Transcript expression-aware annotation improves rare variant interpretation.

The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.

The mutational constraint spectrum quantified from variation in 141,456 humans.

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity.

A major goal of biomedicine is to understand the function of every gene in the human genome. Loss-of-function mutations can disrupt both copies of a given gene in humans and phenotypic analysis of such 'human knockouts' can provide insight into gene function. Consanguineous unions are more likely to result in offspring carrying homozygous loss-of-function mutations. In Pakistan, consanguinity rates are notably high. Here we sequence the protein-coding regions of 10,503 adult participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS), designed to understand the determinants of cardiometabolic diseases in individuals from South Asia. We identified individuals carrying homozygous predicted loss-of-function (pLoF) mutations, and performed phenotypic analysis involving more than 200 biochemical and disease traits. We enumerated 49,138 rare (<1% minor allele frequency) pLoF mutations. These pLoF mutations are estimated to knock out 1,317 genes, each in at least one participant. Homozygosity for pLoF mutations at PLA2G7 was associated with absent enzymatic activity of soluble lipoprotein-associated phospholipase A2; at CYP2F1, with higher plasma interleukin-8 concentrations; at TREH, with lower concentrations of apoB-containing lipoprotein subfractions; at either A3GALT2 or NRG4, with markedly reduced plasma insulin C-peptide concentrations; and at SLC9A3R1, with mediators of calcium and phosphate signalling. Heterozygous deficiency of APOC3 has been shown to protect against coronary heart disease; we identified APOC3 homozygous pLoF carriers in our cohort. We recruited these human knockouts and challenged them with an oral fat load. Compared with family members lacking the mutation, individuals with APOC3 knocked out displayed marked blunting of the usual post-prandial rise in plasma triglycerides. Overall, these observations provide a roadmap for a 'human knockout project', a systematic effort to understand the phenotypic consequences of complete disruption of genes in humans.

Lessons learnt from multifaceted diagnostic approaches to the first 150 families in Victoria's Undiagnosed Diseases Program.

BACKGROUND: Clinical exome sequencing typically achieves diagnostic yields of 30%-57.5% in individuals with monogenic rare diseases. Undiagnosed diseases programmes implement strategies to improve diagnostic outcomes for these individuals. AIM: We share the lessons learnt from the first 3 years of the Undiagnosed Diseases Program-Victoria, an Australian programme embedded within a clinical genetics service in the state of Victoria with a focus on paediatric rare diseases. METHODS: We enrolled families who remained without a diagnosis after clinical genomic (panel, exome or genome) sequencing between 2016 and 2018. We used family-based exome sequencing (family ES), family-based genome sequencing (family GS), RNA sequencing (RNA-seq) and high-resolution chromosomal microarray (CMA) with research-based analysis. RESULTS: In 150 families, we achieved a diagnosis or strong candidate in 64 (42.7%) (37 in known genes with a consistent phenotype, 3 in known genes with a novel phenotype and 24 in novel disease genes). Fifty-four diagnoses or strong candidates were made by family ES, six by family GS with RNA-seq, two by high-resolution CMA and two by data reanalysis. CONCLUSION: We share our lessons learnt from the programme. Flexible implementation of multiple strategies allowed for scalability and response to the availability of new technologies. Broad implementation of family ES with research-based analysis showed promising yields post a negative clinical singleton ES. RNA-seq offered multiple benefits in family ES-negative populations. International data sharing strategies were critical in facilitating collaborations to establish novel disease-gene associations. Finally, the integrated approach of a multiskilled, multidisciplinary team was fundamental to having diverse perspectives and strategic decision-making.

O'Donnell-Luria-Rodan syndrome: description of a second multinational cohort and refinement of the phenotypic spectrum.

BACKGROUND: O'Donnell-Luria-Rodan syndrome (ODLURO) is an autosomal-dominant neurodevelopmental disorder caused by pathogenic, mostly truncating variants in KMT2E. It was first described by O'Donnell-Luria et al in 2019 in a cohort of 38 patients. Clinical features encompass macrocephaly, mild intellectual disability (ID), autism spectrum disorder (ASD) susceptibility and seizure susceptibility. METHODS: Affected individuals were ascertained at paediatric and genetic centres in various countries by diagnostic chromosome microarray or exome/genome sequencing. Patients were collected into a case cohort and were systematically phenotyped where possible. RESULTS: We report 18 additional patients from 17 families with genetically confirmed ODLURO. We identified 15 different heterozygous likely pathogenic or pathogenic sequence variants (14 novel) and two partial microdeletions of KMT2E. We confirm and refine the phenotypic spectrum of the KMT2E-related neurodevelopmental disorder, especially concerning cognitive development, with rather mild ID and macrocephaly with subtle facial features in most patients. We observe a high prevalence of ASD in our cohort (41%), while seizures are present in only two patients. We extend the phenotypic spectrum by sleep disturbances. CONCLUSION: Our study, bringing the total of known patients with ODLURO to more than 60 within 2 years of the first publication, suggests an unexpectedly high relative frequency of this syndrome worldwide. It seems likely that ODLURO, although just recently described, is among the more common single-gene aetiologies of neurodevelopmental delay and ASD. We present the second systematic case series of patients with ODLURO, further refining the mutational and phenotypic spectrum of this not-so-rare syndrome.

Characterization of Prevalence and Health Consequences of Uniparental Disomy in Four Million Individuals from the General Population.

Meiotic nondisjunction and resulting aneuploidy can lead to severe health consequences in humans. Aneuploidy rescue can restore euploidy but may result in uniparental disomy (UPD), the inheritance of both homologs of a chromosome from one parent with no representative copy from the other. Current understanding of UPD is limited to ∼3,300 case subjects for which UPD was associated with clinical presentation due to imprinting disorders or recessive diseases. Thus, the prevalence of UPD and its phenotypic consequences in the general population are unknown. We searched for instances of UPD across 4,400,363 consented research participants from the personal genetics company 23andMe, Inc., and 431,094 UK Biobank participants. Using computationally detected DNA segments identical-by-descent (IBD) and runs of homozygosity (ROH), we identified 675 instances of UPD across both databases. We estimate that UPD is twice as common as previously thought, and we present a machine-learning framework to detect UPD using ROH. While we find a nominally significant association between UPD of chromosome 22 and autism risk, we do not find significant associations between UPD and deleterious traits in the 23andMe database.

Heterozygous Variants in KMT2E Cause a Spectrum of Neurodevelopmental Disorders and Epilepsy.

We delineate a KMT2E-related neurodevelopmental disorder on the basis of 38 individuals in 36 families. This study includes 31 distinct heterozygous variants in KMT2E (28 ascertained from Matchmaker Exchange and three previously reported), and four individuals with chromosome 7q22.2-22.23 microdeletions encompassing KMT2E (one previously reported). Almost all variants occurred de novo, and most were truncating. Most affected individuals with protein-truncating variants presented with mild intellectual disability. One-quarter of individuals met criteria for autism. Additional common features include macrocephaly, hypotonia, functional gastrointestinal abnormalities, and a subtle facial gestalt. Epilepsy was present in about one-fifth of individuals with truncating variants and was responsive to treatment with anti-epileptic medications in almost all. More than 70% of the individuals were male, and expressivity was variable by sex; epilepsy was more common in females and autism more common in males. The four individuals with microdeletions encompassing KMT2E generally presented similarly to those with truncating variants, but the degree of developmental delay was greater. The group of four individuals with missense variants in KMT2E presented with the most severe developmental delays. Epilepsy was present in all individuals with missense variants, often manifesting as treatment-resistant infantile epileptic encephalopathy. Microcephaly was also common in this group. Haploinsufficiency versus gain-of-function or dominant-negative effects specific to these missense variants in KMT2E might explain this divergence in phenotype, but requires independent validation. Disruptive variants in KMT2E are an under-recognized cause of neurodevelopmental abnormalities.

Analysis of protein-coding genetic variation in 60,706 humans.

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

Apcdd1 is a dual BMP/Wnt inhibitor in the developing nervous system and skin.

Animal development and homeostasis depend on precise temporal and spatial intercellular signaling. Components shared between signaling pathways, generally thought to decrease specificity, paradoxically can also provide a solution to pathway coordination. Here we show that the Bone Morphogenetic Protein (BMP) and Wnt signaling pathways share Apcdd1 as a common inhibitor and that Apcdd1 is a taxon-restricted gene with novel domains and signaling functions. Previously, we showed that Apcdd1 inhibits Wnt signaling (Shimomura et al., 2010), here we find that Apcdd1 potently inhibits BMP signaling in body axis formation and neural differentiation in chicken, frog, zebrafish. Furthermore, we find that Apcdd1 has an evolutionarily novel protein domain. Our results from experiments and modeling suggest that Apcdd1 may coordinate the outputs of two signaling pathways that are central to animal development and human disease.

The Genetic Landscape of Diamond-Blackfan Anemia.

Diamond-Blackfan anemia (DBA) is a rare bone marrow failure disorder that affects 7 out of 1,000,000 live births and has been associated with mutations in components of the ribosome. In order to characterize the genetic landscape of this heterogeneous disorder, we recruited a cohort of 472 individuals with a clinical diagnosis of DBA and performed whole-exome sequencing (WES). We identified relevant rare and predicted damaging mutations for 78% of individuals. The majority of mutations were singletons, absent from population databases, predicted to cause loss of function, and located in 1 of 19 previously reported ribosomal protein (RP)-encoding genes. Using exon coverage estimates, we identified and validated 31 deletions in RP genes. We also observed an enrichment for extended splice site mutations and validated their diverse effects using RNA sequencing in cell lines obtained from individuals with DBA. Leveraging the size of our cohort, we observed robust genotype-phenotype associations with congenital abnormalities and treatment outcomes. We further identified rare mutations in seven previously unreported RP genes that may cause DBA, as well as several distinct disorders that appear to phenocopy DBA, including nine individuals with biallelic CECR1 mutations that result in deficiency of ADA2. However, no new genes were identified at exome-wide significance, suggesting that there are no unidentified genes containing mutations readily identified by WES that explain >5% of DBA-affected case subjects. Overall, this report should inform not only clinical practice for DBA-affected individuals, but also the design and analysis of rare variant studies for heterogeneous Mendelian disorders.

Insights into genetics, human biology and disease gleaned from family based genomic studies.

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

matchbox: An open-source tool for patient matching via the Matchmaker Exchange.

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene-disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy-to-use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here, we describe matchbox, which is an open-source, platform-independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME.

Megaloblastic Anemia Progressing to Severe Thrombotic Microangiopathy in Patients with Disordered Vitamin B12 Metabolism: Case Reports and Literature Review.

We describe 2 children with cobalamin G disease, a disorder of vitamin B12 metabolism with normal serum B12 levels. They presented with megaloblastic anemia progressing rapidly to severe thrombotic microangiopathy. In infants presenting with acute thrombotic microangiopathy, cobalamin disorders should be considered early as diagnosis and targeted treatment can be lifesaving.

Pathogenic ASXL1 somatic variants in reference databases complicate germline variant interpretation for Bohring-Opitz Syndrome.

The clinical interpretation of genetic variants has come to rely heavily on reference population databases such as the Exome Aggregation Consortium (ExAC) database. Pathogenic variants in genes associated with severe, pediatric-onset, highly penetrant, autosomal dominant conditions are assumed to be absent or rare in these databases. Exome sequencing of a 6-year-old female patient with seizures, developmental delay, dysmorphic features, and failure to thrive identified an ASXL1 variant previously reported as causative of Bohring-Opitz syndrome (BOS). Surprisingly, the variant was observed seven times in the ExAC database, presumably in individuals without BOS. Although the BOS phenotype fit, the presence of the variant in reference population databases introduced ambiguity in result interpretation. Review of the literature revealed that acquired somatic mosaicism of ASXL1 variants (including pathogenic variants) during hematopoietic clonal expansion can occur with aging in healthy individuals. We examined all ASXL1 truncating variants in the ExAC database and determined most are likely somatic. Failure to consider somatic mosaicism may lead to the inaccurate assumption that conditions like BOS have reduced penetrance, or the misclassification of potentially pathogenic variants.

Using high-resolution variant frequencies to empower clinical genome interpretation.

PurposeWhole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants.MethodsWe present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets.ResultsUsing the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001).ConclusionWe outline a statistically robust framework for assessing whether a variant is "too common" to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.