The cost and diagnostic yield of exome sequencing for children with suspected genetic disorders: a benchmarking study

The cost of genetic diagnosis of suspected hereditary pediatric cataracts with whole-exome sequencing from a middle-income country perspective: a mixed costing analysis

Up to 25% of pediatric cataract cases are inherited. There is sparse information in the literature regarding the cost of whole-exome sequencing (WES) for suspected hereditary pediatric cataracts. Molecular diagnosis of suspected hereditary pediatric cataracts is important for comprehensive genetic counseling. We performed a partial economic evaluation with a mixed costing analysis, using reimbursement data and microcosting approach with a bottom-up technique to estimate the cost of using WES for genetic diagnosis of suspected hereditary pediatric cataracts from the perspective of the Brazilian governmental health care system. One hundred and ten participants from twenty-nine families in Rio de Janeiro (RJ) were included. Costs of consumables, staff and equipment were calculated. Two scenarios were created: (1) The reference scenario included patients from RJ with suspected hereditary pediatric cataracts plus two family members. (2) The alternative scenario considered other genetic diseases, resulting in 5,280 exams per month. Sensitivity analysis was also performed. In the reference scenario, the total cost per exam was 700.09 United States dollars (USD), and in the alternative scenario, the total cost was 559.23 USD. The cost of WES alone was 527.85 USD in the reference scenario and 386.98 USD in the alternative scenario. Sensitivity analysis revealed that the largest costs were associated with consumables in both scenarios. Economic evaluations can help inform policy decisions, especially in middle-income countries such as Brazil.

Extending the new era of genomic testing into pregnancy management: A proposed model for Australian prenatal services

BACKGROUND

Trio exome sequencing can be used to investigate congenital abnormalities identified on pregnancy ultrasound, but its use in an Australian context has not been assessed.

AIMS

Assess clinical outcomes and changes in management after expedited genomic testing in the prenatal period to guide the development of a model for widespread implementation.

MATERIALS AND METHODS

Forty-three prospective referrals for whole exome sequencing, including 40 trios (parents and pregnancy), two singletons and one duo were assessed in a tertiary hospital setting with access to a state-wide pathology laboratory. Diagnostic yield, turn-around time (TAT), gestational age at reporting, pregnancy outcome, change in management and future pregnancy status were assessed for each family.

RESULTS

A clinically significant genomic diagnosis was made in 15/43 pregnancies (35%), with an average TAT of 12 days. Gestational age at time of report ranged from 16 + 5 to 31 + 6 weeks (median 21 + 3 weeks). Molecular diagnoses included neuromuscular and skeletal disorders, RASopathies and a range of other rare Mendelian disorders. The majority of families actively used the results in pregnancy decision making as well as in management of future pregnancies.

CONCLUSIONS

Rapid second trimester prenatal genomic testing can be successfully delivered to investigate structural abnormalities in pregnancy, providing crucial guidance for current and future pregnancy management. The time-sensitive nature of this testing requires close laboratory and clinical collaboration to ensure appropriate referral and result communication. We found the establishment of a prenatal coordinator role and dedicated reporting team to be important facilitators. We propose this as a model for genomic testing in other prenatal services.

Informing a value care model: lessons from an integrated adult neurogenomics clinic

BACKGROUND

Advances in genomics provide improved opportunities for diagnosis of complex neurogenetic disorders, yet the optimal approach to translate these benefits to the outpatient clinic is unclear.

AIMS

We retrospectively reviewed referral indications and outcomes of an integrated multidisciplinary team (MDT) clinic pathway for adults with suspected neurogenetic disorders. The associated cost implications were estimated.

METHODS

Consecutive patients who attended the neurogenomics clinic from January 2017 to April 2020 were included. The clinic comprised neurologists, clinical geneticists and genetic counsellors, who assessed each patient concurrently.

RESULTS

Ninety-nine new patients were referred spanning 45 different clinical diagnoses. Following MDT clinical assessment, 23% (23/99) of referral diagnoses were revised prior to molecular testing. Eighty-one patients (82%) underwent genetic testing, including 43 exome-based panels, 15 whole-genome sequencing, 14 single gene tests, 27 repeat-primed polymerase chain reaction testing and two chromosomal microarrays. Overall, 33/99 patients (33%) received a diagnosis, either a molecular diagnosis (n = 24, of which 22 were diagnostic and two were predictive) or a clinical diagnosis (n = 9). Of the clinical diagnosis cohort, five patients received a diagnosis without molecular testing and four patients whose negative testing (one diagnostic and three predictive) allowed exclusion of genetic differentials and, hence, confirmation of clinical diagnoses. The diagnostic rate following MDT and diagnostic testing was 30% (28/94), excluding the five predictive testing cases. MDT assessment aligned with eventual molecular diagnoses in 96% of cases. The estimated average costs were AU$1386 per patient undergoing MDT assessment and AU$4159 per diagnosis achieved.

CONCLUSIONS

We present an integrated multidisciplinary neurogenomics clinic pathway providing a diagnostic yield of 33% (30% excluding predictive testing cases), with costing implications. The relatively high diagnostic yield may be attributed to multidisciplinary input integrating accurate phenotyping of complex disorders and interpretation of genomic findings.

Genetic Discovery Enabled by A Large Language Model

Artificial intelligence (AI) has been used in many areas of medicine, and recently large language models (LLMs) have shown potential utility for clinical applications. However, since we do not know if the use of LLMs can accelerate the pace of genetic discovery, we used data generated from mouse genetic models to investigate this possibility. We examined whether a recently developed specialized LLM (Med-PaLM 2) could analyze sets of candidate genes generated from analysis of murine models of biomedical traits. In response to free-text input, Med-PaLM 2 correctly identified the murine genes that contained experimentally verified causative genetic factors for six biomedical traits, which included susceptibility to diabetes and cataracts. Med-PaLM 2 was also able to analyze a list of genes with high impact alleles, which were identified by comparative analysis of murine genomic sequence data, and it identified a causative murine genetic factor for spontaneous hearing loss. Based upon this Med-PaLM 2 finding, a novel bigenic model for susceptibility to spontaneous hearing loss was developed. These results demonstrate Med-PaLM 2 can analyze gene-phenotype relationships and generate novel hypotheses, which can facilitate genetic discovery.

Comprehensive prenatal diagnostics: Exome versus genome sequencing

OBJECTIVE

This study aimed to assess the diagnostic yield of prenatal genetic testing using trio whole exome sequencing (WES) and trio whole genome sequencing (WGS) in pregnancies with fetal anomalies by comparing the results with conventional chromosomal microarray (CMA) analysis.

METHODS

A total of 40 pregnancies with fetal anomalies or increased nuchal translucency (NT ≥ 5 mm) were included between the 12th and 21st week of gestation. Trio WES/WGS and CMA were performed in all cases.

RESULTS

The trio WES/WGS analysis increased the diagnostic yield by 25% in cases with negative CMA results. Furthermore, all six chromosomal aberrations identified by CMA were independently detected by WES/WGS analysis. In total, 16 out of 40 cases obtained a genetic sequence variant, copy number variant, or aneuploidy explaining the phenotype, resulting in an overall WES/WGS diagnostic yield of 40%. WES analysis provided a more reliable identification of mosaic sequence variants than WGS because of its higher sequencing depth.

CONCLUSIONS

Prenatal WES/WGS proved to be powerful diagnostic tools for fetal anomalies, surpassing the diagnostic yield of CMA. They have the potential to serve as standalone methods for prenatal diagnosis. The study highlighted the limitations of WGS in accurately detecting mosaic variants, which is particularly relevant when analyzing chorionic villus samples.

Diagnostic yield of pediatric and prenatal exome sequencing in a diverse population

The diagnostic yield of exome sequencing (ES) has primarily been evaluated in individuals of European ancestry, with less focus on underrepresented minority (URM) and underserved (US) patients. We evaluated the diagnostic yield of ES in a cohort of predominantly US and URM pediatric and prenatal patients suspected to have a genetic disorder. Eligible pediatric patients had multiple congenital anomalies and/or neurocognitive disabilities and prenatal patients had one or more structural anomalies, disorders of fetal growth, or fetal effusions. URM and US patients were prioritized for enrollment and underwent ES at a single academic center. We identified definitive positive or probable positive results in 201/845 (23.8%) patients, with a significantly higher diagnostic rate in pediatric (26.7%) compared to prenatal patients (19.0%) (P = 0.01). For both pediatric and prenatal patients, the diagnostic yield and frequency of inconclusive findings did not differ significantly between URM and non-URM patients or between patients with US status and those without US status. Our results demonstrate a similar diagnostic yield of ES between prenatal and pediatric URM/US patients and non-URM/US patients for positive and inconclusive results. These data support the use of ES to identify clinically relevant variants in patients from diverse populations.

Cost of exome analysis in patients with intellectual disability: a micro-costing study in a French setting

BACKGROUND

With the development of next generation sequencing technologies in France, exome sequencing (ES) has recently emerged as an opportunity to improve the diagnosis rate of patients presenting an intellectual disability (ID). To help French policy makers determine an adequate tariff for ES, we aimed to assess the unit cost per ES diagnostic test for ID from the preparation of the pre-analytical step until the report writing step and to identify its main cost drivers.

METHODS

A micro-costing bottom-up approach was conducted for the year 2018 in a French setting as part of the DISSEQ study, a cost-effectiveness study funded by the Ministry of Health and performed in collaboration with the GAD (Génétique des Anomalies du Développement), a genetic team from the Dijon University Hospital, and a public sequencing platform, the Centre National de Recherche en Génomique Humaine (CNRGH). The analysis was conducted from the point of view of these two ES stakeholders. All of the resources (labor, equipment, disposables and reagents, reusable material) required to analyze blood samples were identified, collected and valued. Several sensitivity analyses were performed.

RESULTS

The unit nominal cost per ES diagnostic test for ID was estimated to be €2,019.39. Labor represented 50.7% of the total cost. The analytical step (from the preparation of libraries to the analysis of sequences) represented 88% of the total cost. Sensitivity analyses suggested that a simultaneous price decrease of 20% for the capture kit and 50% for the sequencing support kit led to an estimation of €1,769 per ES diagnostic test for ID.

CONCLUSION

This is the first estimation of ES cost to be done in the French setting of ID diagnosis. The estimation is especially influenced by the price of equipment kits, but more generally by the organization of the centers involved in the different steps of the analysis and the time period in which the study was conducted. This information can now be used to define an adequate tariff and assess the efficiency of ES.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT03287206 on September 19, 2017.

Genome-Wide Sequencing Modalities for Children with Unexplained Global Developmental Delay and Intellectual Disabilities—A Narrative Review

Unexplained global developmental delay (GDD) and intellectual disabilities (ID) together affect nearly 2% of the pediatric population. Establishing an etiologic diagnosis is crucial for disease management, prognostic evaluation, and provision of physical and psychological support for both the patient and the family. Advancements in genome sequencing have allowed rapid accumulation of gene–disorder associations and have accelerated the search for an etiologic diagnosis for unexplained GDD/ID. We reviewed recent studies that utilized genome-wide analysis technologies, and we discussed their diagnostic yield, strengths, and limitations. Overall, exome sequencing (ES) and genome sequencing (GS) outperformed chromosomal microarrays and targeted panel sequencing. GS provides coverage for both ES and chromosomal microarray regions, providing the maximal diagnostic potential, and the cost of ES and reanalysis of ES-negative results is currently still lower than that of GS alone. Therefore, singleton or trio ES is the more cost-effective option for the initial investigation of individuals with GDD/ID in clinical practice compared to a staged approach or GS alone. Based on these updated evidence, we proposed an evaluation algorithm with ES as the first-tier evaluation for unexplained GDD/ID.

Genetic and metabolic investigations for neurodevelopmental disorders: position statement of the Canadian College of Medical Geneticists (CCMG)

PURPOSE AND SCOPE

The aim of this position statement is to provide recommendations for clinicians regarding the use of genetic and metabolic investigations for patients with neurodevelopmental disorders (NDDs), specifically, patients with global developmental delay (GDD), intellectual disability (ID) and/or autism spectrum disorder (ASD). This document also provides guidance for primary care and non-genetics specialists caring for these patients while awaiting consultation with a clinical geneticist or metabolic specialist.

METHODS OF STATEMENT DEVELOPMENT

A multidisciplinary group reviewed existing literature and guidelines on the use of genetic and metabolic investigations for the diagnosis of NDDs and synthesised the evidence to make recommendations relevant to the Canadian context. The statement was circulated for comment to the Canadian College of Medical Geneticists (CCMG) membership-at-large and to the Canadian Pediatric Society (Mental Health and Developmental Disabilities Committee); following incorporation of feedback, it was approved by the CCMG Board of Directors on 1 September 2022.

RESULTS AND CONCLUSIONS

Chromosomal microarray is recommended as a first-tier test for patients with GDD, ID or ASD. Fragile X testing should also be done as a first-tier test when there are suggestive clinical features or family history. Metabolic investigations should be done if there are clinical features suggestive of an inherited metabolic disease, while the patient awaits consultation with a metabolic physician. Exome sequencing or a comprehensive gene panel is recommended as a second-tier test for patients with GDD or ID. Genetic testing is not recommended for patients with NDDs in the absence of GDD, ID or ASD, unless accompanied by clinical features suggestive of a syndromic aetiology or inherited metabolic disease.

Economic evaluation of next-generation sequencing techniques in diagnosis of genetic disorders: A systematic review

In recent years, massively parallel sequencing or next generation sequencing (NGS) has considerably changed both the research and diagnostic fields, and rapid developments have led to the combination of NGS techniques in clinical practice, ease of analysis, and detection of genetic mutations. This article aimed at reviewing the economic evaluation studies of the NGS techniques in the diagnosis of genetic diseases. In this systematic review, scientific databases (PubMed, EMBASE, Web of Science, Cochrane, Scopus, and CEA registry) were searched from 2005 to 2022 to identify the related literature on the economic evaluation of NGS techniques in the diagnosis of genetic diseases. Full-text reviews and data extraction were all performed by two independent researchers. The quality of all the articles included in this study was evaluated using the Checklist of Quality of Health Economic Studies (QHES). Out of 20 521 screened abstracts, 36 studies met the inclusion criteria. The mean score of the QHES checklist for the studies was 0.78 (high quality). Seventeen studies were conducted based on modeling. Cost-effectiveness analysis, cost-utility analysis, and cost-minimization analysis were done in 26 studies, 13 studies, and 1 study, respectively. Based on the available evidence and findings, exome sequencing, which is one of the NGS techniques, could have the potential to be used as a cost-effective genomic test to diagnose children with suspected genetic diseases. The results of the present study support the cost-effectiveness of exome sequencing in diagnosing suspected genetic disorders. However, the use of exome sequencing as a first- or second-line diagnostic test is still controversial. Most studies have been conducted in high-income countries, and research on the cost-effectiveness of NGS methods is recommended in low- and middle-income countries.

Genetically transitional disease: a new concept in genomic medicine

Traditional classification of genetic diseases as monogenic and polygenic has lagged far behind scientific progress. In this opinion article, we propose and define a new terminology, genetically transitional disease (GTD), referring to cases where a large-effect mutation is necessary, but not sufficient, to cause disease. This leads to a working disease nosology based on gradients of four types of genetic architecture: monogenic, polygenic, GTD, and mixed. We present four scenarios under which GTD may occur; namely, subsets of traditionally Mendelian disease, modifiable Tier 1 monogenic conditions, variable penetrance, and situations where a genetic mutational spectrum produces qualitatively divergent pathologies. The implications of the new nosology in precision medicine are discussed, in which therapeutic options may target the molecular cause or the disease phenotype.

Systematic genetic analysis of pediatric patients with autoinflammatory diseases

Monogenic autoinflammatory diseases (AID) encompass a growing group of inborn errors of the innate immune system causing unprovoked or exaggerated systemic inflammation. Diagnosis of monogenic AID requires an accurate description of the patients' phenotype, and the identification of highly penetrant genetic variants in single genes is pivotal. We performed whole exome sequencing (WES) of 125 pediatric patients with suspected monogenic AID in a routine genetic diagnostic setting. Datasets were analyzed in a step-wise approach to identify the most feasible diagnostic strategy. First, we analyzed a virtual gene panel including 13 genes associated with known AID and, if no genetic diagnosis was established, we then analyzed a virtual panel including 542 genes published by the International Union of Immunological Societies associated including all known inborn error of immunity (IEI). Subsequently, WES data was analyzed without pre-filtering for known AID/IEI genes. Analyzing 13 genes yielded a definite diagnosis in 16.0% (n = 20). The diagnostic yield was increased by analyzing 542 genes to 20.8% (n = 26). Importantly, expanding the analysis to WES data did not increase the diagnostic yield in our cohort, neither in single WES analysis, nor in trio-WES analysis. The study highlights that the cost- and time-saving analysis of virtual gene panels is sufficient to rapidly confirm the differential diagnosis in pediatric patients with AID. WES data or trio-WES data analysis as a first-tier diagnostic analysis in patients with suspected monogenic AID is of limited benefit.

The practice of genomic medicine: A delineation of the process and its governing principles

Genomic medicine, an emerging medical discipline, applies the principles of evolution, developmental biology, functional genomics, and structural genomics within clinical care. Enabling widespread adoption and integration of genomic medicine into clinical practice is key to achieving precision medicine. We delineate a biological framework defining diagnostic utility of genomic testing and map the process of genomic medicine to inform integration into clinical practice. This process leverages collaboration and collective cognition of patients, principal care providers, clinical genomic specialists, laboratory geneticists, and payers. We detail considerations for referral, triage, patient intake, phenotyping, testing eligibility, variant analysis and interpretation, counseling, and management within the utilitarian limitations of health care systems. To reduce barriers for clinician engagement in genomic medicine, we provide several decision-making frameworks and tools and describe the implementation of the proposed workflow in a prototyped electronic platform that facilitates genomic care. Finally, we discuss a vision for the future of genomic medicine and comment on areas for continued efforts.

Applying whole exome sequencing in a consanguineous population with autism spectrum disorder

This study aimed to systematically assess the impact of clinical and demographic variables on the diagnostic yield of Whole Exome Sequencing (WES) when applied to children with Autism Spectrum Disorder (ASD) from a consanguineous population. Ninety-seven children were included in the analysis, 63% were male and 37% were females. 77.3% had a suspected syndromic aetiology of which 68% had co-existent central nervous system (CNS) clinical features, while 69% had other systems involved. The diagnostic yield of WES in our cohort with ASD was 34%. Children with seizures were more likely to have positive WES results (46% vs. 31%, p = 0.042). Probands with suspected syndromic ASD aetiology showed no significant differential impact on the diagnostic yield of WES.

Genetic diagnosis for adult patients at a genetic clinic

Clinical utility of genetic testing has rapidly increased in the past decade to identify the definitive diagnosis, etiology, and specific management. The majority of patients receiving testing are children. There are several barriers for genetic tests in adult patients; barriers may arise from either patients or clinicians. Our study aims to realize the detection rate and the benefits of genetic tests in adults. We conducted a prospective study of 10 adult patients who were referred to a genetic clinic. Exome sequencing (ES) was pursued in all cases, and chromosomal microarray (CMA) was performed for six cases. Our result is impressive; six cases (60%) received likely pathogenic and pathogenic variants. Four definitive diagnosis cases had known pathogenic variants in KCNJ2, TGFBR1, SCN1A, and FBN1, whereas another two cases revealed novel likely pathogenic and pathogenic variants in GNB1 and DNAH9. Our study demonstrates the success in genetic diagnosis in adult patients: four cases with definitive, two cases with possible, and one case with partial diagnosis. The advantage of diagnosis is beyond obtaining the diagnosis itself, but also relieving any doubt for the patient regarding any previous questionable diagnosis, guide for management, and recurrence risk in their children or family members. Therefore, this supports the value of genetic testing in adult patients.

Genome sequencing is a sensitive first-line test to diagnose individuals with intellectual disability

PURPOSE

Individuals with intellectual disability (ID) and/or neurodevelopment disorders (NDDs) are currently investigated with several different approaches in clinical genetic diagnostics.

METHODS

We compared the results from 3 diagnostic pipelines in patients with ID/NDD: genome sequencing (GS) first (N = 100), GS as a secondary test (N = 129), or chromosomal microarray (CMA) with or without FMR1 analysis (N = 421).

RESULTS

The diagnostic yield was 35% (GS-first), 26% (GS as a secondary test), and 11% (CMA/FMR1). Notably, the age of diagnosis was delayed by 1 year when GS was performed as a secondary test and the cost per diagnosed individual was 36% lower with GS first than with CMA/FMR1. Furthermore, 91% of those with a negative result after CMA/FMR1 analysis (338 individuals) have not yet been referred for additional genetic testing and remain undiagnosed.

CONCLUSION

Our findings strongly suggest that genome analysis outperforms other testing strategies and should replace traditional CMA and FMR1 analysis as a first-line genetic test in individuals with ID/NDD. GS is a sensitive, time- and cost-effective method that results in a confirmed molecular diagnosis in 35% of all referred patients.

Real-world economic evaluation of prospective rapid whole-genome sequencing compared to a matched retrospective cohort of critically ill pediatric patients in the United States

There is an increasing demand for supporting the adoption of rapid whole-genome sequencing (rWGS) by demonstrating its real-world value. We aimed to assess the cost-effectiveness of rWGS in critically ill pediatric patients with diseases of unknown cause. Data were collected prospectively of patients admitted to the Nicklaus Children's Hospital's intensive care units from March 2018 to September 2020, with rWGS (N = 65). Comparative data were collected in a matched retrospective cohort with standard diagnostic genetic testing. We determined total costs, diagnostic yield (DY), and incremental cost-effectiveness ratio (ICER) adjusted for selection bias and right censoring. Sensitivity analyses explored the robustness of ICER through bootstrapping. rWGS resulted in a diagnosis in 39.8% while standard testing in 13.5% (p = 0.026). rWGS resulted in a mean saving per person of $100,440 (SE = 26,497, p < 0.001) and a total of $6.53 M for 65 patients. rWGS in critically ill pediatric patients is cost-effective, cost-saving, shortens diagnostic odyssey, and triples the DY of traditional approaches.

Trio genome sequencing for developmental delay and pediatric heart conditions: A comparative microcost analysis

PURPOSE

Genome sequencing (GS) can aid clinical management of multiple pediatric conditions. Insurers require accurate cost information to inform funding and implementation decisions. The objective was to compare the laboratory workflows and microcosts of trio GS testing in children with developmental delay (DD) and in children with cardiac conditions.

METHODS

Cost items related to each step in trio GS (child and 2 parents) for both populations were identified and measured. Program costs over 5 years were estimated. Probabilistic and deterministic analyses were conducted.

RESULTS

The mean cost per trio GS was CAD$6634.11 (95% CI = 6352.29-6913.40) for DD and CAD$8053.10 (95% CI = 7699.30-8558.10) for cardiac conditions. The 5-year program cost was CAD$28.11 million (95% CI = 26.91-29.29) for DD and CAD$5.63 million (95% CI = 5.38-5.98) for cardiac conditions. Supplies constituted the largest cost component for both populations. The higher cost per sample for the population with cardiac conditions was due to the inclusion of pharmacogenomics, higher bioinformatics labor costs, and a more labor intensive case review.

CONCLUSION

This analysis indicated important variation in trio GS workflow and costs between pediatric populations in a single institution. Enhanced understanding of the clinical utility and costs of GS can inform harmonization and implementation decision-making.

Clinical and biochemical footprints of inherited metabolic disorders. VII. Ocular phenotypes

Ocular manifestations are observed in approximately one third of all inherited metabolic disorders (IMDs). Although ocular involvement is not life-threatening, it can result in severe vision loss, thereby leading to an additional burden for the patient. Retinal degeneration with or without optic atrophy is the most frequent phenotype, followed by oculomotor problems, involvement of the cornea and lens, and refractive errors. These phenotypes can provide valuable clues that contribute to its diagnosis. In this issue we found 577 relevant IMDs leading to ophthalmologic manifestations. This article is the seventh of a series attempting to create and maintain a comprehensive list of clinical and metabolic differential diagnoses according to system involvement.

Genome-wide Sequencing and the Clinical Diagnosis of Genetic Disease: The CAUSES Study

Genome-wide sequencing (GWS) is a standard of care for diagnosis of suspected genetic disorders, but the proportion of patients found to have pathogenic or likely pathogenic variants ranges from less than 30% to more than 60% in reported studies. It has been suggested that the diagnostic rate can be improved by interpreting genomic variants in the context of each affected individual’s full clinical picture and by regular follow-up and reinterpretation of GWS laboratory results.

Trio exome sequencing was performed in 415 families and trio genome sequencing in 85 families in the CAUSES study. The variants observed were interpreted by a multidisciplinary team including laboratory geneticists, bioinformaticians, clinical geneticists, genetic counselors, pediatric subspecialists, and the referring physician, and independently by a clinical laboratory using standard American College of Medical Genetics and Genomics (ACMG) criteria. Individuals were followed for an average of 5.1 years after testing, with clinical reassessment and reinterpretation of the GWS results as necessary. The multidisciplinary team established a diagnosis of genetic disease in 43.0% of the families at the time of initial GWS interpretation, and longitudinal follow-up and reinterpretation of GWS results produced new diagnoses in 17.2% of families whose initial GWS interpretation was uninformative or uncertain. Reinterpretation also resulted in rescinding a diagnosis in four families (1.9%). Of the families studied, 33.6% had ACMG pathogenic or likely pathogenic variants related to the clinical indication. Close collaboration among clinical geneticists, genetic counselors, laboratory geneticists, bioinformaticians, and individuals’ primary physicians, with ongoing follow-up, reanalysis, and reinterpretation over time, can improve the clinical value of GWS.

Lessons learned: next-generation sequencing applied to undiagnosed genetic diseases

Rare genetic disorders, when considered together, are relatively common. Despite advancements in genetics and genomics technologies as well as increased understanding of genomic function and dysfunction, many genetic diseases continue to be difficult to diagnose. The goal of this Review is to increase the familiarity of genetic testing strategies for non-genetics providers. As genetic testing is increasingly used in primary care, many subspecialty clinics, and various inpatient settings, it is important that non-genetics providers have a fundamental understanding of the strengths and weaknesses of various genetic testing strategies as well as develop an ability to interpret genetic testing results. We provide background on commonly used genetic testing approaches, give examples of phenotypes in which the various genetic testing approaches are used, describe types of genetic and genomic variations, cover challenges in variant identification, provide examples in which next-generation sequencing (NGS) failed to uncover the variant responsible for a disease, and discuss opportunities for continued improvement in the application of NGS clinically. As genetic testing becomes increasingly a part of all areas of medicine, familiarity with genetic testing approaches and result interpretation is vital to decrease the burden of undiagnosed disease.

Cost-effectiveness of whole-exome sequencing in progressive neurological disorders of children

OBJECTIVES

To clarify the diagnostic utility and the cost-effectiveness of whole-exome sequencing (WES) as a routine early-diagnostic tool in children with progressive neurological disorders.

METHODS

Patients with infantile-onset severe neurological diseases or childhood-onset progressive neurological disorders were prospectively recruited to this WES study, in the pediatric neurology clinic at Helsinki University Hospital during 2016-2018. A total of 48 patients underwent a singleton WES. A control group of 49 children underwent traditional diagnostic examinations and were retrospectively collected from the hospital records. Their use of health care services, related to the diagnostic process, was gathered. Incremental cost-effectiveness ratio (ICER) per additional diagnosis was calculated from the health care provider perspective. Bootstrapping methods were used to estimate the uncertainty of cost-effectiveness outcomes.

RESULTS

WES provided a better diagnostic yield (38%) than diagnostic pathway that did not prioritize WES in early diagnosis (25%). WES outperformed other diagnostic paths especially when made early, within one year of first admission (44%). Cost-effectiveness in our results are conservative, affected by WES costs during 2016-18.

CONCLUSIONS

WES is an efficient and cost-effective diagnostic tool that should be prioritized in early diagnostic path of children with progressive neurological disorders. The progressively decreasing price of the test improves cost-effectiveness further.

The diagnostic trajectory of infants and children with clinical features of genetic disease

We characterized US pediatric patients with clinical indicators of genetic diseases, focusing on the burden of disease, utilization of genetic testing, and cost of care. Curated lists of diagnosis, procedure, and billing codes were used to identify patients with clinical indicators of genetic disease in healthcare claims from Optum's de-identified Clinformatics® Database (13,076,038 unique patients). Distinct cohorts were defined to represent permissive and conservative estimates of the number of patients. Clinical phenotypes suggestive of genetic diseases were observed in up to 9.4% of pediatric patients and up to 44.7% of critically-ill infants. Compared with controls, patients with indicators of genetic diseases had higher utilization of services (e.g., mean NICU length of stay of 31.6d in a cohort defined by multiple congenital anomalies or neurological presentations compared with 10.1d for patients in the control population (P < 0.001)) and higher overall costs. Very few patients received any genetic testing (4.2-8.4% depending on cohort criteria). These results highlight the substantial proportion of the population with clinical features associated with genetic disorders and underutilization of genetic testing in these populations.

A data-driven architecture using natural language processing to improve phenotyping efficiency and accelerate genetic diagnoses of rare disorders

Effective genetic diagnosis requires the correlation of genetic variant data with detailed phenotypic information. However, manual encoding of clinical data into machine-readable forms is laborious and subject to observer bias. Natural language processing (NLP) of electronic health records has great potential to enhance reproducibility at scale but suffers from idiosyncrasies in physician notes and other medical records. We developed methods to optimize NLP outputs for automated diagnosis. We filtered NLP-extracted Human Phenotype Ontology (HPO) terms to more closely resemble manually extracted terms and identified filter parameters across a three-dimensional space for optimal gene prioritization. We then developed a tiered pipeline that reduces manual effort by prioritizing smaller subsets of genes to consider for genetic diagnosis. Our filtering pipeline enabled NLP-based extraction of HPO terms to serve as a sufficient replacement for manual extraction in 92% of prospectively evaluated cases. In 75% of cases, the correct causal gene was ranked higher with our applied filters than without any filters. We describe a framework that can maximize the utility of NLP-based phenotype extraction for gene prioritization and diagnosis. The framework is implemented within a cloud-based modular architecture that can be deployed across health and research institutions.

Genome sequencing data analysis for rare disease gene discovery

Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.

Magnitude of Mendelian versus complex inheritance of rare disorders

In medical genetics, the vast majority of patients with a currently known genetic basis harbor a rare deleterious allele explaining its Mendelian inheritance. Increasingly, for these phenotypes, we recognize exceptions to Mendelian expectations from non-penetrance of clinical disease to significant inter-individual variation in clinical manifestations, likely reflecting the actions of additional modifier genes. Despite recent progress, we still remain ignorant about the molecular basis for many rare disorders presumed to be Mendelian. The molecular evidence increasingly suggests a role for multiple genes in some of these cases, but for how many? In this article, I discuss why equating a phenotype as Mendelian or complex may be short-sighted or even erroneous. As we learn more about the functions of the human genome with its genes in networks, we should view the phenotype of an individual patient as arising from his or her total genomic deleterious burden in a set of functionally inter-related genes affecting that phenotype. This can sometimes arise from deleterious allele(s) at a single gene (Mendelian inheritance) creating a specific biochemical deficiency (or excess) but could just as frequently arise from the cumulative effects of multiple disease alleles (complex inheritance) leading to the same biochemical deficiency (or excess).

Has translational genomics come of age in Africa?

The rapid increase in genomics research in Africa and the growing promise of precision public health begs the question of whether African genomics has come of age and is being translated into improved healthcare for Africans. An assessment of the continent's readiness suggests that genetic service delivery remains limited and extremely fragile. The paucity of data on mutation profiles for monogenic disorders and lack of large genome-wide association cohorts for complex traits in African populations is a significant barrier, coupled with extreme genetic variation across different regions and ethnic groups. Data from many different populations is essential to developing appropriate genetic services. Of the proposed genetic service delivery models currently used in Africa-Uncharacterized, Limited, Disease-focused, Emerging and Established-the first three best describe the situation in most African countries. Implementation is fraught with difficulties related to the scarcity of an appropriately skilled medical genetic workforce, limited infrastructure and processes, insufficient health funding and lack of political support, and overstretched health systems. There is a strong nucleus of determined and optimistic clinicians and scientists with a clear vision, and there is hope for innovative solutions and technological leapfrogging. However, a multi-dimensional approach with active interventions to stimulate genomic research, clinical genetics and overarching healthcare systems is needed to reduce genetic service inequalities and accelerate precision public health on the continent. Human and infrastructure capacity development, dedicated funding, political will and supporting legislation, and public education and awareness, are critical elements for success. Africa-relevant genomic and related health economics research remains imperative with an overarching need to translate knowledge into improved healthcare. Given the limited data and genetic services across most of Africa, the continent has not yet come of 'genomics' age.

Cruxome: a powerful tool for annotating, interpreting and reporting genetic variants

Background

Next-generation sequencing (NGS) is an efficient tool used for identifying pathogenic variants that cause Mendelian disorders. However, the lack of bioinformatics training of researchers makes the interpretation of identified variants a challenge in terms of precision and efficiency. In addition, the non-standardized phenotypic description of human diseases also makes it difficult to establish an integrated analysis pathway for variant annotation and interpretation. Solutions to these bottlenecks are urgently needed.

Results

We develop a tool named “Cruxome” to automatically annotate and interpret single nucleotide variants (SNVs) and small insertions and deletions (InDels). Our approach greatly simplifies the current burdensome task of clinical geneticists and scientists to identify the causative pathogenic variants and build personal knowledge reference bases. The integrated architecture of Cruxome offers key advantages such as an interactive and user-friendly interface and the assimilation of electronic health records of the patient. By combining a natural language processing algorithm, Cruxome can efficiently process the clinical description of diseases to HPO standardized vocabularies. By using machine learning, in silico predictive algorithms, integrated multiple databases and supplementary tools, Cruxome can automatically process SNVs and InDels variants (trio-family or proband-only cases) and clinical diagnosis records, then annotate, score, identify and interpret pathogenic variants to finally generate a standardized clinical report following American College of Medical Genetics and Genomics/ Association for Molecular Pathology (ACMG/AMP) guidelines. Cruxome also provides supplementary tools to examine and visualize the genes or variations in historical cases, which can help to better understand the genetic basis of the disease.

Conclusions

Cruxome is an efficient tool for annotation and interpretation of variations and dramatically reduces the workload for clinical geneticists and researchers to interpret NGS results, simplifying their decision-making processes. We present an online version of Cruxome, which is freely available to academics and clinical researchers. The site is accessible at http://114.251.61.49:10024/cruxome/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07728-6.

Diagnosing newborns with suspected mitochondrial disorders: an economic evaluation comparing early exome sequencing to current typical care

PURPOSE

To determine the value of early exome sequencing (eES) relative to the current typical care (TC) in the diagnosis of newborns with suspected severe mitochondrial disorders (MitD).

METHODS

We used a decision tree-Markov hybrid to model neonatal intensive care unit (NICU)-related outcomes and costs, lifetime costs and quality-adjusted life-years among patients with MitD. Probabilities, costs, and utilities were populated using published literature, expert opinion, and the Pediatric Health Information System database. Incremental cost-effectiveness ratios (ICER) and net monetary benefits (NMB) were calculated from lifetime costs and quality-adjusted life-years for singleton and trio eES, and TC. Robustness was assessed using univariate and probabilistic sensitivity analyses (PSA). Scenario analyses were also conducted.

RESULTS

Findings indicate trio eES is a cost-minimizing and cost-effective alternative to current TC. Diagnostic probabilities and NICU length-of-stay were the most sensitive model parameters. Base case analysis demonstrates trio eES has the highest incremental NMB, and PSA demonstrates trio eES had the highest likelihood of being cost-effective at a willingness-to-pay (WTP) of $200,000 relative to TC, singleton eES, and no ES.

CONCLUSION

Trio and singleton eES are cost-effective and cost-minimizing alternatives to current TC in diagnosing newborns suspected of having a severe MitD.

Utilization of telehealth in paediatric genome-wide sequencing: Health services implementation issues in the CAUSES Study

INTRODUCTION

Genome-wide sequencing (exome or whole genome) is transforming the care and management of paediatric patients with a rare disease because of its diagnostic capabilities. Genome-wide sequencing is most effective when both parents and the child are sequenced as a trio. Genetic counselling is recommended for all families considering genome-wide sequencing. Although telehealth is well established in genetic counselling for hereditary cancer and prenatal genetics, its use with genome-wide sequencing has not been well studied. The CAUSES Clinic at BC Children's and Women's Hospitals was a translational paediatric trio-based genome-wide sequencing initiative. Pre-test genetic counselling via telehealth (at a clinical site near the family's residence) was offered to families who had been previously evaluated by a clinical geneticist. We report on the first 300 families seen in the CAUSES clinic and compare health services implementation issues of families seen via telehealth versus on-site.

METHODS

Demographics, cost to families (travel and time), time to first appointment, complete trio sample accrual and diagnostic rates were studied.

RESULTS

Of the 300 patients, 58 (19%) were seen via telehealth and 242 (81%) were seen on-site for pre-test counselling. The mean time to completion of accrual of trio samples in the telehealth group was 56.3 (standard deviation ±87.3) days versus 18.9 (standard deviation ±62.4) days in the onsite group (p < 2.2 × 10^-16). The mean per-family estimated actual or potential travel/time cost savings were greater in the telehealth group (Can$987; standard deviation = Can$1151) than for those seen on-site (Can$305; standard deviation = Can$589) (p = 0.0004).

CONCLUSIONS

Telehealth allowed for access to genome-wide sequencing for families in remote communities and for them to avoid significant travel and time costs; however, there was a significant delay to accrual of the complete trio samples in the telehealth group, impacting on time of result reporting and delaying diagnoses for families for whom genome-wide sequencing was diagnostic.

Exome Sequencing for Isolated Congenital Hearing Loss: A Cost-Effectiveness Analysis

OBJECTIVES/HYPOTHESIS

To assess the relative cost-effectiveness of exome sequencing for isolated congenital deafness compared with standard care.

STUDY DESIGN

Incremental cost-effectiveness and cost-benefit analyses were undertaken from the perspective of the Australian healthcare system using an 18-year time horizon.

METHODS

A decision tree was used to model the costs and outcomes associated with exome sequencing and standard care for infants presenting with isolated congenital deafness.

RESULTS

Exome sequencing resulted in an incremental cost of AU$1,000 per child and an additional 30 diagnoses per 100 children tested. The incremental cost-effectiveness ratio was AU$3,333 per additional diagnosis. The mean societal willingness to pay for exome sequencing was estimated at AU$4,600 per child tested relative to standard care, resulting in a positive net benefit of AU$3,600. Deterministic and probabilistic sensitivity analyses confirmed the cost-effectiveness of exome sequencing.

CONCLUSIONS

Our findings demonstrate the cost-effectiveness of exome sequencing in congenital hearing loss, through increased diagnostic rate and consequent improved process of care by reducing or ceasing diagnostic investigation or facilitating targeted further investigation. We recommend equitable funding for exome sequencing in infants presenting with isolated congenital hearing loss.

LEVEL OF EVIDENCE

N/A. Laryngoscope, 131:E2371-E2377, 2021.

A pipeline-friendly software tool for genome diagnostics to prioritize genes by matching patient symptoms to literature

Despite an explosive growth of next-generation sequencing data, genome diagnostics only provides a molecular diagnosis to a minority of patients. Software tools that prioritize genes based on patient symptoms using known gene-disease associations may complement variant filtering and interpretation to increase chances of success. However, many of these tools cannot be used in practice because they are embedded within variant prioritization algorithms, or exist as remote services that cannot be relied upon or are unacceptable because of legal/ethical barriers. In addition, many tools are not designed for command-line usage, closed-source, abandoned, or unavailable. We present Variant Interpretation using Biomedical literature Evidence (VIBE), a tool to prioritize disease genes based on Human Phenotype Ontology codes. VIBE is a locally installed executable that ensures operational availability and is built upon DisGeNET-RDF, a comprehensive knowledge platform containing gene-disease associations mostly from literature and variant-disease associations mostly from curated source databases. VIBE's command-line interface and output are designed for easy incorporation into bioinformatic pipelines that annotate and prioritize variants for further clinical interpretation. We evaluate VIBE in a benchmark based on 305 patient cases alongside seven other tools. Our results demonstrate that VIBE offers consistent performance with few cases missed, but we also find high complementarity among all tested tools. VIBE is a powerful, free, open source and locally installable solution for prioritizing genes based on patient symptoms. Project source code, documentation, benchmark and executables are available at https://github.com/molgenis/vibe.

Cost-effectiveness of genome-wide sequencing for unexplained developmental disabilities and multiple congenital anomalies

PURPOSE

Genetic testing is routine practice for individuals with unexplained developmental disabilities and multiple congenital anomalies. However, current testing pathways can be costly and time consuming, and the diagnostic yield low. Genome-wide sequencing, including exome sequencing (ES) and genome sequencing (GS), can improve diagnosis, but at a higher cost. This study aimed to assess the cost-effectiveness of genome-wide sequencing in Ontario, Canada.

METHODS

A cost-effectiveness analysis was conducted using a discrete event simulation from a public payer perspective. Six strategies involving ES or GS were compared. Outcomes reported were direct medical costs, number of molecular diagnoses, number of positive findings, and number of active treatment changes.

RESULTS

If ES was used as a second-tier test (after the current first-tier, chromosomal microarray, fails to provide a diagnosis), it would be less costly and more effective than standard testing (CAN$6357 [95% CI: 6179-6520] vs. CAN$8783 per patient [95% CI: 2309-31,123]). If ES was used after standard testing, it would cost an additional CAN$15,228 to identify the genetic diagnosis for one additional patient compared with standard testing. The results remained robust when parameters and assumptions were varied.

CONCLUSION

ES would likely be cost-saving if used earlier in the diagnostic pathway.

(Un)standardized testing: the diagnostic odyssey of children with rare genetic disorders in Alberta, Canada

PURPOSE

We provide a description of the diagnostic odyssey for a cohort of children seeking diagnosis of a rare genetic disorder in terms of the time from initial consultation to most recent visit or receipt of diagnosis, the number of tests per patient, and the types of tests received.

METHODS

Retrospective chart review of 299 children seen at the Alberta Children's Hospital (ACH) Genetics Clinic (GC) for whom the result of at least one single-gene test, gene panel, or chromosome microarray analysis (CMA) was recorded.

RESULTS

Of 299 patients, 90 (30%) received a diagnosis in the period of the review. Patients had an average of 5.4 tests each; 236 (79%) patients received CMA; 172 (58%) patients received single-gene tests and 34 (11%) received gene panels; 167 (56%) underwent imaging/electrical activity studies. The mean observation period was 898 days (95% confidence interval [CI] 791, 1004). Among patients with visits recorded prior to visiting ACH GC, 43% of the total observation time occurred prior to the GC.

CONCLUSION

As genomic technologies expand, the nature of the diagnostic odyssey will change. This study has outlined the current standard of care in the ACH GC, providing a baseline against which future changes can be assessed.

Interpretable Clinical Genomics with a Likelihood Ratio Paradigm

Human Phenotype Ontology (HPO)-based analysis has become standard for genomic diagnostics of rare diseases. Current algorithms use a variety of semantic and statistical approaches to prioritize the typically long lists of genes with candidate pathogenic variants. These algorithms do not provide robust estimates of the strength of the predictions beyond the placement in a ranked list, nor do they provide measures of how much any individual phenotypic observation has contributed to the prioritization result. However, given that the overall success rate of genomic diagnostics is only around 25%-50% or less in many cohorts, a good ranking cannot be taken to imply that the gene or disease at rank one is necessarily a good candidate. Here, we present an approach to genomic diagnostics that exploits the likelihood ratio (LR) framework to provide an estimate of (1) the posttest probability of candidate diagnoses, (2) the LR for each observed HPO phenotype, and (3) the predicted pathogenicity of observed genotypes. LIkelihood Ratio Interpretation of Clinical AbnormaLities (LIRICAL) placed the correct diagnosis within the first three ranks in 92.9% of 384 case reports comprising 262 Mendelian diseases, and the correct diagnosis had a mean posttest probability of 67.3%. Simulations show that LIRICAL is robust to many typically encountered forms of genomic and phenomic noise. In summary, LIRICAL provides accurate, clinically interpretable results for phenotype-driven genomic diagnostics.

Integration of genetic counsellors in genomic testing triage: Outcomes of a genomic consultation service in British Columbia, Canada

PURPOSE

Clinical diagnostic genome-wide (exome or genome) sequencing (GWS) in British Columbia requires funding approval by a provincial agency on a case-by-case basis. The CAUSES Clinic was a pediatric translational trio-based GWS study at BC Children's and Women's Hospitals. Referrals to the CAUSES Clinic were made through a Genomic Consultation Service (GCS), a multidisciplinary team led by genetic counsellors that provided advice regarding genomic testing for physicians considering GWS for their patients. Here we review the outcomes of the GCS, focusing on patients not recommended for the CAUSES Study.

METHODS

Demographic, clinical, and testing data were abstracted from patient charts. Logistic regression analysis was used to explore associations between demographic and clinical variables and two outcomes: the type of recommendation and referring physicians' decisions to follow the recommendation.

RESULTS

Of 972 GCS referrals, 248 patients were not referred to the CAUSES Study. GWS (vs. a targeted test; e.g. multi-gene panel) was more likely to be recommended to physicians of patients with ID than physicians of patients without ID (OR = 2.98; 95% CI = 1.46 to 6.27; n = 149). In total, 40% of physicians who were recommended to pursue clinical genomic testing submitted an application for funding approval; 71% of applications were approved for funding. Among approved tests, 50% resulted in a diagnosis, including 33% of targeted tests and 82% of GWS tests (χ² (1) = 5.0, p = 0.026).

CONCLUSION

The GCS provided an effective model in which physicians can interface with genetic specialists, including genetic counsellors, to facilitate appropriate genomic test selection.

Informed Consent in the Genomics Era

Informed consent, the process of gathering autonomous authorization for a medical intervention or medical research participation, is a fundamental component of medical practice. Medical informed consent assumes decision-making capacity, voluntariness, comprehension, and adequate information. The increasing use of genetic testing, particularly genomic sequencing, in clinical and research settings has presented many new challenges for clinicians and researchers when obtaining informed consent. Many of these challenges revolve around the need for patient comprehension of sufficient information. Genomic sequencing is complex-all of the possible results are too numerous to explain, and many of the risks and benefits remain unknown. Thus, historical standards of consent are difficult to apply. Alternative models of consent have been proposed to increase patient understanding, and several have empirically demonstrated effectiveness. However, there is still a striking lack of consensus in the genetics community about what constitutes informed consent in the context of genomic sequencing. Multiple approaches are needed to address this challenge, including consensus building around standards, targeted use of genetic counselors in nongenetics clinics in which genomic testing is ordered, and the development and testing of alternative models for obtaining informed consent.

Transcriptome sequencing identifies a noncoding, deep intronic variant in CLCN7 causing autosomal recessive osteopetrosis

Background

Over half of children with rare genetic diseases remain undiagnosed despite maximal clinical evaluation and DNA‐based genetic testing. As part of an Undiagnosed Diseases Program applying transcriptome (RNA) sequencing to identify the causes of these unsolved cases, we studied a child with severe infantile osteopetrosis leading to cranial nerve palsies, bone deformities, and bone marrow failure, for whom whole‐genome sequencing was nondiagnostic.

Methods

We performed transcriptome (RNA) sequencing of whole blood followed by analysis of aberrant transcript isoforms and osteoclast functional studies.

Results

We identified a pathogenic deep intronic variant in CLCN7 creating an unexpected, frameshifting pseudoexon causing complete loss of function. Functional studies, including osteoclastogenesis and bone resorption assays, confirmed normal osteoclast differentiation but loss of osteoclast function.

Conclusion

This is the first report of a pathogenic deep intronic variant in CLCN7, and our approach provides a model for systematic identification of noncoding variants causing osteopetrosis—a disease for which molecular‐genetic diagnosis can be pivotal for potentially curative hematopoietic stem cell transplantation. Our work illustrates that cryptic splice variants may elude DNA‐only sequencing and supports broad first‐line use of transcriptome sequencing for children with undiagnosed diseases.

metPropagate: network-guided propagation of metabolomic information for prioritization of metabolic disease genes

Many inborn errors of metabolism (IEMs) are amenable to treatment, therefore early diagnosis is imperative. Whole-exome sequencing (WES) variant prioritization coupled with phenotype-guided clinical and bioinformatics expertise is typically used to identify disease-causing variants; however, it can be challenging to identify the causal candidate gene when a large number of rare and potentially pathogenic variants are detected. Here, we present a network-based approach, metPropagate, that uses untargeted metabolomics (UM) data from a single patient and a group of controls to prioritize candidate genes in patients with suspected IEMs. We validate metPropagate on 107 patients with IEMs diagnosed in Miller et al. (2015) and 11 patients with both CNS and metabolic abnormalities. The metPropagate method ranks candidate genes by label propagation, a graph-smoothing algorithm that considers each gene’s metabolic perturbation in addition to the network of interactions between neighbors. metPropagate was able to prioritize at least one causative gene in the top 20^th percentile of candidate genes for 92% of patients with known IEMs. Applied to patients with suspected neurometabolic disease, metPropagate placed at least one causative gene in the top 20^th percentile in 9/11 patients, and ranked the causative gene more highly than Exomiser’s phenotype-based ranking in 6/11 patients. Interestingly, ranking by a weighted combination of metPropagate and Exomiser scores resulted in improved prioritization. The results of this study indicate that network-based analysis of UM data can provide an additional mode of evidence to prioritize causal genes in patients with suspected IEMs.

Shortened consent forms for genome-wide sequencing: Parent and provider perspectives

BACKGROUND

Consent forms for exome and/or genome sequencing, collectively called genome-wide sequencing (GWS), frequently contain detailed information on complex topics such as sequencing analysis and incidental findings. Considering recent endeavors by the health care community to simplify GWS consent forms, it is important to gain stakeholders' perspectives on the content, length, and use of consent forms.

METHODS

Thematic analysis was conducted on data obtained from focus groups with two participant cohorts: parents who previously provided consent for trio-based GWS as part of the translational pediatric GWS CAUSES Study, and genetic health care providers (HCP) who provide pre-test counseling for GWS.

RESULTS

Genetic HCP indicated that consent forms cannot replace pre-test counseling, and as such, a simplified consent form focusing on the implications of GWS would be beneficial to both patients and HCP. Although parents' primary concerns varied when considering GWS, they all highly valued information. Parents also indicated the need for community and support after the return of GWS results. Both participant cohorts recommended that consent forms be available online and include an appendix for supplementary information.

CONCLUSION

It is important to include both parents and HCP in the design of GWS consent forms, and also, to help connect families who have a shared diagnosis after the post-test counseling session.

Exome sequencing compared with standard genetic tests for critically ill infants with suspected genetic conditions

PURPOSE

As exome sequencing (ES) is increasingly used as a diagnostic tool, we aimed to compare ES with status quo genetic diagnostic workup for infants with suspected genetic disorders in terms of identifying diagnoses, survival, and cost of care.

METHODS

We studied newborns and infants admitted to intensive care with a suspected genetic etiology within the first year of life at a US quaternary-referral children's hospital over 5 years. In this propensity-matched cohort study using electronic medical record data, we compared patients who received ES as part of a diagnostic workup (ES cohort, n = 368) with clinically similar patients who did not receive ES (No-ES cohort, n = 368).

RESULTS

Diagnostic yield (27.4% ES, 25.8% No-ES; p = 0.62) and 1-year survival (80.2% ES, 84.8% No-ES; p = 0.10) were no different between cohorts. ES cohort patients had higher cost of admission, diagnostic investigation, and genetic testing (all p < 0.01).

CONCLUSION

ES did not differ from status quo genetic testing collectively in terms of diagnostic yield or patient survival; however, it had high yield as a single test, led to complementary classes of diagnoses, and was associated with higher costs. Further work is needed to define the most efficient use of diagnostic ES for critically ill newborns and infants.

Genetic Counseling and Genome Sequencing in Pediatric Rare Disease

Both genome sequencing (GS) and exome sequencing (ES) have proven to be revolutionary in the diagnosis of pediatric rare disease. The diagnostic potential and increasing affordability make GS and ES more accessible as a routine clinical test in some centers. Herein, I review aspects of rare disease in pediatrics associated with the use of genomic technologies with an emphasis on the benefits and limitations of both ES and GS, complexities of variant classification, and the importance of genetic counseling. Indications for testing, the role of genetic counselors in genomic test selection, and the diagnostic potential of ES and GS in various pediatric multisystem disorders are discussed. The neonatal population represents an important cohort in pediatric rare disease. Rapid ES and GS in critically ill neonates can have an immediate impact on medical management and present unique genetic counseling challenges. This work includes reviews of recommendations for genetic counseling for families considering genome-wide sequencing, and issues of access to genetic counseling that affect clinical use and will necessitate implementation of innovative methods such as online decision aids. Finally, this work will also review the challenges of having a child with a rare disease, the impact of results from ES and GS on these families, and the role of various support agencies.

The Financial Impact of Genetic Diseases in a Pediatric Accountable Care Organization

Background: Previous studies revealed patients with genetic disease have more frequent and longer hospitalizations and therefore higher healthcare costs. To understand the financial impact of genetic disease on a pediatric accountable care organization (ACO), we analyzed medical claims from 2014 provided by Partners for Kids, an ACO in partnership with Nationwide Children's Hospital (NCH; Columbus, OH, USA). Methods: Study population included insurance claims from 258,399 children. We assigned patients to four different categories (1-A, 1-B, 2, & 3) based on the strength of genetic basis of disease. Results: We identified 22.7% of patients as category 1A or 1B- having a disease with a "strong genetic basis" (e.g., single gene diseases, chromosomal abnormalities). Total ACO paid claims in 2014 were $379M, of which $161M (42.5%) was attributed to category 1 patients. Furthermore, we identified 23.3% of patients as category 2- having a disease with a suspected genetic component or predisposition (e.g., asthma, type 1 diabetes)- whom accounted for an additional 28.6% of 2014 costs. Category 1 patients were more likely to experience at least one hospitalization compared to category 3 patients- those without genetic disease [odds ratio [OR] = 4.12; 95% confidence interval [CI] = 3.86-4.39; p < 0.0001]. Overall, category 1 patients experienced nearly five times the number of inpatient (IP) admissions and twice the number of outpatient (OP) visits compared to category 3 patients (p < 0.0001). Conclusion: Nearly half (42.5%) of healthcare paid claims cost in 2014 for this study population were accounted for by patients with single-gene diseases or chromosomal abnormalities. These findings precede and support a need for an ACO to plan for effective healthcare strategies and capitation models for children with genetic disease.

A Review of Health Economic Studies Comparing Traditional and Massively Parallel Sequencing Diagnostic Pathways for Suspected Genetic Disorders

Genetic disorders are clinically diverse and genetically heterogeneous, and are traditionally diagnosed based on an iterative phenotype-guided genetic assessment. However, such diagnostic approaches are long (diagnostic odysseys are common), misdiagnoses occur frequently, and diagnostic rates are low. Massively parallel sequencing (MPS) technologies may improve diagnostic rates and reduce the time to diagnosis for patients with suspected genetic disorders; however, MPS technologies are expensive and the health economic evidence base to support their use is limited. Several studies have compared the costs of traditional and MPS diagnostic pathways for patients with suspected genetic disorders, however costing methods and diagnostic scenarios are heterogeneous across studies. We conducted a literature review to identify and summarise information on these costing methods and diagnostic scenarios. Relevant studies were identified in MEDLINE, EMBASE, EconLit, University of York Centre for Reviews and Dissemination and the Cochrane Library, from 2010 to 2018. Twenty-four articles were included in the review. We observed considerable heterogeneity across studies with respect to the selection of items of resource use used to derive total diagnostic pathway cost estimates. We also observed structural differences in the diagnostic scenarios used to compare the traditional and MPS diagnostic pathways. There is a need for guidelines on the costing of diagnostic pathways to encourage the use of consistent methods. More micro-costing studies that evaluate diagnostic service delivery are also required. Greater homogeneity in costing approaches would facilitate more reliable comparisons between studies and improve the transferability of cost estimates across countries.

A pediatric perspective on genomics and prevention in the twenty-first century

We present evidence from diverse disciplines and populations to identify the current and emerging role of genomics in prevention from both medical and public health perspectives as well as key challenges and potential untoward consequences of increasing the role of genomics in these endeavors. We begin by comparing screening in healthy populations (newborn screening), with testing in symptomatic populations, which may incidentally identify secondary findings and at-risk relatives. Emerging evidence suggests that variants in genes subject to the reporting of secondary findings are more common than expected in patients who otherwise would not meet the criteria for testing and population testing for variants in these genes may more precisely identify discrete populations to target for various prevention strategies starting in childhood. Conversely, despite its theoretical promise, recent studies attempting to demonstrate benefits of next-generation sequencing for newborn screening have instead demonstrated numerous barriers and pitfalls to this approach. We also examine the special cases of pharmacogenomics and polygenic risk scores as examples of ways genomics can contribute to prevention amongst a broader population than that affected by rare Mendelian disease. We conclude with unresolved questions which will benefit from future investigations of the role of genomics in disease prevention.

Genome analysis and knowledge-driven variant interpretation with TGex

BACKGROUND

The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient's phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants.

RESULTS

We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex's main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex's broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards' recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. Examining use-cases from a variety of TGex users world-wide, we demonstrate its high diagnostic yields (42% for single exome and 50% for trios in 1500 rare genetic disease cases) and critical actionable genetic findings. The platform's support for integration with EHR and LIMS through dedicated APIs facilitates automated retrieval of patient data for TGex's customizable reporting engine, establishing a rapid and cost-effective workflow for an entire range of clinical genetic testing, including rare disorders, cancer predisposition, tumor biopsies and health screening.

CONCLUSIONS

TGex is an innovative tool for the annotation, analysis and prioritization of coding and non-coding genomic variants. It provides access to an extensive knowledgebase of genomic annotations, with intuitive and flexible configuration options, allows quick adaptation, and addresses various workflow requirements. It thus simplifies and accelerates variant interpretation in clinical genetics workflows, with remarkable diagnostic yield, as exemplified in the described use cases. TGex is available at http://tgex.genecards.org/.