Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment

Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer’s disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44). Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education) and better maintenance of memory in mild cognitive impairment (MCI). Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC) and in an independent validation sample (23 MCI/32 HC). Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual) was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN), but positively correlated with the dorsal-attention network (DAN). Greater education predicted stronger LFC-DMN-connectivity (anti-correlation) and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI

The BIN1 rs744373 SNP is associated with increased tau-PET levels and impaired memory

© 2019, The Author(s). The single nucleotide polymorphism (SNP) rs744373 in the bridging integrator-1 gene (BIN1) is a risk factor for Alzheimer’s disease (AD). In the brain, BIN1 is involved in endocytosis and sustaining cytoskeleton integrity. Post-mortem and in vitro studies suggest that BIN1-associated AD risk is mediated by increased tau pathology but whether rs744373 is associated with increased tau pathology in vivo is unknown. Here we find in 89 older individuals without dementia, that BIN1 rs744373 risk-allele carriers show higher AV1451 tau-PET across brain regions corresponding to Braak stages II–VI. In contrast, the BIN1 rs744373 SNP was not associated with AV45 amyloid-PET uptake. Furthermore, the rs744373 risk-allele was associated with worse memory performance, mediated by increased global tau levels. Together, our findings suggest that the BIN1 rs744373 SNP is associated with increased tau but not beta-amyloid pathology, suggesting that alterations in BIN1 may contribute to memory deficits via increased tau pathology

Connectomics and molecular imaging in neurodegeneration.

Our understanding on human neurodegenerative disease was previously limited to clinical data and inferences about the underlying pathology based on histopathological examination. Animal models and in vitro experiments have provided evidence for a cell-autonomous and a non-cell-autonomous mechanism for the accumulation of neuropathology. Combining modern neuroimaging tools to identify distinct neural networks (connectomics) with target-specific positron emission tomography (PET) tracers is an emerging and vibrant field of research with the potential to examine the contributions of cell-autonomous and non-cell-autonomous mechanisms to the spread of pathology. The evidence provided here suggests that both cell-autonomous and non-cell-autonomous processes relate to the observed in vivo characteristics of protein pathology and neurodegeneration across the disease spectrum. We propose a synergistic model of cell-autonomous and non-cell-autonomous accounts that integrates the most critical factors (i.e., protein strain, susceptible cell feature and connectome) contributing to the development of neuronal dysfunction and in turn produces the observed clinical phenotypes. We believe that a timely and longitudinal pursuit of such research programs will greatly advance our understanding of the complex mechanisms driving human neurodegenerative diseases.The Molecular Imaging of Neurodegeneration Cologne (MINC) Symposium was partly funded by the Deutsche Forschungsgemeinschaft (DFG) awarded to Dr. Thilo van Eimeren (EI 892/5-1). The Deutsche Forschungsgemeinschaft (DFG) also awarded funding to Dr. Alexander Drzezga (DR442/91)

Correspondence Between Resting-State and Episodic Memory-Task Related Networks in Elderly Subjects

Resting-state fMRI studies demonstrated temporally synchronous fluctuations in brain activity among ensembles of brain regions, suggesting the existence of intrinsic functional networks. A spatial match between some of the resting-state networks and regional brain activation during cognitive tasks has been noted, suggesting that resting-state networks support particular cognitive abilities. However, the spatial match and predictive value of any resting-state network and regional brain activation during episodic memory is only poorly understood. In order to address this research gap, we obtained fMRI acquired both during rest and a face-name association task in 38 healthy elderly subjects. In separate independent component analyses, networks of correlated brain activity during rest or the episodic memory task were identified. For the independent components identified for task-based fMRI, the design matrix of successful encoding or retrieval trials was regressed against the time course of each of the component to identify significantly activated networks. Spatial regression was used to assess the match of resting-state networks against those related to successful memory encoding or retrieval. We found that resting-state networks covering the medial temporal, middle temporal, and frontal areas showed increased activity during successful encoding. Resting-state networks located within posterior brain regions showed increased activity during successful recognition. However, the level of resting-state network connectivity was not predictive of the task-related activity in these networks. These results suggest that a circumscribed number of functional networks detectable during rest become engaged during successful episodic memory. However, higher intrinsic connectivity at rest may not translate into higher network expression during episodic memory

Higher CSF sTREM2 attenuates ApoE4-related risk for cognitive decline and neurodegeneration

BACKGROUND: The Apolipoprotein E ε4 allele (i.e. ApoE4) is the strongest genetic risk factor for sporadic Alzheimer's disease (AD). TREM2 (i.e. Triggering receptor expressed on myeloid cells 2) is a microglial transmembrane protein brain that plays a central role in microglia activation in response to AD brain pathologies. Whether higher TREM2-related microglia activity modulates the risk to develop clinical AD is an open question. Thus, the aim of the current study was to assess whether higher sTREM2 attenuates the effects of ApoE4-effects on future cognitive decline and neurodegeneration. METHODS: We included 708 subjects ranging from cognitively normal (CN, n = 221) to mild cognitive impairment (MCI, n = 414) and AD dementia (n = 73) from the Alzheimer's disease Neuroimaging Initiative. We used linear regression to test the interaction between ApoE4-carriage by CSF-assessed sTREM2 levels as a predictor of longitudinally assessed cognitive decline and MRI-assessed changes in hippocampal volume changes (mean follow-up of 4 years, range of 1.7-7 years). RESULTS: Across the entire sample, we found that higher CSF sTREM2 at baseline was associated with attenuated effects of ApoE4-carriage (i.e. sTREM2 x ApoE4 interaction) on longitudinal global cognitive (p = 0.001, Cohen's f2 = 0.137) and memory decline (p = 0.006, Cohen's f2 = 0.104) as well as longitudinally assessed hippocampal atrophy (p = 0.046, Cohen's f2 = 0.089), independent of CSF markers of primary AD pathology (i.e. Aβ1-42, p-tau181). While overall effects of sTREM2 were small, exploratory subanalyses stratified by diagnostic groups showed that beneficial effects of sTREM2 were pronounced in the MCI group. CONCLUSION: Our results suggest that a higher CSF sTREM2 levels are associated with attenuated ApoE4-related risk for future cognitive decline and AD-typical neurodegeneration. These findings provide further evidence that TREM2 may be protective against the development of AD

The left frontal cortex supports reserve in aging by enhancing functional network efficiency

Background: Recent evidence from fMRI studies suggests that functional hubs, i.e. highly connected brain regions, are important for mental health. We found recently that global connectivity of a hub in the left frontal cortex (LFC-connectivity) is associated with relatively preserved memory abilities and higher levels of protective factors (education, IQ) in normal aging and Alzheimer’s disease. These results suggest that LFC-connectivity supports reserve capacity alleviating memory decline. An open question is, however, why LFC-connectivity is beneficial and supports memory function in the face of neurodegeneration. We hypothesized that higher LFCconnectivity is associated with enhanced efficiency in connected major networks involved in episodic memory. We further hypothesized that higher LFC-related network efficiency predicts higher memory abilities. Methods: We assessed fMRI during a face-name association learning task in 26 healthy cognitively normal elderly participants. Using beta-series correlation analysis, we computed task-related LFC-connectivity to key memory networks including the default-mode network (DMN) and dorsal attention network (DAN). Network efficiency within the DMN and DAN was estimated by the graph theoretical small-worldness statistic. We applied linear regression analyses in order to test the association between LFC-connectivity to the DMN/DAN and small-worldness of these networks. Mediation analysis was applied to test LFC-connectivity to the DMN and DAN as a mediator of the association between education and higher DMN and DAN smallworldness. Lastly, we tested network small-worldness as a predictor of memory performance. Results: We found that higher LFC-connectivity to the DMN and DAN during successful memory encoding and recognition was associated with higher small-worldness of those networks. Higher task-related LFC-connectivity mediated the association between education and higher small-worldness in the DMN and DAN. Further, higher small-worldness of these networks predicted better performance in the memory task. Conclusions: The current results suggest that higher education-related LFC-connectivity to key memory networks during a memory task is associated with higher network efficiency and thus enhanced reserve of memory abilities in aging

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease‐informed machine‐learning

Introduction Developing cross‐validated multi‐biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. Methods We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid‐PET and fluorodeoxyglucose positron‐emission tomography (FDG‐PET) to predict rates of cognitive decline. Prediction models were trained in autosomal‐dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross‐validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model‐based risk enrichment was estimated. Results A model combining all biomarker modalities and established in ADAD predicted the 4‐year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model‐based risk‐enrichment reduced the sample size required for detecting simulated intervention effects by 50%–75%. Discussion Our independently validated machine‐learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD

Assessment of perfusion deficit with early phases of [18F]PI-2620 tau-PET versus [18F]flutemetamol-amyloid-PET recordings

Purpose Characteristic features of amyloid-PET (A), tau-PET (T), and FDG-PET (N) can serve for the A/T/N classification of neurodegenerative diseases. Recent studies showed that the early, perfusion-weighted phases of amyloid- or tau-PET recordings serve to detect cerebrometabolic deficits equally to FDG-PET, therefore providing a surrogate of neuronal injury. As such, two channels of diagnostic information can be obtained in the setting of a single PET scan. However, there has hitherto been no comparison of early-phase amyloid- and tau-PET as surrogates for deficits in perfusion/metabolism. Therefore, we undertook to compare [18F]flutemetamol-amyloid-PET and [18F]PI-2620 tau-PET as “one-stop shop” dual purpose tracers for the detection of neurodegenerative disease. Methods We obtained early-phase PET recordings with [18F]PI-2620 (0.5–2.5 min p.i.) and [18F]flutemetamol (0–10 min p.i.) in 64 patients with suspected neurodegenerative disease. We contrasted global mean normalized images (SUVr) in the patients with a normal cohort of 15 volunteers without evidence of increased pathology to β-amyloid- and tau-PET examinations. Regional group differences of tracer uptake (z-scores) of 246 Brainnetome volumes of interest were calculated for both tracers, and the correlations of the z-scores were evaluated using Pearson’s correlation coefficient. Lobar compartments, regions with significant neuronal injury (z-scores <  − 3), and patients with different neurodegenerative disease entities (e.g., Alzheimer’s disease or 4R-tauopathies) served for subgroup analysis. Additionally, we used partial regression to correlate regional perfusion alterations with clinical scores in cognition tests. Results The z-scores of perfusion-weighted images of both tracers showed high correlations across the brain, especially in the frontal and parietal lobes, which were the brain regions with pronounced perfusion deficit in the patient group (R = 0.83 ± 0.08; range, 0.61–0.95). Z-scores of individual patients correlated well by region (R = 0.57 ± 0.15; range, 0.16–0.90), notably when significant perfusion deficits were present (R = 0.66 ± 0.15; range, 0.28–0.90). Conclusion The early perfusion phases of [18F]PI-2620 tau- and [18F]flutemetamol-amyloid-PET are roughly equivalent indices of perfusion defect indicative of regional and lobar neuronal injury in patients with various neurodegenerative diseases. As such, either tracer may serve for two diagnostic channels by assessment of amyloid/tau status and neuronal activity

Segregation of functional networks is associated with cognitive resilience in Alzheimer's disease

Cognitive resilience is an important modulating factor of cognitive decline in Alzheimer's disease, but the functional brain mechanisms that support cognitive resilience remain elusive. Given previous findings in normal aging, we tested the hypothesis that higher segregation of the brain's connectome into distinct functional networks represents a functional mechanism underlying cognitive resilience in Alzheimer's disease. Using resting-state functional MRI, we assessed both resting-state-fMRI global system segregation, i.e. the balance of between-network to within-network connectivity, and the alternate index of modularity Q as predictors of cognitive resilience. We performed all analyses in two independent samples for validation: First, we included 108 individuals with autosomal dominantly inherited Alzheimer's disease and 71 non-carrier controls. Second, we included 156 amyloid-PET positive subjects across the spectrum of sporadic Alzheimer's disease as well as 184 amyloid-negative controls. In the autosomal dominant Alzheimer's disease sample, disease severity was assessed by estimated years from symptom onset. In the sporadic Alzheimer's sample, disease stage was assessed by temporal-lobe tau-PET (i.e. composite across Braak stage I & III regions). In both samples, we tested whether the effect of disease severity on cognition was attenuated at higher levels of functional network segregation. For autosomal dominant Alzheimer's disease, we found higher fMRI-assessed system segregation to be associated with an attenuated effect of estimated years from symptom onset on global cognition (p = 0.007). Similarly, for sporadic Alzheimer's disease patients, higher fMRI-assessed system segregation was associated with less decrement in global cognition (p = 0.001) and episodic memory (p = 0.004) per unit increase of temporal lobe tau-PET. Confirmatory analyses using the alternate index of modularity Q revealed consistent results. In conclusion, higher segregation of functional connections into distinct large-scale networks supports cognitive resilience in Alzheimer's disease