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Clinical Laboratories and Pathology Groups

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C₂N Diagnostics Releases PrecivityAD, the First Clinical Laboratory Blood Test for Alzheimer’s Disease

The St. Louis-based in vitro diagnostics (IVD) developer is making PrecivityAD available to physicians while awaiting FDA clearance for the non-invasive test

Clinical laboratories have long awaited a test for Alzheimer’s disease and the wait may soon be over. The first blood test to aid physicians and clinical laboratories in the diagnosis of patients with memory and cognitive issues has been released by C₂N Diagnostics of St. Louis. The test measures biomarkers associated with amyloid plaques in the brain—the pathological hallmark of Alzheimer’s.

C₂N Diagnostics was cofounded by David Holtzman, MD, and Randall Bateman, MD, of Washington University School of Medicine in St. Louis. They headed research that led to the PrecivityAD test and are included on a patent the university licensed to C₂N.

In a news release, PrecivityAD describes the laboratory-developed test (LDT) as “a highly sensitive blood test using mass spectrometry and is performed in C₂N’s CLIA-certified laboratory. While the test by itself cannot diagnose Alzheimer’s disease … the test is an important new tool for physicians to aid in the evaluation process.”

PrecivityAD provides physicians with an Amyloid Probability Score (APS) for each patient. For example:

  • A low APS (0-36) is consistent with a negative amyloid PET scan result and, thus, has a low likelihood of amyloid plaques, an indication other causes of cognitive symptoms should be investigated.
  • An intermediate APS (37-57) does not distinguish between the presence or absence of amyloid plaques and indicates further diagnostic evaluation may be needed to assess the underlying cause(s) for the patient’s cognitive symptoms.
  • A high APS (58-100) is consistent with a positive amyloid positron-emission tomography (PET) scan result and, thus, a high likelihood of amyloid plaques. Presence of amyloid plaques is consistent with an Alzheimer’s disease diagnosis in someone who has cognitive decline, but alone is insufficient for a final diagnosis.

The $1,250 test is not currently covered by health insurance or Medicare. However, C₂N Diagnostics has pledged to offer discounts to patients based on income levels.

Jeff Cummings, MD, ScD
Jeff Cummings, MD, ScD (above) Research Professor, Department of Brain Health, University of Nevada, Las Vegas, said in a C₂N Diagnostics press release, “A blood test for Alzheimer’s is a game changer.” While there is no cure for Alzheimer’s, a non-invasive blood test can help providers diagnose patients when their symptoms are mild and often misdiagnosed. “Advances in Alzheimer’s diagnostics are key to more effective identification, diagnosis, and clinical trial recruitment,” he added. Currently, brain changes caused by the disease are most commonly identified through PET scans. (Photo copyright: University of Nevada Las Vegas.)

Additional Research Requested

While C₂N’s PrecivityAD is the first test of its kind to reach the commercial market, it has not received US Food and Drug Administration (FDA) clearance, nor has the company published detailed data on the test’s accuracy. However, the PrecivityAD website says the laboratory-developed test “correctly identified brain amyloid plaque status (as determined by quantitative PET scans) in 86%” of 686 patients, all of whom were older than 60 years of age with subjective cognitive impairment or dementia.

But some Alzheimer’s advocacy groups are tempering their enthusiasm about the breakthrough. Eliezer Masliah, MD, Director of the Division of Neuroscience, National Institute on Aging, told the Associated Press (AP), “I would be cautious about interpreting any of these things,” he said of the company’s claims. “We’re encouraged, we’re interested, we’re funding this work, but we want to see results.”

Heather Snyder, PhD, Vice President, Medical and Scientific Relations at the Alzheimer’s Association told the AP her organization will not endorse a test without FDA clearance. The Alzheimer’s Association also would like to see the test studied in larger and diverse populations. “It’s not quite clear how accurate or generalizable the results are,” she said.

Braunstein defended the decision to make the test for Alzheimer’s immediately available to physicians, asking in the AP article, “Should we be holding that technology back when it could have a big impact on patient care?”

C₂N CEO Joel Braunstein, MD, told the AP C₂N Diagnostics will seek FDA clearance for PrecivityAD and publish study results. Earlier this month, PrecivityAD received CE marking from the European Union, as well as approval for its clinical laboratory to conduct tests for California patients, making it available in 46 states, the District of Columbia, and Puerto Rico, a press release noted.

ADDF Supports C2N’s Alzheimer’s Diagnostic Test

Howard Fillit, MD, Founding Executive Director and Chief Science Officer of the Alzheimer’s Drug Discovery Foundation (ADDF), maintains the first-of-its-kind blood test is an important milestone in Alzheimer’s research. ADDF invested in C₂N’s development of the test.

“Investing in biomarker research has been a core goal for the ADDF because having reliable, accessible, and affordable biomarkers for Alzheimer’s diagnosis is step one in finding drugs to prevent, slow, and even cure the disease,” Fillit said in an ADDF news release.

C₂N is also developing a Brain Health Panel to detect multiple blood-based markers for Alzheimer’s disease that will aid in better disease staging, treatment monitoring, and differential diagnosis.

Second Alzheimer’s Test in Development

Soon medical laboratories may have two different in vitro diagnostic tests for Alzheimer’s disease. On December 2, Fujirebio Diagnostics filed for FDA 510(k) premarket clearance for its Lumipulse G β-Amyloid Ratio (1-42/1-40) test, which looks for biomarkers found in cerebral spinal fluid.

The FDA granted the test Breakthrough Device Designation in February 2019, which may shorten the timeline to approval. The test utilizes Fujirebio’s Lumipulse G1200 instrument system.

“Accurate and earlier intervention will also facilitate the development of new drug therapies, which are urgently needed as the prevalence of Alzheimer’s disease increases with a rapidly aging population globally,” Fujirebio Diagnostics President and CEO Monte Wiltse said in a news release.

The Lumipulse G β-Amyloid test, which is intended for use in patients aged 50 and over presenting with cognitive impairment, has received CE-marking for use in the European Union.

Clinical laboratory managers will want to keep a close eye on rapidly evolving developments in testing for Alzheimer’s disease. It is the sixth leading cause of death in the United States and any clinical laboratory test that could produce an early and accurate diagnosis of Alzheimer’s Disease would become a valuable tool for physicians who treat patients with the symptoms of Alzheimer’s.

—Andrea Downing Peck

Related Information:

Alzheimer’s Breakthrough: C₂N First to Offer a Widely Accessible Blood Test

First Blood Test to Help Diagnose Alzheimer’s Goes on Sale

PrecivityAD Blood Test’s Reach Expands to Europe and California Following Initial Launch; Test Detects Alzheimer’s Disease Pathology

Fujirebio Diagnostics Files 510(k) with FDA for Lumipulse G β-Amyloid Ratio (1-42/1-40) In Vitro Diagnostic Test

Alzheimer’s Drug Discovery Foundation Announces Major Funding Commitment to Validate an Amyloid Blood Test for Non-invasive Early Detection of Alzheimer’s

Alzheimer’s Disease Facts and Figures

Google DeepMind’s AlphaFold Wins CASP14 Competition, Helps Solve Mystery of Protein Folding in a Discovery That Might be Used in New Medical Laboratory Tests

The AI protein-structure-prediction system may ‘revolutionize life sciences by enabling researchers to better understand disease,’ researchers say

Genomics leaders watched with enthusiasm as artificial intelligence (AI) accelerated discoveries that led to new clinical laboratory diagnostic tests and advanced the evolution of personalized medicine. Now Google’s London-based DeepMind has taken that a quantum step further by demonstrating its AI can predict the shape of proteins to within the width of one atom and model three-dimensional (3D) structures of proteins that scientist have been trying to map accurately for 50 years.

Pathologists and clinical laboratory professionals know that it is estimated that there are around 30,000 human genes. But the human proteome has a much larger number of unique proteins. The total number is still uncertain because scientists continue to identify new human proteins. For this reason, more knowledge of the human protein is expected to trigger an expanding number of new assays that can be used by medical laboratories for diagnostic, therapeutic, and patient-monitoring purposes.

DeepMind’s AI tool is called AlphaFold and the protein-structure-prediction system will enable scientists to quickly move from knowing a protein’s DNA sequence to determining its 3D shape without time-consuming experimentation. It “is expected to accelerate research into a host of illnesses, including COVID-19,” BBC News reported.

This protein-folding breakthrough not only answers one of biology’s biggest mysteries, but also has the potential to revolutionize life sciences by enabling researchers to better understand disease processes and design personalized therapies that target specific proteins.

“It’s a game changer,” Andrei Lupas, PhD, Director at the Max Planck Institute for Developmental Biology in Tübingen, Germany, told the journal Nature. “This will change medicine. It will change research. It will change bioengineering. It will change everything.”

AlphaFold Wins Prestigious CASP14 Competition

In November, DeepMind’s AlphaFold won the 14th Community Wide Experiment on Critical Assessment of Techniques for Protein Structure Prediction (CASP14), a biennial competition in which entrants receive amino acid sequences for about 100 proteins whose 3D structures are unknown. By comparing the computational predictions with the lab results, each CASP14 competitor received a global distance test (GDT) score. Scores above 90 out of 100 are considered equal to experimental methods. AlphaFold produced models for about two-thirds of the CASP14 target proteins with GDT scores above 90, a CASP14 press release states.

According to MIT Technology Review, DeepMind’s discovery is significant. That’s because its speed at predicting the structure of proteins is unprecedented and it matched the accuracy of several techniques used in clinical laboratories, including:

Unlike the laboratory techniques, which, MIT noted, are “expensive and slow” and “can take hundreds of thousands of dollars and years of trial and error for each protein,” AlphaFold can predict a protein’s shape in a few days.

“AlphaFold is a once in a generation advance, predicting protein structures with incredible speed and precision,” Arthur D. Levinson, PhD, Founder and CEO of Calico Life Sciences, said in a DeepMind blogpost. “This leap forward demonstrates how computational methods are poised to transform research in biology and hold much promise for accelerating the drug discovery process.”

AlphaFold graph chart
Science reported that AlphaFold, which scored a median of 87—25 points above the next best predictions—did so well that CASP14 organizers worried DeepMind may have been somehow cheated. To validate the results, they asked AlphaFold to complete a “special challenge”—modeling a membrane protein from an ancient species of microbes called archaea, which they had been unable to model satisfactorily using X-ray crystallography. AlphaFold returned a detailed image of a three-part protein with two long helical arms in the middle. “It’s almost perfect,” Andrei Lupas, PhD, Director at the Max Planck Institute for Developmental Biology, told Science. “They could not possibly have cheated on this. I don’t know how they do it.”  (Graphic copyright: DeepMind/Nature.)

Revolutionizing Life Sciences

John Moult, PhD, Professor, University of Maryland Department of Cell Biology and Molecular Genetics, who cofounded CASP in 1994 and chairs the panel, pointed out that scientists have been attempting to solve the riddle of protein folding since Christian Anfinsen, PhD, was awarded the 1972 Nobel Prize in Chemistry for showing it should be possible to determine the shape of proteins based on their amino acid sequence.

“Even tiny rearrangements of these vital molecules can have catastrophic effects on our health, so one of the most efficient ways to understand disease and find new treatments is to study the proteins involved,” Moult said in the CASP14 press release. “There are tens of thousands of human proteins and many billions in other species, including bacteria and viruses, but working out the shape of just one requires expensive equipment and can take years.”

Science reported that the 3D structures of only 170,000 proteins have been solved, leaving roughly 200 million proteins that have yet to be modeled. Therefore, AlphaFold will help researchers in the fields of genomics, microbiomics, proteomics, and other omics understand the structure of protein complexes.

“Being able to investigate the shape of proteins quickly and accurately has the potential to revolutionize life sciences,” Andriy Kryshtafovych, PhD, Project Scientist at University of California, Davis, Genome Center, said in the press release. “Now that the problem has been largely solved for single proteins, the way is open for development of new methods for determining the shape of protein complexes—collections of proteins that work together to form much of the machinery of life, and for other applications.”

Clinical laboratories play a major role in the study of human biology. This breakthrough in genomics research and new insights into proteomics may provide opportunities for medical labs to develop new diagnostic tools and assays that better identify proteins of interest for diagnostic and therapeutic purposes.

—Andrea Downing Peck

Related Information:

AI Solution to a 50-Year-Old Science Challenge Could ‘Revolutionize’ Medical Research

‘It Will Change Everything’: DeepMind’s AI Makes Gigantic Leap in Solving Protein Structures

Protein Structure Prediction Using Multiple Deep Neural Networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

AlphaFold: A Solution to a 50-Year-Old Grand Challenge in Biology

DeepMind’s Protein-Folding AI Has Solved A 50-Year-Old Grand Challenge of Biology

‘The Game Has Changed.’ AI Triumphs at Solving Protein Structures

One of Biology’s Biggest Mysteries ‘Largely Solved’ by AI

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