Assessment of the ExAC data set for the presence of individuals with pathogenic genotypes implicated in severe Mendelian pediatric disorders

Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants (pLoF) in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. We identified explanations for the presumed lack of disease manifestation in 701 of the variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders rarely occur, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue.

Genetic modifiers of rare variants in monogenic developmental disorder loci

Rare damaging variants in a large number of genes are known to cause monogenic developmental disorders (DDs) and have also been shown to cause milder subclinical phenotypes in population cohorts. Here, we show that carrying multiple (2-5) rare damaging variants across 599 dominant DD genes has an additive adverse effect on numerous cognitive and socioeconomic traits in UK Biobank, which can be partially counterbalanced by a higher educational attainment polygenic score (EA-PGS). Phenotypic deviators from expected EA-PGS could be partly explained by the enrichment or depletion of rare DD variants. Among carriers of rare DD variants, those with a DD-related clinical diagnosis had a substantially lower EA-PGS and more severe phenotype than those without a clinical diagnosis. Our results suggest that the overall burden of both rare and common variants can modify the expressivity of a phenotype, which may then influence whether an individual reaches the threshold for clinical disease.

Sterol O-Acyltransferase 1 (SOAT1): A Genetic Modifier of Niemann-Pick Disease, Type C1

Niemann-Pick disease type C1 (NPC1) is a lysosomal disorder due to impaired intracellular cholesterol transport out of the endolysosomal compartment.. Marked heterogeneity has been observed in individuals with the same NPC1 genotype, thus suggesting a significant effect of modifier genes. Prior work demonstrated that decreased SOAT1 activity decreased disease severity in an NPC1 mouse model. Thus, we hypothesized that a polymorphism associated with decreased SOAT1 expression might influence the NPC1 phenotype. Phenotyping and genomic sequencing of 117 individuals with NPC1 was performed as part of a Natural History trial. Phenotyping included determination of disease severity and disease burden. Significant clinical heterogeneity is present in individuals homozygous for the NPC1I1061T variant and in siblings. Analysis of the SOAT1 polymorphism, rs1044925 (A>C), showed a significant association of the C-allele with earlier age of neurological onset. The C-allele may be associated with a higher Annualized Severity Index Score as well as increased frequency of liver disease and seizures. A polymorphism associated with decreased expression of SOAT1 appears to be a genetic modifier of the NPC1 phenotype. This finding is consistent with prior data showing decreased phenotypic severity in Npc1-/-:Soat1-/- mice and supports efforts to investigate the potential of SOAT1 inhibitors as a potential therapy for NPC1.

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

STIGMA: Single-cell tissue-specific gene prioritization using machine learning

Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.

Exploring factors impacting haplotype-based noninvasive prenatal diagnosis for single-gene recessive disorders

Haplotype-based noninvasive prenatal diagnosis (NIPD) is applicable for various recessive single-gene disorders in proband families. However, a comprehensive exploration of critical factors influencing the assay performance, such as fetal fraction, informative single nucleotide polymorphism (SNP) count, and recombination events, has yet to be performed. It is critical to identify key factors affecting NIPD performance, including its accuracy and success rate, and their impact on clinical diagnostics to guide clinical practice. We conducted a prospective study, recruiting 219 proband families with singleton pregnancies at risk for eight recessive single-gene disorders (Duchenne muscular dystrophy, spinal muscular atrophy, phenylketonuria, methylmalonic acidemia, hemophilia A, hemophilia B, non-syndromic hearing loss, and congenital adrenal hyperplasia) at 7-14 weeks of gestation. Haplotype-based NIPD was performed by evaluating the relative haplotype dosage (RHDO) in maternal circulation, and the results were validated via invasive prenatal diagnosis or newborn follow-ups. Among the 219 families, the median gestational age at first blood draw was 8+5 weeks. Initial testing succeeded for 190 families and failed for 29 due to low fetal fraction (16), insufficient informative SNPs (9), and homologous recombination near pathogenic variation (4). Among low fetal fraction families, successful testing was achieved for 11 cases after a redraw, while 5 remained inconclusive. Test failures linked to insufficient informative SNPs correlated with linkage disequilibrium near the genes, with F8 and MMUT exhibiting the highest associated failure rates (14.3% and 25%, respectively). Homologous recombination was relatively frequent around the DMD and SMN1 genes (8.8% and 4.8%, respectively) but led to detection failure in only 44.4% (4/9) of such cases. All NIPD results from the 201 successful families were consistent with invasive diagnostic findings or newborn follow-up. Fetal fraction, informative SNPs count, and homologous recombination are pivotal to NIPD performance. Redrawing blood effectively improves the success rate for low fetal fraction samples. However, informative SNPs count and homologous recombination rates vary significantly across genes, necessitating careful consideration in clinical practice. We have designed an in silico method based on linkage disequilibrium data to predict the number of informative SNPs. This can identify genomic regions where there might be an insufficient number of SNPs, thereby guiding panel design. With these factors properly accounted for, NIPD is highly accurate and reliable.

Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

ClinVar and HGMD genomic variant classification accuracy has improved over time, as measured by implied disease burden

BACKGROUND

Curated databases of genetic variants assist clinicians and researchers in interpreting genetic variation. Yet, these databases contain some misclassified variants. It is unclear whether variant misclassification is abating as these databases rapidly grow and implement new guidelines.

METHODS

Using archives of ClinVar and HGMD, we investigated how variant misclassification has changed over 6 years, across different ancestry groups. We considered inborn errors of metabolism (IEMs) screened in newborns as a model system because these disorders are often highly penetrant with neonatal phenotypes. We used samples from the 1000 Genomes Project (1KGP) to identify individuals with genotypes that were classified by the databases as pathogenic. Due to the rarity of IEMs, nearly all such classified pathogenic genotypes indicate likely variant misclassification in ClinVar or HGMD.

RESULTS

While the false-positive rates of both ClinVar and HGMD have improved over time, HGMD variants currently imply two orders of magnitude more affected individuals in 1KGP than ClinVar variants. We observed that African ancestry individuals have a significantly increased chance of being incorrectly indicated to be affected by a screened IEM when HGMD variants are used. However, this bias affecting genomes of African ancestry was no longer significant once common variants were removed in accordance with recent variant classification guidelines. We discovered that ClinVar variants classified as Pathogenic or Likely Pathogenic are reclassified sixfold more often than DM or DM? variants in HGMD, which has likely resulted in ClinVar's lower false-positive rate.

CONCLUSIONS

Considering misclassified variants that have since been reclassified reveals our increasing understanding of rare genetic variation. We found that variant classification guidelines and allele frequency databases comprising genetically diverse samples are important factors in reclassification. We also discovered that ClinVar variants common in European and South Asian individuals were more likely to be reclassified to a lower confidence category, perhaps due to an increased chance of these variants being classified by multiple submitters. We discuss features for variant classification databases that would support their continued improvement.

Incidental molecular diagnoses and heterozygous risk alleles in a carrier screening cohort

PURPOSE

Expanded pan-ethnic carrier screening is an effective tool for the management of reproductive risk. However, growth in the number of conditions screened, in combination with increasingly more comprehensive test methodologies, can lead to the detection of genetic findings that may affect the health of the tested individual. The objective of this study was to investigate the frequency of pathogenic genotypes in a presumed healthy carrier screening cohort to facilitate broader discussions regarding disclosure of genetic information from carrier screening.

METHODS

A retrospective analysis of 73,755 targeted carrier screens was performed to identify individuals with pathogenic genotypes and heterozygous risk alleles.

RESULTS

In this study, we identified 79 individuals (0.11%) with pathogenic genotypes associated with moderate to profound autosomal recessive or X-linked conditions. In addition, 10 cases had chromosome X dosage abnormalities suggestive of a sex chromosome abnormality. Heterozygote risk alleles represented the majority of ancillary findings in this cohort, including 280 female carriers of FMR1 premutation alleles, 15 heterozygous females with pathogenic DMD variants, and 174 heterozygotes with pathogenic variants in genes that may confer increased risk for somatic malignancies in the heterozygous state.

CONCLUSION

These data suggest that nearly 1% of individuals undergoing carrier screening will have a finding that may require clinical evaluation or surveillance.

StabilitySort: assessment of protein stability changes on a genome-wide scale to prioritize potentially pathogenic genetic variation

SUMMARY

Missense mutations that change protein stability are strongly associated with human genetic disease. With the recent availability of predicted structures for all human proteins generated using the AlphaFold2 prediction model, genome-wide assessment of the stability effects of genetic variation can, for the first time, be easily performed. This facilitates the interrogation of personal genetic variation for potentially pathogenic effects through the application of stability metrics. Here, we present a novel tool to prioritize variants predicted to cause strong instability in essential proteins. We show that by filtering by ΔΔG values and then prioritizing by StabilitySort Z-scores, we are able to more accurately discriminate pathogenic, protein-destabilizing mutations from population variation, compared with other mutation effect predictors.

AVAILABILITY AND IMPLEMENTATION

StabilitySort is available as a web service (https://www.stabilitysort.org), as a data download for integration with other tools (https://www.stabilitysort.org/download) or can be deployed as a standalone system from source code (https://gitlab.com/baaron/StabilitySort).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Case Report: Biallelic Loss of Function ATM due to Pathogenic Synonymous and Novel Deep Intronic Variant c.1803-270T > G Identified by Genome Sequencing in a Child With Ataxia–Telangiectasia

Ataxia–telangiectasia (AT) is a complex neurodegenerative disease with an increased risk for bone marrow failure and malignancy. AT is caused by biallelic loss of function variants in ATM, which encodes a phosphatidylinositol 3-kinase that responds to DNA damage. Herein, we report a child with progressive ataxia, chorea, and genome instability, highly suggestive of AT. The clinical ataxia gene panel identified a maternal heterozygous synonymous variant (NM_000051.3: c.2250G > A), previously described to result in exon 14 skipping. Subsequently, trio genome sequencing led to the identification of a novel deep intronic variant [NG_009830.1(NM_000051.3): c.1803-270T > G] inherited from the father. Transcript analyses revealed that c.1803-270T > G results in aberrant inclusion of 56 base pairs of intron 11. In silico tests predicted a premature stop codon as a consequence, suggesting non-functional ATM; and DNA repair analyses confirmed functional loss of ATM. Our findings highlight the power of genome sequencing, considering deep intronic variants in undiagnosed rare disease patients.

Low frequency of treatable pediatric disease alleles in gnomAD: An opportunity for future genomic screening of newborns

Hematopoietic stem cell transplant (HSCT) can prevent progression of several genetic disorders. Although a subset of these disorders are identified on newborn screening panels, others are not identified until irreversible symptoms develop. Genetic testing is an efficient methodology to ascertain pre-symptomatic children, but the penetrance of risk-associated variants in the general population is not well understood. We developed a list of 127 genes associated with disorders treatable with HSCT. We identified likely pathogenic or pathogenic (LP/P) and loss-of-function (LoF) variants in these genes in the Genome Aggregation Database (gnomAD), a dataset containing exome and genome sequencing data from 141,456 healthy adults. Within gnomAD, we identified 59 individuals with a LP/P or LoF variant in 15 genes. Genes were associated with bone marrow failure syndromes, bleeding disorders, primary immunodeficiencies, osteopetrosis, metabolic disorders, and epidermolysis bullosa. In conclusion, few ostensibly healthy adults had genotypes associated with pediatric disorders treatable with HSCTs. Given that most of these disorders do not have biomarkers that could be cheaply and universally assessed on a standard newborn screen, our data suggest that genetic testing may be a complementary approach to traditional newborn screening methodology that has the potential to improve mortality and is not expected to lead to a high burden of false-positive results.

Incomplete Penetrance and Variable Expressivity: From Clinical Studies to Population Cohorts

The same genetic variant found in different individuals can cause a range of diverse phenotypes, from no discernible clinical phenotype to severe disease, even among related individuals. Such variants can be said to display incomplete penetrance, a binary phenomenon where the genotype either causes the expected clinical phenotype or it does not, or they can be said to display variable expressivity, in which the same genotype can cause a wide range of clinical symptoms across a spectrum. Both incomplete penetrance and variable expressivity are thought to be caused by a range of factors, including common variants, variants in regulatory regions, epigenetics, environmental factors, and lifestyle. Many thousands of genetic variants have been identified as the cause of monogenic disorders, mostly determined through small clinical studies, and thus, the penetrance and expressivity of these variants may be overestimated when compared to their effect on the general population. With the wealth of population cohort data currently available, the penetrance and expressivity of such genetic variants can be investigated across a much wider contingent, potentially helping to reclassify variants that were previously thought to be completely penetrant. Research into the penetrance and expressivity of such genetic variants is important for clinical classification, both for determining causative mechanisms of disease in the affected population and for providing accurate risk information through genetic counseling. A genotype-based definition of the causes of rare diseases incorporating information from population cohorts and clinical studies is critical for our understanding of incomplete penetrance and variable expressivity. This review examines our current knowledge of the penetrance and expressivity of genetic variants in rare disease and across populations, as well as looking into the potential causes of the variation seen, including genetic modifiers, mosaicism, and polygenic factors, among others. We also considered the challenges that come with investigating penetrance and expressivity.

Driving mosaicism: somatic variants in reference population databases and effect on variant interpretation in rare genetic disease

BACKGROUND

Genetic variation databases provide invaluable information on the presence and frequency of genetic variants in the 'untargeted' human population, aggregated with the primary goal to facilitate the interpretation of clinically important variants. The presence of somatic variants in such databases can affect variant assessment in undiagnosed rare disease (RD) patients. Previously, the impact of somatic mosaicism was only considered in relation to two Mendelian disease-associated genes. Here, we expand the analyses to identify additional mosaicism-prone genes in blood-derived reference population databases.

RESULTS

To identify additional mosaicism-prone genes relevant to RDs, we focused on known/previously established ClinVar pathogenic and likely pathogenic single-nucleotide variants, residing in genes associated with early onset, severe autosomal dominant diseases. We asked whether any of these variants are present in a higher-than-expected frequency in the reference population databases and whether there is evidence of somatic origin (i.e., allelic imbalance) rather than germline heterozygosity (~ half of the reads supporting alternative allele). The mosaicism-prone genes identified were further categorized according to the processes they are involved in. Beyond the previously reported ASXL1 and DNMT3A, we identified 7 additional autosomal dominant RD-associated genes with known pathogenic single-nucleotide variants present in the reference population databases and good evidence of allelic imbalance: BRAF, CBL, FGFR3, IDH2, KRAS, PTPN11 and SETBP1. From this group of 9 genes, the majority (n = 7) was important for hematopoiesis. In addition, 4 of these genes were involved in cell proliferation. Further assessment of the known 156 hematopoietic genes led to identification of 48 genes (21 not yet associated with RDs) with at least some evidence of mosaicism detectable in reference population databases.

CONCLUSIONS

These results stress the importance of considering genes involved in hematopoiesis and cell proliferation when interpreting the presence and frequency of genetic variants in blood-derived reference population databases, both public and private. This is especially important when considering new variants of uncertain significance in known hematopoietic/cell proliferation RD genes and future novel gene-disease associations involving this class of genes.

Revealing modifier variations characterizations for elucidating the genetic basis of human phenotypic variations

Epistatic interactions complicate the identification of variants involved in phenotypic effect. In-depth knowledge in modifiers and in pathogenic variants would benefit the mechanistic studies on the genetic basis of complex traits. We systematically compared the modifier variants which have evidence of modifier effect with the pathogenic variants from multiple angles. Our study found that genomic loci of modifier variations differ from pathogenic loci in many aspects, such as population genetics statistics, epigenetic features, evolutionary characteristics and functional properties of the variations. Genes containing modifier variation(s) exhibit higher probability of being haploinsufficient and higher probability of recessive disease causation, and they are relatively more important in network communication. Furthermore, we reinforced that co-expression analysis is an effective methodology to predict functional associations between modifier genes and their potential target genes. In many aspects, we detected statistically significant differences between modifier variants/genes and pathogenic variants/genes, and investigated relationships between modifiers and their potential targets. Our results offer some actionable insights that may provide appropriate guidelines to clinical genetics and researchers to elucidate the molecular mechanism underlying the human phenotypic variation.

Cases in Precision Medicine: Genetic Testing to Predict Future Risk for Disease in a Healthy Patient

Genetic testing is performed more routinely in clinical practice, and direct-to-consumer tests are widely available. It has obvious appeal as a preventive health measure. Clinicians and their healthy patients increasingly inquire about genetic testing as a tool for predicting diseases, such as cancer, heart disease, or dementia. Despite demonstrated utility for diagnosis in the setting of many diseases, genetic testing still has many limitations as a predictive tool for healthy persons. This article uses a hypothetical case to review key considerations for predictive genetic testing.

Synonymous variants in holoprosencephaly alter codon usage and impact the Sonic Hedgehog protein

Synonymous single nucleotide variants (sSNVs) have been implicated in various genetic disorders through alterations of pre-mRNA splicing, mRNA structure and miRNA regulation. However, their impact on synonymous codon usage and protein translation remains to be elucidated in clinical context. Here, we explore the functional impact of sSNVs in the Sonic Hedgehog (SHH) gene, identified in patients affected by holoprosencephaly, a congenital brain defect resulting from incomplete forebrain cleavage. We identified eight sSNVs in SHH, selectively enriched in holoprosencephaly patients as compared to healthy individuals, and systematically assessed their effect at both transcriptional and translational levels using a series of in silico and in vitro approaches. Although no evidence of impact of these sSNVs on splicing, mRNA structure or miRNA regulation was found, five sSNVs introduced significant changes in codon usage and were predicted to impact protein translation. Cell assays demonstrated that these five sSNVs are associated with a significantly reduced amount of the resulting protein, ranging from 5% to 23%. Inhibition of the proteasome rescued the protein levels for four out of five sSNVs, confirming their impact on protein stability and folding. Remarkably, we found a significant correlation between experimental values of protein reduction and computational measures of codon usage, indicating the relevance of in silico models in predicting the impact of sSNVs on translation. Considering the critical role of SHH in brain development, our findings highlight the clinical relevance of sSNVs in holoprosencephaly and underline the importance of investigating their impact on translation in human pathologies.

BICRA, a SWI/SNF Complex Member, Is Associated with BAF-Disorder Related Phenotypes in Humans and Model Organisms

SWI/SNF-related intellectual disability disorders (SSRIDDs) are rare neurodevelopmental disorders characterized by developmental disability, coarse facial features, and fifth digit/nail hypoplasia that are caused by pathogenic variants in genes that encode for members of the SWI/SNF (or BAF) family of chromatin remodeling complexes. We have identified 12 individuals with rare variants (10 loss-of-function, 2 missense) in the BICRA (BRD4 interacting chromatin remodeling complex-associated protein) gene, also known as GLTSCR1, which encodes a subunit of the non-canonical BAF (ncBAF) complex. These individuals exhibited neurodevelopmental phenotypes that include developmental delay, intellectual disability, autism spectrum disorder, and behavioral abnormalities as well as dysmorphic features. Notably, the majority of individuals lack the fifth digit/nail hypoplasia phenotype, a hallmark of most SSRIDDs. To confirm the role of BICRA in the development of these phenotypes, we performed functional characterization of the zebrafish and Drosophila orthologs of BICRA. In zebrafish, a mutation of bicra that mimics one of the loss-of-function variants leads to craniofacial defects possibly akin to the dysmorphic facial features seen in individuals harboring putatively pathogenic BICRA variants. We further show that Bicra physically binds to other non-canonical ncBAF complex members, including the BRD9/7 ortholog, CG7154, and is the defining member of the ncBAF complex in flies. Like other SWI/SNF complex members, loss of Bicra function in flies acts as a dominant enhancer of position effect variegation but in a more context-specific manner. We conclude that haploinsufficiency of BICRA leads to a unique SSRIDD in humans whose phenotypes overlap with those previously reported.

The GENDULF algorithm: mining transcriptomics to uncover modifier genes for monogenic diseases

Modifier genes are believed to account for the clinical variability observed in many Mendelian disorders, but their identification remains challenging due to the limited availability of genomics data from large patient cohorts. Here, we present GENDULF (GENetic moDULators identiFication), one of the first methods to facilitate prediction of disease modifiers using healthy and diseased tissue gene expression data. GENDULF is designed for monogenic diseases in which the mechanism is loss of function leading to reduced expression of the mutated gene. When applied to cystic fibrosis, GENDULF successfully identifies multiple, previously established disease modifiers, including EHF, SLC6A14, and CLCA1. It is then utilized in spinal muscular atrophy (SMA) and predicts U2AF1 as a modifier whose low expression correlates with higher SMN2 pre-mRNA exon 7 retention. Indeed, knockdown of U2AF1 in SMA patient-derived cells leads to increased full-length SMN2 transcript and SMN protein expression. Taking advantage of the increasing availability of transcriptomic data, GENDULF is a novel addition to existing strategies for prediction of genetic disease modifiers, providing insights into disease pathogenesis and uncovering novel therapeutic targets.

The Frequency of Discordant Variant Classification in the Human Gene Mutation Database: A Comparison of the American College of Medical Genetics and Genomics Guidelines and ClinVar

OBJECTIVE

Discordant variant classifications among public databases is one of the well-documented limitations when interpreting the pathogenicity of variants. The aim of this study is to investigate the level of germline variant misannotation from the Human Gene Mutation Database (HGMD) and the annotation concordance between databases.

METHODS

We used a total of 188,106 classified variants (disease-causing mutations [n = 179,454] and polymorphisms [n = 8652]) in 6466 genes from the HGMD. All variants were reanalyzed based on the American College of Medical Genetics and Genomics (ACMG) guidelines and compared to ClinVar database variants.

RESULTS

When variants were classified based on the ACMG guidelines, misclassification was observed in 3.47% (2289/65,896) of variants. The overall concordance between HGMD and ClinVar was 97.62% (52,499/53,780) of variants studied.

CONCLUSION

Variants in databases must be used with caution when variant pathogenicity is interpreted. This study reveals the frequency of misannotation of the HGMD variants and annotation concordance between databases in depth.

The Consequences of Abnormal Gene Dosage: Lessons from Chromosome 18

Accurate interpretation of genomic copy number variation (CNV) remains a challenge and has important consequences for both congenital and late-onset disease. Hemizygosity dosage characterization of the genes on chromosome 18 reveals a spectrum of outcomes ranging from no clinical effect, to risk factors for disease, to both low- and high-penetrance disease. These data are important for accurate and predictive clinical management. Additionally, the potential mechanisms of reduced penetrance due to dosage compensation are discussed as a key to understanding avenues for potential treatment. This review describes the chromosome 18 findings, and discusses the molecular mechanisms that allow haploinsufficiency, reduced penetrance, and dosage compensation.

Genotype-phenotype correlates of infantile-onset developmental & epileptic encephalopathy syndromes in South India: A single centre experience

INTRODUCTION

A paucity of literature exists on genotype- phenotype correlates of 'unknown-etiology' infantile-onset developmental-epileptic encephalopathies (DEE) from India. The primary objective was to explore the yield of genetic testing in identifying potential disease causing variants in electro-clinical phenotypes of DEE METHODS: An observational hospital-based study was undertaken on children with unexplained refractory seizure-onset ≤12 months age and developmental delay, whose families consented and underwent genetic testing during a three year time period (2016-2018) by next-generation sequencing (NGS) or multiplex ligand protein amplification. Yield was considered based on demonstration of pathogenic/likely pathogenic variants only and variants of unknown significance (VUS) were documented.

RESULTS

Pathogenic/likely pathogenic variants were identified in 26 (31.7 %) out of 82 children with DEE. These included those variants responsible for primarily DEE- 21(76.7 %); neuro-metabolic disorders- 3(18.6 %) and chromosomal deletions- 2(4.7 %). Of these patients, early-infantile epilepsy onset ≤ 6 months age was noted in 22(84.6 %). The DEE studied included Ohtahara syndrome associated with STXBP1 and SCN8A variants with yield of 50 % (2/4 tested); early myoclonic encephalopathy (no yield in 2); West syndrome with CDKL5, yield of 13.3 % (2/15 tested); epilepsy of infancy with migrating partial seizures due to CACNA1A and KCNT1 variants, yield of 67 % (2/3 tested); DEE-unclassified with KCNQ2, AP3B2, ZEB2, metabolic variants (SUOX, ALDH7A1, GLDC) and chromosome deletions (chr 1p36, chr2q24.3); yield of 32 % (8/25 tested). Patients with Dravet syndrome/Dravet-like phenotypes (N = 33) had variants in SCN1A (N = 10), SCN1B, CHD2; yield of 36.4 % (12/33 tested; 57.1 % from NGS). Eighteen patients with potential variants (SCN1A, SCN2A, SCN8A, KCNQ2, ALDH7A1 which also included VUS) could be offered targeted therapy.

CONCLUSIONS

Our study confirms a good yield of genetic testing in neonatal and infantile-onset DEE provided robust phenotyping of infants is attempted with prognostic and therapeutic implications, particularly relevant to centres with resource constraints.

Hypomorphic SI genetic variants are associated with childhood chronic loose stools

OBJECTIVE

The SI gene encodes the sucrase-isomaltase enzyme, a disaccharidase expressed in the intestinal brush border. Hypomorphic SI variants cause recessive congenital sucrase-isomaltase deficiency (CSID) and related gastrointestinal (GI) symptoms. Among children presenting with chronic, idiopathic loose stools, we assessed the prevalence of CSID-associated SI variants relative to the general population and the relative GI symptom burden associated with SI genotype within the study population.

METHODS

A prospective study conducted at 18 centers enrolled 308 non-Hispanic white children ≤18 years old who were experiencing chronic, idiopathic, loose stools at least once per week for >4 weeks. Data on demographics, GI symptoms, and genotyping for 37 SI hypomorphic variants were collected. Race/ethnicity-matched SI data from the Exome Aggregation Consortium (ExAC) database was used as the general population reference.

RESULTS

Compared with the general population, the cumulative prevalence of hypomorphic SI variants was significantly higher in the study population (4.5% vs. 1.3%, P < .01; OR = 3.5 [95% CI: 6.1, 2.0]). Within the study population, children with a hypomorphic SI variant had a more severe GI symptom burden than those without, including: more frequent episodes of loose stools (P < .01), higher overall stool frequency (P < .01), looser stool form (P = .01) and increased flatulence (P = .02).

CONCLUSION

Non-Hispanic white children with chronic idiopathic loose stools have a higher prevalence of CSID-associated hypomorphic SI variants than the general population. The GI symptom burden was greater among the study subjects with a hypomorphic SI variant than those without hypomorphic SI variants.

Current and future advances in genetic testing in systemic autoinflammatory diseases

Systemic autoinflammatory diseases (SAIDs) are a group of inflammatory disorders caused by dysregulation in the innate immune system that leads to enhanced immune responses. The clinical diagnosis of SAIDs can be difficult since individually these are rare diseases with considerable phenotypic overlap. Most SAIDs have a strong genetic background, but environmental and epigenetic influences can modulate the clinical phenotype. Molecular diagnosis has become essential for confirmation of clinical diagnosis. To date there are over 30 genes and a variety of modes of inheritance that have been associated with monogenic SAIDs. Mutations in the same gene can lead to very distinct phenotypes and can have different inheritance patterns. In addition, somatic mutations have been reported in several of these conditions. New genetic testing methods and databases are being developed to facilitate the molecular diagnosis of SAIDs, which is of major importance for treatment, prognosis and genetic counselling. The aim of this review is to summarize the latest advances in genetic testing for SAIDs and discuss potential obstacles that might arise during the molecular diagnosis of SAIDs.

Hardy-Weinberg Equilibrium in the Large Scale Genomic Sequencing Era

Hardy-Weinberg Equilibrium (HWE) is used to estimate the number of homozygous and heterozygous variant carriers based on its allele frequency in populations that are not evolving. Deviations from HWE in large population databases have been used to detect genotyping errors, which can result in extreme heterozygote excess (HetExc). However, HetExc might also be a sign of natural selection since recessive disease causing variants should occur less frequently in a homozygous state in the population, but may reach high allele frequency in a heterozygous state, especially if they are advantageous. We developed a filtering strategy to detect these variants and applied it on genome data from 137,842 individuals. The main limitations of this approach were quality of genotype calls and insufficient population sizes, whereas population structure and inbreeding can reduce sensitivity, but not precision, in certain populations. Nevertheless, we identified 161 HetExc variants in 149 genes, most of which were specific to African/African American populations (∼79.5%). Although the majority of them were not associated with known diseases, or were classified as clinically "benign," they were enriched in genes associated with autosomal recessive diseases. The resulting dataset also contained two known recessive disease causing variants with evidence of heterozygote advantage in the sickle-cell anemia (HBB) and cystic fibrosis (CFTR). Finally, we provide supporting in silico evidence of a novel heterozygote advantageous variant in the chromodomain helicase DNA binding protein 6 gene (CHD6; involved in influenza virus replication). We anticipate that our approach will aid the detection of rare recessive disease causing variants in the future.

Inherited Renal Tubulopathies-Challenges and Controversies

Electrolyte homeostasis is maintained by the kidney through a complex transport function mostly performed by specialized proteins distributed along the renal tubules. Pathogenic variants in the genes encoding these proteins impair this function and have consequences on the whole organism. Establishing a genetic diagnosis in patients with renal tubular dysfunction is a challenging task given the genetic and phenotypic heterogeneity, functional characteristics of the genes involved and the number of yet unknown causes. Part of these difficulties can be overcome by gathering large patient cohorts and applying high-throughput sequencing techniques combined with experimental work to prove functional impact. This approach has led to the identification of a number of genes but also generated controversies about proper interpretation of variants. In this article, we will highlight these challenges and controversies.

Genetic Modifiers and Rare Mendelian Disease

Despite advances in high-throughput sequencing that have revolutionized the discovery of gene defects in rare Mendelian diseases, there are still gaps in translating individual genome variation to observed phenotypic outcomes. While we continue to improve genomics approaches to identify primary disease-causing variants, it is evident that no genetic variant acts alone. In other words, some other variants in the genome (genetic modifiers) may alleviate (suppress) or exacerbate (enhance) the severity of the disease, resulting in the variability of phenotypic outcomes. Thus, to truly understand the disease, we need to consider how the disease-causing variants interact with the rest of the genome in an individual. Here, we review the current state-of-the-field in the identification of genetic modifiers in rare Mendelian diseases and discuss the potential for future approaches that could bridge the existing gap.

Pathogenic and Uncertain Genetic Variants Have Clinical Cardiac Correlates in Diverse Biobank Participants

Background

Genome sequencing coupled with electronic heath record data can uncover medically important genetic variation. Interpretation of rare genetic variation and its role in mediating cardiovascular phenotypes is confounded by variants of uncertain significance.

Methods and Results

We analyzed the whole genome sequence of 900 racially and ethnically diverse biobank participants selected from a single US center. Participants were equally divided among European, African, Hispanic, and mixed races/ethnicities. We evaluated the American College of Medical Genetics and Genomics medically actionable list of 59 genes, focusing on the cardiac genes. Variation was interpreted using the most recent reports in ClinVar, a database of medically relevant human variation. We identified 19 individuals with pathogenic or likely pathogenic variants in cardiac actionable genes (2%) and found evidence of related clinical correlates in the electronic health record. Participants of African ancestry, compared with those of European ancestry, had more variants of uncertain significance in the medically actionable genes including the 30 cardiac actionable genes, even when normalized to total variant count per person. Longitudinal measures of left ventricle size from ≈400 biobank participants (1723 patient‐years) were correlated with genetic findings. The presence of ≥1 uncertain variant in the actionable cardiac genes and a cardiomyopathy diagnosis correlated with increased left ventricular internal diameter in diastole and in systole. In particular, MYBPC3 was identified as a gene with excess variants of uncertain significance.

Conclusions

These data indicate that a subset of uncertain genetic variants may confer risk and should not be considered benign.

De novo pathogenic DNM1L variant in a patient diagnosed with atypical hereditary sensory and autonomic neuropathy

Background

Profiling the entire genome at base pair resolution in a single test offers novel insights into disease by means of dissection of genetic contributors to phenotypic features.

Methods

We performed genome sequencing for a patient who presented with atypical hereditary sensory and autonomic neuropathy, severe epileptic encephalopathy, global developmental delay, and growth hormone deficiency.

Results

Assessment of the variants detected by mapped sequencing reads followed by Sanger confirmation revealed that the proband is a compound heterozygote for rare variants within RETREG1 (FAM134B), a gene associated with a recessive form of hereditary sensory and autonomic neuropathy, but not with epileptic encephalopathy or global developmental delay. Further analysis of the data also revealed a heterozygous missense variant in DNM1L, a gene previously implicated in an autosomal dominant encephalopathy, epilepsy, and global developmental delay and confirmed by Sanger sequencing to be a de novo variant not present in parental genomes.

Conclusions

Our findings emphasize the importance of genome‐wide sequencing in patients with a well‐characterized genetic disease with atypical presentation. This approach reduces the potential for misdiagnoses.

Pathogenic WDFY3 variants cause neurodevelopmental disorders and opposing effects on brain size

The underpinnings of mild to moderate neurodevelopmental delay remain elusive, often leading to late diagnosis and interventions. Here, we present data on exome and genome sequencing as well as array analysis of 13 individuals that point to pathogenic, heterozygous, mostly de novo variants in WDFY3 (significant de novo enrichment P = 0.003) as a monogenic cause of mild and non-specific neurodevelopmental delay. Nine variants were protein-truncating and four missense. Overlapping symptoms included neurodevelopmental delay, intellectual disability, macrocephaly, and psychiatric disorders (autism spectrum disorders/attention deficit hyperactivity disorder). One proband presented with an opposing phenotype of microcephaly and the only missense-variant located in the PH-domain of WDFY3. Findings of this case are supported by previously published data, demonstrating that pathogenic PH-domain variants can lead to microcephaly via canonical Wnt-pathway upregulation. In a separate study, we reported that the autophagy scaffolding protein WDFY3 is required for cerebral cortical size regulation in mice, by controlling proper division of neural progenitors. Here, we show that proliferating cortical neural progenitors of human embryonic brains highly express WDFY3, further supporting a role for this molecule in the regulation of prenatal neurogenesis. We present data on Wnt-pathway dysregulation in Wdfy3-haploinsufficient mice, which display macrocephaly and deficits in motor coordination and associative learning, recapitulating the human phenotype. Consequently, we propose that in humans WDFY3 loss-of-function variants lead to macrocephaly via downregulation of the Wnt pathway. In summary, we present WDFY3 as a novel gene linked to mild to moderate neurodevelopmental delay and intellectual disability and conclude that variants putatively causing haploinsufficiency lead to macrocephaly, while an opposing pathomechanism due to variants in the PH-domain of WDFY3 leads to microcephaly.

Precision oncology: lessons learned and challenges for the future

The decreasing cost of and increasing capacity of DNA sequencing has led to vastly increased opportunities for population-level genomic studies to discover novel genomic alterations associated with both Mendelian and complex phenotypes. To translate genomic findings clinically, a number of health care institutions have worked collaboratively or individually to initiate precision medicine programs. These precision medicine programs involve designing patient enrollment systems, tracking electronic health records, building biobank repositories, and returning results with actionable matched therapies. As cancer is a paradigm for genetic diseases and new therapies are increasingly tailored to attack genetic susceptibilities in tumors, these precision medicine programs are largely driven by the urgent need to perform genetic profiling on cancer patients in real time. Here, we review the current landscape of precision oncology and highlight challenges to be overcome and examples of benefits to patients. Furthermore, we make suggestions to optimize future precision oncology programs based upon the lessons learned from these "first generation" early adopters.

Improving the diagnostic yield of exome- sequencing by predicting gene-phenotype associations using large-scale gene expression analysis

The diagnostic yield of exome and genome sequencing remains low (8-70%), due to incomplete knowledge on the genes that cause disease. To improve this, we use RNA-seq data from 31,499 samples to predict which genes cause specific disease phenotypes, and develop GeneNetwork Assisted Diagnostic Optimization (GADO). We show that this unbiased method, which does not rely upon specific knowledge on individual genes, is effective in both identifying previously unknown disease gene associations, and flagging genes that have previously been incorrectly implicated in disease. GADO can be run on www.genenetwork.nl by supplying HPO-terms and a list of genes that contain candidate variants. Finally, applying GADO to a cohort of 61 patients for whom exome-sequencing analysis had not resulted in a genetic diagnosis, yields likely causative genes for ten cases.

Uncovering Missing Heritability in Rare Diseases

The problem of 'missing heritability' affects both common and rare diseases hindering: discovery, diagnosis, and patient care. The 'missing heritability' concept has been mainly associated with common and complex diseases where promising modern technological advances, like genome-wide association studies (GWAS), were unable to uncover the complete genetic mechanism of the disease/trait. Although rare diseases (RDs) have low prevalence individually, collectively they are common. Furthermore, multi-level genetic and phenotypic complexity when combined with the individual rarity of these conditions poses an important challenge in the quest to identify causative genetic changes in RD patients. In recent years, high throughput sequencing has accelerated discovery and diagnosis in RDs. However, despite the several-fold increase (from ~10% using traditional to ~40% using genome-wide genetic testing) in finding genetic causes of these diseases in RD patients, as is the case in common diseases-the majority of RDs are also facing the 'missing heritability' problem. This review outlines the key role of high throughput sequencing in uncovering genetics behind RDs, with a particular focus on genome sequencing. We review current advances and challenges of sequencing technologies, bioinformatics approaches, and resources.

Impact of germline CTC1 alterations on telomere length in acquired bone marrow failure

Compound heterozygous germline mutations in CTC1 gene have been found in patients with atypical dyskeratosis congenita (DC), whereas heterozygous carriers are unaffected. Through screening of a large cohort of adult patients with acquired bone marrow failure syndromes, in addition to a DC case, we have also found extremely rare or novel heterozygous deleterious germline variants of CTC1 in patients with aplastic anaemia (AA; n = 5), paroxysmal nocturnal haemoglobinuria (PNH; n = 3) and myelodysplastic syndrome (MDS; n = 2). A compound heterozygous case of AA showed clonal evolution. Our results suggest that some of the inherited CTC1 variants may represent predisposition factors for acquired bone marrow failure.

Systematic evaluation of gene variants linked to hearing loss based on allele frequency threshold and filtering allele frequency

As the number of genes identified for linkage to hearing loss has been increasing and more public databases have become available, we aimed to systematically evaluate all variants reported for nonsyndromic hearing loss (NSHL) based on their allele frequencies (AFs) in the general population. Among the 3,549 variants in 97 NSHL genes reported as pathogenic/likely pathogenic in ClinVar and HGMD, 1,618 were found in public databases (gnomAD, ExAC, EVS, and 1000G). To evaluate the pathogenicity of these variants, we employed AF thresholds and NSHL-optimized ACMG guidelines. AF thresholds were determined using a high-resolution variant frequency framework and Hardy-Weinberg equilibrium calculation: 0.6% and 0.1% for recessive and dominant genes, respectively. Filtering AFs of variants linked to NSHL were obtained based on AFs reported in gnomAD and ExAC. We found that 48 variants in 23 genes had filtering AFs above the suggested thresholds and assumed that these variants might be benign based on their filtering AFs. 47 variants, except for one notorious high-frequency GJB2 mutation (c.109G > A; p.Val37Ile), were confirmed to be benign/likely benign by the NSHL-optimized ACMG guidelines. The proposed systematic approach will aid in precise evaluation of NSHL variant pathogenicity in the context of filtering AFs, AF thresholds, and NSHL-specific ACMG guidelines, thus improving NSHL diagnostics.

A Mild PUM1 Mutation Is Associated with Adult-Onset Ataxia, whereas Haploinsufficiency Causes Developmental Delay and Seizures

Certain mutations can cause proteins to accumulate in neurons, leading to neurodegeneration. We recently showed, however, that upregulation of a wild-type protein, Ataxin1, caused by haploinsufficiency of its repressor, the RNA-binding protein Pumilio1 (PUM1), also causes neurodegeneration in mice. We therefore searched for human patients with PUM1 mutations. We identified eleven individuals with either PUM1 deletions or de novo missense variants who suffer a developmental syndrome (Pumilio1-associated developmental disability, ataxia, and seizure; PADDAS). We also identified a milder missense mutation in a family with adult-onset ataxia with incomplete penetrance (Pumilio1-related cerebellar ataxia, PRCA). Studies in patient-derived cells revealed that the missense mutations reduced PUM1 protein levels by ∼25% in the adult-onset cases and by ∼50% in the infantile-onset cases; levels of known PUM1 targets increased accordingly. Changes in protein levels thus track with phenotypic severity, and identifying posttranscriptional modulators of protein expression should identify new candidate disease genes.

Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model

Background

We previously performed targeted sequencing of autism risk genes in probands from the Autism Clinical and Genetic Resources in China (ACGC) (phase I). Here, we expand this analysis to a larger cohort of patients (ACGC phase II) to better understand the prevalence, inheritance, and genotype-phenotype correlations of likely gene-disrupting (LGD) mutations for autism candidate genes originally identified in cohorts of European descent.

Methods

We sequenced 187 autism candidate genes in an additional 784 probands and 85 genes in 599 probands using single-molecule molecular inversion probes. We tested the inheritance of potentially pathogenic mutations, performed a meta-analysis of phase I and phase II data and combined our results with existing exome sequence data to investigate the phenotypes of carrier parents and patients with multiple hits in different autism risk genes.

Results

We validated recurrent, LGD, de novo mutations (DNMs) in 13 genes. We identified a potential novel risk gene (ZNF292), one novel gene with recurrent LGD DNMs (RALGAPB), as well as genes associated with macrocephaly (GIGYF2 and WDFY3). We identified the transmission of private LGD mutations in genes predominantly associated with DNMs and showed that parental carriers tended to share milder autism-related phenotypes. Patients that carried DNMs in two or more candidate genes show more severe phenotypes.

Conclusions

We identify new risk genes and transmission of deleterious mutations in genes primarily associated with DNMs. The fact that parental carriers show milder phenotypes and patients with multiple hits are more severe supports a multifactorial model of risk.

Assessment of coding region variants in Kuwaiti population: implications for medical genetics and population genomics

Consanguineous populations of the Arabian Peninsula have been underrepresented in global efforts that catalogue human exome variability. We sequenced 291 whole exomes of unrelated, healthy native Arab individuals from Kuwait to a median coverage of 45X and characterised 170,508 single-nucleotide variants (SNVs), of which 21.7% were ‘personal’. Up to 12% of the SNVs were novel and 36% were population-specific. Half of the SNVs were rare and 54% were missense variants. The study complemented the Greater Middle East Variome by way of reporting many additional Arabian exome variants. The study corroborated Kuwaiti population genetic substructures previously derived using genome-wide genotype data and illustrated the genetic relatedness among Kuwaiti population subgroups, Middle Eastern, European and Ashkenazi Jewish populations. The study mapped 112 rare and frequent functional variants relating to pharmacogenomics and disorders (recessive and common) to the phenotypic characteristics of Arab population. Comparative allele frequency data and carrier distributions of known Arab mutations for 23 disorders seen among Arabs, of putative OMIM-listed causal mutations for 12 disorders observed among Arabs but not yet characterized for genetic basis in Arabs, and of 17 additional putative mutations for disorders characterized for genetic basis in Arab populations are presented for testing in future Arab studies.

Population data improves variant interpretation in autosomal dominant polycystic kidney disease

PURPOSE

Autosomal dominant polycystic kidney disease (ADPKD) is a common adult-onset monogenic disorder, with prevalence of 1/1000. Population databases including ExAC have improved pathogenic variant prioritization in many diseases. Due to pseudogene homology of PKD1, the predominant ADPKD disease gene, and the variable disease severity and age of onset, we aimed to investigate the utility of ExAC for variant assessment in ADPKD.

METHODS

We assessed coverage and variant quality in the ExAC cohort and combined allele frequency and age data from the ExAC database (n = 60,706) with curated variants from 2000 ADPKD pedigrees (ADPKD Mutation Database).

RESULTS

Seventy-six percent of PKD1 and PKD2 were sequenced adequately for variant discovery and variant quality was high in ExAC. In ExAC, we identified 25 truncating and 393 previously reported disease-causing variants in PKD1 and PKD2, 6.9-fold higher than expected. Fifty-four different variants, previously classified as disease-causing, were observed in ≥5 participants in ExAC.

CONCLUSION

Our study demonstrates that many previously implicated disease-causing variants are too common, challenging their pathogenicity, or penetrance. The presence of protein-truncating variants in older participants in ExAC demonstrates the complexity of variant classification and highlights need for further study of prevalence and penetrance of this common monogenic disease.

Haploinsufficiency of CUX1 Causes Nonsyndromic Global Developmental Delay With Possible Catch-up Development

OBJECTIVE

Developmental delay (DD) with favorable intellectual outcome and mild intellectual disability (ID) are mostly considered to be of complex genetic and environmental origin, but, in fact, often remain unclear. We aimed at proving our assumption that also mild cases of DD and ID may be of monogenic etiology.

METHODS

We clinically evaluated 8 individuals and performed exome sequencing or array copy number analysis and identified variants in CUX1 as the likely cause. In addition, we included a case from the public database, DECIPHER.

RESULTS

All 9 individuals harbored heterozygous null-allele variants in CUX1, encoding the Cut-homeobox 1 transcription factor that is involved in regulation of dendritogenesis and cortical synapse formation in layer II to IV cortical neurons. Six variants arose de novo, while in one family the variant segregated with ID. Of the 9 included individuals, 2 were diagnosed with moderate ID, 3 with mild ID, and 3 showed a normal age-related intelligence at ages 4, 6, and 8 years after a previous history of significant DD.

INTERPRETATION

Our results suggest that null-allele variants, and thus haploinsufficiency of CUX1, cause an isolated phenotype of DD or ID with possible catch-up development. This illustrates that such a developmental course is not necessarily genetic complex, but may also be attributed to a monogenic cause. Ann Neurol 2018;84:200-207.

The coexistence of copy number variations (CNVs) and single nucleotide polymorphisms (SNPs) at a locus can result in distorted calculations of the significance in associating SNPs to disease

With the recent advance in genome-wide association studies (GWAS), disease-associated single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) have been extensively reported. Accordingly, the issue of incorrect identification of recombination events that can induce the distortion of multi-allelic or hemizygous variants has received more attention. However, the potential distorted calculation bias or significance of a detected association in a GWAS due to the coexistence of CNVs and SNPs in the same genomic region may remain under-recognized. Here we performed the association study within a congenital scoliosis (CS) cohort whose genetic etiology was recently elucidated as a compound inheritance model, including mostly one rare variant deletion CNV null allele and one common variant non-coding hypomorphic haplotype of the TBX6 gene. We demonstrated that the existence of a deletion in TBX6 led to an overestimation of the contribution of the SNPs on the hypomorphic allele. Furthermore, we generalized a model to explain the calculation bias, or distorted significance calculation for an association study, that can be 'induced' by CNVs at a locus. Meanwhile, overlapping between the disease-associated SNPs from published GWAS and common CNVs (overlap 10%) and pathogenic/likely pathogenic CNVs (overlap 99.69%) was significantly higher than the random distribution (p < 1 × 10^-6 and p = 0.034, respectively), indicating that such co-existence of CNV and SNV alleles might generally influence data interpretation and potential outcomes of a GWAS. We also verified and assessed the influence of colocalizing CNVs to the detection sensitivity of disease-associated SNP variant alleles in another adolescent idiopathic scoliosis (AIS) genome-wide association study. We proposed that detecting co-existent CNVs when evaluating the association signals between SNPs and disease traits could improve genetic model analyses and better integrate GWAS with robust Mendelian principles.

Functional variants in TBX2 are associated with a syndromic cardiovascular and skeletal developmental disorder

The 17 genes of the T-box family are transcriptional regulators that are involved in all stages of embryonic development, including craniofacial, brain, heart, skeleton and immune system. Malformation syndromes have been linked to many of the T-box genes. For example, haploinsufficiency of TBX1 is responsible for many structural malformations in DiGeorge syndrome caused by a chromosome 22q11.2 deletion. We report four individuals with an overlapping spectrum of craniofacial dysmorphisms, cardiac anomalies, skeletal malformations, immune deficiency, endocrine abnormalities and developmental impairments, reminiscent of DiGeorge syndrome, who are heterozygotes for TBX2 variants. The p.R20Q variant is shared by three affected family members in an autosomal dominant manner; the fourth unrelated individual has a de novo p.R305H mutation. Bioinformatics analyses indicate that these variants are rare and predict them to be damaging. In vitro transcriptional assays in cultured cells show that both variants result in reduced transcriptional repressor activity of TBX2. We also show that the variants result in reduced protein levels of TBX2. Heterologous over-expression studies in Drosophila demonstrate that both p.R20Q and p.R305H function as partial loss-of-function alleles. Hence, these and other data suggest that TBX2 is a novel candidate gene for a new multisystem malformation disorder.

The developmental-genetics of canalization

Canalization, or robustness to genetic or environmental perturbations, is fundamental to complex organisms. While there is strong evidence for canalization as an evolved property that varies among genotypes, the developmental and genetic mechanisms that produce this phenomenon are very poorly understood. For evolutionary biology, understanding how canalization arises is important because, by modulating the phenotypic variation that arises in response to genetic differences, canalization is a determinant of evolvability. For genetics of disease in humans and for economically important traits in agriculture, this subject is important because canalization is a potentially significant cause of missing heritability that confounds genomic prediction of phenotypes. We review the major lines of thought on the developmental-genetic basis for canalization. These fall into two groups. One proposes specific evolved molecular mechanisms while the other deals with robustness or canalization as a more general feature of development. These explanations for canalization are not mutually exclusive and they overlap in several ways. General explanations for canalization are more likely to involve emergent features of development than specific molecular mechanisms. Disentangling these explanations is also complicated by differences in perspectives between genetics and developmental biology. Understanding canalization at a mechanistic level will require conceptual and methodological approaches that integrate quantitative genetics and developmental biology.

Truncating Variants in NAA15 Are Associated with Variable Levels of Intellectual Disability, Autism Spectrum Disorder, and Congenital Anomalies

N-alpha-acetylation is a common co-translational protein modification that is essential for normal cell function in humans. We previously identified the genetic basis of an X-linked infantile lethal Mendelian disorder involving a c.109T>C (p.Ser37Pro) missense variant in NAA10, which encodes the catalytic subunit of the N-terminal acetyltransferase A (NatA) complex. The auxiliary subunit of the NatA complex, NAA15, is the dimeric binding partner for NAA10. Through a genotype-first approach with whole-exome or genome sequencing (WES/WGS) and targeted sequencing analysis, we identified and phenotypically characterized 38 individuals from 33 unrelated families with 25 different de novo or inherited, dominantly acting likely gene disrupting (LGD) variants in NAA15. Clinical features of affected individuals with LGD variants in NAA15 include variable levels of intellectual disability, delayed speech and motor milestones, and autism spectrum disorder. Additionally, mild craniofacial dysmorphology, congenital cardiac anomalies, and seizures are present in some subjects. RNA analysis in cell lines from two individuals showed degradation of the transcripts with LGD variants, probably as a result of nonsense-mediated decay. Functional assays in yeast confirmed a deleterious effect for two of the LGD variants in NAA15. Further supporting a mechanism of haploinsufficiency, individuals with copy-number variant (CNV) deletions involving NAA15 and surrounding genes can present with mild intellectual disability, mild dysmorphic features, motor delays, and decreased growth. We propose that defects in NatA-mediated N-terminal acetylation (NTA) lead to variable levels of neurodevelopmental disorders in humans, supporting the importance of the NatA complex in normal human development.

Integration of genomics and metabolomics for prioritization of rare disease variants: a 2018 literature review

Many inborn errors of metabolism (IEMs) are amenable to treatment; therefore, early diagnosis and treatment is imperative. Despite recent advances, the genetic basis of many metabolic phenotypes remains unknown. For discovery purposes, whole exome sequencing (WES) variant prioritization coupled with clinical and bioinformatics expertise is the primary method used to identify novel disease-causing variants; however, causation is often difficult to establish due to the number of plausible variants. Integrated analysis of untargeted metabolomics (UM) and WES or whole genome sequencing (WGS) data is a promising systematic approach for identifying disease-causing variants. In this review, we provide a literature-based overview of UM methods utilizing liquid chromatography mass spectrometry (LC-MS), and assess approaches to integrating WES/WGS and LC-MS UM data for the discovery and prioritization of variants causing IEMs. To embed this integrated -omics approach in the clinic, expansion of gene-metabolite annotations and metabolomic feature-to-metabolite mapping methods are needed.

MoBiDiC Prioritization Algorithm, a Free, Accessible, and Efficient Pipeline for Single-Nucleotide Variant Annotation and Prioritization for Next-Generation Sequencing Routine Molecular Diagnosis

Interpretation of next-generation sequencing constitutes the main limitation of molecular diagnostics. In diagnosing myopathies and muscular dystrophies, another issue is efficiency in predicting the pathogenicity of variants identified in large genes, especially TTN; current in silico prediction tools show limitations in predicting and ranking the numerous variants of such genes. We propose a variant-prioritization tool, the MoBiDiCprioritization algorithm (MPA). MPA is based on curated interpretation of data on previously reported variants, biological assumptions, and splice and missense predictors, and is used to prioritize all types of single-nucleotide variants. MPA was validated by comparing its sensitivity and specificity to those of dbNSFP database prediction tools, using a data set composed of DYSF, DMD, LMNA, NEB, and TTN variants extracted from expert-reviewed and ExAC databases. MPA obtained the best annotation rates for missense and splice variants. As MPA aggregates the results from several predictors, individual predictor errors are counterweighted, improving the sensitivity and specificity of missense and splice variant predictions. We propose a sequential use of MPA, beginning with the selection of variants with higher scores and followed by, in the absence of candidate pathologic variants, consideration of variants with lower scores. We provide scripts and documentation for free academic use and a validated annotation pipeline scaled for panel and exome sequencing to prioritize single-nucleotide variants from a VCF file.