Relationship between β-amyloid and structural network topology in decedents without dementia

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum

Both plasma biomarkers and brain network topology have shown great potential in the early diagnosis of Alzheimer's disease (AD). However, the specific associations between plasma AD biomarkers, structural network topology, and cognition across the AD continuum have yet to be fully elucidated. This retrospective study evaluated participants from the Sino Longitudinal Study of Cognitive Decline cohort between September 2009 and October 2022 with available blood samples or 3.0-T MRI brain scans. Plasma biomarker levels were measured using the Single Molecule Array platform, including β-amyloid (Aβ), phosphorylated tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). The topological structure of brain white matter was assessed using network efficiency. Trend analyses were carried out to evaluate the alterations of the plasma markers and network efficiency with AD progression. Correlation and mediation analyses were conducted to further explore the relationships among plasma markers, network efficiency, and cognitive performance across the AD continuum. Among the plasma markers, GFAP emerged as the most sensitive marker (linear trend: t = 11.164, p = 3.59 × 10-24 ; quadratic trend: t = 7.708, p = 2.25 × 10-13 ; adjusted R2  = 0.475), followed by NfL (linear trend: t = 6.542, p = 2.9 × 10-10 ; quadratic trend: t = 3.896, p = 1.22 × 10-4 ; adjusted R2  = 0.330), p-tau181 (linear trend: t = 8.452, p = 1.61 × 10-15 ; quadratic trend: t = 6.316, p = 1.05 × 10-9 ; adjusted R2  = 0.346) and Aβ42/Aβ40 (linear trend: t = -3.257, p = 1.27 × 10-3 ; quadratic trend: t = -1.662, p = 9.76 × 10-2 ; adjusted R2  = 0.101). Local efficiency decreased in brain regions across the frontal and temporal cortex and striatum. The principal component of local efficiency within these regions was correlated with GFAP (Pearson's R = -0.61, p = 6.3 × 10-7 ), NfL (R = -0.57, p = 6.4 × 10-6 ), and p-tau181 (R = -0.48, p = 2.0 × 10-4 ). Moreover, network efficiency mediated the relationship between general cognition and GFAP (ab = -0.224, 95% confidence interval [CI] = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA) or NfL (ab = -0.224, 95% CI = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA). Our findings suggest that network efficiency mediates the association between plasma biomarkers, specifically GFAP and NfL, and cognitive performance in the context of AD progression, thus highlighting the potential utility of network-plasma approaches for early detection, monitoring, and intervention strategies in the management of AD.

Multiscale network neuroscience in neuro-oncology: How tumors, brain networks, and behavior connect across scales

Network neuroscience refers to the investigation of brain networks across different spatial and temporal scales, and has become a leading framework to understand the biology and functioning of the brain. In neuro-oncology, the study of brain networks has revealed many insights into the structure and function of cells, circuits, and the entire brain, and their association with both functional status (e.g., cognition) and survival. This review connects network findings from different scales of investigation, with the combined aim of informing neuro-oncological healthcare professionals on this exciting new field and also delineating the promising avenues for future translational and clinical research that may allow for application of network methods in neuro-oncological care.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Nigral Pathology Contributes to Microstructural Integrity of Striatal and Frontal Tracts in Parkinson's Disease

BACKGROUND

Motor and cognitive impairment in Parkinson's disease (PD) is associated with dopaminergic dysfunction that stems from substantia nigra (SN) degeneration and concomitant α-synuclein accumulation. Diffusion magnetic resonance imaging (MRI) can detect microstructural alterations of the SN and its tracts to (sub)cortical regions, but their pathological sensitivity is still poorly understood.

OBJECTIVE

To unravel the pathological substrate(s) underlying microstructural alterations of SN, and its tracts to the dorsal striatum and dorsolateral prefrontal cortex (DLPFC) in PD.

METHODS

Combining post-mortem in situ MRI and histopathology, T1-weighted and diffusion MRI, and neuropathological samples of nine PD, six PD with dementia (PDD), five dementia with Lewy bodies (DLB), and 10 control donors were collected. From diffusion MRI, mean diffusivity (MD) and fractional anisotropy (FA) were derived from the SN, and tracts between the SN and caudate nucleus, putamen, and DLPFC. Phosphorylated-Ser129-α-synuclein and tyrosine hydroxylase immunohistochemistry was included to quantify nigral Lewy pathology and dopaminergic degeneration, respectively.

RESULTS

Compared to controls, PD and PDD/DLB showed increased MD of the SN and SN-DLPFC tract, as well as increased FA of the SN-caudate nucleus tract. Both PD and PDD/DLB showed nigral Lewy pathology and dopaminergic loss compared to controls. Increased MD of the SN and FA of SN-caudate nucleus tract were associated with SN dopaminergic loss. Whereas increased MD of the SN-DLPFC tract was associated with increased SN Lewy neurite load.

CONCLUSIONS

In PD and PDD/DLB, diffusion MRI captures microstructural alterations of the SN and tracts to the dorsal striatum and DLPFC, which differentially associates with SN dopaminergic degeneration and Lewy neurite pathology. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Modular Level Alterations Of Structural-Functional Connectivity Coupling in Mild Cognitive Impairment Patients and Interactions with Age Effect

BACKGROUND

Structural-functional connectivity (SC- FC) coupling is related to various cognitive functions and more sensitive for the detection of subtle brain alterations.

OBJECTIVE

To investigate whether decoupling of SC-FC was detected in mild cognitive impairment (MCI) patients on a modular level, the interaction effect of aging and disease, and its relationship with network efficiency.

METHODS

73 patients with MCI and 65 healthy controls were enrolled who underwent diffusion tensor imaging and resting-state functional MRI to generate structural and functional networks. Five modules were defined based on automated anatomical labeling 90 atlas, including default mode network (DMN), frontoparietal attention network (FPN), sensorimotor network (SMN), subcortical network (SCN), and visual network (VIS). Intra-module and inter-module SC-FC coupling were compared between two groups. The interaction effect of aging and group on modular SC-FC coupling was further analyzed by two-way ANOVA. The correlation between the coupling and network efficiency was finally calculated.

RESULTS

In MCI patients, aberrant intra-module coupling was noted in SMN, and altered inter-module coupling was found in the other four modules. Intra-module coupling exhibited significant age-by-group effects in DMN and SMN, and inter-module coupling showed significant age-by-group effects in DMN and FPN. In MCI patients, both positive or negative correlations between coupling and network efficiency were found in DMN, FPN, SCN, and VIS.

CONCLUSION

SC-FC coupling could reflect the association of SC and FC, especially in modular levels. In MCI, SC-FC coupling could be affected by the interaction effect of aging and disease, which may shed light on advancing the pathophysiological mechanisms of MCI.

Neuroinflammation in Alzheimer's Disease: Current Progress in Molecular Signaling and Therapeutics

Alzheimer's disease, a neurodegenerative disease with amyloid beta accumulation as a major hallmark, has become a dire global health concern as there is a lack of clear understanding of the causative agent. It is a major cause of dementia which is increasing exponentially with age. Alzheimer's disease is marked by tau hyperphosphorylation and amyloid beta accumulation that robs people of their memories. Amyloid beta deposition initiated a spectrum of microglia-activated neuroinflammation, and microglia and astrocyte activation elicited expressions of various inflammatory and anti-inflammatory cytokines. Neuroinflammation is one of the cardinal features of Alzheimer's disease. Pro-inflammatory cytokine signaling plays multifarious roles in neurodegeneration and neuroprotection. Induction of proinflammatory signaling leads to discharge of immune mediators which affect functions of neurons and cause cell death. Sluggish anti-inflammatory system also contributes to neuroinflammation. Numerous pathways like NFκB, p38 MAPK, Akt/mTOR, caspase, nitric oxide, and COX are involved in triggering brain immune cells like astrocytes and microglia to secrete inflammatory cytokines such as tumor necrosis factor, interleukins, and chemokines and participate in Alzheimer's disease pathology. PPAR-γ agonists tend to boost the phagocytosis of amyloid beta and decrease the inflammatory cytokine IL-1β. Recent findings suggest the cross-link between gut microbiota and neuroinflammation contributing in AD which has been explained in this study. The role of cellular, molecular pathways and involvement of inflammatory mediators in neuroinflammation has also been described; targeting them could be a potential therapeutic strategy for treatment of AD.

OUP accepted manuscript

Cognitive deficits in Alzheimer’s disease, specifically amnestic (memory dominant) deficits, are associated with cholinergic degeneration in the basal forebrain. The cholinergic nucleus within the basal forebrain, the nucleus basalis of Meynert, exhibits local atrophy and reduced cortical tract integrity on MRI, and reveals amyloid-β and phosphorylated-tau pathology at autopsy. To understand the pathophysiology of nucleus basalis of Meynert atrophy and its neocortical projections in Alzheimer’s disease, we used a combined post-mortem in situ MRI and histopathology approach. A total of 19 Alzheimer’s disease (10 amnestic and nine non-amnestic) and nine non-neurological control donors underwent 3 T T₁-weighted MRI for anatomical delineation and volume assessment of the nucleus basalis of Meynert, and diffusion-weighted imaging for microstructural assessment of the nucleus and its projections. At subsequent brain autopsy, tissue dissection and immunohistochemistry were performed for amyloid-β, phosphorylated-tau and choline acetyltransferase. Compared to controls, we observed an MRI-derived volume reduction and altered microstructural integrity of the nucleus basalis of Meynert in Alzheimer’s disease donors. Furthermore, decreased cholinergic cell density was associated with reduced integrity of the nucleus and its tracts to the temporal lobe, specifically to the temporal pole of the superior temporal gyrus, and the parahippocampal gyrus. Exploratory post hoc subgroup analyses indicated that cholinergic cell density could be associated with cortical tract alterations in amnestic Alzheimer’s disease donors only. Our study illustrates that in Alzheimer’s disease, cholinergic degeneration in the nucleus basalis of Meynert may contribute to damaged cortical projections, specifically to the temporal lobe, leading to cognitive deterioration.

Cellular Substrates of Functional Network Integration and Memory in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of drug-resistant TLE patients (n = 31), who underwent pseudo resting-state functional magnetic resonance imaging (fMRI), resting-state magnetoencephalography (MEG) and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.

The human connectome in Alzheimer disease - relationship to biomarkers and genetics

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.