Increased diagnostic yield by reanalysis of data from a hearing loss gene panel

Systematic reanalysis of copy number losses of uncertain clinical significance

BACKGROUND

Reanalysis of exome/genome data improves diagnostic yield. However, the value of reanalysis of clinical array comparative genomic hybridisation (aCGH) data has never been investigated. Case-by-case reanalysis can be challenging in busy diagnostic laboratories.

METHODS AND RESULTS

We harmonised historical postnatal clinical aCGH results from ~16 000 patients tested via our diagnostic laboratory over ~7 years with current clinical guidance. This led to identification of 37 009 copy number losses (CNLs) including 33 857 benign, 2173 of uncertain significance and 979 pathogenic. We found benign CNLs to be significantly less likely to encompass haploinsufficient genes compared with the pathogenic or CNLs of uncertain significance in our database. Based on this observation, we developed a reanalysis pipeline using up-to-date disease association data and haploinsufficiency scores and shortlisted 207 CNLs of uncertain significance encompassing at least one autosomal dominant disease-gene associated with haploinsufficiency or loss-of-function mechanism. Clinical scientist reviews led to reclassification of 15 CNLs of uncertain significance as pathogenic or likely pathogenic. This was ~0.7% of the starting cohort of 2173 CNLs of uncertain significance and 7.2% of 207 shortlisted CNLs. The reclassified CNLs included first cases of CNV-mediated disease for some genes where all previously described cases involved only point variants. Interestingly, some CNLs could not be reclassified because the phenotypes of patients with CNLs seemed distinct from the known clinical features resulting from point variants, thus raising questions about accepted underlying disease mechanisms.

CONCLUSIONS

Reanalysis of clinical aCGH data increases diagnostic yield.

Updates on Genetic Hearing Loss: From Diagnosis to Targeted Therapies

Sensorineural hearing loss (SNHL) is the most common sensory disorder, with a high Mendelian genetic contribution. Considering the genotypic and phenotypic heterogeneity of SNHL, the advent of next-generation sequencing technologies has revolutionized knowledge on its genomic architecture. Nonetheless, the conventional application of panel and exome sequencing in real-world practice is being challenged by the emerging need to explore the diagnostic capability of whole-genome sequencing, which enables the detection of both noncoding and structural variations. Small molecules and gene therapies represent good examples of how breakthroughs in genetic understanding can be translated into targeted therapies for SNHL. For example, targeted small molecules have been used to ameliorate autoinflammatory hearing loss caused by gain-of-function variants of NLRP3 and inner ear proteinopathy with OSBPL2 variants underlying dysfunctional autophagy. Strikingly, the successful outcomes of the first-in-human trial of OTOF gene therapy highlighted its potential in the treatment of various forms of genetic hearing loss. clustered regularly interspaced short palindromic repeats (CRISPR)-based technologies are currently being developed for site-specific genome editing to treat human genetic disorders. These advancements have led to an era of genotype- and mechanism-based precision medicine in SNHL practice.

Slice Testing-Considerations from Ordering to Reporting: A Joint Report of the Association for Molecular Pathology, College of American Pathologists, and National Society of Genetic Counselors

As the number of genes associated with various germline disorders continues to grow, it is becoming more difficult for clinical laboratories to maintain separate assays for interrogating disease-focused gene panels. One solution to this challenge is termed slice testing, where capture backbone is used to analyze data specific to a set of genes, and for this article, we will focus on exome. A key advantage to this strategy is greater flexibility by adding genes as they become associated with disease or the ability to accommodate specific provider requests. Here, we provide expert consensus recommendations and results from an Association for Molecular Pathology-sponsored survey of clinical laboratories performing exome sequencing to compare a slice testing approach with traditional static gene panels and comprehensive exome analysis. We explore specific considerations for slices, including gene selection, analytic performance, coverage, quality, and interpretation. Our goal is to provide comprehensive guidance for clinical laboratories interested in designing and using slice tests as a diagnostic.

[Genetics of pediatric hearing loss]

With the rapid development of sequencing technology and bioinformatics, the genetic research and related clinical practice of pediatric hearing loss have also made significant progress. This review summarized and analyzed the genetic causes of hearing impairment in children and the research progress of related genetic diagnosis and screening, in order to provide reference for the prevention and treatment of pediatric hearing loss and related research.

Idiopathic pulmonary fibrosis and the role of genetics in the era of precision medicine

Idiopathic pulmonary fibrosis (IPF) is a chronic, rare progressive lung disease, characterized by lung scarring and the irreversible loss of lung function. Two anti-fibrotic drugs, nintedanib and pirfenidone, have been demonstrated to slow down disease progression, although IPF mortality remains a challenge and the patients die after a few years from diagnosis. Rare pathogenic variants in genes that are involved in the surfactant metabolism and telomere maintenance, among others, have a high penetrance and tend to co-segregate with the disease in families. Common recurrent variants in the population with modest effect sizes have been also associated with the disease risk and progression. Genome-wide association studies (GWAS) support at least 23 genetic risk loci, linking the disease pathogenesis with unexpected molecular pathways including cellular adhesion and signaling, wound healing, barrier function, airway clearance, and innate immunity and host defense, besides the surfactant metabolism and telomere biology. As the cost of high-throughput genomic technologies continuously decreases and new technologies and approaches arise, their widespread use by clinicians and researchers is efficiently contributing to a better understanding of the pathogenesis of progressive pulmonary fibrosis. Here we provide an overview of the genetic factors known to be involved in IPF pathogenesis and discuss how they will continue to further advance in this field. We also discuss how genomic technologies could help to further improve IPF diagnosis and prognosis as well as for assessing genetic risk in unaffected relatives. The development and validation of evidence-based guidelines for genetic-based screening of IPF will allow redefining and classifying this disease relying on molecular characteristics and contribute to the implementation of precision medicine approaches.

Outcomes of Gene Panel Testing for Sensorineural Hearing Loss in a Diverse Patient Cohort

IMPORTANCE

A genetic diagnosis can help elucidate the prognosis of hearing loss, thus significantly affecting management. Previous studies on diagnostic yield of hearing loss genetic tests have been based on largely homogenous study populations.

OBJECTIVES

To examine the diagnostic yield of genetic testing in a diverse population of children, accounting for sociodemographic and patient characteristics, and assess whether these diagnoses are associated with subsequent changes in clinical management.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study included 2075 patients seen at the Children's Communications Clinic, of whom 517 completed hearing loss gene panel testing between January 1, 2015, and November 1, 2021, at the University of California, San Francisco Benioff Children's Hospital system. From those 517 patients, 426 children with at least 2 audiograms were identified and analyzed. Data were gathered from November 2021 to January 2022 and analyzed from January to February 2022.

MAIN OUTCOMES AND MEASURES

The measures of interest were sociodemographic characteristics (age at testing, gender, race and ethnicity, primary language, and insurance type), hearing loss characteristics, and medical variables. The outcome was genetic testing results. Variables were compared with univariate and multivariable logistic regression.

RESULTS

Of the 2075 patients seen at the Children's Communications Clinic, 517 (median [range] age, 8 [0-31] years; 264 [51.1%] male; 351 [67.9%] from an underrepresented minority [URM] group) underwent a hearing loss panel genetic test between January 1, 2015, and November 1, 2021. Among those 517 patients, 426 children (median [range] age, 8 [0-18] years; 221 [51.9%] male; 304 [71.4%] from an URM group) with 2 or more audiograms were included in a subsequent analysis. On multivariable logistic regression, age at testing (odds ratio [OR], 0.87; 95% CI, 0.78-0.97), URM group status (OR, 0.29; 95% CI, 0.13-0.66), comorbidities (OR, 0.27; 95% CI, 0.14-0.53), late-identified hearing loss (passed newborn hearing screen; OR, 0.27; 95% CI, 0.08-0.86), and unilateral hearing loss (OR, 0.04; 95% CI, 0.005-0.33) were the only factors associated with genetic diagnosis. No association was found between genetic diagnosis yield and other sociodemographic variables or hearing loss characteristics. Patients in URM and non-URM groups had statistically similar clinical features. A total of 32 of 109 children (29.4%) who received a genetic diagnosis received diagnoses that significantly affected prognosis because of identification of syndromic or progressive sensorineural hearing loss or auditory neuropathy spectrum disorder relating to otoferlin.

CONCLUSIONS AND RELEVANCE

This cohort study's findings suggest that genetic testing may be broadly useful in improving clinical management of children with hearing loss. More research is warranted to discover and characterize diagnostic genes for those who have been historically underrepresented in research and medicine.

Full etiologic spectrum of pediatric severe to profound hearing loss of consecutive 119 cases

Determining the etiology of severe-to-profound sensorineural hearing loss (SP-SNHL) in pediatric subjects is particularly important in aiding the decision for auditory rehabilitation. We aimed to update the etiologic spectrum of pediatric SP-SNHL by combining internal auditory canal (IAC)-MRI with comprehensive and state-of-the-art genetic testings. From May 2013 to September 2020, 119 cochlear implantees under the age of 15 years with SP-SNHL were all prospectively recruited. They were subjected to genetic tests, including exome sequencing, and IAC-MRI for etiologic diagnosis. Strict interpretation of results were made based on ACMG/AMP guidelines and by an experienced neuroradiologist. The etiology was determined in of 65.5% (78/119) of our cohort. If only one of the two tests was done, the etiologic diagnostic rate would be reduced by at least 21.8%. Notably, cochlear nerve deficiency (n = 20) detected by IAC-MRI topped the etiology list of our cohort, followed by DFNB4 (n = 18), DFNB1 (n = 10), DFNB9 (n = 10) and periventricular leukomalacia associated with congenital CMV infection (n = 8). Simultaneous application of state-of-the-art genetic tests and IAC-MRI is essential for etiologic diagnosis, and if lesions of the auditory nerve or central nerve system are carefully examined on an MRI, we can identify the cause of deafness in more than 65% of pediatric SP-SNHL cases.

Exome sequencing of families from Ghana reveals known and candidate hearing impairment genes

We investigated hearing impairment (HI) in 51 families from Ghana with at least two affected members that were negative for GJB2 pathogenic variants. DNA samples from 184 family members underwent whole-exome sequencing (WES). Variants were found in 14 known non-syndromic HI (NSHI) genes [26/51 (51.0%) families], five genes that can underlie either syndromic HI or NSHI [13/51 (25.5%)], and one syndromic HI gene [1/51 (2.0%)]. Variants in CDH23 and MYO15A contributed the most to HI [31.4% (16/51 families)]. For DSPP, an autosomal recessive mode of inheritance was detected. Post-lingual expression was observed for a family segregating a MARVELD2 variant. To our knowledge, seven novel candidate HI genes were identified (13.7%), with six associated with NSHI (INPP4B, CCDC141, MYO19, DNAH11, POTEI, and SOX9); and one (PAX8) with Waardenburg syndrome. MYO19 and DNAH11 were replicated in unrelated Ghanaian probands. Six of the novel genes were expressed in mouse inner ear. It is known that Pax8-/- mice do not respond to sound, and depletion of Sox9 resulted in defective vestibular structures and abnormal utricle development. Most variants (48/60; 80.0%) have not previously been associated with HI. Identifying seven candidate genes in this study emphasizes the potential of novel HI genes discovery in Africa.

Re-analysis of genomic data: An overview of the mechanisms and complexities of clinical adoption

Re-analyzing genomic information from a patient suspected of having an underlying genetic condition can improve the diagnostic yield of sequencing tests, potentially providing significant benefits to the patient and to the health care system. Although a significant number of studies have shown the clinical potential of re-analysis, less work has been performed to characterize the mechanisms responsible for driving the increases in diagnostic yield. Complexities surrounding re-analysis have also emerged. The terminology itself represents a challenge because "re-analysis" can refer to a range of different concepts. Other challenges include the increased workload that re-analysis demands of curators, adequate reimbursement pathways for clinical and diagnostic services, and the development of systems to handle large volumes of data. Re-analysis also raises ethical implications for patients and families, most notably when re-classification of a variant alters diagnosis, treatment, and prognosis. This review highlights the possibilities and complexities associated with the re-analysis of existing clinical genomic data. We propose a terminology that builds on the foundation presented in a recent statement from the American College of Medical Genetics and Genomics and describes each re-analysis process. We identify mechanisms for increasing diagnostic yield and provide perspectives on the range of challenges that must be addressed by health care systems and individual patients.

Multidimensional Family-Centred Early Intervention in Children with Hearing Loss: A Conceptual Model

At least two per thousand newborns are affected by hearing loss, with up to 40% with an additional disability. Early identification by universal newborn hearing screening and early intervention services are available in many countries around the world, with limited data on their effectiveness and a lack of knowledge about specific intervention-related determinants of child and family outcomes. This concept paper aimed to better understand the mechanisms by which multi-dimensional family-centred early intervention influences child outcomes, through parent behaviour, targeted by intervention by a review of the literature, primarily in the field of childhood hearing loss, supplemented by research findings on physiological and atypical child development. We present a conceptual model of influences of multi-disciplinary family-centred early intervention on family coping/functioning and parent–child interaction, with effects on child psycho-social and cognitive outcomes. Social communication and language skills are postulated as mediators between parent–child interaction and non-verbal child outcomes. Multi-disciplinary networks of professionals trained in family-centred practice and the evaluation of existing services, with respect to best practice guidelines for family-centred early intervention, are recommended. There is a need for longitudinal epidemiological studies, including specific intervention measures, family behaviours and multidimensional child outcomes.

Hearing Screening Combined with Target Gene Panel Testing Increased Etiological Diagnostic Yield in Deaf Children

Genetic testing is the gold standard for exploring the etiology of congenital hearing loss. Here, we enrolled 137 Chinese patients with congenital hearing loss to describe the molecular epidemiology by using 127 gene panel testing or 159 variant testing. Sixty-three deaf children received 127 gene panel testing, while seventy-four patients received 159 variant testing. By use of 127 gene panel testing, more mutant genes and variants were identified. The most frequent mutant genes were GJB2, SLC26A4, MYO15A, CDH23, and OTOF. By analyzing the patients who received 127 gene panel testing, we found that 51 deaf children carried variants which were not included in 159 variant testing. Therefore, a large number of patients would be misdiagnosed if only 159 variant testing is used. This study highlights the advantage of 127 gene panel testing, and it suggests that broader genetic testing should be done to identify the genetic etiology of congenital hearing loss.

Genetic health professionals' experiences with initiating reanalysis of genomic sequence data

Despite the increased diagnostic yield associated with genomic sequencing (GS), a sizable proportion of patients do not receive a genetic diagnosis at the time of the initial GS analysis. Systematic data reanalysis leads to considerable increases in genetic diagnosis rates yet is time intensive and leads to questions of feasibility. Few policies address whether laboratories have a duty to reanalyse and it is unclear how this impacts clinical practice. To address this, we interviewed 31 genetic health professionals (GHPs) across Europe, Australia and Canada about their experiences with data reanalysis and variant reinterpretation practices after requesting GS for their patients. GHPs described a range of processes required to initiate reanalysis of GS data for their patients and often practices involved a combination of reanalysis initiation methods. The most common mechanism for reanalysis was a patient-initiated model, where they instruct patients to return to the genetic service for clinical reassessment after a period of time or if new information comes to light. Yet several GHPs expressed concerns about patients' inabilities to understand the need to return to trigger reanalysis, or advocate for themselves, which may exacerbate health inequities. Regardless of the reanalysis initiation model that a genetic service adopts, patients' and clinicians' roles and responsibilities need to be clearly outlined so patients do not miss the opportunity to receive ongoing information about their genetic diagnosis. This requires consensus on the delineation of these roles for clinicians and laboratories to ensure clear pathways for reanalysis and reinterpretation to be performed to improve patient care.

Children's rare disease cohorts: an integrative research and clinical genomics initiative

While genomic data is frequently collected under distinct research protocols and disparate clinical and research regimes, there is a benefit in streamlining sequencing strategies to create harmonized databases, particularly in the area of pediatric rare disease. Research hospitals seeking to implement unified genomics workflows for research and clinical practice face numerous challenges, as they need to address the unique requirements and goals of the distinct environments and many stakeholders, including clinicians, researchers and sequencing providers. Here, we present outcomes of the first phase of the Children’s Rare Disease Cohorts initiative (CRDC) that was completed at Boston Children’s Hospital (BCH). We have developed a broadly sharable database of 2441 exomes from 15 pediatric rare disease cohorts, with major contributions from early onset epilepsy and early onset inflammatory bowel disease. All sequencing data is integrated and combined with phenotypic and research data in a genomics learning system (GLS). Phenotypes were both manually annotated and pulled automatically from patient medical records. Deployment of a genomically-ordered relational database allowed us to provide a modular and robust platform for centralized storage and analysis of research and clinical data, currently totaling 8516 exomes and 112 genomes. The GLS integrates analytical systems, including machine learning algorithms for automated variant classification and prioritization, as well as phenotype extraction via natural language processing (NLP) of clinical notes. This GLS is extensible to additional analytic systems and growing research and clinical collections of genomic and other types of data.

AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants

Null variants are prevalent within the human genome, and their accurate interpretation is critical for clinical management. In 2018, the ClinGen Sequence Variant Interpretation (SVI) Working Group refined the only criterion with a very strong pathogenicity rating (PVS1). To streamline PVS1 interpretation, we have developed an automatic classification tool with a graphical user interface called AutoPVS1. The performance of AutoPVS1 was assessed using 56 variants manually curated by the ClinGen's SVI Working Group; it achieved an interpretation concordance of 93% (52/56). A further analysis of 28,586 putative loss-of-function variants by AutoPVS1 demonstrated that at least 27.7% of them do not reach a very strong strength level, 17.5% because of variant-specific issues and 10.2% due to disease mechanism considerations. Notably, 41.0% (1,936/4,717) of splicing variants were assigned a decreased preliminary PVS1 strength level, a significantly greater fraction than in frameshift variants (13.2%) and nonsense variants (10.8%). Our results reinforce the necessity of considering variant-specific issues and disease mechanisms in variant interpretation and demonstrate that AutoPVS1 meets an urgent need by enabling biocurators to easily assign accurate, reliable and reproducible PVS1 strength levels in the process of variant interpretation. AutoPVS1 is publicly available at http://autopvs1.genetics.bgi.com/.