Epistasis analysis links immune cascades and cerebral amyloidosis

Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges

The relevant study of transcriptome-wide variations and neurological disorders in the evolved field of genomic data science is on the rise. Deep learning has been highlighted utilizing algorithms on massive amounts of data in a human-like manner, and is expected to predict the dependency or druggability of hidden mutations within the genome. Enormous mutational variants in coding and noncoding transcripts have been discovered along the genome by far, despite of the fine-tuned genetic proofreading machinery. These variants could be capable of inducing various pathological conditions, including neurological disorders, which require lifelong care. Several limitations and questions emerge, including the use of conventional processes via limited patient-driven sequence acquisitions and decoding-based inferences as well as how rare variants can be deduced as a population-specific etiology. These puzzles require harnessing of advanced systems for precise disease prediction, drug development and drug applications. In this review, we summarize the pathophysiological discoveries of pathogenic variants in both coding and noncoding transcripts in neurological disorders, and the current advantage of deep learning applications. In addition, we discuss the challenges encountered and how to outperform them with advancing interpretation.

Predictive Accuracy of Blood-Derived Biomarkers for Amyloid-β Brain Deposition Along with the Alzheimer's Disease Continuum: A Systematic Review

BACKGROUND

An amyloid-β (Aβ) positron emission tomography (Aβ-PET) scan of the human brain could lead to an early diagnosis of Alzheimer's disease (AD) and estimate disease progression. However, Aβ-PET imaging is expensive, invasive, and rarely applicable to cognitively normal subjects at risk for dementia. The identification of blood biomarkers predictive of Aβ brain deposition could help the identification of subjects at risk for dementia and could be helpful for the prognosis of AD progression.

OBJECTIVE

This study aimed to analyze the prognostic accuracy of blood biomarkers in predicting Aβ-PET status along with progression toward AD.

METHODS

In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched bibliographic databases from 2010 to 2020. The quality of the included studies was assessed by the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool.

RESULTS

A total of 8 studies were retrieved. The prognostic accuracy of Aβ-PET status was calculated by obtaining ROCs for the following biomarkers: free, total, and bound Aβ42 and Aβ40; Aβ42/40 ratio; neurofilaments (NFL); total tau (T-tau); and phosphorylated-tau181 (P-tau181). Higher and lower plasma baseline levels of P-tau181 and the Aβ42/40 ratio, respectively, showed consistently good prognostication of Aβ-PET brain accumulation. Only P-tau181 was shown to predict AD progression.

CONCLUSION

In conclusion, the Aβ42/40 ratio and plasma P-tau181 were shown to predict Aβ-PET status. Plasma P-tau181 could also be a preclinical biomarker for AD progression.

Targeting Alzheimer's Disease at the Right Time and the Right Place: Validation of a Personalized Approach to Diagnosis and Treatment

Cautious optimism is appropriate for a near future (five years) time frame for a number of drugs acting on the different pathophysiological components of Alzheimer’s disease (amyloid deposition, tau hyperphosphorylation, neuroinflammation, vascular changes, to name the most important known so far). Since the relative weight of these components will be different between individuals and will even change over time for each individual, a ‘one drug fit for all’ approach is no longer defensible. Precision medicine using biomarkers in the diagnosis and treatment of Alzheimer’s disease is the new strategy.

Early Life Stress and Epigenetics in Late-onset Alzheimer's Dementia: A Systematic Review

Involvement of life stress in Late-Onset Alzheimer's Disease (LOAD) has been evinced in longitudinal cohort epidemiological studies, and endocrinologic evidence suggests involvements of catecholamine and corticosteroid systems in LOAD. Early Life Stress (ELS) rodent models have successfully demonstrated sequelae of maternal separation resulting in LOAD-analogous pathology, thereby supporting a role of insulin receptor signalling pertaining to GSK-3beta facilitated tau hyper-phosphorylation and amyloidogenic processing. Discussed are relevant ELS studies, and findings from three mitogen-activated protein kinase pathways (JNK/SAPK pathway, ERK pathway, p38/MAPK pathway) relevant for mediating environmental stresses. Further considered were the roles of autophagy impairment, neuroinflammation, and brain insulin resistance. For the meta-analytic evaluation, 224 candidate gene loci were extracted from reviews of animal studies of LOAD pathophysiological mechanisms, of which 60 had no positive results in human LOAD association studies. These loci were combined with 89 gene loci confirmed as LOAD risk genes in previous GWAS and WES. Of the 313 risk gene loci evaluated, there were 35 human reports on epigenomic modifications in terms of methylation or histone acetylation. 64 microRNA gene regulation mechanisms were published for the compiled loci. Genomic association studies support close relations of both noradrenergic and glucocorticoid systems with LOAD. For HPA involvement, a CRHR1 haplotype with MAPT was described, but further association of only HSD11B1 with LOAD found; however, association of FKBP1 and NC3R1 polymorphisms was documented in support of stress influence to LOAD. In the brain insulin system, IGF2R, INSR, INSRR, and plasticity regulator ARC, were associated with LOAD. Pertaining to compromised myelin stability in LOAD, relevant associations were found for BIN1, RELN, SORL1, SORCS1, CNP, MAG, and MOG. Regarding epigenetic modifications, both methylation variability and de-acetylation were reported for LOAD. The majority of up-to-date epigenomic findings include reported modifications in the well-known LOAD core pathology loci MAPT, BACE1, APP (with FOS, EGR1), PSEN1, PSEN2, and highlight a central role of BDNF. Pertaining to ELS, relevant loci are FKBP5, EGR1, GSK3B; critical roles of inflammation are indicated by CRP, TNFA, NFKB1 modifications; for cholesterol biosynthesis, DHCR24; for myelin stability BIN1, SORL1, CNP; pertaining to (epi)genetic mechanisms, hTERT, MBD2, DNMT1, MTHFR2. Findings on gene regulation were accumulated for BACE1, MAPK signalling, TLR4, BDNF, insulin signalling, with most reports for miR-132 and miR-27. Unclear in epigenomic studies remains the role of noradrenergic signalling, previously demonstrated by neuropathological findings of childhood nucleus caeruleus degeneration for LOAD tauopathy.

An isoform-selective p38α mitogen-activated protein kinase inhibitor rescues early entorhinal cortex dysfunctions in a mouse model of Alzheimer's disease

Neuroinflammation is a fundamental mechanism in Alzheimer's disease (AD) progression. The stress-induced activation of the p38α mitogen-activated protein kinase (MAPK) leads to increased production of proinflammatory cytokines and neurodegeneration. We investigated the effects of an isoform selective p38α MAPK inhibitor, MW01-18-150SRM (MW150), administered at 2.5 mg/kg/d (i.p.; 14 days) on early entorhinal cortex (EC) alterations in an AD mouse model carrying human mutations of the amyloid precursor protein (mhAPP). We used electrophysiological analyses with long-term potentiation induction in EC-containing brain slices and EC-relevant associative memory tasks. We found that MW150 was capable of rescuing long-term potentiation in 2-month old mhAPP mice. Acute delivery of MW150 to brain slices was similarly effective in rescuing long-term potentiation, with a comparable efficacy to that of the widely used multikinase inhibitor SB203580. MW150-treated mhAPP mice demonstrated improved ability to discriminate novel associations between objects and their position/context. Our findings suggest that the selective inhibition of the stress-activated p38α MAPK with MW150 can attenuate the EC dysfunctions associated with neuroinflammation in an early stage of AD progression.

Retention of normal glia function by an isoform-selective protein kinase inhibitor drug candidate that modulates cytokine production and cognitive outcomes

BACKGROUND

Brain p38α mitogen-activated protein kinase (MAPK), a potential therapeutic target for cognitive dysfunction based on the neuroinflammation-synaptic dysfunction cycle of pathophysiology progression, offers an innovative pharmacological strategy via inhibiting the same activated target in both glia and neurons, thereby enhancing the possibility for efficacy. The highly selective, brain-penetrant p38αMAPK inhibitor MW150 attenuates cognitive dysfunction in two distinct Alzheimer's disease (AD)-relevant models and avoids the problems encountered with previous mixed-kinase inhibitor drug candidates. Therefore, it is essential that the glial effects of this CNS-active kinase inhibitor be addressed in order to anticipate future use in clinical investigations.

METHODS

We explored the effects of MW150 on glial biology in the AD-relevant APP/PS1 knock-in (KI) mouse model where we previously showed efficacy in suppression of hippocampal-dependent associative and spatial memory deficits. MW150 (2.5 mg/kg/day) was administered daily to 11-12-month-old KI mice for 14 days, and levels of proinflammatory cytokines IL-1β, TNFα, and IL-6 measured in homogenates of mouse cortex using ELISA. Glial markers IBA1, CD45, CD68, and GFAP were assessed by immunohistochemistry. Microglia and amyloid plaques were quantified by immunofluorescence staining followed by confocal imaging. Levels of soluble and insoluble of Aβ40 and Aβ42 were measured by ELISA. The studies of in vivo pharmacodynamic effects on markers of neuroinflammation were complemented by mechanistic studies in the murine microglia BV2 cell line, using live cell imaging techniques to monitor proliferation, migration, and phagocytosis activities.

RESULTS

Intervention with MW150 in KI mice during the established therapeutic time window attenuated the increased levels of IL-1β and TNFα but not IL-6. MW150 treatment also increased the IBA1⁺ microglia within a 15 μm radius of the amyloid plaques, without significantly affecting overall microglia or plaque volume. Levels of IBA1, CD45, CD68, GFAP, and Aβ40 and Aβ42 were not affected by MW150 treatment. MW150 did not significantly alter microglial migration, proliferation, or phagocytosis in BV2 cells.

CONCLUSIONS

Our results demonstrate that MW150 at an efficacious dose can selectively modulate neuroinflammatory responses associated with pathology progression without pan-suppression of normal physiological functions of microglia.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Imaging Alzheimer's disease pathophysiology with PET

Alzheimer's disease (AD) has been reconceptualised as a dynamic pathophysiological process characterized by preclinical, mild cognitive impairment (MCI), and dementia stages. Positron emission tomography (PET) associated with various molecular imaging agents reveals numerous aspects of dementia pathophysiology, such as brain amyloidosis, tau accumulation, neuroreceptor changes, metabolism abnormalities and neuroinflammation in dementia patients. In the context of a growing shift toward presymptomatic early diagnosis and disease-modifying interventions, PET molecular imaging agents provide an unprecedented means of quantifying the AD pathophysiological process, monitoring disease progression, ascertaining whether therapies engage their respective brain molecular targets, as well as quantifying pharmacological responses. In the present study, we highlight the most important contributions of PET in describing brain molecular abnormalities in AD.