A case-control collapsing analysis identifies epilepsy genes implicated in trio sequencing studies focused on de novo mutations

Clinical application of trio-based whole-exome sequencing in idiopathic generalized epilepsy

PURPOSE

Idiopathic generalized epilepsies (IGEs) are a common group of genetic generalized epilepsies with high genetic heterogeneity and complex inheritance. However, the genetic basis is still largely unknown. This study aimed to explore the genetic etiologies in IGEs.

METHODS

Trio-based whole-exome sequencing was performed in 60 cases with IGEs. The pathogenicity of candidate genetic variants was evaluated by the criteria of the American College of Medical Genetics and Genomics (ACMG), and the clinical causality was assessed by concordance between the observed phenotype and the reported phenotype.

RESULTS

Seven candidate variants were detected in seven unrelated cases with IGE (11.7%, 7/60). According to ACMG, a de novo SLC2A1 (c.376C>T/p.Arg126Cys) variant identified in childhood absence epilepsy was evaluated as pathogenic with clinical concordance. Six variants were assessed to be uncertain significance by ACMG, but then considered causative after evaluation of clinical concordance. These variants included CLCN4 hemizygous variant (c.2044G>A/p.Glu682Lys) and IQSEC2 heterozygous variant (c.4315C>T/p.Pro1439Ser) in juvenile absence epilepsy, EFHC1 variant (c.1504C>T/p.Arg502Trp) and CACNA1H (c.589G>T/p.Ala197Ser) both with incomplete penetrance in juvenile myoclonic epilepsy, and GRIN2A variant (c.2011C>G/p.Gln671Glu) and GABRB1 variant (c.1075G>A/p.Val359Ile) both co-segregated with juvenile myoclonic epilepsy. Among them, GABRB1 was for the first time identified as potential novel causative gene for IGE.

SIGNIFICANCE

Considering the genetic heterogeneity and complex inheritance of IGEs, a comprehensive evaluation combined the ACMG scoring and assessment of clinical concordance is suggested for the pathogenicity analysis of variants identified in clinical screening. GABRB1 is probably a novel causative gene for IGE, which warrants further studies.

Unraveling the role of non-coding rare variants in epilepsy

The discovery of new variants has leveled off in recent years in epilepsy studies, despite the use of very large cohorts. Consequently, most of the heritability is still unexplained. Rare non-coding variants have been largely ignored in studies on epilepsy, although non-coding single nucleotide variants can have a significant impact on gene expression. We had access to whole genome sequencing (WGS) from 247 epilepsy patients and 377 controls. To assess the functional impact of non-coding variants, ExPecto, a deep learning algorithm was used to predict expression change in brain tissues. We compared the burden of rare non-coding deleterious variants between cases and controls. Rare non-coding highly deleterious variants were significantly enriched in Genetic Generalized Epilepsy (GGE), but not in Non-Acquired Focal Epilepsy (NAFE) or all epilepsy cases when compared with controls. In this study we showed that rare non-coding deleterious variants are associated with epilepsy, specifically with GGE. Larger WGS epilepsy cohort will be needed to investigate those effects at a greater resolution. Nevertheless, we demonstrated the importance of studying non-coding regions in epilepsy, a disease where new discoveries are scarce.

A deep intronic variant in DNM1 in a patient with developmental and epileptic encephalopathy creates a splice acceptor site and affects only transcript variants including exon 10a

DNM1 developmental and epileptic encephalopathy (DEE) is characterized by severe to profound intellectual disability, hypotonia, movement disorder, and refractory epilepsy, typically presenting with infantile spasms. Most of the affected individuals had de novo missense variants in DNM1. DNM1 undergoes alternative splicing that results in expression of six different transcript variants. One alternatively spliced region affects the tandemly arranged exons 10a and 10b, producing isoforms DNM1A and DNM1B, respectively. Pathogenic variants in the DNM1 coding region affect all transcript variants. Recently, a de novo DNM1 NM_001288739.1:c.1197-8G > A variant located in intron 9 has been reported in several unrelated individuals with DEE that causes in-frame insertion of two amino acids and leads to disease through a dominant-negative mechanism. We report on a patient with DEE and a de novo DNM1 variant NM_001288739.2:c.1197-46C > G in intron 9, upstream of exon 10a. By RT-PCR and Sanger sequencing using fibroblast-derived cDNA of the patient, we identified aberrantly spliced DNM1 mRNAs with exon 9 spliced to the last 45 nucleotides of intron 9 followed by exon 10a (NM_001288739.2:r.1196_1197ins[1197-1_1197-45]). The encoded DNM1A mutant is predicted to contain 15 novel amino acids between Ile398 and Arg399 [NP_001275668.1:p.(Ile398_Arg399ins15)] and likely functions in a dominant-negative manner, similar to other DNM1 mutants. Our data confirm the importance of the DNM1 isoform A for normal human brain function that is underscored by previously reported predominant expression of DMN1A transcripts in pediatric brain, functional differences of the mouse Dnm1a and Dnm1b isoforms, and the Dnm1 fitful mouse, an epilepsy mouse model.

Identification of potentially pathogenic variants for autism spectrum disorders using gene-burden analysis

Gene- burden analyses have lately become a very successful way for the identification of genes carrying risk variants underlying the analysed disease. This approach is also suitable for complex disorders like autism spectrum disorder (ASD). The gene-burden analysis using Testing Rare Variants with Public Data (TRAPD) software was conducted on whole exome sequencing data of Slovenian patients with ASD to determine potentially novel disease risk variants in known ASD-associated genes as well as in others. To choose the right control group for testing, principal component analysis based on the 1000 Genomes and ASD cohort samples was conducted. The subsequent protein structure and ligand binding analysis usingI-TASSER package were performed to detect changes in protein structure and ligand binding to determine a potential pathogenic consequence of observed mutation. The obtained results demonstrate an association of two variants-p.Glu198Lys (PPP2R5D:c.592G>A) and p.Arg253Gln (PPP2R5D:c.758G>A) with the ASD. Substitution p.Glu198Lys (PPP2R5D:c.592G>A) is a variant, previously described as pathogenic in association with ASD combined with intellectual disability, whereas p.Arg253Gln (PPP2R5D:c.758G>A) has not been described as an ASD-associated pathogenic variant yet. The results indicate that the filtering process was suitable and could be used in the future for detection of novel pathogenic variants when analysing groups of ASD patients.

Prevalence and Penetrance of Rare Pathogenic Variants in Neurodevelopmental Psychiatric Genes in a Health Care System Population

OBJECTIVE

Autism, schizophrenia, and other clinically distinct neurodevelopmental psychiatric disorders (NPDs) have shared genetic etiologies, including single-gene and multigenic copy number variants (CNVs). Because rare variants are primarily investigated in clinical cohorts, population-based estimates of their prevalence and penetrance are lacking. The authors determined the prevalence, penetrance, and NPD risk of pathogenic single-gene variants in a large health care system population.

METHODS

The authors analyzed linked genomic and electronic health record (EHR) data in a subset of 90,595 participants from Geisinger's MyCode Community Health Initiative, known as the DiscovEHR cohort. Loss-of-function pathogenic variants in 94 high-confidence NPD genes were identified through exome sequencing, and NPD penetrance was calculated using preselected EHR diagnosis codes. NPD risk was estimated using a case-control comparison of DiscovEHR participants with and without NPD diagnoses. Results from single-gene variant analyses were also compared with those from 31 previously reported pathogenic NPD CNVs.

RESULTS

Pathogenic variants were identified in 0.34% of the DiscovEHR cohort and demonstrated a 34.3% penetrance for NPDs. Similar to CNVs, sequence variants collectively conferred a substantial risk for several NPD diagnoses, including autism, schizophrenia, and bipolar disorder. Significant NPD risk remained after participants with intellectual disability were excluded from the analysis, confirming the association with major psychiatric disorders in individuals without severe cognitive deficits.

CONCLUSIONS

Collectively, rare single-gene variants and CNVs were found in >1% of individuals in a large health care system population and play an important contributory role in mental health disorders. Diagnostic genetic testing for pathogenic variants among symptomatic individuals with NPDs could improve clinical outcomes through early intervention and anticipatory therapeutic support.

The phenotypic spectrum of KCNT1: a new family with variable epilepsy syndromes including mild focal epilepsy

BACKGROUND AND OBJECTIVE

Pathogenic variants in KCNT1 have been associated with severe forms of epilepsy, typically sleep-related hypermotor epilepsy or epilepsy of infancy with migrating focal seizures. To show that pathogenic variants in KCNT1 can be associated with mild extra-frontal epilepsy, we report a KCNT1 family with a wide spectrum of phenotypes ranging from developmental and epileptic encephalopathy to mild focal epilepsy without cognitive regression and not consistent with sleep-related hypermotor epilepsy.

METHODS

A large Canadian family of Caucasian descent including 9 affected family members was recruited. Family members were phenotyped by direct interview and review of existing medical records. Clinical epilepsy gene panel analysis and exome sequencing were performed.

RESULTS

Phenotypic information was available for five family members of which two had developmental and epileptic encephalopathy and three had normal development and focal epilepsy with presumed extra-frontal onset. All three had predominantly nocturnal seizures that did not show hyperkinetic features. All three reported clusters of seizures at night with a feeling of being unable to breathe associated with gasping for air, choking and/or repetitive swallowing possibly suggesting insular or opercular involvement. Genetic analysis identified a heterozygous KCNT1 c.2882G > A, p.Arg961His variant that was predicted to be deleterious.

DISCUSSION

This family demonstrates that the phenotypic spectrum associated with KCNT1 pathogenic variants is broader than previously assumed. Our findings indicate that variants in KCNT1 can be associated with mild focal epilepsy and should not be excluded during variant interpretation in such patients based solely on gene-disease validity.

ATAV: a comprehensive platform for population-scale genomic analyses

Background

A common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples are continually added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive.

Results

We present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework.

To allow users to easily access variant-level data directly from the database, we provide a web-based interface, the ATAV data browser (http://atavdb.org/). Through this browser, summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and therefore evolves rapidly as more and more samples are sequenced.

Conclusions

Through ATAV, users have public access to one of the largest variant databases for patients sequenced at a tertiary care center and can look up any genes or variants of interest. Additionally, since the entire code is freely available on GitHub, ATAV can easily be deployed by other groups that wish to build their own platform, database, and user interface.

Serine biosynthesis defect due to haploinsufficiency of PHGDH causes retinal disease

Macular telangiectasia type 2 (MacTel) is a progressive, late-onset retinal degenerative disease linked to decreased serum levels of serine that elevate circulating levels of a toxic ceramide species, deoxysphingolipids (deoxySLs); however, causal genetic variants that reduce serine levels in patients have not been identified. Here we identify rare, functional variants in the gene encoding the rate-limiting serine biosynthetic enzyme, phosphoglycerate dehydrogenase (PHGDH), as the single locus accounting for a significant fraction of MacTel. Under a dominant collapsing analysis model of a genome-wide enrichment analysis of rare variants predicted to impact protein function in 793 MacTel cases and 17,610 matched controls, the PHGDH gene achieves genome-wide significance (P = 1.2 × 10^-13) with variants explaining ~3.2% of affected individuals. We further show that the resulting functional defects in PHGDH cause decreased serine biosynthesis and accumulation of deoxySLs in retinal pigmented epithelial cells. PHGDH is a significant locus for MacTel that explains the typical disease phenotype and suggests a number of potential treatment options.

The phenotypic spectrum of X-linked, infantile onset ALG13-related developmental and epileptic encephalopathy

Objective

Asparagine‐linked glycosylation 13 (ALG13) deficiencies have been repeatedly described in the literature with the clinical phenotype of a developmental and epileptic encephalopathy (DEE). Most cases were females carrying the recurrent ALG13 de novo variant, p.(Asn107Ser), with normal transferrin electrophoresis.

Methods

We delineate the phenotypic spectrum of 38 individuals, 37 girls and one boy, 16 of them novel and 22 published, with the most common pathogenic ALG13 variant p.(Asn107Ser) and additionally report the phenotype of three individuals carrying other likely pathogenic ALG13 variants.

Results

The phenotypic spectrum often comprised pharmacoresistant epilepsy with epileptic spasms, mostly with onset within the first 6 months of life and with spasm persistence in one‐half of the cases. Tonic seizures were the most prevalent additional seizure type. Electroencephalography showed hypsarrhythmia and at a later stage of the disease in one‐third of all cases paroxysms of fast activity with electrodecrement. ALG13‐related DEE was usually associated with severe to profound developmental delay; ambulation was acquired by one‐third of the cases, whereas purposeful hand use was sparse or completely absent. Hand stereotypies and dyskinetic movements including dystonia or choreoathetosis were relatively frequent. Verbal communication skills were absent or poor, and eye contact and pursuit were often impaired.

Significance

X‐linked ALG13‐related DEE usually manifests as West syndrome with severe to profound developmental delay. It is predominantly caused by the recurrent de novo missense variant p.(Asn107Ser). Comprehensive functional studies will be able to prove or disprove an association with congenital disorder of glycosylation.

Causal Genetic Variants in Stillbirth

BACKGROUND

In the majority of cases, the cause of stillbirth remains unknown despite detailed clinical and laboratory evaluation. Approximately 10 to 20% of stillbirths are attributed to chromosomal abnormalities. However, the causal nature of single-nucleotide variants and small insertions and deletions in exomes has been understudied.

METHODS

We generated exome sequencing data for 246 stillborn cases and followed established guidelines to identify causal variants in disease-associated genes. These genes included those that have been associated with stillbirth and strong candidate genes. We also evaluated the contribution of 18,653 genes in case-control analyses stratified according to the degree of depletion of functional variation (described here as "intolerance" to variation).

RESULTS

We identified molecular diagnoses in 15 of 246 cases of stillbirth (6.1%) involving seven genes that have been implicated in stillbirth and six disease genes that are good candidates for phenotypic expansion. Among the cases we evaluated, we also found an enrichment of loss-of-function variants in genes that are intolerant to such variation in the human population (odds ratio, 2.15; 95% confidence interval [CI], 1.46 to 3.06). Loss-of-function variants in intolerant genes were concentrated in genes that have not been associated with human disease (odds ratio, 2.22; 95% CI, 1.41 to 3.34), findings that differ from those in two postnatal clinical populations that were also evaluated in this study.

CONCLUSIONS

Our findings establish the diagnostic utility of clinical exome sequencing to evaluate the role of small genomic changes in stillbirth. The strength of the novel risk signal (as generated through the stratified analysis) was similar to that in known disease genes, which indicates that the genetic cause of stillbirth remains largely unknown. (Funded by the Institute for Genomic Medicine.).

Identifying Common Genes, Cell Types and Brain Regions Between Diseases of the Nervous System

Background: Diseases of the nervous system are widely considered to be caused by genetic mutations, and they have been shown to share pathogenic genes. Discovering the shared mechanisms of these diseases is useful for designing common treatments.

Method: In this study, by reviewing 518 articles published after 2007 on 20 diseases of the nervous system, we compiled data on 1607 mutations occurring in 365 genes, totals that are 1.9 and 3.2 times larger than those collected in the Clinvar database, respectively. A combination with the Clinvar data gives 2434 pathogenic mutations and 424 genes. Using this information, we measured the genetic similarities between the diseases according to the number of genes causing two diseases simultaneously. Further detection was carried out on the similarity between diseases in terms of cell types. Disease-related cell types were defined as those with disease-related gene enrichment among the marker genes of cells, as ascertained by analyzing single-cell sequencing data. Enrichment profiles of the disease-related genes over 25 cell types were constructed. The disease similarity in terms of cell types was obtained by calculating the distances between the enrichment profiles of these genes. The same strategy was applied to measure the disease similarity in terms of brain regions by analyzing the gene expression data from 10 brain regions.

Results: The disease similarity was first measured in terms of genes. The result indicated that the proportions of overlapped genes between diseases were significantly correlated to the DMN scores (phenotypic similarity), with a Pearson correlation coefficient of 0.40 and P-value = 6.0×10^-3. The disease similarity analysis for cell types identified that the distances between enrichment profiles of the disease-related genes were negatively correlated to the DMN scores, with Spearman correlation coefficient = -0.26 (P-value = 1.5 × 10^-2). However, the brain region enrichment profile distances of the disease-related genes were not significantly correlated with the DMN score. Besides the similarity of diseases, this study identified novel relationships between diseases and cell types.

Conclusion: We manually constructed the most comprehensive dataset to date for genes with mutations related to 20 nervous system diseases. By using this dataset, the similarities between diseases in terms of genes and cell types were found to be significantly correlated to their phenotypic similarity. However, the disease similarities in terms of brain regions were not significantly correlated with the phenotypic similarities. Thus, the phenotypic similarity between the diseases is more likely to be caused by dysfunctions of the same genes or the same types of neurons rather than the same brain regions. The data are collected into the database NeurodisM, which is available at http://biomed-ai.org/neurodism.

Epilepsy with migrating focal seizures: KCNT1 mutation hotspots and phenotype variability

Objective

To report new sporadic cases and 1 family with epilepsy of infancy with migrating focal seizures (EIMFSs) due to KCNT1 gain-of-function and to assess therapies' efficacy including quinidine.

Methods

We reviewed the clinical, EEG, and molecular data of 17 new patients with EIMFS and KCNT1 mutations, in collaboration with the network of the French reference center for rare epilepsies.

Results

The mean seizure onset age was 1 month (range: 1 hour to 4 months), and all children had focal motor seizures with autonomic signs and migrating ictal pattern on EEG. Three children also had infantile spasms and hypsarrhythmia. The identified KCNT1 variants clustered as “hot spots” on the C-terminal domain, and all mutations occurred de novo except the p.R398Q mutation inherited from the father with nocturnal frontal lobe epilepsy, present in 2 paternal uncles, one being asymptomatic and the other with single tonic-clonic seizure. In 1 patient with EIMFS, we identified the p.R1106Q mutation associated with Brugada syndrome and saw no abnormality in cardiac rhythm. Quinidine was well tolerated when administered to 2 and 4-year-old patients but did not reduce seizure frequency.

Conclusions

The majority of the KCNT1 mutations appear to cluster in hot spots essential for the channel activity. A same mutation can be linked to a spectrum of conditions ranging from EMFSI to asymptomatic carrier, even in the same family. None of the antiepileptic therapies displayed clinical efficacy, including quinidine in 2 patients.

Rare-variant collapsing analyses for complex traits: guidelines and applications

The first phase of genome-wide association studies (GWAS) assessed the role of common variation in human disease. Advances optimizing and economizing high-throughput sequencing have enabled a second phase of association studies that assess the contribution of rare variation to complex disease in all protein-coding genes. Unlike the early microarray-based studies, sequencing-based studies catalogue the full range of genetic variation, including the evolutionarily youngest forms. Although the experience with common variants helped establish relevant standards for genome-wide studies, the analysis of rare variation introduces several challenges that require novel analysis approaches.

New insights into tardive dyskinesia genetics: Implementation of whole-exome sequencing approach

Tardive dyskinesia (TD) is an adverse movement disorder induced by chronic treatment with antipsychotics drugs. The contribution of common genetic variants to TD susceptibility has been investigated in recent years, but with limited success. The aim of the current study was to investigate the potential contribution of rare variants to TD vulnerability. In order to identify TD risk genes, we performed whole-exome sequencing (WES) and gene-based collapsing analysis focusing on rare (allele frequency < 1%) and putatively deleterious variants (qualifying variants). 82 Jewish schizophrenia patients chronically treated with antipsychotics were included and classified as having severe TD or lack of any abnormal movements based on a rigorous definition of the TD phenotype. First, we performed a case-control, exome-wide collapsing analysis comparing 39 schizophrenia patients with severe TD to 3118 unrelated population controls. Then, we checked the potential top candidate genes among 43 patients without any TD manifestations. All the genes that were found to harbor one or more qualifying variants in patients without any TD features were excluded from the final list of candidate genes. Only one gene, regulating synaptic membrane exocytosis 2 (RIMS2), showed significant enrichment of qualifying variants in TD patients compared with unrelated population controls after correcting for multiple testing (Fisher's exact test p = 5.32E-08, logistic regression p = 2.50E-08). Enrichment was caused by a single variant (rs567070433) due to a frameshift in an alternative transcript of RIMS2. None of the TD negative patients had qualifying variants in this gene. In a validation cohort of 140 schizophrenia patients assessed for TD, the variant was also not detected in any individual. Some potentially suggestive TD genes were detected in the TD cohort and warrant follow-up in future studies. No significant enrichment in previously reported TD candidate genes was identified. To the best of our knowledge, this is the first WES study of TD, demonstrating the potential role of rare loss-of-function variant enrichment in this pharmacogenetic phenotype.

Biallelic SCN2A Gene Mutation Causing Early Infantile Epileptic Encephalopathy: Case Report and Review

The voltage-gated sodium channel neuronal type 2 alpha subunit (Na_vα1.2) encoded by the SCN2A gene causes early infantile epileptic encephalopathy (EIEE) inherited in an autosomal dominant manner. Clinically, it has variable presentations, ranging from benign familial infantile seizures (BFIS) to severe EIEE. Diagnosis is achieved through molecular DNA testing of the SCN2A gene. Herein, we report on a 30-month-old Saudi girl who presented on the fourth day of life with EIEE, normal brain magnetic resonance imaging (MRI), normal electroencephalography (EEG), and well-controlled seizures. Genetic investigation revealed a novel homozygous missense mutation (c.5242A > G; p.Asn1748Asp) in the SCN2A gene (NM_001040142.1). This is the first reported autosomal recessive inheritance of a disease allele in the SCN2A and therefore expands the molecular and inheritance spectrum of the SCN2A gene defects.

Exome-Based Rare-Variant Analyses in CKD

BACKGROUND

Studies have identified many common genetic associations that influence renal function and all-cause CKD, but these explain only a small fraction of variance in these traits. The contribution of rare variants has not been systematically examined.

METHODS

We performed exome sequencing of 3150 individuals, who collectively encompassed diverse CKD subtypes, and 9563 controls. To detect causal genes and evaluate the contribution of rare variants we used collapsing analysis, in which we compared the proportion of cases and controls carrying rare variants per gene.

RESULTS

The analyses captured five established monogenic causes of CKD: variants in PKD1, PKD2, and COL4A5 achieved study-wide significance, and we observed suggestive case enrichment for COL4A4 and COL4A3. Beyond known disease-associated genes, collapsing analyses incorporating regional variant intolerance identified suggestive dominant signals in CPT2 and several other candidate genes. Biallelic mutations in CPT2 cause carnitine palmitoyltransferase II deficiency, sometimes associated with rhabdomyolysis and acute renal injury. Genetic modifier analysis among cases with APOL1 risk genotypes identified a suggestive signal in AHDC1, implicated in Xia-Gibbs syndrome, which involves intellectual disability and other features. On the basis of the observed distribution of rare variants, we estimate that a two- to three-fold larger cohort would provide 80% power to implicate new genes for all-cause CKD.

CONCLUSIONS

This study demonstrates that rare-variant collapsing analyses can validate known genes and identify candidate genes and modifiers for kidney disease. In so doing, these findings provide a motivation for larger-scale investigation of rare-variant risk contributions across major clinical CKD categories.

A case-control collapsing analysis identifies retinal dystrophy genes associated with ophthalmic disease in patients with no pathogenic ABCA4 variants

PURPOSE

Variants in the ABCA4 gene are causal for a variety of retinal dystrophy phenotypes, including Stargardt disease (STGD1). However, 15% of patients who present with symptoms compatible with STGD1/ABCA4 disease do not have identifiable causal ABCA4 variants. We hypothesized that a case-control collapsing analysis in ABCA4-negative patients with compatible symptoms would provide an objective measure to identify additional disease genes.

METHODS

We performed a genome-wide enrichment analysis of "qualifying variants"-ultrarare variants predicted to impact protein function-in protein-coding genes in 79 unrelated cases and 9028 unrelated controls.

RESULTS

Despite modest sample size, two known retinal dystrophy genes, PRPH2 and CRX, achieved study-wide significance (p < 1.33 × 10^-6) under a dominant disease model, and eight additional known retinal dystrophy genes achieved nominal significance (p < 0.05). Across these ten genes, the excess of qualifying variants explained up to 36.8% of affected individuals. Furthermore, under a recessive model, the cone-rod dystrophy gene CERKL approached study-wide significance.

CONCLUSION

Our results indicate that case-control collapsing analyses can efficiently identify pathogenic variants in genes in non-ABCA4 retinal dystrophies. The genome-wide collapsing analysis framework is an objective discovery method particularly suitable in settings with overlapping disease phenotypes.

Improved Pathogenic Variant Localization via a Hierarchical Model of Sub-regional Intolerance

Different parts of a gene can be of differential importance to development and health. This regional heterogeneity is also apparent in the distribution of disease-associated mutations, which often cluster in particular regions of disease-associated genes. The ability to precisely estimate functionally important sub-regions of genes will be key in correctly deciphering relationships between genetic variation and disease. Previous methods have had some success using standing human variation to characterize this variability in importance by measuring sub-regional intolerance, i.e., the depletion in functional variation from expectation within a given region of a gene. However, the ability to precisely estimate local intolerance was restricted by the fact that only information within a given sub-region is used, leading to instability in local estimates, especially for small regions. We show that borrowing information across regions using a Bayesian hierarchical model stabilizes estimates, leading to lower variability and improved predictive utility. Specifically, our approach more effectively identifies regions enriched for ClinVar pathogenic variants. We also identify significant correlations between sub-region intolerance and the distribution of pathogenic variation in disease-associated genes, with AUCs for classifying de novo missense variants in Online Mendelian Inheritance in Man (OMIM) genes of up to 0.86 using exonic sub-regions and 0.91 using sub-regions defined by protein domains. This result immediately suggests that considering the intolerance of regions in which variants are found may improve diagnostic interpretation. We also illustrate the utility of integrating regional intolerance into gene-level disease association tests with a study of known disease-associated genes for epileptic encephalopathy.

A mutation update for the PCDH19 gene causing early-onset epilepsy in females with an unusual expression pattern

The PCDH19 gene consists of six exons encoding a 1,148 amino acid transmembrane protein, Protocadherin 19, which is involved in brain development. Heterozygous pathogenic variants in this gene are inherited in an unusual X-linked dominant pattern in which heterozygous females are affected, while hemizygous males are typically unaffected, although they pass on the pathogenic variant to each affected daughter. PCDH19-related disorder is known to cause early-onset epilepsy in females characterized by seizure clusters exacerbated by fever and in most cases, onset is within the first year of life. This condition was initially described in 1971 and in 2008 PCDH19 was identified as the underlying genetic etiology. This condition is the result of pathogenic loss-of-function variants that may be de novo or inherited from an affected mother or unaffected father and cellular interference has been hypothesized to be the culprit. Heterozygous females are symptomatic because of the presence of both wild-type and mutant cells that interfere with one another due to the production of different surface proteins, whereas nonmosaic hemizygous males produce a homogenous population of cells. Here, we review novel pathogenic variants in the PCDH19 gene since 2012 to date, and summarize any genotype-phenotype correlations.