[IC-P-133]: A GLOBAL MEASURE OF BRAIN AGE IS MORE SENSITIVE THAN HIPPOCAMPAL VOLUME IN PREDICTING INCIDENT MILD COGNITIVE IMPAIRMENT IN COMMUNITY-LIVING INDIVIDUALS

Background and Objectives: A complex network of axonal pathways interlinks the human brain cortex. Brain networks are not distributed evenly, and brain regions making more connections with other parts are defined as brain hubs. Our objective was to analyze brain hub region volume and cortical thickness and determine the association with cognitive assessment scores in patients with mild cognitive impairment (MCI) and dementia. Materials and Methods: In this cross-sectional study, we included 11 patients (5 mild cognitive impairment; 6 dementia). All patients underwent neurological examination, and Montreal Cognitive Assessment (MoCA) test scores were recorded. Scans with a 3T MRI scanner were done, and cortical thickness and volumetric data were acquired using Freesurfer 7.1.0 software. Results: By analyzing differences between the MCI and dementia groups, MCI patients had higher hippocampal volumes (p < 0.05) and left entorhinal cortex thickness (p < 0.05). There was a significant positive correlation between MoCA test scores and left hippocampus volume (r = 0.767, p < 0.01), right hippocampus volume (r = 0.785, p < 0.01), right precuneus cortical thickness (r = 0.648, p < 0.05), left entorhinal cortex thickness (r = 0.767, p < 0.01), and right entorhinal cortex thickness (r = 0.612, p < 0.05). Conclusions: In our study, hippocampal volume and entorhinal cortex showed significant differences in the MCI and dementia patient groups. Additionally, we found a statistically significant positive correlation between MoCA scores, hippocampal volume, entorhinal cortex thickness, and right precuneus. Although other brain hub regions did not show statistically significant differences, there should be additional research to evaluate the brain hub region association with MCI and dementia.

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12-year prediction of mild cognitive impairment aided by Alzheimer’s brain signatures at mean age 56

Brain Communications ◽

10.1093/braincomms/fcab167 ◽

2021 ◽

Author(s):

McKenna E Williams ◽

Jeremy A Elman ◽

Linda K McEvoy ◽

Ole A Andreassen ◽

Anders M Dale ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Mean Diffusivity ◽

Area Under The Curve ◽

Polygenic Risk Score ◽

Age Difference ◽

Cognitively Normal ◽

Brain Age

Abstract Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer’s disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Toward that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: 1) a validated MRI-derived Alzheimer’s disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and 2) a novel gray matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246–367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51–60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer’s disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61–71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply aging-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P=0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently-derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step toward improving very early identification of Alzheimer’s disease risk and the potential value of mean diffusivity and/or multimodal brain signatures.

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Whole-exome sequencing and imaging genetics identify functional variants for rate of change in hippocampal volume in mild cognitive impairment

Molecular Psychiatry ◽

10.1038/mp.2013.24 ◽

2013 ◽

Vol 18 (7) ◽

pp. 781-787 ◽

Cited By ~ 54

Author(s):

K Nho ◽

◽

J J Corneveaux ◽

S Kim ◽

H Lin ◽

...

Keyword(s):

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Hippocampal Volume ◽

Imaging Genetics ◽

Rate Of Change ◽

Functional Variants ◽

Whole Exome

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Differences in cognitive ability and hippocampal volume between Alzheimer’s disease, amnestic mild cognitive impairment, and healthy control groups, and their correlation

Neuroscience Letters ◽

10.1016/j.neulet.2016.03.044 ◽

2016 ◽

Vol 620 ◽

pp. 115-120 ◽

Cited By ~ 9

Author(s):

Mi-Hyun Choi ◽

Hyung-Sik Kim ◽

Seon-Young Gim ◽

Woo-Ram Kim ◽

Kyung-Ryul Mun ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Ability ◽

Hippocampal Volume ◽

Amnestic Mild Cognitive Impairment ◽

Control Groups ◽

Healthy Control

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The Use of a Virtual Reality Platform for the Assessment of the Memory Decline and the Hippocampal Neural Injury in Subjects with Mild Cognitive Impairment: The Validity of Smart Aging Serious Game (SASG)

Journal of Clinical Medicine ◽

10.3390/jcm9051355 ◽

2020 ◽

Vol 9 (5) ◽

pp. 1355 ◽

Cited By ~ 3

Author(s):

Monia Cabinio ◽

Federica Rossetto ◽

Sara Isernia ◽

Francesca Lea Saibene ◽

Monica Di Cesare ◽

...

Keyword(s):

Virtual Reality ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Neuronal Degeneration ◽

Linear Regression Analysis ◽

Hippocampal Volume ◽

Volume Measurement ◽

Serious Game ◽

Cognitive Profile ◽

Discrimination Ability

Due to the lack of pharmacological treatment for dementia, timely detection of subjects at risk can be of seminal importance for preemptive rehabilitation interventions. The aim of the study was to determine the usability of the smart aging serious game (SASG), a virtual reality platform, in assessing the cognitive profile of an amnestic mild cognitive impairment (aMCI) population, its validity in discriminating aMCI from healthy controls (HC), and in detecting hippocampal degeneration, a biomarker of clinical progression towards dementia. Thirty-six aMCI and 107 HC subjects were recruited and administered the SASG together with a neuropsychological evaluation. All aMCI and 30 HC subjects performed also an MRI for hippocampal volume measurement. Results showed good usability of the SASG despite the low familiarity with technology in both groups. ROC curve analyses showed similar discriminating abilities for SASG and gold standard tests, and a greater discrimination ability compared to non-specific neuropsychological tests. Finally, linear regression analysis revealed that the SASG outperformed the Montreal cognitive assessment test (MoCA) in the ability to detect neuronal degeneration in the hippocampus on the right side. These data show that SASG is an ecological task, that can be considered a digital biomarker providing objective and clinically meaningful data about the cognitive profile of aMCI subjects.

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