Pitfalls of Artificial Intelligence for COVID-19 Variant Classification

While you have surely heard about all of the SARS-CoV-2 variants and how concerning they are, I would bet that you may not know how they are classified. Sure, from my last post, the technical aspects of whole genome sequencing and targeted approaches have been described, but bioinformatic (big data) analyses are essential to assign lineages. Furthermore, the advances of machine learning have been integrated into this system for SARS-CoV-2 lineage assignment.

How VOC lineages are given

First, phylogenetic trees (circular example below) are formed to demonstrate relatedness of strains based on how many mutations they share. The more similar they are, the closer they are together. These trees are not new nor do they rely on artificial intelligence, but they can give visual clues as to whether a lineage is new.  For instance, when the first variant of concern B.1.1.7 (now called Alpha) was discovered, it branched away from other limbs of the phylogenetic tree.

Within these new viral variants, there are a set of mutations that are present in most of the viral variants. For instance, there are 17 protein coding changes in Alpha variant. However, these exact 17 mutations may not be in every Alpha variant. Individually, mutations may be present in 98% of isolates or lower; the spike gene deletion of amino acids 242-244 of the Beta variant (B.1.351, South Africa origin) is only present in 88% of specimens sequenced. This could be due to issues in sequencing, data processing, or just the prevalance/biology of the virus.

As there are many mutations that fit into certain variants, it would be difficult for a human to process all of this information in a probabilistic manner to assign lineages. Thus, machine learning tools (most common SARS-CoV-2 program is Pangolin) have been added onto the end of bioinformatic analyses to assign the lineage to a sample.

How machine learning works

The subject of machine learning has been discussed in a previous post about Protein folding prediction. Briefly, it is helpful to remember that machine learning is a process to create algorithms that give an outcome based on training data. The more diverse, large, and well curated the data, the better the accuracy of the program. One pitfall is they are based on previous data, which works well for many situations: using AI to find a lung cancer on chest x-ray would work well, because lung cancers have consistent characteristics.

However, with COVID-19, new variants keep arising and current variants are evolving (think Delta and Delta “plus”). Furthermore, if the classifier Pangolin is trained on high quality data, then trying to interpret lower quality data (missing genome regions, few sequencing reads) may confuse Pangolin and lead to inaccurate results. What follows is an example of how this occurred at our institution.

Case study

We have been sequencing COVID-19 positive specimens at UT Southwestern for the last several months. Many of the cases have been the Alpha variant (B.1.1.7, origin U.K.). However, it was around this time that Delta (B.1.617.2, origin India) cases started to arise. In one week, we found two specimens that were classified as B.1.95. This was an unusual variant I had not heard of before. There are several “wild type” strains that are B.1.1/ B.1.2 and other derivations, but I had not seen anything like this before.

Clinical history

Two specimens sequenced belonging to Hispanic, adolescent brothers whose mother had recently been hospitalized with COVID-19. There was information on mother’s travel history.

Therefore, I performed manual review of the specific variants. Many of the diverse mutations occur in the spike protein, so this was analyzed first. Immediately, I noticed two classic mutations of the Delta variant: a 2 amino acid deletion in the spike gene (S:Del157_158) and a receptor binding site mutation (S:L452R) also seen in the variant from California (B.1.429). Other mutations could be evaluated, but the combination of these two mutations is unique to Delta variant.

One suspected cause was that the Pangolin lineage classifier had an issue. Specifically, it had not been updated since February 2021- when Delta did not exist. Thus, there was no data for the program to classify the variant properly. Upgrading to the latest version of Pangolin provided the correct lineage classification.

A Few weeks later…

Once again, I was checking the lineages reported by the classifier and there were several B.1.617.2 and B.1.617.1. Both of these are variants from India (before the helpful WHO Delta designation), but they are distinct sub-variants. It was odd to see B.1.617.1, because this was found to be less infectious compared to the dominant B.1.617.2 variant (later named Delta) and B.1.617.1 was not spreading across the globe.

Intervention:

Therefore, I once again went to the sequence data for the spike protein to compare some mutations. Although these are sub-variants from the same original variant, they have several mutually exclusive mutations in the spike protein. The figure below compares the prevalence of specific mutations in the spike protein of B.1.617.1 and B.1.617.2 (dark purple = common in a variant, white = rare).

Upon manual review, all of the spike gene mutations were specific to B.1.617.2. So why was there an issue in classification? Again, there were few sequences for either of these sub-variants at that time, so the classifier wasn’t as well trained. Updating the Pangolin version brought the benefit of new data and more accurate classifications.

Take away messages

  1. Updating Lineage classification software (Pangolin) on a regular basis is needed for accurate results.
  2. Manual review is essential for any abnormal findings- a typical process for pathologists, but also plays an important role in COVID-19 variant monitoring.
  3. Know what you’re looking for and know which mutations differentiate the variants.
  4. Delta is now the dominant strain in the U.S. (graphic below).

References

  1. Outbreak.info
  2. https://pangolin.cog-uk.io/

Jeff SoRelle, MD is Assistant Instructor of Pathology at the University of Texas Southwestern Medical Center in Dallas, TX working in the Next Generation Sequencing lab. His clinical research interests include understanding how lab medicine impacts transgender healthcare and improving genetic variant interpretation. Follow him on Twitter @Jeff_SoRelle.

How to Detect COVID-19 Variants of Concern

It’s a little deja-vu writing this title one year after a similar blog post on how to validate a COVID-19 assay at the start of the pandemic. In many ways, the challenges are similar: limited reagents/control material, and rising case counts. At least now, there is increasing support in the way of funding from the federal government that could help with monitoring and surveillance. I’m going to summarize the current methods available for detecting the Variants of Concern and emerging variants.

Whole Genome Sequencing

The principle method used by many is whole genome sequencing. It has the advantage of being able to comprehensively examine every letter (nucleotide) of the SARS-CoV-2 genome (30 kilobases long). At our institution, I’ve been working on the effort to sequence all of our positive specimens. While it is achievable, it is not simple nor feasible at most locations. Limitations include:

  • Financial: must already own expensive sequencers
  • Expertise: advanced molecular diagnostics personnel needed who perform NGS testing
  • Data Analytics: bioinformatics personnel needed to create pipelines, analyze data and report it in a digestible format.
  • Timing: the process usually takes a week at best and several weeks if there is a backlog or not enough samples for a sequencing run to be financially viable.
  • Sensitivity: the limit of detection for NGS is 30 CT cycles, which for us includes only about 1/2- 1/3 of all positive COVID19 specimens.

 Bottom line: WGS is the best at detecting new/ emerging strains or mutations when cost/ time is not a concern.

Mutation Screening

Other institutions have begun efforts to screen for variants of concern by detecting characteristic mutations. For instance, the N501Y mutation in the spike protein is common to the major Variants of Concern (UK B.1.1.7, Brazil P.1, and S Africa B.1.351) and E484K is present in the Brazil (P.1), S Africa (B.1.351) and New York Variant (B.1.526). Thus, several institutions (listed below) took approaches to 1) screen for these mutations and then 2) perform WGS sequentially.

InstitutionMethodTargets
Hackensack Meridian Health (HMH)Molecular Beacon Probes, melting tempN501Y, E484K molecular beacons
Rutgers, New JerseyMolecular Beacon Probes, melting tempN501Y molecular beacons
VancouverProbe + melting curve (VirSNiP SARS-CoV-2 Mutation Assays)N501Y screen + qPCR reflex; Probe, melt curve assay
YaleRT-qPCR probe assayS:144del, ORF1Adel
ColumbiaRT-qPCR probe-assayN501Y, E484K

As you can see, HMH, Rutgers and Vancouver are using assays that use probes specific to characteristic alleles combined with melting temperature curves to detect a mutation induced change. Melting curve analysis is normally performed after qPCR to ensure that a single, correct PCR product is formed. This measure is calculated based on the change in fluorescence that occurs when the fluorescent marker is able to bind to its target DNA. Thus the Tm (melting temperature) is similar to the annealing temperature. In this case where a mutation is present in the probe (DNA fragment) binding site, binding is disrupted and occurs at lower a temperature as seen by the downward shift of 5 degrees Celsius in the graph below.

Figure 1. Schematic showing the melting temperature shift for the HMH designed probe binding normal and mutant (E484K variant) sequences at decreasing concentrations.
Figure 2. Similar shift downward in melting temperature for the Rutgers assay when a wild type probe encounters a mutant vs. WT sequence.

These approaches are quick, but can only perform a 2-3 reactions per well and require much of the same expenses as diagnostic RT-qPCR assays. Most of the studies describe this method as a way of screening for samples to be NGS sequenced, however they will not be as good at detecting emerging strains. For example, the N501Y mutation is not present in the New York nor California variants.

Multiplex RT-qPCR can solve some of these problems. At Columbia and Yale, multiple targets are designed to detect B.1.1.7 (N501Y only at Columbia and S144del + ORF1A del at Yale) vs. Brazil/ S. Africa variants (N501Y & E484K at Columbia and ORF1A only at Yale). As new variants have arrived, we found the New York strain carrying both ORF1A deletion and the E484K mutation. It is now clear there are some hotspot areas for mutation within the SARS-CoV-2 genome, which can complicate interpretations. Therefore, these RT-PCR assays are still useful for screening, but do not replace the need for Whole Genome Sequencing.

Genotyping

Given the overlapping spectrum of mutations, it would be helpful to test several markers all at once in a single reaction. At a certain point, this would effectively “genotype” a variant as well as WGS. The assays above have been limited to 2 targets/ reaction due to limited light detection channels. Therefore, I’ve created a multiplex assay that can be scaled up to include 30-40 targets within a single reaction without the need for expensive probes. This method is multiplex PCR fragment analysis, which is traditionally used for forensic fingerprinting or bone marrow transplant tracking. In this method, DNA of different length is amplified by PCR, then separated by capillary electrophoresis-the same instrument that performs Sanger Sequencing.

Fragment analysis can be performed to detect deletion/ insertion mutations and single nucleotide polymorphisms (SNPs) by allele-specific primers or with restriction enzymes that only cut the WT or Mutant sequence.

I designed the assay to target 3 deletion mutations in B.1.1.7: S:D69_70, S: D144, and ORF1A: D3675_3677. Each deletion has a specific length and if 3/3 mutations are present, then there is 95% specificity for the B.1.1.7 strain. Samples from December to present were tested and in the first batch, I detected the characteristic B.1.1.7 pattern (expected pattern and observed pattern below).

Theoretical picture of what the fragment analysis assay would look like for B.1.1.7. An actual patient sample results below, which showed the expected deletions exactly as predicted:

We have tested and sequenced over 500 positive specimens, and we found increasing levels of the B.1.1.7 strain prevalence up to nearly 30% by the middle of March. All screened B.1.1.7 specimens were validated by WGS. These results and the ability to detect the New York and California variants are detailed in our recent pre-print.

Weekly prevalence of isolates consistent with B.1.1.7 in North Texas.

Implications for future Variant Surveillance

As B.1.1.7 has become the dominant strain, and sequencing efforts are increasing. I would argue that assays should be used for what they are best at. For instance, it could be considered a waste of NGS time and resources to sequence all Variants when >50% are going to be B.1.1.7 if other tests can verify the strain faster for 10-20% of the cost. Instead, I think WGS should be focused on discovering emerging variants for which it is best suited. Across the US, case numbers have been decreasing and the number of specimens testable could be expanded by using a more sensitive PCR assay that could.

References

  1. Clark AE et al. Multiplex Fragment Analysis Identifies SARS-CoV-2 Variants. https://www.medrxiv.org/content/10.1101/2021.04.15.21253747v1
  2. Zhao Y et al. A Novel Diagnostic Test to Screen SARS-CoV-2 Variants Containing E484K and N501Y Mutations. A Novel Diagnostic Test to Screen SARS-CoV-2 Variants Containing E484K and N501Y Mutations | medRxiv
  3. Banada P et al. A Simple RT-PCR Melting temperature Assay to Rapidly Screen for Widely Circulating SARS-CoV-2 Variants. A Simple RT-PCR Melting temperature Assay to Rapidly Screen for Widely Circulating SARS-CoV-2 Variants | medRxiv
  4. Annavajhala MK et al. A Novel SARS-CoV-2 Variant of Concern, B.1.526, Identified in New York. A Novel SARS-CoV-2 Variant of Concern, B.1.526, Identified in New York | medRxiv
  5. Matic N et al. Rapid detection of SARS-CoV-2 variants of concern identifying a cluster of B.1.1.28/P.1 variant in British Columbia, Canada. Rapid detection of SARS-CoV-2 variants of concern identifying a cluster of B.1.1.28/P.1 variant in British Columbia, Canada | medRxiv
  6. Vogels CBF et al. PCR assay to enhance global surveillance for SARS-CoV-2 variants of concern. PCR assay to enhance global surveillance for SARS-CoV-2 variants of concern | medRxiv

Jeff SoRelle, MD is Assistant Instructor of Pathology at the University of Texas Southwestern Medical Center in Dallas, TX working in the Next Generation Sequencing lab. His clinical research interests include understanding how lab medicine impacts transgender healthcare and improving genetic variant interpretation. Follow him on Twitter @Jeff_SoRelle.

COVID Variants

Since my last post on the B.1.1.7 (UK) variant, several other variants have arisen. I wanted to describe what makes some Variants of Interest and other Variants of Concern. While a “variant” is often synonymous with a mutation in genetic terms, in the context of SARS-CoV-2, variant means an alternative strain of the virus.

To become a Variant of Interest (VOI), the World Health Organization (WHO) or Centers for Disease Control (CDC) has the following characteristics:

  • Evidence of variants that affect transmission, resistance to vaccines/ therapeutics, mortality, or diagnostic tests
  • Evidence that the variants is contributing to a rise in the proportion of cases in an area.
  • However, limited geographical spread.

Examples: P.2 (from Brazil) B.1.525 (New York), and B.1.526 (New York).

Variants of Concern have increased problems with the same characteristics listed above:

  • Evidence of reduced vaccine protection from severe disease
  • Evidence of substantially reduced response to neutralizing antibodies or therapeutics
  • Evidence of widespread spread
  • Increased Transmissibility or disease severity

Current VOCs: B.1.1.7 (UK), B.1.351 (South Africa), P.1 (Brazil), and B.1.427/ B.1.429 (California).

The initial VOC of B.1.1.7, B.1.351 and P.1 were identified from having increased spread and more mutations than expected, especially in the Spike gene region (Figure 1).

The N501Y mutation in the Spike protein is present in each VOC. It is located at the tip of the protein that binds the ACE2 receptor, increasing binding strength.

So far, vaccines react against the B.1.1.7 variant. However, B.1.351 pseudovirus shows decreased neutralization by both Moderna and Pfizer sera. Specifically, the E484K mutation in the Spike protein confers resistance to neutralizing antibodies. Thus, the strains B.1.351 and P.1 are more likely to be resistant as would any other strain with the E484K variant.

Lastly, the California variant arose as it was found to rise in prevalence from November to February. The key mutations include W152C and L452R, but the significance of this variant is uncertain. However, this variant has begun to spread over much of Southern California and Nevada.

References

  1. Wu K, Werner AP, Moliva JI, Koch M, Choi A, Stewart-Jones GBE, Bennett H, Boyoglu-Barnum S, Shi W, Graham BS, Carfi A, Corbett KS, Seder RA, Edwards DK. mRNA-1273 vaccine induces neutralizing antibodies against spike mutants from global SARS-CoV-2 variants. bioRxiv [Preprint]. 2021 Jan 25:2021.01.25.427948. doi: 10.1101/2021.01.25.427948. PMID: 33501442; PMCID: PMC7836112.
  2. Tada T, Dcosta BM, Samanovic-Golden M, et al. Neutralization of viruses with European, South African, and United States SARS-CoV-2 variant spike proteins by convalescent sera and BNT162b2 mRNA vaccine-elicited antibodies. Preprint. bioRxiv. 2021;2021.02.05.430003. Published 2021 Feb 7. doi:10.1101/2021.02.05.430003
  3. Gangavarapu, Karthik; Alkuzweny, Manar; Cano, Marco; Haag, Emily; Latif, Alaa Abdel; Mullen, Julia L.; Rush, Benjamin; Tsueng, Ginger; Zhou, Jerry; Andersen, Kristian G.; Wu, Chunlei; Su, Andrew I.; Hughes, Laura D. outbreak.info. Available online: https://outbreak.info/ (2020)
  4. https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/variant-surveillance/variant-info.html

Jeff SoRelle, MD is Assistant Instructor of Pathology at the University of Texas Southwestern Medical Center in Dallas, TX working in the Next Generation Sequencing lab. His clinical research interests include understanding how lab medicine impacts transgender healthcare and improving genetic variant interpretation. Follow him on Twitter @Jeff_SoRelle.

Critical Values: The Burden, Promise and Realization of Virtual Interviews for Pathology Residency During a Pandemic

The SARS-CoV-2 virus continues to cause increased infections and deaths around the world with considerable impact on clinical and laboratory medicine communities. Meanwhile, medical students and the medical community are also undertaking the yearly tribulation of residency interview season. Following the May announcement by the Coalition for Physician Accountability’s Work Group on Medical Students,1 the 2020 interview season will be entirely conducted utilizing virtual interviews. In pointed response to this change in format, residency programs rapidly scrambled to bolster websites, increase their social media presence, add virtual tours and prepare for the virtual interview format prior to the start of interview season. Now, at the midpoint of interview season, it is evident that some burdens of traditional on-site interviews are indeed being alleviated. Whether or not online resident socials and virtual tours can sufficiently substitute for all aspects of on-site visits and if the promise of increased spread of geographic and cultural diversity can be realized remains to be accurately assessed. The survival of the virtual format may even depend on this assessment.

The average cost of traditional on-site pathology interviews has continued to increase for medical students from a per person average of $3400 in 2015 to $4000 in 2020.2 Much of this expense comes from travel/transportation while some pathology programs provided accommodations. Additionally, interview season required about 20 total days away from medical school. To cover these expenses, about half (49%) of medical students borrow money for interviews . Not surprisingly, the majority of them agree that travel (79%) and lodging (65%) are overly burdensome components of interview season.2 Beyond accounting, the salient impact of these time and financial investments is that they were influencing the majority (58%) of interview decisions.

While the rising time and financial burdens of traditional on-site residency interviews were well-known and there was and continues to be a myriad of ideas3 on how to best address these concerns and the match overall, a small burgeoning literature on virtual resident interviews was available prior to the pandemic that showed promise for addressing these concerns.4,5 That is, in the 2020 – 2021 residency interview season, medical students are estimated to spend about 3.5 hours on an average virtual interview day instead of the 8 hour day of a traditional interview and through the elimination of travel time they may spend 7 less days on the interview trail. Thus, the cost of interviewing is also projected to be skeletonized to that of necessary professional clothing and computer hardware. Additional promising data from this small body of research suggests that 85% of virtual interviewees were satisfied with their understanding of the program and their ability to present themselves to residency programs.6 Furthermore, the fact that the residency program’s rank list showed no significant impact based on whether candidates interviewed virtually or in-person suggests that residency programs may feel capable of fairly assessing candidates.7

Beyond time and financial savings for pathology residency applicants and the assessment of candidates by residency programs and vice versa, the measurability of additional outcomes may be critical to the continuation of virtual resident interviews. In particular, there is great interest in online social events and interview day resident panels as a sufficient substitute for the naturally evolving casual conversations that occur during the dinners, lunches and tours available with on-site visits. Also, whether or not these socials combined with interviews with a small subset of faculty can accurately portray a pathology residency program’s culture. In prior surveys that compared in-person, virtual or a combined approach to interviews, candidates always favored in-person assessment when given the choice. The present circumstance will perhaps be the best attempt at an unbiased assessment of the perception of culture through virtual interviews. Last but not least, given the turbulent nature of race relations and culture in the United States over the last year combined with the ability of applicants to virtually interview without travel or financial restrictions, it will be absolutely critical to understand if virtual interviews portend to increase the spread of geographic and cultural diversity among applicants to pathology residency programs. That is, if current trends in resident recruitment can be altered from the current rate of 40 – 60% intraregional resident matriculation or whether the needs of financial and family assistance and/or intraregional familiarity are insurmountable.8 For if the potential for greater diversity is attainable in a significant manner that can be perpetuated into the future, it will be hard to argue for a return to the traditional format. That said, there will likely be bias in the data as an increasing number of pathology residency programs have heard the call to arms and are marching towards diversity, inclusion and equity through greater promotion, recruitment and retention efforts.9

In a tumultuous year that has included race relations reminiscent of the Civil Rights Era combined with a total number of worldwide pandemic deaths similar to the 1957 or 1968 influenza pandemics, medicine continues its steady progression toward improved healthcare and education for all. Following the May 2020 recommendations to implement virtual residency interviews, pathology residency programs moved expeditiously to bolster their websites, increase their social media presence, add virtual tours and prepare for the virtual interview format. Amid this tumult, the virtual interview format has already served to lessen the burdens of time and cost while also serving the practical needs of interview assessments for both medical students and residency programs. Yet, only time and methodical assessment will tell if the virtual interview format eliminates the impact of these burdens on residency decisions, allows both parties to adequately assess cultural fit and if the format and its advantages are here to stay. Regardless, it is imperative that the emphasis on diversity, inclusion and equity remains irrespective of future format.

References

  1. The Coalition for Physician Accountability’s Work Group on Medical Students in the Class of 2021 Moving Across Institutions for Post Graduate Training Final Report and Recommendations for Medical Education Institutions of LCME-Accredited, U.S. Osteopathic, and Non-U.S. Medical School Applicants.
  2. Pourmand, A., Lee, H., Fair, M., Maloney, K. & Caggiula, A. Feasibility and usability of tele-interview for medical residency interview. Western Journal of Emergency Medicine 19, 80–86 (2018).
  3. Hammoud, M. M., Andrews, J. & Skochelak, S. E. Improving the Residency Application and Selection Process: An Optional Early Result Acceptance Program. JAMA – Journal of the American Medical Association 323, 503–504 (2020).
  4. Chandler, N. M., Litz, C. N., Chang, H. L. & Danielson, P. D. Efficacy of Videoconference Interviews in the Pediatric Surgery Match. J. Surg. Educ. 76, 420–426 (2019).
  5. Vining, C. C. et al. Virtual Surgical Fellowship Recruitment During COVID-19 and Its Implications for Resident/Fellow Recruitment in the Future. Ann. Surg. Oncol. 1 (2020). doi:10.1245/s10434-020-08623-2
  6. Healy, W. L. & Bedair, H. Videoconference Interviews for an Adult Reconstruction Fellowship: Lessons Learned. Journal of Bone and Joint Surgery – American Volume 99, E114 (2017).
  7. Vadi, M. G. et al. Comparison of web-based and face-to-face interviews for application to an anesthesiology training program: a pilot study. Int. J. Med. Educ. 7, 102–108 (2016).
  8. Shappell, C. N., Farnan, J. M., McConville, J. F. & Martin, S. K. Geographic Trends for United States Allopathic Seniors Participating in the Residency Match: a Descriptive Analysis. J. Gen. Intern. Med. 34, 179–181 (2019).
  9. Ware, A. D. et al. The “Race” Toward Diversity, Inclusion, and Equity in Pathology: The Johns Hopkins Experience. Acad. Pathol. 6, (2019).

-Josh Klonoski, MD, PhD, is a chief resident at the University of Utah, Salt Lake City, Utah, with a focus in neuroinfectious disease and global health. He has completed the first year of a neuropathology fellowship (out of sequence) and is in his final year of an anatomical and clinical pathology residency. Dr. Klonoski will return to the second neuropathology fellowship year in 2021 – 2022 and apply for a mentored clinical scientist research career development award (K08). The focus of his laboratory research is influenza and active projects include flu pneumonia, super-infections, encephalitis and oncolytic virotherapy.

What to Expect When You Don’t Know What You’re Expecting: COVID-19 and Flu Season in the Laboratory

Welcome to October 2020 and a flu season unlike any other. What can we expect? Well, it’s complicated. And if we aren’t sure what to expect, can we still be prepared? Yes (at least for some things)!

From the beginning of the COVID-19 pandemic and throughout the summer of 2020 clinicians and laboratorians have been anxiously wondering what effect global presence of respiratory virus SARS-CoV-2 would have on the 2020-2021 flu season. “Flu season,” the annual, relatively predictable period of increased cases and deaths due to Influenza A and B, occurs during colder, winter months. In the northern hemisphere this is September through March. We have extensive experience tracking the onset and genetic variability of the predominant influenza viruses. We manufacturer flu vaccines based on data of potentially likely influenza strains. Other viruses that cause respiratory symptoms follow similar seasonal patterns. These include common (non-SARS-CoV-2) human coronaviruses, and Respiratory Syncytial Virus (RSV). In short: this is a known, annual occurrence that we can usually prepare to some extent.

So what will that look like this year? During the historic 1918 pandemic influenza, deaths seen during the first winter of the outbreak paled in comparison to those seen the following winter. Even if that kind of terrible scenario doesn’t occur during this pandemic year, it is possible we are facing “perfect storm” of COVID-19 plus influenza resulting in overwhelmed hospitals and depleted testing supplies. [https://www.cidrap.umn.edu/news-perspective/2020/09/fears-perfect-storm-flu-season-nears]

We know that COVID-19 spreads well in enclosed spaces with prolonged person-to-person contact, regardless of climate and temperature, via respiratory secretions. Because of this, there has been widespread adoption of mask wearing, social distancing, and limitations on in-person gathering. Promisingly, these interventions to prevent the spread of COVID-19 seem to be contributing to historically low influenza rates in the Southern Hemisphere! [https://www.cdc.gov/mmwr/volumes/69/wr/mm6937a6.htm] But adoption of these mitigation strategies are not being universally or rigorously followed in all regions and communities. As temperatures drop, we could see more people conducting activity indoors – will this change transmission patterns? Will regions with ongoing COVID-19 outbreaks be more prone to influenza as well? If hospital capacity becomes strained, will criteria for ordering tests change?

During COVID-19 laboratories have responded heroically and rapidly to test kit shortages, supply chain issues, and staffing challenges. At this stage (October of 2020) many high-level decisions about SARS-CoV-2 testing, like test platform purchasing and validation or manufacturer test kit allocations, might already be set in stone. So is there anything that can be done to help labs and laboratory workers successfully make it through flu season?

Here are 3 suggestions:

1) Establish testing algorithms and clear sample workflows.

Each facility and laboratory will have their own platforms for testing COVID-19 and other respiratory pathogens. Depending on the service ordering the test, there can be both immediate and downstream consequences for when a test comes back positive, negative, or even when that test result is slower than expected!

An algorithm helps set institutional expectations for what tests are ordered under different scenarios. For example symptomatic patients presenting to a hospital with influenza-like illness (ILI), especially when they will be admitted, should likely have both SARS-CoV-2 and influenza tests ordered simultaneously. But asymptomatic patients being admitted for procedures may only require a SARS-CoV-2 test.

Let’s say your lab has both a SARS-CoV-2 PCR test and SARS-CoV-2 rapid antigen test. But due to risk a false negative, lab and clinical leaders are uncomfortable using only a rapid antigen test to conclusively rule out COVID-19 in patients being admitted to the hospital. Your algorithm could use specify the use of SARS-CoV-2 antigen testing in symptomatic patients to quickly “rule in” potential positives, where antigen-negative patients will also have a PCR test. Algorithm specifics come down to what your institutions stake holders (clinical AND laboratory) need and capacity are. The details of an algorithm will be dependent on your lab test platforms, your available test orders, and may need to be modified to accommodate restricted test allocations.

Along with clinical algorithms, clear workflow for specimens and test types can help laboratory workers get tests where they need to go within the lab. Not all SARS-CoV-2 tests have approval in the instructions for use for, say, nasal swabs. If nasal swab comes to the lab with orders for both influenza and SARS-CoV-2 tests, what is the procedure for informing the floor for an appropriate collection? Or say that your test platforms for different tests live in different areas of the lab. Your workflow may be to set up one test and do a pour off into an aliquot tube so tests can be run at the same time. Or you may have sufficient test collection materials to request a separate sample for each test.

Probably the most important part of developing or reviewing your existing algorithms and laboratory workflow is doing it in connection with others. The purpose is to streamline the entire process from clinical decision making to test performing and reporting and help everyone be on the same page.

2) Communicate to clinical staff frequently about your tests.

Because of the intense interest surrounding COVID-19 laboratory testing, it’s entirely possible that more people have had to learn about previously niche laboratory concepts like “sensitivity vs. specificity” and “PCR vs. antibody vs. antigen tests” than at any previously time in human history! However, it is also likely that many clinicians or administrators in your own institution may know more about a test platform they read about in the news than the COVID-19 test platform that their laboratory performs.

Even at this stage in the pandemic with perhaps more exposure (pun not intended!) then the laboratory has ever had, miscommunication and unclear expectations abound surrounding test performance or turnaround times.

Whenever possible, lab leaders who interact with clinicians and administrators should look for ways to educate on test platforms, testing capacity, and expected test performance (i.e. time to result, comparative sensitivity etc.). This could include asking for time to provide formal updates during monthly meetings, monitoring test statistics (e.g. a test “dashboard”), or just informal reminders about what tests the lab performs during phone calls.

3) Keep the lab staff off the phone.

A critical part of the job of the lab is to provide information and updates on when test results are available. But when the hospital floors or clinics are busiest with patients, often the lab is busiest performing those patients’ tests. A phone call about the status of a respiratory virus test can be undeniably helpful to that patient’s clinical care team! But a dozen such phone calls over the course of a lab worker’s shift, especially under normal lab conditions (e.g. no staff shortages or instrument issues) is a failure of communication and can be detrimental to both lab performance and lab worker wellbeing.

In addition to the need for regular education about testing mentioned above, to help protect your lab staff’s bench time here are some possible ways keep from being overwhelmed with phone calls:

  • In some institutions, passive reminders (for example about hand hygiene or upcoming events) cycle through computer screen savers or on television screens in clinical areas. You could see if a message like “Reminder from the lab: COVID-19 tests are completed in [length of time].” could be put on a rotation.
  • If there is no client service or switchboard for your lab, but people call the lab directly for updates, you could institute a message stop. This is where phone calls routed to the laboratory must listen to a reminder that (for example), “If you are calling for an update of a COVID-19 test, these tests cannot be completed faster than [length of time] after arriving in the lab.”

    While these messages can be undeniably annoying and disruptive for people calling the lab for other reasons (and become less effective over time) if phone calls get out of hand, this option could be considered.
  • A lab instrument going down can result in test backlogs and numerous phone calls to the lab. Some institutions centralize their information in the form of a duty officer (for example in the emergency department). This will be a person who can be informed of actionable information, like test delays due to instrument issues, and who will post and distribute that information to those affected.

There is a lot we don’t know about what’s to come in the COVID-19 pandemic. While we can’t predict the ways the lab may be challenged with the next unforeseen disruption, or even what our flu season testing needs may look like, hopefully we can prepare now to continue to support our patients by helping and supporting our labs.

-Dr. Richard Davis, PhD, D(ABMM), MLS(ASCP)CM is a clinical microbiologist and regional director of microbiology for Providence Health Care in Eastern Washington. A certified medical laboratory scientist, he received his PhD studying the tropical parasite Leishmania. He transitioned back to laboratory medicine (though he still loves parasites!), and completed a clinical microbiology fellowship at the University of Utah/ARUP Laboratories in Utah before accepting his current position. He is a 2020 ASCP 40 Under Forty Honoree.

Casualties of COVID-19: Measuring the Length, Width, and Depth of a Pandemic’s Impact

An editorial in Nature on August 12, 2020 entitled, “How to stop COVID-19 fuelling a resurgence of AIDS, malaria, and tuberculosis” provided four suggested solutions specifically for these diseases in the wake of Sars-CoV-2. For reference, here are the four approaches suggested as written in the editorial (#4 in detail):

  1. Hospitals and health authorities in affected cities and regions must recognize that AIDS, malaria and TB are surging again.
  2. Researchers must continue to refine their models using more real-world data.
  3. There is a need for public-information campaigns
  4. These campaigns cannot on their own keep surgeries and wards open, or equipment functioning. The resurgence of infectious diseases has created a greater demand for tests, treatments and research. All of these need more funding. 

Do those strike you as odd? The entire economy of nations along with the focus of their healthcare has been derailed and distracted by COVID-19 and the solution for these diseases is to recognize them, improve models, inform the public and seek more funding. You are either completely in tuned with the author in seeing that more funding is needed or you are a bit miffed that, in the wake of all that is happening, THESE guys want more money?

The US is a major contributor to the Global Fund for HIV, TB, and Malaria (the largest funder of these activities) and the total pledges to date for the GF approach $69 billion dollars with the US providing $54 billion (92%). From 2008 to 2016, the US contribution increased almost every year from $840 million to $1.65 billion annually until 2015 when it was frozen at $1.35 billion until 2019. In 2020, prior to the COVID-19 pandemic (i.e., during calendar year 2019 when the fiscal year 2020 budget was being planned), the amount from the US dropped to $958 million (2010 levels), representing a 30% drop in funding. So, to recap: The Global Fund started the year down by nearly 30% of what had been available, COVID-19 derailed all activities and drained the fiscal resources of patients and nations, and now, the progress that has been made on these diseases has been set back bay possibly a decade. The situation couldn’t be more desperate and, YES, the program needs a massive increase in funding. But, to be very clear, that massive increase pre-dated COVID-19 and represents something more distressing underneath.

I was fortunate to give the Michelle Rablais lecture at the ASCP Annual Meeting in Phoenix in 2019 where I carefully laid out the costs of controlling JUST malaria (not to mention TB and HIV) and demonstrated for the audience that as the number of cases get smaller and smaller (because your measures are so successful), the cost of finding the remaining cases goes up. As we successfully approach elimination or eradication of a disease, the final push requires at least the same but often more funding to make it across the finish line. This is not an opinion but is based on an enormous amount of data from other diseases as well as from the world’s experience with the first malaria eradication campaign. For HIV, we can’t eliminate it or eradicate it but we have converted it to a chronic disease and, therefore, infrastructure and funding to support patients ongoing is needed and by any form of math has to increase as the population lives longer and more people are added to the disease pool (although those numbers had been greatly reducing). Tuberculosis in its simplest form is a disease of poverty related to lack of access to drugs and healthcare, cramped living conditions, etc. When a pandemic derails the economy and causes the poor to become even more poor, tuberculosis is going to surge.

To the authors of this editorial I offer a gracious thank you and note with a heavy heart that the estimate of $28.5 billion additional dollars being needed to make up the ground lost by COVID-19 does also include the ground they had already lost by defunding principles trending over the last 4 years for global health.

But at least the countries that struggle with these diseases only have HIV, TB, and malaria to worry about, right? Wrong. In almost every low- to middle-income country where HIV, TB, and malaria are or have been major health challenges, hypertension, diabetes, cancer, cardiovascular disease, stroke, and mental health are equivalent or worse health problems than compared with high income countries. Do not be dissuaded by sheer numbers and always consider the outcomes, pre-COVID-19. For cancer, mortality in the US averages around 35% while in Africa it is closer to 80%. In full COVID-19 response mode, cancer programs—fledgling, underfunded, and disorganized—became non-existent and are only now (nearly 6 months after closing) starting to re-open and find their way back to where they were—fledgling, underfunded, and disorganized! Diabetics cannot go 6 months without insulin, hypertensive patients cannot have unregulated blood pressure, etc. While in the safety of a high-income country, makeshift systems, telehealth, contactless visits, etc. were brought on board to keep some semblance of a healthcare system in place, cancer patients were delayed in receiving diagnoses and treatment due to rationing of time and elimination of “elective” procedures.

As the data continues to be tallied and as models continue to be developed to understand just how much we have lost from our failed response to COVID-19 as a world and certainly as a nation, please do not slough off the staggering “additional” deaths that are going to be reported because of patients who didn’t have access to their regular health system. Every person from November 2019 until the end of this pandemic whose death occurred because their regular supply lines were disrupted, their planned treatments were cancelled, their medical supplies were not available, or their access to life-saving interventions were delayed is just as much a casualty from COVID-19 as a directly infected patient who succumbs to the disease. Our recent experience as a nation with the disasters in Puerto Rico around both the confusing death tolls from the hurricanes as well as the total death toll from the fiscal challenges of their medical system (prior to COVID-19) should serve as valuable lessons. Let us not come out of the other side of this pandemic with a similar disregard for the value of every human life or without an understanding of how our individual and collective mistakes as a nation have lead directly to these effects.

milner-small


-Dan Milner, MD, MSc, spent 10 years at Harvard where he taught pathology, microbiology, and infectious disease. He began working in Africa in 1997 as a medical student and has built an international reputation as an expert in cerebral malaria. In his current role as Chief Medical officer of ASCP, he leads all PEPFAR activities as well as the Partners for Cancer Diagnosis and Treatment in Africa Initiative.

Massive COVID-19 Testing: 30 Million Tests/Week

Population COVID-19 testing

Population-wide testing to identify symptomatic and asymptomatic infections could be a powerful tool to control Coronvirus Disease 2019 (COVID-19) spread, but current global testing capacity does not permit widespread testing of asymptomatic individuals. These tests are still limited to individuals who are symptomatic with limited availability to those with recent exposure to an infected person.

Because of the high prevalence of asymptomatic COVID-19 infections, proposals from the Rockefeller Foundation for disease mitigation include widespread and frequent testing of the US population. In the United States, diagnostic testing for SARS-CoV-2, the causative virus of COVID-19 is currently >2 million per week. Estimates for US testing needs for population wide surveillance range from 30 to 300 million per week. In order to scale testing by an order of magnitude, novel technologies and rethinking current testing paradigms are needed. The NIH has initiated a rapid funding program to develop SARS-CoV-2 testing, and these new technologies may play a part. However, we can broadly conceptualize key problems to address in population-wide testing in the US. The first is high-sensitivity testing which identifies active infection and can be performed with massive throughput. The second is the logistics of gathering hundreds of thousands of samples to each testing laboratory each day.

Next Generation Solutions to COVID testing

Emerging technologies using targeted next-generation sequencing have been suggested as a potential solution to population-wide testing. The key features include 1) extraction free amplification 2) an easily collected specimen such as saliva, 3) nucleotide barcodes to enable sample pooling, and 4) a limited number of targets (to allow deeper sequencing, i.e. higher sensitivity). Illumina is selling a whole genome test for SARS-CoV-2, but this limits sequencing to 3,000 tests/ run. Another recent approval for a private testing lab uses only one target, and may allow it to increase to 100,000 tests/ day. And a recent protocol for LAMP-Seq in pre-print outlines how this could work in a scheme below. An attractive aspect of this approach is decentralized specimen processing.

Whereas Bill Gates has supported a portfolio approach to vaccines placing multiple bets on different processes in parallel, a similar approach should be applied to multiplexed sequencing methods. Two sequencing runs can be performed on a single instrument in a single day, which can process several thousand samples. However, sequencing is not the only step in sequencing; library preparation and specimen handling take significant amounts of time too.

Laboratory Logistics

This technology would represent an exponential expansion in analytic testing capacity, but clinical labs will require a similar escalation in logistic capacity. The largest clinical laboratories in the world process less than 100,000 samples per day. Clinical laboratories have a long history of automation with the first robotic specimen track systems developed in the 1980s. Engineering and clinical lab expertise should thus partner to innovate on methods to handle high volumes. This level of investment for an issue that is likely to fade in 2 years, is not attractive to most private health systems, so public investment from multiple states in regional reference labs is needed.

It is still hard to conceive the necessary scale up in sample processing can be achieve within the time frame needed, so I would also propose a de-centralized sample processing approach. This would include self-collection of saliva (a safe, effective sample type with similar sensitivity as nasopharyngeal swabs), drop-off sites, and processing at places like Pharmacies (>90% of Americans live within 5 miles of a pharmacy and they could be authorized to administer tests- just as they administer vaccines). This would introduce pre-analytic problems, but if the goal is frequent and high rates of testing, then we will have to accept certain losses in sensitivity (which currently is arguably better than it needs to be). Interestingly, pre-analytic concerns with saliva have not led to sample instability or degradation of RNA causing false negatives, as described in my last post. However, other factors could affect saliva quality: smoking, age, and genetic factors of water: protein ratio affecting viscosity.

Testing solutions should be considered in the context of the planned testing network. The specimen type should be easy for the patient to provide, processed with existing laboratory equipment and resulted electronically. For example, current COVID-19 testing is based on sample collections requiring a healthcare worker encased in personal protective equipment (PPE) utilizing a swab device. Testing needs to progress to a simpler solution such as saliva which can be collected by the patient in the absence of a swab or PPE. Preliminary studies have demonstrated that saliva is sample type comparable to nasopharyngeal swab. The ideal saliva sample would be collected into an existing collection tube type (e.g. red-top tubes) which are already compatible with existing laboratory automation. In aggregate, a person could spit into a tube at-home, have the tube sent to a laboratory, and in the laboratory the tube would be directly placed onto an automated robotic track system. 

Laboratory professionals need to provide a comprehensive plan for regional and national laboratory networks which can scale to provide overwhelming force to COVID-19 testing. No other profession or governmental organization understands testing as much as we do. Our understanding of managing samples from collection to result should be applied to the pandemic at hand. Until now most laboratorians in the US have focused on the immediate needs of providing testing for symptomatic patients and healthcare workers.

Vision for automated COVID-19 testing

One could envision an automated line of testing that moves samples through processing to allow multiplexing and combinations of samples to allow large numbers of patients to be tested at once (see below). This is feasible in some specialized centers, but would require investments in automation, bioinformatics, and interfaces for a seamless process (figure below). If testing mostly asymptomatic patients, it may also be possible to do this on pooled samples. The number of samples to pool would depend on the likelihood to having a positive result (this would require sequencing all individuals in a pool).

This represents a synthesis of ideas in decentralized specimen collection, laboratory automation and massive testing throughput with Next-Generation Sequencing, but unfortunately this is not yet a reality.

References

  1. Jonathan L. Schmid-Burgk et al. LAMP-Seq: Population-Sclae COVID-19 Diagnostics Using Combinatorial Barcoding. bioRxiv 2020.04.06.025635.
  2. The Rockefeller Foundation. National Covid-19 Testing Action Plan Pragmatic steps to reopen our workplaces and our communities. 2020.
  3. Cahill TJ, Cravatt B, Goldman LR, Iwasaki A, Kemp RS, Lin MZ et al. Scientists to Stop COVID-19.  OR Rob Copeland, Wall Street Journal (2020) The Secret Group of Scientists and Billionaires Pushing a Manhattan Project for Covid-19. April 27
  4. https://www.illumina.com/products/by-type/ivd-products/covidseq.html

-Jeff SoRelle, MD is a Chief Resident of Pathology at the University of Texas Southwestern Medical Center in Dallas, TX. His clinical research interests include understanding how the lab intersects with transgender healthcare and improving genetic variant interpretation.

The Story of the Mott Cell, COVID-19 and the Cute Little Mouse

I have worked in hematology for many years, and there are certain things that never fail to excite technologists. Working in New Hampshire, it was always exciting to sickle cells or malaria, something common to some, but not common in our patient population. I now work in Baltimore, and see sickle cells nearly every day, and we come across malaria not too infrequently, but we still share good examples and save them for training. When we see something different or unusual, we always share the finding. Cells may need to be sent to the pathologists for a pathology review, and we always check back to see the pathologist’s identification and comments. Medical Technologists by nature are a curious bunch, and we always want to see ‘cool’ things. I wrote a blog two years ago about the only patient I have ever seen with Trypanosoma (Hematology Case Study: The Race to Save a 48 Year Old Man from a Rare Disease). Last month I wrote about Blue-green cytoplasmic inclusions (COVID-19 Patients with “Green Crystals of …” STOP! Please Don’t Call Them That). So, when I saw something else ‘cool’ and different on a peripheral smear, and then saw it AGAIN, on another patient, and saw other techs here in the US and in other countries were also mentioning these, because it’s my nature, I got curious.

When I write these blogs, I often feel a little bit like the mouse in the children’s story “If You Give a Mouse a Cookie”, by Laura Joffe Numeroff. It’s about an adorable little mouse who asks for a cookie, and then decides he needs a glass of milk to go with it, and then he needs a straw, and it goes on and on, in a circle, back to the beginning. Maybe it’s that the mouse is a little ADD, but I like to believe that he’s just creative and curious. I start with an idea, and often go off on many tangents before a blog is finished and comes back to where I started.. When I started writing this, it was because I saw an interesting cell, and I started exploring, and found that others had seen them, too. Then I started looking through my textbooks for references and information, and searched for recent research or studies, and then I wanted to find out more… just like that mouse.

There are some things that we learn about in school and we may see on CAP surveys, but no matter where you work, they are still rarely seen, so are a novelty. Mott cells are one of these things. I have a collection of Hematology texts from grad school and years of teaching Hematology. Several of these don’t even mention Mott cells, but, when they do, it’s barely a sentence in a discussion of plasma cells. I happen to have a very old copy of Abbott Laboratories “The Morphology of Human Blood Cells” . The one with the red cover, from 1975. The term Mott cell does not appear in this manual, but they do show pictures and describe “Plasma cells with globular bodies (Grape, Berry or Morula cells)”, and describe these globules as “Russell bodies”.1 So some of us who have been working in the field for many years may remember Russell bodies and Morula cells, or Grape cells, even if the term Mott cell is not familiar. Regardless of what we or textbooks call them, they tend to trigger a memory because the images are so unique.

So, again, I’m a bit like that mouse and getting distracted with the background. Why am I writing this blog? In recent months I have seen cells identified as plasmacytoid lymphocytes and Mott cells in several hospitalized patients. I have heard reports of these cells in other facilities as well. So, like a good medical technologist, I got curious about Mott cells. What are they, and what is their significance? And why are we seeing more of these now?

Mott Cells are named after surgeon F.W. Mott. In the 1890’s, William Russell first observed these cells with grape like globular inclusions, but did not recognize what the inclusions were or their significance. Russell examined the cytoplasmic globular inclusions and assumed that these cells were fungi. Ten years later, Mott described cells he called morular cells. He recognized that these cells were plasma cells and the inclusions were indicative of chronic inflammation. Thus, today we refer to these cells as Mott cells, morular cells or grape cells, and the inclusions as Russell bodies.2

Hematology texts describe Mott cells as morphologic variations of plasma cells packed with globules called Russell bodies. We know that plasma cells produce immunoglobulin. When the plasma cells produce excessive amounts of immunoglobulin, and there is defective immunoglobulin secretion, it accumulates in the endoplasmic reticulum and golgi complex of the cells, forming Russell bodies. Russell bodies are eosinophilic, but in the staining process the globulin may dissolve and they therefore appear to be clear vacuoles in the cell under the microscope. Thus, a plasma cell with cytoplasm packed with these Ig inclusions is called a Mott cell.

Mott recognized that these atypical plasma cells were present in inflammation. Plasma cells are not typically seen on peripheral blood smears and constitute less than 4% of the cells in a normal bone marrow. Yet, on occasion, we can see plasma cells, including Mott cells, on peripheral blood smears in both malignant and non-malignant conditions. Mott cells are associated with stress conditions occurring in a number of conditions including chronic inflammation, autoimmune diseases, lymphomas, multiple myeloma, and Wiskott–Aldrich syndrome.3

So, why are we seeing an increased mention of Mott cells now? We seem to be seeing these on patients testing positive for SARS-CoV-2. I have seen cells on patients at my facility that resemble Mott cells. I belong to a Hematology Interest group and over the past few months I have seen several people post pictures of Mott cells, cells with Russell bodies, and plasmacytoid lymphocytes identified on peripheral blood smears of COVID-19 patients. Other techs chimed in with comments that they have also seen these cells recently. I have even seen a comment propose that these cells are indicative of COVID-19 infection.

SARS-CoV-2 definitely causes inflammatory processes and stress conditions in the body, so it makes sense that we may see these cells in COVID-19 positive patients.

Figure 1 shows a Mott cell on an image from Parkland Medical Center Laboratory, Derry, NH. A Mott cell was identified by pathologist in a male patient who tested negative for COVID-19 at the time the sample was drawn, and subsequently tested positive. Mariana Garza, a Medical Technologist working at Las Palmas Medical Center in El Paso, TX shared a case of a 59 year old diabetic male, diagnosed with COVID-19. The patient’s WBC was 31 x 103/μL. Two Mott cells were identified by pathologist on his differential. So, the curious little mouse in me researched some more.

Image 1. Mott cell. Photo courtesy Parkland Medical Center, Laboratory, Derry, NH.

Several published research papers have studied morphologic changes in peripheral blood cells in COVID-19 patients. As we now know, SARS-CoV-2 affects many organs including the hematopoietic and immune systems. A study in Germany showed that COVID-19 patients exhibited abnormalities in all cell lines; white blood cells, red blood cells and platelets. Increased WBC counts were seen in 41% of samples in their study. Differentials performed on study patients showed lymphocytopenia in 83%, and monocytopenia in 88%. Red blood cell morphology changes were noted. Platelet counts ranged from thrombocytopenia to thrombocytosis, but giant platelets were noted across the board.4

Mott cells are indicative of chronic inflammation and may have significance in association with COVID-1. In the above mentioned study, aberrant lymphocytes were noted in 81% of patients who were SARS-CoV-2 positive, and observable in 86% of the same patients after they tested negative. The paper shows plasmacytoid lymphocytes and Mott cells amongst these aberrant lymphocytes. Moreover, morphologic changes in neutrophils, such as a left shift and pseudo‐Pelger‐Huët anomaly, decreased after virus elimination but changes in lymphocytes, indicators of chronic infection, remained.4

Another study also reported reactive or plasmacytoid lymphocytes and Mott cells observed in peripheral blood.4,5 Researchers at Northwick Park Hospital, UK, presented a case study of a 59 year old male with COVID-19 with a normal WBC and thrombocytosis. His differential revealed lymphocytopenia. His differential also showed lymphoplasmacytoid lymphocytes and Mott cells. In their conclusions it is stated that “In our experience, the lymphocyte features illustrated above are common in blood films of patients presenting to hospital with clinically significant Covid‐19. The observation of plasmacytoid lymphocytes supports a provisional clinical diagnosis of this condition.”5

Can these variant plasma cells, along with other commonly seen morphological changes, be used as part of a diagnostic algorithm for SARS-Cov-2 infection? As we see more COVID-19 patients there will be more, larger studies done and more Mott cells identified. Some disorders, such as Epstein Barr Virus and Dengue Fever are characterized by distinct viral changes in cells. However, since Mott cells can be seen in many conditions, these alone could not be considered diagnostic, but the indications are that these cells, along with the entire differential and morphological patterns, could prove to be a straightforward and easy to perform supplementary diagnostic tool. More, larger studies need to be done. It was concluded in the German study, that this pattern of morphologic changes in cells could be further investigated and validated with a larger blinded study, and that this information could lead to the development of a morphologic COVID‐19 scoring system.4 In the meantime, keep an eye out for Mott cells. These should not be ignored and should be in some way noted because they may be of future diagnostic use. That’s all or now, folks! Something to dig deeper into in another blog! The mouse strikes again!

Many thanks to Nikki O’Donnell, MLT, Parkland Medical Center, Derry, NH and Mariana Garza, MT, Las Palmas Medical Center in El Paso, TX for sharing their case studies and photos.

Becky Socha MS, MLS(ASCP)CMBB

References

  1. Diggs, LAW, Sturm, D, Bell,A. The Morphology of Human Blood Cells, Third edition. Abbott Laboratories. 1975.
  2. ManasaRavath CJ, Noopur Kulkarni, et al. Mott cells- at a glance. International Journal of Contemporary Mudeical Research 2017;4(1):43-44.
  3. Bavle RM. Bizzare plasma cell – mott cell. J Oral Maxillofac Pathol. 2013;17(1):2-3.doi: 10.4103/0973-029X.110682.
  4. Luke, F, Orso, E, et al. Coronavirus disease 2019 induces multi‐lineage, morphologic changes in peripheral blood cells:eJHaem. 2020;1–8.
  5. Foldes D, Hinton R, Arami S, Bain BJ. Plasmacytoid lymphocytes in SARS-CoV-2 infection (Covid-19). Am J Hematol. 2020;1–2. https://doi.org/10.1002/ajh.
  6. Numeroff, Laura. If You Give a Mouse a Cookie, 1985.

-Becky Socha, MS, MLS(ASCP)CM BB CM graduated from Merrimack College in N. Andover, Massachusetts with a BS in Medical Technology and completed her MS in Clinical Laboratory Sciences at the University of Massachusetts, Lowell. She has worked as a Medical Technologist for over 30 years. She’s worked in all areas of the clinical laboratory, but has a special interest in Hematology and Blood Banking. When she’s not busy being a mad scientist, she can be found outside riding her bicycle.

False Negatives in COVID-19 Testing

I left for vacation at the beginning of June thinking “once I get back, all of this COVID stuff will be quieted down.” …Well that wasn’t quite the case and testing for novel Coronavirus has continued to be very important. In fact, this last weekend I was tested by occupational health. It came back negative, but I’m am very enthusiastic to get alternative specimen types validated; those Nasopharyngeal swabs are quite…uncomfortable. Luckily, my test was processed at our institution which gets results back in 24-48 hours. However, with the resurgence around the country, turnaround times are backing up to 7-8 days. One solution has been the widely used IDNOW point of care platform. However, there has been significant concern over false negatives produced by this platform. One reason the sensitivity is different is because this platform performs isothermal amplification of nucleic acid. This method amplifies RNA at a stable temperature instead of cycling the temperature as in real-time PCR.

Colleagues at my institution reflexed any negative IDNOW samples to the m2000 Real-Time PCR assay for SARS-CoV-2 for one month. Within that time, over 500 samples were tested and the IDNOW was found to have missed 21% of positive cases (prevalence rate of 5%)2. One the positive side, it had a 98% negative predictive value, which helped rule out COVID19 infection. However, as prevalence rates are increasing, a high negative predictive value isn’t as important as sensitivity.

One study drew much attention when it claimed the IDNOW had a sensitivity of 52% in a New York City academic institution (Basu)4. However, this seems to be an outlier compared to other studies of this platform: one large multi-center study found positive percent agreement (equivalent of sensitivity when a gold standard test hasn’t been established) of 74%1. The highest PPA of 88%3 for the IDNOW was found in a study that indicated it can be completed in 17 minutes, whereas another quick instrument (but not point of care instrument: Xpert Xpress, 45min) had a PPA of 98%2.

Myself and other colleagues looked more closely at the clinical characteristics of false negative test results on the IDNOW. Overall, we found 82% PPA, and 8 patients with false negative tests. Interestingly, a majority of these patients were tested over 2 weeks after their initial onset of symptoms. The virus is known to be at its highest levels at the beginning of symptom onset. So the test may not be limited, but it should be used in the correct clinical context (< 2weeks from symptom onset). After that time, other RT-PCR based tests are more appropriate.

As clinical laboratorians, we often hear: “the right test for the right patient at the right time.” Now with so many platforms available for use in different contexts, we should help guide clinicians to Choose Wisely.

References

  1. Harrington A et al. Comparison of Abbott ID Now and Abbott m2000 methods for the detection of SARS-CoV-2 from nasopharyngeal and nasal swabs from symptomatic patients. JCM 2020. PMID: PMID: 32327448
  2. McDonald et al. Diagnostic Performance of a Rapid Point of Care Test for SARS-CoV-2 in an Urban ED Setting. Academ. Emerg. Med. 2020. PMID: 32492760
  3. Zhen W et al. Clinical Evaluation of Three Sample-To-Answer Platforms for the Detection of SARS-CoV-2. JCM 2020. PMID: 32332061
  4. Basu A et al. Performance of the rapid Nucleic Acid Amplification by Abbott ID NOW COVID-19 in nasopharyngeal swabs transported in viral media and dry nasal swabs, in a New York City academic institution. BioRxiv 2020.

-Jeff SoRelle, MD is a Chief Resident of Pathology at the University of Texas Southwestern Medical Center in Dallas, TX. His clinical research interests include understanding how the lab intersects with transgender healthcare and improving genetic variant interpretation.

COVID-19 Patients with “Green Crystals of …” STOP! Please Don’t Call Them That

Blue-green cytoplasmic inclusions in neutrophils and monocytes are a novelty in hematology. It is rare to see these inclusions on peripheral smears, and when we do, there is excitement, but sadness too, because, when noted, they usually indicate a poor prognosis and impending death. Thus, we have heard them called “green crystals of death” or “death crystals.” I know I would not want to read a family member’s medical chart and see reference to “death crystals.” It’s an insensitive term, and one the medical community is trying to discourage. And, in fact, though it typically does indicate a poor prognosis, not all cases lead to death. In published reports, it has been shown that short term mortality in patients with these crystals is about 60%.1

These rare inclusions are refractile and irregular in shape, and are found in neutrophils, and occasionally in monocytes. Color seems to be subjective here. They call them green when inclusions in photos or cells I am looking at look very blue to me. The color perceived may depend on the type of stain (Giemsa, Wright or Wright-Giemsa) used and how fancy we get in color names and descriptions. Or, maybe I’m just color blind! Some people (like my husband) are “lumpers” and call anything blue-green, blue, or green, but don’t recognize subtleties of colors. Thus, I guess to make everyone happy, or to compromise, the blue-green description may fit them best.

Image 1. Blue-green inclusions seen in neutrophils. Photos courtesy of Alana D. Swanson. UMMC

These blue-green inclusions were originally reported in patients with hepatic injury and failure. Laboratory results include elevations in AST, ALT and LDH. More recently, there have been cases with no evidence of hepatic injury. Researchers are now finding that these crystals can occur in patients with tissue injury other than liver, and in patients with multiorgan failure. In patients with no liver injury, what is a common factor is that LDH is elevated, indicating tissue injury. Additionally, along with these crystals, lactic acid levels can be used as a predictor of survival. Higher levels of lactic acidosis at the time crystals are noted is a negative predictor of survival.2

In trying to determine the clinical significance of these crystals, they have been subject to a number of different stains to determine their content. The association with hepatic failure led researchers to hypothesize that the crystals were a bile product in circulation. Since then, the crystals have been found to be negative in bile stains. When stained with other stains, Oil Red O showed positive in neutrophils, indicating high lipid content. The inclusions did not stain positive with iron stain or myeloperoxidase. Acid fast stains showed the inclusions to be acid fast positive.3 These crystals also show an interesting similarity to sea-blue histiocytes, which further associates them with tissue injury. After analysis, it is now thought that these crystals contain lipofuscin-like deposits representing lysosomal degradation products, and may be present in multiple types of tissue injury.2

With the current pandemic, I have seen reports of these crystals in COVID-19 patients. I have heard of fellow technologists seeing these, and a recent paper described the first reported cases in patients with COVID-19. These recent incidences may lead to new information about exactly what clinical significance they hold. About one third of COVID-19 patients have elevated ALT and AST, though it is not yet clear whether the liver dysfunction is directly caused by the virus, due to sepsis, or other complications of patient comorbidities. Many COVID-19 patients have mild disease, yet some develop severe pneumonia, respiratory complications, and multiorgan failure. Mortality is increased in these severely affected patients. To better understand and manage treatment for COVID-19, physicians seek to identify biological indicators associated with adverse outcomes.1

In a New York City study, Cantu and colleagues reported on six COVID-19 patients who presented with blue-green crystals in neutrophils and/or monocytes. All six patients had an initial lymphocytopenia, and significantly elevated AST, ALT, LDH and lactic acid at the time the crystals were noted. All of the patients had comorbidities, yet only two of the six presented with acute liver disease. Interestingly, in the six cases reported on in the study, only one had blue-green inclusions reported from the original manual differential. The others were found retrospectively when correlating the cases with patients known to have elevated ALT and AST. All patients died within 20 days of initial diagnosis.1

The consensus of several papers in the last few years is that these crystals are being underreported. As seen in the above study, the crystals were originally seen in just one of the six patients. A look back revealed the other cases. With an increase in COVID-19 cases in our facilities, these blue-green crystal inclusions may be a novelty that is wearing off. We may see a rise in their presence, and need to be able to recognize and report them. This information is important to report if clinicians are to use these crystal inclusions along with acute transaminase and lactic acid elevations to predict poor patient outcomes.

Clinicians, hematologists, and laboratory technologists should be educated and have a high level of awareness of these inclusions. The University of Rochester conducted a study a few years ago that noted that, because these crystals are rare, techs may not be on the lookout for them. Once techs see them, they seem to be on the alert and more are reported. The hospital instituted an “increased awareness” campaign, which resulted in an increase in detection. This revealed cases that were not related to liver injury, including patients with metastatic cancer and sepsis. However, an important correlating factor was that all of the patients had mild to severe elevations in liver enzymes. With more awareness, we are starting to see them in patients without hepatic injury, but with other inflammation and tissue injury.4

Image 2. Blue- green crystal inclusions seen in a patient diagnosed with sepsis and multiorgan failure. Photo courtesy of Karen Cable, YRMC.

Let’s raise our level of awareness of these maybe-not-so-rare crystal inclusions. And, please be sure to call them by their preferred name, blue-green neutrophil inclusions! Let’s not talk about death crystals or crystals of death.

Many thanks to my colleague Alana D. Swanson, MLS(ASCP)CM , University of Maryland Medical Center and Karen Cable, Hematology Section Lead, Yavapai Regional Medical Center, Arizona, for the photos used in this blog. 

References

  1. Cantu, M, Towne, W, Emmons, F et al. Clinical Significance of blue-green neutrophil and monocyte cytoplasmic inclusions in SARS-CoV-2 positive critically ill patients. Br J Haematol. May 26, 2020.
  2. Hodgkins, SR, Jones, J. A Case of Blue-Green neutrophil inclusions. ASCLS Today. 2019;32:431.
  3. Hodgson, T.O., Ruskova, A., Shugg, C.J., McCallum, V.J. and Morison, I.M. Green neutrophil and monocyte inclusions – time to acknowledge and report. Br J Haematol, 2015;170: 229-235.
  4. Patel,N, Hoffman,CM, Goldman,BJ et al. Green Inclusions in Neutrophils and Monocytes are an Indicator of Acute Liver Injury and High Mortality. Acta Haematol. 2017;138:85-90

-Becky Socha, MS, MLS(ASCP)CM BB CM graduated from Merrimack College in N. Andover, Massachusetts with a BS in Medical Technology and completed her MS in Clinical Laboratory Sciences at the University of Massachusetts, Lowell. She has worked as a Medical Technologist for over 30 years. She’s worked in all areas of the clinical laboratory, but has a special interest in Hematology and Blood Banking. When she’s not busy being a mad scientist, she can be found outside riding her bicycle.