Gene Discovery and Glutamate Signaling Defects in Intellectual Disability and Autism

Neurodevelopmental disorders are a common class of brain disorders that affect up to 1 in 6 children in the industrialized world. They include a range of diseases, including Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorders, and various forms Intellectual Disability. Many of these disorders display overlapping clinical phenotypes, including reductions in intellectual quotient, learning delays, difficulties in social behavior, stereotypical behaviors, and deficits in verbalization and communication. Frequently, other comorbidities may be present, such as epilepsy or craniofacial defects. Many of these disorders are strictly genetic in their etiology, as determined by a consistent pattern of Mendelian inheritance in affected families. Other, more complex neurodevelopmental disorders, such as schizophrenia, major depression, bipolar disorder, and autism, show strong evidence that genetics is a substantial cause, along with a role for environmental factors. The focus of this dissertation will be on elucidating genetic and molecular mechanisms involved in the etiology of two neurodevelopmental disorders, X-Linked Intellectual Disability and Autism Spectrum Disorders. Throughout this dissertation, a series of important observations and concepts will be discussed regarding the challenges faced when studying neurodevelopmental disorders of genetic etiology. These challenges are based in the intersecting complexities of how genetic variation influences neural mechanisms and how neural mechanisms influence intellectual function and behavior. In order to address these challenges, I have developed computational tools to improve our ability to identify potential disease-causing variants and genes. One of these tools is an effective method to identify causal genes in XLID, through improvements in the quality of sequenced variant calls, and through effective methods of variant filtering using a combination of datasets. Lastly, I have employed a series of targeted genomic and functional studies to determine how genetic variation can modify neural function and behavior. This series of studies will discuss the role of glutamate signaling defects in autism etiology, with a focus on Glutamate Receptor Interacting Proteins (GRIP1/2) as autism susceptibility genes. As a whole, these studies should provide a framework demonstrating how old and new genomic techniques can be used effectively to find disease-causing variants and genes in neurodevelopmental disorders of increasing complexity. Importantly, this work should reinforce our appreciation of the complexity of neural and genetic systems, and that any computational inference should be diligently investigated by functional work to identify a molecular mechanism for disease

Effective detection of rare variants in pooled DNA samples using Cross-pool tailcurve analysis

Sequencing targeted DNA regions in large samples is necessary to discover the full spectrum of rare variants. We report an effective Illumina sequencing strategy utilizing pooled samples with novel quality (Srfim) and filtering (SERVIC4E) algorithms. We sequenced 24 exons in two cohorts of 480 samples each, identifying 47 coding variants, including 30 present once per cohort. Validation by Sanger sequencing revealed an excellent combination of sensitivity and specificity for variant detection in pooled samples of both cohorts as compared to publicly available algorithms

ZC4H2, an XLID gene, is required for the generation of a specific subset of CNS interneurons

Miles-Carpenter syndrome (MCS) was described in 1991 as an XLID syndrome with fingertip arches and contractures and mapped to proximal Xq. Patients had microcephaly, short stature, mild spasticity, thoracic scoliosis, hyperextendable MCP joints, rocker-bottom feet, hyperextended elbows and knees. A mutation, p.L66H, in ZC4H2, was identified in a XLID resequencing project. Additional screening of linked families and next generation sequencing of XLID families identified three ZC4H2 mutations: p.R18K, p.R213W and p.V75in15aa. The families shared some relevant clinical features. In silico modeling of the mutant proteins indicated all alterations would destabilize the protein. Knockout mutations in zc4h2 were created in zebrafish and homozygous mutant larvae exhibited abnormal swimming, increased twitching, defective eye movement and pectoral fin contractures. Because several of the behavioral defects were consistent with hyperactivity, we examined the underlying neuronal defects and found that sensory neurons and motoneurons appeared normal. However, we observed a striking reduction in GABAergic interneurons. Analysis of cell-type-specificmarkers showed a specific loss of V2 interneurons in the brain and spinal cord, likely arising from mis-specification of neural progenitors. Injected human wt ZC4H2 rescued the mutant phenotype. Mutant zebrafish injectedwith human p.L66H or p.R213W mRNA failed to be rescued, while the p.R18K mRNA was able to rescue the interneuron defect. Our findings clearly support ZC4H2 as a novel XLID gene with a required function in interneuron development. Loss of function of ZC4H2 thus likely results in altered connectivity ofmany brain and spinal circuits

Affected Kindred Analysis of Human X Chromosome Exomes to Identify Novel X-Linked Intellectual Disability Genes

<div><p>X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ~10% of X chromosome genes are implicated in causing XLID disorders in ~50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders.</p></div

Shared Segment Filter and Error Reduction by Strand/Proximity Pre-Filter.

<p>The Shared Segment Filter (component of the Affected Kindred/Cross-Cohort Filter) retains chromosomal segments shared as Identical by Descent between two related samples in the XLID cohort. In this example, <b>Panels A</b> and <b>B</b> each reflect the same kindred pair, two brothers. The X-axis is position along the X chromosome exome. The Y-axis indicates the allelic status of a given variant for both siblings. Each point in the graph is a variant site for at least one sample. R|R allelic status indicates that the given point (genomic site) matches the reference sequence (hg19) in both samples (both samples are wildtype). A|A allelic status indicates the given point (variant site) is alternate to hg19 in both samples (both samples are hemizygous mutant). A|R allelic status indicates the given point matches reference in one sample and is alternate in the kindred sample (the samples are genotypically discordant). The orange blocks delineate chromosomal segments devoid of A|R points. All sequence in that segment is Identical by Descent between the two samples. The Shared Segment Filter retains variants (A|A) within the orange block. <b>Panel A</b> shows variant allele status in the Shared Segment Filter prior to the application of the strand- and proximity-based pre-filters. With the exception of the rare <i>de novo</i> mutation, there should be no discordant (A|R) variants within the orange block. Such variants are likely erroneous. <b>Panel B</b> shows the Shared Segment Filter after application of the strand- and proximity-based pre-filters. The A|R variants previously present in the orange block are eliminated, reflecting a reduction in erroneous variant calls as a result of these pre-filters.</p

Enrichment of Potential Pathological Variants in X-Exome of XLID Cohort with Different Variant Filters.

<p>Average number of variants remaining per sample after sequential or aggregate filtering steps.</p><p>¹ Strand and Proximity Pre-Filters are applied universally on top of all other filters. The percent of variants remaining after a particular filter is relative to the variant output after application of the Strand and Proximity Pre-Filters and is provided in column 5.</p><p>² Shared Segment Filter: for demonstration purposes, results of this filter are provided separately from the rest of the Affected Kindred/Cross-Cohort Filter.</p><p>³ [1000G] Male-162 Internal Exome Filter: removes variants from the XLID cohort shared in common with 162 males from the 1000 Genomes.</p><p>⁴ Exome Variant Server (Male Only) Filter: removes variants from the XLID cohort shared in common with variants of the male fraction of EVS.</p><p>⁵ “Non-Clinical” dbSNP is redacted of known, probable, or potentially pathological variants in dbSNP Build 137.</p><p>⁶ Affected Kindred/Cross-Cohort Filter: results exclude the Shared Segment Filter component (see Row 2).</p><p>⁷ All filters, including re-introduction of known rare pathological variants (from dbSNP) that are inappropriately eliminated by the Affected Kindred/Cross-Cohort Filter.</p><p>Enrichment of Potential Pathological Variants in X-Exome of XLID Cohort with Different Variant Filters.</p

Identification of Known and Potentially Novel Genes for XLID Using X Chromosome Exome Sequencing and Affected Kindred/Cross-Cohort Analysis.

<p>Identification of Known and Potentially Novel Genes for XLID Using X Chromosome Exome Sequencing and Affected Kindred/Cross-Cohort Analysis.</p

XLID Cohort for X Chromosome Exome Sequencing.

<p>All samples are diagnosed with an X-linked Intellectual Disorder. Criteria for X-linkage are described in <b>Materials and Methods</b>.</p><p>XLID Cohort for X Chromosome Exome Sequencing.</p