A genomic mutational constraint map using variation in 76,156 human genomes.

The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders1-4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)-the largest public open-access human genome allele frequency reference dataset-and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation.

Pathogenic variants in KMT2C result in a neurodevelopmental disorder distinct from Kleefstra and Kabuki syndromes.

Trithorax-related H3K4 methyltransferases, KMT2C and KMT2D, are critical epigenetic modifiers. Haploinsufficiency of KMT2C was only recently recognized as a cause of neurodevelopmental disorder (NDD), so the clinical and molecular spectrums of the KMT2C-related NDD (now designated as Kleefstra syndrome 2) are largely unknown. We ascertained 98 individuals with rare KMT2C variants, including 75 with protein-truncating variants (PTVs). Notably, ∼15% of KMT2C PTVs were inherited. Although the most highly expressed KMT2C transcript consists of only the last four exons, pathogenic PTVs were found in almost all the exons of this large gene. KMT2C variant interpretation can be challenging due to segmental duplications and clonal hematopoesis-induced artifacts. Using samples from 27 affected individuals, divided into discovery and validation cohorts, we generated a moderate strength disorder-specific KMT2C DNA methylation (DNAm) signature and demonstrate its utility in classifying non-truncating variants. Based on 81 individuals with pathogenic/likely pathogenic variants, we demonstrate that the KMT2C-related NDD is characterized by developmental delay, intellectual disability, behavioral and psychiatric problems, hypotonia, seizures, short stature, and other comorbidities. The facial module of PhenoScore, applied to photographs of 34 affected individuals, reveals that the KMT2C-related facial gestalt is significantly different from the general NDD population. Finally, using PhenoScore and DNAm signatures, we demonstrate that the KMT2C-related NDD is clinically and epigenetically distinct from Kleefstra and Kabuki syndromes. Overall, we define the clinical features, molecular spectrum, and DNAm signature of the KMT2C-related NDD and demonstrate they are distinct from Kleefstra and Kabuki syndromes highlighting the need to rename this condition.

Neurodevelopmental Disorder Caused by Deletion of CHASERR, a lncRNA Gene.

CHASERR encodes a human long noncoding RNA (lncRNA) adjacent to CHD2, a coding gene in which de novo loss-of-function variants cause developmental and epileptic encephalopathy. Here, we report our findings in three unrelated children with a syndromic, early-onset neurodevelopmental disorder, each of whom had a de novo deletion in the CHASERR locus. The children had severe encephalopathy, shared facial dysmorphisms, cortical atrophy, and cerebral hypomyelination - a phenotype that is distinct from the phenotypes of patients with CHD2 haploinsufficiency. We found that the CHASERR deletion results in increased CHD2 protein abundance in patient-derived cell lines and increased expression of the CHD2 transcript in cis. These findings indicate that CHD2 has bidirectional dosage sensitivity in human disease, and we recommend that other lncRNA-encoding genes be evaluated, particularly those upstream of genes associated with mendelian disorders. (Funded by the National Human Genome Research Institute and others.).

Advanced variant classification framework reduces the false positive rate of predicted loss-of-function variants in population sequencing data.

Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines' PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 genes associated with autosomal-recessive disease from the Genome Aggregation Database (gnomAD v.2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in a low proportion expressed across transcripts (pext) scored region, or the presence of cryptic in-frame splice rescues. Variants predicted to evade LoF or to be potential artifacts were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of pLoF variants predicted as likely not LoF/not LoF, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Beyond the exome: What's next in diagnostic testing for Mendelian conditions.

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

Bi-allelic TTI1 variants cause an autosomal-recessive neurodevelopmental disorder with microcephaly.

Telomere maintenance 2 (TELO2), Tel2 interacting protein 2 (TTI2), and Tel2 interacting protein 1 (TTI1) are the three components of the conserved Triple T (TTT) complex that modulates activity of phosphatidylinositol 3-kinase-related protein kinases (PIKKs), including mTOR, ATM, and ATR, by regulating the assembly of mTOR complex 1 (mTORC1). The TTT complex is essential for the expression, maturation, and stability of ATM and ATR in response to DNA damage. TELO2- and TTI2-related bi-allelic autosomal-recessive (AR) encephalopathies have been described in individuals with moderate to severe intellectual disability (ID), short stature, postnatal microcephaly, and a movement disorder (in the case of variants within TELO2). We present clinical, genomic, and functional data from 11 individuals in 9 unrelated families with bi-allelic variants in TTI1. All present with ID, and most with microcephaly, short stature, and a movement disorder. Functional studies performed in HEK293T cell lines and fibroblasts and lymphoblastoid cells derived from 4 unrelated individuals showed impairment of the TTT complex and of mTOR pathway activity which is improved by treatment with Rapamycin. Our data delineate a TTI1-related neurodevelopmental disorder and expand the group of disorders related to the TTT complex.

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

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.

A structural variation reference for medical and population genetics.

Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

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.

Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria.

Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as "supporting" level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying moderate and several reached strong evidence levels. One tool reached very strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

Recurrent de novo missense variants across multiple histone H4 genes underlie a neurodevelopmental syndrome.

Chromatin is essentially an array of nucleosomes, each of which consists of the DNA double-stranded fiber wrapped around a histone octamer. This organization supports cellular processes such as DNA replication, DNA transcription, and DNA repair in all eukaryotes. Human histone H4 is encoded by fourteen canonical histone H4 genes, all differing at the nucleotide level but encoding an invariant protein. Here, we present a cohort of 29 subjects with de novo missense variants in six H4 genes (H4C3, H4C4, H4C5, H4C6, H4C9, and H4C11) identified by whole-exome sequencing and matchmaking. All individuals present with neurodevelopmental features of intellectual disability and motor and/or gross developmental delay, while non-neurological features are more variable. Ten amino acids are affected, six recurrently, and are all located within the H4 core or C-terminal tail. These variants cluster to specific regions of the core H4 globular domain, where protein-protein interactions occur with either other histone subunits or histone chaperones. Functional consequences of the identified variants were evaluated in zebrafish embryos, which displayed abnormal general development, defective head organs, and reduced body axis length, providing compelling evidence for the causality of the reported disorder(s). While multiple developmental syndromes have been linked to chromatin-associated factors, missense-bearing histone variants (e.g., H3 oncohistones) are only recently emerging as a major cause of pathogenicity. Our findings establish a broader involvement of H4 variants in developmental syndromes.

Monoallelic de novo variants in DDX17 cause a neurodevelopmental disorder.

DDX17 is an RNA helicase shown to be involved in critical processes during the early phases of neuronal differentiation. Globally, we compiled a case-series of 11 patients with neurodevelopmental phenotypes harbouring de novo monoallelic variants in DDX17. All 11 patients in our case series had a neurodevelopmental phenotype, whereby intellectual disability, delayed speech and language, and motor delay predominated. We performed in utero cortical electroporation in the brain of developing mice, assessing axon complexity and outgrowth of electroporated neurons, comparing wild-type and Ddx17 knockdown. We then undertook ex vivo cortical electroporation on neuronal progenitors to quantitatively assess axonal development at a single cell resolution. Mosaic ddx17 crispants and heterozygous knockouts in Xenopus tropicalis were generated for assessment of morphology, behavioural assays, and neuronal outgrowth measurements. We further undertook transcriptomic analysis of neuroblastoma SH-SY5Y cells, to identify differentially expressed genes in DDX17-KD cells compared to controls. Knockdown of Ddx17 in electroporated mouse neurons in vivo showed delayed neuronal migration as well as decreased cortical axon complexity. Mouse primary cortical neurons revealed reduced axon outgrowth upon knockdown of Ddx17 in vitro. The axon outgrowth phenotype was replicated in crispant ddx17 tadpoles and in heterozygotes. Heterozygous tadpoles had clear neurodevelopmental defects and showed an impaired neurobehavioral phenotype. Transcriptomic analysis identified a statistically significant number of differentially expressed genes involved in neurodevelopmental processes in DDX17-KD cells compared to control cells. We have identified potential neurodevelopment disease-causing variants in a gene not previously associated with genetic disease, DDX17. We provide evidence for the role of the gene in neurodevelopment in both mammalian and non-mammalian species and in controlling the expression of key neurodevelopment genes.

Unique variants in CLCN3, encoding an endosomal anion/proton exchanger, underlie a spectrum of neurodevelopmental disorders.

The genetic causes of global developmental delay (GDD) and intellectual disability (ID) are diverse and include variants in numerous ion channels and transporters. Loss-of-function variants in all five endosomal/lysosomal members of the CLC family of Cl- channels and Cl-/H+ exchangers lead to pathology in mice, humans, or both. We have identified nine variants in CLCN3, the gene encoding CIC-3, in 11 individuals with GDD/ID and neurodevelopmental disorders of varying severity. In addition to a homozygous frameshift variant in two siblings, we identified eight different heterozygous de novo missense variants. All have GDD/ID, mood or behavioral disorders, and dysmorphic features; 9/11 have structural brain abnormalities; and 6/11 have seizures. The homozygous variants are predicted to cause loss of ClC-3 function, resulting in severe neurological disease similar to the phenotype observed in Clcn3-/- mice. Their MRIs show possible neurodegeneration with thin corpora callosa and decreased white matter volumes. Individuals with heterozygous variants had a range of neurodevelopmental anomalies including agenesis of the corpus callosum, pons hypoplasia, and increased gyral folding. To characterize the altered function of the exchanger, electrophysiological analyses were performed in Xenopus oocytes and mammalian cells. Two variants, p.Ile607Thr and p.Thr570Ile, had increased currents at negative cytoplasmic voltages and loss of inhibition by luminal acidic pH. In contrast, two other variants showed no significant difference in the current properties. Overall, our work establishes a role for CLCN3 in human neurodevelopment and shows that both homozygous loss of ClC-3 and heterozygous variants can lead to GDD/ID and neuroanatomical abnormalities.

A form of muscular dystrophy associated with pathogenic variants in JAG2.

JAG2 encodes the Notch ligand Jagged2. The conserved Notch signaling pathway contributes to the development and homeostasis of multiple tissues, including skeletal muscle. We studied an international cohort of 23 individuals with genetically unsolved muscular dystrophy from 13 unrelated families. Whole-exome sequencing identified rare homozygous or compound heterozygous JAG2 variants in all 13 families. The identified bi-allelic variants include 10 missense variants that disrupt highly conserved amino acids, a nonsense variant, two frameshift variants, an in-frame deletion, and a microdeletion encompassing JAG2. Onset of muscle weakness occurred from infancy to young adulthood. Serum creatine kinase (CK) levels were normal or mildly elevated. Muscle histology was primarily dystrophic. MRI of the lower extremities revealed a distinct, slightly asymmetric pattern of muscle involvement with cores of preserved and affected muscles in quadriceps and tibialis anterior, in some cases resembling patterns seen in POGLUT1-associated muscular dystrophy. Transcriptome analysis of muscle tissue from two participants suggested misregulation of genes involved in myogenesis, including PAX7. In complementary studies, Jag2 downregulation in murine myoblasts led to downregulation of multiple components of the Notch pathway, including Megf10. Investigations in Drosophila suggested an interaction between Serrate and Drpr, the fly orthologs of JAG1/JAG2 and MEGF10, respectively. In silico analysis predicted that many Jagged2 missense variants are associated with structural changes and protein misfolding. In summary, we describe a muscular dystrophy associated with pathogenic variants in JAG2 and evidence suggests a disease mechanism related to Notch pathway dysfunction.

A gene pathogenicity tool "GenePy" identifies missed biallelic diagnoses in the 100,000 Genomes Project.

PURPOSE: The 100,000 Genomes Project diagnosed a quarter of affected participants, but 26% of diagnoses were not on the applied gene panel(s); with many being de novo variants. Assessing biallelic variants without a gene panel is more challenging. METHODS: We sought to identify missed biallelic diagnoses using GenePy, which incorporates allele frequency, zygosity, and a user-defined deleterious metric, generating an aggregate GenePy score per gene, per participant. We calculated GenePy scores for 2862 recessive disease genes in 78,216 100,000 Genomes Project participants. For each gene, we ranked participant GenePy scores and scrutinized affected participants without a diagnosis, whose scores ranked among the top 5 for each gene. In cases which participant phenotypes overlapped with the disease gene of interest, we extracted rare variants and applied phase, ClinVar, and ACMG classification. RESULTS: 3184 affected individuals without a molecular diagnosis had a top-5-ranked GenePy score and 682 of 3184 (21%) had phenotypes overlapping with a top-ranking gene. In 122 of 669 (18%) phenotype-matched cases (excluding 13 withdrawn participants), we identified a putative missed diagnosis (2.2% of all undiagnosed participants). A further 334 of 669 (50%) cases have a possible missed diagnosis but require functional validation. CONCLUSION: Applying GenePy at scale has identified 456 potential diagnoses, demonstrating the value of novel diagnostic strategies.

Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations.

PURPOSE: To investigate the number of rare missense variants observed in human genome sequences by ACMG/AMP PP3/BP4 evidence strength, following the ClinGen-calibrated PP3/BP4 computational recommendations. METHODS: Missense variants from the genome sequences of 300 probands from the Rare Genomes Project with suspected rare disease were analyzed using computational prediction tools that were able to reach PP3_Strong and BP4_Moderate evidence strengths (BayesDel, MutPred2, REVEL, and VEST4). The numbers of variants at each evidence strength were analyzed across disease-associated genes and genome-wide. RESULTS: From a median of 75.5 rare (≤1% allele frequency) missense variants in disease-associated genes per proband, a median of one reached PP3_Strong, 3-5 PP3_Moderate, and 3-5 PP3_Supporting. Most were allocated BP4 evidence (median 41-49 per proband) or were indeterminate (median 17.5-19 per proband). Extending the analysis to all protein-coding genes genome-wide, the number of variants reaching PP3_Strong score thresholds increased approximately 2.6-fold compared with disease-associated genes, with a median per proband of 1-3 PP3_Strong, 8-16 PP3_Moderate, and 10-17 PP3_Supporting. CONCLUSION: A small number of variants per proband reached PP3_Strong and PP3_Moderate in 3424 disease-associated genes. Although not the intended use of the recommendations, this was also observed genome-wide. Use of PP3/BP4 evidence as recommended from calibrated computational prediction tools in the clinical diagnostic laboratory is unlikely to inappropriately contribute to the classification of an excessive number of variants as pathogenic or likely pathogenic by ACMG/AMP rules.

Expanding the genetics and phenotypes of ocular congenital cranial dysinnervation disorders.

PURPOSE: To identify genetic etiologies and genotype/phenotype associations for unsolved ocular congenital cranial dysinnervation disorders (oCCDDs). METHODS: We coupled phenotyping with exome or genome sequencing of 467 probands (550 affected and 1108 total individuals) with genetically unsolved oCCDDs, integrating analyses of pedigrees, human and animal model phenotypes, and de novo variants to identify rare candidate single nucleotide variants, insertion/deletions, and structural variants disrupting protein-coding regions. Prioritized variants were classified for pathogenicity and evaluated for genotype/phenotype correlations. RESULTS: Analyses elucidated phenotypic subgroups, identified pathogenic/likely pathogenic variant(s) in 43/467 probands (9.2%), and prioritized variants of uncertain significance in 70/467 additional probands (15.0%). These included known and novel variants in established oCCDD genes, genes associated with syndromes that sometimes include oCCDDs (e.g., MYH10, KIF21B, TGFBR2, TUBB6), genes that fit the syndromic component of the phenotype but had no prior oCCDD association (e.g., CDK13, TGFB2), genes with no reported association with oCCDDs or the syndromic phenotypes (e.g., TUBA4A, KIF5C, CTNNA1, KLB, FGF21), and genes associated with oCCDD phenocopies that had resulted in misdiagnoses. CONCLUSION: This study suggests that unsolved oCCDDs are clinically and genetically heterogeneous disorders often overlapping other Mendelian conditions and nominates many candidates for future replication and functional studies.

Interpreting variants in genes affected by clonal hematopoiesis in population data.

Reference population databases like the Genome Aggregation Database (gnomAD) have improved our ability to interpret the human genome. Variant frequencies and frequency-derived tools (such as depletion scores) have become fundamental to variant interpretation and the assessment of variant-gene-disease relationships. Clonal hematopoiesis (CH) obstructs variant interpretation as somatic variants that provide proliferative advantage will affect variant frequencies, depletion scores, and downstream filtering. Further, default filtering of variants or genes associated with CH risks filtering bona fide germline variants as variants associated with CH can also cause Mendelian conditions. Here, we provide our insights on interpreting population variant data in genes affected by clonal hematopoiesis, as well as recommendations for careful review of 36 established CH genes associated with neurodevelopmental conditions.