Clinical laboratories could play a key role in helping users collect their samples correctly, interpret results, and transfer flu test data to their health records
Clinical laboratories may have another opportunity to provide service to their clients and the physicians who treat them. With the success of at-home COVID-19 testing, consumer demand for self-tests is changing and advances in diagnostic technology now make it feasible to make more influenza (flu) tests available for consumers to buy and use at home.
At-home tests for SARS-CoV-2 can be found at pharmacies all across America. But that’s not the case with tests for influenza.
Should self-test flu kits eventually become available and common, clinical laboratories could offer the service of helping consumers understand:
that the test was conducted correctly (specimen collection and analysis),
“Home flu testing would ensure that those who do need and receive antiviral medication for influenza are the ones who need it the most,” and that “we are making our treatment decisions based on data,” infectious disease specialist Christina Yen, MD (above), University of Texas Southwestern Medical Center, told STAT News. At-home flu self-tests could also bring opportunities for clinical laboratories to provide service to healthcare consumers and the physicians who treat them. (Photo copyright: UT Southwestern Medical Center.)
Pros and Cons of Consumers Doing At-home Influenza Testing
“It’s really rare, and it’s really new that people are allowed to know about what’s happening inside their body without a physician in the middle,” Harvard epidemiologist Michael Mina, MD, PhD, told STAT News. The article uses the example of at-home pregnancy tests. Despite a prototype for an at-home pregnancy test being created in 1967, it took another decade before an over-the-counter pregnancy test became available to the public.
“The general thinking was, ‘How could a woman possibly know what to do if she found out she was pregnant on her own without a doctor in the room?’ That is a ridiculous concern because women have been doing that for millions of years,” Mina added.
So, why be cautious when it comes to giving patients the option of at-home flu testing?
There are some cons to at-home influenza tests. Average citizens are not clinical laboratory professionals. They might obtain too little sample for an accurate reading or read the results incorrectly. Then, there is the possibility for false-negatives or false-positives.
An at-home test user is not likely to consider the possibility of a false result, however clinicians look at the situation with more nuance. If the patient was still symptomatic or in a high-risk community, the provider could administer a more sensitive medical laboratory test to confirm the previous test results.
“In a Facebook post from mid-November with hundreds of responses, concertgoers compared symptoms and positive test results, many of those from tests taken at home. But those data weren’t added to state public health tallies of COVID’s spread,” STAT News noted.
The larger concern is that samples obtained by at-home self-test users are not submitted for genomic sequencing. This could lead to incomplete data and delay identifying new variants of the coronavirus in communities.
Another barrier to at-home flu testing is that rapid influenza diagnostic testing can be unreliable. In 2009, the rapid influenza tests could only detect the H1N1 influenza virus in a mere 11% of samples, STAT News reported. Because of this, the FDA now requires manufacturers to test their rapid tests against eight different strains that change every year depending upon which strains are prevalent. This could present a problem if individuals use leftover tests from the previous flu season.
Do Pros of At-home Testing Outweigh the Cons?
At-home testing is convenient and makes testing more accessible to patients who may not be able to get to a clinic. Being able to test at home also encourages individuals to take precautions necessary to stop the spread of whichever illness they may have. Given the similarities in symptoms between influenza and COVID-19, people could benefit from having tools at home that correctly identify their illness.
At-home COVID-19 tests are here to stay, and at-home influenza tests may be on the way soon. Clinical laboratories could play an important role in educating the public on the correct handling of these tests.
Researchers say their method can trace ancestry back 100,000 years and could lay groundwork for identifying new genetic markers for diseases that could be used in clinical laboratory tests
Cheaper, faster, and more accurate genomic sequencing technologies are deepening scientific knowledge of the human genome. Now, UK researchers at the University of Oxford have used this genomic data to create the largest-ever human family tree, enabling individuals to trace their ancestry back 100,000 years. And, they say, it could lead to new methods for predicting disease.
This new database also will enable genealogists and medical laboratory scientists to track when, where, and in what populations specific genetic mutations emerged that may be involved in different diseases and health conditions.
New Genetic Markers That Could Be Used for Clinical Laboratory Testing
As this happens, it may be possible to identify new diagnostic biomarkers and genetic indicators associated with specific health conditions that could be incorporated into clinical laboratory tests and precision medicine treatments for chronic diseases.
“We have basically built a huge family tree—a genealogy for all of humanity—that models as exactly as we can the history that generated all the genetic variation we find in humans today,” said Yan Wong, DPhil, an evolutionary geneticist at the Big Data Institute (BDI) at the University of Oxford, in a news release. “This genealogy allows us to see how every person’s genetic sequence relates to every other, along all the points of the genome.”
The BDI team overcame the major obstacle to tracing the origins of human genetic diversity when they developed algorithms to handle the massive amount of data created when combining genome sequences from many different databases. In total, they compiled the genomic sequences of 3,601 modern and eight high-coverage ancient people from 215 populations in eight datasets.
The ancient genomes included three Neanderthal genomes, a Denisovan genome, and a family of four people who lived in Siberia around 4,600 years ago.
The University of Oxford researchers noted in their news release that their method could be scaled to “accommodate millions of genome sequences.”
“This structure is a lossless and compact representation of 27 million ancestral haplotype fragments and 231 million ancestral lineages linking genomes from these datasets back in time. The tree sequence also benefits from the use of an additional 3,589 ancient samples compiled from more than 100 publications to constrain and date relationships,” the researchers wrote in their published study.
Wong believes his research team has laid the groundwork for the next generation of DNA sequencing.
“As the quality of genome sequences from modern and ancient DNA samples improves, the tree will become even more accurate and we will eventually be able to generate a single, unified map that explains the descent of all the human genetic variation we see today,” he said in the news release.
Developing New Clinical Laboratory Biomarkers for Modern Diagnostics
In a video illustrating the study’s findings, evolutionary geneticist Yan Wong, DPhil, a member of the BDI team, said, “If you wanted to know why some people have some sort of medical conditions, or are more predisposed to heart attacks or, for example, are more susceptible to coronavirus, then there’s a huge amount of that described by their ancestry because they’ve inherited their DNA from other people.”
Wohns agrees that the significance of their tree-recording methods extends beyond simply a better understanding of human evolution.
“[This study] could be particularly beneficial in medical genetics, in separating out true associations between genetic regions and diseases from spurious connections arising from our shared ancestral history,” he said.
The underlying methods developed by Wohns’ team could have widespread applications in medical research and lay the groundwork for identifying genetic predictors of disease risk, including future pandemics.
Clinical laboratory scientists will also note that those genetic indicators may become new biomarkers for clinical laboratory diagnostics for all sorts of diseases currently plaguing mankind.
GISAID hosts a vast, open database of genomic sequences of SARS-CoV-2 coronavirus samples, and medical laboratory scientists in countries across the globe are contributing
Clinical laboratories around the world have been contributing to the global scientific community’s database of knowledge about SARS-CoV-2, the coronavirus that caused the COVID-19 pandemic, and its variants, through an ingenious and crucial network known as GISAID. This cooperative sharing of the coronavirus’ genetic data (now four million genomic sequences strong) has greatly contributed to understanding the spread of infections and progress obtained in developing effective treatments and vaccines.
Headquartered in Munich, Germany, GISAID, which stands for Global Initiative on Sharing Avian Influenza Data, was created in 2008 during the Avian Influenza (Bird Flu) pandemic. The GISAID initiative promotes “the rapid sharing of data from all influenza viruses and the coronavirus causing COVID-19. This includes genetic sequence and related clinical and epidemiological data associated with human viruses, and geographical as well as species-specific data associated with avian and other animal viruses, to help researchers understand how viruses evolve and spread during epidemics and pandemics,” according to the GISAID website.
Clinical pathologists are likely familiar with GISAID. The initiative has become an indispensable tool for researchers battling SARS-CoV-2. GISAID allows scientists and organizations worldwide to upload genetic sequences of COVID-19 samples. Those sequences can then be used in research for treatments, vaccines, and to track emerging variants. The information is invaluable, freely available, and represents the collaborative efforts of scientists around the world in the fight against COVID-19 and other infectious diseases.
An article published in The World, titled, “From Congo to Chile, Small Labs Are Playing a Growing Role in Global Understanding of COVID,” noted that more than four million genomic sequences have been submitted as of October 15, 2021. The more countries around the world that submit sequences to GISAID, the more understanding scientists have of how the virus is mutating. And, as the cost of performing genomic sequencing declines, the number of countries submitting genomes of SARS-CoV-2 to GISAID is rising.
How GISAID Ensures Contributors Receive Credit for Their Work
One of the reasons that GISAID has been so successful in gathering data is that it requires anyone who uses data downloaded from the massive database to give credit to the person or organization who uploaded it. In other words, if a scientist in the United Kingdom (UK) does breakthrough research using genomes that were originally uploaded to GISAID by a scientist in the Congo, the UK scientist must credit the work of the scientist from the Congo.
Other genomic databases do not have this requirement and genetic researchers are often hesitant to share information due to fear their work will be co-opted by others. According to The World, scientists in lower income countries are particularly vulnerable to having their work appropriated.
Even worse is having one’s work appropriated, used to create a product, and then not being given access to that product.
The guarantee that credit will be given softens some of those fears and explains why the GISAID database is so vast, and increasingly contains sequences from scientists in Africa, South American, and other places where genomic sequencing was not widespread prior to the pandemic. Information from all over the world is crucial for scientists monitoring the mutations of the SARS-CoV-2 coronavirus.
Criticisms of GISAID
The fact that more countries are contributing to the GISAID database is certainly a positive, but the non-profit is not without its critics. There have been complaints about the lack of transparency, and some researchers claim to have had their access denied to the data without any explanation.
An article published in Science reported that “Scientists live in fear of losing access to the GISAID database.”
One scientist who requested anonymity told Science, “I am so tired of being scared all the time, of being terrified that if I take a step wrong, I will lose access to the data that I base my research on. [GISAID] has that sword hanging over any scientist that works on SARS-CoV-2.”
The strict sharing rules may be necessary to encourage researchers in lower income countries to contribute their genomic data on SARS-CoV-2. Charles Rotimi, PhD, a geneticist at the National Human Genome Research Institute (NHGRI), told Science, “To make scientists, especially from developing countries, more comfortable—making sure that they are recognized in the work that they are doing—sometimes you have to create an extra layer [of protection].”
GISAID has certainly accomplished much in its assembling four million SARS-CoV-2 genetic sequences. The initiative’s efforts have contributed to a substantial increase in the number of countries around the world that now have gene sequencing capabilities.
This is another illustration for clinical laboratory managers and pathologists of how continual technology advances in gene sequencing equipment and data analysis software make it significantly cheaper, faster, and more accurate to do genetic sequencing. This was not true, just a few years ago.
Molecular probes designed to spot minute amounts of pathogens in biological samples may aid clinical laboratories’ speed-to-answer
Driven to find a better way to isolate minute samples of pathogens from among high-volumes of other biological organisms, researchers at Canada’s McMaster University in Hamilton, Ontario, have unveiled a bioinformatics algorithm which they claim shortens time-to-answer and speeds diagnosis of deadly diseases.
Two disease pathogens the researchers specifically targeted in their study are responsible for sepsis and SARS-CoV-2, the coronavirus causing COVID-19. Clinical laboratories would welcome a technology which both shortens time-to-answer and improves diagnostic accuracy, particularly for pathogens such as sepsis and SARS-CoV-2.
Their design of molecular probes that target the genomic sequences of specific pathogens can enable diagnosticians and clinical laboratories to spot extremely small amounts of viral and bacterial pathogens in patients’ biological samples, as well as in the environment and wildlife.
“There are thousands of bacterial pathogens and being able to determine which one is present in a patient’s blood sample could lead to the correct treatment faster when time is very important,” Zachery Dickson, a lead author of the study, told Brighter World. Dickson is a bioinformatics PhD candidate in the Department of Biology at McMaster University. “The probe makes identification much faster, meaning we could potentially save people who might otherwise die,” he added.
Sepsis is a life-threatening response to infection that leads to organ failure, tissue damage, and death in hospitals worldwide. According to Sepsis Alliance, about 30% of people diagnosed with severe sepsis will die without quick and proper treatment. Thus, a “shortcut” to identifying sepsis in its early stages may well save many lives, the McMaster researchers noted.
And COVID-19 has killed millions. Such a tool that identifies sepsis and SARS-CoV-2 in minute biological samples would be a boon to hospital medical laboratories worldwide.
Is Bioinformatics ‘Shortcut’ Faster than PCR Testing?
The researchers say their probes enable a shortcut to detection—even in an infection’s early stages—by “targeting, isolating, and identifying the DNA sequences specifically and simultaneously.”
The probes’ design makes possible simultaneous targeted capture of diverse metagenomics targets, Biocompare explained.
But is it faster than PCR (polymerase chain reaction) testing?
The McMaster scientists were motivated by the “challenges of low signal, high background, and uncertain targets that plague many metagenomic sequencing efforts,” they noted in their paper.
They pointed to challenges posed by PCR testing, a popular technique used for detection of sepsis pathogens as well as, more recently, for SARS-CoV-2, the coronavirus causing COVID-19.
“The (PCR) technique relies on primers that bind to nucleic acid sequences specific to an organism or group of organisms. Although capable of sensitive, rapid detection and quantification of a particular target, PCR is limited when multiple loci are targeted by primers,” the researchers wrote in Cell Reports Methods.
According to LabMedica, “A wide array of metagenomic study efforts are hampered by the same challenge: low concentrations of targets of interest combined with overwhelming amounts of background signal. Although PCR or naive DNA capture can be used when there are a small number of organisms of interest, design challenges become untenable for large numbers of targets.”
Detecting Pathogens Faster, Cheaper, and More Accurately
As part of their study, researchers tested two probe sets:
one to target bacterial pathogens linked to sepsis, and
another to detect coronaviruses including SARS-CoV-2.
They were successful in using the probes to capture a variety of pathogens linked to sepsis and SARS-CoV-2.
“We validated HUBDesign by generating probe sets targeting the breadth of coronavirus diversity, as well as a suite of bacterial pathogens often underlying sepsis. In separate experiments demonstrating significant, simultaneous enrichment, we captured SARS-CoV-2 and HCoV-NL63 [Human coronavirus NL 63] in a human RNA background and seven bacterial strains in human blood. HUBDesign has broad applicability wherever there are multiple organisms of interest,” the researchers wrote in Cell Reports Methods.
The findings also have implications to the environment and wildlife, the researchers noted.
Of course, more research is needed to validate the tool’s usefulness in medical diagnostics. The McMaster University researchers intend to improve HUBDesign’s efficiency but note that probes cannot be designed for unknown targets.
Nevertheless, the advanced application of novel technologies to diagnose of sepsis, which causes 250,000 deaths in the US each year, according to the federal Centers for Disease Control and Prevention, is a positive development worth watching.
The McMaster scientists’ discoveries—confirmed by future research and clinical studies—could go a long way toward ending the dire effects of sepsis as well as COVID-19. That would be a welcome development, particularly for hospital-based laboratories.
Data was used to create a transmission map that tracked the spread of infections among school athletes and helped public health officials determine where best to disrupt exposure
Genomic sequencing played a major role in tracking a SARS-CoV-2 outbreak in a Minnesota school system. Understanding how and where the coronavirus was spreading helped local officials implement restrictions to help keep the public safe. This episode demonstrates how clinical laboratories that can quickly sequence SARS-CoV-2 accurately and at a reasonable cost will give public health officials new tools to manage the COVID-19 pandemic.
Officials in Carver County, Minn., used the power of genomic epidemiology to map the COVID-19 outbreak, and, according to the Star Tribune, revealed how the B.1.1.7 variant of the SARS-CoV-2 coronavirus was spreading through their community.
“The resulting investigation of the Carver County outbreak produced one of the most detailed maps of COVID-19 transmission in the yearlong history of the pandemic—a chart that looks like a fireworks grand finale with infections producing cascading clusters of more infections,” the Star Tribune reported.
Private Labs, Academic Labs, Public Health Labs Must Work Together
For gene sequencing to guide policy and decision making as well as it did in Carver County, coordination, cooperation, and standardization among public, private, and academic medical laboratories is required. Additionally, each institution must report the same information in similar formats for it to be the most useful.
“Maintain Policies That Slow Transmission: Variants will continue to emerge as the pandemic unfolds, but the best chance of minimizing their frequency and impact will be to continue public health measures that reduce transmission. This includes mask mandates, social distancing requirements, and limited gatherings.
“Prioritize Contact Tracing and Case Investigation for Data Collection: Cases of variants of concern should be prioritized for contact tracing and case investigation so that public health officials can observe how the new variant behaves compared to previously circulating versions.
“Develop a Genomic Surveillance Strategy: To guide the public health response, maximize resources, and ensure an equitable distribution of benefits, the US Department of Health and Human Services (HHS) should develop a national strategy for genomic surveillance to implement and direct a robust SARS-CoV-2 genomic surveillance program, drawing on resources and expertise from across the US government.
“Improve Coordination for Genomic Surveillance and Characterization: There are several factors in creating a successful genomic surveillance and characterization network. Clear leadership and coordination will be necessary.”
Practical Application of Genomic Sequencing
Genomic epidemiology uses the genetic sequence of a virus to better understand how and where a given virus is spreading, as well as how it may be mutating. Pathologists understand that this information can be used at multiple levels.
Locally, as was the case in Carver County, Minn., it helps school officials decide whether to halt sports for a time. Nationally, it helps scientists identify “hot spots” and locate mutations of the coronavirus. Using this data, vaccine manufacturers can adjust their vaccines or create boosters as needed.
Will Cost Decreases Provide Opportunities for Clinical Laboratories?
Every year since genomic sequencing became available the cost has decreased. Experts expect that trend to continue. However, as of now, the cost may still be a barrier to clinical laboratories that lack financial resources.
“Purchasing laboratory equipment, computer resources, and staff training requires significant up-front investments. However, the cost per sequence is far less today than it was under earlier methods,” the GAO noted. This is good news for public and independent clinical laboratories. Like Carver County, a significant SARS-CoV-2 outbreak in the future may be averted thanks to genetic sequencing.
“The first piece of the cluster was spotted in a private K-8 school, which served as an incubator of sorts because its students live in different towns and play on different club teams,” the Star Tribune reported.
Finding such clusters may provide opportunities to halt the outbreak. “We can try to cut it off at the knees or maybe get ahead of it,” epidemiologist Susan Klammer with Minnesota Public Health and for childcare and schools, told the Star Tribune.
This story is a good example of how genomic sequencing and surveillance tracking—along with cooperation between public health agencies and clinical laboratories—are critical elements in slowing and eventually halting the spread of COVID-19.