Do 2-year changes in superior frontal gyrus and global brain atrophy affect cognition?

Atypical Alzheimer's disease: new insights into an overlapping spectrum between the language and visual variants

Overlap between language and visual variants of atypical Alzheimer's disease (AD) has been reported. However, the extent, frequency of overlap, and its neuroanatomical underpinnings remain unclear. Eighty-two biomarker-confirmed AD patients who presented with either predominant language (n = 34) or visuospatial/perceptual (n = 48) deficits underwent detailed clinical examinations, MRI, and [18F]flortaucipir-PET. Subgroups were defined based on language/visual testing and patterns of volume loss and tau uptake were assessed. 28% of the language group had visual dysfunction (marked in 8%), and 47% of the visual group had language impairment (marked in 26%). Progressive involvement of the parieto-occipital and frontal lobes was noted with greater visual impairment in the language group, and greater left parieto-temporal and frontal involvement with worsening language impairment in the visual group. Only 25% of our cohort showed a pure language or visual presentation, highlighting the high frequency of syndromic overlap in atypical AD and the diagnostic challenge of categorical phenotyping.

Distinct brain iron profiles associated with logopenic progressive aphasia and posterior cortical atrophy

Quantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating local tissue magnetic susceptibility properties at every voxel. Iron deposition patterns are well studied in typical Alzheimer's disease (tAD), but little is known about these patterns in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA). Seventeen PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five-echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions-of-interest across the brain using the Mayo Clinic Adult Lifespan Template. Bayesian hierarchical models were fit per-region and per-hemisphere to compare PCA, LPA, 63 healthy controls, and 20 tAD patients. Strong evidence (posterior probability > 0.99) was observed for greater susceptibility in the middle occipital gyrus and amygdala in both LPA and PCA, and in the right inferior parietal, inferior temporal, and angular gyri in PCA and the caudate and substantia nigra in LPA compared to controls. Moderate evidence for greater susceptibility (posterior probability > 0.90) was also observed in the inferior occipital gyrus, precuneus, putamen and entorhinal cortex in both LPA and PCA, along with superior frontal gyrus in PCA and inferior temporal gyri, insula and basal ganglia in LPA, when compared to controls. Between phenotypic comparisons, LPA had greater susceptibility in the caudate, hippocampus, and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right superior frontal and middle temporal gyri compared to LPA. Both LPA and PCA showed moderate and strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions, while tAD showed greater susceptibility in the hippocampus and basal ganglia. This study proposes the possibility of unique iron profiles existing between LPA and PCA within cortical and subcortical structures. These changes match well with the disease-related changes of the clinical phenotypes, suggesting that QSM could be an informative candidate marker to study iron deposition in these patients.

Introducing ADNP and SIRT1 as new partners regulating microtubules and histone methylation

Activity-dependent neuroprotective protein (ADNP) is essential for brain formation and function. As such, de novo mutations in ADNP lead to the autistic ADNP syndrome and somatic ADNP mutations may drive Alzheimer's disease (AD) tauopathy. Sirtuin 1 (SIRT1) is positively associated with aging, the major risk for AD. Here, we revealed two key interaction sites for ADNP and SIRT1. One, at the microtubule end-binding protein (EB1 and EB3) Tau level, with EB1/EB3 serving as amplifiers for microtubule dynamics, synapse formation, axonal transport, and protection against tauopathy. Two, on the DNA/chromatin site, with yin yang 1, histone deacetylase 2, and ADNP, sharing a DNA binding motif and regulating SIRT1, ADNP, and EB1 (MAPRE1). This interaction was linked to sex- and age-dependent altered histone modification, associated with ADNP/SIRT1/WD repeat-containing protein 5, which mediates the assembly of histone modification complexes. Single-cell RNA and protein expression analyses as well as gene expression correlations placed SIRT1-ADNP and either MAPRE1 (EB1), MAPRE3 (EB3), or both in the same mouse and human cell; however, while MAPRE1 seemed to be similarly regulated to ADNP and SIRT1, MAPRE3 seemed to deviate. Finally, we demonstrated an extremely tight correlation for the gene transcripts described above, including related gene products. This correlation was specifically abolished in affected postmortem AD and Parkinson's disease brain select areas compared to matched controls, while being maintained in blood samples. Thus, we identified an ADNP-SIRT1 complex that may serve as a new target for the understanding of brain degeneration.

Spatial Transcriptomics and In Situ Sequencing to Study Alzheimer's Disease

Although complex inflammatory-like alterations are observed around the amyloid plaques of Alzheimer's disease (AD), little is known about the molecular changes and cellular interactions that characterize this response. We investigate here, in an AD mouse model, the transcriptional changes occurring in tissue domains in a 100-μm diameter around amyloid plaques using spatial transcriptomics. We demonstrate early alterations in a gene co-expression network enriched for myelin and oligodendrocyte genes (OLIGs), whereas a multicellular gene co-expression network of plaque-induced genes (PIGs) involving the complement system, oxidative stress, lysosomes, and inflammation is prominent in the later phase of the disease. We confirm the majority of the observed alterations at the cellular level using in situ sequencing on mouse and human brain sections. Genome-wide spatial transcriptomics analysis provides an unprecedented approach to untangle the dysregulated cellular network in the vicinity of pathogenic hallmarks of AD and other brain diseases.

Alzheimer's Patient Microglia Exhibit Enhanced Aging and Unique Transcriptional Activation

Damage-associated microglia (DAM) profiles observed in Alzheimer's disease (AD)-related mouse models reflect an activation state that could modulate AD risk or progression. To learn whether human AD microglia (HAM) display a similar profile, we develop a method for purifying cell types from frozen cerebrocortical tissues for RNA-seq analysis, allowing better transcriptome coverage than typical single-nucleus RNA-seq approaches. The HAM profile we observe bears little resemblance to the DAM profile. Instead, HAM display an enhanced human aging profile, in addition to other disease-related changes such as APOE upregulation. Analyses of whole-tissue RNA-seq and single-cell/nucleus RNA-seq datasets corroborate our findings and suggest that the lack of DAM response in human microglia occurs specifically in AD tissues, not other neurodegenerative settings. These results, which can be browsed at http://research-pub.gene.com/BrainMyeloidLandscape, provide a genome-wide picture of microglial activation in human AD and highlight considerable differences between mouse models and human disease.

Epigenetic Regulation of BMAL1 with Sleep Disturbances and Alzheimer's Disease

BACKGROUND

An early symptom of Alzheimer's disease (AD) is a disturbance of the circadian rhythm that is associated with disrupted sleep/wake cycles.

OBJECTIVE

To investigate if BMAL1, a key gene that drives the circadian cycle, is epigenetically regulated in brains in relation to longitudinal changes in cognition, sleep quality, and AD neuropathology.

METHODS

Frontal cortex tissues were acquired from the Manchester Brain Bank (N = 96). DNA methylation at six CpG sites at the promoter of BMAL1, determined using bisulfite pyrosequencing, was tested for associations with Braak stage, CERAD score and Thal phase, longitudinal changes in cognition, sleep measurements and cross-section measures of depressive symptoms (BDI score).

RESULTS

Methylation across all the CpGs strongly correlated with each other. We found increased CpG2 methylation with higher Braak (t(92), p = 0.015) and CERAD (t(94), p = 0.044) stages. No significance was found between longitudinal fluid intelligence, processing speed and memory tests, but methylation at CpG1 (r = 0.20, p = 0.05) and CpG4 (r = 0.20, p = 0.05) positively correlated with vocabulary. CpG2 positively correlated with cross-sectional fluid intelligence (r = 0.20 p = 0.05) and vocabulary (r = 0.22 p = 0.03). Though longitudinal analysis revealed no significance between sleep duration, midsleep and efficiency for any of the CpG sites, CpG3 (B = 0.03, 95% CI, p = 0.03) and CpG5 (B = 0.04, 95% CI, p = 0.01) significantly correlated with night wake. CpG4 correlated with depressive symptoms (B = -0.27, 95% CI, p = 0.02).

CONCLUSION

Methylation of BMAL1 associated with tau pathology, changes in cognitive measures, a measure of sleep and depressive symptoms, suggesting an involvement of the circadian cycle.

Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images

We present the application of limited one-time sampling irregularity map (LOTS-IM): a fully automatic unsupervised approach to extract brain tissue irregularities in magnetic resonance images (MRI), for quantitatively assessing white matter hyperintensities (WMH) of presumed vascular origin, and multiple sclerosis (MS) lesions and their progression. LOTS-IM generates an irregularity map (IM) that represents all voxels as irregularity values with respect to the ones considered "normal". Unlike probability values, IM represents both regular and irregular regions in the brain based on the original MRI's texture information. We evaluated and compared the use of IM for WMH and MS lesions segmentation on T2-FLAIR MRI with the state-of-the-art unsupervised lesions' segmentation method, Lesion Growth Algorithm from the public toolbox Lesion Segmentation Toolbox (LST-LGA), with several well established conventional supervised machine learning schemes and with state-of-the-art supervised deep learning methods for WMH segmentation. In our experiments, LOTS-IM outperformed unsupervised method LST-LGA on WMH segmentation, both in performance and processing speed, thanks to the limited one-time sampling scheme and its implementation on GPU. Our method also outperformed supervised conventional machine learning algorithms (i.e., support vector machine (SVM) and random forest (RF)) and deep learning algorithms (i.e., deep Boltzmann machine (DBM) and convolutional encoder network (CEN)), while yielding comparable results to the convolutional neural network schemes that rank top of the algorithms developed up to date for this purpose (i.e., UResNet and UNet). LOTS-IM also performed well on MS lesions segmentation, performing similar to LST-LGA. On the other hand, the high sensitivity of IM on depicting signal change deems suitable for assessing MS progression, although care must be taken with signal changes not reflective of a true pathology.