Late‐life cognitive decline is associated with hippocampal volume, above and beyond its associations with traditional neuropathologic indices

Dawe, Robert J.; Yu, Lei; Arfanakis, Konstantinos; Schneider, Julie A.; Bennett, David A.; Boyle, Patricia A.

doi:10.1002/alz.12009

Cited by 45 publications

(44 citation statements)

References 49 publications

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“…A recent study examining hippocampal volumes on postmortem MRI using Religious Orders Study (ROS) and Memory and Aging Project (MAP) data found that, after accounting for demographic and neuropathological variables, the addition of hippocampal volumes to their models explained an additional 5% in the variance of cognitive decline in participants 30 . Our results are in agreement with the ROS/MAP study.…”

Section: Discussionmentioning

confidence: 99%

Dementia is strongly associated with medial temporal atrophy even after accounting for neuropathologies

Woodworth¹,

Sheikh‐Bahaei

Ka³

et al. 2021

Preprint

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Objective: Brain atrophy is associated with degenerative neuropathologies as well as clinical status of dementia. Whether dementia influences atrophy independent of neuropathologies is not known. In this study, we examined the pattern of atrophy associated with dementia while accounting for the most common dementia-related neuropathologies. Methods: We used data from National Alzheimer's Coordinating Center (NACC, N=129) and Alzheimer's Disease Neuroimaging Initiative (ADNI, N=47) participants with suitable in-vivo 3D-T1w MRI and autopsy data. We determined dementia status at visit closest to MRI. We examined the following dichotomized neuropathological variables: Alzheimer's disease neuropathology, hippocampal sclerosis, Lewy Bodies, cerebral amyloid angiopathy, atherosclerosis. Voxel-based morphometry (VBM) identified areas associated with dementia after accounting for neuropathologies. Identified regions of interest were further analyzed. We used multiple linear regression models adjusted for neuropathologies and demographic variables. Results: We found strong associations for dementia with volumes of the hippocampus, amygdala, and parahippocampus (semi-partial correlations≥0.28, P<0.0001 for all regions in NACC; semi-partial correlations≥0.35, P≤0.01 for hippocampus and parahippocampus in ADNI). Dementia status accounted for more unique variance in atrophy in these structures (~8%) compared with neuropathological variables; the only exception was hippocampal sclerosis which accounted for more variance in hippocampal atrophy (10%). Conclusion: Even after accounting for the most common neuropathologies, dementia still had among the strongest correlations with atrophy of medial temporal lobe structures. This suggests that atrophy of the medial temporal lobe is most related to clinical status of dementia as opposed to Alzheimer's or other neuropathologies.

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Section: Discussionmentioning

confidence: 99%

Dementia is strongly associated with medial temporal atrophy even after accounting for neuropathologies

Woodworth¹,

Sheikh‐Bahaei

Ka³

et al. 2021

Preprint

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“…A more direct measurement of hippocampal cellular loss after irradiation can be the assessment of changes in hippocampal volume as a function of dose and time. Hippocampal neuronal and volume loss have been systematically linked to cognitive decline, independently of concomitant neuropathological diseases (17)(18)(19). However, at present, it is unknown to which extent and over which period of time HA-WBRT can prevent hippocampal cellular loss compared to conventional WBRT.…”

Section: Introductionmentioning

confidence: 99%

Hippocampus-Avoidance Whole-Brain Radiation Therapy Is Efficient in the Long-Term Preservation of Hippocampal Volume

et al. 2021

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Background and PurposeWith improved life expectancy, preventing neurocognitive decline after cerebral radiotherapy is gaining more importance. Hippocampal damage has been considered the main culprit for cognitive deficits following conventional whole-brain radiation therapy (WBRT). Here, we aimed to determine to which extent hippocampus-avoidance WBRT (HA-WBRT) can prevent hippocampal atrophy compared to conventional WBRT.Methods and MaterialsThirty-five HA-WBRT and 48 WBRT patients were retrospectively selected, comprising a total of 544 contrast-enhanced T1-weighted magnetic resonance imaging studies, longitudinally acquired within 24 months before and 48 months after radiotherapy. HA-WBRT patients were treated analogously to the ongoing HIPPORAD-trial (DRKS00004598) protocol with 30 Gy in 12 fractions and dose to 98% of the hippocampus ≤ 9 Gy and to 2% ≤ 17 Gy. WBRT was mainly performed with 35 Gy in 14 fractions or 30 Gy in 10 fractions. Anatomical images were segmented and the hippocampal volume was quantified using the Computational Anatomy Toolbox (CAT), including neuroradiological expert review of the segmentations.ResultsAfter statistically controlling for confounding variables such as age, gender, and total intracranial volume, hippocampal atrophy was found after both WBRT and HA-WBRT (p < 10−6). However, hippocampal decline across time following HA-WBRT was approximately three times lower than following conventional WBRT (p < 10−6), with an average atrophy of 3.1% versus 8.5% in the first 2 years after radiation therapy, respectively.ConclusionHA-WBRT is a therapeutic option for patients with multiple brain metastases, which can effectively and durably minimize hippocampal atrophy compared to conventional WBRT.

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“…Images were warped to a previously developed postmortem cerebral hemisphere template, on which we had manually drawn a mask encompassing the hippocampus. We back-transformed this mask onto images in their original space by applying the inverse of the individual-to-template transform to the mask image, as previously described 42 , 43 . After eliminating non-tissue-containing voxels, we extracted the resultant volume of each back-transformed mask, yielding a measure of hippocampal volume.…”

Section: Methodsmentioning

confidence: 99%

Inferring protein expression changes from mRNA in Alzheimer’s dementia using deep neural networks

Tasaki

Avey

et al. 2022

Nat Commun

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Identifying the molecular systems and proteins that modify the progression of Alzheimer’s disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic data, has limited our ability to advance candidate targets that are mainly based on gene expression. Therefore, by using a deep neural network that predicts protein abundance from mRNA expression, here we attempt to track the early protein drivers of ADRD. Specifically, by applying the clei2block deep learning model to 1192 brain RNA-seq samples, we identify protein modules and disease-associated expression changes that were not directly observed at the mRNA level. Moreover, pseudo-temporal trajectory inference based on the predicted proteome became more closely correlated with cognitive decline and hippocampal atrophy compared to RNA-based trajectories. This suggests that the predicted changes in protein expression could provide a better molecular representation of ADRD progression. Furthermore, overlaying clinical traits on protein pseudotime trajectory identifies protein modules altered before cognitive impairment. These results demonstrate how our method can be used to identify potential early protein drivers and possible drug targets for treating and/or preventing ADRD.

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Late‐life cognitive decline is associated with hippocampal volume, above and beyond its associations with traditional neuropathologic indices

Cited by 45 publications

References 49 publications

Dementia is strongly associated with medial temporal atrophy even after accounting for neuropathologies

Dementia is strongly associated with medial temporal atrophy even after accounting for neuropathologies

Hippocampus-Avoidance Whole-Brain Radiation Therapy Is Efficient in the Long-Term Preservation of Hippocampal Volume

Inferring protein expression changes from mRNA in Alzheimer’s dementia using deep neural networks

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