Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease.

Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and, with new innovative methods, can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the Genomics Research to Elucidate the Genetics of Rare Diseases consortium and analyzed using the seqr platform. The addition of CNV detection to exome analysis identified causal CNVs for 171 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb. The causal CNVs consisted of 140 deletions, 15 duplications, 3 suspected complex structural variants (SVs), 3 insertions, and 10 complex SVs, the latter two groups being identified by orthogonal confirmation methods. To classify CNV variant pathogenicity, we used the 2020 American College of Medical Genetics and Genomics/ClinGen CNV interpretation standards and developed additional criteria to evaluate allelic and functional data as well as variants on the X chromosome to further advance the framework. We interpreted 151 CNVs as likely pathogenic/pathogenic and 20 CNVs as high-interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher-resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.

Genome Sequencing for Diagnosing Rare Diseases.

BACKGROUND: Genetic variants that cause rare disorders may remain elusive even after expansive testing, such as exome sequencing. The diagnostic yield of genome sequencing, particularly after a negative evaluation, remains poorly defined. METHODS: We sequenced and analyzed the genomes of families with diverse phenotypes who were suspected to have a rare monogenic disease and for whom genetic testing had not revealed a diagnosis, as well as the genomes of a replication cohort at an independent clinical center. RESULTS: We sequenced the genomes of 822 families (744 in the initial cohort and 78 in the replication cohort) and made a molecular diagnosis in 218 of 744 families (29.3%). Of the 218 families, 61 (28.0%) - 8.2% of families in the initial cohort - had variants that required genome sequencing for identification, including coding variants, intronic variants, small structural variants, copy-neutral inversions, complex rearrangements, and tandem repeat expansions. Most families in which a molecular diagnosis was made after previous nondiagnostic exome sequencing (63.5%) had variants that could be detected by reanalysis of the exome-sequence data (53.4%) or by additional analytic methods, such as copy-number variant calling, to exome-sequence data (10.8%). We obtained similar results in the replication cohort: in 33% of the families in which a molecular diagnosis was made, or 8% of the cohort, genome sequencing was required, which showed the applicability of these findings to both research and clinical environments. CONCLUSIONS: The diagnostic yield of genome sequencing in a large, diverse research cohort and in a small clinical cohort of persons who had previously undergone genetic testing was approximately 8% and included several types of pathogenic variation that had not previously been detected by means of exome sequencing or other techniques. (Funded by the National Human Genome Research Institute and others.).

"It's hard to wait": Provider perspectives on current genomic care in safety-net NICUs.

PURPOSE: Critically ill infants from marginalized populations disproportionately receive care in neonatal intensive care units (NICUs) that lack access to state-of-the-art genomic care, leading to inequitable outcomes. We sought provider perspectives to inform our implementation study (VIGOR) providing rapid genomic sequencing within these settings. METHODS: We conducted semistructured focus groups with neonatal and genetics providers at 6 NICUs at safety-net hospitals, informed by the Promoting Action on Research Implementation in Health Services framework, which incorporates evidence, context, and facilitation domains. We iteratively developed codes and themes until thematic saturation was reached. RESULTS: Regarding evidence, providers felt that genetic testing benefits infants and families. Regarding context, the major barriers identified to genomic care were genetic testing cost, lack of genetics expertise for disclosure and follow-up, and navigating the complexity of selecting and ordering genetic tests. Providers had negative feelings about the current status quo and inequity in genomic care across NICUs. Regarding facilitation, providers felt that a virtual support model such as VIGOR would address major barriers and foster family-centered care and collaboration. CONCLUSION: NICU providers at safety-net hospitals believe that access to state-of-the-art genomic care is critical for optimizing infant outcomes; yet, substantial barriers exist that the VIGOR study may address.

Multidimensional and Longitudinal Impact of a Genetic Diagnosis for Critically Ill Infants.

Background and Objectives: Many genetic conditions present in the neonatal intensive care unit (NICU), where a diagnostic evaluation is pursued. However, understanding of the impact of a genetic diagnosis on clinical outcomes and health-related quality of life for these infants remains incomplete. We therefore evaluated parent-reported outcomes complemented by clinical outcomes measures over one year for a cohort of infants in the NICU undergoing genetic evaluation. Methods: Prospective cohort study evaluating outcomes after genetics consultation in a level IV NICU via parent-report and electronic medical records (EMR) review. Eligible infants were genetically undiagnosed at enrollment. Parent surveys were administered at baseline and three, six-, and 12-months following enrollment and assessed genetic testing utility as well as parent-reported infant health-related quality of life using the Infant Toddler Quality of Life Questionnaire. Results: 110 infant-parent pairs were enrolled. Infants had a median age at enrollment of 15 days (interquartile range 8-37.75). At baseline, 74% (81/110) of parents endorsed high importance of finding a genetic diagnosis, but perceived importance significantly decreased over time. Over the study period, 38 infants received a molecular diagnosis per parent report, though this was discordant with EMR review. Identification of a diagnosis did not significantly impact health-related quality of life across most domains, which was lower overall than population norms. Conclusions: A genetic diagnosis is highly desired by parents in the NICU, though waning interest over time for undiagnosed families may reflect parental emotional adaptation and acceptance. Additional supports are needed to improve perceived quality of life.

Implementation of rapid genomic sequencing in safety-net neonatal intensive care units: protocol for the VIrtual GenOme CenteR (VIGOR) proof-of-concept study.

INTRODUCTION: Rapid genomic sequencing (rGS) in critically ill infants with suspected genetic disorders has high diagnostic and clinical utility. However, rGS has primarily been available at large referral centres with the resources and expertise to offer state-of-the-art genomic care. Critically ill infants from racial and ethnic minority and/or low-income populations disproportionately receive care in safety-net and/or community settings lacking access to state-of-the-art genomic care, contributing to unacceptable health equity gaps. VIrtual GenOme CenteR is a 'proof-of-concept' implementation science study of an innovative delivery model for genomic care in safety-net neonatal intensive care units (NICUs). METHODS AND ANALYSIS: We developed a virtual genome centre at a referral centre to remotely support safety-net NICU sites predominantly serving racial and ethnic minority and/or low-income populations and have limited to no access to rGS. Neonatal providers at each site receive basic education about genomic medicine from the study team and identify eligible infants. The study team enrols eligible infants (goal n of 250) and their parents and follows families for 12 months. Enrolled infants receive rGS, the study team creates clinical interpretive reports to guide neonatal providers on interpreting results, and neonatal providers return results to families. Data is collected via (1) medical record abstraction, (2) surveys, interviews and focus groups with neonatal providers and (3) surveys and interviews with families. We aim to examine comprehensive implementation outcomes based on the Proctor Implementation Framework using a mixed methods approach. ETHICS AND DISSEMINATION: This study is approved by the institutional review board of Boston Children's Hospital (IRB-P00040496) and participating sites. Participating families are required to provide electronic written informed consent and neonatal provider consent is implied through the completion of surveys. The results will be disseminated via peer-reviewed publications and data will be made accessible per National Institutes of Health (NIH) policies. TRIAL REGISTRATION NUMBER: NCT05205356/clinicaltrials.gov.

Genomic testing and molecular diagnosis among infants with congenital heart disease in the neonatal intensive care unit.

OBJECTIVE: To evaluate patterns of genetic testing among infants with CHD at a tertiary care center. STUDY DESIGN: We conducted a retrospective observational cohort study of infants in the NICU with suspicion of a genetic disorder. 1075 of 7112 infants admitted to BCH had genetic evaluation including 329 with CHD and 746 without CHD. 284 of 525 infants with CHD admitted to CMHH had genetic evaluation. Patterns of testing and diagnoses were compared. RESULTS: The rate of diagnosis after testing was similar for infants with or without CHD (38% [121/318] vs. 36% [246/676], p = 0.14). In a multiple logistic regression, atrioventricular septal defects were most high associated with genetic diagnosis (odds ratio 29.99, 95% confidence interval 2.69-334.12, p < 0.001). CONCLUSIONS: Infants with suspicion of a genetic disorder with CHD had similar rates of molecular diagnosis as those without CHD. These results support a role for genetic testing among NICU infants with CHD.

Unique Capabilities of Genome Sequencing for Rare Disease Diagnosis.

Background: Causal variants underlying rare disorders may remain elusive even after expansive gene panels or exome sequencing (ES). Clinicians and researchers may then turn to genome sequencing (GS), though the added value of this technique and its optimal use remain poorly defined. We therefore investigated the advantages of GS within a phenotypically diverse cohort. Methods: GS was performed for 744 individuals with rare disease who were genetically undiagnosed. Analysis included review of single nucleotide, indel, structural, and mitochondrial variants. Results: We successfully solved 218/744 (29.3%) cases using GS, with most solves involving established disease genes (157/218, 72.0%). Of all solved cases, 148 (67.9%) had previously had non-diagnostic ES. We systematically evaluated the 218 causal variants for features requiring GS to identify and 61/218 (28.0%) met these criteria, representing 8.2% of the entire cohort. These included small structural variants (13), copy neutral inversions and complex rearrangements (8), tandem repeat expansions (6), deep intronic variants (15), and coding variants that may be more easily found using GS related to uniformity of coverage (19). Conclusion: We describe the diagnostic yield of GS in a large and diverse cohort, illustrating several types of pathogenic variation eluding ES or other techniques. Our results reveal a higher diagnostic yield of GS, supporting the utility of a genome-first approach, with consideration of GS as a secondary or tertiary test when higher-resolution structural variant analysis is needed or there is a strong clinical suspicion for a condition and prior targeted genetic testing has been negative.