An official website of the United States government
Background: Sex differences impact Alzheimer’s disease (AD) neuropathology, but cell-to-network level dysfunctions in the prodromal phase are unclear. Alterations in hippocampal excitation-inhibition balance (EIB) have recently been linked to early AD pathology. Objective: Examine how AD risk factors (age, APOE ɛ4, amyloid-β) relate to hippocampal EIB in cognitively normal males and females using connectome-level measures. Methods: Individuals from the OASIS-3 cohort (age 42–95) were studied (N = 437), with a subset aged 65+ undergoing neuropsychological testing (N = 231). Results: In absence of AD risk factors (APOE ɛ4/Aβ+), whole-brain EIB decreases with age more significantly in males than females (p = 0.021, β= –0.007). Regression modeling including APOE ɛ4 allele carriers (Aβ–) yielded a significant positive AGE-by-APOE interaction in the right hippocampus for females only (p = 0.013, β= 0.014), persisting with inclusion of Aβ+ individuals (p = 0.012, β= 0.014). Partial correlation analyses of neuropsychological testing showed significant associations with EIB in females: positive correlations between right hippocampal EIB with categorical fluency and whole-brain EIB with the Trail Making Test (p < 0.05). Conclusions: Sex differences in EIB emerge during normal aging and progresses differently with AD risk. Results suggest APOE ɛ4 disrupts hippocampal balance more than amyloid in females. Increased excitation correlates positively with neuropsychological performance in the female group, suggesting a duality in terms of potential beneficial effects prior to cognitive impairment. This underscores the translational relevance of APOE ɛ4 related hyperexcitation in females, potentially informing therapeutic targets or early interventions to mitigate AD progression in this vulnerable population.
more »
« less
In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
Abstract Neuroimaging in the preclinical phase of Alzheimer’s disease provides information crucial to early intervention, particularly in people with a high genetic risk. Metabolic network modularity, recently applied to the study of dementia, is increased in Alzheimer’s disease patients compared with controls, but network modularity in cognitively unimpaired elderly with various risks of developing Alzheimer’s disease needs to be determined. Based on their 5-year cognitive progression, we stratified 117 cognitively normal participants (78.3 ± 4.0 years of age, 52 women) into three age-matched groups, each with a different level of risk for Alzheimer’s disease. From their fluorodeoxyglucose PET we constructed metabolic networks, evaluated their modular structures using the Louvain algorithm, and compared them between risk groups. As the risk for Alzheimer’s disease increased, the metabolic connections among brain regions weakened and became more modular, indicating network fragmentation and functional impairment of the brain. We then set out to determine the correlation between regional brain metabolism, particularly in the modules derived from the previous analysis, and the regional expression of Alzheimer-risk genes in the brain, obtained from the Allen Human Brain Atlas. In all risk groups of this elderly population, the regional brain expression of most Alzheimer-risk genes showed a strong correlation with brain metabolism, particularly in the module that corresponded to regions of the brain that are affected earliest and most severely in Alzheimer’s disease. Among the genes, APOE and CD33 showed the strongest negative correlation and SORL1 showed the strongest positive correlation with brain metabolism. The Pearson correlation coefficients remained significant when contrasted against a null-hypothesis distribution of correlation coefficients across the whole transcriptome of 20 736 genes (SORL1: P = 0.0130; CD33, P = 0.0136; APOE: P = 0.0093). The strong regional correlation between Alzheimer-related gene expression in the brain and brain metabolism in older adults highlights the role of brain metabolism in the genesis of dementia.
more »
« less
- Award ID(s):
- 2019745
- PAR ID:
- 10417199
- Date Published:
- Journal Name:
- Brain Communications
- Volume:
- 4
- Issue:
- 5
- ISSN:
- 2632-1297
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Alzheimer’s disease has a prolonged asymptomatic phase during which pathological changes accumulate before clinical symptoms emerge. This study aimed to stratify the risk of clinical disease to inform future disease-modifying treatments. Cerebrospinal fluid analysis from participants in the Emory Healthy Brain Study was used to classify individuals based on amyloid beta 42 (Aβ42), total tau (tTau) and phosphorylated tau (pTau) levels. Cognitively normal (CN), biomarker-positive (CN)/BM+individuals were identified using a tTau: Aβ42 ratio > 0.24, determined by Gaussian mixture models. CN/BM+ individuals (n = 134) were classified as having asymptomatic Alzheimer’s disease (AsymAD), while CN, biomarker-negative (CN/BM−) individuals served as controls (n = 134). Cognitively symptomatic, biomarker-positive individuals with an Alzheimer’s disease diagnosis confirmed by the Emory Cognitive Neurology Clinic were labelled as Alzheimer’s disease (n = 134). Study groups were matched for age, sex, race and education. Cerebrospinal fluid samples from these matched Emory Healthy Brain Study groups were analysed using targeted proteomics via selected reaction monitoring mass spectrometry. The targeted cerebrospinal fluid panel included 75 peptides from 58 unique proteins. Machine learning approaches identified a subset of eight peptides (ADQDTIR, AQALEQAK, ELQAAQAR, EPVAGDAVPGPK, IASNTQSR, LGADMEDVCGR, VVSSIEQK, YDNSLK) that distinguished between CN/BM− and symptomatic Alzheimer’s disease samples with a binary classifier area under the curve performance of 0.98. Using these eight peptides, Emory Healthy Brain Study AsymAD cases were further stratified into ‘Control-like’ and ‘Alzheimer’s disease-like’ subgroups, representing varying levels of risk for developing clinical disease. The eight peptides were evaluated in an independent dataset from the Alzheimer’s Disease Neuroimaging Initiative, effectively distinguishing CN/BM− from symptomatic Alzheimer’s disease cases (area under the curve = 0.89) and stratifying AsymAD individuals into control-like and Alzheimer’s disease-like subgroups (area under the curve = 0.89). In the absence of matched longitudinal data, an established cross-sectional event-based disease progression model was employed to assess the generalizability of these peptides for risk stratification. In summary, results from two independent modelling methods and datasets demonstrate that the identified eight peptides effectively stratify the risk of progression from asymptomatic to symptomatic Alzheimer’s disease.more » « less
-
null (Ed.)Abstract Sleep disruption has been associated with increased beta-amyloid deposition and greater risk for later development of Alzheimer’s disease. Studies indicate that sleep disturbance correlates with regional brain volumes, but data are limited. We sought to determine the effect of sleep disturbance on regional brain volumes by cognitive and apolipoprotein e (APOE) e4 status. We conducted a secondary analysis of the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set using complete structural imaging data from 1,371 participants (mean age: 70.5; SD: 11.7). Multiple linear regression was used to estimate the adjusted effect of sleep disturbance (via Neuropsychiatric Inventory Questionnaire) on regional brain volumes through measurement of 30 structural MRI biomarkers. Sleep disruption was associated with greater volumes in the right and left lateral ventricles and greater volume of total white matter hyperintensities (p<.05). Lower mean volumes in total brain, total gray matter, and total cerebrum grey matter volumes, and in 12 hippocampal, frontal, parietal, and temporal lobe volumes were observed among participants who reported sleep disturbance. Males, Hispanic participants, and those with less education were more likely to report sleep disruption. Cognitive status moderated the relationship between sleep disturbance and lateral ventricular volumes, while APOE e4 moderated the effect between sleep disturbance and parietal lobe volumes. These findings suggest that disrupted sleep is associated with atrophy across multiple brain regions and ventricular hydrocephalus ex vacuo, after controlling for intracranial volume and demographic covariates. The influence of cognition and APOE e4 status indicates that this relationship is affected by co-occurring physiological processes.more » « less
-
Background and Objectives: Prediction of decline to dementia using objective biomarkers in high-risk patients with amnestic mild cognitive impairment (aMCI) has immense utility. Our objective was to use multimodal MRI to (1) determine whether accurate and precise prediction of dementia conversion could be achieved using baseline data alone, and (2) generate a map of the brain regions implicated in longitudinal decline to dementia. Methods: Participants meeting criteria for aMCI at baseline ( N = 55) were classified at follow-up as remaining stable/improved in their diagnosis ( N = 41) or declined to dementia ( N = 14). Baseline T1 structural MRI and resting-state fMRI (rsfMRI) were combined and a semi-supervised support vector machine (SVM) which separated stable participants from those who decline at follow-up with maximal margin. Cross-validated model performance metrics and MRI feature weights were calculated to include the strength of each brain voxel in its ability to distinguish the two groups. Results: Total model accuracy for predicting diagnostic change at follow-up was 92.7% using baseline T1 imaging alone, 83.5% using rsfMRI alone, and 94.5% when combining T1 and rsfMRI modalities. Feature weights that survived the p < 0.01 threshold for separation of the two groups revealed the strongest margin in the combined structural and functional regions underlying the medial temporal lobes in the limbic system. Discussion: An MRI-driven SVM model demonstrates accurate and precise prediction of later dementia conversion in aMCI patients. The multi-modal regions driving this prediction were the strongest in the medial temporal regions of the limbic system, consistent with literature on the progression of Alzheimer’s disease.more » « less
-
null (Ed.)Abstract Anxiety has been associated with greater risk of Alzheimer’s disease (AD) and existing research has identified structural differences in regional brain tissue in anxious compared to healthy samples, but results have been variable and somewhat inconsistent. We sought to determine the effect of anxiety on regional brain volumes by cognitive and apolipoprotein e (APOE) e4 status using data from a large, national dataset. A secondary analysis of the National Alzheimer’s Coordinating Center Uniform (NACC) Data Set was conducted using complete MRI data from 1,371 participants (mean age: 70.5; SD: 11.7). Multiple linear regression was used to estimate the adjusted effect of anxiety (via the Neuropsychiatric Inventory Questionnaire) on regional brain volumes through measurement of 30 structural MRI biomarkers. Anxiety was associated with lower total brain and total cortical gray matter volumes and increased lateral ventricular volume (p<.05). Lower mean volumes were also observed in all hippocampal, frontal lobe, parietal lobe, temporal lobe, and right occipital lobe volumes among participants who reported anxiety. Conversely, greater ventricular volumes were also correlated with anxiety. Findings suggest that anxiety is associated with significant atrophy in multiple brain regions and ventricular enlargement, even after controlling for intracranial volume and demographic covariates. Anxiety-related changes to brain morphology may contribute to greater AD risk.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/braincomms/fcac216
