Fig. 7: Hypothetical flow diagram of implications of pattern pathways on the ATN framework. | Nature Communications

Fig. 7: Hypothetical flow diagram of implications of pattern pathways on the ATN framework.

From: A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure

Fig. 7

Cascade of biomarkers can follow a canonical AD pathway, which is the most represented in the ADNI sample (red). The relationships of patterns with amyloid/tau status identifies another large group with the presence of AD pathology and significant or even dominant copathology (orange) as well as groups with suspected non-AD pathology (yellow). These pathways also indicate that certain typical AD neurodegenerative phenotypes may in some cases be driven by copathology. For example, A+T+ nodes are typical for AD; however, there are several potential paths (orange) whereby copathology may be the dominant cause of the neurodegenerative pattern. Path thickness estimates approximate flux through nodes in ADNI. This model is based on distribution of cross-sectional data in A/T/P categories and the assumption that events happen in certain order (A-→A+; T-→T+; P1→P2→P4 and P1→P3→P4).

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