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Impaired default network functional connectivity in autosomal dominant Alzheimer disease
Abstract
To investigate default mode network (DMN) functional connectivity MRI (fcMRI) in a large cross-sectional cohort of subjects from families harboring pathogenic presenilin-1 (PSEN1), presenilin-2 (PSEN2), and amyloid precursor protein (APP) mutations participating in the Dominantly Inherited Alzheimer Network.
Eighty-three mutation carriers and 37 asymptomatic noncarriers from the same families underwent fMRI during resting state at 8 centers in the United States, United Kingdom, and Australia. Using group-independent component analysis, fcMRI was compared using mutation status and Clinical Dementia Rating to stratify groups, and related to each participant's estimated years from expected symptom onset (eYO).
We observed significantly decreased DMN fcMRI in mutation carriers with increasing Clinical Dementia Rating, most evident in the precuneus/posterior cingulate and parietal cortices (p < 0.001). Comparison of asymptomatic mutation carriers with noncarriers demonstrated decreased fcMRI in the precuneus/posterior cingulate (p = 0.014) and right parietal cortex (p = 0.0016). We observed a significant interaction between mutation carrier status and eYO, with decreases in DMN fcMRI observed as mutation carriers approached and surpassed their eYO.
Functional disruption of the DMN occurs early in the course of autosomal dominant Alzheimer disease, beginning before clinically evident symptoms, and worsening with increased impairment. These findings suggest that DMN fcMRI may prove useful as a biomarker across a wide spectrum of disease, and support the feasibility of DMN fcMRI as a secondary endpoint in upcoming multicenter clinical trials in Alzheimer disease.
... Functional brain connectivity is captured based on the assessment of temporal correlations between different brain regions of interest (ROIs) using functional magnetic resonance imaging (fMRI). There has been growing evidence that a number of functional connectivity networks are disrupted at each stage of the full clinical Alzheimer's disease (AD) spectrum [2][3][4]. Particularly, such neural differences are also detectable in cognitive normal (CN) carrying mutations of AD risk genes, suggesting a substantial relationship between genetics and AD-altered functional brain networks [5]. However, direct genetic effect on functional connectivity networks has not been measured [5,6]. ...
... Suppose we observe n 1 i.i.d. random samples {X (1) 1 , ..., X (1) n 1 } from X (1) and n 2 i.i.d samples random samples {X (2) 1 , ..., X (2) n 2 } from X (2) , and the two samples are independent. The goal is to estimate the differential correlation matrix D = R 1 − R 2 , under the assumption that D is sparse. ...
... Suppose we observe n 1 i.i.d. random samples {X (1) 1 , ..., X (1) n 1 } from X (1) and n 2 i.i.d samples random samples {X (2) 1 , ..., X (2) n 2 } from X (2) , and the two samples are independent. The goal is to estimate the differential correlation matrix D = R 1 − R 2 , under the assumption that D is sparse. ...
Background
There is growing evidence indicating that a number of functional connectivity networks are disrupted at each stage of the full clinical Alzheimer’s disease spectrum. Such differences are also detectable in cognitive normal (CN) carrying mutations of AD risk genes, suggesting a substantial relationship between genetics and AD-altered functional brain networks. However, direct genetic effect on functional connectivity networks has not been measured.
Methods
Leveraging existing AD functional connectivity studies collected in NeuroSynth, we performed a meta-analysis to identify two sets of brain regions: ones with altered functional connectivity in resting state network and ones without. Then with the brain-wide gene expression data in the Allen Human Brain Atlas, we applied a new biclustering method to identify a set of genes with differential co-expression patterns between these two set of brain regions.
Results
Differential co-expression analysis using biclustering method led to a subset of 38 genes which showed distinctive co-expression patterns between AD-related and non AD-related brain regions in default mode network. More specifically, we observed 4 sub-clusters with noticeable co-expression difference, where the difference in correlations is above 0.5 on average.
Conclusions
This work applies a new biclustering method to search for a subset of genes with altered co-expression patterns in AD-related default mode network regions. Compared with traditional differential expression analysis, differential co-expression analysis yielded many more significant hits with extra insights into the wiring mechanism between genes. Particularly, the differential co-expression pattern was observed between two sets of genes, suggesting potential upstream genetic regulators in AD development.
... Alteration of DMN connectivity is associated with a genetic mutation in AD. In particular, autosomal-dominant mutation carriers (PSEN1, PSEN2, or APP), who were young and asymptomatic, presented with altered DMN connectivity [145][146][147]. Regarding the Apo ε4 allele, various studies have reported diminished DMN connectivity in carriers of at least one Apo ε4 allele in all age ranges [144,[146][147][148][149][150][151]. ...
... In particular, autosomal-dominant mutation carriers (PSEN1, PSEN2, or APP), who were young and asymptomatic, presented with altered DMN connectivity [145][146][147]. Regarding the Apo ε4 allele, various studies have reported diminished DMN connectivity in carriers of at least one Apo ε4 allele in all age ranges [144,[146][147][148][149][150][151]. These results suggest some potential for the use of DMN connectivity for early identification of AD in young adults who carry relevant genetic mutations. ...
... Decreased in DMN functional connectivity [112,118,123,[126][127][128]131] Dissociation within DMN network; -decreased posterior DMN functional connectivity -elevation anterior DMN functional connectivity [134,135] DMN networks had longer distances with the loss of edges [138,141,142] Altered DMN functional connectivity was associated with decline of cognition [143,158,160] Altered DMN functional connectivity was associated with genetic mutation [146,149,152,154,157,163] Abbreviations: DMN, default mode network. ...
Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.
... The aggregation of amyloid beta (Aβ) peptides in AD primarily affects specific brain functional networks that collaborate to perform tasks. Impaired brain network connectivity is associated with the clinical severity and cognitive function of AD [4][5][6]. It has been proposed that these disrupted connectivity patterns within large-scale networks manifest the diverse clinical symptoms and cognitive impairments across dementia variants [7][8][9]. ...
... This may explain the observed correlation between CSF Aβ levels and microstates C/B. The intricate collaboration of large-scale functional brain networks in task performance can lead to cognitive impairment when connectivity is compromised [4][5][6]. Therefore, we propose that pathological changes in AD lead to a wide range of functional brain network disorders, affecting EEG microstate patterns and contributing to cognitive decline. However, to substantiate these claims, further investigations are warranted, including mediation effect analyses with expanded sample sizes, as well as CSF and fMRI-EEG studies. ...
Electroencephalography (EEG) microstates are used to study cognitive processes and brain disease-related changes. However, dysfunctional patterns of microstate dynamics in Alzheimer's disease (AD) remain uncertain. To investigate microstate changes in AD using EEG and assess their association with cognitive function and pathological changes in cerebrospinal fluid (CSF). We enrolled 56 patients with AD and 38 age- and sex-matched healthy controls (HC). All participants underwent various neuropsychological assessments and resting-state EEG recordings. Patients with AD also underwent CSF examinations to assess biomarkers related to the disease. Stepwise regression was used to analyze the relationship between changes in microstate patterns and CSF biomarkers. Receiver operating characteristics analysis was used to assess the potential of these microstate patterns as diagnostic predictors for AD. Compared with HC, patients with AD exhibited longer durations of microstates C and D, along with a decreased occurrence of microstate B. These microstate pattern changes were associated with Stroop Color Word Test and Activities of Daily Living scale scores (all P < 0.05). Mean duration, occurrences of microstate B, and mean occurrence were correlated with CSF Aβ 1–42 levels, while duration of microstate C was correlated with CSF Aβ 1–40 levels in AD (all P < 0.05). EEG microstates are used to predict AD classification with moderate accuracy. Changes in EEG microstate patterns in patients with AD correlate with cognition and disease severity, relate to Aβ deposition, and may be useful predictors for disease classification.
... Furthermore, within ADAD individuals, white matter disruption has been observed up to 10 years prior to symptom onset, particularly in the forceps major 73 . These corpus callosal alterations are thought to potentially underpin functional network disruptions to the default mode network also observed in ADAD individuals 78 . Importantly, posterior white matter alterations have been noted immediately prior to conversion from asymptomatic to symptomatic status in individuals outside of DIAN with a genetic predisposition to ADAD 79 . ...
... , rsMRI is a promising tool for helping researchers understand the connection between structural and functional disruption caused by ADAD progression61,78,91,92 . Therefore, the following parameters were used to acquire the axial rsMRI scan: TE = 30ms, TR = 3000ms, FOV = 212mm, flip angle = 80 degrees, slices = 48, voxel size = 3.3 x 3.3 x 3.3mm, acquisition time = 5m 08s, eyes = open.This scan was repeated for a total acquisition time of 10m 16s. ...
The Dominantly Inherited Alzheimer Network (DIAN) Observational Study is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). This rare form of Alzheimer disease (AD) is caused by mutations in the presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) genes. As individuals from these families have a 50% chance of inheriting the familial mutation, this provides researchers with a well-matched cohort of carriers vs non-carriers for case-control studies. An important trait of ADAD is that the age at symptom onset is highly predictable and consistent for each specific mutation, allowing researchers to estimate an individual's point in their disease time course prior to symptom onset. Although ADAD represents only a small proportion (approximately 0.1%) of all AD cases, studying this form of AD allows researchers to investigate preclinical AD and the progression of changes that occur within the brain prior to AD symptom onset. Furthermore, the young age at symptom onset (typically 30-60 years) means age-related comorbidities are much less prevalent than in sporadic AD, thereby allowing AD pathophysiology to be studied independent of these confounds. A major goal of the DIAN Observational Study is to create a global resource for AD researchers. To that end, the current manuscript provides an overview of the DIAN magnetic resonance imaging (MRI) and positron emission tomography (PET) protocols and highlights the key imaging results of this study to date.
... Evidence is also consistent when analysing ADAD reports. Even in PMC, volume loss (Fox et al., 2001), hypometabolism (Mosconi et al., 2006) and impaired functional connectivity (Chhatwal et al., 2013) in the PCC have been reported. As a core structure of the DMN, functional disruption of the PCC is evident in presymptomatic ADAD and continues worsening in more advanced stages of the disease (Chhatwal et al., 2013). ...
... Even in PMC, volume loss (Fox et al., 2001), hypometabolism (Mosconi et al., 2006) and impaired functional connectivity (Chhatwal et al., 2013) in the PCC have been reported. As a core structure of the DMN, functional disruption of the PCC is evident in presymptomatic ADAD and continues worsening in more advanced stages of the disease (Chhatwal et al., 2013). Notably, impaired DMN functional connectivity before clinical symptomatology onset traces a similar pattern in ADAD and sporadic AD. ...
The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer’s disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is ‘only’ one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit ‘downstream’ of the hippocampus. However, this notion is oversimplistic and increasing evidence suggest that other Papez regions might be affected before or concurrently with the hippocampus. In addition, AD research has mostly focused on episodic memory deficits, whereas spatial navigation processes are also subserved by the Papez circuit with increasing evidence supporting its valuable potential as a diagnostic measure of incipient AD pathophysiology.
In the current review we take a step forward analysing recent evidence on the structural and functional integrity of the Papez circuit across AD disease stages. Specifically, we will review the integrity of specific Papez regions from at-genetic-risk (APOE4 carriers), to mild cognitive impairment (MCI), to dementia stage of sporadic AD, as well as autosomal dominant AD (ADAD). We related those changes to episodic memory and spatial navigation/orientation deficits in AD. Finally, we provide an overview of how the Papez circuit is affected in AD diseases and their specific symptomology contributions. This overview strengthened the need for moving away from a hippocampal-centric view to a network approach on how the whole Papez circuit is affected in AD and contributes to its symptomology, informing future research and clinical approaches.
... A cross-sectional functional MRI connectivity study of 83 mutation carriers from the DIAN cohort, harbouring either APP, PSEN1 or PSEN2 mutations, reported that the clinical diagnosis of AD can be preceded by many years by functional disruptions of the default mode network (DMN) in ADAD [157]. Similar changes in resting state network, though occurring later, are found in LOAD [157,158]. ...
... A cross-sectional functional MRI connectivity study of 83 mutation carriers from the DIAN cohort, harbouring either APP, PSEN1 or PSEN2 mutations, reported that the clinical diagnosis of AD can be preceded by many years by functional disruptions of the default mode network (DMN) in ADAD [157]. Similar changes in resting state network, though occurring later, are found in LOAD [157,158]. Altered default mode connectivity was also observed in adults with DS with detectable fibrillar Aβ as measured by positron emission tomography (PET) using PiB as the tracer [159]. There are different explanations for the functional changes described. ...
The purpose of this review is to compare and highlight the clinical and pathological aspects of genetic versus acquired Alzheimer’s disease: Down syndrome-associated Alzheimer’s disease in (DSAD) and Autosomal Dominant Alzheimer’s disease (ADAD) are compared with the late-onset form of the disease (LOAD). DSAD and ADAD present in a younger population and are more likely to manifest with non-amnestic (such as dysexecutive function features) in the prodromal phase or neurological features (such as seizures and paralysis) especially in ADAD. The very large variety of mutations associated with ADAD explains the wider range of phenotypes. In the LOAD, age-associated comorbidities explain many of the phenotypic differences.
... To date, functional connectome changes in autosomal-dominant AD have been assessed with fMRI only. In one such fMRI study, Chhatwal et al. assessed DMN functional connectivity in asymptomatic autosomal-dominant AD mutation carriers (APP, PSEN1 and PSEN2) and non-carriers from the same families and found that the mutation carriers had a lower connectivity, particularly in the PCC/precuneus and right parietal cortex 167 . Of note, the disruption of DMN connectivity in mutation carriers worsened as the disease progressed. ...
... attention network and cingulo-opercular network (also referred to as the salience network) 168 . Consistent with the findings of Chhatwal et al. 167 , autosomal-dominant AD mutation carriers showed a lower functional connectivity in these multiple resting-state networks than non-carriers, slightly preceding their predicted age of symptom onset. The most recent of this series of fMRI connectivity studies, published in 2018, also reported specific effects of autosomal-dominant AD mutations on the degradation of the DMN and dorsal attention network in the preclinical stage of the disease 169 . ...
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
... for early detection of AD have shown promising results and rsfMRI is discussed as a biomarker preceding Aβ biomarkers . In autosomal dominant AD, default-mode network (DMN) functional connectivity has been found to decrease with increasing CDR and to be lower in asymptomatic mutation carriers that noncarriers with prominent involvement of the posterior cingulate cortex (PCC) (Chhatwal et al., 2013), suggesting alterations in this functional network already at the preclinical stage. An earlier study using task-related fMRI showed that PCC activity during a sensorymotor processing task was decreased in individuals with mild AD compared to age-matched elderly controls (Greicius, Srivastava, Reiss, & Menon, 2004), ...
... Although rsfMRI provides promising measures in preclinical AD (Chhatwal et al., 2013;Greicius et al., 2004;Thomas et al., 2014) biomarker research possibly preceding Aβ biomarkers (Jagust & Mormino, 2011), it is not yet incorporated in AD biomarker change models (Counts et al., 2017;Jack et al., 2013) or in the proposed framework for stageing of the preclinical phase of AD by the NIA-AA working group . To date, only few studies have investigated rsfMRI in preclinical AD, and reliability and reproducibility are affected by pooling of data acquired by different scanners (Teipel et al., 2017), and variation in participant instruction Yan et al., 2009). ...
... Recently, a set of biomarker criteria has been proposed to stage late onset AD disease progression [11a]. This model describes the earliest changes involve amyloid accumulation (A), followed by tau (T) deposition, and eventually neurodegeneration (N) that lead to cognitive dysfunction [12][13][14][15][16][17][18][19]. Changes in amyloid biomarkers, such as cerebrospinal fluid (CSF) Aβ 1-42 and [11C] Pittsburgh compound B (PiB) amyloid positron emission tomography (PET), have been observed ~15-20 years before symptom onset in ADAD [8,18,20,21,22,23]. ...
... This model describes the earliest changes involve amyloid accumulation (A), followed by tau (T) deposition, and eventually neurodegeneration (N) that lead to cognitive dysfunction [12][13][14][15][16][17][18][19]. Changes in amyloid biomarkers, such as cerebrospinal fluid (CSF) Aβ 1-42 and [11C] Pittsburgh compound B (PiB) amyloid positron emission tomography (PET), have been observed ~15-20 years before symptom onset in ADAD [8,18,20,21,22,23]. Tau (T) biomarkers, such as CSF phosphorylated tau 181 (p-tau 181 ) [4], change ~10-15 years prior to symptom onset in ADAD. ...
Aim:
Identify a global resting state functional connectivity (gFC) signature in mutation carriers (MC) from the Dominantly Inherited Alzheimer Network (DIAN). Assess the gFC with regards to amyloid (A), tau (T), and neurodegeneration (N) biomarkers and estimated years to symptom onset (EYO).
Introduction:
Cross-sectional measures were assessed in MC (n=171) and mutation non-carriers (NC) (n=70) participants. A FC matrix that encompassed multiple resting state networks (RSNs) was computed for each participant.
Methods:
A gFC was compiled as a single index indicating functional connectivity strength. Global FC signature was modeled as a non-linear function of EYO. gFC was linearly associated with other biomarkers used for assessing the AT(N) framework including: cerebrospinal fluid (CSF), positron emission tomography (PET) molecular biomarkers, and structural magnetic resonance imaging.
Results:
The gFC was reduced in MC compared to NC participants. When MC participants were differentiated by clinical dementia rating (CDR), the gFC was significantly decreased in MC CDR > 0 (demented) compared to either MC CDR 0 (cognitively normal) or NC participants. The gFC varied non-linearly with EYO and initially decreased at EYO = -24 years, followed by a stable period followed by a further decline near EYO =0 years. Irrespective of EYO, a lower gFC associated with values of amyloid PET, CSF Aβ1-42, CSF p-tau, CSF t-tau, FDG and hippocampal volume.
Conclusions:
The gFC correlated with biomarkers used for defining the AT(N) framework. A biphasic change in the gFC suggested early changes associated with CSF amyloid and later changes associated with hippocampal volume.
... Impairment of DMN deactivation in AD often precedes the formation of the Aβ plaque and the onset of clinical symptoms, which merits further investigation. 64 In the meantime, the increased paramagnetic susceptibility values are predominantly present in precentral, middle frontal, and temporal cortices, aligning with previous studies demonstrating that the accumulation of iron increases with age mainly in the areas related to motor, cognitive, and visual functions. 65 Notably, the brain regions most often reported to show brain iron accumulation in published studies are the temporal lobe in AD, 66 a pattern also observed in the temporal cor-tex in this study. ...
INTRODUCTION
The paramagnetic iron, diamagnetic amyloid beta (Aβ) plaques and their interaction are crucial in Alzheimer's disease (AD) pathogenesis, complicating non‐invasive magnetic resonance imaging for prodromal AD detection.
METHODS
We used a state‐of‐the‐art sub‐voxel quantitative susceptibility mapping method to simultaneously measure Aβ and iron levels in post mortem human brains, validated by histology. Further transcriptomic analysis using Allen Human Brain Atlas elucidated the underlying biological processes.
RESULTS
Regional increased paramagnetic and diamagnetic susceptibility were observed in medial prefrontal, medial parietal, and para‐hippocampal cortices associated with iron deposition (R = 0.836, p = 0.003) and Aβ accumulation (R = 0.853, p = 0.002) in AD brains. Higher levels of gene expression relating to cell cycle, post‐translational protein modifications, and cellular response to stress were observed.
DISCUSSION
These findings provide quantitative insights into the variable vulnerability of cortical regions to higher levels of Aβ aggregation, iron overload, and subsequent neurodegeneration, indicating changes preceding clinical symptoms.
Highlights
The vulnerability of distinct brain regions to amyloid beta (Aβ) and iron accumulation varies.
Histological validation was performed on stained sections of ex‐vivo human brains.
Regional variations in susceptibility were linked to gene expression profiles.
Iron and Aβ levels in ex‐vivo brains were simultaneously quantified.
... The study of functional connectivity (FC) offers significant insights into inter-network communication within the brain using functional magnetic resonance imaging (fMRI) (Biswal, Yetkin et al. 1995, Lowe, Dzemidzic et al. 2000, Fingelkurts, Fingelkurts et al. 2005, Bastos and Schoffelen 2016. FC and functional network connectivity (FNC), functional connectivity between intrinsic networks from the fMRI data, techniques have uncovered several key findings about intrinsic blood oxygenation level-dependent (BOLD) brain activity, particularly through restingstate fMRI (rsfMRI), and have provided valuable information about various brain disorders, including but not limited to schizophrenia (Calhoun, Kiehl et al. 2004, Lynall, Bassett et al. 2010, Sheffield and Barch 2016, Alzheimer's disease (Allen, Barnard et al. 2007, Chhatwal, Schultz et al. 2013, Sheline and Raichle 2013, and depression (Veer, Beckmann et al. 2010, Zeng, Shen et al. 2012, Mulders, van Eijndhoven et al. 2015. Numerous methods exist for quantifying FC/FNC between brain network time series, including Pearson correlation (Greicius, Krasnow et al. 2003, Damoiseaux, Rombouts et al. 2006, partial correlation (Sun, Miller et al. 2004), mutual information (Calhoun, Kim et al. 2003, Wang, Alahmadi et al. 2015, Salman, Vergara et al. 2019, Mohanty, Sethares et al. 2020, phase locking value (Zhang, Pan et al. 2016), and dynamic time warping (Meszlényi, Hermann et al. 2017, Linke, Mash et al. 2020, Wiafe, Faghiri et al. 2024, among others. ...
Nitazoxanide has an anti-inflammatory effect, we clarified the ameliorative effect of nitazoxanide on asthmatic airway inflammation by conducting in vitro and in vivo experiments. In vitro, we assessed the effect of nitazoxanide on cytokine production by lipopolysaccharide-stimulated RAW 264.7 cells, as well as the diastolic effect of nitazoxanide on isolated rat airways. Nitazoxanide was found to have a diastolic effect on isolated tracheal spasms caused by spasmogenic substances, and to inhibit IL-6 and IL-1β production by RAW 264.7 cells. Meanwhile, nitazoxanide can inhibit the proliferation and migration of human bronchial smooth muscle cells (HBSMCs). In vivo, an ovalbumin (OVA)-induced asthma model was established in mice, and the airway resistance was measured by Whole Body Plethysmography (WBP) after inhalation of acetylcholine in mice, and the levels of IL-4, IL-6, IL-12, and IL-17 were detected in bronchoalveolar lavage fluid (BALF) of mice by ELISA and the inflammatory cells were counted. H&E staining was used to observe the changes in lung histopathology, and the expression of NFkB, MAPK, AMPK, and STAT3 in lung tissues was quantified using Western-blot. Nitazoxanide reduced inflammatory cell infiltration and goblet cell proliferation in the lungs of asthmatic mice. Moreover, the expression of IL-4, IL-5, and IL-6 in BALF was down-regulated in asthmatic mice. In addition, nitazoxanide could inhibit the expression of NFkB, MAPK, STAT 3 proteins and ascend the expression of AMPK in lung tissues. In conclusion, nitazoxanide could diastole airway smooth muscle and ameliorate OVA-induced airway inflammation in asthmatic mice via NFkB/MAPK and AMPK/STAT3 pathways.
... The study of functional connectivity (FC) offers significant insights into inter-network communication within the brain using functional magnetic resonance imaging (fMRI) (Biswal, Yetkin et al. 1995, Lowe, Dzemidzic et al. 2000, Fingelkurts, Fingelkurts et al. 2005, Bastos and Schoffelen 2016. FC and functional network connectivity (FNC), functional connectivity between intrinsic networks from the fMRI data, techniques have uncovered several key findings about intrinsic blood oxygenation level-dependent (BOLD) brain activity, particularly through restingstate fMRI (rsfMRI), and have provided valuable information about various brain disorders, including but not limited to schizophrenia (Calhoun, Kiehl et al. 2004, Lynall, Bassett et al. 2010, Sheffield and Barch 2016, Alzheimer's disease (Allen, Barnard et al. 2007, Chhatwal, Schultz et al. 2013, Sheline and Raichle 2013, and depression (Veer, Beckmann et al. 2010, Zeng, Shen et al. 2012, Mulders, van Eijndhoven et al. 2015. Numerous methods exist for quantifying FC/FNC between brain network time series, including Pearson correlation (Greicius, Krasnow et al. 2003, Damoiseaux, Rombouts et al. 2006, partial correlation (Sun, Miller et al. 2004), mutual information (Calhoun, Kim et al. 2003, Wang, Alahmadi et al. 2015, Salman, Vergara et al. 2019, Mohanty, Sethares et al. 2020, phase locking value (Zhang, Pan et al. 2016), and dynamic time warping (Meszlényi, Hermann et al. 2017, Linke, Mash et al. 2020, Wiafe, Faghiri et al. 2024, among others. ...
Time-resolved functional connectivity (trFC) assesses the time-resolved coupling between brain regions using functional magnetic resonance imaging (fMRI) data. This study aims to compare two techniques used to estimate trFC, to investigate their similarities and differences when applied to fMRI data. These techniques are the sliding window Pearson correlation (SWPC), an amplitude-based approach, and phase synchronization (PS), a phase-based technique.
To accomplish our objective, we used resting-state fMRI data from the Human Connectome Project (HCP) with 827 subjects (repetition time: 0.7s) and the Function Biomedical Informatics Research Network (fBIRN) with 311 subjects (repetition time: 2s), which included 151 schizophrenia patients and 160 controls.
Our simulations reveal distinct strengths in two connectivity methods: SWPC captures high-magnitude, low-frequency connectivity, while PS detects low-magnitude, high-frequency connectivity. Stronger correlations between SWPC and PS align with pronounced fMRI oscillations. For fMRI data, higher correlations between SWPC and PS occur with matched frequencies and smaller SWPC window sizes (~30s), but larger windows (~88s) sacrifice clinically relevant information. Both methods identify a schizophrenia-associated brain network state but show different patterns: SWPC highlights low anti-correlations between visual, subcortical, auditory, and sensory-motor networks, while PS shows reduced positive synchronization among these networks.
Our findings underscore the complementary nature of SWPC and PS, elucidating their respective strengths and limitations without implying the superiority of one over the other.
... When rs-fMRI is applied to people with AD, or its precursor, mild cognitive impairment (MCI), there are substantial changes in functional connectivity at the group level, when contrasted with healthy controls [6][7][8][9] . Similar changes have been identified in individuals who do not yet have MCI or AD but are considered high risk due to genetic polymorphisms [10][11][12] , mutations for autosomal dominant AD 13 , a family history of AD 14 or a high burden of pathogenic amyloid and tau proteins [15][16][17][18][19][20] . Altered functional connectivity-measured with rs-fMRI-is therefore widely considered a potential preclinical biomarker of AD 21 . ...
Altered functional connectivity precedes structural brain changes and symptoms in dementia. Alzheimer’s disease is the largest contributor to dementia at the population level, and disrupts functional connectivity in the brain’s default-mode network (DMN). We investigated whether a neurobiological model of DMN effective connectivity could predict a future dementia diagnosis at the single-participant level. We applied spectral dynamic causal modeling to resting-state functional magnetic resonance imaging data in a nested case–control group from the UK Biobank, including 81 undiagnosed individuals who developed dementia up to nine years after imaging, and 1,030 matched controls. Dysconnectivity predicted both future dementia incidence (AUC = 0.82) and time to diagnosis ( R = 0.53), outperforming models based on brain structure and functional connectivity. We also evaluated associations between DMN dysconnectivity and major risk factors for dementia, revealing strong relationships with polygenic risk for Alzheimer’s disease and social isolation. Neurobiological models of effective connectivity may facilitate early detection of dementia at population level, supporting rational deployment of targeted dementia-prevention strategies.
... The current investigation was not adequately powered to examine antihypertensive treatment effects on functional connectivity, but future work in this area is needed and has the potential to update BP control guidelines for older adults. Nevertheless, both BPV elevation and attenuated default network functional connectivity have independently been shown to emerge before the onset of major neurocognitive symptoms of AD (Chhatwal et al., 2013;Sible and Nation, 2020). These findings suggest early changes in vascular and neuronal functioning associated with high BPV may have synergetic contributions to cognitive decline that could be intervened on with existing antihypertensive medications. ...
Background
Blood pressure variability is increasingly linked with cerebrovascular disease and Alzheimer’s disease, independent of mean blood pressure levels. Elevated blood pressure variability is also associated with attenuated cerebrovascular reactivity, which may have implications for functional hyperemia underpinning brain network connectivity. It remains unclear whether blood pressure variability is related to functional network connectivity. We examined relationships between beat-to-beat blood pressure variability and functional connectivity in brain networks vulnerable to aging and Alzheimer’s disease.
Methods
53 community-dwelling older adults (mean [SD] age = 69.9 [7.5] years, 62.3% female) without history of dementia or clinical stroke underwent continuous blood pressure monitoring and resting state fMRI scan. Blood pressure variability was calculated as variability independent of mean. Functional connectivity was determined by resting state fMRI for several brain networks: default, salience, dorsal attention, fronto-parietal, and language. Multiple linear regression examined relationships between short-term blood pressure variability and functional network connectivity.
Results
Elevated short-term blood pressure variability was associated with lower functional connectivity in the default network (systolic: standardized ß = −0.30 [95% CI −0.59, −0.01], p = .04). There were no significant associations between blood pressure variability and connectivity in other functional networks or between mean blood pressure and functional connectivity in any network.
Discussion
Older adults with elevated short-term blood pressure variability exhibit lower resting state functional connectivity in the default network. Findings support the role of blood pressure variability in neurovascular dysfunction and Alzheimer’s disease. Blood pressure variability may represent an understudied early vascular risk factor for neurovascular dysfunction relevant to Alzheimer’s disease, with potential therapeutic implications.
... The study also highlights the usefulness of eLORETA-ICA as a non-invasive tool for assessing EEG-functional network activities, providing insights into the complex neurophysiological mechanisms underlying AD. Additionally, fMRI has been used to investigate the functional connectivity of different subregions of the amygdala AD patients compared to healthy controls [14]. Three subregions of the amygdala were defined based on probabilistic cytoarchitectonic atlases, and their whole-brain resting-state functional connectivity was mapped. ...
The disruption of functional connectivity is one of the early events that occurs in the brains of Alzheimer’s disease (AD) patients. This paper reports a study on the clustering structure of functional connectivity in eight important brain networks in healthy, AD, and prodromal stage subjects. We used the threshold-free cluster enhancement (TFCE) method to explore the connectivity from resting-state functional MR images (rs-fMRIs). We conducted the study on a total of 32 AD, 32 HC, and 31 MCI subjects. We modeled the brain as a graph-based network to study these impairments, and pairwise Pearson’s correlation-based functional connectivity was used to construct the brain network. The study found that connections in the sensory motor network (SMN), dorsal attention network (DAN), salience network (SAN), default mode network (DMN), and cerebral network were severely affected in AD and MCI. The disruption in these networks may serve as potential biomarkers for distinguishing AD and MCI from HC. The study suggests that alterations in functional connectivity in these networks may contribute to cognitive deficits observed in AD and MCI. Additionally, a negative correlation was observed between the global clinical dementia rating (CDR) score and the Z-score of functional connectivity within identified clusters in AD subjects. These findings provide compelling evidence suggesting that the neurodegenerative disruption of functional magnetic resonance imaging (fMRI) connectivity is extensively distributed across multiple networks in individuals diagnosed with AD.
... The increase in gamma wPLI observed in the current study may thus point to a pre-symptomatic stage that precedes neuronal hyperexcitability. In line with the reduced amplitudebased beta connectivity observed here, a number of fMRI studies reported decreased connectivity in human PSEN1 mutation carriers, specifically in the default mode network [38,94,95]. ...
Background
Studies in animal models of Alzheimer’s disease (AD) have provided valuable insights into the molecular and cellular processes underlying neuronal network dysfunction. Whether and how AD-related neurophysiological alterations translate between mice and humans remains however uncertain.
Methods
We characterized neurophysiological alterations in mice and humans carrying AD mutations in the APP and/or PSEN1 genes, focusing on early pre-symptomatic changes. Longitudinal local field potential recordings were performed in APP/PS1 mice and cross-sectional magnetoencephalography recordings in human APP and/or PSEN1 mutation carriers. All recordings were acquired in the left frontal cortex, parietal cortex, and hippocampus. Spectral power and functional connectivity were analyzed and compared with wildtype control mice and healthy age-matched human subjects.
Results
APP/PS1 mice showed increased absolute power, especially at higher frequencies (beta and gamma) and predominantly between 3 and 6 moa. Relative power showed an overall shift from lower to higher frequencies over almost the entire recording period and across all three brain regions. Human mutation carriers, on the other hand, did not show changes in power except for an increase in relative theta power in the hippocampus. Mouse parietal cortex and hippocampal power spectra showed a characteristic peak at around 8 Hz which was not significantly altered in transgenic mice. Human power spectra showed a characteristic peak at around 9 Hz, the frequency of which was significantly reduced in mutation carriers. Significant alterations in functional connectivity were detected in theta, alpha, beta, and gamma frequency bands, but the exact frequency range and direction of change differed for APP/PS1 mice and human mutation carriers.
Conclusions
Both mice and humans carrying APP and/or PSEN1 mutations show abnormal neurophysiological activity, but several measures do not translate one-to-one between species. Alterations in absolute and relative power in mice should be interpreted with care and may be due to overexpression of amyloid in combination with the absence of tau pathology and cholinergic degeneration. Future studies should explore whether changes in brain activity in other AD mouse models, for instance, those also including tau pathology, provide better translation to the human AD continuum.
... Previous studies have found that early onset/familial AD gene mutations, such as presenilin 1/2 and amyloid precursor protein, can be detected in the carriers at very early-stage AD when cognitive abilities are still intact (Selkoe, 1997;Selkoe, 2001;Chhatwal et al., 2013;Van Cauwenberghe et al., 2016). In the carriers of late onset/ sporadic AD gene mutation, such as apolipoprotein E (APOE4), dysfunction of neurons in the PFC/HIPP also occurs before fibrillar Aβ deposition and the clinical symptoms of AD (Persson et al., 2008;Sheline et al., 2010). ...
The normal function of the medial prefrontal cortex (mPFC) is essential for regulating neurocognition, but it is disrupted in the early stages of Alzheimer’s disease (AD) before the accumulation of Aβ and the appearance of symptoms. Despite this, little is known about how the functional activity of medial prefrontal cortex pyramidal neurons changes as Alzheimer’s disease progresses during aging. We used electrophysiological techniques (patch-clamping) to assess the functional activity of medial prefrontal cortex pyramidal neurons in the brain of 3xTg-Alzheimer’s disease mice modeling early-stage Alzheimer’s disease without Aβ accumulation. Our results indicate that firing rate and the frequency of spontaneous excitatory postsynaptic currents (sEPSCs) were significantly increased in medial prefrontal cortex neurons from young Alzheimer’s disease mice (4–5-month, equivalent of <30-year-old humans) compared to age-matched control mice. Blocking ionotropic glutamatergic NMDA receptors, which regulate neuronal excitability and Ca²⁺ homeostasis, abolished this neuronal hyperactivity. There were no changes in Ca²⁺ influx through the voltage-gated Ca²⁺ channels (VGCCs) or inhibitory postsynaptic activity in medial prefrontal cortex neurons from young Alzheimer’s disease mice compared to controls. Additionally, acute exposure to Aβ42 potentiated medial prefrontal cortex neuronal hyperactivity in young Alzheimer’s disease mice but had no effects on controls. These findings indicate that the hyperactivity of medial prefrontal cortex pyramidal neurons at early-stage Alzheimer’s disease is induced by an abnormal increase in presynaptic glutamate release and postsynaptic NMDA receptor activity, which initiates neuronal Ca²⁺ dyshomeostasis. Additionally, because accumulated Aβ forms unconventional but functional Ca²⁺ channels in medial prefrontal cortex neurons in the late stage of Alzheimer’s disease, our study also suggests an exacerbated Ca²⁺ dyshomeostasis in medial prefrontal cortex pyramidal neurons following overactivation of such VGCCs.
... Previous GWAS studies have revealed a bidirectional interplay between the genetic profile and neurological network connectivity (Palk et al. 2020). Chhatwal, J. P. et al. observed alterations in DMN connectivity in both symptomatic and asymptomatic carriers of pathogenic mutations of presenilin-1, presenilin-2 and amyloid precursor protein (APP) (Chhatwal et al. 2013). The clusterin gene has been reported to consistently affect the changing patterns of the DMN in subjects at high risk of AD (Ye et al. 2017). ...
Alzheimer's disease (AD) is a highly heritable disease. The morphological changes of cortical cortex (such as, cortical thickness and surface area) in AD always accompany by the change of the functional connectivity to other brain regions and influence the short‐ and long‐range brain network connections, causing functional deficits of AD. In this study, the first hypothesis is that genetic variations might affect morphology‐based brain networks, leading to functional deficits; the second hypothesis is that protein–protein interaction (PPI) between the candidate proteins and known interacting proteins to AD might exist and influence AD. 600 470 variants and structural magnetic resonance imaging scans from 175 AD patients and 214 healthy controls were obtained from the Alzheimer's Disease Neuroimaging Initiative‐1 database. A co‐sparse reduced‐rank regression model was fit to study the relationship between non‐synonymous mutations and morphology‐based brain networks. After that, PPIs between selected genes and BACE1, an enzyme that was known to be related to AD, are explored by using molecular dynamics (MD) simulation and co‐immunoprecipitation (Co‐IP) experiments. Eight genes affecting morphology‐based brain networks were identified. The results of MD simulation showed that the PPI between TGM4 and BACE1 was the strongest among them and its interaction was verified by Co‐IP. Hence, gene variations influence morphology‐based brain networks in AD, leading to functional deficits. This finding, validated by MD simulation and Co‐IP, suggests that the effect is robust. image
... As recently reviewed, the pathophysiology of AD is associated with a disruption in structural and functional brain network connectivity [128]. Several factors indicate that amyloid deposition on PET accumulates in highly connected regions characterized as 'hubs', and in large areas of association cortex overlapping a set of regions active at rest, also known as the default-mode-network (DMN) [129,130]. Amyloid-related DMN hypoconnectivity occurs in ADAD, EOAD, and LOAD, although in association with different genetic variants across these subtypes [128]. In LOAD, the earliest amyloid deposits are observed at the preclinical stage in the DMN, before plaque can be identified on PET, and before neurodegeneration and hypometabolism [131]. ...
Le système physiopathologique de la maladie d'Alzheimer (MA) s'organise à différentes échelles spatio-temporelles (moléculaire, cellulaire, cognitive...). L'organisation de ces sous-systèmes et de leurs perturbations dans la MA est à la base des stratégies diagnostiques et thérapeutiques. Une première étude a été effectuée sur la valeur diagnostique des biomarqueurs amyloïdes du liquide cérébrospinal. Cette étude a permis de révéler de fortes incohérences dans le cas d'un diagnostic purement biologique de MA et de la classification ATN. Elle permit de discuter brièvement l'emploi et l'interprétation de ces biomarqueurs dans ce contexte. La neuroinflammation prend une importance croissante dans la physiopathologie de la MA. Dans cette thèse, l'ensemble des travaux se sont basés sur le projet V.I.P. qui étudie le rôle de la neuroinflammation en imagerie tomographie par émission de positons (TEP) aux premiers stades de la MA. Ce projet est un essai clinique de phase 2 d'un composé anti-inflammatoire innovant dont l'effet est évalué en TEP scan ainsi qu'une évaluation neuropsychologique exhaustive. Une première étude a été effectuée sur les examens de la visite d'inclusion du projet V.I.P. et révéla l'hétérogénéité des profils neuroinflammatoires parmi les patients inclus, tant en termes de topographie que d'association avec leurs profils cliniques. Une deuxième étude montra que la variabilité des profils de neuroinflammation en TEP était également dissociée des profils de neurodégénérescence. Bien qu'introductifs à l'analyse longitudinale de l'effet du traitement, ces résultats montrèrent la difficulté de l'étude de la neuroinflammation aux premiers stades de la MA sur des aspects méthodologique et physiopathologique. La suite du projet V.I.P. permettra ainsi de discuter l'intérêt d'interventions immunologiques aux premiers stades de la MA.
... No reduction in functional connectivity was observed in the mutation carriers. The opposite results were found in other studies using the independent component correlation algorithm (Chhatwal et al., 2013), in which functional connectivity within much of the DMN was decreased in ADAD mutation carriers compared with non-carriers. The most apparent decreased connectivity was with the major posterior node of the DMN (precuneus/posterior cingulate, PPC), along with the anterior node of the DMN (mPFC) and bilateral parietal cortices. ...
Alzheimer’s disease (AD) is the most common form of dementia, with no cure to stop its progression. Early detection, diagnosis, and intervention have become the hot spots in AD research. The long asymptomatic and slightly symptomatic phases of autosomal dominant AD (ADAD) allow studies to explore early biomarkers and the underlying pathophysiological changes. Functional magnetic resonance imaging (fMRI) provides a method to detect abnormal patterns of brain activity and functional connectivity in vivo , which correlates with cognitive decline earlier than structural changes and more strongly than amyloid deposition. Here, we will provide a brief overview of the network-level findings in ADAD in fMRI studies. In general, abnormalities in brain activity were mainly found in the hippocampus, the medial temporal lobe (MTL), the posterior cortex, the cingulate cortices, and the frontal regions in ADAD. Moreover, ADAD and sporadic AD (SAD) have similar fMRI changes, but not with aging.
... The degree of task induced DMN deactivation is correlated with cognitive performance (Sperling et al., 2010). The DMN is rather impaired in the course of disease onset (Chhatwal et al., 2013). Earlier hypersynchronization and subsequent decline are similarly observed in AD mice (Bero et al., 2012;Shah et al., 2018;Ben-Nejma et al., 2019). ...
The amyloid hypothesis for the pathogenesis of Alzheimer’s disease (AD) is widely accepted. Last year, the US Food and Drug Administration considered amyloid-β peptide (Aβ) as a surrogate biomarker and approved an anti-Aβ antibody, aducanumab, although its effectiveness in slowing the progression of AD is still uncertain. This approval has caused a great deal of controversy. Opinions are divided about whether there is enough evidence to definitely consider Aβ as a causative substance of AD. To develop this discussion constructively and to discover the most suitable therapeutic interventions in the end, an alternative persuasive hypothesis needs to emerge to better explain the facts. In this paper, I propose a hypothesis that excessive/aberrant and maladaptive synaptic plasticity is the pathophysiological basis for AD.
... The severe loss in strength of RSCd regions in dKI mice may therefore indicate an OP recall-dependent roadblock for the mPFC-MTL communication. Our results also corroborate those of human studies showing that mPFC and PCC/RSC regions are often disrupted when functional and structural connectivity are evaluated in aMCI patients, APOE e4 carriers and presymptomatic ADAD patients [12,16,85]. Reduced connectivity in the PCC/RSC may constitute a typical FC marker of preclinical AD [36]. ...
A critical challenge in current research on Alzheimer’s disease (AD) is to clarify the relationship between network dysfunction and the emergence of subtle memory deficits in itspreclinical stage. The AppNL-F/MAPT double knock-in (dKI) model with humanized β-amyloid peptide (Aβ) and tau was used to investigate both memory and network dysfunctions at an early stage. Young male dKI mice (2 to 6 months) were tested in three tasks taxing different aspects of recognition memory affected in preclinical AD. An early deficit first appeared in the object-place association task at the age of 4 months, when increased levels of β-CTF and Aβ were detected in both the hippocampus and the medial temporal cortex, and tau pathology was found only in the medial temporal cortex. Object-place task-dependent c-Fos activation was then analyzed in 22 subregions across the medial prefrontal cortex, claustrum, retrosplenial cortex, and medial temporal lobe. Increased c-Fos activation was detected in the entorhinal cortex and the claustrum of dKI mice. During recall, network efficiency was reduced across cingulate regions with a major disruption of information flow through the retrosplenial cortex. Our findings suggest that early perirhinal-entorhinal pathology is associated with abnormal activity which may spread to downstream regions such as the claustrum, the medial prefrontal cortex and ultimately the key retrosplenial hub which relays information from frontal to temporal lobes. The similarity between our findings and those reported in preclinical stages of AD suggests that the AppNL-F/MAPT dKI model has a high potential for providing key insights into preclinical AD.
... Participants of the DIAN-OBS study provided the first presymptomatic data in a mainly crosssectional analysis [5]. Subsequent studies included increasing numbers of participants and longitudinal data that have refined the diversity of the age of onset relative to a given mutation or within a family [33], but also early subtle neuropsychological changes [34], or structural [35,36] and functional neuroimaging [37], or blood/cerebrospinal fluid (CSF) biomarkers [36,38]. These major advances have established the timeline of autosomal dominant AD pathophysiology events that are quantifiable more than 20 years before the first clinical signs. ...
Alzheimer's disease (AD) is the most common neurodegenerative disorder. Although its etiology remains incompletely understood, genetic variants are important contributors. The prediction of AD risk through individual genetic variants is an important topic of research that may have individual and societal consequences when preventive treatments will become available. However, the genetic substratum of AD is heterogeneous. In addition to the extremely rare and fully penetrant pathogenic variants of the PSEN1, PSEN2 or APP genes causing autosomal dominant AD, a large spectrum of risk factors have been identified in complex forms, including the common risk factor APOEɛ4, which is associated with a moderate-to-high risk, common polymorphisms associated with a modest individual risk, and a plethora of rare variants in genes like SORL1, TREM2 or ABCA7 with moderate to high-magnitude effect. Understanding how these genetic factors contribute to AD risk in a given individual, in additional to non-genetic factors, remains a challenge. Over the last 10 years, age-related penetrance curves have progressively incorporated advances in the knowledge of AD genetics, from APOE to common polygenic components and, currently, SORL1 rare variants, which represents an important step towards precision medicine in AD. In this review, we present the complex genetic architecture of AD and we expose the prediction of AD risk according to its underlying genetic component.
... Prior studies with other ADAD mutations have also reported decreased functional DMN segregation as individuals approach symptom onset. One particular study demonstrated decreased functional connectivity of the precuneus and other posterior DMN regions in cognitively unimpaired mutation carriers (32), while another showed that both anterior and posterior regions of the network are disrupted early (33). Notably, other studies have only observed less functional connectivity, including in the DMN and between networks, in cognitively impaired mutation carriers as measured by a score of 1 on the clinical dementia rating (CDR) scale, and not in cognitively unimpaired mutation carriers (CDR = 0) (11,13). ...
SIGNIFICANCE
Amyloid-β and tau, hallmark pathologies of Alzheimer’s disease (AD), are hypothesized to spread through brain functional networks that are critical for neural communication. Using high-resolution network analyses and positron emission tomography, we showed that greater tau burden was related to functional dysconnectivity of regions associated with memory function and increased connectivity of structures that are important for integrating information in cognitively unimpaired Presenilin-1 E280A carriers, who will develop early-onset AD dementia. These findings enlighten how brain pathology relates to distinct patterns of functional connectivity in regions that are essential for memory and information processing. Elucidating how brain pathology alters functional connections before individuals experience cognitive impairment could help detect AD early and predict disease progression and dementia risk.
... Previous studies of ADAD in participants in DIAN have demonstrated that abnormal levels of amyloid were detected in the cortex of mutation carriers 15 years in advance of expected onset of clinical symptoms (11,19,20). Moreover, studies in the same population using resting-state functional MRI have demonstrated that functional disruption of the default mode network begins before clinically evident symptoms in mutation carriers and worsens with increasing impairment (23)(24)(25). Studies have demonstrated that white matter structural connectivity is affected by AD-related pathology, namely amyloid, and may mediate changes in other markers of AD (4,26,27). ...
Background Pathologic evidence of Alzheimer disease (AD) is detectable years before onset of clinical symptoms. Imaging-based identification of structural changes of the brain in people at genetic risk for early-onset AD may provide insights into how genes influence the pathologic cascade that leads to dementia. Purpose To assess structural connectivity differences in cortical networks between cognitively normal autosomal dominant Alzheimer disease (ADAD) mutation carriers versus noncarriers and to determine the cross-sectional relationship of structural connectivity and cortical amyloid burden with estimated years to symptom onset (EYO) of dementia in carriers. Materials and Methods In this exploratory analysis of a prospective trial, all participants enrolled in the Dominantly Inherited Alzheimer Network between January 2009 and July 2014 who had normal cognition at baseline, T1-weighted MRI scans, and diffusion tensor imaging (DTI) were analyzed. Amyloid PET imaging using Pittsburgh compound B was also analyzed for mutation carriers. Areas of the cerebral cortex were parcellated into three cortical networks: the default mode network, frontoparietal control network, and ventral attention network. The structural connectivity of the three networks was calculated from DTI. General linear models were used to examine differences in structural connectivity between mutation carriers and noncarriers and the relationship between structural connectivity, amyloid burden, and EYO in mutation carriers. Correlation network analysis was performed to identify clusters of related clinical and imaging markers. Results There were 30 mutation carriers (mean age ± standard deviation, 34 years ± 10; 17 women) and 38 noncarriers (mean age, 37 years ± 10; 20 women). There was lower structural connectivity in the frontoparietal control network in mutation carriers compared with noncarriers (estimated effect of mutation-positive status, -0.0266; P = .04). Among mutation carriers, there was a correlation between EYO and white matter structural connectivity in the frontoparietal control network (estimated effect of EYO, -0.0015, P = .01). There was no significant relationship between cortical global amyloid burden and EYO among mutation carriers (P > .05). Conclusion White matter structural connectivity was lower in autosomal dominant Alzheimer disease mutation carriers compared with noncarriers and correlated with estimated years to symptom onset. Clinical trial registration no. NCT00869817 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by McEvoy in this issue.
... Aggregation of amyloid beta (Aβ) peptides preferentially affects DMN regions , while impaired DMN connectivity is associated with AD clinical severity and memory abilities (Brier et al., 2012;Buckner et al., 2005;Petrella et al., 2011). Moreover, in asymptomatic carriers of pathogenic mutations for AD, DMN disruption occurs before clinically evident symptoms, suggesting that functional disconnection might serve as marker of brain changes among patients earlier in the AD clinical course (Chhatwal et al., 2013). Additionally, other networks are involved in AD pathology, including the LMB (Pini et al., 2020a;Gour et al., 2014). ...
Alzheimer's disease (AD) is characterized by different clinical entities. Although AD phenotypes share a common molecular substrate (i.e., amyloid beta and tau accumulation), several clinicopathological differences exist. Brain functional networks might provide a macro-scale scaffolding to explain this heterogeneity. In this review, we summarize the evidence linking different large-scale functional network abnormalities to distinct AD phenotypes. Specifically, executive deficits in early-onset AD link with the dysfunction of networks that support sustained attention and executive functions. Posterior cortical atrophy relates to the breakdown of visual and dorsal attentional circuits, while the primary progressive aphasia variant of AD may be associated with the dysfunction of the left-lateralized language network. Additionally, network abnormalities might provide in vivo signatures for distinguishing proteinopathies that mimic AD, such as TAR DNA binding protein 43 related pathologies. These network differences vis-a-vis clinical syndromes are more evident in the earliest stage of AD. Finally, we discuss how these findings might pave the way for new tailored interventions targeting the most vulnerable brain circuit at the optimal time window to maximize clinical benefits.
... compared asymptomatic mutation carriers and non-carriers and suggested reduction in Default Mode Network functional connectivity among asymptomatic carriers 56 . This finding is concordant with literature on sAD suggesting that change in rs-fMRI is one of the earliest biomarkers of the disease 25,26 . ...
Resting state functional connectivity (rs-fMRI) is impaired early in persons who subsequently develop Alzheimer’s disease (AD) dementia. This impairment may be leveraged to aid investigation of the pre-clinical phase of AD. We developed a model that predicts brain age from resting state (rs)-fMRI data, and assessed whether genetic determinants of AD, as well as beta-amyloid (Aβ) pathology, can accelerate brain aging. Using data from 1340 cognitively unimpaired participants between 18–94 years of age from multiple sites, we showed that topological properties of graphs constructed from rs-fMRI can predict chronological age across the lifespan. Application of our predictive model to the context of pre-clinical AD revealed that the pre-symptomatic phase of autosomal dominant AD includes acceleration of functional brain aging. This association was stronger in individuals having significant Aβ pathology.
... Amplitude of low-frequency fluctuation (ALFF) is a relatively stable indicator in fMRI sequences that can respond to the low-frequency electrical activity of local neurons in the resting state. Most studies using ALFF as a biomarker have focused on specific brain region findings and functional connectivity in patients with psychiatric and neurodegenerative disorders (17)(18)(19)(20)(21)(22)(23). ALFF has the potential to be a special tool in the study of psychiatric or neurological disorders to assess the electrical activity of neurons in the resting state early in the course of the disease (24,25). ...
Background:
Acute bilirubin encephalopathy or kernicterus is the worst consequence of brain damage caused by the elevation of total unbound serum bilirubin (TSB) in neonates. The present study aimed to visualize the characteristic brain regions of neonates with hyperbilirubinemia (HB) using functional magnetic resonance imaging (fMRI) and to measure the amplitude of low-frequency fluctuation (ALFF) values.
Methods:
This was a prospective cohort study, which included newborns with HB who were hospitalized at the Children's Hospital of Fudan University. The control group included neonates admitted with neonatal simple wet lung or pneumonia without neurological disease or brain injury. Newborns were divided into a severe hyperbilirubinemia group (SHB), moderate HB group, and control group based on TSB levels. The newborns completed routine MRI combined with fMRI scans and brainstem auditory evoked potentials (BAEPs) during their hospitalization.
Results:
A total of 251 newborns were included in this study. There were 45 patients in the SHB group, 65 in the HB group, and 141 in the control group. The average ALFF value in the basal ganglia region in the SHB group was the highest, which was greater than that in the HB and control groups (P<0.001). The ALFF increased with an increase in TSB concentration. Based on the results of the Bayley Scales of infant development assessment, we further found that the most significant difference in ALFF remained in the basal ganglia region between newborns with motor development scores above 70 (including 70) and below 70. Correlation analysis revealed a strong negative correlation between motor development scores and ALFF (r=-0.691, P<0.001). When ALFF alone was used to predict motor development, the sensitivity was 89%. When ALFF was combined with TSB and BEAP results, the area under the ROC curve was the largest (AUC =0.85). The sensitivity and specificity of the model were 67.86% and 90.77%, respectively.
Conclusions:
The ALFF value may be able to serve as an early imaging biomarker and has a greater sensitivity than TSB or BAEP results in predicting long-term motor development (18 m) in HB.
... Looking to other neurodegenerative diseases, Alzheimer's studies have also demonstrated concurrent increases and decreases in functional connectivity in the early disease process but with more consistent widespread decreases in functional connectivity occurring with disease progression (Chhatwal et al. 2013;Badhwar et al. 2017;Demirtaş et al. 2017 ...
Whilst there are currently no available disease modifying therapies for Huntington’s Disease (HD), recent progress in huntingtin-lowering strategies hold great promise. Initiating therapies early in the disease course will be important and a complete characterisation of the premanifest period will help inform when to initiate disease modifying therapies and the biomarkers that may be useful in such trials. Previous research has characterised the premanifest period up to approximately 15 years from predicted onset, but even at this early stage the disease process is already underway as evidenced by striatal and white matter atrophy, reductions in structural connectivity within brain networks, rising biofluid biomarkers of neuronal dysfunction, elevations in psychiatric symptoms and emerging subtle cognitive impairments. In order to understand how early neurodegeneration can be detected and which measures are most sensitive to the early disease processes, we need to look even earlier in the disease course. This thesis documents the recruitment and analysis of the HD Young Adult Study: a premanifest cohort further from predicted clinical onset than previously studied with an average of 24 years prior to predicted onset. Differences between gene carriers and controls were examined across a range of imaging, cognitive, neuropsychiatric and biofluid measures. The structural and functional brain connectivity in this cohort is then investigated in further detail. By providing a detailed characterisation of brain structure and function in the early premanifest period along with the most sensitive biomarkers at this stage, this work will inform future treatment strategies that may seek to delay the onset of functional impairments in HD.
... The DMN is primarily implicated in episodic memory retrieval and deactivated during the processing of external stimuli in cognitively demanding tasks (59,60). Furthermore, the DMN system, especially the medial temporal lobe subsystem, is frequently disrupted in AD and correlates with disease severity (61,62). The brain regions comprising the DMN and areas with high Ab load also show considerable overlap, and subjects with positive 11 C Pittsburgh Compound B PET scans showed significantly lower resting-state FC in the DMN compared with subjects with negative 11 C Pittsburgh Compound B PET scans (63)(64)(65). ...
Background
Individualized and reliable biomarkers are crucial for diagnosing Alzheimer’s disease (AD). However, the lack of accessibility and neurobiological correlation are the main obstacles to their clinical application. Machine learning algorithms can effectively identify personalized biomarkers based on the prominent symptoms of AD.
Methods
The episodic memory-related magnetic resonance imaging (MRI) features of 143 amnesic mild cognitive impairment (aMCI) patients were identified using a multivariate relevance vector regression (RVR) algorithm. The support vector machine (SVM) classification model was constructed using these MRI features and verified in two independent datasets (N=994). The neurobiological basis was also investigated based on cognitive assessments, neuropathologic biomarkers of cerebrospinal fluid (CSF), and positron emission tomography (PET) images of amyloid-β plaques.
Results
The combination of gray matter volume and amplitude of low-frequency fluctuation MRI features accurately predicted episodic memory impairment in individual aMCI patients (correlation = 0.638) when measured using an episodic memory assessment panel. The MRI features that contributed to episodic memory prediction were primarily distributed across the default mode network and limbic network. The classification model based on these features distinguished patients with AD from normal controls (NCs) with more than 86% accuracy. Furthermore, most identified episodic memory-related regions showed significantly different amyloid-β PET measurements among the AD, MCI, and NC groups. Moreover, the classification outputs significantly correlated with cognitive assessment scores and CSF amyloid-β42 and total tau levels in the MCI and AD groups.
Conclusions
Neuroimaging features can reflect individual episodic memory function and serve as potential diagnostic biomarkers of AD.
This manuscript describes and summarizes the Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs), highlighting the wealth of longitudinal data, samples, and results from this human cohort study of brain aging and a rare monogenic form of Alzheimers disease (AD). DIAN Obs is an international collaborative longitudinal study initiated in 2008 with support from the National Institute on Aging (NIA), designed to obtain comprehensive and uniform data on brain biology and function in individuals at risk for autosomal dominant AD (ADAD). ADAD gene mutations in the amyloid protein precursor (APP), presenilin 1 (PSEN1), or presenilin 2 (PSEN2) genes are deterministic causes of ADAD, with virtually full penetrance, and a predictable age at symptomatic onset. Data and specimens collected are derived from full clinical assessments, including neurologic and physical examinations, extensive cognitive batteries, structural and functional neuro-imaging, amyloid and tau pathological measures using positron emission tomography (PET), flurordeoxyglucose (FDG) PET, cerebrospinal fluid and blood collection (plasma, serum, and whole blood), extensive genetic and multi-omic analyses, and brain donation upon death. This comprehensive evaluation of the human nervous system is performed longitudinally in both mutation carriers and family non-carriers, providing one of the deepest and broadest evaluations of the human brain across decades and through AD progression. These extensive data sets and samples are available for researchers to address scientific questions on the human brain, aging, and AD.
Sex and gender—biological and social constructs—significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories. Understanding the interplay of these factors is central to understanding resilience and resistance mechanisms explaining maintained cognitive function and reduced pathology accumulation in aging and AD. In this narrative review, the ADDRESS! Special Interest Group (Alzheimer's Association) adopted a multidisciplinary approach to provide the foundations and recommendations for future research into sex‐ and gender‐specific drivers of resilience, including a sex/gender‐oriented review of risk factors, genetics, AD and non‐AD pathologies, brain structure and function, and animal research. We urge the field to adopt a sex/gender‐aware approach to resilience to advance our understanding of the intricate interplay of biological and social determinants and consider sex/gender‐specific resilience throughout disease stages.
Highlights
Sex differences in resilience to cognitive decline vary by age and cognitive status.
Initial evidence supports sex‐specific distinctions in brain pathology.
Findings suggest sex differences in the impact of pathology on cognition.
There is a sex‐specific change in resilience in the transition to clinical stages.
Gender and sex factors warrant study: modifiable, immune, inflammatory, and vascular.
Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Computational simulations and animal experiments have hinted at the theory of activity-dependent degeneration as the cause of this hub vulnerability. However, two critical issues remain unresolved. First, past research hasn't disambiguated between the scenario where hub regions face a higher likelihood of connectivity disruption compared to other regions (targeted attack) and a uniformly distributed likelihood of connectivity disruption (random attack). Second, human studies offering support for activity-dependent explanations remain scarce.We refined the hub disruption index to demonstrate a hub disruption pattern in functional connectivity in autosomal dominant AD that aligned with targeted attacks. This hub disruption is detectable even in pre-clinical stages 12 years before the expected symptom onset and amplified alongside symptomatic progression. Moreover, hub disruption was primarily tied to regional differences in global connectivity, and sequentially followed changes observed in Aβ PET cortical markers, consistent with the activity-dependent degeneration explanation. Taken together, our findings deepened the understanding of brain network organization in neurodegenerative diseases and could be instrumental in refining diagnostic and targeted therapeutic strategies for AD in the future.
Long-term manned spaceflight and extraterrestrial planet settlement become the focus of space powers. However, the potential influence of closed and socially isolating spaceflight on the brain function remains unclear. A 180-day controlled ecological life support system integrated experiment was conducted, establishing a spaceflight analog environment to explore the effect of long-term socially isolating living. Three crewmembers were enrolled and underwent resting-state fMRI scanning before and after the experiment. We performed both seed-based and network-based analyses to investigate the functional connectivity (FC) changes of the default mode network (DMN), considering its key role in multiple higher-order cognitive functions. Compared with normal controls, the leader of crewmembers exhibited significantly reduced within-DMN and between-DMN FC after the experiment, while two others exhibited opposite trends. Moreover, individual differences of FC changes were further supported by evidence from behavioral analyses. The findings may shed new light on the development of psychological protection for space exploration.
Purpose: Cerebellar functional connectivity changes have been reported in Alzheimer’s disease (AD), but a comprehensive framework integrating these findings is lacking. This retrospective study investigates the cerebello-thalamo-cortical (CTC) circuit in AD, using functional gradient analysis to elucidate deficits and potential biomarkers.
Method:246 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (58 AD, 103 mild cognitive impairment [MCI], 85 normal cognitions [CN]) underwent 3T MRI. The CTC circuitry was constructed using T1 weighted imaging and resting-state functional MRI. Voxel-based gradient values were analyzed globally, in subfields, and cerebellar functional networks. Cognitive scores (MMSE, MoCA, ADAS-Cog) were assessed at each ADNI site. Statistical analyses included ANCOVA, post hoc analyses, Pearson correlations, LASSO regression, logistic regression, and Kolmogorov-Smirnov tests. False discovery rate (FDR) corrections were used, setting the statistical significance threshold was set at P < 0.05.
Results: AD and MCI individuals exhibited increased CTC connectivity compared to CN (all P < 0.05). Average CTC connectivity did not correlate with cognitive scores (P > 0.05), but specific CTC edges were correlated. LASSO regression identified 20 discriminative edges, achieving high accuracy in AD-CN classification (AUC = 0.92 training, AUC = 0.80 test). Thalamic and cerebellar gradient distributions differed significantly across groups (all P < 0.05), with specific regions showing distinct gradient scores. Five cerebellar functional networks exhibited decreased gradient scores.
Conclusions: This study provides preliminary evidence supporting CTC hyperconnectivity as a potential diagnostic biomarker for AD. It suggests the involvement of the thalamus and cerebellum in cognitive impairment in individuals with AD.
Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels—a phenomenon termed “activity-dependent degeneration”. Yet, two critical issues were unresolved. First, past research hasn’t definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce.
We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence.
Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruption’s severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in Aβ PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset.
Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future.
The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case–control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual’s point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of ‘sporadic’ AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.
The age distribution in developed countries is shifting, with more seniors living to age 80, 90, and beyond. This shift has created a challenge for medical professionals caring for geriatric patients, as an aging population means an increased prevalence of age-related neurodegenerative brain diseases with signs and symptoms such as memory impairment, frank dementia, and motor deterioration.KeywordsFunctional magnetic resonance imagingNeurodegenerative diseaseAlzheimer’s diseaseMild cognitive impairmentDementiaParkinson’s diseaseHuntington’s disease
Background:
Altered glutamatergic neurotransmission may contribute to impaired default mode network (DMN) function in Alzheimer's disease (AD). Among the DMN hub regions, frontal cortex (FC) was suggested to undergo a glutamatergic plasticity response in prodromal AD, while the status of glutamatergic synapses in the precuneus (PreC) during clinical-neuropathological AD progression is not known.
Objective:
To quantify vesicular glutamate transporter VGluT1- and VGluT2-containing synaptic terminals in PreC and FC across clinical stages of AD.
Methods:
Unbiased sampling and quantitative confocal immunofluorescence of cortical VGluT1- and VGluT2-immunoreactive profiles and spinophilin-labeled dendritic spines were performed in cases with no cognitive impairment (NCI), mild cognitive impairment (MCI), mild-moderate AD (mAD), or moderate-severe AD (sAD).
Results:
In both regions, loss of VGluT1-positive profile density was seen in sAD compared to NCI, MCI, and mAD. VGluT1-positive profile intensity in PreC did not differ across groups, while in FC it was greater in MCI, mAD, and sAD compared to NCI. VGluT2 measures were stable in PreC while FC had greater VGluT2-positive profile density in MCI compared to sAD, but not NCI or mAD. Spinophilin measures in PreC were lower in mAD and sAD compared to NCI, while in FC they were stable across groups. Lower VGluT1 and spinophilin measures in PreC, but not FC, correlated with greater neuropathology.
Conclusion:
Frank loss of VGluT1 in advanced AD relative to NCI occurs in both DMN regions. In FC, an upregulation of VGluT1 protein content in remaining glutamatergic terminals may contribute to this region's plasticity response in AD.
Alzheimer's disease (AD) is a multi-etiology disease. The biological system of AD is associated with multidomain genetic, molecular, cellular, and network brain dysfunctions, interacting with central and peripheral immunity. These dysfunctions have been primarily conceptualized according to the assumption that amyloid deposition in the brain, whether from a stochastic or a genetic accident, is the upstream pathological change. However, the arborescence of AD pathological changes suggests that a single amyloid pathway might be too restrictive or inconsistent with a cascading effect. In this review, we discuss the recent human studies of late-onset AD pathophysiology in an attempt to establish a general updated view focusing on the early stages. Several factors highlight heterogenous multi-cellular pathological changes in AD, which seem to work in a self-amplifying manner with amyloid and tau pathologies. Neuroinflammation has an increasing importance as a major pathological driver, and perhaps as a convergent biological basis of aging, genetic, lifestyle and environmental risk factors.
Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer’s disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer’s disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer’s disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light.
Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function.
Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer’s disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer’s disease.
During aging, the brain milieu changes in a multitude of ways, resulting in a decline of physiological functions and increased susceptibility to disease. One of the major age-related pathological changes in the brain is the accumulation of amyloid-β (Aβ) peptides as plaques. The appearance of pathologic Aβ species is believed to trigger Alzheimer’s disease (AD), one of the principal neurodegenerative diseases and the leading cause of dementia, of which aging is the most important risk factor. Accumulation of Aβ in the brain is caused by an imbalance in Aβ kinetics that may arise from aging-related changes in degradation or clearance mechanisms. Aβ is degraded by enzymes such as neprilysin and is removed from the brain via numerous pathways including glial phagocytosis, transport across the blood-brain barrier, interstitial fluid bulk flow, and cerebrospinal fluid absorption. The functional activity of many of these systems declines with aging. Elevated levels of pathogenic Aβ species result in the emergence of senile plaques in the neuropil or as cerebral amyloid angiopathy in blood vessels. In addition, soluble Aβ oligomers appear prior to amyloid fibril formation and have detrimental effects on neuronal functions. To elucidate the pathomechanisms underlying AD, we have previously developed new mouse models that precisely recapitulate amyloid pathology without overexpressing disease-relevant molecules. Here we provide an overview of the catabolism, anabolism, and clearance of Aβ, the characteristics of amyloid pathologies in the human brain, and recent advances in AD research, including new technologies and animal models.KeywordsSenile plaqueCAAAPPBACE1γ-SecretaseNeprilysinAβ transportApoEAPP knock-in miceMarmosetNonhuman primate model
“Brain-predicted age” quantifies apparent brain age compared to normative neuroimaging trajectories. Advanced brain-predicted age has been well established in symptomatic Alzheimer disease (AD), but is underexplored in preclinical AD. Prior brain-predicted age studies have typically used structural MRI, but resting-state functional connectivity (FC) remains underexplored. Our model predicted age from FC in 391 cognitively normal, amyloid-negative controls (ages 18-89). We applied the trained model to 145 amyloid-negative, 151 preclinical AD, and 156 symptomatic AD participants to test group differences. The model accurately predicted age in the training set. FC-predicted brain age gaps (FC-BAG) were significantly older in symptomatic AD and significantly younger in preclinical AD compared to controls. There was minimal correspondence between networks predictive of age and AD. Elevated FC-BAG may reflect network disruption during symptomatic AD. Reduced FC-BAG in preclinical AD was opposite to the expected direction, and may reflect a biphasic response to preclinical AD pathology or may be driven by inconsistency between age-related vs. AD-related networks. Overall, FC-predicted brain age may be a sensitive AD biomarker.
Objective:
The amyloid cascade hypothesis of Alzheimer disease (AD) has been increasingly challenged. Here, we aim to refocus the amyloid cascade hypothesis on its original premise that the accumulation of amyloid beta (Aβ) peptide is the primary and earliest event in AD pathogenesis as based on current evidence, initiating several pathological events and ultimately leading to AD dementia.
Background:
An ongoing debate about the validity of the amyloid cascade hypothesis for AD has been triggered by clinical trials with investigational disease-modifying drugs targeting Aβ that have not demonstrated consistent clinically meaningful benefits.
Updated hypothesis:
It is an open question if monotherapy targeting Aβ pathology could be markedly beneficial at a stage when the brain has been irreversibly damaged by a cascade of pathological changes. Interventions in cognitively unimpaired individuals at risk for dementia, during amyloid-only and pre-amyloid stages, are more appropriate for proving or refuting the amyloid hypothesis. Our updated hypothesis states that anti-Aβ investigational therapies are likely to be most efficacious when initiated in the preclinical (asymptomatic) stages of AD and specifically when the disease is driven primarily by amyloid pathology. Given the young age at symptom onset and the deterministic nature of the mutations, autosomal dominant AD (ADAD) mutation carriers represent the ideal population to evaluate the efficacy of putative disease-modifying Aβ therapies.
Major challenges for the hypothesis:
Key challenges of the amyloid hypothesis include the recognition that disrupted Aβ homeostasis alone is insufficient to produce the AD pathophysiologic process, poor correlation of Aβ with cognitive impairment, and inconclusive data regarding clinical efficacy of therapies targeting Aβ. Challenges of conducting ADAD research include the rarity of the disease and uncertainty of the generalizability of ADAD findings for the far more common "sporadic" late-onset AD.
Linkage to other major theories:
The amyloid cascade hypothesis, modified here to pertain to the preclinical stage of AD, still needs to be integrated with the development and effects of tauopathy and other co-pathologies, including neuroinflammation, vascular insults, synucleinopathy, and many others.
Background:
Down syndrome (DS) is associated with increased risk for Alzheimer's disease (AD). In neurotypical individuals, clinical AD is preceded by reduced resting state functional connectivity in the default mode network (DMN), but it is unknown whether changes in DMN connectivity predict clinical onset of AD in DS.
Objective:
Does lower DMN functional connectivity predict clinical onset of AD and cognitive decline in people with DS?
Methods:
Resting state functional MRI (rsfMRI), longitudinal neuropsychological, and clinical assessment data were collected on 15 nondemented people with DS (mean age = 51.66 years, SD = 5.34 years, range = 42-59 years) over four years, during which 4 transitioned to dementia. Amyloid-β (Aβ) PET data were acquired on 13 of the 15 participants. Resting state fMRI, neuropsychological, and clinical assessment data were also acquired on an independent, slightly younger unimpaired sample of 14 nondemented people with DS (mean age = 44.63 years, SD = 7.99 years, range = 38-61 years).
Results:
Lower functional connectivity between long-range but not short-range DMN regions predicts AD diagnosis and cognitive decline in people with DS. Aβ accumulation in the inferior parietal cortex is associated with lower regional DMN functional connectivity.
Conclusion:
Reduction of long-range DMN connectivity is a potential biomarker for AD in people with DS that precedes and predicts clinical conversion.
Resting-state functional connectivity has been used to study Alzheimer's disease, revealing underlying differences between groups of individuals at different levels of cognitive impairment, or groupwise changes over time. Most of these studies have employed a single scanner and/or a single scan per subject. In this study, we used data collected from a substudy to two randomized clinical trials in patients with mild-to-moderate Alzheimer's Disease to investigate the robustness of functional connectivity in a multicenter, longitudinal setting. This substudy was not powered to detect drug treatment effects. With a basic imaging charter for inter-site acquisition standardization, we found no changes to functional connectivity over time in the placebo group, despite observable changes in clinical test scores and regional brain atrophy. We infer that functional connectivity, as implemented in our study, is not sensitive enough to detect disease progression in our patients. Using an 8-week interval between scans (in both treatment and placebo groups), we found that our test-retest reproducibility was comparable with other published results. We also found that the dominant source of measurement variability was within individuals over time, compared with variability between subjects and sites. Finally, we propose a simple method of visual inspection to identify scans that should be excluded from longitudinal analysis.
Functional brain connectivity of the resting-state networks has gained recent attention as a possible biomarker of Alzheimer’s Disease (AD). In this paper, we review the literature of functional connectivity differences in young adults and middle-aged cognitively intact individuals with non-modifiable risk factors of AD (n = 17). We focus on three main intrinsic resting-state networks: The Default Mode network, Executive network, and the Salience network. Overall, the evidence from the literature indicated early vulnerability of functional connectivity across different at-risk groups, particularly in the Default Mode Network. While there was little consensus on the interpretation on directionality, the topography of the findings showed frequent overlap across studies, especially in regions that are characteristic of AD (i.e., precuneus, posterior cingulate cortex, and medial prefrontal cortex areas). We conclude that while resting-state functional connectivity markers have great potential to identify at-risk individuals, implementing more data-driven approaches, further longitudinal and cross-validation studies, and the analysis of greater sample sizes are likely to be necessary to fully establish the effectivity and utility of resting-state network-based analyses.
Background:
Cerebrospinal fluid t-tau (CSF t-tau) is a measure of neurodegeneration in Alzheimer's disease (AD) and has been increasingly demonstrated to be a non-specific biomarker within the AD continuum.
Objective:
We sought to test whether t-tau influences the longitudinal effects of amyloid-β (Aβ) and phospho-tau (p-tau) on memory and executive function (EF) in mild cognitive impairment (MCI).
Methods:
319 MCI individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with baseline and 2-year CSF Aβ, p-tau, t-tau, and neuropsychological assessments were studied. Mediation and moderation analyses evaluated the role of t-tau in the effects of Aβ and p-tau on memory and EF over 2 years.
Results:
We found that high baseline p-tau but not Aβ was associated with higher t-tau and lower memory scores at 2 years follow-up. The association between p-tau and memory impairment was partially mediated by t-tau, whereby higher p-tau was indirectly associated with lower memory via higher t-tau. t-tau also moderated the association between p-tau and memory. When t-tau level was relatively lower, higher p-tau was associated with lower memory scores at 2 years. When t-tau level was higher, the memory scores were low regardless of the p-tau level.
Conclusion:
Tau-induced neurodegeneration is one key pathway by which AD pathology (p-tau) affects memory impairment. Furthermore, in individuals with lower levels of tau-induced neurodegeneration, higher levels of p-tau were required for memory impairment. Our findings suggest that t-tau plays a significant role in how early AD pathology affects cognitive outcomes.
Background:
Self-referential processing is associated with the progression of Alzheimer's disease (AD), and cerebrospinal fluid (CSF) proteins have become accepted biomarkers of AD.
Objective:
Our objective in this study was to focus on the relationships between the self-referential network (SRN) and CSF pathology in AD-spectrum patients.
Methods:
A total of 80 participants, including 20 cognitively normal, 20 early mild cognitive impairment (EMCI), 20 late MCI (LMCI), and 20 AD, were recruited for this study. Independent component analysis was used to explore the topological SRN patterns, and the abnormalities of this network were identified at different stages of AD. Finally, CSF pathological characteristics (i.e., CSF Aβ, t-tau, and p-tau) that affected the abnormalities of the SRN were further determined during the progression of AD.
Results:
Compared to cognitively normal subjects, AD-spectrum patients (i.e., EMCI, LMCI, and AD) showed a reversing trend toward an association between CSF pathological markers and the abnormal SRN occurring during the progression of AD. However, a certain disease state (i.e., the present LMCI) with a low concentration of CSF tau could evoke more hyperconnectivity of the SRN than other patients with progressively increasing concentrations of CSF tau (i.e., EMCI and AD), and this fluctuation of CSF tau was more sensitive to the hyperconnectivity of the SRN than the dynamic changes of CSF Aβ.
Conclusion:
The integrity of the SRN was closely associated with CSF pathological characteristics, and these findings support the view that the hyperconnectivity of the SRN will play an important role in monitoring the progression of the pre-dementia state to AD.
The order and magnitude of pathologic processes in Alzheimer's disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer's disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease.
In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant's age at baseline assessment and the parent's age at the onset of symptoms of Alzheimer's disease to calculate the estimated years from expected symptom onset (age of the participant minus parent's age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes.
Concentrations of amyloid-beta (Aβ)(42) in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset.
We found that autosomal dominant Alzheimer's disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer's disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer's disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.).
Het concept ‘mild cognitive impairment’ (MCI) wordt gebruikt voor cognitieve stoornissen die niet zo ernstig zijn dat ze aan de criteria van dementie voldoen.
MCI kan veroorzaakt worden door elke neurologische, somatische, of psychiatrische aandoening die het functioneren van de hersenen beïnvloedt.
Het beloop van MCI is variabel en afhankelijk van de onderliggende oorzaak, de definitie van MCI, de setting waarin de patiënt gezien wordt en de leeftijd.
De ziekte van Alzheimer is een belangrijke oorzaak van MCI bij oudere patiënten.
De mogelijkheden voor de behandeling van MCI zijn vooralsnog beperkt.
Recent progress in molecular imaging has provided new important knowledge for further understanding the time course of early pathological disease processes in Alzheimer's disease (AD). Positron emission tomography (PET) amyloid beta (Aβ) tracers such as Pittsburgh Compound B detect increasing deposition of fibrillar Aβ in the brain at the prodromal stages of AD, while the levels of fibrillar Aβ appear more stable at high levels in clinical AD. There is a need for PET ligands to visualize smaller forms of Aβ, oligomeric forms, in the brain and to understand how they interact with synaptic activity and neurodegeneration. The inflammatory markers presently under development might provide further insight into the disease mechanism as well as imaging tracers for tau. Biomarkers measuring functional changes in the brain such as regional cerebral glucose metabolism and neurotransmitter activity seem to strongly correlate with clinical symptoms of cognitive decline. Molecular imaging biomarkers will have a clinical implication in AD not only for early detection of AD but for selecting patients for certain drug therapies and to test disease-modifying drugs. PET fibrillar Aβ imaging together with cerebrospinal fluid biomarkers are promising as biomarkers for early recognition of subjects at risk for AD, for identifying patients for certain therapy and for quantifying anti-amyloid effects. Functional biomarkers such as regional cerebral glucose metabolism together with measurement of the brain volumes provide valuable information about disease progression and outcome of drug treatment.
There is an urgent need to find effective presymptomatic Alzheimer's disease (AD) treatments that reduce the risk of AD symptoms or prevent them completely. It currently takes too many healthy people, too much money and too many years to evaluate the range of promising presymptomatic treatments using clinical endpoints. We have used brain imaging and other measurements to track some of the earliest changes associated with the predisposition to AD. We have proposed the Alzheimer's Prevention Initiative (API) to evaluate investigational amyloid-modifying treatments in healthy people who, based on their age and genetic background, are at the highest imminent risk of developing symptomatic AD using brain imaging, cerebrospinal fluid (CSF), and cognitive endpoints. In one trial, we propose to study AD-causing presenilin 1 [PS1] mutation carriers from the world's largest early-onset AD kindred in Antioquia, Colombia, close to their estimated average age at clinical onset. In another trial, we propose to study apolipoprotein E (APOE) ε4 homozygotes (and possibly heterozygotes) close to their estimated average age at clinical onset. The API has several goals: 1) to evaluate investigational AD-modifying treatments sooner than otherwise possible; 2) to determine the extent to which the treatment's brain imaging and other biomarker effects predict a clinical benefit-information needed to help qualify biomarker endpoints for use in pivotal prevention trials; 3) to provide a better test of the amyloid hypothesis than clinical trials in symptomatic patients, when these treatments may be too little too late to exert their most profound effect; 4) to establish AD prevention registries needed to support these and other presymptomatic AD trials; and 5) to give those individuals at highest imminent risk of AD symptoms access to the most promising investigational treatments in clinical trials.
Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
To examine default mode and salience network functional connectivity as a function of APOE ε4 status in a group of cognitively normal age-, sex-, and education-matched older adults.
Case-control study.
Fifty-six cognitively normal APOE ε4 carriers and 56 age-, sex- and education-matched cognitively normal APOE ε4 noncarriers.
Alterations in in-phase default mode and salience network connectivity in APOE ε4 carriers compared with APOE ε4 noncarriers ranging from 63 to 91 years of age.
A posterior cingulate seed revealed decreased in-phase connectivity in regions of the posterior default mode network that included the left inferior parietal lobe, left middle temporal gyrus, and bilateral anterior temporal lobes in the ε4 carriers relative to APOE ε4 noncarriers. An anterior cingulate seed showed greater in-phase connectivity in the salience network including the cingulate gyrus, medial prefrontal cortex, bilateral insular cortex, striatum, and thalamus in APOE ε4 carriers vs noncarriers. There were no groupwise differences in brain anatomy.
The observation of functional alterations in default mode and salience network connectivity in the absence of structural changes between APOE ε4 carriers and noncarriers suggests that alterations in connectivity may have the potential to serve as an early biomarker.
Although beta-amyloid (Aβ) deposition is a characteristic feature of Alzheimer's disease (AD), this pathology is commonly
found in elderly normal controls (NC). The pattern of Aβ deposition as detected with Pittsburgh compound-B positron emission
tomography (PIB-PET) imaging shows substantial spatial overlap with the default mode network (DMN), a group of brain regions
that typically deactivates during externally driven cognitive tasks. In this study, we show that DMN functional connectivity
(FC) during rest is altered with increasing levels of PIB uptake in NC. Specifically, FC decreases were identified in regions
implicated in episodic memory (EM) processing (posteromedial cortex, ventral medial prefrontal cortex, and angular gyrus),
whereas connectivity increases were detected in dorsal and anterior medial prefrontal and lateral temporal cortices. This
pattern of decreases is consistent with previous studies that suggest heightened vulnerability of EM-related brain regions
in AD, whereas the observed increases in FC may reflect a compensatory response.
Autosomal-dominant Alzheimer's disease has provided significant understanding of the pathophysiology of Alzheimer's disease. The present review summarizes clinical, pathological, imaging, biochemical, and molecular studies of autosomal-dominant Alzheimer's disease, highlighting the similarities and differences between the dominantly inherited form of Alzheimer's disease and the more common sporadic form of Alzheimer's disease. Current developments in autosomal-dominant Alzheimer's disease are presented, including the international Dominantly Inherited Alzheimer Network and this network's initiative for clinical trials. Clinical trials in autosomal-dominant Alzheimer's disease may test the amyloid hypothesis, determine the timing of treatment, and lead the way to Alzheimer's disease prevention.
Identifying high-risk populations is an important component of disease prevention strategies. One approach for identifying at-risk populations for Alzheimer's disease (AD) is examining neuroimaging parameters that differ between patients, including functional connections known to be disrupted within the default-mode network. We have previously shown these same disruptions in cognitively normal elderly who have amyloid-β (Aβ) plaques [detected using Pittsburgh Compound B (PIB) PET imaging], suggesting neuronal toxicity of plaques. Here we sought to determine if pathological effects of apolipoprotein E ε4 (APOE4) genotype could be seen independent of Aβ plaque toxicity by examining resting state fMRI functional connectivity (fcMRI) in participants without preclinical fibrillar amyloid deposition (PIB-). Cognitively normal participants enrolled in longitudinal studies (n = 100, mean age = 62) who were PIB- were categorized into those with and without an APOE4 allele and studied using fcMRI. APOE4 allele carriers (E4+) differed significantly from E4- in functional connectivity of the precuneus to several regions previously defined as having abnormal connectivity in a group of AD participants. These effects were observed before any manifestations of cognitive changes and in the absence of brain fibrillar Aβ plaque deposition, suggesting that early manifestations of a genetic effect can be detected using fcMRI and that these changes may antedate the pathological effects of fibrillar amyloid plaque toxicity.
Amyloid-β (Aβ) plaque deposition can precede the clinical manifestations of dementia of the Alzheimer type (DAT) by many years and can be associated with changes in brain metabolism. Both the Aβ plaque deposition and the changes in metabolism appear to be concentrated in the brain's default-mode network. In contrast to prior studies of brain metabolism which viewed brain metabolism from a unitary perspective that equated glucose utilization with oxygen consumption, we here report on regional glucose use apart from that entering oxidative phosphorylation (so-called "aerobic glycolysis"). Using PET, we found that the spatial distribution of aerobic glycolysis in normal young adults correlates spatially with Aβ deposition in individuals with DAT and cognitively normal participants with elevated Aβ, suggesting a possible link between regional aerobic glycolysis in young adulthood and later development of Alzheimer pathology.
Amyloid deposition is present in 20-50% of nondemented older adults yet the functional consequences remain unclear. The current study found that amyloid accumulation is correlated with functional disruption of the default network as measured by intrinsic activity correlations. Clinically normal participants (n = 38, aged 60-88 years) were characterized using (11)C-labeled Pittsburgh Compound B positron emission tomography imaging to estimate fibrillar amyloid burden and, separately, underwent functional magnetic resonance imaging (fMRI). The integrity of the default network was estimated by correlating rest-state fMRI time courses extracted from a priori regions including the posterior cingulate, lateral parietal, and medial prefrontal cortices. Clinically normal participants with high amyloid burden displayed significantly reduced functional correlations within the default network relative to participants with low amyloid burden. These reductions were also observed when amyloid burden was treated as a continuous, rather than a dichotomous, measure and when controlling for age and structural atrophy. Whole-brain analyses initiated by seeding the posterior cingulate cortex, a region of high amyloid burden in Alzheimer's disease, revealed significant disruption in the default network including functional disconnection of the hippocampal formation.
During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.
• functional MRI
• functional connectivity
• spontaneous activity
Memory function is likely subserved by multiple distributed neural networks, which are disrupted by the pathophysiological process of Alzheimer's disease (AD). In this study, we used multivariate analytic techniques to investigate memory-related functional magnetic resonance imaging (fMRI) activity in 52 individuals across the continuum of normal aging, mild cognitive impairment (MCI), and mild AD. Independent component analyses revealed specific memory-related networks that activated or deactivated during an associative memory paradigm. Across all subjects, hippocampal activation and parietal deactivation demonstrated a strong reciprocal relationship. Furthermore, we found evidence of a nonlinear trajectory of fMRI activation across the continuum of impairment. Less impaired MCI subjects showed paradoxical hyperactivation in the hippocampus compared with controls, whereas more impaired MCI subjects demonstrated significant hypoactivation, similar to the levels observed in the mild AD subjects. We found a remarkably parallel curve in the pattern of memory-related deactivation in medial and lateral parietal regions with greater deactivation in less-impaired MCI and loss of deactivation in more impaired MCI and mild AD subjects. Interestingly, the failure of deactivation in these regions was also associated with increased positive activity in a neocortical attentional network in MCI and AD. Our findings suggest that loss of functional integrity of the hippocampal-based memory systems is directly related to alterations of neural activity in parietal regions seen over the course of MCI and AD. These data may also provide functional evidence of the interaction between neocortical and medial temporal lobe pathology in early AD.
The neural underpinnings of age-related memory impairment remain to be fully elucidated. Using a subsequent memory face–name functional MRI (fMRI) paradigm, young and old adults showed a similar magnitude and extent of hippocampal activation during successful associative encoding. Young adults demonstrated greater deactivation (task-induced decrease in BOLD signal) in medial parietal regions during successful compared with failed encoding, whereas old adults as a group did not demonstrate a differential pattern of deactivation between trial types. The failure of deactivation was particularly evident in old adults who performed poorly on the memory task. These low-performing old adults demonstrated greater hippocampal and prefrontal activation to achieve successful encoding trials, possibly as a compensatory response. Findings suggest that successful encoding requires the coordination of neural activity in hippocampal, prefrontal, and parietal regions, and that age-related memory impairment may be primarily related to a loss of deactivation in medial parietal regions.
• aging
• fMRI
• hippocampus
• default network
• Alzheimer's disease
A family of Finnish descent with very-early-onset Alzheimer's disease has been identified. Genetic analysis of this family eliminated the amyloid precursor protein gene as the pathogenic locus, but strongly implicated a locus on chromosome 14q23.4 between D14S52 and D14S55. The early age at onset of the disease (average, 36 years; range, 35–39 years), the rapid progression, and the early and prominent myoclonus, while they appear to be frequent findings in the chromosome 14–encoded form of Alzheimer's disease, raised the clinical suspicion of prion disease. However, sequencing the prion gene–coding region of 2 affected members of the pedigree failed to show any abnormality. Apart from the presence of modest cortical vacuolar change, the pathological features of our index patient appeared typical of Alzheimer's disease with abundant senile plaques immunoreactive with beta-amyloid, but not with prion protein antibodies.
Background:
We have previously characterised functional brain abnormalities in young adults at genetic risk for late-onset Alzheimer's disease. To gain further knowledge on the preclinical phase of Alzheimer's disease, we sought to characterise structural and functional MRI, CSF, and plasma biomarkers in a cohort of young adults carrying a high-penetrance autosomal dominant mutation that causes early-onset Alzheimer's disease.
Methods:
Between January and August, 2010, 18-26-year-old presenilin 1 (PSEN1) E280A mutation carriers and non-carriers from the Colombian Alzheimer's Prevention Initiative Registry in Medellín Antioquia, Colombia, had structural MRI, functional MRI during associative memory encoding and novel viewing and control tasks, and cognitive assessments. Consenting participants also had lumbar punctures and venepunctures. Outcome measures were task-dependent hippocampal or parahippocampal activations and precuneus or posterior cingulate deactivations, regional grey matter reductions, CSF Aβ(1-42), total tau and phospho-tau(181) concentrations, and plasma Aβ(1-42) concentrations and Aβ(1-42):Aβ(1-40) ratios. Structural and functional MRI data were compared using automated brain mapping algorithms and search regions related to Alzheimer's disease. Cognitive and fluid biomarkers were compared using Mann-Whitney tests.
Findings:
44 participants were included: 20 PSEN1 E280A mutation carriers and 24 non-carriers. The carrier and non-carrier groups did not differ significantly in their dementia ratings, neuropsychological test scores, or proportion of apolipoprotein E (APOE) ɛ4 carriers. Compared with non-carriers, carriers had greater right hippocampal and parahippocampal activation (p=0·001 and p<0·014, respectively, after correction for multiple comparisons), less precuneus and posterior cingulate deactivation (all p<0·010 after correction), and less grey matter in several parietal regions (all p<0·002 uncorrected and corrected p=0·009 in the right parietal search region). In the 20 participants (ten PSEN1 E280A mutation carriers and ten non-carriers) who had lumbar punctures and venepunctures, mutation carriers had higher CSF Aβ(1-42) concentrations (p=0·008) and plasma Aβ(1-42) concentrations (p=0·01) than non-carriers.
Interpretation:
Young adults at genetic risk for autosomal dominant Alzheimer's disease have functional and structural MRI findings and CSF and plasma biomarker findings consistent with Aβ(1-42) overproduction. Although the extent to which the underlying brain changes are either neurodegenerative or developmental remain to be determined, this study shows the earliest known biomarker changes in cognitively normal people at genetic risk for autosomal dominant Alzheimer's disease.
Funding:
Banner Alzheimer's Foundation, Nomis Foundation, Anonymous Foundation, Forget Me Not Initiative, Boston University Department of Psychology, Colciencias, National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the State of Arizona.
Functional magnetic resonance imaging (fMRI) is a non-invasive technique that has come into common use to examine neural network function in normal and impaired cognitive states. Using this promising type of analysis, researchers have identified the presence of anatomically distributed regions operating as large-scale neural networks, which are observed both during the performance of associative memory tasks and in the resting state. The assembly of these anatomically distinct regions into functional ensembles and their choreographed activation and deactivation sets the stage for complex behaviors such as the formation and retrieval of associative memories. We review progress in the use of task-related and task-free MRI to elucidate the changes in neural activity in normal older individuals, patients with mild cognitive impairment, and those with Alzheimer's disease, focusing on the altered activity of the default mode network and medial temporal lobe. We place task-free fMRI studies into the larger context of more traditional, task-based fMRI studies of human memory, which have firmly established the critical role of the medial temporal lobe in associative encoding. Lastly, we discuss the data from our group and others that suggests task-free MRI and task-based fMRI may prove useful as non-invasive biomarkers in studying the progression of memory failure over the course of Alzheimer's disease.
Rare autosomal dominant mutations result in familial Alzheimer's disease (FAD) with a relatively consistent age of onset within families. This provides an estimate of years until disease onset (relative age) in mutation carriers. Increased AD risk has been associated with differences in functional magnetic resonance imaging (fMRI) activity during memory tasks, but most of these studies have focused on possession of apolipoprotein E allele 4 (APOE4), a risk factor, but not causative variant, of late-onset AD. Evaluation of fMRI activity in presymptomatic FAD mutation carriers versus noncarriers provides insight into preclinical changes in those who will certainly develop AD in a prescribed period of time. Adults from FAD mutation-carrying families (nine mutation carriers, eight noncarriers) underwent fMRI scanning while performing a memory task. We examined fMRI signal differences between carriers and noncarriers, and how signal related to fMRI task performance within mutation status group, controlling for relative age and education. Mutation noncarriers had greater retrieval period activity than carriers in several AD-relevant regions, including the left hippocampus. Better performing noncarriers showed greater encoding period activity including in the parahippocampal gyrus. Poorer performing carriers showed greater retrieval period signal, including in the frontal and temporal lobes, suggesting underlying pathological processes. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.
During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. Neurodegenerative diseases have been thought to target these systems, but this hypothesis has not been systematically tested in living humans. We used network-sensitive neuroimaging methods to show that five different neurodegenerative syndromes cause circumscribed atrophy within five distinct, healthy, human intrinsic functional connectivity networks. We further discovered a direct link between intrinsic connectivity and gray matter structure. Across healthy individuals, nodes within each functional network exhibited tightly correlated gray matter volumes. The findings suggest that human neural networks can be defined by synchronous baseline activity, a unified corticotrophic fate, and selective vulnerability to neurodegenerative illness. Future studies may clarify how these complex systems are assembled during development and undermined by disease.
To investigate age-related default mode network (DMN) connectivity in a large cognitively normal elderly cohort and in patients with Alzheimer disease (AD) compared with age-, gender-, and education-matched controls.
We analyzed task-free-fMRI data with both independent component analysis and seed-based analysis to identify anterior and posterior DMNs. We investigated age-related changes in connectivity in a sample of 341 cognitively normal subjects. We then compared 28 patients with AD with 56 cognitively normal noncarriers of the APOE ε4 allele matched for age, education, and gender.
The anterior DMN shows age-associated increases and decreases in fontal lobe connectivity, whereas the posterior DMN shows mainly age-associated declines in connectivity throughout. Relative to matched cognitively normal controls, subjects with AD display an accelerated pattern of the age-associated changes described above, except that the declines in frontal lobe connectivity did not reach statistical significance. These changes survive atrophy correction and are correlated with cognitive performance.
The results of this study indicate that the DMN abnormalities observed in patients with AD represent an accelerated aging pattern of connectivity compared with matched controls.
There is a well-established association between APOE genotype and the risk of developing Alzheimer's disease (AD). Relative to individuals with the common ε3/ε3 genotype, carriers of the ε4 allele are at increased risk of developing AD, while carriers of the ε2 allele appear to be protected against the disease. However, we recently reported that in a sample of cognitively healthy adults, both ε4 and ε2 carriers showed nearly identical changes in the pattern of fMRI activity during memory and non-memory tasks, relative to ε3 homozygotes. These findings suggest that the effects of APOE on brain function are not tightly linked to the effects of this gene on AD risk. Here we test the hypothesis that APOE has an intrinsic effect on the brain's functional networks. Resting-state fMRI was used to compare the pattern of functional connectivity of a variety of resting-state networks between 77 cognitively healthy participants aged 32 to 55 with different APOE genotypes (23 ε2/ε3, 20 ε3/ε3, 26 ε3/ε4, and 8 ε4/ε4). Differences between genotype groups were found in two hippocampal networks, the auditory network, the left frontal-parietal network, and the lateral visual network. While there was considerable variety in the brain regions affected and the direction of change across networks, the main finding was that changes in functional connectivity were similar in ε4 and ε2 carriers, relative to ε3 homozygotes. APOE appears to have an intrinsic effect on the differentiation of functional networks in the brain. This effect is apparent in cognitively healthy adults and does not manifest in a manner reflective of the link between APOE and AD risk. Rather, the effects of APOE on brain function may relate to the role of this gene in neurodevelopment.
Functional connectivity MRI (fcMRI) has been widely applied to explore group and individual differences. A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (>0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks--two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions--a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals.
The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long "preclinical" phase of AD would provide a critical opportunity for therapeutic intervention; however, we need to further elucidate the link between the pathological cascade of AD and the emergence of clinical symptoms. The National Institute on Aging and the Alzheimer's Association convened an international workgroup to review the biomarker, epidemiological, and neuropsychological evidence, and to develop recommendations to determine the factors which best predict the risk of progression from "normal" cognition to mild cognitive impairment and AD dementia. We propose a conceptual framework and operational research criteria, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies. These recommendations are solely intended for research purposes and do not have any clinical implications at this time. It is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD, and ultimately, aid the field in moving toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious.
The neural networks supporting encoding of new information are thought to decline with age, although mnemonic techniques such as repetition may enhance performance in older individuals. Accumulation of amyloid-β, one hallmark pathology of Alzheimer's disease (AD), may contribute to functional alterations in memory networks measured with functional magnetic resonance imaging (fMRI) prior to onset of cognitive impairment. We investigated the effects of age and amyloid burden on fMRI activity in the default network and hippocampus during repetitive encoding. Older individuals, particularly those with high amyloid burden, demonstrated decreased task-induced deactivation in the posteromedial cortices during initial stimulus presentation and failed to modulate fMRI activity in response to repeated trials, whereas young subjects demonstrated a stepwise decrease in deactivation with repetition. The hippocampus demonstrated similar patterns across the groups, showing task-induced activity that decrease