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British Researchers Discover Common Mouth Bacteria That ‘Melts’ Head and Neck Cancers

Bacteria could become new biomarker for testing patients’ reaction to cancer treatments which would give microbiologists and clinical laboratories a new tool for aiding diagnosis and in the selection of appropriate therapies

In a surprising study conducted at King’s College London and Guy’s and St Thomas’ NHS Foundation Trust, British scientists have discovered that a common bacteria found in the mouth may be able to “melt” certain cancers. The bacteria could also be used as a clinical laboratory biomarker to determine how patients may react to specific cancer treatments.

The researchers found that the presence of Fusobacterium can help neutralize head and neck cancers and provide better outcomes in patients with those diseases, according to a Kings College London news release.

Fusobacterium is a genus of anaerobic gram-negative bacteria that are prevalent colonizers of the mouth microbiome. It can be associated with mouth abscesses, periodontal disease, skin ulcers, and Lemierre’s syndrome. The most common species of the genus, Fusobacterium nucleatum, is a marker for the early prediction, diagnosis, and prognosis of colorectal cancer.

“In essence, we found that when you find these bacteria within head and neck cancers, [patients] have much better outcomes,” said Miguel Reis Ferreira, MD, PhD, clinical oncologist at Guy’s and St Thomas’, adjunct senior clinical lecturer at King’s College London and senior author of the study, in the news release. “The other thing that we found is that in cell cultures this bacterium is capable of killing cancer.”

The researchers published their findings in the journal Cancer Communications titled, “Fusobacterium is Toxic for Head and Neck Squamous Cell Carcinoma, and its Presence May Determine a Better Prognosis.”

“This research reveals that these bacteria play a more complex role than previously known in their relationship with cancer—that they essentially melt head and neck cancer cells,” said Miguel Reis Ferreira, MD, PhD (above), clinical oncologist at Guy’s and St Thomas’, adjunct senior clinical lecturer at King’s College London and senior author of the study, in a news release. “However, this finding should be balanced by their known role in making cancers such as those in the bowel get worse.” Should these findings prove sound, clinical laboratories may soon have a new biomarker for testing patients’ reaction to cancer treatments. (Photo copyright: King’s College London.)

Researchers Surprised by Their Findings

The researchers began their research by using computer modeling to identify the types of bacteria to further scrutinize. They then studied the effect of those bacteria on cancer cells by analyzing data on 155 head and neck cancer patients whose tumor information had been submitted to the Cancer Genome Atlas. Head and neck cancers include cancers of the mouth, throat, voice box, nose, and sinuses.

The scientists placed Fusobacterium in petri dishes and kept the bacteria there for a few days. They observed the effect of that bacteria on head and neck cancers and discovered there was a 70% to 90% reduction in the number of viable cancer cells after being infused with the Fusobacterium.

Due to the known correlation between Fusobacterium and colorectal cancer, the team was astonished to find the cancer cells present in head and neck cancers had almost been eradicated.

In the news release, Ferreira said the researchers initially expected the Fusobacterium to boost the growth of the cancers and render those cancers more resistant to treatments like radiotherapy. However, they found the opposite to be true.

“The research in colorectal cancer indicates that these bacteria are bad, and that was kind of ingrained into our minds, and we were expecting to find the same thing,” said Ferreira in a Press Association (PA) interview, The Independent reported. “When we started finding things the other way around, we were brutally surprised.”

Predicting Better Outcomes, Lower Risk of Death

“You put it in the cancer at very low quantities and it just starts killing it very quickly,” Ferreira said in the King’s College London news release. “What we’re finding is that this little bug is causing a better outcome based on something that it’s doing inside the cancer. So we are looking for that mechanism at present, and it should be the theme for a new paper in the very short-term future.”

In addition, the scientists discovered that patients with Fusobacterium within their cancer showed improved survival rates when compared to those without the bacteria. The presence of the bacteria correlated with a 65% reduction in death risk.

“What it could mean is that we can use these bacteria to better predict which patients are more likely to have good or worse outcomes, and based on that, we could change their treatment to make it kinder in the patients that have better outcomes or make it more intense in patients that are more likely to have their cancers come back,” said Ferreira in the PA interview.

“Our findings are remarkable and very surprising. We had a eureka moment when we found that our international colleagues also found data that validated the discovery,” said Anjali Chander, PhD student, senior clinical research fellow, Comprehensive Cancer Center, King’s College London, and lead author of the study in the news release.

More to Learn about Bacteria as Biomarkers

According to the National Cancer Institute (NCI), more than 71,000 people will be diagnosed with one of the major types of head and neck cancer this year in the US and more than 16,000 patients will die from these diseases.

The Global Cancer Observatory (GLOBOCAN) estimates there are about 900,000 new cases of head and neck cancers diagnosed annually worldwide with approximately 450,000 deaths attributed to those cancers every year. GLOBOCAN also claims head and neck cancers are the seventh most common cancer globally.

More research and studies are needed to confirm the virtue of this latest venture into the human microbiome. However, the preliminary results of this study appear promising.

The study of human microbiota continues to bring unexpected surprises, as scientists gain more insights and identify specific strains of bacteria that may have a positive or negative influence on an individual’s health. These discoveries may give microbiologists and clinical laboratories intriguing new biomarkers that could be incorporated into medical tests that aid diagnosis and the selection of appropriate therapies.

—JP Schlingman

Related Information:

Type of Mouth Bacteria ‘Melts’ Some Cancers, Study Finds

Bacteria ‘Melts’ Head and Neck Cancer in Revolutionary Discovery

Fusobacterium is Toxic for Head and Neck Squamous Cell Carcinoma, and its Presence May Determine a Better Prognosis

Bacteria ‘Melts’ Head and Neck Cancer in Revolutionary Discovery

Common Mouth Bacteria Found to ‘Melt’ Certain Cancers in ‘Surprising’ Discovery

Fusobacterium Nucleatum, a Key Pathogenic Factor and Microbial Biomarker for Colorectal Cancer

Detection of Fusobacterium in Oral and Head and Neck Cancer Samples: A Systematic Review and Meta-analysis

King’s College London Researchers Discover Causal Link between Blood Type and COVID-19 Severity; May Provide Clinical Laboratories with a Useful Diagnostic Insight

Findings are ‘a vital first step in discovering potentially valuable targets for development of new [COVID-19] treatments,’ noted co-first author of the study

Researchers at King’s College London (KCL) have determined that levels of certain blood proteins specific to each person’s blood type can be “causally linked” to an increased risk of hospitalization and death from a COVID-19 infection. The scientists also found that a person’s genetics play a key role in establishing the levels of those proteins in the blood.

This is relevant for clinical laboratories—particularly hospital/health system laboratories—because testing for specific proteins in the blood by medical laboratories could help flag incoming patients at higher risk for an acute COVID-19 infection.

Also, “By identifying this suite of proteins, the research has highlighted a number [of] possible targets for drugs that could be used to help treat severe COVID-19,” noted a KCL news release.

Identifying certain drugs that would be more effective for specific individuals or healthcare groups is a core goal of precision medicine.

The KCL researchers published their findings in the journal PLOS Genetics, titled, “Proteome-wide Mendelian Randomization Identifies Causal Links between Blood Proteins and Severe COVID-19.”

Alish Palmos, PhD
“We have used a purely genetic approach to investigate a large number of blood proteins and established that a handful have causal links to the development of severe COVID-19,” said Alish Palmos, PhD (above), Postdoctoral Research Associate, King’s College London Social, Genetic and Developmental Psychiatry Center, and co-first author of the study. “Honing in on this group of proteins is a vital first step in discovering potentially valuable targets for development of new treatments.” Medical laboratories may soon be able to use this knowledge as a way to determine risk for severe COVID-19 hospitalization, as well as to guide decisions on how to use new precision medicine drugs for combating the infection. (Photo copyright: Twitter.)

Genetic Variants Linked to Causality

Since the COVID-19 pandemic began in late 2019, scientists and researchers have been vigorously trying to understand the SARS-CoV-2 coronavirus and determine why some patients have more severe symptoms than others.

To conduct their study, the KCL researchers screened more than 3,000 blood proteins to identify which proteins have a causal link to hospitalization risk, the need for respiratory support, and death from a severe COVID-19 infection.

“Causality between exposure and disease can be established because genetic variants inherited from parent to offspring are randomly assigned at conception similar to how a randomized controlled trial assigns people to groups,” said Vincent Millischer, MD, PhD, Medical University of Vienna and co-first author of the study in the KCL news release.

“In our study, the groups are defined by their genetic propensity to different blood protein levels, allowing an assessment of causal direction from high blood protein levels to COVID-19 severity whilst avoiding influence of environmental effects,” he added. 

The scientists selected genetic variants, known as single nucleotide polymorphisms, that were strongly associated with blood protein levels. They then performed their analysis using Mendelian randomization to test the causal associations of those blood proteins with the development of severe COVID-19 infections.

“Mendelian randomization uses genetic variants associated with a trait [e.g., protein level] and measures their causal effect on disease outcomes, [avoiding] environmental confounding factors, such as lifestyle, being physically ill, etc.,” Alish Palmos, PhD, told Medical News Today. Palmos is a Postdoctoral Research Associate at King’s College London’s Social, Genetic, and Developmental Psychiatry Center and co-first author of the study.

Blood Groups Linked to COVID-19 Hospitalization, Death

One of the most important findings of the KCL research is a causal association between COVID-19 severity and an enzyme called ABO, which determines blood type. This discovery suggests that blood groups perform an instrumental role in whether individuals develop severe forms of the illness. 

“The enzyme helps determine the blood group of an individual and our study has linked it with both risk of hospitalization and the need of respiratory support or death,” said Christopher Hübel, PhD, Postdoctoral Research Associate, King’s College and co-last author of the study in the press release. “Our study does not link precise blood group with risk of severe COVID-19, but since previous research has found that proportion of people who are group A is higher in COVID-19 positive individuals, this suggests that blood group A is more likely candidate for follow-up studies.” 

The KCL researchers uncovered several compelling findings regarding blood proteins and COVID-19, including:

  • The discovery of six blood markers that were significantly associated with an elevated risk of hospitalization.
  • The discovery of nine blood markers that were significantly associated with a decreased risk of hospitalization.
  • Consistent results indicating hospitalization being significantly associated with decreased levels of macrophage inflammatory protein.
  • Five blood markers associated with the need for respiratory support or death.
  • Eight blood markers causally associated with a statistically significantly decreased risk of need for respiratory support or death.
  • Consistent results with respiratory support or death being significantly causally associated with decreased levels of neprilysin.

Developing New COVID-19 Treatments and Preventative Therapies

“What we have done in our study is provide a shortlist for the next stage of research,” said Gerome Breen, PhD, in the KCL news release. Breen is Professor of Psychiatric Genetics at King’s College London’s Institute of Psychiatry, Psychology and Neuroscience, and co-last author of the study.

“Out of 1000s of blood proteins we have whittled it down to about 14 that have some form of causal connection to the risk of severe COVID-19 and present a potentially important avenue for further research to better understand the mechanisms behind COVID-19 with an ultimate aim of developing new treatments but potentially also preventative therapies,” he added. 

Further research and clinical investigation are needed to validate the King’s College London researchers’ findings. However, their insights could result in new clinical laboratory tests and personalized treatments for COVID-19.

JP Schlingman

Related Information:

Genetic Study Reveals Causal Link Between Blood Type and COVID Severity

Proteome-wide Mendelian Randomization Identifies Causal Links Between Blood Proteins and Severe COVID-19

New Research Suggests a Causal Link Between Blood Group and Severe COVID-19

Researchers Identify Six Proteins Linked with Severe COVID-19

COVID: Risk of Severe Disease Could be in Your Blood, New Research Finds

COVID-19 Severity: Blood Group May Influence Risk

A Two Minute Primer on Mendelian Randomization

Researchers Find Health of Human Microbiome Greatly Influenced by Foods We Eat

One key finding of interest to clinical laboratory scientists is that this research study indicates that the human microbiome may more closely correlate with blood markers of metabolic disease than the genome of individuals

In the search for more sensitive diagnostic biomarkers (meaning the ability to detect disease with smaller samples and smaller quantities of the target biomarker), an international team of researchers has teased out a finding that a panel of multiple biomarkers in the human microbiome is more closely correlated with metabolic disease than genetic markers.

The team also discovered that the foods an individual ate had a more powerful impact on their microbiomes than their genes. The study participants included several sets of identical twins. The researchers found that identical twins shared only about 34% of the same gut microbes. People who were unrelated shared 30% of the same gut microbes.

This is a fascinating insight for pathologists and microbiologists involved in the study of the human microbiome for use in development of precision medicine clinical laboratory testing and drug therapies.

Microbiome Markers for Obesity, Heart Disease, and More

The study began in 2018, when an international team of researchers analyzed the gut microbiomes, diets, and blood biomarkers for cardiometabolic health obtained from 1,100 mostly healthy adults in the United Kingdom (UK) and the United States (US). They collected blood samples from the participants before and after meals to examine blood sugar levels, hormones, cholesterol, and inflammation levels. Sleep and activity levels also were monitored. Participants had to wear a continuous glucose monitor for two weeks during the research period.

The scientists discovered that the composition of a healthy gut microbiome is strongly linked to certain foods, food groups, nutrients, and diet composition. They identified markers for obesity, impaired glucose tolerance, and cardiovascular disease in the gut bacteria. 

“When you eat, you’re not just nourishing your body, you’re feeding the trillions of microbes that live inside your gut,” genetic epidemiologist Tim Spector, MD, FmedSCi, told Labroots. Spector is a professor of genetic epidemiology at King’s College London and one of the authors of the study.

The scientists found that a diet rich in nutrient-dense, whole foods was more beneficial to a healthy gut microbiome, which can be an indicator of good health. Individuals who ate minimally processed foods, such as vegetables, nuts, eggs, and seafood were more likely to have healthy gut bacteria than individuals who consumed large amounts of highly processed foods, like juices and other sweetened beverages, processed meats, and refined grains and foods that were high in added sugars and salt.

“It goes back to the age-old message of eating as many whole and unprocessed foods as possible,” Sarah Berry, PhD, a nutrition scientist at King’s College London and a co-author of the study told The New York Times. “What this research shows for the first time is the link between the quality of the food we’re eating, the quality of our microbiomes, and ultimately our health outcomes,” she added.

The researchers concluded that heavily processed foods tend to contain very minimal amounts of fiber, a macronutrient that helps promote good bacteria in the gut microbiome and leads to better metabolic and cardiovascular health.

They found that people who had healthy blood sugar levels following a meal had higher levels of good bacteria called Prevotella copri, a genus of gram-negative bacteria, and Blastocystis, a genus of single-celled heterokont parasites, present in their guts. These bacteria are associated with lower levels of visceral fat, which accumulates around internal organs and increases risk of heart disease.

These “good” microbes also are affiliated with lower levels of inflammation, better blood sugar control, and lower spikes in blood fat and cholesterol levels after meals.

Nicola Segata, PhD

“We were surprised to see such large, clear groups of what we informally call ‘good’ and ‘bad’ microbes emerging from our analysis,” Nicola Segata, PhD (above), told News Medical. Segata is a professor and principal investigator at the Computational Metagenomics Lab at the University of Trento in Italy, and co-author of the study. “It is also exciting to see that microbiologists know so little about many of these microbes that they are not even named yet. This is now a big area of focus for us, as we believe they may open new insights in the future into how we could use the gut microbiome as a modifiable target to improve human metabolism and health,” he added. Pathologists and clinical laboratory scientists who read Dark Daily are already familiar with the plethora of ways the human microbiome is being studied for use in diagnostic testing and drug therapy. (Photo copyright: University of Trento.)

The study also found that different people have wildly varying metabolic responses to the same foods, partially due to the types of bacteria residing in their gut microbiome. The consumption of some foods is better for overall health than other foods, but there is no definitive, one-size-fits-all diet that works for everyone.

“What we found in our study was that the same diet in two different individuals does not lead to the same microbiome, and it does not lead to the same metabolic response. There is a lot of variation,” Andrew Chan, MD, Professor of Medicine at Harvard Medical School, told The New York Times. Chan is also Chief of the Clinical and Translational Epidemiology Unit at Massachusetts General Hospital and co-author of the study.

Small Changes in Diet, Big Impact to Health

The team is now planning a clinical trial to test whether changes in diet can alter levels of good and bad microbes in the gut. If proven to be true, such information could help clinicians design personalized nutritional plans that would enable individuals to improve their gut microbiome and their overall health.

“As a nutritional scientist, finding novel microbes that are linked to specific foods, as well as metabolic health, is exciting,” Berry told News Medical. “Given the highly personalized composition of each individual’s microbiome, our research suggests that we may be able to modify our gut microbiome to optimize our health by choosing the best foods for our unique biology.

“We think there are lots of small changes that people can make that can have a big impact on their health that might be mediated through the microbiome,” Berry told The New York Times.

The researchers published their findings in Nature Medicine, titled, “Microbiome Connections with Host Metabolism and Habitual Diet from 1,098 Deeply Phenotyped Individuals.”

More research and clinical trials are needed before diagnostic tests that use microbiome biomarkers to detect metabolic diseases can be developed. But these early research findings are a sign to pathologists and clinical laboratory managers that microbiome-based assays may come to play a more significant role in the early detection of several metabolic diseases.

JP Schlingman

Related Information:

Connecting Gut Microbes, Diet, and Health

Study Uncovers Strong Links Between a Person’s Diet, Gut Microbes and Health

Microbiome Connections with Host Metabolism and Habitual Diet from 1,098 Deeply Phenotyped Individuals

How the Right Foods May Lead to a Healthier Gut, and Better Health

University of Utah and Sloan Kettering Institute Study Sheds Light on How the Body Recognizes “Good” from Bad Bacteria in the Microbiome

International Study into Ancient Poop Yields Insight into the Human Microbiome, May Produce Useful Insights for Microbiologists

Mayo Clinic Researchers Find Some Bacteria Derail Weight Loss, Suggest Analysis of Individuals’ Microbiomes; a Clinical Lab Test Could Help Millions Fight Obesity

King’s College London Study Identifies Six Distinct ‘Types’ of COVID-19 Illness, Each with a Distinct ‘Cluster’ of Symptoms

The KCL researchers’ new models for predicting which patients will need hospitalization and breathing support may be useful for pathologists and clinical laboratory scientists

One more window into understanding the SARS-CoV-2 coronavirus may have just opened. A British study identified six distinct “clusters” of symptoms that the research scientists believe may help predict which patients diagnosed with COVID-19 will require hospitalization and respiratory support. If further research confirms these early findings, pathologists and medical laboratory managers may gain new tools to diagnose infections faster and more accurately.

Researchers from King’s College London (KCL) analyzed data gathered from the COVID Symptom Study App, a mobile-device application developed by health science company ZOE in collaboration with scientists and physicians at KCL and Massachusetts General Hospital, as well as:

Launched in March in the United Kingdom and extended to the United States and Sweden, the app has attracted more than four million users who track their health and potential COVID symptoms on a daily basis.

Increased Accuracy in Predicting COVID-19 Hospitalizations

On July 17, 2020, the Centers for Disease Control and Prevention (CDC) published “Symptom Profiles of a Convenience Sample of Patients with COVID-19—United States, January–April 2020,” which identifies cough, fever, and shortness of breath as the most typical symptoms of COVID-19. However, the KCL study takes those findings a step further.

KCL researchers identified six distinct “types” of COVID-19, each distinguished by a particular cluster of symptoms. They include headaches, muscle pains, fatigue, diarrhea, confusion, loss of appetite, shortness of breath, and more. The researchers also found that COVID-19 disease progression and outcome also vary significantly between people, ranging from mild flu-like symptoms or a simple rash to severe or fatal conditions.

Using app data logged by 1,600 users in March and April, the researchers developed an algorithm that combined information on age, gender, body mass index (BMI), and pre-existing conditions with recorded symptoms from the onset of the illness through the first five days. The researchers then tested the algorithm using a second independent dataset of 1,000 users, logged in May.

In a news release, the KCL researchers identified the six clusters of symptoms as:

  • Flu-like with No Fever: Headache, loss of smell, muscle pains, cough, sore throat, chest pain, no fever.
  • Flu-like with Fever: Headache, loss of smell, cough, sore throat, hoarseness, fever, loss of appetite.
  • Gastrointestinal: Headache, loss of smell, loss of appetite, diarrhea, sore throat, chest pain, no cough.
  • Severe Level One, Fatigue: Headache, loss of smell, cough, fever, hoarseness, chest pain, fatigue.
  • Severe Level Two, Confusion: Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain.
  • Severe Level Three, Abdominal and Respiratory: Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain, shortness of breath, diarrhea, abdominal pain.

Using the data, the researchers were able to more accurately predict—78.8% versus 69.5%—which of the six symptom clusters placed patients at higher risk of requiring hospitalization and breathing support (ventilation or additional oxygen) than with prediction models based on personal characteristics alone. For example, nearly 50% of the patients in cluster six (Severe Level Three, Abdominal and Respiratory) ended up in the hospital, compared with 16% of those in cluster one (Flu-like with No Fever).

Claire Steves, MD, PhD a Clinical Senior Lecturer at King’s College London
“These findings have important implications for care and monitoring of people who are most vulnerable to severe COVID-19,” Claire Steves, MD, PhD (above left), Clinical Senior Lecturer at King’s College London, said in the KCL news release. “If you can predict who these people are at day five, you have time to give them support and early interventions, such as monitoring blood oxygen and sugar levels, and ensuring they are properly hydrated—simple care that could be given at home, preventing hospitalizations and saving lives.” (Photo copyright: King’s College London.)

According to the Zoe website, the ongoing research is led by:

The researchers published their study findings at medRxiv, titled, “Symptom Clusters in COVID-19: A Potential Clinical Prediction Tool from the COVID Symptom Study App.” The study has not yet undergone peer review.

Encouraging Everyone to Use the COVID-Symptom Study App

The study points out that—broadly speaking—people with cluster four, five, or six COVID-19 symptoms tended to be older and frailer and were more likely to be overweight and have pre-existing conditions, such as diabetes or lung disease, than those with cluster one, two, or three symptoms.

Carole Sudre, PhD a research fellow at King's College London
“Our study illustrates the importance of monitoring symptoms over time to make our predictions about individual risk and outcomes more sophisticated and accurate,” said lead researcher Carole Sudre, PhD (above), a Research Fellow at King’s College London and the study’s lead researcher, in the KCL news release. “This approach is helping us to understand the unfolding story of this disease in each patient so they can get the best care.” (Photo copyright: University College London.)

Tim Spector, FMedSci, Head of the Department of Twin Research and Genetic Epidemiology, and Professor of Genetic Epidemiology at King’s College London, encourages everyone to download the COVID Symptom Study app and help increase the data available to researchers.

“Data is our most powerful tool in the fight against COVID-19,” Spector said in the KCL news release. “We urge everyone to get in the habit of using the app daily to log their health over the coming months, helping us to stay ahead of any local hotspots or a second wave of infections.”

As the body of knowledge surrounding COVID-19 grows, clinical laboratory professionals would be well advised to remain informed on further research regarding not only the potential for COVID-19 variants to exist, but also the evolving guidance on infection prevention and testing.

—Andrea Downing Peck

Related Information:

Six Distinct ‘Types’ of COVID-19 Identified

Symptom Clusters in COVID19: A Potential Clinical Prediction Tool from the COVID Symptom Study App

Symptom Profile of a Convenience Sample of Patients with COVID-19–United States, January-April 2020

Clinical Laboratory Test for Alzheimer’s Disease Gets Ever Closer to Reality

Scientists worldwide engaged in research to develop a biomarker for dementia are predicting success, though some say additional research will be needed

Could a blood test for Alzheimer’s disease soon be on clinical laboratory test menus nationwide? Perhaps so. A recent Associated Press (AP) article that was picked up by NBC News and other healthcare publications reported that experimental test results presented during the Alzheimer’s Association International Conference (AAIC) in July suggest the Holy Grail of dementia tests—one where the specimen can be collected in a doctor’s office during a routine screening exam—may be close at hand.

The AP story noted that “half a dozen research groups gave new results on various experimental tests, including one that seems 88% accurate at indicating Alzheimer’s risk.” And Richard Hodes, MD, Director of the National Institute on Aging, told AP, “In the past year, we’ve seen a dramatic acceleration in progress [on Alzheimer’s tests]. This has happened at a pace that is far faster than any of us would have expected.”

This could be a boon for medical laboratories seeking way to contribute more value to patient care. Especially among Alzheimer’s patients, who account for as many as 70% of all dementia cases.

Plasma Biomarker for Predicting Alzheimer’s

One of the experimental blood tests presented at the AAIC involved a 2018 study into “the potential clinical utility of plasma biomarkers in predicting brain amyloid-β burden at an individual level. These plasma biomarkers also have cost-benefit and scalability advantages over current techniques, potentially enabling broader clinical access and efficient population screening,” the researchers stated an article they published in Nature.

Dark Daily reported on this study in “Researchers in Two Countries Develop Blood Tests That Detect Alzheimer’s Decades Before Symptoms Appear; Could Eventually Give Clinical Laboratories a Diagnostic Tool,” June 4, 2018. The test “measures abnormal versions of the protein [amyloid beta] that forms the plaques in the brain that are the hallmark of Alzheimer’s,” the AP story reported.

AP also reported that Japanese scientists at the AAIC presented results of a validation test conducted on 201 people who had either Alzheimer’s, other types of dementia, or little or no symptoms. They found that the test “correctly identified 92% of people who had Alzheimer’s and correctly ruled out 85% who did not have it, for an overall accuracy of 88%.”

Akinori Nakamura, MD, PhD, of the National Center for Geriatrics and Gerontology in Obu, Japan, was a member of the research team and first author of the research paper. He told the AP that the test results “closely matched those from the top tests used now—three types of brain scans and a mental assessment exam.”

Eric McDade, DO (above), Associate Professor of Neurology at Washington University in St. Louis, told Neurology Today, “The results reported here provide a relatively high level of confidence given that this is a relatively well characterized population with an amyloid PET scan to provide confirmation of a significant level of amyloid plaque burden in the brain.” Could this level of physician confidence lead to a clinical laboratory test based on the plasma biomarker? (Photo copyright: Washington University.)

Koichi Tanaka is a Japanese engineer who won the Nobel prize winner for chemistry. He heads the Koichi Tanaka Research Lab at Shimadzu Corp. (OTCMKTS:SHMZF) in Kyoto, Japan, and was on the team that developed the Amyloid beta biomarker test that was presented at AAIC. He told Bloomberg, “Our finding overturned the common belief that it wouldn’t be possible to estimate amyloid accumulation in the brain from blood. We’re now being chased by others, and the competition is intensifying.”

But Tanaka cautions that the test needs further study before it is ready for clinical use, and that for now “it belongs in the hands of drug developers and research laboratories,” Bloomberg reported.

Other Studies into Developing an Alzheimer’s Biomarker

Alzheimer’s is usually diagnosed after symptoms appear, such as memory loss. To arrive at their diagnoses, doctors often rely on medical history, brain imaging (MRI, CT), PET, and measurement of amyloid in spinal fluid.  

An article published on Alzforum, a website and news service dedicated to the research and treatment for Alzheimer’s and other related disorders, noted a study by King’s College London researchers who, using mass spectrometry, “found a panel of biomarkers that predicted with almost 90% accuracy whether cognitively normal people had a positive amyloid scan.”

Nicholas Ashton, PhD, neuroscientist and Wallenberg Postdoctoral Fellow at University of Gothenburg in Sweden, and first author of the King’s College study, explained that “Amyloid-burden and neurofilament light polypeptide (NFL) peptides were important in predicting Alzheimer’s, but alone they weren’t as predictable as when we combined them with novel proteins related to amyloid PET.”

The researchers published their study earlier this year in Science Advances. “Using an unbiased mass spectrometry approach, we have found and replicated with high accuracy, specificity, and sensitivity a plasma protein classifier reflecting amyloid-beta burden in a cognitively unimpaired cohort,” the researchers wrote.

Meanwhile, researchers at Washington University School of Medicine St. Louis, along with the German Center for Neurodegenerative Diseases, a member of the Helmholtz Association, stated in a news release that a blood test they developed works by detecting leaks of NFL before the onset of symptoms. When the protein is found in cerebrospinal fluid, it could be a sign that Alzheimer’s may develop, as well as point to other neurodegenerative conditions such as multiple sclerosis, brain injury, or stroke, the researchers stated.  

“This is something that would be easy to incorporate into a screening test in a neurology clinic,” Brian Gordon, PhD, Assistant Professor of Radiology at Washington University’s Mallinckrodt Institute of Radiology, and an author of the study, stated in the news release.

These parallel studies into screening for Alzheimer’s by researchers worldwide are intriguing. The favorable results suggest that someday there may be a screen for Alzheimer’s using a clinical laboratory blood test.

With Alzheimer’s affecting nearly six million Americans of all ages, such an assay would enable clinical laboratories to help many people.

—Donna Marie Pocius

Related Information:

Scientists Close in On Blood Test for Alzheimer’s

Advances in the Global Search for Blood Markers for Alzheimer’s Disease and Other Dementias

A Blood Test Can Predict Dementia. Trouble Is, There’s No Cure

Plasma Biomarker for Amyloid Correlates with Alzheimer’s Progression, Study Finds

High Performance Plasma Amyloid-β Biomarkers for Alzheimer’s Disease

Panel Blood Markers Signals Amyloid in Brain

A Plasma Protein Classifier for Predicting Amyloid Burden for Preclinical Alzheimer’s Disease

Blood Test Detects Alzheimer’s Damage Before Symptoms; Test Also May Identify Neurodegeneration in Other Brain Diseases

Blood-Brain Barrier Breakdown is an Early Biomarker of Human Cognitive Dysfunction

Researchers in Two Countries Develop Blood Tests That Detect Alzheimer’s Decades Before Symptoms Appear Could Eventually Give Clinical Laboratories A Diagnostic Tool

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