Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository

State of open science in cancer research

PURPOSE

This study has been focused on assessing the Open Science scenario of cancer research during the period 2011-2021, in terms of the derived scientific publications and raw data dissemination.

METHODS

A cancer search equation was executed in the Science Citation Index-Expanded, collecting the papers signed by at least one Spanish institution. The same search strategy was performed in the Data Citation Index to describe dataset diffusion.

RESULTS

50,822 papers were recovered, 71% of which belong to first and second quartile journals. 59% of the articles were published in Open Access (OA) journals. The Open Access model and international collaboration positively conditioned the number of citations received. Among the most productive journals stood out Plos One, Cancers, and Clinical and Translational Oncology. 2693 genomics, proteomics and metabolomics datasets were retrieved, being Gene Expression Omnibus the favoured repository.

CONCLUSIONS

There has been an increase in oncology publications in Open Access. Most were published in first quartile journals and received higher citations than non-Open Access articles, as well as when oncological investigation was performed between international research teams, being relevant in the context of Open Science. Genetic repositories have been the preferred for sharing oncology datasets. Further investigation of research and data sharing in oncology is needed, supported by stronger Open Science policies, to achieve better data sharing practices among three scientific main pillars: researchers, publishers, and scientific organizations.

Variant classification changes over time in the clinical molecular diagnostic laboratory setting

BACKGROUND

Variant classification in the setting of germline genetic testing is necessary for patients and their families to receive proper care. Variants are classified as pathogenic (P), likely pathogenic (LP), uncertain significance (VUS), likely benign (LB) and benign (B) using the standards and guidelines recommended by the American College of Medical Genetics and the Association for Molecular Pathology, with modifications for specific genes. As the literature continues to rapidly expand, and evidence continues to accumulate, prior classifications can be updated accordingly. In this study, we aim to characterise variant reclassifications in Ontario.

METHODS

DNA samples from patients seen at hereditary cancer clinics in Ontario from January 2012 to April 2022 were submitted for testing. Patients met provincial eligibility criteria for testing for hereditary cancer syndromes or polycystic kidney disease. Reclassification events were determined to be within their broader category of significance (B to LB or vice versa, or P to LP or vice versa) or outside of their broader category as significance (ie, significant reclassifications from B/LB or VUS or P/LP, from P/LP to VUS or B/LB, or from VUS to any other category).

RESULTS

Of the 8075 unique variants included in this study, 23.7% (1912) of variants were reassessed, and 7.2% (578) of variants were reclassified. Of these, 351 (60.7%) variants were reclassified outside of their broader category of significance. Overall, the final classification was significantly different for 336 (58.1%) variants. Importantly, most reclassified variants were downgraded to a more benign classification (n=245; 72.9%). Of note, most reclassified VUS was downgraded to B/LB (n=233; 84.7%).

CONCLUSIONS

The likelihood for reclassification of variants on reassessment is high. Most reclassified variants were downgraded to a more benign classification. Our findings highlight the importance of periodic variant reassessment to ensure timely and appropriate care for patients and their families.

SpadaHC: a database to improve the classification of variants in hereditary cancer genes in the Spanish population

Accurate classification of genetic variants is crucial for clinical decision-making in hereditary cancer. In Spain, genetic diagnostic laboratories have traditionally approached this task independently due to the lack of a dedicated resource. Here we present SpadaHC, a web-based database for sharing variants in hereditary cancer genes in the Spanish population. SpadaHC is implemented using a three-tier architecture consisting of a relational database, a web tool and a bioinformatics pipeline. Contributing laboratories can share variant classifications and variants from individuals in Variant Calling Format (VCF) format. The platform supports open and restricted access, flexible dataset submissions, automatic pseudo-anonymization, VCF quality control, variant normalization and liftover between genome builds. Users can flexibly explore and search data, receive automatic discrepancy notifications and access SpadaHC population frequencies based on many criteria. In February 2024, SpadaHC included 18 laboratory members, storing 1.17 million variants from 4306 patients and 16 343 laboratory classifications. In the first analysis of the shared data, we identified 84 genetic variants with clinically relevant discrepancies in their classifications and addressed them through a three-phase resolution strategy. This work highlights the importance of data sharing to promote consistency in variant classifications among laboratories, so patients and family members can benefit from more accurate clinical management. Database URL: https://spadahc.ciberisciii.es/.

The expanding diagnostic toolbox for rare genetic diseases

Genomic technologies, such as targeted, exome and short-read genome sequencing approaches, have revolutionized the care of patients with rare genetic diseases. However, more than half of patients remain without a diagnosis. Emerging approaches from research-based settings such as long-read genome sequencing and optical genome mapping hold promise for improving the identification of disease-causal genetic variants. In addition, new omic technologies that measure the transcriptome, epigenome, proteome or metabolome are showing great potential for variant interpretation. As genetic testing options rapidly expand, the clinical community needs to be mindful of their individual strengths and limitations, as well as remaining challenges, to select the appropriate diagnostic test, correctly interpret results and drive innovation to address insufficiencies. If used effectively - through truly integrative multi-omics approaches and data sharing - the resulting large quantities of data from these established and emerging technologies will greatly improve the interpretative power of genetic and genomic diagnostics for rare diseases.

Applying data science methodologies with artificial intelligence variant reinterpretation to map and estimate genetic disorder prevalence utilizing clinical data

Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patient encounters. Genetic variants from all genetic testing resulting to a large pediatric healthcare system for a 5-year period were obtained and reinterpreted utilizing the previously validated Franklin© Artificial Intelligence (AI). Using PowerBI©, the data were further matched to patients in the electronic healthcare record to associate with demographic data to generate a variant data table and mapped by ZIP codes. Three thousand and sixty-five variants were identified and 98% were matched to patients with geographic data. Franklin© changed the interpretation for 24% of variants. One hundred and fifty-six clinically actionable variant reinterpretations were made. A total of 739 Mendelian genetic disorders were identified with disorder prevalence estimation. Mapping of variants demonstrated hot-spots for pathogenic genetic variation such as PEX6-associated Zellweger Spectrum Disorder. Seven patients were identified with Bardet-Biedl syndrome and seven patients with Rett syndrome amenable to newly FDA-approved therapeutics. Utilizing readily available software we developed a database and Exploratory Data Analysis (EDA) methodology enabling us to systematically reinterpret variants, estimate variant prevalence, identify conditions amenable to new treatments, and localize geographies enriched for pathogenic variants.

Avoiding Liability and Other Legal Land Mines in the Evolving Genomics Landscape

This article reviews evolving legal implications for clinicians and researchers as genomics is used more widely in both the clinic and in translational research, reflecting rapid changes in scientific knowledge as well as the surrounding cultural and political environment. Professionals will face new and changing duties to make or act upon a genetic diagnosis, address direct-to-consumer genetic testing in patient care, consider the health implications of results for patients' family members, and recontact patients when test results change over time. Professional duties in reproductive genetic testing will need to be recalibrated in response to disruptive changes to reproductive rights in the United States. We also review the debate over who controls the flow of genetic information and who is responsible for its protection, considering the globally influential European Union General Data Protection Regulation and the rapidly evolving data privacy law landscape of the United States.

Analysis of hereditary cancer gene variant classifications from ClinVar indicates a need for regular reassessment of clinical assertions

The clinical classification of variants may change with new information, however, there is limited guidance on how often significant changes in variant classification occur. We used ClinVar to examine how variant classification changes over time. We developed a custom parser and accessed variant data from ClinVar between January 2015 and July 2021. The ClinVar-assigned "aggregate" classification of variants in 121 hereditary cancer genes was harmonized across releases to align to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology terms. Aggregate classification categories were grouped as: benign/likely benign (B/LB); likely pathogenic/pathogenic (LP/P); variant of uncertain significance (VUS); conflicting interpretations of pathogenicity (Conflicting); or Other. We profiled changes in aggregate variant classification between consecutive semi-annual ClinVar releases. The proportion of variants that changed aggregate classification between semi-annual ClinVar releases ranged from 0.6% to 6.4%. The most frequent changes were "VUS to conflicting," "other to LP/P," and "B/LB to Conflicting." A limited number of variants changed aggregate classification from "LP/P to B/LB," or vice versa. Our analysis indicates need for regular reassessment of clinical variant interpretations. The parser developed for this project will facilitate extraction of relevant interpretation data from ClinVar.

Shariant platform: Enabling evidence sharing across Australian clinical genetic-testing laboratories to support variant interpretation

Sharing genomic variant interpretations across laboratories promotes consistency in variant assertions. A landscape analysis of Australian clinical genetic-testing laboratories in 2017 identified that, despite the national-accreditation-body recommendations encouraging laboratories to submit genotypic data to clinical databases, fewer than 300 variants had been shared to the ClinVar public database. Consultations with Australian laboratories identified resource constraints limiting routine application of manual processes, consent issues, and differences in interpretation systems as barriers to sharing. This information was used to define key needs and solutions required to enable national sharing of variant interpretations. The Shariant platform, using both the GRCh37 and GRCh38 genome builds, was developed to enable ongoing sharing of variant interpretations and associated evidence between Australian clinical genetic-testing laboratories. Where possible, two-way automated sharing was implemented so that disruption to laboratory workflows would be minimized. Terms of use were developed through consultation and currently restrict access to Australian clinical genetic-testing laboratories. Shariant was designed to store and compare structured evidence, to promote and record resolution of inter-laboratory classification discrepancies, and to streamline the submission of variant assertions to ClinVar. As of December 2021, more than 14,000 largely prospectively curated variant records from 11 participating laboratories have been shared. Discrepant classifications have been identified for 11% (28/260) of variants submitted by more than one laboratory. We have demonstrated that co-design with clinical laboratories is vital to developing and implementing a national variant-interpretation sharing effort. This approach has improved inter-laboratory concordance and enabled opportunities to standardize interpretation practices.

From the patient to the population: Use of genomics for population screening

Genomic medicine is expanding from a focus on diagnosis at the patient level to prevention at the population level given the ongoing under-ascertainment of high-risk and actionable genetic conditions using current strategies, particularly hereditary breast and ovarian cancer (HBOC), Lynch Syndrome (LS) and familial hypercholesterolemia (FH). The availability of large-scale next-generation sequencing strategies and preventive options for these conditions makes it increasingly feasible to screen pre-symptomatic individuals through public health-based approaches, rather than restricting testing to high-risk groups. This raises anew, and with urgency, questions about the limits of screening as well as the moral authority and capacity to screen for genetic conditions at a population level. We aimed to answer some of these critical questions by using the WHO Wilson and Jungner criteria to guide a synthesis of current evidence on population genomic screening for HBOC, LS, and FH.

The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources

PURPOSE

Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed.

METHODS

The GenCC drafted harmonized definitions for differing levels of gene-disease validity on the basis of existing resources, and performed a modified Delphi survey with 3 rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members.

RESULTS

On the basis of 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contained 15,241 gene-disease assertions on 4569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%.

CONCLUSION

Terminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

Frequency of Parkinson’s Disease Genes and Role of PARK2 in Amyotrophic Lateral Sclerosis: An NGS Study

Amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease (AD) patients show a higher prevalence of Lewy body disease than the general population. Additionally, parkinsonian features were found in about 30% of ALS patients. We aimed to explore the frequency of Parkinson’s disease (PD)-causative genes in ALS patients, compared to AD and healthy controls (HCs). We used next-generation sequencing multigene panels by analyzing SNCA, LRRK2, PINK1, PARK2, PARK7, SYNJ1, CHCHD2, PLA2G6, GCH1, ATP13A2, DNAJC6 and FBXO genes. GBA gene, a risk factor for PD, was also analyzed. In total, 130 ALS and 100 AD patients were investigated. PD-related genes were found to be altered in 26.2% of ALS, 20% of AD patients and 19.2% of HCs. Autosomal recessive genes were significantly more involved in ALS as compared to AD and HCs (p = 0.021). PARK2 variants were more frequent in ALS than in AD and HCs, although not significantly. However, the p.Arg402Cys variant was increased in ALS than in HCs (p = 0.025). This finding is consistent with current literature, as parkin levels were found to be decreased in ALS animal models and patients. Our results confirm the possible role of PD-related genes as risk modifier in ALS pathogenesis.

Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology

During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; however, many cases remain undiagnosed after applying standard diagnostic sequencing techniques. This review discusses various methods to improve the molecular diagnostic rates in these genomic cold cases. We discuss extended analysis methods to consider, non-Mendelian inheritance models, mosaicism, dual/multiple diagnoses, periodic re-analysis, artificial intelligence tools, and deep phenotyping, in addition to integrating various omics methods to improve variant prioritization. Last, novel genomic technologies, including long-read sequencing, artificial long-read sequencing, and optical genome mapping are discussed. In conclusion, a more comprehensive molecular analysis and a timely re-analysis of unsolved cases are imperative to improve diagnostic rates. In addition, our current understanding of the human genome is still limited due to restrictions in technologies. Novel technologies are now available that improve upon some of these limitations and can capture all human genomic variation more accurately. Last, we recommend a more routine implementation of high molecular weight DNA extraction methods that is coherent with the ability to use and/or optimally benefit from these novel genomic methods.

BRCA1 Norway: comparison of classification for BRCA1 germline variants detected in families with suspected hereditary breast and ovarian cancer between different laboratories

Pathogenic germline variants in Breast cancer susceptibility gene 1 (BRCA1) predispose carriers to hereditary breast and ovarian cancer (HBOC). Through genetic testing of patients with suspected HBOC an increasing number of novel BRCA1 variants are discovered. This creates a growing need to determine the clinical significance of these variants through correct classification (class 1-5) according to established guidelines. Here we present a joint collection of all BRCA1 variants of class 2-5 detected in the four diagnostic genetic laboratories in Norway. The overall objective of the study was to generate an overview of all BRCA1 variants in Norway and unveil potential discrepancies in variant interpretation between the hospitals, serving as a quality control at the national level. For a subset of variants, we also assessed the change in classification over a ten-year period with increasing information available. In total, 463 unique BRCA1 variants were detected. Of the 126 variants found in more than one hospital, 70% were interpreted identically, while 30% were not. The differences in interpretation were mainly by one class (class 2/3 or 4/5), except for one larger discrepancy (class 3/5) which could affect the clinical management of patients. After a series of digital meetings between the participating laboratories to disclose the cause of disagreement for all conflicting variants, the discrepancy rate was reduced to 10%. This illustrates that variant interpretation needs to be updated regularly, and that data sharing and improved national inter-laboratory collaboration greatly improves the variant classification and hence increases the accuracy of cancer risk assessment.

Implementation of serological and molecular tools to inform COVID-19 patient management: protocol for the GENCOV prospective cohort study

INTRODUCTION

There is considerable variability in symptoms and severity of COVID-19 among patients infected by the SARS-CoV-2 virus. Linking host and virus genome sequence information to antibody response and biological information may identify patient or viral characteristics associated with poor and favourable outcomes. This study aims to (1) identify characteristics of the antibody response that result in maintained immune response and better outcomes, (2) determine the impact of genetic differences on infection severity and immune response, (3) determine the impact of viral lineage on antibody response and patient outcomes and (4) evaluate patient-reported outcomes of receiving host genome, antibody and viral lineage results.

METHODS AND ANALYSIS

A prospective, observational cohort study is being conducted among adult patients with COVID-19 in the Greater Toronto Area. Blood samples are collected at baseline (during infection) and 1, 6 and 12 months after diagnosis. Serial antibody titres, isotype, antigen target and viral neutralisation will be assessed. Clinical data will be collected from chart reviews and patient surveys. Host genomes and T-cell and B-cell receptors will be sequenced. Viral genomes will be sequenced to identify viral lineage. Regression models will be used to test associations between antibody response, physiological response, genetic markers and patient outcomes. Pathogenic genomic variants related to disease severity, or negative outcomes will be identified and genome wide association will be conducted. Immune repertoire diversity during infection will be correlated with severity of COVID-19 symptoms and human leucocyte antigen-type associated with SARS-CoV-2 infection. Participants can learn their genome sequencing, antibody and viral sequencing results; patient-reported outcomes of receiving this information will be assessed through surveys and qualitative interviews.

ETHICS AND DISSEMINATION

This study was approved by Clinical Trials Ontario Streamlined Ethics Review System (CTO Project ID: 3302) and the research ethics boards at participating hospitals. Study findings will be disseminated through peer-reviewed publications, conference presentations and end-users.