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Clinical Laboratories and Pathology Groups

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Clinical Laboratories and Pathology Groups

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University of Oxford Researchers Use Spectroscopy and Artificial Intelligence to Create a Blood Test for Chronic Fatigue Syndrome

Spectroscopic technique was 91% accurate in identifying the notoriously difficult-to-diagnose disease suggesting a clinical diagnostic test for CFS may be possible

Most clinical pathologists know that, despite their best efforts, scientists have failed to come up with a reliable clinical laboratory blood test for diagnosing myalgic encephalomyelitis (ME), the condition commonly known as chronic fatigue syndrome (CFS)—at least not one that’s ready for clinical use.

But now an international team of researchers at the University of Oxford has developed an experimental non-invasive test for CFS using a simple blood draw, artificial intelligence (AI), and a spectroscopic technique known as Raman spectroscopy.

The approach uses a laser to identify unique cellular “fingerprints” associated with the disease, according to an Oxford news release.

“When Raman was added to a panel of potentially diagnostic outputs, we improved the ability of the model to identify the ME/CFS patients and controls,” Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University, told Advanced Science News. Morton led the research team along with Wei Huang, PhD, Professor of Biological Engineering at Oxford.

The researchers claim the test is 91% accurate in differentiating between healthy people, disease controls, and ME/CFS patients, and 84% accurate in differentiating between mild, moderate, and severe cases, the new release states.

The researchers published their paper in the journal Advanced Science titled, “Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells.”

Karl Morten, PhD

“This could be a game changer as we are unsure what causes [ME/CFS] and diagnosis occurs perhaps 10 to 20 years after the condition has started to develop,” said Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University. “An early diagnosis might allow us to identify what is going wrong with the potential to fix it before the more long-term degenerative changes are observed.” Though this research may not lead to a simple clinical laboratory blood test for CFS, any non-invasive diagnostic test would enable doctors to help many people. (Photo copyright: Oxford University.)

Need for an ME/CFS Test

The federal Centers for Disease Control and Prevention (CDC) describes ME/CFS as “a serious, long-term illness that affects many body systems,” with symptoms that include severe fatigue and sleep difficulties. Citing an Institute of Medicine (IoM) report, the agency estimates that 836,000 to 2.5 million Americans suffer from the condition but notes that most cases have not been diagnosed.

“One of the difficulties is the complexity of the disease,” said Jonas Bergquist, MD, PhD, Director of the ME/CFS Research Center of Uppsala University in Sweden, told Advanced Science News. “Because it’s a multi-organ disorder, you get symptoms from many different regions of the body with different onsets, though it’s common with post viral syndrome to have different overlapping [symptoms] that disguise the diagnosis.” Bergquist was not involved with the Oxford study.

One key to the Oxford researchers’ technique is the use of multiple artificial intelligence models to analyze the spectral profiles. “These signatures are complex and by eye there are not necessarily clear features that separate ME/CFS patients from other groups,” Morten told Advanced Science News.

“The AI looks at this data and attempts to find features which can separate the groups,” he continued. “Different AI methods find different features in the data. Individually, each method is not that successful at assigning an unknown sample to the correct group. However, when we combine the different methods, we produce a model which can assign the subjects to the different groups very accurately.”

Without a reliable test, “diagnosis of the condition is difficult, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis,” the Oxford press release noted.

But developing such a test has been challenging, Advanced Science News noted.

How Oxford’s Raman Technique Works

Raman spectroscopy uses a laser to determine the “vibrational modes of molecules,” according to the Oxford press release.

“When a laser beam is directed at a cell, some of the scattered photons undergo frequency shifts due to energy exchanges with the cell’s molecular components,” the press release stated. “Raman micro-spectroscopy detects these shifted photons, providing a non-invasive method for single cell analysis. The resulting single cell Raman spectra serve as a unique fingerprint, revealing the intrinsic and biochemical properties and indicating the physiological and metabolic state of the cell.”

The researchers employed the technique on blood samples from 98 subjects, including 61 ME/CFS patients, 16 healthy controls, and 21 controls with multiple sclerosis (MS), Advanced Science reported.

The Oxford scientists focused their attention on peripheral blood mononuclear cells (PBMCs), as previous studies found that these cells showed “reduced energetic function” in ME/CFS patients. “With this evidence, the team proposed that single-cell analysis of PBMCs might reveal differences in the structure and morphology in ME/CFS patients compared to healthy controls and other disease groups such as multiple sclerosis,” the press release states.

Clinical Laboratory Blood Processing and the Oxford Raman Technique

Oxford’s Raman spectroscopic technique “only requires a small blood sample which could be developed as a point-of-care test perhaps from one drop of blood,” the researchers wrote. However, Advanced Science News pointed out that required laser microscopy equipment costs more than $250,000.

In their Advanced Science paper, the researchers note that the test could be made more widely available by transferring blood samples collected by local clinical laboratories to diagnostic centers that have the needed hardware.

“Alternatively, a compact system containing portable Raman instruments could be developed, which would be much cheaper than a standard Raman microscope, and [which] incorporated with microfluidic systems to stream cells through a Raman laser for detection, eliminating the need for lengthy blood sample processing,” the researchers wrote.

They noted that the technique could be adapted to test for other chronic conditions as well, such as MS, fibromyalgia, Lyme disease, and long COVID.

“Our paper is very much a starting point for future research,” Morten told Advanced Science News. “Larger cohorts need to be studied, and if Raman proves useful, we need to think carefully about how a test might be developed.”

Bergquist agreed, stating it’s “not necessarily something you would see in a doctor’s office. It requires a lot of advanced data analysis to use—I still see it as a research methodology. But in the long run, it could be developed into a tool that could be used in a more simplistic way.”

Though a useable diagnostic test may be far off, clinical laboratories should consider how they can aid in ME/CFS research.

—Stephen Beale

Related Information:

First Steps Towards Developing a New Diagnostic Test to Accurately Identify Hallmarks of Chronic Fatigue Syndrome in Blood Cells

First Ever Diagnostic Test for Chronic Fatigue Syndrome Sparks Hope

Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells

Blood Test for Chronic Fatigue Syndrome Found to Be 91% Accurate

Scientists Develop Blood Test for Chronic Fatigue Syndrome

Biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): A Systematic Review

Biomarker for Chronic Fatigue Syndrome Identified

Swedish Researchers Publish High-resolution Single-cell Transcriptomic Map of Human Tissues in Findings That May Advance Diagnostics and Medical Laboratory Testing

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.

Scientists from the KTH Royal Institute of Technology in Stockholm, Uppsala University, Karolinska Institute, and the Karolinska University Hospital in Sweden, the Arctic University of Norway, and other institutions, used both RNA sequencing and antibody-based profiling to formulate a publicly-available map of 192 human cell types.

The researchers published their findings in the peer-reviewed journal Science Advances, titled, “A Single–Cell Type Transcriptomics Map of Human Tissues.” They wrote, “the marked improvements in massive parallel sequencing coupled with single-cell sample preparations and data deconvolution have allowed single-cell RNA sequencing (scRNA-Seq) to become a powerful approach to characterize the gene expression profile in single cells.”

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.”

Cecilia Lindskog, PhD

“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 goal of this venture is to map all the human proteins in cells, tissues, and organs through various “omics” technologies. As Dark Daily wrote in “Spatial Transcriptomics Provide a New and Innovative Way to Analyze Tissue Biology, May Have Value in Surgical Pathology,” omics have the potential to deliver biomarkers which can be used for earlier and more accurate diagnoses of diseases and health conditions. Omics, such as genomics, epigenomics, proteomics, metabolomics, metagenomics, and transcriptomics, are taking greater roles in precision medicine diagnostics as well.

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.

It is another example of how and why those medical laboratories that succeed going forward will have robust laboratory information management systems (LIMS). Forward-looking lab leaders may want to make larger investments in their lab’s health information technology (HIT).

JP Schlingman

Related Information:

A Single Cell Type Map of Human Tissues

A Single-cell Type Transcriptomics Map of Human Tissues

The Human Protein Atlas Press Release – A Single Cell Type Map of Human Tissues

The Human Protein Atlas: A Spatial Map of the Human Proteome

Spatial Transcriptomics Provide a New and Innovative Way to Analyze Tissue Biology, May Have Value in Surgical Pathology

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