Novel biomarker found for Alzheimer’s disease

Publish date: January 20, 2022

Author(s):

The study covered in this summary was published in medRxiv.org as a preprint and has not yet been peer reviewed.

Key takeaways

Measurement of the rate of cellular amyloid uptake and metabolic production of toxic amyloid species could be used as novel biomarkers for early and/or differential diagnosis of Alzheimer’s disease (AD).
Estimated beta-amyloid (Aβ42) cellular uptake can be more than two times greater in AD patients compared to cognitively normal subjects. A less pronounced yet increased uptake rate was also observed in patients with late-onset mild cognitive impairment (MCI). This increased uptake may prove to be a key mechanism defining age-related AD progression.
The increased cellular amyloid uptake in AD and LMCI may lead to quicker disease progression, but early-onset MCI may result from increased production of toxic amyloid metabolites.

Additional biomarkers for AD could greatly aid diagnosis and course prediction, as they are currently limited to PET scan analysis of amyloid plaque deposits and concentration of Aβ42 in cerebrospinal fluid (CSF).
Amyloid deposits found by PET have a positive correlation with AD diagnosis. In contrast, CSF-Aβ42 and AD diagnosis or cognitive decline are negatively correlated. Normal cognition (NC) is associated with higher CSF beta-amyloid levels, but previous research has not explained why CSF-Aβ42 levels can be equivalent in patients with NC but high amyloid load and patients with AD and low amyloid load.

The authors of this retrospective study used anonymized data obtained from the Alzheimer’s’s Disease Neuroimaging Initiative (ADNI). ADNI’s goal has been to test whether serial MRI scans, PET scans, biomarkers, and clinical/neuropsychological assessment can be combined to measure the progression of MCI and AD.
Study subjects had either an AD diagnosis or NC and were divided into two groups: low amyloid load and high amyloid load. The fraction of patients with an AD diagnosis was calculated as a function of CSF-Aβ42.
Calculations and statistical comparisons were performed using Microsoft Excel and custom-written C++ programs.

The lowest levels of CSF-Aβ42 correlated with the highest percentage of AD-diagnosed patients, estimated to be 27% in subjects with low amyloid deposit density and 65% in those with high deposit density.
The relationship between CSF-Aβ42 levels and amyloid load can be described using a simple mathematical model: Amyloid concentration in the interstitial cells is equal to the synthesis rate divided by the density of amyloid deposits plus the sum of the rate of amyloid removal through the CSF and the cellular amyloid uptake rate.
AD and late-onset MCI patients had a significantly higher amyloid removal rate compared to NC subjects.
Early-onset MCI patients had Aβ42 turnover similar to that of NC subjects, pointing to a different underlying mechanism such as enzymatic disbalance.

The model used to explain amyloid exchange between the interstitial space and the CSF is oversimplified; the actual process is more complex.
Synthesis and uptake rates of Aβ42 vary throughout areas of the brain. The model assumes a homogeneous distribution within the interstitial compartment.

Research reported in this publication was not supported by any external funding. Data collection and sharing for this project were funded by ADNI.

A version of this article first appeared on Medscape.com.