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The new blood-based p-tau biomarkers have shown great promise as clinically useful tools to screen patients with early cognitive symptoms suggestive of Alzheimer’s disease.

Plasma Test Screens for Alzheimer’s with Very High Accuracy

The new test employs a two-step workflow to accurately identify or exclude brain amyloidosis in patients with MCI

University of Gothenburg
Published:Aug 31, 2023
|2 min read
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In recent years, a lot of effort has been put into developing blood biomarkers that could potentially help to identify Alzheimer’s disease (AD). Tau protein, particularly its phosphorylated variant (p-tau), has been the focus of extensive research and developments in the last few years.

The new blood-based p-tau biomarkers, especially a variant called p-tau217, have shown great promise as clinically useful tools to screen patients with memory problems or other early cognitive symptoms suggestive of early Alzheimer’s disease. 

However, a concern has been that classifying early patients into either having “AD or not AD” will still result in a rather high percentage of false-positives (individuals with a positive test result who do not have AD) and false-negatives (individuals with a negative test result who prove to have AD based on other examinations such as amyloid PET scans).

Considering the ethical and psychological concerns induced by possible misdiagnosis, high costs, and potential medical risks of initiating treatments on people not having AD, the scientists at the University of Gothenburg and their colleagues developed a novel strategy for the clinical implementation of blood biomarkers. The study is published in Nature Aging.

A two-step workflow

The two-step model is built on a first step with a diagnostic model (based on levels of plasma p-tau217, age, and APOE ε4 status) to stratify patients with mild cognitive impairment (MCI) for risk of amyloid PET positivity. The second step is based on confirmatory testing with cerebrospinal fluid (CSF) Aβ42/Aβ40 ratio (or amyloid PET) only in those with uncertain outcomes in the first step.

The workflow was evaluated in 348 MCI participants from the Swedish BioFINDER studies (Lund University) and validated in the independent TRIAD cohort (McGill University, Montreal, Canada) also using an independent method for analysis of plasma p-tau217.

Very high accuracy of the model

The model was evaluated at three different thresholding strategies to classify participants into groups with low, intermediate, and high risk for being “Aβ positive” (having AD-type pathology). 

At the stringent lower probability thresholds with 97.5 percent sensitivity (to avoid missing detection of patients who are Aβ positive), as little as 6.6 percent false-negatives were found, while the stringent 97.5 percent specificity (to avoid classifying patients who are Aβ negative as “high risk”) gave only 2.3 percent false-positives.

At the stringent sensitivity/specificity thresholds, 41 percent of patients fell into the intermediate risk group (compared to 29 percent of patients for the 95 percent threshold). Further evaluations of this group with CSF Aβ42/40 ratio showed very good agreement (86 percent) with amyloid PET results. Results were verified in the independent cohort of patients at McGill University.

Clinical applicability of p-tau217 blood test for AD screening

The study presents a blood plasma p-tau217-based two-step model to categorize patients with MCI as having high, low, and intermediate risks of brain amyloidosis and early AD pathology. The blood test applied in step 1 shows very high accuracy in identifying high-risk patients, who (depending on the clinical situation) can either be given a diagnosis and initiated on symptomatic treatments or be referred to specialists for therapeutic intervention in the future.

In the low-risk group, AD can be excluded with a high degree of certainty. The intermediate risk group will only encompass around one-third of patients, which would substantially reduce the need for confirmatory CSF or PET testing at the specialist clinic and, thus, incurring costs.

- This press release was originally published on the University of Gothenburg website