Prediction of Alzheimer’s disease biomarker status defined by the ‘ATN framework’ among cognitively healthy individuals: results from the EPAD longitudinal cohort study

Abstract

Background The Amyloid/Tau/Neurodegeneration (ATN) framework has been proposed as a means of evidencing the biological state of Alzheimer’s disease (AD). Predicting ATN status in pre-dementia individuals therefore provides an important opportunity for targeted recruitment into AD interventional studies. We investigated the extent to which ATN-defined biomarker status can be predicted by known AD risk factors as well as vascular-related composite risk scores. Methods One thousand ten cognitively healthy older adults were allocated to one of five ATN-defined biomarker categories. Multinomial logistic regression tested risk factors including age, sex, education, APOE4, family history of dementia, cognitive function, vascular risk indices (high systolic blood pressure, body mass index (BMI), high cholesterol, physical inactivity, ever smoked, blood pressure medication, diabetes, prior cardiovascular disease, atrial fibrillation and white matter lesion (WML) volume), and three vascular-related composite scores, to predict five ATN subgroups; ROC curve models estimated their added value in predicting pathology. Results Age, APOE4, family history, BMI, MMSE and white matter lesions (WML) volume differed between ATN biomarker groups. Prediction of Alzheimer’s disease pathology (versus normal AD biomarkers) improved by 7% after adding family history, BMI, MMSE and WML to a ROC curve that included age, sex and APOE4. Risk composite scores did not add value. Conclusions ATN-defined Alzheimer’s disease biomarker status prediction among cognitively healthy individuals is possible through a combination of constitutional and cardiovascular risk factors but established dementia composite risk scores do not appear to add value in this context.

Prediction of Cognitive Progression in Individuals with Mild Cognitive Impairment Using Radiomics as an Improvement of the ATN System: A Five-Year Follow-Up Study

“…Brain atrophy can reflect the degree of neurodegeneration, and can be detected using MRI. Most previous studies only used a single indicator of the volume or thickness of AD-specific regions, such as the hippocampus and temporal lobe, to evaluate N biomarkers [ 6 7 8 9 10 11 ]. Many other important brain areas and features have been ignored.…”

“…Accessible methods, such as CSF and MRI, are most widely used in clinical practice. However, most previous studies have only used a single indicator in parts of the brain, such as the volume of the hippocampus [ 6 7 8 ], the rating of medial temporal lobe atrophy [ 9 10 11 ], or the thickness of the cerebral cortex [ 6 8 ] to assess the N biomarker. In fact, areas with neural damage caused by AD in the brain include the entire cortex and subcortical nuclei.…”

Secondary Prevention of Dementia: Combining Risk Factors and Scalable Screening Technology

“…We propose that the mechanics of creating an at-risk cohort should be based on models estimating the risk of developing dementia in the next 5–10 years by combining demographic, genetic and cardiovascular severity data. We have previously shown that detecting Alzheimer's disease pathology among cognitively normal individuals can be achieved using models incorporating age, sex and APOE4 carriership (AUC 0.82) (155) and that this can be increased further (AUC 0.84), for example by adding body mass index, a proxy for insulin resistance ( 151 ). Individuals deemed to be at high risk can then be longitudinally (e.g., annually) monitored via plasma biomarkers for signs of AD pathophysiology being triggered (e.g., change in ptau-181 levels).…”

Optimal ATN biomarkers and their role in predicting cognitive progress of mild cognitive impairment

“…Brain atrophy can re ect the degree of neurodegeneration and can be detected by magnetic resonance imaging. Most of the previous studies only used a single indicator of the volume or thickness of AD speci c regions such as hippocampus and temporal lobe to evaluate N biomarker [6][7][8][9][10][11]. Many other important brain areas and features were ignored.…”

“…However, it is not clear which indicators could accurately identify different cognitive states and should be used as the optimal clinical biomarkers. On the other hand, most previous studies only used a single indicator to assess the atrophy of parts of the brain, such as the volume of the hippocampus[6-8], the rating of the medial temporal lobe atrophy [9][10][11] or the thickness of the cerebral cortex [6,8]. In fact, the neural damage of AD on the brain includes all the cortex and most of subcortical nucleus.…”