Lumping versus splitting: How to approach defining a disease to enable accurate genomic curation

Perspectives on the Current and Future State of Artificial Intelligence in Medical Genetics

Artificial intelligence (AI) is rapidly transforming numerous aspects of daily life, including clinical practice and biomedical research. In light of this rapid transformation, and in the context of medical genetics, we assembled a group of leaders in the field to respond to the question about how AI is affecting, and especially how AI will affect, medical genetics. The authors who contributed to this collection of essays intentionally represent different areas of expertise, career stages, and geographies, and include diverse types of clinicians, computer scientists, and researchers. The individual pieces cover a wide range of areas related to medical genetics; we expect that these pieces may provide helpful windows into the ways in which AI is being actively studied, used, and considered in medical genetics.

Artificial intelligence-driven genotype-epigenotype-phenotype approaches to resolve challenges in syndrome diagnostics

BACKGROUND

Decisions to split two or more phenotypic manifestations related to genetic variations within the same gene can be challenging, especially during the early stages of syndrome discovery. Genotype-based diagnostics with artificial intelligence (AI)-driven approaches using next-generation phenotyping (NGP) and DNA methylation (DNAm) can be utilized to expedite syndrome delineation within a single gene.

METHODS

We utilized an expanded cohort of 56 patients (22 previously unpublished individuals) with truncating variants in the MN1 gene and attempted different methods to assess plausible strategies to objectively delineate phenotypic differences between the C-Terminal Truncation (CTT) and N-Terminal Truncation (NTT) groups. This involved transcriptomics analysis on available patient fibroblast samples and AI-assisted approaches, including a new statistical method of GestaltMatcher on facial photos and blood DNAm analysis using a support vector machine (SVM) model.

FINDINGS

RNA-seq analysis was unable to show a significant difference in transcript expression despite our previous hypothesis that NTT variants would induce nonsense mediated decay. DNAm analysis on nine blood DNA samples revealed an episignature for the CTT group. In parallel, the new statistical method of GestaltMatcher objectively distinguished the CTT and NTT groups with a low requirement for cohort number. Validation of this approach was performed on syndromes with known DNAm signatures of SRCAP, SMARCA2 and ADNP to demonstrate the effectiveness of this approach.

INTERPRETATION

We demonstrate the potential of using AI-based technologies to leverage genotype, phenotype and epigenetics data in facilitating splitting decisions in diagnosis of syndromes with minimal sample requirement.

FUNDING

The specific funding of this article is provided in the acknowledgements section.

Curation of gene-disease relationships in primary antibody deficiencies using the ClinGen validation framework

BACKGROUND

The Clinical Genome Resource (ClinGen) is an international collaborative effort among scientists and clinicians, diagnostic and research laboratories, and the patient community. Using a standardized framework, ClinGen has established guidelines to classify gene-disease relationships as definitive, strong, moderate, and limited on the basis of available scientific and clinical evidence. When the genetic and functional evidence for a gene-disease relationship has conflicting interpretations or contradictory evidence, they can be disputed or refuted.

OBJECTIVE

We assessed genes related to primary antibody deficiencies.

METHODS

The ClinGen Antibody Deficiencies Gene Curation Expert Panel, using the ClinGen framework, classified genes related to primary antibody deficiency that primarily affect B-cell development and/or function, and that account for the largest proportion of inborn errors of immunity or primary immunodeficiencies.

RESULTS

The expert panel curated a total of 65 genes associated with humoral immune defects to validate 74 gene-disease relationships. Of these, 40 were classified as definitive, 1 as strong, 16 as moderate, 15 as limited, and 2 as disputed. The curation process involved reviewing 490 patient records and 3546 associated human phenotype ontology entries. The 3 most frequently observed terms related to primary antibody deficiency were decreased circulating antibody level, pneumonia, and lymphadenopathy.

CONCLUSIONS

These curations (publicly available at ClinicalGenome.org) represent the first effort to provide a comprehensive genetic and phenotypic revision of genetic disorders affecting humoral immunity, as reviewed and approved by experts in the field.

Evaluation of Targeted Therapies Currently Available for Congenital Genetic Conditions Indexed in GeneReviews

In this study, we propose a definition of targeted therapy and use GeneReviews, a peer-reviewed, online point-of-care resource for primarily constitutional (or rare congenital mosaic) genetic conditions, to compile a list of primarily heritable genetic disorders for which such targeted therapy is available. This study aims to give a high-level view of the types of targeted therapies and the proportion of congenital genetic disorders for which a targeted therapy is available. We propose that a targeted therapy is one that addresses the underlying molecular mechanism of the disorder and/or can alter the disease course (including by providing a cure in some instances) but may not be an obvious treatment option without knowledge of the patient's underlying genetic condition. For the purposes of this study, a treatment meeting one or both of these criteria was categorized as targeted. This means that the clinician might not consider the specific treatment option unless the patient was known to have the genetic diagnosis. This definition does not include therapies based on symptoms alone, which does not rely on the clinician being aware of a patient's genetic diagnosis. As most of the congenital genetic conditions in this study are rare and often diagnosed in a pediatric age group, determining efficacy for the specific use of most of the targeted therapies is not possible, although any drug or medication in the Management section of GeneReviews is approved by the Food and Drug Administration (FDA), with rare exceptions for drugs approved by the European Medicines Agency (EMA) of the European Union (EU) but not yet FDA approved. Of 790 GeneReviews chapters on primarily constitutional genetic conditions included in this study, 176 chapters representing over 255 genes meet the definition of having a targeted therapy.

Genes Associated With Hypertrophic Cardiomyopathy: A Reappraisal by the ClinGen Hereditary Cardiovascular Disease Gene Curation Expert Panel

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is an inherited cardiac condition affecting ∼1 in 500 and exhibits marked genetic heterogeneity. Previously published in 2019, 57 HCM-associated genes were curated providing the first systematic evaluation of gene-disease validity.

OBJECTIVES

The authors report work by the Clinical Genome Resource Hereditary Cardiovascular Disease (HCVD) Gene Curation Expert Panel (GCEP) to reappraise the clinical validity of previously curated and new putative HCM genes.

METHODS

The Clinical Genome Resource systematic gene curation framework was used to reclassify the gene-disease relationships for HCM and related syndromic entities involving left ventricular hypertrophy. Genes previously curated were included if their classification was not definitive, and if the time since curation was >2 to 3 years. New genes with literature assertions for HCM were included for initial evaluation. Existing genes were curated for new inheritance patterns where evidence existed. Curations were presented on twice monthly calls, with the HCVD GCEP composed of 29 individuals from 21 institutions across 6 countries.

RESULTS

Thirty-one genes were recurated and an additional 5 new potential HCM-associated genes were curated. Among the recurated genes, 17 (55%) genes changed classification: 1 limited and 4 disputed (from no known disease relationship), 9 disputed (from limited), and 3 definitive (from moderate). Among these, 3 (10%) genes had a clinically relevant upgrade, including TNNC1, a 9th sarcomere gene with definitive HCM association. With new evidence, 2 genes were curated for multiple inheritance patterns (TRIM63, disputed for autosomal dominant but moderate for autosomal recessive; ALPK3, strong for autosomal dominant and definitive for recessive). CSRP3 was curated for a semidominant mode of inheritance (definitive). Nine (29%) genes were downgraded to disputed, further discouraging clinical reporting of variants in these genes. Five genes recently reported to cause HCM were curated: RPS6KB1 and RBM20 (limited), KLHL24 and MT-TI (moderate), and FHOD3 (definitive).

CONCLUSIONS

We report 29 genes with definitive, strong, or moderate evidence of causation for HCM or isolated left ventricular hypertrophy, including sarcomere, sarcomere-associated, and syndromic conditions.

ClinGen recuration of hearing loss-associated genes demonstrates significant changes in gene-disease validity over time

PURPOSE

The Clinical Genome Resource (ClinGen) Hearing Loss Gene Curation Expert Panel was assembled in 2016 and has since curated 174 gene-disease relationships (GDRs) using ClinGen's semiquantitative framework. ClinGen mandates the timely recuration of all GDRs classified as Disputed, Limited, Moderate, and Strong every 2 to 3 years.

METHODS

Thirty-five GDRs met the criteria for recuration within 2 years of original curation. Previous evidence was reevaluated using the latest curation guidelines, and a comprehensive literature review was performed to obtain new evidence. Recurations were approved by the Gene Curation Expert Panel and published on the ClinGen website (www.clinicalgenome.org).

RESULTS

Eight of 35 GDRs (22%) changed their classification. Two Moderate and 5 Strong GDRs were upgraded to Definitive because of new case evidence. One Strong was subsumed under another Definitive GDR after evaluation of the lumping/splitting of disease entities. Twenty-seven of 35 patients remained unchanged, with little to no new evidence reported.

CONCLUSION

Genes classified as Moderate and Strong were likely to build evidence and change their classification over time, whereas Limited were unlikely to gain evidence. These findings highlight the critical role of recuration in ensuring that genetic tests and research studies incorporate the most recent evidence into their efforts.

A guide to gene-disease relationships in nephrology

The use of next-generation sequencing technologies such as exome and genome sequencing in research and clinical care has transformed our understanding of the molecular architecture of genetic kidney diseases. Although the capability to identify and rigorously assess genetic variants and their relationship to disease has advanced considerably in the past decade, the curation of clinically relevant relationships between genes and specific phenotypes has received less attention, despite it underpinning accurate interpretation of genomic tests. Here, we discuss the need to accurately define gene-disease relationships in nephrology and provide a framework for appraising genetic and experimental evidence critically. We describe existing international programmes that provide expert curation of gene-disease relationships and discuss sources of discrepancy as well as efforts at harmonization. Further, we highlight the need for alignment of disease and phenotype terminology to ensure robust and reproducible curation of knowledge. These collective efforts to support evidence-based translation of genomic sequencing into practice across clinical, diagnostic and research settings are crucial for delivering the promise of precision medicine in nephrology, providing more patients with timely diagnoses, accurate prognostic information and access to targeted treatments.

The ClinGen Syndromic Disorders Gene Curation Expert Panel: Assessing the Clinical Validity of 111 Gene-Disease Relationships

Purpose

The Clinical Genome Resource (ClinGen) Gene Curation Expert Panels (GCEPs) have historically focused on specific organ systems or phenotypes; thus, the ClinGen Syndromic Disorders GCEP (SD-GCEP) was formed to address an unmet need.

Methods

The SD-GCEP applied ClinGen's framework to evaluate the clinical validity of genes associated with rare syndromic disorders. 111 Gene-Disease Relationships (GDRs) associated with 100 genes spanning the clinical spectrum of syndromic disorders were curated.

Results

From April 2020 through March 2024, 38 precurations were performed on genes with multiple disease relationships and were reviewed to determine if the disorders were part of a spectrum or distinct entities. 14 genes were lumped into a single disease entity and 24 were split into separate entities, of which 11 were curated by the SD-GCEP. A full review of 111 GDRs for 100 genes followed, with 78 classified as Definitive, 9 as Strong, 15 as Moderate, and 9 as Limited highlighting where further data are needed. All diseases involved two or more organ systems, while the majority (88/111 GDRs, 79.2%) had five or more organ systems affected.

Conclusion

The SD-GCEP addresses a critical gap in gene curation efforts, enabling inclusion of genes for syndromic disorders in clinical testing and contributing to keeping pace with the rapid discovery of new genetic syndromes.

Beyond genomic studies of congenital heart defects through systematic modelling and phenotyping

Congenital heart defects (CHDs), the most common congenital anomalies, are considered to have a significant genetic component. However, despite considerable efforts to identify pathogenic genes in patients with CHDs, few gene variants have been proven as causal. The complexity of the genetic architecture underlying human CHDs likely contributes to this poor genetic discovery rate. However, several other factors are likely to contribute. For example, the level of patient phenotyping required for clinical care may be insufficient for research studies focused on mechanistic discovery. Although several hundred mouse gene knockouts have been described with CHDs, these are generally not phenotyped and described in the same way as CHDs in patients, and thus are not readily comparable. Moreover, most patients with CHDs carry variants of uncertain significance of crucial cardiac genes, further complicating comparisons between humans and mouse mutants. In spite of major advances in cardiac developmental biology over the past 25 years, these advances have not been well communicated to geneticists and cardiologists. As a consequence, the latest data from developmental biology are not always used in the design and interpretation of studies aimed at discovering the genetic causes of CHDs. In this Special Article, while considering other in vitro and in vivo models, we create a coherent framework for accurately modelling and phenotyping human CHDs in mice, thereby enhancing the translation of genetic and genomic studies into the causes of CHDs in patients.

Expert panel curation of 31 genes in relation to limb girdle muscular dystrophy

OBJECTIVE

Limb girdle muscular dystrophies (LGMDs) are a group of genetically heterogeneous autosomal conditions with some degree of phenotypic homogeneity. LGMD is defined as having onset >2 years of age with progressive proximal weakness, elevated serum creatine kinase levels and dystrophic features on muscle biopsy. Advances in massively parallel sequencing have led to a surge in genes linked to LGMD.

METHODS

The ClinGen Muscular Dystrophies and Myopathies gene curation expert panel (MDM GCEP, formerly Limb Girdle Muscular Dystrophy GCEP) convened to evaluate the strength of evidence supporting gene-disease relationships (GDR) using the ClinGen gene-disease clinical validity framework to evaluate 31 genes implicated in LGMD.

RESULTS

The GDR was exclusively LGMD for 17 genes, whereas an additional 14 genes were related to a broader phenotype encompassing congenital weakness. Four genes (CAPN3, COL6A1, COL6A2, and COL6A3) were split into two separate disease entities, based on each displaying both dominant and recessive inheritance patterns, resulting in curation of 35 GDRs. Of these, 30 (86%) were classified as definitive, 4 (11%) as moderate, and 1 (3%) as limited. Two genes, POMGNT1 and DAG1, though definitively related to myopathy, currently have insufficient evidence to support a relationship specifically with LGMD.

INTERPRETATION

The expert-reviewed assertions on the clinical validity of genes implicated in LGMDs form an invaluable resource for clinicians and molecular geneticists. We encourage the global neuromuscular community to publish case-level data that help clarify disputed or novel LGMD associations.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

ClinGen Hereditary Cardiovascular Disease Gene Curation Expert Panel: Reappraisal of Genes associated with Hypertrophic Cardiomyopathy

Background

Hypertrophic cardiomyopathy (HCM) is an inherited cardiac condition affecting ~1 in 500 and exhibits marked genetic heterogeneity. Previously published in 2019, 57 HCM-associated genes were curated providing the first systematic evaluation of gene-disease validity. Here we report work by the ClinGen Hereditary Cardiovascular Disorders Gene Curation Expert Panel (HCVD-GCEP) to reappraise the clinical validity of previously curated and new putative HCM genes.

Methods

The ClinGen systematic gene curation framework was used to re-classify the gene-disease relationships for HCM and related syndromic entities involving left ventricular hypertrophy. Genes previously curated were included if their classification was not definitive, and if the time since curation was >2-3 years. New genes with literature assertions for HCM were included for initial evaluation. Existing genes were curated for new inheritance patterns where evidence existed. Curations were presented on twice monthly calls, with the HCVD-GCEP composed of 29 individuals from 21 institutions across 6 countries.

Results

Thirty-one genes were re-curated and an additional 5 new potential HCM-associated genes were curated. Among the re-curated genes, 17 (55%) genes changed classification: 1 limited and 4 disputed (from no known disease relationship), 9 disputed (from limited), and 3 definitive (from moderate). Among these, 3 (10%) genes had a clinically relevant upgrade, including TNNC1, a 9th sarcomere gene with definitive HCM association. With new evidence, two genes were curated for multiple inheritance patterns (TRIM63, disputed for autosomal dominant but moderate for autosomal recessive; ALPK3, strong for autosomal dominant and definitive for recessive). CSRP3 was curated for a semi-dominant mode of inheritance (definitive). Nine (29%) genes were downgraded to disputed, further discouraging clinical reporting of variants in these genes. Five genes recently reported to cause HCM were curated: RPS6KB1 and RBM20 (limited), KLHL24 and MT-TI (moderate), and FHOD3 (definitive).

Conclusions

We report 29 genes with definitive, strong or moderate evidence of causation for HCM or isolated LVH, including sarcomere, sarcomere-associated and syndromic conditions.

Human ABL1 deficiency syndrome (HADS) is a recognizable syndrome distinct from ABL1-related congenital heart defects and skeletal malformations syndrome

Germline gain of function variants in the oncogene ABL1 cause congenital heart defects and skeletal malformations (CHDSKM) syndrome. Whether a corresponding ABL1 deficiency disorder exists in humans remains unknown although developmental defects in mice deficient for Abl1 support this notion. Here, we describe two multiplex consanguineous families, each segregating a different homozygous likely loss of function variant in ABL1. The associated phenotype is multiple congenital malformations and distinctive facial dysmorphism that are opposite in many ways to CHDSKM. We suggest that a tight balance of ABL1 activity is required during embryonic development and that both germline gain of function and loss of function variants result in distinctively different allelic congenital malformation disorders.

Expert Panel Curation of 31 Genes in Relation to Limb Girdle Muscular Dystrophy

Introduction

Limb girdle muscular dystrophies (LGMDs) are a group of genetically heterogeneous autosomal conditions with some degree of phenotypic homogeneity. LGMD is defined as having onset >2 years of age with progressive proximal weakness, elevated serum creatine kinase levels and dystrophic features on muscle biopsy. Advances in massively parallel sequencing have led to a surge in genes linked to LGMD.

Methods

The ClinGen Muscular Dystrophies and Myopathies gene curation expert panel (MDM GCEP, formerly Limb Girdle Muscular Dystrophy GCEP) convened to evaluate the strength of evidence supporting gene-disease relationships (GDR) using the ClinGen gene-disease clinical validity framework to evaluate 31 genes implicated in LGMD.

Results

The GDR was exclusively LGMD for 17 genes, whereas an additional 14 genes were related to a broader phenotype encompassing congenital weakness. Four genes (CAPN3, COL6A1, COL6A2, COL6A3) were split into two separate disease entities, based on each displaying both dominant and recessive inheritance patterns, resulting in curation of 35 GDRs. Of these, 30 (86%) were classified as Definitive, 4 (11%) as Moderate and 1 (3%) as Limited. Two genes, POMGNT1 and DAG1, though definitively related to myopathy, currently have insufficient evidence to support a relationship specifically with LGMD.

Conclusions

The expert-reviewed assertions on the clinical validity of genes implicated in LGMDs form an invaluable resource for clinicians and molecular geneticists. We encourage the global neuromuscular community to publish case-level data that help clarify disputed or novel LGMD associations.

How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?

Incomplete penetrance is the rule rather than the exception in Mendelian disease. In syndromic monogenic disorders, phenotypic variability can be viewed as the combination of incomplete penetrance for each of multiple independent clinical features. Within genetically identical individuals, such as isogenic model organisms, stochastic variation at molecular and cellular levels is the primary cause of incomplete penetrance according to a genetic threshold model. By defining specific probability distributions of causal biological readouts and genetic liability values, stochasticity and incomplete penetrance provide information about threshold values in biological systems. Ascertainment of threshold values has been achieved by simultaneous scoring of relatively simple phenotypes and quantitation of molecular readouts at the level of single cells. However, this is much more challenging for complex morphological phenotypes using experimental and reductionist approaches alone, where cause and effect are separated temporally and across multiple biological modes and scales. Here I consider how causal inference, which integrates observational data with high confidence causal models, might be used to quantify the relative contribution of different sources of stochastic variation to phenotypic diversity. Collectively, these approaches could inform disease mechanisms, improve predictions of clinical outcomes and prioritize gene therapy targets across modes and scales of gene function. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Exploring the impact and utility of genomic sequencing in established CKD

Clinical genetics is increasingly recognized as an important area within nephrology care. Clinicians require awareness of genetic kidney disease to recognize clinical phenotypes, consider use of genomics to aid diagnosis, and inform treatment decisions. Understanding the broad spectrum of clinical phenotypes and principles of genomic sequencing is becoming increasingly required in clinical nephrology, with nephrologists requiring education and support to achieve meaningful patient outcomes. Establishment of effective clinical resources, multi-disciplinary teams and education is important to increase application of genomics in clinical care, for the benefit of patients and their families. Novel applications of genomics in chronic kidney disease include pharmacogenomics and clinical translation of polygenic risk scores. This review explores established and emerging impacts and utility of genomics in kidney disease.

NeuroTri2-VISDOT: An open-access tool to harness the power of second trimester human single cell data to inform models of Mendelian neurodevelopmental disorders

Whole exome and genome sequencing, coupled with refined bioinformatic pipelines, have enabled improved diagnostic yields for individuals with Mendelian conditions and have led to the rapid identification of novel syndromes. For many Mendelian neurodevelopmental disorders (NDDs), there is a lack of pre-existing model systems for mechanistic work. Thus, it is critical for translational researchers to have an accessible phenotype- and genotype-informed approach for model system selection. Single-cell RNA sequencing data can be informative in such an approach, as it can indicate which cell types express a gene of interest at the highest levels across time. For Mendelian NDDs, such data for the developing human brain is especially useful. A valuable single-cell RNA sequencing dataset of the second trimester developing human brain was produced by Bhaduri et al in 2021, but access to these data can be limited by computing power and the learning curve of single-cell data analysis. To reduce these barriers for translational research on Mendelian NDDs, we have built the web-based tool, Neurodevelopment in Trimester 2 - VIsualization of Single cell Data Online Tool (NeuroTri2-VISDOT), for exploring this single-cell dataset, and we have employed it in several different settings to demonstrate its utility for the translational research community.

Fifty years of executive control research in attention-deficit/hyperactivity disorder:What we have learned and still need to know

For 50 years, attention-deficit/hyperactivity disorder (ADHD) has been considered a disorder of executive control (EC), the higher-order, cognitive skills that support self-regulation, goal attainment and what we generally call "attention." This review surveys our current understanding of the nature of EC as it pertains to ADHD and considers the evidence in support of eight hypotheses that can be derived from the EC theory of ADHD. This paper provides a resource for practitioners to aid in clinical decision-making. To support theory building, I draw a parallel between the EC theory of ADHD and the common gene-common variant model of complex traits such as ADHD. The conclusion offers strategies for advancing collaborative research.

Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

BACKGROUND

As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings.

METHODS

We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering.

RESULTS

For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches.

CONCLUSIONS

Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing.

Exploring the complex spectrum of dominance and recessiveness in genetic cardiomyopathies

Discrete categorization of Mendelian disease genes into dominant and recessive models often oversimplifies their underlying genetic architecture. Cardiomyopathies (CMs) are genetic diseases with complex etiologies for which an increasing number of recessive associations have recently been proposed. Here, we comprehensively analyze all published evidence pertaining to biallelic variation associated with CM phenotypes to identify high-confidence recessive genes and explore the spectrum of monoallelic and biallelic variant effects in established recessive and dominant disease genes. We classify 18 genes with robust recessive association with CMs, largely characterized by dilated phenotypes, early disease onset and severe outcomes. Several of these genes have monoallelic association with disease outcomes and cardiac traits in the UK Biobank, including LMOD2 and ALPK3 with dilated and hypertrophic CM, respectively. Our data provide insights into the complex spectrum of dominance and recessiveness in genetic heart disease and demonstrate how such approaches enable the discovery of unexplored genetic associations.

Expert Panel Curation of 113 Primary Mitochondrial Disease Genes for the Leigh Syndrome Spectrum

OBJECTIVE

Primary mitochondrial diseases (PMDs) are heterogeneous disorders caused by inherited mitochondrial dysfunction. Classically defined neuropathologically as subacute necrotizing encephalomyelopathy, Leigh syndrome spectrum (LSS) is the most frequent manifestation of PMD in children, but may also present in adults. A major challenge for accurate diagnosis of LSS in the genomic medicine era is establishing gene-disease relationships (GDRs) for this syndrome with >100 monogenic causes across both nuclear and mitochondrial genomes.

METHODS

The Clinical Genome Resource (ClinGen) Mitochondrial Disease Gene Curation Expert Panel (GCEP), comprising 40 international PMD experts, met monthly for 4 years to review GDRs for LSS. The GCEP standardized gene curation for LSS by refining the phenotypic definition, modifying the ClinGen Gene-Disease Clinical Validity Curation Framework to improve interpretation for LSS, and establishing a scoring rubric for LSS.

RESULTS

The GDR with LSS across the nuclear and mitochondrial genomes was classified as definitive for 31 of 114 GDRs curated (27%), moderate for 38 (33%), limited for 43 (38%), and disputed for 2 (2%). Ninety genes were associated with autosomal recessive inheritance, 16 were maternally inherited, 5 were autosomal dominant, and 3 were X-linked.

INTERPRETATION

GDRs for LSS were established for genes across both nuclear and mitochondrial genomes. Establishing these GDRs will allow accurate variant interpretation, expedite genetic diagnosis of LSS, and facilitate precision medicine, multisystem organ surveillance, recurrence risk counseling, reproductive choice, natural history studies, and determination of eligibility for interventional clinical trials. ANN NEUROL 2023;94:696-712.

Using whole genome sequence findings to assess gene-disease causality in cardiomyopathy and arrhythmia patients

Aim: The genetic etiologies of cardiomyopathies and arrhythmias have not been fully elucidated. Materials & methods: Research findings from genome analyses in a cardiomyopathy and arrhythmia cohort were gathered. Gene-disease relationships from two databases were compared with patient phenotypes. A literature review was conducted for genes with limited evidence. Results: Of 43 genes with candidate findings from 18 cases, 23.3% of genes had never been curated, 15.0% were curated for cardiomyopathies, 16.7% for arrhythmias and 31.3% for other conditions. 25.5% of candidate findings were curated for the patient's specific phenotype with 11.8% having definitive evidence. MYH6 and TPCN1 were flagged for recuration. Conclusion: Findings from genome sequencing in disease cohorts may be useful to guide gene-curation efforts.

Beyond gene-disease validity: capturing structured data on inheritance, allelic-requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

Background

As availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including as secondary findings.

Methods

We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering.

Results

For 36/65 gene-disease pairs, loss-of-function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using CardiacG2P as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches.

Conclusions

Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is pre-requisite for scalable genomic testing.