Norgan, Andrew P.

Abstract The raging COVID-19 pandemic in India and reports of “vaccine breakthrough infections” globally have raised alarm mandating the characterization of the immuno-evasive features of SARS-CoV-2. Here, we systematically analyzed over 1.3 million SARS-CoV-2 genomes from 178 countries and performed whole-genome viral sequencing from 53 COVID-19 patients, including 20 vaccine breakthrough infections. We identified 116 Spike protein mutations that increased in prevalence during at least one surge in SARS-CoV-2 test positivity in any country over a three-month window. Deletions in the Spike protein N-terminal domain (NTD) are highly enriched for these ‘surge-associated mutations’ (Odds Ratio = 18.2, 95% CI: 7.53-48.7; p=1.465x10-18). In the recent COVID-19 surge in India, an NTD deletion (ΔF157/R158) increased over 10-fold in prevalence from February 2021 (1.1%) to April 2021 (15%). During the recent surge in Chile, an NTD deletion (Δ246-253) increased rapidly over 30-fold in prevalence from January 2021 (0.86%) to April 2021 (33%). Strikingly, these simultaneously emerging deletions associated with surges in different parts of the world both occur at an antigenic supersite that is targeted by neutralizing antibodies. Finally, we generated clinically annotated SARS-CoV-2 whole genome sequences and identified deletions within this NTD antigenic supersite in a patient with vaccine breakthrough infection (Δ156-164) and other deletions from unvaccinated severe COVID-19 patients that could represent emerging deletion-prone regions. Overall, the expanding repertoire of Spike protein deletions throughout the pandemic and their association with case surges and vaccine breakthrough infections point to antigenic minimalism as an emerging evolutionary strategy for SARS-CoV-2 to evade immune responses. This study highlights the urgent need to sequence SARS-CoV-2 genomes at a larger scale globally and to mandate a public health policy for transparent reporting of relevant clinical annotations (e.g. vaccination status) in order to aid the development of comprehensive therapeutic strategies.

Newborn screening for congenital hypothyroidism remains challenging decades after broad implementation worldwide. Testing protocols are not uniform in terms of targets (TSH and/or T4) and protocols (parallel vs. sequential testing; one or two specimen collection times), and specificity (with or without collection of a second specimen) is overall poor. The purpose of this retrospective study is to investigate the potential impact of multivariate pattern recognition software (CLIR) to improve the post-analytical interpretation of screening results. Seven programs contributed reference data (N = 1,970,536) and two sets of true (TP, N = 1369 combined) and false (FP, N = 15,201) positive cases for validation and verification purposes, respectively. Data were adjusted for age at collection, birth weight, and location using polynomial regression models of the fifth degree to create three-dimensional regression surfaces. Customized Single Condition Tools and Dual Scatter Plots were created using CLIR to optimize the differential diagnosis between TP and FP cases in the validation set. Verification testing correctly identified 446/454 (98%) of the TP cases, and could have prevented 1931/5447 (35%) of the FP cases, with variable impact among locations (range 4% to 50%). CLIR tools either as made here or preferably standardized to the recommended uniform screening panel could improve performance of newborn screening for congenital hypothyroidism.

Context.— Small case series have evaluated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection in formalin-fixed, paraffin-embedded tissue using reverse transcription–polymerase chain reaction, immunohistochemistry (IHC), and/or RNA in situ hybridization (RNAish). Objective.— To compare droplet digital polymerase chain reaction, IHC, and RNAish to detect SARS-CoV-2 in formalin-fixed, paraffin-embedded tissue in a large series of lung specimens from coronavirus disease 2019 (COVID-19) patients. Design.— Droplet digital polymerase chain reaction and RNAish used commercially available probes; IHC used clone 1A9. Twenty-six autopsies of COVID-19 patients with formalin-fixed, paraffin-embedded tissue blocks of 62 lung specimens, 22 heart specimens, 2 brain specimens, and 1 liver, and 1 umbilical cord were included. Control cases included 9 autopsy lungs from patients with other infections/inflammation and virus-infected tissue or cell lines. Results.— Droplet digital polymerase chain reaction had the highest sensitivity for SARS-CoV-2 (96%) when compared with IHC (31%) and RNAish (36%). All 3 tests had a specificity of 100%. Agreement between droplet digital polymerase chain reaction and IHC or RNAish was fair (κ = 0.23 and κ = 0.35, respectively). Agreement between IHC and in situ hybridization was substantial (κ = 0.75). Interobserver reliability was almost perfect for IHC (κ = 0.91) and fair to moderate for RNAish (κ = 0.38–0.59). Lung tissues from patients who died earlier after onset of symptoms revealed higher copy numbers by droplet digital polymerase chain reaction (P = .03, Pearson correlation = −0.65) and were more likely to be positive by RNAish (P = .02) than lungs from patients who died later. We identified SARS-CoV-2 in hyaline membranes, in pneumocytes, and rarely in respiratory epithelium. Droplet digital polymerase chain reaction showed low copy numbers in 7 autopsy hearts from ProteoGenex Inc. All other extrapulmonary tissues were negative. Conclusions.— Droplet digital polymerase chain reaction was the most sensitive and highly specific test to identify SARS-CoV-2 in lung specimens from COVID-19 patients.

AbstractBackgroundPrimary cold agglutinin disease (CAD) is a monoclonal antibody (M‐protein) and complement‐mediated chronic hemolytic disease process. Antibody glycosylation can play a role in both antibody half‐life and complement fixation. Recently, M‐protein light chain (LC) glycosylation has been shown to be associated with AL amyloidosis. We hypothesized that M‐protein LC glycosylation is also associated with cold agglutinin (CA) titers and CA‐mediated hemolysis.Study Design and MethodsA cross‐sectional study of patients undergoing CA titer evaluation underwent mass spectrometric analysis for M‐proteins and M‐protein LC glycosylation. A subset of serum samples also underwent evaluation for the ability to trigger cold hemolysis in vitro. M‐protein and M‐protein LC glycosylation rates were compared across CA titer groups, clinical diagnosis, direct antiglobulin testing (DAT) results, and cold in vitro hemolysis rates.ResultsBoth M‐protein and M‐protein LC glycosylation rates significantly differed across CA titer groups with the highest rates in those with elevated CA titers. M‐protein LC glycosylation occurred almost exclusively on IgM kappa M‐proteins and was significantly associated with positive DAT results and a clinical diagnosis of CAD. Cold in vitro hemolysis was demonstrated in two patients who both had a CA titer of more than 512 but there was no significant association with CA titer group or M‐protein LC glycosylation status.ConclusionM‐protein LC glycosylation is significantly associated with higher CA titer levels. Given the role that antibody glycosylation can play in antibody half‐life and complement fixation, further studies are needed to clarify the effects of LC glycosylation within the context of CAD.

Abstract Objectives Error simulation models have been used to understand the relationship between analytical performance and clinical outcomes. We developed an error simulation model to understand the effects of method bias and precision on misclassification rate for neonatal hyperbilirubinemia using an age-adjusted risk assessment tool. Methods For each of 176 measured total bilirubin (TSB M ) values, 10,000 simulated total bilirubin (TB S ) values were generated at each combination of bias and precision conditions for coefficient of variation (CV) between 1 and 15%, and for biases between −51.3 μmol/L and 51.3 μmol/L (−3 and 3 mg/dL) fixed bias. TB S values were analyzed to determine if they were in the same risk zone as the TSB M value. We then calculated sensitivity and specificity for prediction of ≥75th percentile for postnatal age values as a function of assay bias and precision, and determined the rate of critical errors (≥95th percentile for age TSB M with <75th percentile TB S ). Results A sensitivity >95% for predicting ≥75th percentile bilirubin values was observed when there is a positive fixed bias of greater than 17.1 μmol/L (1.0 mg/dL) and CV is maintained ≤10%. A specificity >70% for predicting <75th percentile bilirubin values was observed when positive systematic bias was 17.1 μmol/L (1 mg/dL) or less at CV ≤ 10%. Critical errors did not occur with a frequency >0.2% until negative bias was −17.1 μmol/L (−1 mg/dL) or lower. Conclusions A positive systematic bias of 17.1 μmol/L (1 mg/dL) may be optimal for balancing sensitivity and specificity for predicting ≥75th percentile TSB values. Negative systematic bias should be avoided to allow detection of high risk infants and avoid critical classification errors.

Abstract Introduction/Objective Advances in whole slide imaging have enabled the application of machine learning algorithms to anatomic pathology. In the current state, the development of accurate algorithms requires robust training data with correctly assigned diagnostic and classification labels. Increasingly, institutions have looked to their archival slides as a source of “ground truth” for algorithm development. However, the curation and use of archival data poses several challenges. Here, we share lessons learned from reviewing head and neck pathology consult cases spanning a 10- year period at Mayo Clinic Rochester. Methods Archived surgical pathology slides from 2,590 consult cases were reviewed. Clinical and demographic information was recorded for each case, including surgical date, surgical procedure, anatomic site, age, gender and diagnosis. Cases were excluded from the curated archive if there was insufficient volume or quality of tissue to render a specific diagnosis (141 cases, 5.6%). Slides with a range of tissue size and quality, from numerable laboratories were included in the curated archive. Selected cases were collated by anatomic site: ear, gnathic, larynx, nasopharynx, neck, oral cavity, oropharynx, salivary gland and sinonasal tract. Results Common diagnostic reconciliations (115 cases, 4.4%) fell within the following categories: (1) novel entities (59 cases, 2.3%), including biphenotypic sinonasal sarcoma and clear cell carcinoma; (2) novel classifications (21 cases, 0.8%), as seen in HPV-related oropharyngeal squamous cell carcinoma and polymorphous adenocarcinoma; and (3) novel grading schema (35 cases, 1.4%), as seen in keratinizing dysplasia and oropharyngeal malignancies. Conclusion Several nuances emerged in the process of reviewing slides, highlighting the need for continual amendment of any machine learning dataset over time. Curating anatomic pathology cases for machine learning algorithm development requires the recognition of emerging entities, with re-classification and re-grading as needed.

Shotgun metagenomic sequencing can detect nucleic acids from bacteria, fungi, viruses, and/or parasites in clinical specimens; however, little data exist to guide its optimal application to clinical practice. We retrospectively reviewed results of shotgun metagenomic sequencing testing requested on cerebrospinal fluid samples submitted to an outside reference laboratory from December 2017 through December 2019. Of the 53 samples from Mayo Clinic patients, 47 were requested by neurologists, with infectious diseases consultation in 23 cases.

AbstractBackgroundPlatelet (PLT) transfusion refractoriness increases bleeding complications, hospital stays, and PLT inventory usage. Immune‐mediated refractoriness can be evaluated for using a physical PLT crossmatch with ABO‐compatible inventory and, if positive, managed with HLA‐compatible PLT inventory and donors. Manual completion of these complex tasks can be time‐consuming and potentially error‐prone. This study was conducted to determine if a Web‐based software application could improve process efficiency and accuracy.Study Design and MethodsWorkflow analysis was performed to identify process, data, and analytic requirements for a software application for three PLT transfusion‐refractoriness associated tasks: (a) physical PLT crossmatch inventory selection, (b) HLA‐compatible inventory selection, and (c) HLA‐compatible donor selection. After software application development, a comparison study was performed over 10 consecutive days, with each task performed manually and with the software application (Platelet Virtual Crossmatch [PLT VXM]) for a different unique immune‐mediated PLT transfusion–refractory recipient. Task completion time, number of incompatible units/donors presented, and number of documentation errors were compared.ResultsPLT VXM is a Web‐based software application developed using R and the Shiny Web application framework. PLT VXM significantly reduced median task completion times by 4.5 (49%), 11.2 (79%), and 59.1 minutes (94%), respectively. PLT VXM did not present any incompatible PLT units or donors for user consideration. PLT VXM also had a lower number of documentation errors than the manual process, and none of these documentation errors were software generated.ConclusionComputer‐aided evaluation and management of immune‐mediated PLT transfusion–refractory recipients can significantly improve workflow and reduce manual errors in this complex process.

Context.— Preanalytic errors, including specimen labeling errors and specimen loss, occur frequently during specimen collection, transit, and accessioning. Radio-frequency identification tags can decrease specimen identification and tracking errors through continuous and automated tracking of specimens. Objective.— To implement a specimen tracking infrastructure to reduce preanalytic errors (specimen mislabeling or loss) between specimen collection and laboratory accessioning. Specific goals were to decrease preanalytic errors by at least 70% and to simultaneously decrease employee effort dedicated to resolving preanalytic errors or investigating lost specimens. Design.— A radio-frequency identification specimen-tracking system was developed. Major features included integral radio-frequency identification labels (radio-frequency identification tags and traditional bar codes in a single printed label) printed by point-of-care printers in collection suites; dispersed radio-frequency identification readers at major transit points; and systems integration of the electronic health record, laboratory information system, and radio-frequency identification tracking system to allow for computerized physician order entry driven label generation, specimen transit time tracking, interval-based alarms, and automated accessioning. Results.— In the 6-month postimplementation period, 6 mislabeling events occurred in collection areas using the radio-frequency identification system, compared with 24 events in the 6-month preimplementation period (75% decrease; P = .001). In addition, the system led to the timely recovery of 3 lost specimens. Labeling expenses were decreased substantially in the transition from high-frequency to ultrahigh frequency radio-frequency identification tags. Conclusions.— Radio-frequency identification specimen tracking prevented several potential specimen-loss events, decreased specimen recovery time, and decreased specimen labeling errors. Increases in labeling/tracking expenses for the system were more than offset by time savings and loss avoidance through error mitigation.

Abstract Objectives Pathogenic free-living amebae (FLAs) cause skin, ocular, and central nervous system (CNS) infections with significant morbidity and mortality. Diagnosis of FLA infections by pathologic examination of tissue sections can be aided using molecular assays. This study investigated the performance characteristics of a multiplex real-time polymerase chain reaction (PCR) assay (FLA-PCR) for detection and differentiation of FLAs in clinical specimens. Methods FLA-PCR was performed on 39 human specimens comprising one cutaneous, 14 corneal, and 24 CNS formalin-fixed, paraffin-embedded (FFPE) tissues with a histopathologic diagnosis of FLA infection and four CNS FFPE tissues with inflammation but no evidence of FLAs. In addition, clinical specificity and assay limit of detection were determined. Results FLA detection sensitivities ranged from 79% to 84% in FFPE tissues. No cross-reactivity was observed. Conclusions While sensitivity is limited, FLA-PCR assay may serve as a useful adjunct for detection or confirmation of FLA infections in FFPE tissues.