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Purpose: Dilated cardiomyopathy is characterized by substantial locus, allelic, and clinical heterogeneity that necessitates testing of many genes across clinically overlapping diseases. Few studies have sequenced sufficient individuals; thus, the contributions of individual genes and the pathogenic variant spectrum are still poorly defined. We analyzed 766 dilated cardiomyopathy patients tested over 5 years in our molecular diagnostics laboratory. Methods: Patients were tested using gene panels of increasing size from 5 to 46 genes, including 121 cases tested with a multiple-cardiomyopathy next-generation panel covering 46 genes. All variants were reassessed using our current clinical-grade scoring system to eliminate false-positive disease associations that afflict many older analyses. Results: Up to 37% of dilated cardiomyopathy cases carry a clinically relevant variant in one of 20 genes, titin ( TTN ) being the largest contributor (up to 14%). Desmoplakin ( DSP ), an arrhythmogenic right ventricular cardiomyopathy gene, contributed 2.4%, illustrating the utility of multidisease testing. The clinical sensitivity increased from 10 to 37% as gene panel sizes increased. However, the number of inconclusive cases also increased from 4.6 to 51%. Conclusion: Our data illustrate the utility of broad gene panels for genetically and clinically heterogeneous diseases but also highlight challenges as molecular diagnostics moves toward genome-wide testing. Genet Med 16 8, 601–608.

Purpose: Hypertrophic cardiomyopathy (HCM) is caused primarily by pathogenic variants in genes encoding sarcomere proteins. We report genetic testing results for HCM in 2,912 unrelated individuals with nonsyndromic presentations from a broad referral population over 10 years. Methods: Genetic testing was performed by Sanger sequencing for 10 genes from 2004 to 2007, by HCM CardioChip for 11 genes from 2007 to 2011 and by next-generation sequencing for 18, 46, or 51 genes from 2011 onward. Results: The detection rate is ~32% among unselected probands, with inconclusive results in an additional 15%. Detection rates were not significantly different between adult and pediatric probands but were higher in females compared with males. An expanded gene panel encompassing more than 50 genes identified only a very small number of additional pathogenic variants beyond those identifiable in our original panels, which examined 11 genes. Familial genetic testing in at-risk family members eliminated the need for longitudinal cardiac evaluations in 691 individuals. Based on the projected costs derived from Medicare fee schedules for the recommended clinical evaluations of HCM family members by the American College of Cardiology Foundation/American Heart Association, our data indicate that genetic testing resulted in a minimum cost savings of about $0.7 million. Conclusion: Clinical HCM genetic testing provides a definitive molecular diagnosis for many patients and provides cost savings to families. Expanded gene panels have not substantively increased the clinical sensitivity of HCM testing, suggesting major additional causes of HCM still remain to be identified. Genet Med 17 11, 880–888.

The BRCA Challenge is a long-term data-sharing project initiated within the Global Alliance for Genomics and Health (GA4GH) to aggregate BRCA1 and BRCA2 data to support highly collaborative research activities. Its goal is to generate an informed and current understanding of the impact of genetic variation on cancer risk across the iconic cancer predisposition genes, BRCA1 and BRCA2. Initially, reported variants in BRCA1 and BRCA2 available from public databases were integrated into a single, newly created site, www.brcaexchange.org. The purpose of the BRCA Exchange is to provide the community with a reliable and easily accessible record of variants interpreted for a high-penetrance phenotype. More than 20,000 variants have been aggregated, three times the number found in the next-largest public database at the project's outset, of which approximately 7,250 have expert classifications. The data set is based on shared information from existing clinical databases-Breast Cancer Information Core (BIC), ClinVar, and the Leiden Open Variation Database (LOVD)-as well as population databases, all linked to a single point of access. The BRCA Challenge has brought together the existing international Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium expert panel, along with expert clinicians, diagnosticians, researchers, and database providers, all with a common goal of advancing our understanding of BRCA1 and BRCA2 variation. Ongoing work includes direct contact with national centers with access to BRCA1 and BRCA2 diagnostic data to encourage data sharing, development of methods suitable for extraction of genetic variation at the level of individual laboratory reports, and engagement with participant communities to enable a more comprehensive understanding of the clinical significance of genetic variation in BRCA1 and BRCA2.

The Genome Aggregation Database (gnomAD) is a foundational resource for allele frequency data, widely used in genomic research and clinical interpretation. However, traditional estimates rely on individual-level genetic ancestry groupings that may obscure variation in recently admixed populations. To improve resolution, we applied local ancestry inference (LAI) to over 27 million variants in two admixed groups: Admixed American ( n  = 7612) and African/African American ( n  = 20,250), deriving ancestry-specific allele frequencies. We show that 78.5% and 85.1% of variants in these groups, respectively, exhibit at least a twofold difference in ancestry-specific frequencies. Moreover, 81.49% of variants with LAI information would be assigned a higher gnomAD-wide maximum frequency after incorporating LAI, potentially altering clinical interpretations. This LAI-informed release reveals clinically relevant frequency differences that are masked in aggregate estimates and may support reclassifying some variants from Uncertain Significance to Benign or Likely Benign. This study incorporates local ancestry into the Genome Aggregation Database (gnomAD) to improve allele frequency estimates for admixed populations, enhancing variant interpretation and enabling more accurate and equitable genomic research and clinical care.

Introduction Multiple studies demonstrate social deprivation is associated with inferior outcomes after total hip (THA) and total knee (TKA) arthroplasty; its effect on patient-reported outcomes is debated. The primary objective of this study evaluated the relationship between social vulnerability and the PROMIS-PF measure in patients undergoing THA and TKA. A secondary aim compared social vulnerability between patients who required increased resource utilization or experienced complications and those who didn’t. Materials and methods A retrospective review of 537 patients from March 2020 to February 2022 was performed. The Centers for Disease Control Social Vulnerability Index (SVI) were used to quantify socioeconomic disadvantage. The cohort was split into THA and TKA populations; univariate and multivariate analyses were performed to evaluate primary and secondary outcomes. Statistical significance was assessed at p  < 0.05. Results 48.6% of patients achieved PROMIS-PF MCID at 1-year postoperatively. Higher levels of overall social vulnerability (0.40 vs. 0.28, p  = 0.03) were observed in TKA patients returning to the ED within 90-days of discharge. Increased overall SVI (OR = 9.18, p  = 0.027) and household characteristics SVI (OR = 9.57, p  = 0.015) were independent risk factors for 90-day ED returns after TKA. In THA patients, increased vulnerability in the household type and transportation dimension was observed in patients requiring 90-day ED returns (0.51 vs. 0.37, p  = 0.04). Conclusion Despite an increased risk for 90-day ED returns, patients with increased social vulnerability still obtain good 1-year functional outcomes. Initiatives seeking to mitigate the effect of social deprivation on TJA outcomes should aim to provide safe alternatives to ED care during early recovery.

Background PLA2G6-associated neurodegeneration (PLAN) comprises three diseases with overlapping features: infantile neuroaxonal dystrophy (INAD), atypical neuroaxonal dystrophy (atypical NAD), and PLA2G6-related dystonia-parkinsonism. INAD is an early onset disease characterized by progressive loss of vision, muscular control, and mental skills. The prevalence of PLA2G6-associated diseases has not been previously calculated. Methods To provide the most accurate prevalence estimate, we utilized two independent approaches: database-based approach which included collecting variants from ClinVar, Human Gene Mutation Database (HGMD) and high confidence predicted loss-of-function (pLoF) from gnomAD (Rare Genomes Project Genetic Prevalence Estimator; GeniE), and literature-based approach which gathered variants through Mastermind Genomic Search Engine (Genomenon, Inc). Genetic prevalence of PLAN was calculated based on allele frequencies from gnomAD, assuming Hardy–Weinberg equilibrium. Results In the PLA2G6 gene, our analysis found 122 pathogenic, 82 VUS, and 15 variants with conflicting interpretations (pathogenic vs VUS) between two approaches . Allele frequency was available for 58 pathogenic, 42 VUS, and 15 conflicting variants in gnomAD database. If pathogenic and/or conflicting variants are included, the overall genetic prevalence was estimated to be between 1 in 987,267 to 1 in 1,570,079 pregnancies, with the highest genetic prevalence in African/African-American (1 in 421,960 to 1 in 365,197) and East-Asian (1 in 683,978 to 1 in 190,771) populations. Conclusion Our estimates highlight the significant underdiagnosis of PLA2G6-associated neurodegeneration and underscores the need for increased awareness and diagnostic efforts. Furthermore, our study revealed a higher carrier frequency of PLA2G6 variants in African and Asian populations, stressing the importance of expanded genetic sequencing in non-European populations to ensure accurate and comprehensive diagnosis. Future research should focus on confirming our findings and implementing expanded sequencing strategies to facilitate maximal and accurate diagnosis, particularly in non-European populations.

As length of stay after total knee arthroplasty (TKA) continues to shorten, interventions that may reduce early postoperative pain and complications must be studied. Peripheral nerve block is being explored as a potential means of improving pain management. The purpose of this study was to evaluate the impact of adductor canal block (ACB) on postoperative outcomes for patients undergoing TKA. We conducted a retrospective review of 565 patients who received unilateral TKA under spinal anesthesia with a periarticular anesthetic injection. Patients were divided by ACB status. Univariate comparisons and multivariate regression were used to compare outcomes for patients receiving ACBs vs those who did not. Of the 565 patients, 167 received an ACB, and 398 did not. Patients who received an ACB were less likely to require nausea medication during the immediate postoperative period. Length of stay, narcotic consumption, rate of discharge to home, postanesthesia care unit recovery time, urinary retention, ability to complete physical therapy, and 30-day readmission rate did not differ significantly between groups. After risk adjustment, the only significant finding was decreased likelihood of nausea in patients receiving an ACB. ACBs appear to have little to no significant impact on early clinical outcomes in patients having TKA under spinal anesthesia with a periarticular anesthetic injection. Further study of larger patient cohorts is required to validate these findings.

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

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias. Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Immunological complexity in atherosclerosis warrants targeted treatment of specific inflammatory cells that aggravate the disease. With the initiation of large phase III trials investigating immunomodulatory drugs for atherosclerosis, cardiovascular disease treatment enters a new era. We here propose a radically different approach: implementing and evaluating in vivo a combinatorial library of nanoparticles with distinct physiochemical properties and differential immune cell specificities. The library’s nanoparticles are based on endogenous high-density lipoprotein, which can preferentially deliver therapeutic compounds to pathological macrophages in atherosclerosis. Using the apolipoprotein E-deficient (Apoe −/−) mouse model of atherosclerosis, we quantitatively evaluated the library’s immune cell specificity by combining immunological techniques and in vivo positron emission tomography imaging. Based on this screen, we formulated a liver X receptor agonist (GW3965) and abolished its liver toxicity while still preserving its therapeutic function. Screening the immune cell specificity of nanoparticles can be used to develop tailored therapies for atherosclerosis and other inflammatory diseases.