Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity.

The spatial and temporal domain of a gene's expression can range from ubiquitous to highly specific. Quantifying the degree to which this expression is unique to a specific tissue or developmental timepoint can provide insight into the etiology of genetic diseases. However, quantifying specificity remains challenging as measures of specificity are sensitive to similarity between samples in the sample set. For example, in the Gene-Tissue Expression project (GTEx), brain subregions are overrepresented at 13 of 54 (24%) unique tissues sampled. In this dataset, existing specificity measures have a decreased ability to identify genes specific to the brain relative to other organs. To solve this problem, we leverage sample similarity information to weight samples such that overrepresented tissues do not have an outsized effect on specificity estimates. We test this reweighting procedure on 4 measures of specificity, Z-score, Tau, Tsi and Gini, in the GTEx data and in single cell datasets for zebrafish and mouse. For all of these measures, incorporating sample similarity information to weight samples results in greater stability of sets of genes called as specific and decreases the overall variance in the change of specificity estimates as sample sets become more unbalanced. Furthermore, the genes with the largest improvement in their specificity estimate's stability are those with functions related to the overrepresented sample types. Our results demonstrate that incorporating similarity information improves specificity estimates' stability to the choice of the sample set used to define the transcriptome, providing more robust and reproducible measures of specificity for downstream analyses.

Increased frequency of clonal hematopoiesis of indeterminate potential in Bloom syndrome probands and carriers.

Not available.

The omics era: a nexus of untapped potential for Mendelian chromatinopathies.

The OMICs cascade describes the hierarchical flow of information through biological systems. The epigenome sits at the apex of the cascade, thereby regulating the RNA and protein expression of the human genome and governs cellular identity and function. Genes that regulate the epigenome, termed epigenes, orchestrate complex biological signaling programs that drive human development. The broad expression patterns of epigenes during human development mean that pathogenic germline mutations in epigenes can lead to clinically significant multi-system malformations, developmental delay, intellectual disabilities, and stem cell dysfunction. In this review, we refer to germline developmental disorders caused by epigene mutation as "chromatinopathies". We curated the largest number of human chromatinopathies to date and our expanded approach more than doubled the number of established chromatinopathies to 179 disorders caused by 148 epigenes. Our study revealed that 20.6% (148/720) of epigenes cause at least one chromatinopathy. In this review, we highlight key examples in which OMICs approaches have been applied to chromatinopathy patient biospecimens to identify underlying disease pathogenesis. The rapidly evolving OMICs technologies that couple molecular biology with high-throughput sequencing or proteomics allow us to dissect out the causal mechanisms driving temporal-, cellular-, and tissue-specific expression. Using the full repertoire of data generated by the OMICs cascade to study chromatinopathies will provide invaluable insight into the developmental impact of these epigenes and point toward future precision targets for these rare disorders.

KAT6A mutations in Arboleda-Tham syndrome drive epigenetic regulation of posterior HOXC cluster.

Arboleda-Tham Syndrome (ARTHS) is a rare genetic disorder caused by heterozygous, de novo mutations in Lysine(K) acetyltransferase 6A (KAT6A). ARTHS is clinically heterogeneous and characterized by several common features, including intellectual disability, developmental and speech delay, and hypotonia, and affects multiple organ systems. KAT6A is the enzymatic core of a histone-acetylation protein complex; however, the direct histone targets and gene regulatory effects remain unknown. In this study, we use ARTHS patient (n = 8) and control (n = 14) dermal fibroblasts and perform comprehensive profiling of the epigenome and transcriptome caused by KAT6A mutations. We identified differential chromatin accessibility within the promoter or gene body of 23% (14/60) of genes that were differentially expressed between ARTHS and controls. Within fibroblasts, we show a distinct set of genes from the posterior HOXC gene cluster (HOXC10, HOXC11, HOXC-AS3, HOXC-AS2, and HOTAIR) that are overexpressed in ARTHS and are transcription factors critical for early development body segment patterning. The genomic loci harboring HOXC genes are epigenetically regulated with increased chromatin accessibility, high levels of H3K23ac, and increased gene-body DNA methylation compared to controls, all of which are consistent with transcriptomic overexpression. Finally, we used unbiased proteomic mass spectrometry and identified two new histone post-translational modifications (PTMs) that are disrupted in ARTHS: H2A and H3K56 acetylation. Our multi-omics assays have identified novel histone and gene regulatory roles of KAT6A in a large group of ARTHS patients harboring diverse pathogenic mutations. This work provides insight into the role of KAT6A on the epigenomic regulation in somatic cell types.

DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features.

BACKGROUND: Pathogenic mutations in genes that control chromatin function have been implicated in rare genetic syndromes. These chromatin modifiers exhibit extraordinary diversity in the scale of the epigenetic changes they affect, from single basepair modifications by DNMT1 to whole genome structural changes by PRM1/2. Patterns of DNA methylation are related to a diverse set of epigenetic features across this full range of epigenetic scale, making DNA methylation valuable for mapping regions of general epigenetic dysregulation. However, existing methods are unable to accurately identify regions of differential methylation across this full range of epigenetic scale directly from DNA methylation data. RESULTS: To address this, we developed DMRscaler, a novel method that uses an iterative windowing procedure to capture regions of differential DNA methylation (DMRs) ranging in size from single basepairs to whole chromosomes. We benchmarked DMRscaler against several DMR callers in simulated and natural data comparing XX and XY peripheral blood samples. DMRscaler was the only method that accurately called DMRs ranging in size from 100 bp to 1 Mb (pearson's r = 0.94) and up to 152 Mb on the X-chromosome. We then analyzed methylation data from rare-disease cohorts that harbor chromatin modifier gene mutations in NSD1, EZH2, and KAT6A where DMRscaler identified novel DMRs spanning gene clusters involved in development. CONCLUSION: Taken together, our results show DMRscaler is uniquely able to capture the size of DMR features across the full range of epigenetic scale and identify novel, co-regulated regions that drive epigenetic dysregulation in human disease.

Retrospective Detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Symptomatic Patients Prior to Widespread Diagnostic Testing in Southern California.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused one of the worst pandemics in recent history. Few reports have revealed that SARS-CoV-2 was spreading in the United States as early as the end of January. In this study, we aimed to determine if SARS-CoV-2 had been circulating in the Los Angeles (LA) area at a time when access to diagnostic testing for coronavirus disease 2019 (COVID-19) was severely limited. METHODS: We used a pooling strategy to look for SARS-CoV-2 in remnant respiratory samples submitted for regular respiratory pathogen testing from symptomatic patients from November 2019 to early March 2020. We then performed sequencing on the positive samples. RESULTS: We detected SARS-CoV-2 in 7 specimens from 6 patients, dating back to mid-January. The earliest positive patient, with a sample collected on January 13, 2020 had no relevant travel history but did have a sibling with similar symptoms. Sequencing of these SARS-CoV-2 genomes revealed that the virus was introduced into the LA area from both domestic and international sources as early as January. CONCLUSIONS: We present strong evidence of community spread of SARS-CoV-2 in the LA area well before widespread diagnostic testing was being performed in early 2020. These genomic data demonstrate that SARS-CoV-2 was being introduced into Los Angeles County from both international and domestic sources in January 2020.

Genomic epidemiology of the Los Angeles COVID-19 outbreak and the early history of the B.1.43 strain in the USA.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused global disruption of human health and activity. Being able to trace the early outbreak of SARS-CoV-2 within a locality can inform public health measures and provide insights to contain or prevent viral transmission. Investigation of the transmission history requires efficient sequencing methods and analytic strategies, which can be generally useful in the study of viral outbreaks. METHODS: The County of Los Angeles (hereafter, LA County) sustained a large outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To learn about the transmission history, we carried out surveillance viral genome sequencing to determine 142 viral genomes from unique patients seeking care at the University of California, Los Angeles (UCLA) Health System. 86 of these genomes were from samples collected before April 19, 2020. RESULTS: We found that the early outbreak in LA County, as in other international air travel hubs, was seeded by multiple introductions of strains from Asia and Europe. We identified a USA-specific strain, B.1.43, which was found predominantly in California and Washington State. While samples from LA County carried the ancestral B.1.43 genome, viral genomes from neighboring counties in California and from counties in Washington State carried additional mutations, suggesting a potential origin of B.1.43 in Southern California. We quantified the transmission rate of SARS-CoV-2 over time, and found evidence that the public health measures put in place in LA County to control the virus were effective at preventing transmission, but might have been undermined by the many introductions of SARS-CoV-2 into the region. CONCLUSION: Our work demonstrates that genome sequencing can be a powerful tool for investigating outbreaks and informing the public health response. Our results reinforce the critical need for the USA to have coordinated inter-state responses to the pandemic.

From chemoproteomic-detected amino acids to genomic coordinates: insights into precise multi-omic data integration.

The integration of proteomic, transcriptomic, and genetic variant annotation data will improve our understanding of genotype-phenotype associations. Due, in part, to challenges associated with accurate inter-database mapping, such multi-omic studies have not extended to chemoproteomics, a method that measures the intrinsic reactivity and potential "druggability" of nucleophilic amino acid side chains. Here, we evaluated mapping approaches to match chemoproteomic-detected cysteine and lysine residues with their genetic coordinates. Our analysis revealed that database update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomics data with computational methods for predicting genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious and allowed us to identify and functionally characterize a new damaging residue in the cysteine protease caspase-8. Our study provides a roadmap for more precise inter-database mapping and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites.

Phenotype-Specific Enrichment of Mendelian Disorder Genes near GWAS Regions across 62 Complex Traits.

Although recent studies provide evidence for a common genetic basis between complex traits and Mendelian disorders, a thorough quantification of their overlap in a phenotype-specific manner remains elusive. Here, we have quantified the overlap of genes identified through large-scale genome-wide association studies (GWASs) for 62 complex traits and diseases with genes containing mutations known to cause 20 broad categories of Mendelian disorders. We identified a significant enrichment of genes linked to phenotypically matched Mendelian disorders in GWAS gene sets; of the total 1,240 comparisons, a higher proportion of phenotypically matched or related pairs (n = 50 of 92 [54%]) than phenotypically unmatched pairs (n = 27 of 1,148 [2%]) demonstrated significant overlap, confirming a phenotype-specific enrichment pattern. Further, we observed elevated GWAS effect sizes near genes linked to phenotypically matched Mendelian disorders. Finally, we report examples of GWAS variants localized at the transcription start site or physically interacting with the promoters of genes linked to phenotypically matched Mendelian disorders. Our results are consistent with the hypothesis that genes that are disrupted in Mendelian disorders are dysregulated by non-coding variants in complex traits and demonstrate how leveraging findings from related Mendelian disorders and functional genomic datasets can prioritize genes that are putatively dysregulated by local and distal non-coding GWAS variants.

De novo nonsense mutations in KAT6A, a lysine acetyl-transferase gene, cause a syndrome including microcephaly and global developmental delay.

Chromatin remodeling through histone acetyltransferase (HAT) and histone deactylase (HDAC) enzymes affects fundamental cellular processes including the cell-cycle, cell differentiation, metabolism, and apoptosis. Nonsense mutations in genes that are involved in histone acetylation and deacetylation result in multiple congenital anomalies with most individuals displaying significant developmental delay, microcephaly and dysmorphism. Here, we report a syndrome caused by de novo heterozygous nonsense mutations in KAT6A (a.k.a., MOZ, MYST3) identified by clinical exome sequencing (CES) in four independent families. The same de novo nonsense mutation (c.3385C>T [p.Arg1129∗]) was observed in three individuals, and the fourth individual had a nearby de novo nonsense mutation (c.3070C>T [p.Arg1024∗]). Neither of these variants was present in 1,815 in-house exomes or in public databases. Common features among all four probands include primary microcephaly, global developmental delay including profound speech delay, and craniofacial dysmorphism, as well as more varied features such as feeding difficulties, cardiac defects, and ocular anomalies. We further demonstrate that KAT6A mutations result in dysregulation of H3K9 and H3K18 acetylation and altered P53 signaling. Through histone and non-histone acetylation, KAT6A affects multiple cellular processes and illustrates the complex role of acetylation in regulating development and disease.

Identification of novel PIEZO1 variants using prenatal exome sequencing and correlation to ultrasound and autopsy findings of recurrent hydrops fetalis.

Nonimmune hydrops fetalis (NIHF) is a rare disorder with a high perinatal mortality of at least 50%. One cause of NIHF is generalized lymphatic dysplasia (GLD), a rare form of primary lymphedema of the extremities and systemic involvement including chylothoraces and pericardial effusions. An autosomal recessive form of GLD has been described, caused by variants in the PIEZO1 gene. It has been reported clinically to cause NIHF and childhood onset of facial and limb lymphedema, most of which were diagnosed postnatally. We present a case of a woman with recurrent pregnancies affected by NIHF because of novel compound heterozygous variants in the PIEZO1 gene diagnosed prenatally using exome sequencing (ES). Two variants in PIEZO1 (c.3206G>A and c.6208A>C) were identified that were inherited from the father and mother, and are predicted to cause a nonsense and missense change, respectively, in the PIEZO1 subunits. Ultrasound demonstrated severe bilateral pleural effusions, whole body edema and polyhydramnios. Histopathology revealed an increased number of lymphatic channels, many of which showed failure of luminal canalization. Sanger sequencing confirmed the same variants in a prior fetal demise. We provide phenotypic correlation with ultrasound and autopsy finding, review PIEZO1 variants as a cause of GLD and discuss the uses of prenatal ES to date.

Mutant cohesin in premature ovarian failure.

Premature ovarian failure is a major cause of female infertility. The genetic causes of this disorder remain unknown in most patients. Using whole-exome sequence analysis of a large consanguineous family with inherited premature ovarian failure, we identified a homozygous 1-bp deletion inducing a frameshift mutation in STAG3 on chromosome 7. STAG3 encodes a meiosis-specific subunit of the cohesin ring, which ensures correct sister chromatid cohesion. Female mice devoid of Stag3 are sterile, and their fetal oocytes are arrested at early prophase I, leading to oocyte depletion at 1 week of age.

A novel follicle-stimulating hormone receptor mutation causing primary ovarian failure: a fertility application of whole exome sequencing.

STUDY QUESTION: Can whole exome sequencing (WES) and in vitro validation studies be used to find the causative genetic etiology in a patient with primary ovarian failure and infertility? SUMMARY ANSWER: A novel follicle-stimulating hormone receptor (FSHR) mutation was found by WES and shown, via in vitro flow cytometry studies, to affect membrane trafficking. WHAT IS KNOWN ALREADY: WES may diagnose up to 25-35% of patients with suspected disorders of sex development (DSD). FSHR mutations are an extremely rare cause of 46, XX gonadal dysgenesis with primary amenorrhea due to hypergonadotropic ovarian failure. STUDY DESIGN, SIZE, DURATION: A WES study was followed by flow cytometry studies of mutant protein function. PARTICIPANTS/MATERIALS, SETTING, METHODS: The study subjects were two Turkish sisters with hypergonadotropic primary amenorrhea, their parents and two unaffected sisters. The affected siblings and both parents were sequenced (trio-WES). Transient transfection of HEK 293T cells was performed with a vector containing wild-type FSHR as well as the novel FSHR variant that was discovered by WES. Cellular localization of FSHR protein as well as FSH-stimulated cyclic AMP (cAMP) production was evaluated using flow cytometry. MAIN RESULTS AND THE ROLE OF CHANCE: Both affected sisters were homozygous for a previously unreported missense mutation (c.1222G>T, p.Asp408Tyr) in the second transmembrane domain of FSHR. Modeling predicted disrupted secondary structure. Flow cytometry demonstrated an average of 48% reduction in cell-surface signal detection (P < 0.01). The mean fluorescent signal for cAMP (second messenger of FSHR), stimulated by FSH, was reduced by 50% in the mutant-transfected cells (P < 0.01). LIMITATIONS, REASONS FOR CAUTION: This is an in vitro validation. All novel purported genetic variants can be clinically reported only as 'variants of uncertain significance' until more patients with a similar phenotype are discovered with the same variant. WIDER IMPLICATIONS OF THE FINDINGS: We report the first WES-discovered FSHR mutation, validated by quantitative flow cytometry. WES is a valuable tool for diagnosis of rare genetic diseases, and flow cytometry allows for quantitative characterization of purported variants. WES-assisted diagnosis allows for treatments aimed at the underlying molecular etiology of disease. Future studies should focus on pharmacological and assisted reproductive treatments aimed at the disrupted FSHR, so that patients with FSH resistance can be treated by personalized medicine. STUDY FUNDING/COMPETING INTERESTS: E.V. is partially funded by the DSD Translational Research Network (NICHD 1R01HD068138). M.S.B. is funded by the Neuroendocrinology, Sex Differences and Reproduction training grant (NICHD 5T32HD007228). The authors have no competing interests to disclose.

Electronic health record signatures identify undiagnosed patients with common variable immunodeficiency disease.

Human inborn errors of immunity include rare disorders entailing functional and quantitative antibody deficiencies due to impaired B cells called the common variable immunodeficiency (CVID) phenotype. Patients with CVID face delayed diagnoses and treatments for 5 to 15 years after symptom onset because the disorders are rare (prevalence of ~1/25,000), and there is extensive heterogeneity in CVID phenotypes, ranging from infections to autoimmunity to inflammatory conditions, overlapping with other more common disorders. The prolonged diagnostic odyssey drives excessive system-wide costs before diagnosis. Because there is no single causal mechanism, there are no genetic tests to definitively diagnose CVID. Here, we present PheNet, a machine learning algorithm that identifies patients with CVID from their electronic health records (EHRs). PheNet learns phenotypic patterns from verified CVID cases and uses this knowledge to rank patients by likelihood of having CVID. PheNet could have diagnosed more than half of our patients with CVID 1 or more years earlier than they had been diagnosed. When applied to a large EHR dataset, followed by blinded chart review of the top 100 patients ranked by PheNet, we found that 74% were highly probable to have CVID. We externally validated PheNet using >6 million records from disparate medical systems in California and Tennessee. As artificial intelligence and machine learning make their way into health care, we show that algorithms such as PheNet can offer clinical benefits by expediting the diagnosis of rare diseases.

Multiomics of Bohring-Opitz syndrome truncating ASXL1 mutations identify canonical and noncanonical Wnt signaling dysregulation.

ASXL1 (additional sex combs-like 1) plays key roles in epigenetic regulation of early developmental gene expression. De novo protein-truncating mutations in ASXL1 cause Bohring-Opitz syndrome (BOS; OMIM #605039), a rare neurodevelopmental condition characterized by severe intellectual disabilities, distinctive facial features, hypertrichosis, increased risk of Wilms tumor, and variable congenital anomalies, including heart defects and severe skeletal defects giving rise to a typical BOS posture. These BOS-causing ASXL1 variants are also high-prevalence somatic driver mutations in acute myeloid leukemia. We used primary cells from individuals with BOS (n = 18) and controls (n = 49) to dissect gene regulatory changes caused by ASXL1 mutations using comprehensive multiomics assays for chromatin accessibility (ATAC-seq), DNA methylation, histone methylation binding, and transcriptome in peripheral blood and skin fibroblasts. Our data show that regardless of cell type, ASXL1 mutations drive strong cross-tissue effects that disrupt multiple layers of the epigenome. The data showed a broad activation of canonical Wnt signaling at the transcriptional and protein levels and upregulation of VANGL2, which encodes a planar cell polarity pathway protein that acts through noncanonical Wnt signaling to direct tissue patterning and cell migration. This multiomics approach identifies the core impact of ASXL1 mutations and therapeutic targets for BOS and myeloid leukemias.

The genetic underpinnings of variable penetrance and expressivity of pathogenic mutations in cardiometabolic traits.

Over three percent of people carry a dominant pathogenic mutation, yet only a fraction of carriers develop disease (incomplete penetrance), and phenotypes from mutations in the same gene range from mild to severe (variable expressivity). Here, we investigate underlying mechanisms for this heterogeneity: variable variant effect sizes, carrier polygenic backgrounds, and modulation of carrier effect by genetic background (epistasis). We leveraged exomes and clinical phenotypes from the UK Biobank and the Mt. Sinai Bio Me Biobank to identify carriers of pathogenic variants affecting cardiometabolic traits. We employed recently developed methods to study these cohorts, observing strong statistical support and clinical translational potential for all three mechanisms of variable penetrance and expressivity. For example, scores from our recent model of variant pathogenicity were tightly correlated with phenotype amongst clinical variant carriers, they predicted effects of variants of unknown significance, and they distinguished gain- from loss-of-function variants. We also found that polygenic scores predicted phenotypes amongst pathogenic carriers and that epistatic effects can exceed main carrier effects by an order of magnitude.

3D Printing as an Effective Quality Assurance Implementation in Massive-Scale SARS-CoV-2 Testing at a SwabSeq Next-Generation Sequencing Laboratory.

Massive-scale SARS-CoV-2 testing using the SwabSeq diagnostic platform came with quality assurance challenges due to the novelty and scale of sequencing-based testing. The SwabSeq platform relies on accurate mapping between specimen identifiers and molecular barcodes to match a result back to a patient specimen. To identify and mitigate mapping errors, we instituted quality control using placement of negative controls within a rack of patient samples. We designed 2-dimensional paper templates to fit over a 96-position rack of specimens with holes to show the control tube placements. We designed and 3-dimensionally printed plastic templates that fit onto 4 racks of patient specimens and provide accurate indications of the correct control tube placements. The final plastic templates dramatically reduced plate mapping errors from 22.55% in January 2021 to less than 1% after implementation and training in January 2021. We show how 3D printing can be a cost-effective quality assurance tool to mitigate human error in the clinical laboratory.

KAT6A mutations in Arboleda-Tham syndrome drive epigenetic regulation of posterior HOXC cluster.

Arboleda-Tham Syndrome (ARTHS) is a rare genetic disorder caused by heterozygous, de novo truncating mutations in Lysine(K) acetyltransferase 6A (KAT6A). ARTHS is clinically heterogeneous and characterized by several common features including intellectual disability, developmental and speech delay, hypotonia and affects multiple organ systems. KAT6A is highly expressed in early development and plays a key role in cell-type specific differentiation. KAT6A is the enzymatic core of a histone-acetylation protein complex, however the direct histone targets and gene regulatory effects remain unknown. In this study, we use ARTHS patient (n=8) and control (n=14) dermal fibroblasts and perform comprehensive profiling of the epigenome and transcriptome caused by KAT6A mutations. We identified differential chromatin accessibility within the promoter or gene body of 23%(14/60) of genes that were differentially expressed between ARTHS and controls. Within fibroblasts, we show a distinct set of genes from the posterior HOXC gene cluster (HOXC10, HOXC11, HOXC-AS3, HOXC-AS2, HOTAIR) that are overexpressed in ARTHS and are transcription factors critical for early development body segment patterning. The genomic loci harboring HOXC genes are epigenetically regulated with increased chromatin accessibility, high levels of H3K23ac, and increased gene-body DNA methylation compared to controls, all of which are consistent with transcriptomic overexpression. Finally, we used unbiased proteomic mass spectrometry and identified two new histone post-translational modifications (PTMs) that are disrupted in ARTHS: H2A and H3K56 acetylation. Our multi-omics assays have identified novel histone and gene regulatory roles of KAT6A in a large group of ARTHS patients harboring diverse pathogenic mutations. This work provides insight into the role of KAT6A on the epigenomic regulation in somatic cell types.

Disease risk and healthcare utilization among ancestrally diverse groups in the Los Angeles region.

An individual's disease risk is affected by the populations that they belong to, due to shared genetics and environmental factors. The study of fine-scale populations in clinical care is important for identifying and reducing health disparities and for developing personalized interventions. To assess patterns of clinical diagnoses and healthcare utilization by fine-scale populations, we leveraged genetic data and electronic medical records from 35,968 patients as part of the UCLA ATLAS Community Health Initiative. We defined clusters of individuals using identity by descent, a form of genetic relatedness that utilizes shared genomic segments arising due to a common ancestor. In total, we identified 376 clusters, including clusters with patients of Afro-Caribbean, Puerto Rican, Lebanese Christian, Iranian Jewish and Gujarati ancestry. Our analysis uncovered 1,218 significant associations between disease diagnoses and clusters and 124 significant associations with specialty visits. We also examined the distribution of pathogenic alleles and found 189 significant alleles at elevated frequency in particular clusters, including many that are not regularly included in population screening efforts. Overall, this work progresses the understanding of health in understudied communities and can provide the foundation for further study into health inequities.

Whole-Exome Sequencing Identifies Homozygote Nonsense Variants in LMOD2 Gene Causing Infantile Dilated Cardiomyopathy.

As an essential component of the sarcomere, actin thin filament stems from the Z-disk extend toward the middle of the sarcomere and overlaps with myosin thick filaments. Elongation of the cardiac thin filament is essential for normal sarcomere maturation and heart function. This process is regulated by the actin-binding proteins Leiomodins (LMODs), among which LMOD2 has recently been identified as a key regulator of thin filament elongation to reach a mature length. Few reports have implicated homozygous loss of function variants of LMOD2 in neonatal dilated cardiomyopathy (DCM) associated with thin filament shortening. We present the fifth case of DCM due to biallelic variants in the LMOD2 gene and the second case with the c.1193G>A (p.W398*) nonsense variant identified by whole-exome sequencing. The proband is a 4-month male infant of Hispanic descent with advanced heart failure. Consistent with previous reports, a myocardial biopsy exhibited remarkably short thin filaments. However, compared to other cases of identical or similar biallelic variants, the patient presented here has an unusually late onset of cardiomyopathy during infancy. Herein, we present the phenotypic and histological features of this variant, confirm the pathogenic impact on protein expression and sarcomere structure, and discuss the current knowledge of LMOD2-related cardiomyopathy.