Longitudinal atrophy in early Braak regions in preclinical Alzheimer's disease

Abstract

A major focus of Alzheimer's disease (AD) research has been finding sensitive outcome measures to disease progression in preclinical AD, as intervention studies begin to target this population. We hypothesize that tailored measures of longitudinal change of the medial temporal lobe (MTL) subregions (the sites of earliest cortical tangle pathology) are more sensitive to disease progression in preclinical AD compared to standard cognitive and plasma NfL measures. Longitudinal T1-weighted MRI of 337 participants were included, divided into amyloid-β negative (Aβ−) controls, cerebral spinal fluid p-tau positive (T+) and negative (T−) preclinical AD (Aβ+ controls), and early prodromal AD. Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI using a novel pipeline. Unbiased change rates of subregions were estimated using MRI scans within a 2-year-follow-up period. Experimental results showed that longitudinal atrophy rates of all MTL subregions were significantly higher for T+ preclinical AD and early prodromal AD than controls, but not for T− preclinical AD. Posterior hippocampus and BA35 demonstrated the largest group differences among hippocampus and MTL cortex respectively. None of the crosssectional MTL measures, longitudinal cognitive measures (PACC, ADAS-Cog) and cross-sectional or longitudinal plasma NfL reached significance in preclinical AD. In conclusion, longitudinal atrophy measurements reflect active neurodegeneration and Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu

Medial Temporal Lobe Subregional Atrophy in Aging and Alzheimer's Disease: A Longitudinal Study

“…In line with previous findings, MTL subregional atrophy differed along the Alzheimer's continuum, with later clinical stages being more affected (Wolk et al, 2017;Xie et al, 2019Xie et al, , 2020. Specifically, baseline volumes were significantly greater in CU older adults (either Aβ− or Aβ+) vs. Aβ+ AD patients for all MTL subregions, and vs. Aβ+ MCI patients only for HPC, aHPC, pHPC and ERC.…”

“…Previous cross-sectional findings are inconsistent regarding the potential ability of MTL subregional volumes to differentiate between Aβ− and Aβ+ CU older adults. Some studies report no differences (Xie et al, 2019) while others found smaller BA 35 in Aβ+ CU (Wolk et al, 2017;Xie et al, 2020). Because these results were derived from cortical thickness measurements rather than volumetric measurements, we suppose that cortical thickness may be more sensitive in tracking early signs of AD, especially since extra-hippocampal volume measures are biased by the depth of the collateral sulcus which varies among individuals (Feczko et al, 2009;Schwarz et al, 2016;Berron et al, 2017).…”

“…In addition, hippocampal volumetry might be a relevant tool to predict the conversion to AD-dementia in patients with MCI (Pennanen et al, 2004;Apostolova et al, 2006;Devanand et al, 2007;Henneman et al, 2009;Brueggen et al, 2015). As neuropathological changes are known to start several years before symptom onset, more and more studies have focused on the preclinical stage of AD-defined as amyloidpositive (Aβ+) cognitively unimpaired (CU) individuals (Jack et al, 2018)- (Miller et al, 2013;Fortea et al, 2014;Pegueroles et al, 2017;Pettigrew et al, 2017); findings are sparse with only a few studies showing medial temporal lobe subregional atrophy in Aβ+ compared to amyloid-negative (Aβ−) CU (Wolk et al, 2017;Xie et al, 2020), while others have found no difference (Xie et al, 2019).…”

“…To date, most of the investigations on MTL structural alterations were performed using cross-sectional designs and were mainly limited to the HPC and ERC (Juottonen et al, 1998;Du et al, 2001Du et al, , 2003Pennanen et al, 2004;Barnes et al, 2009;Wisse et al, 2014;Pini et al, 2016). Given that MTL subregions are affected heterogeneously in AD (Braak and Braak, 1995;Krumm et al, 2016;Xie et al, 2020), longitudinal designs accounting for inter-individual variability and including usually neglected MTL subregions such as the PRC and PHC might enhance the clinical utility of these neurodegeneration biomarkers. In addition, automatic procedures recently emerged to segment MTL subregions from standard T1-weighted MRI scans (Pipitone et al, 2014;Iglesias et al, 2015;Xie et al, 2019), and appear promising in characterizing AD-related changes in clinical routines as MRI images are more accessible compared with other neuroimaging techniques which are more expensive and invasive.…”

3D Mapping of Neurofibrillary Tangle Burden in the Human Medial Temporal Lobe

“…However, tau PET is not a direct measure of NFT burden in the brain, since it has limited spatial resolution and has variable binding to multiple types of tau pathology. Structural magnetic resonance imaging (MRI) studies examining patterns of neurodegeneration in the MTL also suggest that, while BA35 is clearly impacted early in the disease, other MTL structures undergo similar rates of atrophy [77, 79]. The analysis of in vivo PET and MRI is significantly hampered by the lack of a comprehensive “gold standard” postmortem reference that would characterize the distribution and spread of NFT pathology in 3D and would be compatible with tools used analyze in vivo PET and MRI data.…”