Early amygdala and ERC atrophy linked to 3D reconstruction of rostral neurofibrillary tau tangle pathology in Alzheimer’s disease

Stouffer, Kaitlin; Chen, Claire; Kulason, Sue; Xu, Eileen; Ceritoglu, Can; Albert, Marilyn; Mori, Susumu; Troncoso, Juan C.; Tward, Daniel J.; Miller, Michael I.

doi:10.1016/j.nicl.2023.103374

Cited by 12 publications

(19 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our findings support the latter view, revealing a selective right‐lateralized pattern of neuronal loss, which agrees with our 5 and previous findings by other groups 16 . and Stouffer and colleagues 10 …”

Section: Discussionsupporting

confidence: 94%

“…However, little is still known about the earlier macro‐structural signs of the conversion from cognitively healthy (HC) subjects to MCI. Some evidence has shown that the hippocampus and entorhinal cortex become atrophic in Aβ‐positive cognitively normal individuals 9 or HC subjects 10 . However, no hippocampal alterations have been observed in community‐dwelling individuals lamenting subjective cognitive decline 8 …”

Section: Introductionmentioning

confidence: 99%

“…However, additional primate and human research indicates a more general role of the amygdala in cognition, such as in attention, stimulus value representation, and decision‐making 14 . To date, the evaluation of the early morphometric MRI modifications of the amygdala is still incomplete 10,15–17 …”

Section: Introductionmentioning

confidence: 99%

“…The atrophy of the whole amygdala, associated with cognitive decline, has been demonstrated in individuals with subjective cognitive decline 16,17 or in Aβ‐positive subjects with concurrent cognitive deficits 15 who had no history of long‐term illness and did not meet the criteria for MCI/dementia. A recent MRI study has shown a faster rate of amygdala atrophy in subjects progressing from HC to MCI and from MCI to AD 10 . However, the structural substrates involving the amygdala in these preclinical stages remain unclear.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment

Padulo,

Sestieri,

Punzi

et al. 2023

A&D Transl Res & Clin Interv

View full text Add to dashboard Cite

IntroductionAccumulating evidence indicates that the amygdala exhibits early signs of Alzheimer's disease (AD) pathology. However, it is still unknown whether the atrophy of distinct subfields of the amygdala also participates in the transition from healthy cognition to mild cognitive impairment (MCI).MethodsOur sample was derived from the AD Neuroimaging Initiative 3 and consisted of 97 cognitively healthy (HC) individuals, sorted into two groups based on their clinical follow‐up: 75 who remained stable (s‐HC) and 22 who converted to MCI within 48 months (c‐HC). Anatomical magnetic resonance (MR) images were analyzed using a semi‐automatic approach that combines probabilistic methods and a priori information from ex vivo MR images and histology to segment and obtain quantitative structural metrics for different amygdala subfields in each participant. Spearman's correlations were performed between MR measures and baseline and longitudinal neuropsychological measures. We also included anatomical measurements of the whole amygdala, the hippocampus, a key target of AD‐related pathology, and the whole cortical thickness as a test of spatial specificity.ResultsCompared with s‐HC individuals, c‐HC subjects showed a reduced right amygdala volume, whereas no significant difference was observed for hippocampal volumes or changes in cortical thickness. In the amygdala subfields, we observed selected atrophy patterns in the basolateral nuclear complex, anterior amygdala area, and transitional area. Macro‐structural alterations in these subfields correlated with variations of global indices of cognitive performance (measured at baseline and the 48‐month follow‐up), suggesting that amygdala changes shape the cognitive progression to MCI.DiscussionOur results provide anatomical evidence for the early involvement of the amygdala in the preclinical stages of AD.Highlights Amygdala's atrophy marks elderly progression to mild cognitive impairment (MCI). Amygdala's was observed within the basolateral and amygdaloid complexes. Macro‐structural alterations were associated with cognitive decline. No atrophy was found in the hippocampus and cortex.

show abstract

Section: Discussionsupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment

Padulo,

Sestieri,

Punzi

et al. 2023

A&D Transl Res & Clin Interv

View full text Add to dashboard Cite

show abstract

“…Magnetic Resonance Imaging (MRI) is a valuable, non-invasive tool for studying the macrostructural changes characterizing the AD spectrum [ [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] ; Table 1 ]. Neuroimaging research has primarily focused on medial temporal structures, such as the hippocampus [ [12] , [13] , [14] , [15] , [16] , [17] , [18] ] and, more recently, the amygdala [ [19] , [20] , [21] ]. These regions are of particular interest as they exhibit early signs of tau pathology, a process strongly associated with neurodegeneration and cognitive decline in AD [ 19 , 20 , [22] , [23] , [24] , [25] , [26] , [27] ].…”

Section: Introductionmentioning

confidence: 99%

Atrophy of hippocampal subfields and amygdala nuclei in subjects with mild cognitive impairment progressing to Alzheimer's disease

Punzi,

Sestieri,

Picerni

et al. 2024

Heliyon

View full text Add to dashboard Cite

Applying Joint Graph Embedding to Study Alzheimer’s Neurodegeneration Patterns in Volumetric Data

Tward

2023

Neuroinform

View full text Add to dashboard Cite

Neurodegeneration measured through volumetry in MRI is recognized as a potential Alzheimer’s Disease (AD) biomarker, but its utility is limited by lack of specificity. Quantifying spatial patterns of neurodegeneration on a whole brain scale rather than locally may help address this. In this work, we turn to network based analyses and extend a graph embedding algorithm to study morphometric connectivity from volume-change correlations measured with structural MRI on the timescale of years. We model our data with the multiple random eigengraphs framework, as well as modify and implement a multigraph embedding algorithm proposed earlier to estimate a low dimensional embedding of the networks. Our version of the algorithm guarantees meaningful finite-sample results and estimates maximum likelihood edge probabilities from population-specific network modes and subject-specific loadings. Furthermore, we propose and implement a novel statistical testing procedure to analyze group differences after accounting for confounders and locate significant structures during AD neurodegeneration. Family-wise error rate is controlled at 5% using permutation testing on the maximum statistic. We show that results from our analysis reveal networks dominated by known structures associated to AD neurodegeneration, indicating the framework has promise for studying AD. Furthermore, we find network-structure tuples that are not found with traditional methods in the field.

show abstract

Early amygdala and ERC atrophy linked to 3D reconstruction of rostral neurofibrillary tau tangle pathology in Alzheimer’s disease

Cited by 12 publications

References 77 publications

Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment

Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment

Atrophy of hippocampal subfields and amygdala nuclei in subjects with mild cognitive impairment progressing to Alzheimer's disease

Applying Joint Graph Embedding to Study Alzheimer’s Neurodegeneration Patterns in Volumetric Data

Contact Info

Product

Resources

About