) play an important role but these were mainly studied in subjects of European ancestry and focused on coding regions. In this study, we sought to address the role of SVs in non-European populations and outside of coding regions. To that end, we generated whole genome sequence (WGS) data on 875 individuals, including 205 ADHD cases and 670 non-ADHD controls. The ADHD cases included 116 African Americans (AA) and 89 of European Ancestry (EA) with SVs in comparison with 408 AA and 262 controls, respectively. Multiple SVs and target genes that associated with ADHD from previous studies were identified or replicated, and novel recurrent ADHD-associated SV loci were discovered. We identified clustering of non-coding SVs around neuroactive ligand-receptor interaction pathways, which are involved in neuronal brain function, and highly relevant to ADHD pathogenesis and regulation of gene expression related to specific ADHD phenotypes. There was little overlap (around 6%) in the genes impacted by SVs between AA and EA. These results suggest that SVs within non-coding regions may play an important role in ADHD development and that WGS could be a powerful discovery tool for studying the molecular mechanisms of ADHD

Slitrk Missense Mutations Associated with Neuropsychiatric Disorders Distinctively Impair Slitrk Trafficking and Synapse Formation

Slit- and Trk-like (Slitrks) are a six-member family of synapse organizers that control excitatory and inhibitory synapse formation by forming trans-synaptic adhesions with LAR receptor protein tyrosine phosphatases (PTPs). Intriguingly, genetic mutations of Slitrks have been associated with a multitude of neuropsychiatric disorders. However, nothing is known about the neuronal and synaptic consequences of these mutations. Here, we report the structural and functional effects on synapses of various rare de novo mutations identified in patients with schizophrenia or Tourette syndrome. A number of single amino acid substitutions in Slitrk1 (N400I or T418S) or Slitrk4 (V206I or I578V) reduced their surface expression levels. These substitutions impaired glycosylation of Slitrks expressed in HEK293T cells, caused retention of Slitrks in the endoplasmic reticulum and cis-Golgi compartment in COS-7 cells and neurons, and abolished Slitrk binding to PTPδ. Furthermore, these substitutions eliminated the synapse-inducing activity of Slitrks, abolishing their functional effects on synapse density in cultured neurons. Strikingly, a valine-to-methionine mutation in Slitrk2 (V89M) compromised synapse formation activity in cultured neuron, without affecting surface transport, expression, or synapse-inducing activity in coculture assays. Similar deleterious effects were observed upon introduction of the corresponding valine-to-methionine mutation into Slitrk1 (V85M), suggesting that this conserved valine residue plays a key role in maintaining the synaptic functions of Slitrks. Collectively, these data indicate that inactivation of distinct cellular mechanisms caused by specific Slitrk dysfunctions may underlie Slitrk-associated neuropsychiatric disorders in humans, and provide a robust cellular readout for the development of knowledge-based therapies.

A New Method for Detecting Associations with Rare Copy-Number Variants

Copy number variants (CNVs) play an important role in the etiology of many diseases such as cancers and psychiatric disorders. Due to a modest marginal effect size or the rarity of the CNVs, collapsing rare CNVs together and collectively evaluating their effect serves as a key approach to evaluating the collective effect of rare CNVs on disease risk. While a plethora of powerful collapsing methods are available for sequence variants (e.g., SNPs) in association analysis, these methods cannot be directly applied to rare CNVs due to the CNV-specific challenges, i.e., the multi-faceted nature of CNV polymorphisms (e.g., CNVs vary in size, type, dosage, and details of gene disruption), and etiological heterogeneity (e.g., heterogeneous effects of duplications and deletions that occur within a locus or in different loci). Existing CNV collapsing analysis methods (a.k.a. the burden test) tend to have suboptimal performance due to the fact that these methods often ignore heterogeneity and evaluate only the marginal effects of a CNV feature. We introduce CCRET, a random effects test for collapsing rare CNVs when searching for disease associations. CCRET is applicable to variants measured on a multi-categorical scale, collectively modeling the effects of multiple CNV features, and is robust to etiological heterogeneity. Multiple confounders can be simultaneously corrected. To evaluate the performance of CCRET, we conducted extensive simulations and analyzed large-scale schizophrenia datasets. We show that CCRET has powerful and robust performance under multiple types of etiological heterogeneity, and has performance comparable to or better than existing methods when there is no heterogeneity.

Genetics of cognition in epilepsy

With the completion of the Human Genome Project and the advent of more advanced sequencing platforms capable of high throughput genotyping at reduced cost, research on the genetics/genomics of cognition has expanded rapidly over the past several decades. This has been facilitated even further by global consortia including HapMap, 1000 Genomes Project, ENCODE, and others, which have made information regarding genetic variation and genomic functional elements readily available to all researchers. Thus, the goal of this Targeted Review is not to provide an exhaustive review of the existing literature on the role of genetic factors in cognition. Rather, we will highlight some of the most consistent findings in this field, review the research in epilepsy to date, and provide a background within which to set forth unique opportunities epilepsy may provide to further elucidate the role of genetics in cognition.

Etiology of autism spectrum disorder: a genomics perspective

In recent years, considerable progress has been made in understanding the genomic basis of autism spectrum disorder (ASD). Hundreds of variants have been proposed as predisposing to ASD, and the challenge now is to validate candidates and to understand how gene networks interact to produce ASD phenotypes. Genome-wide association and second-generation sequencing studies in particular have provided important indications about how to understand ASD on a molecular level, and we are beginning to see these experimental approaches translate into novel treatments and diagnostic tests. We review key studies in the field over the past five years and discuss some of the remaining technological and methodological challenges that remain.

Copy number variation analysis in the context of electronic medical records and large-scale genomics consortium efforts

The goal of this paper is to review recent research on copy number variations (CNVs) and their association with complex and rare diseases. In the latter part of this paper, we focus on how large biorepositories such as the electronic medical record and genomics (eMERGE) consortium may be best leveraged to systematically mine for potentially pathogenic CNVs, and we end with a discussion of how such variants might be reported back for inclusion in electronic medical records as part of medical history.

Low-Frequency Copy-Number Variants and General Cognitive Ability: No Evidence of Association

Although twin, family, and adoption studies have shown that general cognitive ability (GCA) is substantially heritable, GWAS has not uncovered a genetic polymorphism replicably associated with this phenotype. However, most polymorphisms used in GWAS are common SNPs. The present study explores use of a different class of genetic variant, the copy-number variant (CNV), to predict GCA in a sample of 6,199 participants, combined from two longitudinal family studies. We aggregated low-frequency (<5%) CNV calls into eight different mutational burden scores, each reflecting a different operationalization of mutational burden. We further conducted three genome-wide association scans, each of which utilized a different subset of identified low-frequency CNVs. Association signals from the burden analyses were generally small in effect size, and none were statistically significant after a careful Type I error correction was applied. No signal from the genome-wide scans significantly differed from zero at the adjusted Type I error rate. Thus, the present study provides no evidence that CNVs underlie heritable variance in GCA, though we cannot rule out the possibility of very rare or small-effect CNVs for this trait, which would require even larger samples to detect. We interpret these null results in light of recent breakthroughs that aggregate SNP effects to explain much, but not all, of the heritable variance in some quantitative traits.

Child development and structural variation in the human genome

Structural variation of the human genome sequence is the insertion, deletion, or rearrangement of stretches of DNA sequence sized from around 1,000 to millions of base pairs. Over the past few years, structural variation has been shown to be far more common in human genomes than previously thought. Very little is currently known about the effects of structural variation on normal child development, but such effects could be of considerable significance. This review provides an overview of the phenomenon of structural variation in the human genome sequence, describing the novel genomics technologies that are revolutionizing the way structural variation is studied and giving examples of genomic structural variations that affect child development.

Genetics of schizophrenia from a clinicial perspective

Schizophrenia (SZ) is a common disorder that runs in families. It has a relatively high heritability, i.e., inherited factors account for the major proportion of its etiology. The high heritability has motivated gene mapping studies that have improved in sophistication through the past two decades. Belying earlier expectations, it is now becoming increasingly clear that the cause of SZ does not reside in a single mutation, or even in a single gene. Rather, there are multiple DNA variants, not all of which have been identified. Additional risk may be conferred by interactions between individual DNA variants, as well as 'gene-environment' interactions. We review studies that have accounted for a fraction of the heritability. Their relevance to the practising clinician is discussed. We propose that continuing research in DNA variation, in conjunction with rapid ongoing advances in allied fields, will yield dividends from the perspective of diagnosis, treatment prediction through pharmacogenetics, and rational treatment through discoveries in pathogenesis.