The Predictive Potential of Blood-Based Biomarkers for Alzheimer’s Disease
Paper Review1: A Breakthrough in Diagnosing Alzheimer’s Disease
Biomarkers detected in cerebrospinal fluid (CSF) have been established as an accepted method to diagnose Alzheimer’s Disease (AD). An AD diagnosis, or differentiation from other related neurological disorders, including mild cognitive impairment (MCI) or other forms of dementia, can be made from the quantification of three classic protein biomarkers: tau (N), phosphorylated tau (such as p-tau181) (T), and amyloid b 42/40 ratio (A).
The Question: Are Blood Biomarkers Reliable?
A CSF assay requires a lumbar puncture, an invasive and costly technique. In a new publication, a multi-national collaboration of researchers sought to determine whether blood plasma biomarkers could be predictive of the data provided by a CSF assay. If so, at least in certain instances, physicians could approach AD diagnoses in a stepwise fashion that is less demanding of the patient.
The research team specifically addressed the issue of whether blood biomarkers could accurately differentiate between a nonpathological CSF profile and a specific pathological AD profile. If blood could easily be evaluated for early indicators of neurodegeneration or neuronal damage, it could be an extremely valuable first step in AD detection and could guide physicians and their patients towards the most necessary further testing and treatment strategy.
The task was to compare biomarker profiles from blood plasma with those from CSF.
The team of researchers studied over 300 patients from two independent cohorts. The Barcelona cohort included 150 participants and were patients with a diagnosis of AD, Dementia with Lewy bodies (DLB), frontotemporal lobar degeneration-related syndromes (FTLD), and MCI, or cognitively normal controls. The Montpellier cohort included 161 patients and in addition to AD, DLB, FTLD and MCI, patients from this cohort had also mixed dementia, normal pressure hydrocephalus and Parkinson disease.
Each participant underwent thorough clinical evaluations, including plasma and CSF tests, neuropsychological assessments, and brain imaging. The two cohorts differed significantly in one characteristic: the Barcelona cohort contained far more A+/N–/T– patients. This difference was important because it provided a solid test for the general utility of a plasma-based assay to reflect primary diagnostic differentiation.
About A/T/N Classification
In 2016, Jack et al.2 devised the A/T/N classification for various states of dementia. In this system, a nonpathological profile (A–/T–/N–) is defined as having an amyloid b 42/40 ratio above a particular cutoff value, combined with tau (N) and p-tau181 (T) values below particular thresholds. By the same token, the progressively more concerning amyloid and tau-neurodegenerative profiles would be defined as A+ and N+/T+, respectively.
The Quanterix Simoa® platform was used to acquire plasma levels of amyloid b 42/40 and p-tau181. The Simoa® platform has the ability to detect proteins down to the single molecule level. Many researchers have confirmed the ability of the Simoa® platform to detect AD-related biomarkers in various scenarios.
Simoa® Neurology 3-Plex A and Neurology 4-Plex E kits were used to assess amyloid b 42/40 ratios in the plasma. The Simoa® Neurology 3-Plex A kit was also used to measure total tau. Plasma p-tau 181 levels were measured using Simoa® Homebrew Custom Assay Development.
Blood-Based Biomarkers are Predictive of CSF Profiles
The researchers showed that blood amyloid b and p-tau181 biomarkers performed well in detecting nonpathological amyloid and tau CSF profiles. In these assays, total tau (N) levels were similar between the non-pathological and pathological groups, so this biomarker was not used to assess the quality of the blood-based biomarkers.
Accurately identifying patients with non-pathological profiles can help reduce the need for lumbar puncture, significantly reducing unnecessary medical procedures and related costs.
Two Markers are Better than One
The data shows that the combined use of amyloid b 42/40 and p-tau181 levels offer the best predictive power of the CSF profiles for discriminating the nonpathological profile from other the pathological profiles—with a sensitivity and specificity of ~85%, at least in the Barcelona cohort. Using either variable on its own, particularly the amyloid b 42/40 ratio, was less powerful. Moreover, when a discrimination between two pathological states (for example, T–/N– vs. T+/N+) is the goal, p-tau181 levels were better predictors.
Blood Biomarkers May be the Future of AD Diagnoses
This research reflects the potential of blood biomarkers to be a valuable first step in accurate diagnosis for Alzheimer’s disease. One important ramification of their results is that doctors could forgo a lumbar puncture, and thus spare significant discomfort for the patient and healthcare costs. In this regard, it is likely that a greater number of diagnoses can be made at earlier stages of the disease, where treatments can be more efficacious.
Opening up Doors for AD Research
The data demonstrate the competence of Quanterix’s Simoa® biomarker assay technology in dementia-related research. Only two biomarker assays, amyloid b 42/40 ratio and the p-tau181 may be needed to discriminate between nonpathological and pathological states in two large patient cohorts. The latter biomarker in particular holds great promise for blood-based assays.
Particularly striking is the result of blood p-tau181 outperforming the amyloid b 42/40 ratio as a surrogate for CSF-based assays, confirming the value of detecting phosphorylated tau proteins in blood.
More research is needed to solidify these findings and advance Alzheimer’s Disease research and diagnostics.
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- Delaby, Constance, et al. “Blood amyloid and tau biomarkers as predictors of cerebrospinal fluid profiles.” Journal of Neural Transmission 129.2 (2022): 231-237.
- Jack, Clifford R., et al. “A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers.” Neurology 87.5 (2016): 539-547.
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