Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes

Lethal phenotypes in Mendelian disorders

PURPOSE

Existing resources that characterize the essentiality status of genes are based on either proliferation assessment in human cell lines, viability evaluation in mouse knockouts, or constraint metrics derived from human population sequencing studies. Several repositories document phenotypic annotations for rare disorders; however, there is a lack of comprehensive reporting on lethal phenotypes.

METHODS

We queried Online Mendelian Inheritance in Man for terms related to lethality and classified all Mendelian genes according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. We characterized the genes across these lethality categories, examined the evidence on viability from mouse models and explored how this information could be used for novel gene discovery.

RESULTS

We developed the Lethal Phenotypes Portal to showcase this curated catalog of human essential genes. Differences in the mode of inheritance, physiological systems affected, and disease class were found for genes in different lethality categories, as well as discrepancies between the lethal phenotypes observed in mouse and human.

CONCLUSION

We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.

Towards a standard benchmark for variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework

Background

Computational approaches to support rare disease diagnosis are challenging to build, requiring the integration of complex data types such as ontologies, gene-to-phenotype associations, and cross-species data into variant and gene prioritisation algorithms (VGPAs). However, the performance of VGPAs has been difficult to measure and is impacted by many factors, for example, ontology structure, annotation completeness or changes to the underlying algorithm. Assertions of the capabilities of VGPAs are often not reproducible, in part because there is no standardised, empirical framework and openly available patient data to assess the efficacy of VGPAs - ultimately hindering the development of effective prioritisation tools.

Results

In this paper, we present our benchmarking tool, PhEval, which aims to provide a standardised and empirical framework to evaluate phenotype-driven VGPAs. The inclusion of standardised test corpora and test corpus generation tools in the PhEval suite of tools allows open benchmarking and comparison of methods on standardised data sets.

Conclusions

PhEval and the standardised test corpora solve the issues of patient data availability and experimental tooling configuration when benchmarking and comparing rare disease VGPAs. By providing standardised data on patient cohorts from real-world case-reports and controlling the configuration of evaluated VGPAs, PhEval enables transparent, portable, comparable and reproducible benchmarking of VGPAs. As these tools are often a key component of many rare disease diagnostic pipelines, a thorough and standardised method of assessment is essential for improving patient diagnosis and care.

Exome Sequencing has a high diagnostic rate in sporadic congenital hypopituitarism and reveals novel candidate genes

CONTEXT

The pituitary gland is key for childhood growth, puberty, and metabolism. Pituitary dysfunction is associated with a spectrum of phenotypes, from mild to severe. Congenital Hypopituitarism (CH) is the most commonly reported pediatric endocrine dysfunction with an incidence of 1:4000, yet low rates of genetic diagnosis have been reported.

OBJECTIVE

We aimed to unveil the genetic etiology of CH in a large cohort of patients from Argentina.

METHODS

We performed whole exome sequencing of 137 unrelated cases of CH, the largest cohort examined with this method to date.

RESULTS

Of the 137 cases, 19.1% and 16% carried pathogenic or likely pathogenic variants in known and new genes, respectively, while 28.2% carried variants of uncertain significance. This high yield was achieved through the integration of broad gene panels (genes described in animal models and/or other disorders), an unbiased candidate gene screen with a new bioinformatics pipeline (including genes high loss of function intolerance), and analysis of copy number variants. Three novel findings emerged. First, the most prevalent affected gene encodes the cell adhesion factor ROBO1. Affected children had a spectrum of phenotypes, consistent with a role beyond pituitary stalk interruption syndrome. Second, we found that CHD7 mutations also produce a phenotypic spectrum, not always associated with full CHARGE syndrome. Third, we add new evidence of pathogenicity in the genes PIBF1 and TBC1D32, and report 13 novel candidate genes associated with CH (e.g. PTPN6, ARID5B).

CONCLUSION

Overall, these results provide an unprecedented insight into the diverse genetic etiology of hypopituitarism.

The landscape of regional missense mutational intolerance quantified from 125,748 exomes

Missense variants can have a range of functional impacts depending on factors such as the specific amino acid substitution and location within the gene. To interpret their deleteriousness, studies have sought to identify regions within genes that are specifically intolerant of missense variation 1-12 . Here, we leverage the patterns of rare missense variation in 125,748 individuals in the Genome Aggregation Database (gnomAD) 13 against a null mutational model to identify transcripts that display regional differences in missense constraint. Missense-depleted regions are enriched for ClinVar 14 pathogenic variants, de novo missense variants from individuals with neurodevelopmental disorders (NDDs) 15,16 , and complex trait heritability. Following ClinGen calibration recommendations for the ACMG/AMP guidelines, we establish that regions with less than 20% of their expected missense variation achieve moderate support for pathogenicity. We create a missense deleteriousness metric (MPC) that incorporates regional constraint and outperforms other deleteriousness scores at stratifying case and control de novo missense variation, with a strong enrichment in NDDs. These results provide additional tools to aid in missense variant interpretation.

Whole genome sequencing in clinical practice

Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identification of actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. Whereas, the laboratory requirements are similar to conventional molecular genetics, the amount of data is large and WGS requires a comprehensive computational and storage infrastructure in order to facilitate data processing within a clinically relevant timeframe. The output of a single WGS analyses is roughly 5 MIO variants and data interpretation involves specialized staff collaborating with the clinical specialists in order to provide standard of care reports. Although the field is continuously refining the standards for variant classification, there are still unresolved issues associated with the clinical application. The review provides an overview of WGS in clinical practice - describing the technology and current applications as well as challenges connected with data processing, interpretation and clinical reporting.

Lethal phenotypes in Mendelian disorders

Essential genes are those whose function is required for cell proliferation and/or organism survival. A gene's intolerance to loss-of-function can be allocated within a spectrum, as opposed to being considered a binary feature, since this function might be essential at different stages of development, genetic backgrounds or other contexts. Existing resources that collect and characterise the essentiality status of genes are based on either proliferation assessment in human cell lines, embryonic and postnatal viability evaluation in different model organisms, and gene metrics such as intolerance to variation scores derived from human population sequencing studies. There are also several repositories available that document phenotypic annotations for rare disorders in humans such as the Online Mendelian Inheritance in Man (OMIM) and the Human Phenotype Ontology (HPO) knowledgebases. This raises the prospect of being able to use clinical data, including lethality as the most severe phenotypic manifestation, to further our characterisation of gene essentiality. Here we queried OMIM for terms related to lethality and classified all Mendelian genes into categories, according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. To showcase this curated catalogue of human essential genes, we developed the Lethal Phenotypes Portal (https://lethalphenotypes.research.its.qmul.ac.uk), where we also explore the relationships between these lethality categories, constraint metrics and viability in cell lines and mouse. Further analysis of the genes in these categories reveals differences in the mode of inheritance of the associated disorders, physiological systems affected and disease class. We highlight how the phenotypic similarity between genes in the same lethality category combined with gene family/group information can be used for novel disease gene discovery. Finally, we explore the overlaps and discrepancies between the lethal phenotypes observed in mouse and human and discuss potential explanations that include differences in transcriptional regulation, functional compensation and molecular disease mechanisms. We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.

Reclassifying variations of unknown significance in diseases affecting Saudi Arabia's population reveal new associations

Introduction: Physicians face diagnostic dilemmas upon reports indicating disease variants of unknown significance (VUS). The most puzzling cases are patients with rare diseases, where finding another matched genotype and phenotype to associate their results is challenging. This study aims to prove the value of updating patient files with new classifications, potentially leading to better assessment and prevention. Methodology: We recruited retrospective phenotypic and genotypic data from King Saud Medical City, Riyadh, Kingdom of Saudi Arabia. Between September 2020 and December 2021, 1,080 patients' genetic profiles were tested in a College of American Pathologists accredited laboratory. We excluded all confirmed pathogenic variants, likely pathogenic variants and copy number variations. Finally, we further reclassified 194 VUS using different local and global databases, employing in silico prediction to justify the phenotype-genotype association. Results: Of the 194 VUS, 90 remained VUS, and the other 104 were reclassified as follows: 16 pathogenic, 49 likely pathogenic, nine benign, and 30 likely benign. Moreover, most of these variants had never been observed in other local or international databases. Conclusion: Reclassifying the VUS adds value to understanding the causality of the phenotype if it has been reported in another family or population. The healthcare system should establish guidelines for re-evaluating VUS, and upgrading VUS should reflect on individual/family risks and management strategies.

Genomic newborn screening for rare diseases

Rare diseases are a leading cause of infant mortality and lifelong disability. To improve outcomes, timely diagnosis and effective treatments are needed. Genomic sequencing has transformed the traditional diagnostic process, providing rapid, accurate and cost-effective genetic diagnoses to many. Incorporating genomic sequencing into newborn screening programmes at the population scale holds the promise of substantially expanding the early detection of treatable rare diseases, with stored genomic data potentially benefitting health over a lifetime and supporting further research. As several large-scale newborn genomic screening projects launch internationally, we review the challenges and opportunities presented, particularly the need to generate evidence of benefit and to address the ethical, legal and psychosocial issues that genomic newborn screening raises.

Prospect of genetic disorders in Saudi Arabia

Introduction: Rare diseases (RDs) create a massive burden for governments and families because sufferers of these diseases are required to undergo long-term treatment or rehabilitation to maintain a normal life. In Saudi Arabia (SA), the prevalence of RDs is high as a result of cultural and socio-economic factors. This study, however, aims to shed light on the genetic component of the prevalence of RDs in SA. Methodology: A retrospective study was conducted between September 2020 and December 2021 at King Saud Medical City, a tertiary hospital of the Ministry of Health (MOH), SA. A total of 1080 individuals with 544 potentially relevant variants were included. The index was 738, and the samples were tested in a commercialized laboratory using different molecular techniques, including next-generation sequencing. Result: A total of 867 molecular genetics tests were conducted on 738 probands. These tests included 610 exome sequencing (ES) tests, four genome sequencing (GS) tests, 82 molecular panels, 106 single nucleotide polymorphism (SNP) array, four methylation studies, 58 single-gene studies and three mitochondrial genome sequencing tests. The diagnostic yield among molecular genetics studies was 41.8% in ES, 24% in panels, 12% in SNP array and 24% in single gene studies. The majority of the identified potential variants (68%) were single nucleotide variants (SNV). Other ascertained variants included frameshift (11%), deletion (10%), duplication (5%), splicing (9%), in-frame deletion (3%) and indels (1%). The rate of positive consanguinity was 56%, and the autosomal recessive accounted for 54%. We found a significant correlation between the ES detection rate and positive consanguinity. We illustrated the presence of rare treatable conditions in DNAJC12, SLC19A3, and ALDH7A1, and the presence of the founder effect variant in SKIC2. Neurodevelopmental disorders were the main phenotype for which genetics studies were required (35.7%). Conclusion: This is the sixth-largest local study reporting next-generation sequencing. The results indicate the influence of consanguineous marriages on genetic disease and the burden it causes for the Kingdom of SA. This study highlights the need to enrich our society's knowledge of genetic disorders. We recommend utilising ES as a first-tier test to establish genetic diagnosis in a highly consanguineous population.

Integrated multi-omics for rapid rare disease diagnosis on a national scale

Critically ill infants and children with rare diseases need equitable access to rapid and accurate diagnosis to direct clinical management. Over 2 years, the Acute Care Genomics program provided whole-genome sequencing to 290 families whose critically ill infants and children were admitted to hospitals throughout Australia with suspected genetic conditions. The average time to result was 2.9 d and diagnostic yield was 47%. We performed additional bioinformatic analyses and transcriptome sequencing in all patients who remained undiagnosed. Long-read sequencing and functional assays, ranging from clinically accredited enzyme analysis to bespoke quantitative proteomics, were deployed in selected cases. This resulted in an additional 19 diagnoses and an overall diagnostic yield of 54%. Diagnostic variants ranged from structural chromosomal abnormalities through to an intronic retrotransposon, disrupting splicing. Critical care management changed in 120 diagnosed patients (77%). This included major impacts, such as informing precision treatments, surgical and transplant decisions and palliation, in 94 patients (60%). Our results provide preliminary evidence of the clinical utility of integrating multi-omic approaches into mainstream diagnostic practice to fully realize the potential of rare disease genomic testing in a timely manner.

Knockout mouse models as a resource for the study of rare diseases

Rare diseases (RDs) are a challenge for medicine due to their heterogeneous clinical manifestations and low prevalence. There is a lack of specific treatments and only a few hundred of the approximately 7,000 RDs have an approved regime. Rapid technological development in genome sequencing enables the mass identification of potential candidates that in their mutated form could trigger diseases but are often not confirmed to be causal. Knockout (KO) mouse models are essential to understand the causality of genes by allowing highly standardized research into the pathogenesis of diseases. The German Mouse Clinic (GMC) is one of the pioneers in mouse research and successfully uses (preclinical) data obtained from single-gene KO mutants for research into monogenic RDs. As part of the International Mouse Phenotyping Consortium (IMPC) and INFRAFRONTIER, the pan-European consortium for modeling human diseases, the GMC expands these preclinical data toward global collaborative approaches with researchers, clinicians, and patient groups.Here, we highlight proprietary genes that when deleted mimic clinical phenotypes associated with known RD targets (Nacc1, Bach2, Klotho alpha). We focus on recognized RD genes with no pre-existing KO mouse models (Kansl1l, Acsf3, Pcdhgb2, Rabgap1, Cox7a2) which highlight novel phenotypes capable of optimizing clinical diagnosis. In addition, we present genes with intriguing phenotypic data (Zdhhc5, Wsb2) that are not presently associated with known human RDs.This report provides comprehensive evidence for genes that when deleted cause differences in the KO mouse across multiple organs, providing a huge translational potential for further understanding monogenic RDs and their clinical spectrum. Genetic KO studies in mice are valuable to further explore the underlying physiological mechanisms and their overall therapeutic potential.

A retrospective analysis of phosphatase catalytic subunit gene variants in patients with rare disorders identifies novel candidate neurodevelopmental disease genes

Rare genetic disorders represent some of the most severe and life-limiting conditions that constitute a considerable burden on global healthcare systems and societies. Most individuals affected by rare disorders remain undiagnosed, highlighting the unmet need for improved disease gene discovery and novel variant interpretation. Aberrant (de) phosphorylation can have profound pathological consequences underpinning many disease processes. Numerous phosphatases and associated proteins have been identified as disease genes, with many more likely to have gone undiscovered thus far. To begin to address these issues, we have performed a systematic survey of de novo variants amongst 189 genes encoding phosphatase catalytic subunits found in rare disease patients recruited to the 100,000 Genomes Project (100 kGP), the largest national sequencing project of its kind in the United Kingdom. We found that 49% of phosphatases were found to carry de novo mutation(s) in this cohort. Only 25% of these phosphatases have been previously linked to genetic disorders. A gene-to-patient approach matching variants to phenotypic data identified 9 novel candidate rare-disease genes: PTPRD, PTPRG, PTPRT, PTPRU, PTPRZ1, MTMR3, GAK, TPTE2, PTPN18. As the number of patients undergoing whole genome sequencing increases and information sharing improves, we anticipate that reiterative analysis of genomic and phenotypic data will continue to identify candidate phosphatase disease genes for functional validation. This is the first step towards delineating the aetiology of rare genetic disorders associated with altered phosphatase function, leading to new biological insights and improved clinical outcomes for the affected individuals and their families.

Clinical and Neurophysiologic Phenotypes in Neonates With BRAT1 Encephalopathy

BACKGROUND AND OBJECTIVES

BRAT1 encephalopathy is an ultra-rare autosomal recessive neonatal encephalopathy. We delineate the neonatal electroclinical phenotype at presentation and provide insights for early diagnosis.

METHODS

Through a multinational collaborative, we studied a cohort of neonates with encephalopathy associated with biallelic pathogenic variants in BRAT1 for whom detailed clinical, neurophysiologic, and neuroimaging information was available from the onset of symptoms. Neuropathologic changes were also analyzed.

RESULTS

We included 19 neonates. Most neonates were born at term (16/19) from nonconsanguineous parents. 15/19 (79%) were admitted soon after birth to a neonatal intensive care unit, exhibiting multifocal myoclonus, both spontaneous and exacerbated by stimulation. 7/19 (37%) had arthrogryposis at birth, and all except 1 progressively developed hypertonia in the first week of life. Multifocal myoclonus, which was present in all but 1 infant, was the most prominent manifestation and did not show any EEG correlate in 16/19 (84%). Video-EEG at onset was unremarkable in 14/19 (74%) infants, and 6 (33%) had initially been misdiagnosed with hyperekplexia. Multifocal seizures were observed at a median age of 14 days (range: 1-29). During the first months of life, all infants developed progressive encephalopathy, acquired microcephaly, prolonged bouts of apnea, and bradycardia, leading to cardiac arrest and death at a median age of 3.5 months (range: 20 days to 30 months). Only 7 infants (37%) received a definite diagnosis before death, at a median age of 34 days (range: 25-126), and almost two-thirds (12/19, 63%) were diagnosed 8 days to 12 years postmortem (median: 6.5 years). Neuropathology examination, performed in 3 patients, revealed severely delayed myelination and diffuse astrogliosis, sparing the upper cortical layers.

DISCUSSION

BRAT1 encephalopathy is a neonatal-onset, rapidly progressive neurologic disorder. Neonates are often misdiagnosed as having hyperekplexia, and many die undiagnosed. The key phenotypic features are multifocal myoclonus, an organized EEG, progressive, persistent, and diffuse hypertonia, and an evolution into refractory multifocal seizures, prolonged bouts of apnea, bradycardia, and early death. Early recognition of BRAT1 encephalopathy allows for prompt workup, appropriate management, and genetic counseling.

Targeting de novo loss-of-function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project

BACKGROUND

Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient's phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP methods.

METHODS

The Loss-of-function Observed/Expected Upper-bound Fraction (LOEUF) score quantifies gene constraint, with low scores correlated with haploinsufficiency. We applied DeNovoLOEUF, a filtering strategy to sequencing data from 13,949 rare disease trios in the 100KGP, by filtering for rare, de novo, loss-of-function variants in disease genes with a LOEUF score < 0.2. We compared our findings with the corresponding patient's diagnostic reports.

RESULTS

324/332 (98%) of the variants identified using DeNovoLOEUF were diagnostic or partially diagnostic (whereby the variant was responsible for some of the phenotype). We identified 39 diagnoses that were "missed" by 100KGP standard analyses, which are now being returned to patients.

CONCLUSION

We have demonstrated a highly specific and rapid method with a 98% positive predictive value that has good concordance with standard analysis, low false-positive rate, and can identify additional diagnoses. Globally, as more patients are being offered genome sequencing, we anticipate that DeNovoLOEUF will rapidly identify new diagnoses and facilitate iterative analyses when new disease genes are discovered.

Exome/Genome Sequencing in Undiagnosed Syndromes

Exome sequencing (ES) and genome sequencing (GS) have radically transformed the diagnostic approach to undiagnosed rare/ultrarare Mendelian diseases. Next-generation sequencing (NGS), the technology integral for ES, GS, and most large (100+) gene panels, has enabled previously unimaginable diagnoses, changes in medical management, new treatments, and accurate reproductive risk assessments for patients, as well as new disease gene discoveries. Yet, challenges remain, as most individuals remain undiagnosed with current NGS. Improved NGS technology has resulted in long-read sequencing, which may resolve diagnoses in some patients who do not obtain a diagnosis with current short-read ES and GS, but its effectiveness is unclear, and it is expensive. Other challenges that persist include the resolution of variants of uncertain significance, the urgent need for patients with ultrarare disorders to have access to therapeutics, the need for equity in patient access to NGS-based testing, and the study of ethical concerns. However, the outlook for undiagnosed disease resolution is bright, due to continual advancements in the field.

Considerations on the use of carrier screening testing in human reproduction: comparison between recommendations from the Italian Society of Human Genetics and other international societies

PURPOSE

Carrier screening (CS) is a term used to describe a genetic test performed on individuals without family history of genetic disorders, to investigate the carrier status for pathogenic variants associated with multiple recessive conditions. The advent of next-generation sequencing enabled simultaneous CS for an increasing number of conditions; however, a consensus on which diseases to include in gene panels and how to best develop the provision of CS is far to be reached. Therefore, the provision of CS is jeopardized and inconsistent and requires solving several important issues.

METHODS

In 2020, the Italian Society of Human Genetics (SIGU) established a working group composed of clinical and laboratory geneticists from public and private fields to elaborate a document to define indications and best practice of CS provision for couples planning a pregnancy.

RESULTS

Hereby, we present the outcome of the Italian working group's activity and compare it with previously published international recommendations (American College of Medical Genetics and Genomics (ACMG), American College of Obstetricians and Gynecologists (ACOG), and Royal Australian and New Zealand College of Obstetricians and Gynaecologists (RANZCOG)). We determine a core message on genetic counseling and nine main subject categories to explore, spanning from goals and execution to technical scientific, ethical, and socio-economic topics. Moreover, a level of agreement on the most critical points is discussed using a 5-point agreement scale, demonstrating a high level of consensus among the four societies.

CONCLUSIONS

This document is intended to provide genetic and healthcare professionals involved in human reproduction with guidance regarding the clinical implementation of CS.

Complex genomic rearrangements: an underestimated cause of rare diseases

Complex genomic rearrangements (CGRs) are known contributors to disease but are often missed during routine genetic screening. Identifying CGRs requires (i) identifying copy number variants (CNVs) concurrently with inversions, (ii) phasing multiple breakpoint junctions incis, as well as (iii) detecting and resolving structural variants (SVs) within repeats. We demonstrate how combining cytogenetics and new sequencing methodologies is being successfully applied to gain insights into the genomic architecture of CGRs. In addition, we review CGR patterns and molecular features revealed by studying constitutional genomic disorders. These data offer invaluable lessons to individuals interested in investigating CGRs, evaluating their clinical relevance and frequency, as well as assessing their impact(s) on rare genetic diseases.

Mendelian gene identification through mouse embryo viability screening

BACKGROUND

The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.

METHODS

Here we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project.

RESULTS

We found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts.

CONCLUSIONS

Information on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes

PURPOSE

Exome and genome sequencing have drastically accelerated novel disease gene discoveries. However, discovery is still hindered by myriad variants of uncertain significance found in genes of undetermined biological function. This necessitates intensive functional experiments on genes of equal predicted causality, leading to a major bottleneck.

METHODS

We apply the loss-of-function observed/expected upper-bound fraction metric of intolerance to gene inactivation to curate a list of predicted haploinsufficient disease genes. Using data from the 100,000 Genomes Project, we adopt a gene-to-patient approach that matches de novo loss-of-function variants in constrained genes to patients with rare disease. Through large-scale aggregation of data, we reduce excess analytical noise currently hindering novel discoveries.

RESULTS

Results from 13,949 trios revealed 643 rare, de novo predicted loss-of-function events filtered from 1044 loss-of-function observed/expected upper-bound fraction-constrained genes. A total of 168 variants occurred within 126 genes without a known disease-gene relationship. Of these, 27 genes had >1 kindred affected, and for 18 of these genes, multiple kindreds had overlapping phenotypes. Two years after initial analysis, 11 of 18 (61%) of these genes have been independently published as novel disease gene discoveries.

CONCLUSION

Using large cohorts and adopting gene-based approaches can rapidly and objectively accelerate dominantly inherited novel gene discovery by targeting the most appropriate genes for functional validation.

Recommendations for next generation sequencing data reanalysis of unsolved cases with suspected Mendelian disorders: A systematic review and meta-analysis

PURPOSE

The study aimed to determine the diagnostic yield, optimal timing, and methodology of next generation sequencing data reanalysis in suspected Mendelian disorders.

METHODS

We conducted a systematic review and meta-analysis of studies that conducted data reanalysis in patients with suspected Mendelian disorders. Random effects model was used to pool the estimated outcome with subgroup analysis stratified by timing, sequencing methodology, sample size, segregation, use of research validation, and artificial intelligence (AI) variant curation tools.

RESULTS

A search of PubMed, Embase, Scopus, and Web of Science between 2007 and 2021 yielded 9327 articles, of which 29 were selected. Significant heterogeneity was noted between studies. Reanalysis had an overall diagnostic yield of 0.10 (95% CI = 0.06-0.13). Literature updates accounted for most new diagnoses. Diagnostic yield was higher after 24 months, although this was not statistically significant. Increased diagnoses were obtained with research validation and data sharing. AI-based tools did not adversely affect reanalysis diagnostic rate.

CONCLUSION

Next generation sequencing data reanalysis can improve diagnostic yield. Owing to the heterogeneity of the studies, the optimal time to reanalysis and the impact of AI-based tools could not be determined with confidence. We propose standardized guidelines for future studies to reduce heterogeneity and improve the quality of the conclusions.

Diagnostic testing laboratories are valuable partners for disease gene discovery: 5-year experience with GeneMatcher

Although the rates of disease gene discovery have steadily increased with the expanding use of genome and exome sequencing by clinical and research laboratories, only ~16% of genes in the genome have confirmed disease associations. Here we describe our clinical laboratory's experience utilizing GeneMatcher, an online portal designed to promote disease gene discovery and data sharing. Since 2016, we submitted 246 candidates from 243 unique genes to GeneMatcher, of which 111 (45%) are now clinically characterized. Submissions meeting our candidate gene‐reporting criteria based on a scoring system using patient and molecular‐weighted evidence were significantly more likely to be characterized as of October 2021 versus genes that did not meet our clinical‐reporting criteria (p = 0.025). We reported relevant findings related to these newly characterized gene–disease associations in 477 probands. In 218 (46%) instances, we issued reclassifications after an initial negative or candidate gene (uncertain) report. We coauthored 104 publications delineating gene–disease relationships, including descriptions of new associations (60%), additional supportive evidence (13%), subsequent descriptive cohorts (23%), and phenotypic expansions (4%). Clinical laboratories are pivotal for disease gene discovery efforts and can screen phenotypes based on genotype matches, contact clinicians of relevant cases, and issue proactive reclassification reports.

Variant interpretation using population databases: Lessons from gnomAD

Reference population databases are an essential tool in variant and gene interpretation. Their use guides the identification of pathogenic variants amidst the sea of benign variation present in every human genome, and supports the discovery of new disease-gene relationships. The Genome Aggregation Database (gnomAD) is currently the largest and most widely used publicly available collection of population variation from harmonized sequencing data. The data is available through the online gnomAD browser (https://gnomad.broadinstitute.org/) that enables rapid and intuitive variant analysis. This review provides guidance on the content of the gnomAD browser, and its usage for variant and gene interpretation. We introduce key features including allele frequency, per-base expression levels, constraint scores, and variant co-occurrence, alongside guidance on how to use these in analysis, with a focus on the interpretation of candidate variants and novel genes in rare disease.