Quality assurance for next-generation sequencing diagnostics of rare neurological diseases in the European Reference Network.

In the past decade, next-generation sequencing (NGS) has revolutionised genetic diagnostics for rare neurological disorders (RND). However, the lack of standardised technical, interpretative, and reporting standards poses a challenge for ensuring consistent and high-quality diagnostics globally. To address this, the European Reference Network for Rare Neurological Diseases (ERN-RND) collaborated with the European Molecular Genetics Quality Network (EMQN) to establish an external quality assessment scheme for NGS-based diagnostics in RNDs. The scheme, initiated in 2021 with a pilot involving 29 labs and followed by a second round in 2022 with 42 labs, aimed to evaluate the performance of laboratories in genetic testing for RNDs. Each participating lab analysed genetic data from three hypothetical cases, assessing genotyping, interpretation, and clerical accuracy. Despite a majority of labs using exome or genome sequencing, there was considerable variability in gene content, sequencing quality, adherence to standards, and clinical guidance provision. Results showed that while most labs provided correct molecular diagnoses, there was significant variability in reporting technical quality, adherence to interpretation standards, reporting strategies, and clinical commentary. Notably, some labs returned results with the potential for adverse medical outcomes. This underscores the need for further harmonisation, guideline development, and external quality assessment in the evolving landscape of genomic diagnostics for RNDs. Overall, the experience with the scheme highlighted the generally good quality of participating labs but emphasised the imperative for ongoing improvement in data analysis, interpretation, and reporting to enhance patient safety.

EMQN best practice guidelines for genetic testing in hereditary breast and ovarian cancer.

Hereditary Breast and Ovarian Cancer (HBOC) is a genetic condition associated with increased risk of cancers. The past decade has brought about significant changes to hereditary breast and ovarian cancer (HBOC) diagnostic testing with new treatments, testing methods and strategies, and evolving information on genetic associations. These best practice guidelines have been produced to assist clinical laboratories in effectively addressing the complexities of HBOC testing, while taking into account advancements since the last guidelines were published in 2007. These guidelines summarise cancer risk data from recent studies for the most commonly tested high and moderate risk HBOC genes for laboratories to refer to as a guide. Furthermore, recommendations are provided for somatic and germline testing services with regards to clinical referral, laboratory analyses, variant interpretation, and reporting. The guidelines present recommendations where 'must' is assigned to advocate that the recommendation is essential; and 'should' is assigned to advocate that the recommendation is highly advised but may not be universally applicable. Recommendations are presented in the form of shaded italicised statements throughout the document, and in the form of a table in supplementary materials (Table S4). Finally, for the purposes of encouraging standardisation and aiding implementation of recommendations, example report wording covering the essential points to be included is provided for the most common HBOC referral and reporting scenarios. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories.

Tumor mutation burden testing: a survey of the International Quality Network for Pathology (IQN Path).

While tumour mutation burden (TMB) is emerging as a possible biomarker for immune-checkpoint inhibitors (ICI), methods for testing have not been standardised as yet. In April 2019, the International Quality Network for Pathology (IQN Path) launched a survey to assess the current practice of TMB testing. Of the 127 laboratories that replied, 69 (54.3%) had already introduced TMB analysis for research purposes and/or clinical applications. Fifty laboratories (72.5%) used targeted sequencing, although a number of different panels were employed. Most laboratories tested formalin-fixed paraffin-embedded material (94.2%), while 18/69 (26%) tested also cell-free DNA. Fifty-five laboratories used both single nucleotide variants and indels for TMB calculation; 20 centers included only non-synonymous variants. In conclusion, the data from this survey indicate that multiple global laboratories were capable of rapidly introducing routine clinical TMB testing. However, the variability of testing methods raises concerns about the reproducibility of results among centers.

ISSAID/EMQN Best Practice Guidelines for the Genetic Diagnosis of Monogenic Autoinflammatory Diseases in the Next-Generation Sequencing Era.

BACKGROUND: Monogenic autoinflammatory diseases are caused by pathogenic variants in genes that regulate innate immune responses, and are characterized by sterile systemic inflammatory episodes. Since symptoms can overlap within this rapidly expanding disease category, accurate genetic diagnosis is of the utmost importance to initiate early inflammation-targeted treatment and prevent clinically significant or life-threatening complications. Initial recommendations for the genetic diagnosis of autoinflammatory diseases were limited to a gene-by-gene diagnosis strategy based on the Sanger method, and restricted to the 4 prototypic recurrent fevers (MEFV, MVK, TNFRSF1A, and NLRP3 genes). The development of best practices guidelines integrating critical recent discoveries has become essential. METHODS: The preparatory steps included 2 online surveys and pathogenicity annotation of newly recommended genes. The current guidelines were drafted by European Molecular Genetics Quality Network members, then discussed by a panel of experts of the International Society for Systemic Autoinflammatory Diseases during a consensus meeting. RESULTS: In these guidelines, we combine the diagnostic strength of next-generation sequencing and recommendations to 4 more recently identified genes (ADA2, NOD2, PSTPIP1, and TNFAIP3), nonclassical pathogenic genetic alterations, and atypical phenotypes. We present a referral-based decision tree for test scope and method (Sanger versus next-generation sequencing) and recommend on complementary explorations for mosaicism, copy-number variants, and gene dose. A genotype table based on the 5-category variant pathogenicity classification provides the clinical significance of prototypic genotypes per gene and disease. CONCLUSIONS: These guidelines will orient and assist geneticists and health practitioners in providing up-to-date and appropriate diagnosis to their patients.

What's in a Name? A Coordinated Approach toward the Correct Use of a Uniform Nomenclature to Improve Patient Reports and Databases.

The Human Genome Variation Society (HGVS) recommendations provide standardized nomenclature for reporting variants. This should be encouraged in molecular pathology-both for issuing diagnostic reports and for correct data recording in electronic databases. Many providers of external quality assessment (EQA) promote the correct use of HGVS nomenclature by scoring variant descriptions used in EQA reports. This study focuses on the type and impact of variant nomenclature errors. An assessment was made of EGFR gene variant nomenclature by four EQA providers (European Society of Pathology [ESP], European Molecular Genetics Quality Network [EMQN], United Kingdom National External Quality Assessment Service for Molecular Genetics, and the French national Gen&Tiss EQA scheme) for two EQA distributions. Laboratories testing for oncology biomarkers make different errors when describing EGFR gene variants. Significant differences were observed regarding inclusion of the correct reference sequence: EMQN participants made fewer errors compared to ESP EQA participants (P-value = 0.015). The analysis of ESP EQA participants showed significant improvement over 2 years (P-value = 0.016). Results demonstrate the need for improvement of variant reporting according to HGVS guidelines. Consequences of using incorrect mutation nomenclature are currently perceived as low by many laboratories, but the impact will rise with an increased reliance on databases to assist in result analysis.