DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data.

DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case-control data that provide evidence of gene-disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research.

The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings.

Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of individuals referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 affected individuals, 1,332 variants) and dilated cardiomyopathy (DCM; 2,564 affected individuals, 663 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant cardiomyopathy (CM). Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (found in 51% of HCM- and 17% of DCM-affected individuals). 49 variants were observed at least ten times (14% of affected individuals) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry and simulate the impact of including future cohorts. This dataset reports penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some individuals with highly penetrant variants may benefit from SFs.

Genetic and functional insights into the fractal structure of the heart.

The inner surfaces of the human heart are covered by a complex network of muscular strands that is thought to be a remnant of embryonic development1,2. The function of these trabeculae in adults and their genetic architecture are unknown. Here we performed a genome-wide association study to investigate image-derived phenotypes of trabeculae using the fractal analysis of trabecular morphology in 18,096 participants of the UK Biobank. We identified 16 significant loci that contain genes associated with haemodynamic phenotypes and regulation of cytoskeletal arborization3,4. Using biomechanical simulations and observational data from human participants, we demonstrate that trabecular morphology is an important determinant of cardiac performance. Through genetic association studies with cardiac disease phenotypes and Mendelian randomization, we find a causal relationship between trabecular morphology and risk of cardiovascular disease. These findings suggest a previously unknown role for myocardial trabeculae in the function of the adult heart, identify conserved pathways that regulate structural complexity and reveal the influence of the myocardial trabeculae on susceptibility to cardiovascular disease.

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.

LAVASET: Latent Variable Stochastic Ensemble of Trees. An ensemble method for correlated datasets with spatial, spectral, and temporal dependencies.

MOTIVATION: Random forests (RFs) can deal with a large number of variables, achieve reasonable prediction scores, and yield highly interpretable feature importance values. As such, RFs are appropriate models for feature selection and further dimension reduction. However, RFs are often not appropriate for correlated datasets due to their mode of selecting individual features for splitting. Addressing correlation relationships in high-dimensional datasets is imperative for reducing the number of variables that are assigned high importance, hence making the dimension reduction most efficient. Here, we propose the LAtent VAriable Stochastic Ensemble of Trees (LAVASET) method that derives latent variables based on the distance characteristics of each feature and aims to incorporate the correlation factor in the splitting step. RESULTS: Without compromising on performance in the majority of examples, LAVASET outperforms RF by accurately determining feature importance across all correlated variables and ensuring proper distribution of importance values. LAVASET yields mostly non-inferior prediction accuracies to traditional RFs when tested in simulated and real 1D datasets, as well as more complex and high-dimensional 3D datatypes. Unlike traditional RFs, LAVASET is unaffected by single 'important' noisy features (false positives), as it considers the local neighbourhood. LAVASET, therefore, highlights neighbourhoods of features, reflecting real signals that collectively impact the model's predictive ability. AVAILABILITY AND IMPLEMENTATION: LAVASET is freely available as a standalone package from https://github.com/melkasapi/LAVASET.

Left Ventricular Systolic Dysfunction in Patients Diagnosed With Hypertrophic Cardiomyopathy During Childhood: Insights From the SHaRe Registry.

BACKGROUND: The development of left ventricular systolic dysfunction (LVSD) in hypertrophic cardiomyopathy (HCM) is rare but serious and associated with poor outcomes in adults. Little is known about the prevalence, predictors, and prognosis of LVSD in patients diagnosed with HCM as children. METHODS: Data from patients with HCM in the international, multicenter SHaRe (Sarcomeric Human Cardiomyopathy Registry) were analyzed. LVSD was defined as left ventricular ejection fraction <50% on echocardiographic reports. Prognosis was assessed by a composite of death, cardiac transplantation, and left ventricular assist device implantation. Predictors of developing incident LVSD and subsequent prognosis with LVSD were assessed using Cox proportional hazards models. RESULTS: We studied 1010 patients diagnosed with HCM during childhood (<18 years of age) and compared them with 6741 patients with HCM diagnosed as adults. In the pediatric HCM cohort, median age at HCM diagnosis was 12.7 years (interquartile range, 8.0-15.3), and 393 (36%) patients were female. At initial SHaRe site evaluation, 56 (5.5%) patients with childhood-diagnosed HCM had prevalent LVSD, and 92 (9.1%) developed incident LVSD during a median follow-up of 5.5 years. Overall LVSD prevalence was 14.7% compared with 8.7% in patients with adult-diagnosed HCM. Median age at incident LVSD was 32.6 years (interquartile range, 21.3-41.6) for the pediatric cohort and 57.2 years (interquartile range, 47.3-66.5) for the adult cohort. Predictors of developing incident LVSD in childhood-diagnosed HCM included age <12 years at HCM diagnosis (hazard ratio [HR], 1.72 [CI, 1.13-2.62), male sex (HR, 3.1 [CI, 1.88-5.2), carrying a pathogenic sarcomere variant (HR, 2.19 [CI, 1.08-4.4]), previous septal reduction therapy (HR, 2.34 [CI, 1.42-3.9]), and lower initial left ventricular ejection fraction (HR, 1.53 [CI, 1.38-1.69] per 5% decrease). Forty percent of patients with LVSD and HCM diagnosed during childhood met the composite outcome, with higher rates in female participants (HR, 2.60 [CI, 1.41-4.78]) and patients with a left ventricular ejection fraction <35% (HR, 3.76 [2.16-6.52]). CONCLUSIONS: Patients with childhood-diagnosed HCM have a significantly higher lifetime risk of developing LVSD, and LVSD emerges earlier than for patients with adult-diagnosed HCM. Regardless of age at diagnosis with HCM or LVSD, the prognosis with LVSD is poor, warranting careful surveillance for LVSD, especially as children with HCM transition to adult care.

Toward robust clinical genome interpretation: Developing a consistent terminology to characterize Mendelian disease-gene relationships-allelic requirement, inheritance modes, and disease mechanisms.

PURPOSE: The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here, we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation and to support variant classification within the ACMG/AMP framework. METHODS: Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated. RESULTS: We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both Sequence Ontology (SO) and Human Phenotype Ontology (HPO) ontologies. Gene Curation Coalition member groups intend to use or map to these terms in their respective resources. CONCLUSION: The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

Ethnicity, consanguinity, and genetic architecture of hypertrophic cardiomyopathy.

AIMS: Hypertrophic cardiomyopathy (HCM) is characterized by phenotypic heterogeneity that is partly explained by the diversity of genetic variants contributing to disease. Accurate interpretation of these variants constitutes a major challenge for diagnosis and implementing precision medicine, especially in understudied populations. The aim is to define the genetic architecture of HCM in North African cohorts with high consanguinity using ancestry-matched cases and controls. METHODS AND RESULTS: Prospective Egyptian patients (n = 514) and controls (n = 400) underwent clinical phenotyping and genetic testing. Rare variants in 13 validated HCM genes were classified according to standard clinical guidelines and compared with a prospective HCM cohort of majority European ancestry (n = 684). A higher prevalence of homozygous variants was observed in Egyptian patients (4.1% vs. 0.1%, P = 2 × 10-7), with variants in the minor HCM genes MYL2, MYL3, and CSRP3 more likely to present in homozygosity than the major genes, suggesting these variants are less penetrant in heterozygosity. Biallelic variants in the recessive HCM gene TRIM63 were detected in 2.1% of patients (five-fold greater than European patients), highlighting the importance of recessive inheritance in consanguineous populations. Finally, rare variants in Egyptian HCM patients were less likely to be classified as (likely) pathogenic compared with Europeans (40.8% vs. 61.6%, P = 1.6 × 10-5) due to the underrepresentation of Middle Eastern populations in current reference resources. This proportion increased to 53.3% after incorporating methods that leverage new ancestry-matched controls presented here. CONCLUSION: Studying consanguineous populations reveals novel insights with relevance to genetic testing and our understanding of the genetic architecture of HCM.

Genetic Architecture of Acute Myocarditis and the Overlap With Inherited Cardiomyopathy.

BACKGROUND: Acute myocarditis is an inflammatory condition that may herald the onset of dilated cardiomyopathy (DCM) or arrhythmogenic cardiomyopathy (ACM). We investigated the frequency and clinical consequences of DCM and ACM genetic variants in a population-based cohort of patients with acute myocarditis. METHODS: This was a population-based cohort of 336 consecutive patients with acute myocarditis enrolled in London and Maastricht. All participants underwent targeted DNA sequencing for well-characterized cardiomyopathy-associated genes with comparison to healthy controls (n=1053) sequenced on the same platform. Case ascertainment in England was assessed against national hospital admission data. The primary outcome was all-cause mortality. RESULTS: Variants that would be considered pathogenic if found in a patient with DCM or ACM were identified in 8% of myocarditis cases compared with <1% of healthy controls (P=0.0097). In the London cohort (n=230; median age, 33 years; 84% men), patients were representative of national myocarditis admissions (median age, 32 years; 71% men; 66% case ascertainment), and there was enrichment of rare truncating variants (tv) in ACM-associated genes (3.1% of cases versus 0.4% of controls; odds ratio, 8.2; P=0.001). This was driven predominantly by DSP-tv in patients with normal LV ejection fraction and ventricular arrhythmia. In Maastricht (n=106; median age, 54 years; 61% men), there was enrichment of rare truncating variants in DCM-associated genes, particularly TTN-tv, found in 7% (all with left ventricular ejection fraction <50%) compared with 1% in controls (odds ratio, 3.6; P=0.0116). Across both cohorts over a median of 5.0 years (interquartile range, 3.9-7.8 years), all-cause mortality was 5.4%. Two-thirds of deaths were cardiovascular, attributable to worsening heart failure (92%) or sudden cardiac death (8%). The 5-year mortality risk was 3.3% in genotype-negative patients versus 11.1% for genotype-positive patients (Padjusted=0.08). CONCLUSIONS: We identified DCM- or ACM-associated genetic variants in 8% of patients with acute myocarditis. This was dominated by the identification of DSP-tv in those with normal left ventricular ejection fraction and TTN-tv in those with reduced left ventricular ejection fraction. Despite differences between cohorts, these variants have clinical implications for treatment, risk stratification, and family screening. Genetic counseling and testing should be considered in patients with acute myocarditis to help reassure the majority while improving the management of those with an underlying genetic variant.

Evaluation of gene validity for CPVT and short QT syndrome in sudden arrhythmic death.

AIMS: Catecholaminergic polymorphic ventricular tachycardia (CPVT) and short QT syndrome (SQTS) are inherited arrhythmogenic disorders that can cause sudden death. Numerous genes have been reported to cause these conditions, but evidence supporting these gene-disease relationships varies considerably. To ensure appropriate utilization of genetic information for CPVT and SQTS patients, we applied an evidence-based reappraisal of previously reported genes. METHODS AND RESULTS: Three teams independently curated all published evidence for 11 CPVT and 9 SQTS implicated genes using the ClinGen gene curation framework. The results were reviewed by a Channelopathy Expert Panel who provided the final classifications. Seven genes had definitive to moderate evidence for disease causation in CPVT, with either autosomal dominant (RYR2, CALM1, CALM2, CALM3) or autosomal recessive (CASQ2, TRDN, TECRL) inheritance. Three of the four disputed genes for CPVT (KCNJ2, PKP2, SCN5A) were deemed by the Expert Panel to be reported for phenotypes that were not representative of CPVT, while reported variants in a fourth gene (ANK2) were too common in the population to be disease-causing. For SQTS, only one gene (KCNH2) was classified as definitive, with three others (KCNQ1, KCNJ2, SLC4A3) having strong to moderate evidence. The majority of genetic evidence for SQTS genes was derived from very few variants (five in KCNJ2, two in KCNH2, one in KCNQ1/SLC4A3). CONCLUSIONS: Seven CPVT and four SQTS genes have valid evidence for disease causation and should be included in genetic testing panels. Additional genes associated with conditions that may mimic clinical features of CPVT/SQTS have potential utility for differential diagnosis.

Titin Circular RNAs Create a Back-Splice Motif Essential for SRSF10 Splicing.

BACKGROUND: TTN (Titin), the largest protein in humans, forms the molecular spring that spans half of the sarcomere to provide passive elasticity to the cardiomyocyte. Mutations that disrupt the TTN transcript are the most frequent cause of hereditary heart failure. We showed before that TTN produces a class of circular RNAs (circRNAs) that depend on RBM20 to be formed. In this study, we show that the back-splice junction formed by this class of circRNAs creates a unique motif that binds SRSF10 to enable it to regulate splicing. Furthermore, we show that one of these circRNAs (cTTN1) distorts both localization of and splicing by RBM20. METHODS: We calculated genetic constraint of the identified motif in 125 748 exomes collected from the gnomAD database. Furthermore, we focused on the highest expressed RBM20-dependent circRNA in the human heart, which we named cTTN1. We used shRNAs directed to the back-splice junction to induce selective loss of cTTN1 in human induced pluripotent stem cell-derived cardiomyocytes. RESULTS: Human genetics suggests reduced genetic tolerance of the generated motif, indicating that mutations in this motif might lead to disease. RNA immunoprecipitation confirmed binding of circRNAs with this motif to SRSF10. Selective loss of cTTN1 in human induced pluripotent stem cell-derived cardiomyocytes induced structural abnormalities, apoptosis, and reduced contractile force in engineered heart tissue. In line with its SRSF10 binding, loss of cTTN1 caused abnormal splicing of important cardiomyocyte SRSF10 targets such as MEF2A and CASQ2. Strikingly, loss of cTTN1 also caused abnormal splicing of TTN itself. Mechanistically, we show that loss of cTTN1 distorts both localization of and splicing by RBM20. CONCLUSIONS: We demonstrate that circRNAs formed from the TTN transcript are essential for normal splicing of key muscle genes by enabling splice regulators RBM20 and SRSF10. This shows that the TTN transcript also has regulatory roles, besides its well-known signaling and structural function. In addition, we demonstrate that the specific sequence created by the back-splice junction of these circRNAs has important functions. This highlights the existence of functionally important sequences that cannot be recognized as such in the human genome but provides an as-yet unrecognized source for functional sequence variation.

Evidence-Based Assessment of Genes in Dilated Cardiomyopathy.

BACKGROUND: Each of the cardiomyopathies, classically categorized as hypertrophic cardiomyopathy, dilated cardiomyopathy (DCM), and arrhythmogenic right ventricular cardiomyopathy, has a signature genetic theme. Hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy are largely understood as genetic diseases of sarcomere or desmosome proteins, respectively. In contrast, >250 genes spanning >10 gene ontologies have been implicated in DCM, representing a complex and diverse genetic architecture. To clarify this, a systematic curation of evidence to establish the relationship of genes with DCM was conducted. METHODS: An international panel with clinical and scientific expertise in DCM genetics evaluated evidence supporting monogenic relationships of genes with idiopathic DCM. The panel used the Clinical Genome Resource semiquantitative gene-disease clinical validity classification framework with modifications for DCM genetics to classify genes into categories on the basis of the strength of currently available evidence. Representation of DCM genes on clinically available genetic testing panels was evaluated. RESULTS: Fifty-one genes with human genetic evidence were curated. Twelve genes (23%) from 8 gene ontologies were classified as having definitive (BAG3, DES, FLNC, LMNA, MYH7, PLN, RBM20, SCN5A, TNNC1, TNNT2, TTN) or strong (DSP) evidence. Seven genes (14%; ACTC1, ACTN2, JPH2, NEXN, TNNI3, TPM1, VCL) including 2 additional ontologies were classified as moderate evidence; these genes are likely to emerge as strong or definitive with additional evidence. Of these 19 genes, 6 were similarly classified for hypertrophic cardiomyopathy and 3 for arrhythmogenic right ventricular cardiomyopathy. Of the remaining 32 genes (63%), 25 (49%) had limited evidence, 4 (8%) were disputed, 2 (4%) had no disease relationship, and 1 (2%) was supported by animal model data only. Of the 16 evaluated clinical genetic testing panels, most definitive genes were included, but panels also included numerous genes with minimal human evidence. CONCLUSIONS: In the curation of 51 genes, 19 had high evidence (12 definitive/strong, 7 moderate). It is notable that these 19 genes explain only a minority of cases, leaving the remainder of DCM genetic architecture incompletely addressed. Clinical genetic testing panels include most high-evidence genes; however, genes lacking robust evidence are also commonly included. We recommend that high-evidence DCM genes be used for clinical practice and that caution be exercised in the interpretation of variants in variable-evidence DCM genes.

Vitamin D Supplementation and Prevention of Type 2 Diabetes.

BACKGROUND: Observational studies support an association between a low blood 25-hydroxyvitamin D level and the risk of type 2 diabetes. However, whether vitamin D supplementation lowers the risk of diabetes is unknown. METHODS: We randomly assigned adults who met at least two of three glycemic criteria for prediabetes (fasting plasma glucose level, 100 to 125 mg per deciliter; plasma glucose level 2 hours after a 75-g oral glucose load, 140 to 199 mg per deciliter; and glycated hemoglobin level, 5.7 to 6.4%) and no diagnostic criteria for diabetes to receive 4000 IU per day of vitamin D3 or placebo, regardless of the baseline serum 25-hydroxyvitamin D level. The primary outcome in this time-to-event analysis was new-onset diabetes, and the trial design was event-driven, with a target number of diabetes events of 508. RESULTS: A total of 2423 participants underwent randomization (1211 to the vitamin D group and 1212 to the placebo group). By month 24, the mean serum 25-hydroxyvitamin D level in the vitamin D group was 54.3 ng per milliliter (from 27.7 ng per milliliter at baseline), as compared with 28.8 ng per milliliter in the placebo group (from 28.2 ng per milliliter at baseline). After a median follow-up of 2.5 years, the primary outcome of diabetes occurred in 293 participants in the vitamin D group and 323 in the placebo group (9.39 and 10.66 events per 100 person-years, respectively). The hazard ratio for vitamin D as compared with placebo was 0.88 (95% confidence interval, 0.75 to 1.04; P = 0.12). The incidence of adverse events did not differ significantly between the two groups. CONCLUSIONS: Among persons at high risk for type 2 diabetes not selected for vitamin D insufficiency, vitamin D3 supplementation at a dose of 4000 IU per day did not result in a significantly lower risk of diabetes than placebo. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; D2d ClinicalTrials.gov number, NCT01942694.).

Annotating high-impact 5'untranslated region variants with the UTRannotator.

SUMMARY: Current tools to annotate the predicted effect of genetic variants are heavily biased towards protein-coding sequence. Variants outside of these regions may have a large impact on protein expression and/or structure and can lead to disease, but this effect can be challenging to predict. Consequently, these variants are poorly annotated using standard tools. We have developed a plugin to the Ensembl Variant Effect Predictor, the UTRannotator, that annotates variants in 5'untranslated regions (5'UTR) that create or disrupt upstream open reading frames. We investigate the utility of this tool using the ClinVar database, providing an annotation for 31.9% of all 5'UTR (likely) pathogenic variants, and highlighting 31 variants of uncertain significance as candidates for further follow-up. We will continue to update the UTRannotator as we gain new knowledge on the impact of variants in UTRs. AVAILABILITY AND IMPLEMENTATION: UTRannotator is freely available on Github: https://github.com/ImperialCardioGenetics/UTRannotator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants.

PURPOSE: Conditions and thresholds applied for evidence weighting of within-codon concordance (PM5) for pathogenicity vary widely between laboratories and expert groups. Because of the sparseness of available clinical classifications, there is little evidence for variation in practice. METHODS: We used as a truthset 7541 dichotomous functional classifications of BRCA1 and MSH2, spanning 311 codons of BRCA1 and 918 codons of MSH2, generated from large-scale functional assays that have been shown to correlate excellently with clinical classifications. We assessed PM5 at 5 stringencies with incorporation of 8 in silico tools. For each analysis, we quantified a positive likelihood ratio (pLR, true positive rate/false positive rate), the predictive value of PM5-lookup in ClinVar compared with the functional truthset. RESULTS: pLR was 16.3 (10.6-24.9) for variants for which there was exactly 1 additional colocated deleterious variant on ClinVar, and the variant under examination was equally or more damaging when analyzed using BLOSUM62. pLR was 71.5 (37.8-135.3) for variants for which there were 2 or more colocated deleterious ClinVar variants, and the variant under examination was equally or more damaging than at least 1 colocated variant when analyzed using BLOSUM62. CONCLUSION: These analyses support the graded use of PM5, with potential to use it at higher evidence weighting where more stringent criteria are met.

Quantifying evidence toward pathogenicity for rare phenotypes: The case of succinate dehydrogenase genes, SDHB and SDHD.

PURPOSE: The weight of the evidence to attach to observation of a novel rare missense variant in SDHB or SDHD in individuals with the rare neuroendocrine tumors, pheochromocytomas and paragangliomas (PCC/PGL), is uncertain. METHODS: We compared the frequency of SDHB and SDHD very rare missense variants (VRMVs) in 6328 and 5847 cases of PCC/PGL, respectively, with that of population controls to generate a pan-gene VRMV likelihood ratio (LR). Via windowing analysis, we measured regional enrichments of VRMVs to calculate the domain-specific VRMV-LR (DS-VRMV-LR). We also calculated subphenotypic LRs for variant pathogenicity for various clinical, histologic, and molecular features. RESULTS: We estimated the pan-gene VRMV-LR to be 76.2 (54.8-105.9) for SDHB and 14.8 (8.7-25.0) for SDHD. Clustering analysis revealed an SDHB enriched region (ɑɑ 177-260, P = .001) for which the DS-VRMV-LR was 127.2 (64.9-249.4) and an SDHD enriched region (ɑɑ 70-114, P = .000003) for which the DS-VRMV-LR was 33.9 (14.8-77.8). Subphenotypic LRs exceeded 6 for invasive disease (SDHB), head-and-neck disease (SDHD), multiple tumors (SDHD), family history of PCC/PGL, loss of SDHB staining on immunohistochemistry, and succinate-to-fumarate ratio >97 (SDHB, SDHD). CONCLUSION: Using methodology generalizable to other gene-phenotype dyads, the LRs relating to rarity and phenotypic specificity for a single observation in PCC/PGL of a SDHB/SDHD VRMV can afford substantial evidence toward pathogenicity.

The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources.

PURPOSE: Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed. METHODS: The GenCC drafted harmonized definitions for differing levels of gene-disease validity on the basis of existing resources, and performed a modified Delphi survey with 3 rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members. RESULTS: On the basis of 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contained 15,241 gene-disease assertions on 4569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%. CONCLUSION: Terminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

Exposure to Elevated Nitrogen Dioxide Concentrations and Cardiac Remodeling in Patients With Dilated Cardiomyopathy.

BACKGROUND: Empirical evidence suggests a strong link between exposure to air pollution and heart failure incidence, hospitalizations, and mortality, but the biological basis of this remains unclear. We sought to determine the relationship between differential air pollution levels and changes in cardiac structure and function in patients with dilated cardiomyopathy. METHODS AND RESULTS: We undertook a prospective longitudinal observational cohort study of patients in England with dilated cardiomyopathy (enrollment 2009-2015, n = 716, 66% male, 85% Caucasian) and conducted cross sectional analysis at the time of study enrollment. Annual average air pollution exposure estimates for nitrogen dioxide (NO2) and particulate matter with diameter of 2.5 µm or less (PM2.5) at enrolment were assigned to each residential postcode (on average 12 households). The relationship between air pollution and cardiac morphology was assessed using linear regression modelling. Greater ambient exposure to NO2 was associated with higher indexed left ventricular (LV) mass (4.3 g/m2 increase per interquartile range increase in NO2, 95% confidence interval 1.9-7.0 g/m2) and lower LV ejection fraction (-1.5% decrease per interquartile range increase in NO2, 95% confidence interval -2.7% to -0.2%), independent of age, sex, socioeconomic status, and clinical covariates. The associations were robust to adjustment for smoking status and geographical clustering by postcode area. The effect of air pollution on LV mass was greatest in women. These effects were specific to NO2 exposure. CONCLUSIONS: Exposure to air pollution is associated with raised LV mass and lower LV ejection fraction, with the strongest effect in women. Although epidemiological associations between air pollution and heart failure have been established and supported by preclinical studies, our findings provide novel empirical evidence of cardiac remodeling and exposure to air pollution with important clinical and public health implications.

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.