Increasing SARS-CoV-2 testing capacity through specimen pooling: An acute care center experience.

Innovation in laboratory testing algorithms to address seemingly uncontrollable global supply chain shortages in plastics and other consumables during emergencies such as the current COVID-19 pandemic have been urgently needed. We report our experience with specimen pooling on SARS-CoV-2 testing in an acute care hospital microbiology laboratory during a high testing demand period that exceeded available processing capacity. A fully automated four-in-one pooling algorithm was designed and validated. Correlation and agreement were calculated. A custom Microsoft Excel tool was designed for use by the technologists to aid interpretation, verification and result entry. Cost-per-test impact for pooling was measured in reference to the consumable cost and was denoted as the percentage reduction of cost versus the baseline cost-per-test of testing specimens individually. Validation showed a strong correlation between the signals observed when testing specimens individually versus those that were pooled. Average crossing point difference was 1.352 cycles (95% confidence interval of -0.235 and 2.940). Overall agreement observed between individually and pooled tested specimens was 96.8%. Stratified agreement showed an expected decreased performance of pooling for weakly positive specimens dropping below 60% after a crossing point of 35. Post-implementation data showed the consumable cost-savings achieved through this algorithm was 85.5% after 8 months, creating both testing and resource capacity. Pooling is an effective method to be used for SARS-CoV-2 testing during the current pandemic to address resource shortages and provide quick turnaround times for high test volumes without compromising performance.

A Rational Approach to JAK2 Mutation Testing in Patients with Elevated Hemoglobin: Results from the JAK2 Prediction Cohort (JAKPOT) Study.

BACKGROUND: Erythrocytosis, most often measured as an increase in hemoglobin and/or hematocrit, is a common reason for referral to internal medicine and hematology clinics and a rational approach is required to effectively identify patients with polycythemia vera while avoiding over-investigation. AIM: We aimed to develop and validate a simple rule to predict JAK2 mutation positivity based on complete blood count parameters to aid in the diagnostic approach to patients referred for elevated hemoglobin. SETTING: Internal medicine and hematology clinics at an academic tertiary referral center. PARTICIPANTS: The JAK2 Prediction Cohort (JAKPOT), a large retrospective cohort (n = 901) of patients evaluated by internal medicine and hematology specialists for elevated hemoglobin. DESIGN: JAK2 mutation analysis was performed in all patients and clinical and laboratory variables were collected. Patients were randomly divided into derivation and validation cohorts. A prediction rule was developed using data from the derivation cohort and tested in the validation cohort. KEY RESULTS: The JAKPOT prediction rule included three variables: (i) red blood cell count >6.45×1012/L, (ii) platelets >350×109/L, and (iii) neutrophils >6.2×109/L; absence of all criteria was effective at ruling out JAK2-positivity with sensitivities 94.7% and 100%, and negative predictive values of 98.8% and 100% in the derivation and validation cohorts, respectively, with an overall low false negative rate of 0.4%. The rule was validated for three different methods of JAK2 testing. Applying this rule to our entire cohort would have resulted in over 50% fewer tests. CONCLUSION: In patients with elevated hemoglobin, the use of a simple prediction rule helps to accurately identify patients with a low likelihood of having a JAK2 mutation, potentially limiting costly over-investigation in this common referral population.

Reducing cytogenetic testing in the era of next generation sequencing: Are we choosing wisely?

INTRODUCTION: In most laboratories, next generation sequencing (NGS) has been added without consideration for redundancy compared to conventional cytogenetics (CG). We tested a streamlined approach to genomic testing in patients with suspected myeloid and plasma cell neoplasms using next generation sequencing ("NGS first") as the primary testing modality and limiting cytogenetics (CG) to samples with morphologic abnormalities in the marrow aspirate. METHODS: Based on morphologic interpretation of bone marrow aspirate and flow cytometry, samples were triaged into four groups: (a) Samples with dysplasia or excess blasts had both NGS and karyotyping; (b) Samples without excess blasts or dysplasia had NGS only; (c) Repeat samples with previous NGS and/or CG studies were not retested; (d) Samples for suspected myeloma with less than 5% plasma cell had CG testing cancelled. RESULTS: Seven hundred eleven adult bone marrow (BM) samples met the study criteria. The NGS first algorithm eliminated CG testing in 229/303 (75.6%) of patients, primarily by reducing repeat testing. Potential cost avoided was approximately $124 000 per annum. Hematologists overruled the triage comment in only 11/303 (3.6%) cases requesting CG testing for a specific indication. CONCLUSIONS: Utilizing NGS as the primary genomic testing modality NGS was feasible and well accepted, reducing over three quarters of all CG requests and improving the financial case for adoption of NGS. Key factors for the success of this study were collaboration of clinical and genomic diagnostic teams in developing the algorithm, rapid turnaround time for BM interpretation for triage, and communication between laboratories.

Analysis of Sequence and Copy Number Variants in Canadian Patient Cohort With Familial Cancer Syndromes Using a Unique Next Generation Sequencing Based Approach.

BACKGROUND: Hereditary cancer predisposition syndromes account for approximately 10% of cancer cases. Next generation sequencing (NGS) based multi-gene targeted panels is now a frontline approach to identify pathogenic mutations in cancer predisposition genes in high-risk families. Recent evolvement of NGS technologies have allowed simultaneous detection of sequence and copy number variants (CNVs) using a single platform. In this study, we have analyzed frequency and nature of sequence variants and CNVs, in a Canadian cohort of patients, suspected with hereditary cancer syndrome, referred for genetic testing following specific genetic testing guidelines based on patient's personal and/or family history of cancer. METHODS: A 2870 patients were subjected to a single NGS based multi-gene targeted hereditary cancer panel testing algorithm to identify sequence variants and CNVs in cancer predisposition genes at our reference laboratory in Southwestern Ontario. CNVs identified by NGS were confirmed by alternative techniques like Multiplex ligation-dependent probe amplification (MLPA). RESULTS: A 15% (431/2870) patients had a pathogenic variant and 36% (1032/2870) had a variant of unknown significance (VUS), in a cancer susceptibility gene. A total of 287 unique pathogenic variant were identified, out of which 23 (8%) were novel. CNVs identified by NGS based approach accounted for 9.5% (27/287) of pathogenic variants, confirmed by alternate techniques with high accuracy. CONCLUSION: This study emphasizes the utility of NGS based targeted testing approach to identify both sequence and CNVs in patients suspected with hereditary cancer syndromes in clinical setting and expands the mutational spectrum of high and moderate penetrance cancer predisposition genes.

Clinical epigenomics: genome-wide DNA methylation analysis for the diagnosis of Mendelian disorders.

PURPOSE: We describe the clinical implementation of genome-wide DNA methylation analysis in rare disorders across the EpiSign diagnostic laboratory network and the assessment of results and clinical impact in the first subjects tested. METHODS: We outline the logistics and data flow between an integrated network of clinical diagnostics laboratories in Europe, the United States, and Canada. We describe the clinical validation of EpiSign using 211 specimens and assess the test performance and diagnostic yield in the first 207 subjects tested involving two patient subgroups: the targeted cohort (subjects with previous ambiguous/inconclusive genetic findings including genetic variants of unknown clinical significance) and the screening cohort (subjects with clinical findings consistent with hereditary neurodevelopmental syndromes and no previous conclusive genetic findings). RESULTS: Among the 207 subjects tested, 57 (27.6%) were positive for a diagnostic episignature including 48/136 (35.3%) in the targeted cohort and 8/71 (11.3%) in the screening cohort, with 4/207 (1.9%) remaining inconclusive after EpiSign analysis. CONCLUSION: This study describes the implementation of diagnostic clinical genomic DNA methylation testing in patients with rare disorders. It provides strong evidence of clinical utility of EpiSign analysis, including the ability to provide conclusive findings in the majority of subjects tested.

Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders.

Genetic syndromes frequently present with overlapping clinical features and inconclusive or ambiguous genetic findings which can confound accurate diagnosis and clinical management. An expanding number of genetic syndromes have been shown to have unique genomic DNA methylation patterns (called "episignatures"). Peripheral blood episignatures can be used for diagnostic testing as well as for the interpretation of ambiguous genetic test results. We present here an approach to episignature mapping in 42 genetic syndromes, which has allowed the identification of 34 robust disease-specific episignatures. We examine emerging patterns of overlap, as well as similarities and hierarchical relationships across these episignatures, to highlight their key features as they are related to genetic heterogeneity, dosage effect, unaffected carrier status, and incomplete penetrance. We demonstrate the necessity of multiclass modeling for accurate genetic variant classification and show how disease classification using a single episignature at a time can sometimes lead to classification errors in closely related episignatures. We demonstrate the utility of this tool in resolving ambiguous clinical cases and identification of previously undiagnosed cases through mass screening of a large cohort of subjects with developmental delays and congenital anomalies. This study more than doubles the number of published syndromes with DNA methylation episignatures and, most significantly, opens new avenues for accurate diagnosis and clinical assessment in individuals affected by these disorders.