Side view of a head silhouette in blue showing a cloud around the brain to symbolize Alzheimer's disease, which can be caused by carriage of the APOE4 allele
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Scientists at the University of Pittsburgh have validated a new blood test platform capable of simultaneously measuring more than one hundred biomarkers of Alzheimer’s disease (AD). This new diagnostic called the NULISAseq CNS Disease Panel 120 has the potential to alter the landscape of AD diagnostics by allowing physicians to better understand, in a single test, the complex nature of AD and provide a more comprehensive method of early  detection of neurodegenerative diseases.

Details of the analysis were published in the journal Molecular Neurodegeneration.

“Alzheimer’s disease should not be looked at through one single lens,” said Thomas Karikari, PhD, an assistant professor of psychiatry at Pitt. “Capturing aspects of Alzheimer’s pathology in a panel of clinically validated biomarkers would increase the likelihood of stopping the disease before any cognitive symptoms emerge.”

Current methods for diagnosing AD are resource intensive, requiring patients to undergo multiple visits with a clinician and often burdensome invasive medical procedures and tests. The new diagnostic approach promises to find early signs of neuroinflammation and dysfunction in brain blood vessels as markers of AD development.

A better understanding of the multiple molecular changes in the development of the disease could help clinicians identify people at risk or who are in the very early stage of the disease, but not yet exhibiting the hallmark symptoms of cognitive impairment and changes in memory.

In a proof-of-concept study, Karikari and his team analyzed the performance of NULISAseq, which was developed by Alamar Biosciences, using 113 blood samples from cognitively normal older adults living in an economically underserved area of Southwestern Pennsylvania. This test measures known Alzheimer’s biomarkers, including phosphorylated tau and amyloid beta, as well as changes in 120 proteins linked to neurodegenerative diseases.

The findings, independently evaluated against a series of classical AD biomarkers, revealed that the NULISAseq panel effectively detected several biomarkers correlated with patients’ amyloid positivity status as validated against a series of assays of AD biomarkers. Changes in biomarker profile were also compared with imaging methods of detecting amyloid, tau, and neurodegeneration.

According Karikari, the panel detected several biomarkers that correlated with patients’ amyloid positivity status and changes in amyloid burden over time. The biomarkers were all previously linked to AD, but are today usually analyzed via a cerebrospinal fluid test. The assay also measured other biomarkers associated with neuroinflammation, synaptic function, and vascular health, which had not previously been validated in blood samples.

The new test potentially provides a more accessible method of detecting and tracking disease progression via serial testing using a simple blood draw versus the many current AD tests that need a more invasive procedure to collect cerebrospinal fluid.

The Pitt investigators are now focused on the development of a predictive model that connects biomarker changes identified by NULISAseq with brain autopsy data and cognitive assessments collected over several years, with a goal to create a system for staging Alzheimer’s disease and predicting its progression—information which would also assist in clinical management of AD.

While the study demonstrates the platform’s promise, Karikari noted the need for further validation in larger and more diverse populations. The cohort primarily consisted of non-Hispanic White participants, and broader studies are planned to confirm the findings of the current study across a broader set of demographics

Additionally, the research did not explore cognitive function variations in relation to the biomarkers, as most participants remained cognitively normal throughout the study. Future studies will aim to address these gaps to further evaluate the clinical utility of the identified biomarkers.

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