APOE ε4 Allele Frequency Among Cognitively Healthy Members of an Ojibwe Tribal Nation.

Objectives: APOE ε4 frequency varies by geography and ancestry. We provide data regarding the frequency of this allele in the Ojibwe people, the fifth largest Indigenous people in the United States. Methods: Population study including 33 cognitively normal older individuals of an Ojibwe Tribal Nation (total population: 984; all with ≥25% Ojibwe ancestry). Results: APOE ε4 allele frequency was 19.7%, which is comparable with other cognitively normal American Indian, Alaskan Native, and non-Hispanic White populations of the United States and Europe, with the exception of a lower frequency among Choctaw Nation of Oklahoma participants with >50% American Indian ancestry. Discussion: While some global populations have very low APOE ε4 prevalence, this allele appears common among American Indian Tribal Nations included thus far in the United States. Because APOE ε4 is a cornerstone for novel diagnostics and therapeutics for Alzheimer disease (AD), future study is warranted to understand ancestry-dependent effects of APOE ε4 on AD risk and biology.

Saliva Testing Is Accurate for Early-Stage and Presymptomatic COVID-19.

Although nasopharyngeal samples have been considered the gold standard for COVID-19 testing, variability in viral load across different anatomical sites could cause nasopharyngeal samples to be less sensitive than saliva or nasal samples in certain cases. Self-collected samples have logistical advantages over nasopharyngeal samples, making them amenable to population-scale screening. To evaluate sampling alternatives for population screening, we collected nasopharyngeal, saliva, and nasal samples from two cohorts with varied levels and types of symptoms. In a mixed cohort of 60 symptomatic and asymptomatic participants, we found that saliva had 88% concordance with nasopharyngeal samples when tested in the same testing lab (n = 41) and 68% concordance when tested in different testing labs (n = 19). In a second cohort of 20 participants hospitalized for COVID-19, saliva had 74% concordance with nasopharyngeal samples tested in the same testing lab but detected virus in two participants that tested negative with nasopharyngeal samples on the same day. Medical record review showed that the saliva-based testing sensitivity was related to the timing of symptom onset and disease stage. We find that no sample site will be perfectly sensitive for COVID-19 testing in all situations, and the significance of negative results will always need to be determined in the context of clinical signs and symptoms. Saliva retained high clinical sensitivity for early-stage and presymptomatic COVID-19 while allowing easier collection, minimizing the exposure of health care workers, and need for personal protective equipment and making it a viable option for population-scale testing. IMPORTANCE Methods for COVID-19 detection are necessary for public health efforts to monitor the spread of disease. Nasopharyngeal samples have been considered the best approach for COVID-19 testing. However, alternative samples like self-collected saliva offer advantages for population-scale screening. Meta-analyses of recent studies suggest that saliva is useful for detecting SARS-CoV-2; however, differences in disease prevalence, sample collection, and analysis methods still confound strong conclusions on the utility of saliva compared to nasopharyngeal samples. Here, we find that the sensitivity of saliva testing is related to both the timing of the sample collection relative to symptom onset and the disease stage. Importantly, several clinical vignettes in our cohorts highlight the challenges of medical decision making with limited knowledge of the associations between laboratory test data and the natural biology of infection.

Prediction of False-Positive Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Molecular Results in a High-Throughput Open-Platform System.

Widespread high-throughput testing for identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by RT-PCR has been a foundation in the response to the coronavirus disease 2019 (COVID-19) pandemic. Quality assurance metrics for these RT-PCR tests are still evolving as testing is widely implemented. As testing increases, it is important to understand performance characteristics and the errors associated with these tests. Herein, we investigate a high-throughput, laboratory-developed SARS-CoV-2 RT-PCR assay to determine whether modeling can generate quality control metrics that identify false-positive (FP) results due to contamination. This study reviewed repeated clinical samples focusing on positive samples that test negative on re-extraction and PCR, likely representing false positives. To identify and predict false-positive samples, we constructed machine learning-derived models based on the extraction method used. These models identified variables associated with false-positive results across all methods, with sensitivities for predicting FP results ranging between 67% and 100%. Application of the models to all results predicted a total FP rate of 0.08% across all samples, or 2.3% of positive results, similar to reports for other RT-PCR tests for RNA viruses. These models can predict quality control parameters, enabling laboratories to generate decision trees that reduce interpretation errors, allow for automated reflex testing of samples with a high FP probability, improve workflow efficiency, and increase diagnostic accuracy for patient care.

Single-Cell Gene Expression Analyses Reveal Distinct Self-Renewing and Proliferating Subsets in the Leukemia Stem Cell Compartment in Acute Myeloid Leukemia.

Standard chemotherapy for acute myeloid leukemia (AML) targets proliferative cells and efficiently induces complete remission; however, many patients relapse and die of their disease. Relapse is caused by leukemia stem cells (LSC), the cells with self-renewal capacity. Self-renewal and proliferation are separate functions in normal hematopoietic stem cells (HSC) in steady-state conditions. If these functions are also separate functions in LSCs, then antiproliferative therapies may fail to target self-renewal, allowing for relapse. We investigated whether proliferation and self-renewal are separate functions in LSCs as they often are in HSCs. Distinct transcriptional profiles within LSCs of Mll-AF9/NRASG12V murine AML were identified using single-cell RNA sequencing. Single-cell qPCR revealed that these genes were also differentially expressed in primary human LSCs and normal human HSPCs. A smaller subset of these genes was upregulated in LSCs relative to HSPCs; this subset of genes constitutes "LSC-specific" genes in human AML. To assess the differences between these profiles, we identified cell surface markers, CD69 and CD36, whose genes were differentially expressed between these profiles. In vivo mouse reconstitution assays resealed that only CD69High LSCs were capable of self-renewal and were poorly proliferative. In contrast, CD36High LSCs were unable to transplant leukemia but were highly proliferative. These data demonstrate that the transcriptional foundations of self-renewal and proliferation are distinct in LSCs as they often are in normal stem cells and suggest that therapeutic strategies that target self-renewal, in addition to proliferation, are critical to prevent relapse and improve survival in AML. SIGNIFICANCE: These findings define and functionally validate a self-renewal gene profile of leukemia stem cells at the single-cell level and demonstrate that self-renewal and proliferation are distinct in AML. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/3/458/F1.large.jpg.

Next generation sequencing for clinical diagnostics: Five year experience of an academic laboratory.

Clinical laboratories have adopted next generation sequencing (NGS) as a gold standard for the diagnosis of hereditary disorders because of its analytic accuracy, high throughput, and potential for cost-effectiveness. We describe the implementation of a single broad-based NGS sequencing assay to meet the genetic testing needs at the University of Minnesota. A single hybrid capture library preparation was used for each test ordered, data was informatically blinded to clinically-ordered genes, and identified variants were reviewed and classified by genetic counselors and molecular pathologists. We performed 2509 sequencing tests from August 2012 till December 2017. The diagnostic yield has remained steady at 25%, but the number of variants of uncertain significance (VUS) included in a patient report decreased over time with 50% of the patient reports including at least one VUS in 2012 and only 22% of the patient reports reporting a VUS in 2017 (p = .002). Among the various clinical specialties, the diagnostic yield was highest in dermatology (60% diagnostic yield) and ophthalmology (42% diagnostic yield) while the diagnostic yield was lowest in gastrointestinal diseases and pulmonary diseases (10% detection yield in both specialties). Deletion/duplication analysis was also implemented in a subset of panels ordered, with 9% of samples having a diagnostic finding using the deletion/duplication analysis. We have demonstrated the feasibility of this broad-based NGS platform to meet the needs of our academic institution by aggregating a sufficient sample volume from many individually rare tests and providing a flexible ordering for custom, patient-specific panels.

Diagnosis of epidermodysplasia verruciformis: Two cases highlighting the role of direct HPV L1 gene sequencing.

Epidermodysplasia verruciformis (EV) is a rare skin disease characterized by the development of multiple flat warts with the potential for malignant transformation. Patients are susceptible to human papillomavirus (HPV) infection that develops in a background of either a genetic or acquired immunodeficiency predisposing patients to infection with specific HPV types that are ubiquitous but generally non-pathogenic in healthy individuals. There is no standard clinical methodology for determining the causative HPV from patients with suspected EV. Here, we report the diagnostic workup of two EV cases and describe the use of L1 gene Sanger sequencing as a specific method to accurately identify the causative HPV genotype and confirm the diagnosis of EV.

Optimization of a microfluidics-based next generation sequencing assay for clinical oncology diagnostics.

BACKGROUND: Massively parallel, or next-generation, sequencing is a powerful technique for the assessment of somatic genomic alterations in cancer samples. Numerous gene targets can be interrogated simultaneously with a high degree of sensitivity. The clinical standard of care for many advanced solid and hematologic malignancies currently requires mutation analysis of several genes in the front-line setting, making focused next generation sequencing (NGS) assays an effective tool for clinical molecular diagnostic laboratories. METHODS: We have utilized an integrated microfluidics circuit (IFC) technology for multiplex PCR-based library preparation coupled with a bioinformatic method designed to enhance indel detection. A parallel low input PCR-based library preparation method was developed for challenging specimens with low DNA yield. Computational data filters were written to optimize analytic sensitivity and specificity for clinically relevant variants. RESULTS: Minimum sequencing coverage and precision of variant calls were the two primary criteria used to establish minimum DNA mass input onto the IFC. Wet-bench and bioinformatics protocols were modified based on data from the optimization and familiarization process to improve assay performance. The NGS platform was then clinically validated for single nucleotide and indel (up to 93 base pair) variant detection with overall analytic accuracy of 98% (97% sensitivity; 100% specificity) using as little as 3 ng of formalin-fixed, paraffin-embedded DNA or 0.3 ng of unfixed DNA. CONCLUSIONS: We created a targeted clinical NGS assay for common solid and hematologic cancers with high sensitivity, high specificity, and the flexibility to test very limited tissue samples often encountered in routine clinical practice.

Buccal epithelial cells display somatic, bone marrow-derived CALR mutation.

Buccal epithelial cells harbor an MPN-associated CALR mutation in a patient with CALR-mutant essential thrombocytosis, Ph+ CML, and no germ line CALR mutation.

Complete and sustained response of adult medulloblastoma to first-line sonic hedgehog inhibition with vismodegib.

Medulloblastoma is an aggressive primitive neuroectodermal tumor of the cerebellum that is rare in adults. Medulloblastomas fall into 4 prognostically significant molecular subgroups that are best defined by experimental gene expression profiles: the WNT pathway, sonic hedgehog (SHH) pathway, and subgroups 3 and 4 (non-SHH/WNT). Medulloblastoma of adults belong primarily to the SHH category. Vismodegib, an SHH-pathway inhibitor FDA-approved in 2012 for treatment of basal cell carcinoma, has been used successfully in the setting of chemorefractory medulloblastoma, but not as a first-line therapy. In this report, we describe a sustained response of an unresectable multifocal form of adult medulloblastoma to vismodegib. Molecular analysis in this case revealed mutations in TP53 and a cytogenetic abnormality, i17q, that is prevalent and most often associated with subgroup 4 rather than the SHH-activated form of medulloblastoma. Our findings indicate that vismodegib may also block alternate, non-canonical forms of downstream SHH pathway activation. These findings provide strong impetus for further investigation of vismodegib in clinical trials in the first-line setting for pediatric and adult forms of medulloblastoma.

CNV-RF Is a Random Forest-Based Copy Number Variation Detection Method Using Next-Generation Sequencing.

Simultaneous detection of small copy number variations (CNVs) (<0.5 kb) and single-nucleotide variants in clinically significant genes is of great interest for clinical laboratories. The analytical variability in next-generation sequencing (NGS) and artifacts in coverage data because of issues with mappability along with lack of robust bioinformatics tools for CNV detection have limited the utility of targeted NGS data to identify CNVs. We describe the development and implementation of a bioinformatics algorithm, copy number variation-random forest (CNV-RF), that incorporates a machine learning component to identify CNVs from targeted NGS data. Using CNV-RF, we identified 12 of 13 deletions in samples with known CNVs, two cases with duplications, and identified novel deletions in 22 additional cases. Furthermore, no CNVs were identified among 60 genes in 14 cases with normal copy number and no CNVs were identified in another 104 patients with clinical suspicion of CNVs. All positive deletions and duplications were confirmed using a quantitative PCR method. CNV-RF also detected heterozygous deletions and duplications with a specificity of 50% across 4813 genes. The ability of CNV-RF to detect clinically relevant CNVs with a high degree of sensitivity along with confirmation using a low-cost quantitative PCR method provides a framework for providing comprehensive NGS-based CNV/single-nucleotide variant detection in a clinical molecular diagnostics laboratory.

Clinical validation of targeted next-generation sequencing for inherited disorders.

CONTEXT: Although next-generation sequencing (NGS) can revolutionize molecular diagnostics, several hurdles remain in the implementation of this technology in clinical laboratories. OBJECTIVES: To validate and implement an NGS panel for genetic diagnosis of more than 100 inherited diseases, such as neurologic conditions, congenital hearing loss and eye disorders, developmental disorders, nonmalignant diseases treated by hematopoietic cell transplantation, familial cancers, connective tissue disorders, metabolic disorders, disorders of sexual development, and cardiac disorders. The diagnostic gene panels ranged from 1 to 54 genes with most of panels containing 10 genes or fewer. DESIGN: We used a liquid hybridization-based, target-enrichment strategy to enrich 10 067 exons in 568 genes, followed by NGS with a HiSeq 2000 sequencing system (Illumina, San Diego, California). RESULTS: We successfully sequenced 97.6% (9825 of 10 067) of the targeted exons to obtain a minimum coverage of 20× at all bases. We demonstrated 100% concordance in detecting 19 pathogenic single-nucleotide variations and 11 pathogenic insertion-deletion mutations ranging in size from 1 to 18 base pairs across 18 samples that were previously characterized by Sanger sequencing. Using 4 pairs of blinded, duplicate samples, we demonstrated a high degree of concordance (>99%) among the blinded, duplicate pairs. CONCLUSIONS: We have successfully demonstrated the feasibility of using the NGS platform to multiplex genetic tests for several rare diseases and the use of cloud computing for bioinformatics analysis as a relatively low-cost solution for implementing NGS in clinical laboratories.

Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory.

BACKGROUND: The introduction of next generation sequencing (NGS) has revolutionized molecular diagnostics, though several challenges remain limiting the widespread adoption of NGS testing into clinical practice. One such difficulty includes the development of a robust bioinformatics pipeline that can handle the volume of data generated by high-throughput sequencing in a cost-effective manner. Analysis of sequencing data typically requires a substantial level of computing power that is often cost-prohibitive to most clinical diagnostics laboratories. FINDINGS: To address this challenge, our institution has developed a Galaxy-based data analysis pipeline which relies on a web-based, cloud-computing infrastructure to process NGS data and identify genetic variants. It provides additional flexibility, needed to control storage costs, resulting in a pipeline that is cost-effective on a per-sample basis. It does not require the usage of EBS disk to run a sample. CONCLUSIONS: We demonstrate the validation and feasibility of implementing this bioinformatics pipeline in a molecular diagnostics laboratory. Four samples were analyzed in duplicate pairs and showed 100% concordance in mutations identified. This pipeline is currently being used in the clinic and all identified pathogenic variants confirmed using Sanger sequencing further validating the software.