Structural Heterogeneity of TDP‐43 Fragments in Alzheimer's Disease and Primary Age‐Related Tauopathy by Artificial Intelligence (AI)–Based 3D Segmentation

ABSTRACT

TAR DNA‐binding protein 43 (TDP‐43) inclusions are defining pathological features of frontotemporal lobar degeneration (FTLD) but are also often observed in Alzheimer's disease (

) and primary age‐related tauopathy (PART). TDP‐43 in is either associated with cognitive impairment or a protective‐life prolonging impact, and yet the localization, cellular and fragment characteristics of TDP‐43 need to be determined. We investigated the relationships between TDP‐43 volumetric inclusion burden in low likelihood (lAD) and definite PART by immunostaining against phosphorylated TDP‐43 (pTDP‐43), TDP‐43 C terminal (TDP‐C) and TDP‐43 N‐terminal (TDP‐N) fragments combined with 3D confocal imaging taken from eight regions: amygdala (basolateral [amygdala‐BL] and centromedial amygdala [amygdala‐CM]), the hippocampus (Cornu Ammonis [CA]‐1, CA2/3, CA4, dentate gyrus [DG] and subiculum [SUB]) and entorhinal cortex (ERC) and artificial intelligence (AI)–based segmentation via object recognition, reconstruction and quantification. We found amygdala‐CM in lAD and PART to have the overall greatest burden of pTDP‐43 whereas TDP‐N burden in amygdala‐BL of PART cases was greater than other TDP‐43 fragments. There was no difference in TDP‐43 burden in hippocampal subfields in PART. However, CA2/3 region showed greater pTDP‐43 burden while TDP‐N stood out in DG and SUB. Multiple comparisons among the groups revealed that TDP‐C was the only fragment showing differences among PART and lAD in CA2/3, DG and SUB regions. Overall, unbiased AI‐based volumetric burden analysis pipeline demonstrated unique fragment aggregation patterns in the neurodegenerative processes of PART and .