The NIH’s Researching COVID to Enhance Recovery (RECOVER) Initiative used a cohort study of more than 10,000 individuals with and without previous COVID-19 diagnoses and compared samples using 25 common laboratory tests in hopes a useful biomarker could be identified. They were unsuccessful.
Long COVID—or PASC—is an umbrella term for those with persistent post-COVID infection symptoms that negatively impact quality of life. Though it affects millions worldwide and has been called a major public health burden, the NIH/Langone study scientists noted one glaring problem: PASC is defined differently in the major tests they studied. This makes consistent diagnoses difficult.
The study brought to light possible roadblocks that prevented biomarker identification.
“This study is an important step toward defining long COVID beyond any one individual symptom,” said study author Leora Horwitz, MD (above), director of the Center for Healthcare Innovation and Delivery Science and co-principal investigator for the RECOVER CSC at NYU Langone, in a Langone Health news release. “This definition—which may evolve over time—will serve as a critical foundation for scientific discovery and treatment design.” In the future, clinical laboratories may be tasked with finding combinations of routine and reference tests that, together, enable a more precise and earlier diagnosis of long COVID. (Photo copyright: Yale School of Medicine.)
NIH/Langone Study Details
“The study … examined 25 routinely used and standardized laboratory tests chosen based on availability across institutions, prior literature, and clinical experience. These tests were conducted prospectively in laboratories that are certified by the Clinical Laboratory Improvement Amendments (CLIA). The samples were collected from 10,094 RECOVER-Adult participants, representing a diverse cohort from all over the US,” Inside Precision Medicine reported.
However, the scientists found no clinical laboratory “value” among the 25 tests examined that “reliably indicate previous infection, PASC, or the particular cluster type of PASC,” Inside Precision Medicine noted, adding that “Although some minor differences in the results of specific laboratory tests attempted to differentiate between individuals with and without a history of infection, these findings were generally clinically meaningless.”
“In a cohort study of more than 10,000 participants with and without prior SARS-CoV-2 infection, we found no evidence that any of 25 routine clinical laboratory values provide a reliable biomarker of prior infection, PASC, or the specific type of PASC cluster. … Overall, no evidence was found that any of the 25 routine clinical laboratory values assessed in this study could serve as a clinically useful biomarker of PASC,” the study authors wrote in Annals of Internal Medicine.
In addition to a vague definition of PASC, the NIH/Langone researchers noted a few other potential problems identifying a biomarker from the research.
“Use of only selected biomarkers, choice of comparison groups, if any (people who have recovered from PASC or healthy control participants); duration of symptoms; types of symptoms or phenotypes; and patient population features, such as sex, age, race, vaccination status, comorbidities, and severity of initial infection,” could be a cause for ambiguous results, the scientists wrote.
Future Research
“Understanding the basic biological underpinnings of persistent symptoms after SARS-CoV-2 infection will likely require a rigorous focus on investigations beyond routine clinical laboratory studies (for example, transcriptomics, proteomics, metabolomics) to identify novel biomarkers,” the study authors wrote in Annals of Internal Medicine.
“Our challenge is to discover biomarkers that can help us quickly and accurately diagnose long COVID to ensure people struggling with this disease receive the most appropriate care as soon as possible,” said David Goff, MD, PhD, director of the division of cardiovascular sciences at the NIH’s National Heart, Lung, and Blood Institute, in an NHLBI news release. “Long COVID symptoms can prevent someone from returning to work or school, and may even make everyday tasks a burden, so the ability for rapid diagnosis is key.”
“Approximately one in 20 US adults reported persisting symptoms after COVID-19 in June 2024, with 1.4% reporting significant limitations,” the NIH/Langone scientists wrote in their published study.
Astute clinical laboratory scientists will recognize this as possible future diagnostic testing. There is no shortage of need.
Scientists believe useful new clinical laboratory assays could be developed by better understanding the huge number of ‘poorly researched’ genes and the proteins they build
Researchers have added a new “-ome” to the long list of -omes. The new -ome is the “unknome.” This is significant for clinical laboratory managers because it is part of an investigative effort to better understand the substantial number of genes, and the proteins they build, that have been understudied and of which little is known about their full function.
The Unknome Database includes “thousands of understudied proteins encoded by genes in the human genome, whose existence is known but whose functions are mostly not,” according to a news release.
The database, which is available to the public and which can be customized by the user, “ranks proteins based on how little is known about them,” the PLOS Biology paper notes.
It should be of interest to pathologists and clinical laboratory scientists. The fruit of this research may identify additional biomarkers useful in diagnosis and for guiding decisions on how to treat patients.
“These uncharacterized genes have not deserved their neglect,” said Sean Munro, PhD (above), MRC Laboratory of Molecular Biology in Cambridge, England, in a press release. “Our database provides a powerful, versatile and efficient platform to identify and select important genes of unknown function for analysis, thereby accelerating the closure of the gap in biological knowledge that the unknome represents.” Clinical laboratory scientists may find the Unknome Database intriguing and useful. (Photo copyright: Royal Society.)
Risk of Ignoring Understudied Proteins
Proteomics (the study of proteins) is a rapidly advancing area of clinical laboratory testing. As genetic scientists learn more about proteins and their functions, diagnostics companies use that information to develop new assays. But did you know that researchers tend to focus on only a small fraction of the total number of protein-coding DNA sequences contained in the human genome?
The study of proteomics is primarily interested in the part of the genome that “contains instructions for building proteins … [which] are essential for development, growth, and reproduction across the entire body,” according to Scientific American. These are all protein-coding genes.
Proteomics estimates that there are more than two million proteins in the human body, which are coded for 20,000 to 25,000 genes, according to All the Science.
To build their database, the MRC researchers ranked the “unknome” proteins by how little is known about their functions in cellular processes. When they tested the database, they found some of these less-researched proteins important to biological functions such as development and stress resistance.
“The role of thousands of human proteins remains unclear and yet research tends to focus on those that are already well understood,” said Sean Munro, PhD, MRC Laboratory of Molecular Biology in Cambridge, England, in the news release. “To help address this we created an Unknome database that ranks proteins based on how little is known about them, and then performed functional screens on a selection of these mystery proteins to demonstrate how ignorance can drive biological discovery.”
In the paper, they acknowledged the human genome encodes about 20,000 proteins, and that the application of transcriptomics and proteomics has “confirmed that most of these new proteins are expressed, and the function of many of them has been identified.
“However,” the authors added, “despite over 20 years of extensive effort, there are also many others that still have no known function.”
They also recognized limited resources for research and that a preference for “relative safety” and “well-established fields” are likely holding back discoveries.
The researchers note “significant” risks to continually ignoring unexplored proteins, which may have roles in cell processes, serve as targets for therapies, and be associated with diseases as well as being “eminently druggable,” Genetic Engineering News reported.
Setting up the Unknome Database
To develop the Unknome Database, the researchers first turned to what has already come to fruition. They gave each protein in the human genome a “knownness” score based on review of existing information about “function, conservation across species, subcellular localization, and other factors,” Interesting Engineering reported.
It turns out, 3,000 groups of proteins (805 with a human protein) scored zero, “showing there’s still much to learn within the human genome,” Science News stated, adding that the Unknome Database catalogues more than 13,000 protein groups and nearly two million proteins.
The researchers then tested the database by using it to determine what could be learned about 260 “mystery” genes in humans that are also present in Drosophila (small fruit flies).
“We used the Unknome Database to select 260 genes that appeared both highly conserved and particularly poorly understood, and then applied functional assays in whole animals that would be impractical at genome-wide scale,” the researchers wrote in PLOS Biology.
“We initially selected all genes that had a knownness score of ≤1.0 and are conserved in both humans and flies, as well as being present in at least 80% of available metazoan genome sequences. … After testing for viability, the nonessential genes were then screened with a panel of quantitative assays designed to reveal potential roles in a wide range of biological functions,” they added.
“Our screen in whole organisms reveals that, despite several decades of extensive genetic screens in Drosophila, there are many genes with essential roles that have eluded characterization,” the researchers conclude.
Clinical Laboratory Testing Using the Unknome Database
Future use of the Unknome Database may involve CRISPR technology to explore functions of unknown genes, according to the PLOS Biology paper.
Munro told Science News the research team may work with other research efforts aimed at understanding “mysterious proteins,” such as the Understudied Proteins Initiative.
The Unknome Database’s ability to be customized by others means researchers can create their own “knownness” scores as it applies to their studies. Thus, the database could be a resource in studies of treatments or medications to fight diseases, Chemistry World noted.
According to a statement prepared for Healthcare Dive by SomaLogic, a Boulder, Colorado-based protein biomarker company, diagnostic tests that measure proteins can be applied to diseases and conditions such as:
“The 27-protein model has potential as a ‘universal’ surrogate end point for cardiovascular risk,” the researchers wrote in Science Translational Medicine.
Proteomics definitely has its place in clinical laboratory testing. The development of MRC-LMB’s Unknome Database will help researchers’ increase their knowledge about the functions of more proteins which should in turn lead to new diagnostic assays for labs.
Findings could lead to deeper understanding of why we age, and to medical laboratory tests and treatments to slow or even reverse aging
Can humans control aging by keeping their genes long and balanced? Researchers at Northwestern University in Evanston, Illinois, believe it may be possible. They have unveiled a “previously unknown mechanism” behind aging that could lead to medical interventions to slow or even reverse aging, according to a Northwestern news release.
Should additional studies validate these early findings, this line of testing may become a new service clinical laboratories could offer to referring physicians and patients. It would expand the test menu with assays that deliver value in diagnosing the aging state of a patient, and which identify the parts of the transcriptome that are undergoing the most alterations that reduce lifespan.
It may also provide insights into how treatments and therapies could be implemented by physicians to address aging.
“I find it very elegant that a single, relatively concise principle seems to account for nearly all of the changes in activity of genes that happen in animals as they change,” Thomas Stoeger, PhD, postdoctoral scholar in the Amaral Lab who led the study, told GEN. Clinical laboratories involved in omics research may soon have new anti-aging diagnostic tests to perform. (Photo copyright: Amaral Lab.)
Possible ‘New Instrument’ for Biological Testing
Researchers found clues to aging in the length of genes. A gene transcript length reveals “molecular-level changes” during aging: longer genes relate to longer lifespans and shorter genes suggest shorter lives, GEN summarized.
The phenomenon the researchers uncovered—which they dubbed transcriptome imbalance—was “near universal” in the tissues they analyzed (blood, muscle, bone, and organs) from both humans and animals, Northwestern said.
According to the National Human Genome Research Institute fact sheet, a transcriptome is “a collection of all the gene readouts (aka, transcript) present in a cell” shedding light on gene activity or expression.
The Northwestern study suggests “systems-level” changes are responsible for aging—a different view than traditional biology’s approach to analyzing the effects of single genes.
“We have been primarily focusing on a small number of genes, thinking that a few genes would explain disease,” said Luis Amaral, PhD, Senior Author of the Study and Professor of Chemical and Biological Engineering at Northwestern, in the news release.
“So, maybe we were not focused on the right thing before. Now that we have this new understanding, it’s like having a new instrument. It’s like Galileo with a telescope, looking at space. Looking at gene activity through this new lens will enable us to see biological phenomena differently,” Amaral added.
In their Nature Aging paper, Amaral and his colleagues wrote, “We hypothesize that aging is associated with a phenomenon that affects the transcriptome in a subtle but global manner that goes unnoticed when focusing on the changes in expression of individual genes.
“We show that transcript length alone explains most transcriptional changes observed with aging in mice and humans,” they continued.
In tissues studied, older animals’ long transcripts were not as “abundant” as short transcripts, creating “imbalance.”
“Imbalance” likely prohibited the researchers’ discovery of a “specific set of genes” changing.
As animals aged, shorter genes “appeared to become more active” than longer genes.
In humans, the top 5% of genes with the shortest transcripts “included many linked to shorter life spans such as those involved in maintaining the length of telomeres.”
Conversely, the researchers’ review of the leading 5% of genes in humans with the longest transcripts found an association with long lives.
Antiaging drugs—rapamycin (aka, sirolimus) and resveratrol—were linked to an increase in long-gene transcripts.
“The changes in the activity of genes are very, very small, and these small changes involve thousands of genes. We found this change was consistent across different tissues and in different animals. We found it almost everywhere,” Thomas Stoeger, PhD, postdoctoral scholar in the Amaral Lab who led the study, told GEN.
In their paper, the Northwestern scientists noted implications for creation of healthcare interventions.
“We believe that understanding the direction of causality between other age-dependent cellular and transcriptomic changes and length-associated transcriptome imbalance could open novel research directions for antiaging interventions,” they wrote.
While more research is needed to validate its findings, the Northwestern study is compelling as it addresses a new area of transcriptome knowledge. This is another example of researchers cracking open human and animal genomes and gaining new insights into the processes supporting life.
For clinical laboratories and pathologists, diagnostic testing to reverse aging and guide the effectiveness of therapies may one day be possible—kind of like science’s take on the mythical Fountain of Youth.
Teams from multiple Swedish organizations are investigating the relationship of protein-coding genes to antibodies
Scientists in Sweden are discovering new ways to map the expression of genes in cells, tissues, and organs within the human body thanks to advances in molecular profiling. Their study has successfully combined the analysis of single-cell transcriptomics with spatial antibody-based protein profiling to produce a high-resolution, single-cell mapping of human tissues.
The data links protein-coding genes to antibodies, which could help researchers develop clinical laboratory tests that use specific antibodies to identify and target infectious disease. Might this also lead to a new menu of serology tests that could be used by medical laboratories?
This research is another example of how various databases of genetic and proteomic information—different “omics”—are being combined to produce new understanding of human biology and physiology.
In a Human Protein Atlas (HPA) project press release, Director of the HPA consortium and Professor of Microbiology at Royal Institute of Technology in Stockholm, Mathias Uhlén, PhD, said, “The [Science Advances] paper describes an important addition to the Human Protein Atlas (HPA) which has become one of the world’s most visited biological databases, harboring millions of web pages with information about all the human protein coding genes.”
“We are excited that the new open-access Single Cell Type section constitutes a unique resource for studying the cell type specificity and exact spatial localization of all our proteins”, said Cecilia Lindskog, PhD (above), Head of the HPA Tissue Atlas and Associate Professor, Experimental Pathology, Uppsala University, in the Protein Atlas press release. Medical laboratories may soon have new serology tests to perform that were developed based on HPA data. (Photo copyright: Human Uterus Cell Atlas.)
Distinct Expression Clusters Consistent to Similar Cell Types
To perform their research, the scientists mapped the gene expression profile of all protein-coding genes across different cell types. Their analysis showed that there are distinct expression clusters which are consistent to cell types sharing similar functions within the same organs and between organs of the human body.
The scientists examined data from non-diseased human tissues and organs using three main criteria:
Publicly available raw data from human tissues containing good technical quality with at least 4,000 cells analyzed and at least 20 million read counts by the sequencing for each tissue.
High correlation between pseudo-bulk transcriptomics profile from the scRNA-Seq data and bulk RNA-Seq generated as part of the Human Protein Atlas (HPA).
High correlation between the cluster-specific expression and the expected expression pattern of an extensive selection of marker genes representing well-known tissue- and cell type-specific markers, including both markers from the original publications and additional markers used in pathology diagnostics.
According to the HPA press release, “across all analyzed cell types, almost 14,000 genes showed an elevated expression in particular cell types, out of which approximately 2,000 genes were found to be specific for only one of the cell types.”
The press release also states, “cell types in testis showed the highest numbers of cell type elevated genes, followed by ciliated cells. Interestingly, only 11% of the genes were detected in all analyzed cell types suggesting that the number of essential genes (‘house-keeping’) are surprisingly few.”
Omics-based Biomarkers for Accurate Diagnosis of Disease
The Human Protein Atlas is the largest and most comprehensive database for spatial distribution of proteins in human tissues and cells. It provides a valuable tool for researchers who study and analyze protein localization and expression in human tissues and cells.
Ongoing improvements in gene sequencing technologies are making research of genes more accurate, faster, and more economical. Advances in gene sequencing also could help medical professionals discover more personalized care for patients leading to improved outcomes. A key goal of precision medicine.
One of the conclusions to be drawn from this work is that clinical laboratories and anatomic pathology groups will need to be able to handle immense amounts of data, while at the same time having the capabilities to analyze that data and identify useful patterns that can help diagnose patients earlier and more accurately.
Newly combined digital pathology, artificial intelligence (AI), and omics technologies are providing anatomic pathologists and medical laboratory scientists with powerful diagnostic tools
Add “spatial transcriptomics” to the growing list of “omics” that have the potential to deliver biomarkers which can be used for earlier and more accurate diagnoses of diseases and health conditions. As with other types of omics, spatial transcriptomics might be a new tool for surgical pathologists once further studies support its use in clinical care.
Among this spectrum of omics is spatial transcriptomics, or ST for short.
Spatial Transcriptomics is a groundbreaking and powerful molecular profiling method used to measure all gene activity within a tissue sample. The technology is already leading to discoveries that are helping researchers gain valuable information about neurological diseases and breast cancer.
Marriage of Genetic Imaging and Sequencing
Spatial transcriptomics is a term used to describe a variety of methods designed to assign cell types that have been isolated and identified by messenger RNA (mRNA), to their locations in a histological section. The technology can determine subcellular localization of mRNA molecules and can quantify gene expression within anatomic pathology samples.
In “Spatial: The Next Omics Frontier,” Genetic Engineering and Biotechnology News (GEN) wrote, “Spatial transcriptomics gives a rich, spatial context to gene expression. By marrying imaging and sequencing, spatial transcriptomics can map where particular transcripts exist on the tissue, indicating where particular genes are expressed.”
In an interview with Technology Networks, George Emanuel, PhD, co-founder of life-science genomics company Vizgen, said, “Spatial transcriptomic profiling provides the genomic information of single cells as they are intricately spatially organized within their native tissue environment.
“With techniques such as single-cell sequencing, researchers can learn about cell type composition; however, these techniques isolate individual cells in droplets and do not preserve the tissue structure that is a fundamental component of every biological organism,” he added.
“Direct spatial profiling the cellular composition of the tissue allows you to better understand why certain cell types are observed there and how variations in cell state might be a consequence of the unique microenvironment within the tissue,” he continued. “In this way, spatial transcriptomics allows us to measure the complexity of biological systems along the axes that are most relevant to their function.”
“Although spatial genomics is a nascent field, we are already seeing broad interest among the community and excitement across a range of questions, all the way from plant biology to improving our understanding of the complex interactions of the tumor microenvironment,” George Emanuel, PhD (above), told Technology Networks. Oncologists, anatomic pathologists, and medical laboratory scientists my soon see diagnostics that take advantage of spatial genomics technologies. (Photo copyright: Vizgen.)
According to 10x Genomics, “spatial transcriptomics utilizes spotted arrays of specialized mRNA-capturing probes on the surface of glass slides. Each spot contains capture probes with a spatial barcode unique to that spot.
“When tissue is attached to the slide, the capture probes bind RNA from the adjacent point in the tissue. A reverse transcription reaction, while the tissue is still in place, generates a cDNA [complementary DNA] library that incorporates the spatial barcodes and preserves spatial information.
“Each spot contains approximately 200 million capture probes and all of the probes in an individual spot share a barcode that is specific to that spot.”
“The highly multiplexed transcriptomic readout reveals the complexity that arises from the very large number of genes in the genome, while high spatial resolution captures the exact locations where each transcript is being expressed,” Emanuel told Technology Networks.
Spatial Transcriptomics for Breast Cancer and Neurological Diagnostics
In that paper, the authors wrote “we envision that in the coming years we will see simplification, further standardization, and reduced pricing for the ST protocol leading to extensive ST sequencing of samples of various cancer types.”
Spatial transcriptomics is also being used to research neurological conditions and neurodegenerative diseases. ST has been proven as an effective tool to hunt for marker genes for these conditions as well as help medical professionals study drug therapies for the brain.
“You can actually map out where the target is in the brain, for example, and not only the approximate location inside the organ, but also in what type of cells,” Malte Kühnemund, PhD, Director of Research and Development at 10x Genomics, told Labiotech.eu. “You actually now know what type of cells you are targeting. That’s completely new information for them and it might help them to understand side effects and so on.”
The field of spatial transcriptomics is rapidly moving and changing as it branches out into more areas of healthcare. New discoveries within ST methodologies are making it possible to combine it with other technologies, such as Artificial Intelligence (AI), which could lead to powerful new ways oncologists and anatomic pathologists diagnose disease.
“I think it’s going to be tricky for pathologists to look at that data,” Kühnemund said. “I think this will go hand in hand with the digital pathology revolution where computers are doing the analysis and they spit out an answer. That’s a lot more precise than what any doctor could possibly do.”
Spatial transcriptomics certainly is a new and innovative way to look at tissue biology. However, the technology is still in its early stages and more research is needed to validate its development and results.
Nevertheless, this is an opportunity for companies developing artificial intelligence tools for analyzing digital pathology images to investigate how their AI technologies might be used with spatial transcriptomics to give anatomic pathologists a new and useful diagnostic tool.
