High frequency of mosaic pathogenic variants in genes causing epilepsy-related neurodevelopmental disorders

PurposeMosaicism probably represents an underreported cause of genetic disorders due to detection challenges during routine molecular diagnostics. The purpose of this study was to evaluate the frequency of mosaicism detected by next-generation sequencing in genes associated with epilepsy-related neurodevelopmental disorders.MethodsWe conducted a retrospective analysis of 893 probands with epilepsy who had a multigene epilepsy panel or whole-exome sequencing performed in a clinical diagnostic laboratory and were positive for a pathogenic or likely pathogenic variant in one of nine genes (CDKL5, GABRA1, GABRG2, GRIN2B, KCNQ2, MECP2, PCDH19, SCN1A, or SCN2A). Parental results were available for 395 of these probands.ResultsMosaicism was most common in the CDKL5, PCDH19, SCN2A, and SCN1A genes. Mosaicism was observed in GABRA1, GABRG2, and GRIN2B, which previously have not been reported to have mosaicism, and also in KCNQ2 and MECP2. Parental mosaicism was observed for pathogenic variants in multiple genes including KCNQ2, MECP2, SCN1A, and SCN2A.ConclusionMosaic pathogenic variants were identified frequently in nine genes associated with various neurological conditions. Given the potential clinical ramifications, our findings suggest that next-generation sequencing diagnostic methods may be utilized when testing these genes in a diagnostic laboratory.     

Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing

PurposeNeurodevelopmental disorders (NDDs) often result from rare genetic variation, but genomic testing yield for NDDs remains below 50%, suggesting that clinically relevant variants may be missed by standard analyses. Here, we analyze “poison exons” (PEs), which are evolutionarily conserved alternative exons often absent from standard gene annotations. Variants that alter PE inclusion can lead to loss of function and may be highly penetrant contributors to disease.MethodsWe curated published RNA sequencing data from developing mouse cortex to define 1937 conserved PE regions potentially relevant to NDDs, and we analyzed variants found by genome sequencing in multiple NDD cohorts.ResultsAcross 2999 probands, we found 6 novel clinically relevant variants in PE regions. Five of these variants are in genes that are part of the sodium voltage-gated channel alpha subunit family (SCN1A, SCN2A, and SCN8A), which is associated with epilepsies. One variant is in SNRPB, associated with cerebrocostomandibular syndrome. These variants have moderate to high computational impact assessments, are absent from population variant databases, and in genes with gene-phenotype associations consistent with each probands reported features.ConclusionWith a very minimal increase in variant analysis burden (average of 0.77 variants per proband), annotation of PEs can improve diagnostic yield for NDDs and likely other congenital conditions.     

DNA methylation signature classification of rare disorders using publicly available methylation data

Disease-specific DNA methylation patterns (DNAm signatures) have been established for an increasing number of genetic disorders and represent a valuable tool for classification of genetic variants of uncertain significance (VUS). Sample size and batch effects are critical issues for establishing DNAm signatures, but their impact on the sensitivity and specificity of an already established DNAm signature has not previously been tested. Here, we assessed whether publicly available DNAm data can be employed to generate a binary machine learning classifier for VUS classification, and used variants in KMT2D, the gene associated with Kabuki syndrome, together with an existing DNAm signature as proof-of-concept. Using publicly available methylation data for training, a classifier for KMT2D variants was generated, and individuals with molecularly confirmed Kabuki syndrome and unaffected individuals could be correctly classified. The present study documents the clinical utility of a robust DNAm signature even for few affected individuals, and most importantly, underlines the importance of data sharing for improved diagnosis of rare genetic disorders.     

Detection of clinically relevant copy-number variants by exome sequencing in a large cohort of genetic disorders

PurposeCopy-number variation is a common source of genomic variation and an important genetic cause of disease. Microarray-based analysis of copy-number variants (CNVs) has become a first-tier diagnostic test for patients with neurodevelopmental disorders, with a diagnostic yield of 10–20%. However, for most other genetic disorders, the role of CNVs is less clear and most diagnostic genetic studies are generally limited to the study of single-nucleotide variants (SNVs) and other small variants. With the introduction of exome and genome sequencing, it is now possible to detect both SNVs and CNVs using an exome- or genome-wide approach with a single test.MethodsWe performed exome-based read-depth CNV screening on data from 2,603 patients affected by a range of genetic disorders for which exome sequencing was performed in a diagnostic setting.ResultsIn total, 123 clinically relevant CNVs ranging in size from 727 bp to 15.3 Mb were detected, which resulted in 51 conclusive diagnoses and an overall increase in diagnostic yield of ~2% (ranging from 0 to –5.8% per disorder).ConclusionsThis study shows that CNVs play an important role in a broad range of genetic disorders and that detection via exome-based CNV profiling results in an increase in the diagnostic yield without additional testing, bringing us closer to single-test genomics.Genet Med advance online publication 27 October 2016     

A model to infer the pathogenic significance of CDH1 germline missense variants

Germline mutations of the E-cadherin gene (CDH1) are involved in the tumorigenesis of hereditary diffuse gastric cancer (HDGC). Recent studies have highlighted the lifesaving potential of total prophylactic gastrectomy for CDH1 germline mutation carriers. In this regard, CDH1 germline mutations of the missense type represent a clinical burden in genetic counseling, as their pathogenic relevance is not straightforward. In this work, we have outlined a possible multivariate approach to infer the significance of such variants. We reviewed all HDGC-associated E-cadherin germline missense mutations reported to date. The information collected included: co-segregation of the mutation within pedigrees, frequency in healthy population control, recurrence in independent families, and functional in vitro and in silico data. We used the neighbor-joining method to group mutations according to the collected information and assessed the robustness of mutation clusters with a bootstrap test. CDH1 germline missense variants were classified according to the parameters defined in the multivariate analysis. This analysis allowed the distribution of the variants into two distinct groups: neutral variants vs mutations. The model described in this study provides an important tool that can ultimately improve the genetic counseling offered to the carriers of the germline CDH1 missense variants.     

Characterization of publicly available SNPs in the Korean population

Single-nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations and have a great potential for mapping studies of complex genetic traits. Currently a great deal of effort is invested in the identification of SNPs, and a large volume of data is already available through public databases (NCBI, NCI, WICGR, HGBASE). For an association mapping study, SNP allele frequencies in the population are critical. As an initial step toward construction of an SNP database of the Korean population, we have determined the allele frequencies of 300 cSNPs selected from the public database in 24 individuals. Among the tested markers, approximately 23% did not show polymorphism in the population. The results suggest that the ethnic and population based differences should be considered in the selection of SNPs for the study of complex diseases with association mapping methods.     

De novo heterozygous missense and loss‐of‐function variants in CDC42BPB are associated with a neurodevelopmental phenotype

CDC42BPB encodes MRCKβ (myotonic dystrophy‐related Cdc42‐binding kinase beta), a serine/threonine protein kinase, and a downstream effector of CDC42, which has recently been associated with Takenouchi‐Kosaki syndrome, an autosomal dominant neurodevelopmental disorder. We identified 12 heterozygous predicted deleterious variants in CDC42BPB (9 missense, 2 frameshift, and 1 nonsense) in 14 unrelated individuals (confirmed de novo in 11/14) with neurodevelopmental disorders including developmental delay/intellectual disability, autism, hypotonia, and structural brain abnormalities including cerebellar vermis hypoplasia and agenesis/hypoplasia of the corpus callosum. The frameshift and nonsense variants in CDC42BPB are expected to be gene‐disrupting and lead to haploinsufficiency via nonsense‐mediated decay. All missense variants are located in highly conserved and functionally important protein domains/regions: 3 are found in the protein kinase domain, 2 are in the citron homology domain, and 4 in a 20‐amino acid sequence between 2 coiled‐coil regions, 2 of which are recurrent. Future studies will help to delineate the natural history and to elucidate the underlying biological mechanisms of the missense variants leading to the neurodevelopmental and behavioral phenotypes.     

An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease–related patterns

More than 90% of genetic variants are rare in most modern sequencing studies, such as the Alzheimer''s Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data. Furthermore, 54% of the rare variants in ADSP WES are singletons. However, both single variant and unit-based tests are limited in their statistical power to detect an association between rare variants and phenotypes. To best use missense rare variants and investigate their biological effect, we examine their association with phenotypes in the context of protein structures. We developed a protein structure–based approach, protein optimized kernel evaluation of missense nucleotides (POKEMON), which evaluates rare missense variants based on their spatial distribution within a protein rather than their allele frequency. The hypothesis behind this test is that the three-dimensional spatial distribution of variants within a protein structure provides functional context to power an association test. POKEMON identified three candidate genes (TREM2, SORL1, and EXOC3L4) and another suggestive gene from the ADSP WES data. For TREM2 and SORL1, two known Alzheimer''s disease (AD) genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low-frequency risk variants within these genes. EXOC3L4 is a novel AD risk gene that has a cluster of variants primarily shared by case subjects around the Sec6 domain. This cluster is also validated in an independent replication data set and a validation data set with a larger sample size.

High-throughput DNA sequencing of diverse humans has identified millions of genetic variants, the vast majority of which are exceptionally rare. A survey of ∼60,000 individuals from the Exome Aggregation Consortium (ExAC) found that out of ∼7 million variants, 99% have a frequency <1% and 54% are singletons (Taliun et al. 2021). Similarly, in the Alzheimer''s Disease Sequencing Project (ADSP) whole-exome sequencing (WES) of ∼10,000 individuals, 97% of identified variants have a minor allele frequency <1%, and 23% are singletons (Butkiewicz et al. 2018). However, the effect of most rare variants on diseases of interest remains unknown because of insufficient statistical power to detect the associations between these variants and phenotypes.We hypothesized that rare missense variants contribute to common diseases by disrupting the protein function and are likely to form clustered or dispersed patterns within protein structures when examined in population-based studies. Therefore, incorporating spatial context will improve rare variant association tests. Prior studies have shown that missense variants show nonrandom patterns in protein structures, such as cancer-associated hotspot regions with a high density of missense somatic mutations (Tokheim et al. 2016). Our group (Sivley et al. 2018) also found that germline causal missense variants for Mendelian diseases show nonrandom patterns in three-dimensional (3D) space. These patterns include clusters that likely reflect disruption of a key functional region and dispersions that likely reflect depletion of variants within a sensitive protein core.To test this hypothesis within sequencing studies of disease traits, we developed a kernel function to quantify genetic similarity among individuals by using protein structure information. When two individuals have different missense variants distal in genomic coordinates but close in 3D protein structure, these individuals will be assigned a high genetic similarity through our kernel function. When applied over an entire data set, our kernel function captures differences in the spatial patterns of rare missense variants among cases and controls or over continuous traits. Using a statistical framework similar to SKAT (Wu et al. 2011), we test the association of rare variants with quantitative and dichotomous phenotypes using this structure-based kernel. We call this approach protein optimized kernel evaluation of missense nucleotides (POKEMON). We validated that POKEMON can identify trait associations with spatial patterns formed by missense variants both in simulation studies and real-world data.     

A novel classification system to predict the pathogenic effects of CHD7 missense variants in CHARGE syndrome

CHARGE syndrome is characterized by the variable occurrence of multisensory impairment, congenital anomalies, and developmental delay, and is caused by heterozygous mutations in the CHD7 gene. Correct interpretation of CHD7 variants is essential for genetic counseling. This is particularly difficult for missense variants because most variants in the CHD7 gene are private and a functional assay is not yet available. We have therefore developed a novel classification system to predict the pathogenic effects of CHD7 missense variants that can be used in a diagnostic setting. Our classification system combines the results from two computational algorithms (PolyPhen-2 and Align-GVGD) and the prediction of a newly developed structural model of the chromo- and helicase domains of CHD7 with segregation and phenotypic data. The combination of different variables will lead to a more confident prediction of pathogenicity than was previously possible. We have used our system to classify 145 CHD7 missense variants. Our data show that pathogenic missense mutations are mainly present in the middle of the CHD7 gene, whereas benign variants are mainly clustered in the 5' and 3' regions. Finally, we show that CHD7 missense mutations are, in general, associated with a milder phenotype than truncating mutations.     

Phagocytes,antibiotics and intracellular parasites: Are the experimental data clinically relevant?

Conclusion In recent years, a growing number of investigations have widened our understanding of the activity of antibiotics against microorganisms ingested by phagocytes. For the clinician, the most useful conclusion derived from these studies is that the serum pharmacokinetics of antibiotics are not necessarily good predictors of antibiotic activity in the patient. The newer macrolides (roxithromycin, clarithromycin, azithromycin) clearly illustrate this: they are clinically active against susceptible intracellular pathogens, they do not dispaly impressive serum levels, but they accumulate dramatically in phagocytes. Nevertheless, we are far from having a clear picture of phagocyte-microorganism-antibiotic interactions and an empiric approach remains necessary in the management of intracellular infections.     

Clinical versus automated assessments of morphological variants in twins with and without neurodevelopmental disorders

Physical examinations are recommended as part of a comprehensive evaluation for individuals with neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention–deficit/hyperactivity disorder. These examinations should include assessment for morphological variants. Previous studies have shown an increase in morphological variants in individuals with NDDs, particularly ASD, and that these variants may be present in greater amounts in individuals with genetic alterations. Unfortunately, assessment for morphological variants can be subjective and time‐consuming, and require a high degree of clinical expertise. Therefore, objective, automated methods of morphological assessment are desirable. This study compared the use of Face2Gene, an automated tool to explore facial morphological variants, to clinical consensus assessment, using a cohort of N = 290 twins enriched for NDDs (n = 135 with NDD diagnoses). Agreement between automated and clinical assessments were satisfactory to complete (78.3–100%). In our twin sample, individuals with NDDs did not have greater numbers of facial morphological variants when compared to those with typical development, nor when controlling for shared genetic and environmental factors within twin pairs. Common facial morphological variants in those with and without NDDs were similar and included thick upper lip vermilion, abnormality of the nasal tip, long face, and upslanted palpebral fissure. We conclude that although facial morphological variants can be assessed reliably in NDDs with automated tools like Face2Gene, clinical utility is limited when just exploring the facial region. Therefore, currently, automated assessments may best complement, rather than replace, in‐person clinical assessments.     

Predominance of pathogenic missense variants in the RAD51C gene occurring in breast and ovarian cancer families

RAD51C was defined by Meindl et al. in 2010 as a high-risk gene involved in hereditary breast and ovarian cancers. Although this role seems to be clear, nowadays there is controversy about the indication of including the gene in routine clinical genetic testing, due to the lower prevalence or the absence of mutations found in subsequent studies. Here, we present the results of a comprehensive mutational screening of the RAD51C gene in a large series of 785 Spanish breast and/or ovarian cancer families, which, in contrast to the various subsequent studies published to date, includes the functional characterization of suspicious missense variants as reported in the initial study. We have detected 1.3% mutations of RAD51C in breast and ovarian cancer families, while mutations in breast cancer only families seem to be very rare. More than half of the deleterious variants detected were of missense type, which highlights their significance in the gene, and suggest that RAD51C mutations may have been so far partially disregarded and their prevalence underestimated due to the lack of functional complementation assays. Our results provide new evidences, suggesting that the genetic testing of RAD51C should be considered for inclusion into the clinical setting, at least for breast and ovarian cancer families, and encourage re-evaluating its role incorporating functional assays.