Abstract
This is an exciting time and a significant milestone for the treatment of Alzheimer's. After decades of failures in finding a cure for Alzheimer's, recently, the U.S. Food and Drug Administration (FDA) has approved anti-amyloid drug lecanemab. At the Alzheimer's Association International Conference very exciting data on new treatment donanemab for Alzheimer's disease were presented. The results show donanemab slowed cognitive decline by 35% in patients with early-stage Alzheimer's. It is expected the FDA will make a decision on the drug's approval by the year's end. This will accelerate further inventions and development of subcutaneous and oral formulations of anti-amyloid therapies and therapies aimed at other targets.
Another development in the Alzheimer's field is the positron emission tomography (PET) biomarkers. Apart from amyloid, tau imaging is now licensed by the FDA and the diagnostic criterion for Alzheimer's has continuously been revised. There are several new plasma and cerebrospinal fluid biomarkers.
Brain Connectivity, a leading print journal covering clinical neurology, neuroscience, and neuroimaging, has recently expanded the remit to cover a much broader field of neurology and neuroscience. This gives the journal audience an opportunity to have a comprehensive knowledge of advances in the field.
The involvement of the brain in different neurological diseases is accompanied by different molecular changes and neuropathological processes. Pathological substrates such as amyloid deposition, tau deposition, microglial activation, synuclein pathology, astrocyte activation, mitochondrial function, and other changes in structural and functional connectivity are closely interrelated. Stroke is associated with multiple downstream events, which could lead to persistent changes in the neuropathological processes.
After the expansion of the remit of Brain Connectivity, we are now inviting articles in the field of Clinical Neurology, Neuroscience, & Neuroimaging by focusing on
▪ Alzheimer's disease, Frontotemporal dementia, Lewy Body dementia, and other neurodegenerative diseases
▪ Movement disorders, including Parkinson's disease
▪ Stroke and multiple sclerosis
▪ Neurological complications and their mechanism after emerging infections.
▪ Biology of human aging.
We invite you to submit articles focusing on the aforementioned theme. Any of the following themes will be of huge interest: ▪ Clinical and translational research ▪ Review articles in the field of clinical neurology, neuroscience, and neuroimaging ▪ Novel PET and magnetic resonance imaging (MRI) markers in neurodegenerative diseases and stroke ▪ Influence of genetic and epigenetic factors on neurodegenerative diseases ▪ Structural and functional connectivity in brain disorders ▪ Multimodal imaging in brain disorders in both human subjects and animal models ▪ Experimental techniques combining MRI (connectivity), electroencephalography, magnetoencephalography, PET, single photon emission computed tomography, and other new and evolving methods.
For more information about the journal, including scope and instructions for authors, please visit our website
Feel free to contact editor-in-chief Dr. Paul Edison at
In this special issue, you will find articles covering highly relevant topics.
Mass Spectrometry Imaging in Alzheimer's Disease (https://doi.org/10.1089/brain.2022.0057 )
Alzheimer's is characterized by amyloid-beta (Aβ) pathology. Although the formation of amyloid plaques in human brains is suggested to be a key factor in initiating Alzheimer pathogenesis, the upstream events that lead to Aβ plaque formation and its metabolism is not fully understood.
Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MSI) has been successfully introduced to study Alzheimer's pathology in brain tissue both in Alzheimer's mouse models and human samples. Masaya Ikegawa and Jörg Hanrieder along with their colleagues used MALDI-MSI, to demonstrate a highly selective deposition of Aβ peptides in Alzheimer's brains with a variety of cerebral amyloid angiopathy.
MALDI-MSI visualized depositions of shorter peptides in Alzheimer's brains; Aβ 1-36 to Aβ 1-39 were quite similarly distributed with Aβ 1-40 as a vascular pattern, deposition of Aβ 1-42 and Aβ 1-43 were visualized with a distinct senile plaque pattern distributed in the parenchyma.
Additionally, they introduce the methodological concepts and challenges of MALDI MSI for the studies of Alzheimer's pathogenesis.
Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease (https://doi.org/10.1089/brain.2020.0847 )
Alzheimer's is the most common age-related dementia. The initial stages of dementia can be associated with mild symptoms, and symptom progression to a more severe state is heterogeneous across patients. Recent study has demonstrated the potential for functional network mapping to assist in the prediction of symptomatic progression. However, this study has primarily used static functional connectivity (sFC) from resting-state functional magnetic resonance imaging (rs-fMRI). Dynamic functional connectivity (dFC) has been recognized as a powerful advance in functional connectivity methodology to differentiate brain network dynamics between healthy and diseased populations.
Mohammed Sendi and Robyn L Miller along with their colleagues applied Group independent component analysis to extract 17 components within the cognitive control network (CCN) from 1385 individuals across varying stages of Alzheimer's symptomology. They estimated dFC among 17 components within the CCN, followed by clustering the dFCs into 3 recurring brain states, and then estimated a hidden Markov model and the occupancy rate for each subject. Then, they investigated the link between CCN dFC connectivity features with Alzheimer's progression. They also investigated the link between sFC and Alzheimer's progression and compared its results with dFC results.
Progression of Alzheimer's symptoms were associated with increases in connectivity within the middle frontal gyrus. Very mild Alzheimer's subjects showed less connectivity within the inferior parietal lobule (in both sFC and dFC) and between this region with the rest of CCN (in dFC analysis). They found within-middle frontal gyrus connectivity increases with Alzheimer's progression in both sFC and dFC results. Finally, comparing with very mild Alzheimer's, they found that the normal brain spends significantly more time in a state with lower within-middle frontal gyrus connectivity and higher connectivity between the hippocampus and the rest of CCN, highlighting the importance of assessing the dynamics of brain connectivity Alzheimer's.
Concordance of Intrinsic Brain Connectivity Measures is Disrupted in Alzheimer's Disease (https://doi.org/10.1089/brain.2020.0918 )
Recently, a new rs-fMRI measure to evaluate the concordance between different rs-fMRI metrics has been proposed and has not been investigated in Alzheimer's.
Özgür Onur and Julian Dronse along with their colleagues obtained 3T rs-fMRI data from healthy young controls (YC), senior controls (SC) and Alzheimer's patients. The fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were analyzed, followed by the calculation of their concordance using Kendall's W for each brain voxel across time. Group differences in the concordance were compared globally, within seven intrinsic brain networks, and on a voxel-by-voxel basis with covariates of age, sex, head motion, and gray matter volume.
The global concordance was lowest in Alzheimer's among the three groups, with similar differences for the single metrics. When comparing Alzheimer's to SC, reductions of concordance were detected in each of the investigated networks apart from the limbic network. For SC in comparison with YC, lower global concordance without any network-level difference was observed. Voxel-wise analyses revealed lower concordance in the right middle temporal gyrus in Alzheimer's compared with SC, and lower concordance in the left middle frontal gyrus in SC compared with YC. Lower fALFF was observed in the right angular gyrus in Alzheimer's in comparison with SC, but ReHo and DC showed no group differences.
They conclude that resting-state measures differentiate Alzheimer's from healthy aging and may represent a novel imaging marker in Alzheimer's.
Hypermetabolic Cerebellar Connectome in Alzheimer's Disease (https://doi.org/10.1089/brain.2020.0937 )
Hypermetabolism in the cerebellum in Alzheimer's has been consistently observed but often neglected as an artefact produced by the commonly used proportional scaling procedure in the statistical parametric mapping. Vinay Gupta and Ji Hyun Ko along with their colleagues hypothesize that the hypermetabolic regions are important in disease pathology in Alzheimer's.
Using FDG-PET images from Alzheimer's subjects and age-sex matched normal controls the authors developed general linear model-based classifier that differentiated Alzheimer's patients from normal individuals. They constructed region–region groupwise correlation matrices and evaluated differences in network organization using graph theory analysis between Alzheimer's and control subjects.
First they confirm that hypermetabolism in the cerebellum in Alzheimer's is not an artefact by replicating it using white matter as the reference region. They further investigate hypermetabolic cerebellum using graph theory. The differences in betweenness centrality (BC) between Alzheimer's versus NL network were correlated with region weights of FDG PET-based Alzheimer's classifier. In particular, the hypermetabolism in cerebellum was accompanied with higher BC. The brain regions with higher BC in Alzheimer's network showed a progressive increase in FDG uptake over 2 years in prodromal Alzheimer's patients.
The authors conclude that hypermetabolism in the cerebellum associated with Alzheimer's may play an important role in forming the Alzheimer's-related metabolic network.
It is with great pleasure to inform you that the Impact factor of Brain Connectivity has gone up to 3.4. I would like to thank all the researchers, editors, and reviewers of Brain Connectivity, and all the staff at Mary Ann Liebert, Inc. publishers for their hard work in advancing the research.