Transcriptional vulnerability of brain regions in Alzheimer's disease and dementia

Structural MRI of brain similarity networks

Recent advances in structural MRI analytics now allow the network organization of individual brains to be comprehensively mapped through the use of the biologically principled metric of anatomical similarity. In this Review, we offer an overview of the measurement and meaning of structural MRI similarity, especially in relation to two key assumptions that often underlie its interpretation: (i) that MRI similarity can be representative of architectonic similarity between cortical areas and (ii) that similar areas are more likely to be axonally connected, as predicted by the homophily principle. We first introduce the historical roots and technical foundations of MRI similarity analysis and compare it with the distinct MRI techniques of structural covariance and tractography analysis. We contextualize this empirical work with two generative models of homophilic networks: an economic model of cost-constrained connectional homophily and a heterochronic model of ontogenetically phased cortical maturation. We then review (i) studies of the genetic and transcriptional architecture of MRI similarity in population-averaged and disorder-specific contexts and (ii) developmental studies of normative cohorts and clinical studies of neurodevelopmental and neurodegenerative disorders. Finally, we prioritize knowledge gaps that must be addressed to consolidate structural MRI similarity as an accessible, valid marker of the architecture and connectivity of an individual brain network.

Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet

Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimer's disease cases and 149 controls.

Human brain organoids containing microglia that have arisen innately adapt to a β-amyloid challenge better than those in which microglia are integrated by co-culture

BACKGROUND

Alzheimer disease (AD) is a heterogenous and multifactorial disease, and its pathology is partly driven by microglia and their activated phenotype. Brain organoids (BOs) are gaining prominence as a relevant model of the human brain for the study of AD; however, BOs are commonly devoid of microglia. To overcome this limitation, current protocols incorporate microglia through either (1) co-culture (BO co-culture), or (2) molecular manipulation at critical windows of BO development to have microglia arise innately (BO innate cultures). It is currently unclear whether the microglia incorporated into BOs by either of these two protocols differ in function.

METHODS

At in vitro day 90, BO innate cultures and BO-co-cultures were challenged with the AD-related β-amyloid peptide (Aβ) for up to 72 h. After Aβ challenge, BOs were collected for immunoblotting. Immunoblots compared immunodensity and protein banding of Aβ and ionized calcium-binding adapter molecule 1 (IBA1, a marker of microglial activation) in BOs. The translational potential of these observations was supported using 56 human cortical samples from neurocognitively normal donors and patients with early-onset AD and late-onset AD. Statistical analyses were conducted using the Kruskal-Wallis test, a two-way ANOVA, or a simple linear regression, and where applicable, followed by Dunn's or Sidak's test.

RESULTS

We show that BO co-cultures promote Aβ oligomerization as early as 24 h and this coincides with a significant increase in IBA1 levels. In contrast, the Aβs do not oligomerize in BO innate cultures and the IBA1 response was modest and only emerged after 48 h. In human cortical samples, we found IBA1 levels correlated with age at onset, age at death, and the putative diagnostic Aβ(1-42)/Aβ(1-40) ratio (particularly in their oligomeric forms) in a sex-dependent manner.

CONCLUSIONS

Our unique observations suggest that BOs with innate microglia model the response of a healthy brain to Aβ, and by extension the initial stages of Aβ challenge. It would be impossible to model these early stages of pathogenesis in BOs where microglia are already compromised, such as those with microglia incorporated by co-culture.

Beyond memory impairment: the complex phenotypic landscape of Alzheimer's disease

Neuropsychiatric symptoms (NPSs) in Alzheimer's disease (AD) constitute multifaceted behavioral manifestations that reflect processes of emotional regulation, thinking, and social behavior. They are as prevalent in AD as cognitive impairment and develop independently during the progression of neurodegeneration. As studying NPSs in AD is clinically challenging, most AD research to date has focused on cognitive decline. In this opinion article we summarize emerging literature on the prevalence, time course, and the underlying genetic, molecular, and pathological mechanisms related to NPSs in AD. Overall, we propose that NPSs constitute a cluster of core symptoms in AD, and understanding their neurobiology can lead to a more holistic approach to AD research, paving the way for more accurate diagnostic tests and personalized treatments embracing the goals of precision medicine.

Regulation of cell distancing in peri-plaque glial nets by Plexin-B1 affects glial activation and amyloid compaction in Alzheimer's disease

Communication between glial cells has a profound impact on the pathophysiology of Alzheimer's disease (AD). We reveal here that reactive astrocytes control cell distancing in peri-plaque glial nets, which restricts microglial access to amyloid deposits. This process is governed by guidance receptor Plexin-B1 (PLXNB1), a network hub gene in individuals with late-onset AD that is upregulated in plaque-associated astrocytes. Plexin-B1 deletion in a mouse AD model led to reduced number of reactive astrocytes and microglia in peri-plaque glial nets, but higher coverage of plaques by glial processes, along with transcriptional changes signifying reduced neuroinflammation. Additionally, a reduced footprint of glial nets was associated with overall lower plaque burden, a shift toward dense-core-type plaques and reduced neuritic dystrophy. Altogether, our study demonstrates that Plexin-B1 regulates peri-plaque glial net activation in AD. Relaxing glial spacing by targeting guidance receptors may present an alternative strategy to increase plaque compaction and reduce neuroinflammation in AD.

The role of cognitive flexibility on higher level executive functions in mild cognitive impairment and healthy older adults

BACKGROUND

Mild Cognitive Impairment (MCI) is a preclinical condition between healthy and pathological aging, which is characterized by impairments in executive functions (EFs), including cognitive flexibility. According to Diamond's model, cognitive flexibility is a core executive function, along with working memory and inhibition, but it requires the development of these last EFs to reach its full potential. In this model, planning and fluid intelligence are considered higher-level EFs. Given their central role in enabling individuals to adapt their daily life behavior efficiently, the goal is to gain valuable insight into the functionality of cognitive flexibility in a preclinical form of cognitive decline. This study aims to investigate the role of cognitive flexibility and its components, set-shifting and switching, in MCI. The hypotheses are as follows: (I) healthy participants are expected to perform better than those with MCI on cognitive flexibility and higher-level EFs tasks, taking into account the mediating role of global cognitive functioning; (II) cognitive flexibility can predict performance on higher-level EFs (i.e., planning and fluid intelligence) tasks differently in healthy individuals and those diagnosed with MCI.

METHODS

Ninety participants were selected and divided into a healthy control group (N = 45; mean age 64.1 ± 6.80; 66.6% female) and an MCI group (N = 45; mean age 65.2 ± 8.14; 40% female). Cognitive flexibility, fluid intelligence, planning, and global cognitive functioning of all participants were assessed using standardized tasks.

RESULTS

Results indicated that individuals with MCI showed greater impairment in global cognitive functioning and EFs performance. Furthermore, the study confirms the predictive role of cognitive flexibility for higher EFs in individuals with MCI and only partially in healthy older adults.

Case-control virtual histology elucidates cell types associated with cortical thickness differences in Alzheimer's disease

Many neuropsychiatric disorders are characterised by altered cortical thickness, but the cell types underlying these changes remain largely unknown. Virtual histology (VH) approaches map regional patterns of gene expression with regional patterns of MRI-derived phenotypes, such as cortical thickness, to identify cell types associated with case-control differences in those MRI measures. However, this method does not incorporate valuable information of case-control differences in cell type abundance. We developed a novel method, termed case-control virtual histology (CCVH), and applied it to Alzheimer's disease (AD) and dementia cohorts. Leveraging a multi-region gene expression dataset of AD cases (n = 40) and controls (n = 20), we quantified AD case-control differential expression of cell type-specific markers across 13 brain regions. We then correlated these expression effects with MRI-derived AD case-control cortical thickness differences across the same regions. Cell types with spatially concordant AD-related effects were identified through resampling marker correlation coefficients. Among regions thinner in AD, gene expression patterns identified by CCVH suggested fewer excitatory and inhibitory neurons, and greater proportions of astrocytes, microglia, oligodendrocytes, oligodendrocyte precursor cells, and endothelial cells in AD cases vs. controls. In contrast, original VH identified expression patterns suggesting that excitatory but not inhibitory neuron abundance was associated with thinner cortex in AD, despite the fact that both types of neurons are known to be lost in the disorder. Compared to original VH, cell types identified through CCVH are more likely to directly underlie cortical thickness differences in AD. Sensitivity analyses suggest our results are largely robust to specific analysis choices, like numbers of cell type-specific marker genes used and background gene sets used to construct null models. As more multi-region brain expression datasets become available, CCVH will be useful for identifying the cellular correlates of cortical thickness across neuropsychiatric illnesses.

Sex specific molecular networks and key drivers of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a progressive and age-associated neurodegenerative disorder that affects women disproportionally. However, the underlying mechanisms are poorly characterized. Moreover, while the interplay between sex and ApoE genotype in AD has been investigated, multi-omics studies to understand this interaction are limited. Therefore, we applied systems biology approaches to investigate sex-specific molecular networks of AD.

METHODS

We integrated large-scale human postmortem brain transcriptomic data of AD from two cohorts (MSBB and ROSMAP) via multiscale network analysis and identified key drivers with sexually dimorphic expression patterns and/or different responses to APOE genotypes between sexes. The expression patterns and functional relevance of the top sex-specific network driver of AD were further investigated using postmortem human brain samples and gene perturbation experiments in AD mouse models.

RESULTS

Gene expression changes in AD versus control were identified for each sex. Gene co-expression networks were constructed for each sex to identify AD-associated co-expressed gene modules shared by males and females or specific to each sex. Key network regulators were further identified as potential drivers of sex differences in AD development. LRP10 was identified as a top driver of the sex differences in AD pathogenesis and manifestation. Changes of LRP10 expression at the mRNA and protein levels were further validated in human AD brain samples. Gene perturbation experiments in EFAD mouse models demonstrated that LRP10 differentially affected cognitive function and AD pathology in sex- and APOE genotype-specific manners. A comprehensive mapping of brain cells in LRP10 over-expressed (OE) female E4FAD mice suggested neurons and microglia as the most affected cell populations. The female-specific targets of LRP10 identified from the single cell RNA-sequencing (scRNA-seq) data of the LRP10 OE E4FAD mouse brains were significantly enriched in the LRP10-centered subnetworks in female AD subjects, validating LRP10 as a key network regulator of AD in females. Eight LRP10 binding partners were identified by the yeast two-hybrid system screening, and LRP10 over-expression reduced the association of LRP10 with one binding partner CD34.

CONCLUSIONS

These findings provide insights into key mechanisms mediating sex differences in AD pathogenesis and will facilitate the development of sex- and APOE genotype-specific therapies for AD.

MicroRNA (miRNA) Complexity in Alzheimer's Disease (AD)

AD is a complex, progressive, age-related neurodegenerative disorder representing the most common cause of senile dementia and neurological dysfunction in our elderly domestic population. The widely observed heterogeneity of AD is a reflection of the complexity of the AD process itself and the altered molecular-genetic mechanisms operating in the diseased human brain and CNS. One of the key players in this complex regulation of gene expression in human pathological neurobiology are microRNAs (miRNAs) that, through their actions, shape the transcriptome of brain cells that normally associate with very high rates of genetic activity, gene transcription and messenger RNA (mRNA) generation. The analysis of miRNA populations and the characterization of their abundance, speciation and complexity can further provide valuable clues to our molecular-genetic understanding of the AD process, especially in the sporadic forms of this common brain disorder. Current in-depth analyses of high-quality AD and age- and gender-matched control brain tissues are providing pathophysiological miRNA-based signatures of AD that can serve as a basis for expanding our mechanistic understanding of this disorder and the future design of miRNA- and related RNA-based therapeutics. This focused review will consolidate the findings from multiple laboratories as to which are the most abundant miRNA species, both free and exosome-bound in the human brain and CNS, which miRNA species appear to be the most prominently affected by the AD process and review recent developments and advancements in our understanding of the complexity of miRNA signaling in the hippocampal CA1 region of AD-affected brains.

Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet

Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimer's disease cases and 149 controls.

Definition of the contribution of an Osteopontin-producing CD11c+ microglial subset to Alzheimer's disease

Alzheimer's disease (AD) is the most common form of incurable dementia and represents a critical public health issue as the world's population ages. Although microglial dysregulation is a cardinal feature of AD, the extensive heterogeneity of these immunological cells in the brain has impeded our understanding of their contribution to this disease. Here, we identify a pathogenic microglial subset which expresses the CD11c surface marker as the sole producer of Osteopontin (OPN) in the 5XFAD mouse model of AD. OPN production divides Disease-Associated Microglia (DAM) into two functionally distinct subsets, i.e., a protective CD11c+OPN- subset that robustly ingests amyloid β (Aβ) in a noninflammatory fashion and a pathogenic CD11c+OPN+ subset that produces proinflammatory cytokines and fails to ingest significant amounts of Aβ. Genetic ablation of OPN or administration of monoclonal anti-OPN antibody to 5XFAD mice reduces proinflammatory microglia, plaque formation, and numbers of dystrophic neurites and results in improved cognitive function. Analysis of brain tissue from AD patients indicates that levels of OPN-producing CD11c+ microglia correlate strongly with the degree of cognitive deficit and AD neuropathology. These findings define an OPN-dependent pathway to disease driven by a distinct microglial subset, and identify OPN as a novel therapeutic target for potentially effective immunotherapy to treat AD.

Regional transcriptional vulnerability to basal forebrain functional dysconnectivity in mild cognitive impairment patients

Nucleus basalis of Meynert (NbM), one of the earliest targets of Alzheimer's disease (AD), may act as a seed for pathological spreading to its connected regions. However, the underlying basis of regional vulnerability to NbM dysconnectivity remains unclear. NbM functional dysconnectivity was assessed using resting-state fMRI data of health controls and mild cognitive impairment (MCI) patients from the Alzheimer's disease Neuroimaging Initiative (ADNI2/GO phase). Transcriptional correlates of NbM dysconnectivity was explored by leveraging public intrinsic and differential post-mortem brain-wide gene expression datasets from Allen Human Brain Atlas (AHBA) and Mount Sinai Brain Bank (MSBB). By constructing an individual-level tissue-specific gene set risk score (TGRS), we evaluated the contribution of NbM dysconnectivity-correlated gene sets to change rate of cerebral spinal fluid (CSF) biomarkers during preclinical stage of AD, as well as to MCI onset age. An independent cohort of health controls and MCI patients from ADNI3 was used to validate our main findings. Between-group comparison revealed significant connectivity reduction between the right NbM and right middle temporal gyrus in MCI. This regional vulnerability to NbM dysconnectivity correlated with intrinsic expression of genes enriched in protein and immune functions, as well as with differential expression of genes enriched in cholinergic receptors, immune, vascular and energy metabolism functions. TGRS of these NbM dysconnectivity-correlated gene sets are associated with longitudinal amyloid-beta change at preclinical stages of AD, and contributed to MCI onset age independent of traditional AD risks. Our findings revealed the transcriptional vulnerability to NbM dysconnectivity and their crucial role in explaining preclinical amyloid-beta change and MCI onset age, which offer new insights into the early AD pathology and encourage more investigation and clinical trials targeting NbM.

Genome-Wide Analysis of Periodontal and Peri-implant Cells and Tissues

-Omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, are powerful means of generating comprehensive genome-level data sets on complex diseases. We have systematically assessed the transcriptome, microbiome, miRNome, and methylome of gingival and peri-implant tissues from human subjects and further studied the transcriptome of primary cells ex vivo, or in vitro after infection with periodontal pathogens.Our data offer new insight on the pathophysiology underlying periodontal and peri-implant diseases, a possible route to a better and earlier diagnosis of these highly prevalent chronic inflammatory diseases and thus, to a personalized and efficient treatment approach.Herein, we outline the laboratory steps required for the processing of periodontal cells and tissues for -omics analyses using current microarrays or next-generation sequencing technology.

Common signatures of differential microRNA expression in Parkinson's and Alzheimer's disease brains

Dysregulation of microRNA gene expression has been implicated in many neurodegenerative diseases, including Parkinson's disease. However, the individual dysregulated microRNAs remain largely unknown. Previous meta-analyses have highlighted several microRNAs being differentially expressed in post-mortem Parkinson's disease and Alzheimer's disease brains versus controls, but they were based on small sample sizes. In this study, we quantified the expression of the most compelling Parkinson's and Alzheimer's disease microRNAs from these meta-analyses ('candidate miRNAs') in one of the largest Parkinson's/Alzheimer's disease case-control post-mortem brain collections available (n = 451), thereby quadruplicating previously investigated sample sizes. Parkinson's disease candidate microRNA hsa-miR-132-3p was differentially expressed in our Parkinson's (P = 4.89E-06) and Alzheimer's disease samples (P = 3.20E-24) compared with controls. Alzheimer's disease candidate microRNAs hsa-miR-132-5p (P = 4.52E-06) and hsa-miR-129-5p (P = 0.0379) were differentially expressed in our Parkinson's disease samples. Combining these novel data with previously published data substantially improved the statistical support (α = 3.85E-03) of the corresponding meta-analyses, clearly implicating these microRNAs in both Parkinson's and Alzheimer's disease. Furthermore, hsa-miR-132-3p/-5p (but not hsa-miR-129-5p) showed association with α-synuclein neuropathological Braak staging (P = 3.51E-03/P = 0.0117), suggesting that hsa-miR-132-3p/-5p play a role in α-synuclein aggregation beyond the early disease phase. Our study represents the largest independent assessment of recently highlighted candidate microRNAs in Parkinson's and Alzheimer's disease brains, to date. Our results implicate hsa-miR-132-3p/-5p and hsa-miR-129-5p to be differentially expressed in both Parkinson's and Alzheimer's disease, pinpointing shared pathogenic mechanisms across these neurodegenerative diseases. Intriguingly, based on publicly available high-throughput sequencing of RNA isolated by cross-linking immunoprecipitation data, hsa-miR-132 may interact with SNCA messenger RNA in the human brain, possibly pinpointing novel therapeutic approaches in fighting Parkinson's disease.

Transcriptomic profiling of sporadic Alzheimer's disease patients

Alzheimer's disease (AD) manifested before age 65 is commonly referred to as early-onset AD (EOAD) (Reitz et al. Neurol Genet. 2020;6:e512). While the majority (> 90%) of EOAD cases are not caused by autosomal-dominant mutations in PSEN1, PSEN2, and APP, they do have a higher heritability (92-100%) than sporadic late-onset AD (LOAD, 70%) (Wingo et al. Arch Neurol. 2012;69:59-64, Fulton-Howard et al. Neurobiol Aging. 2021;99:101.e1-101.e9). Although the endpoint clinicopathological changes, i.e., Aβ plaques, tau tangles, and cognitive decline, are common across EOAD and LOAD, the disease progression is highly heterogeneous (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). This heterogeneity, leading to temporally distinct age at onset (AAO) and stages of cognitive decline, may be caused by myriad combinations of distinct disease-associated molecular mechanisms. We and others have used transcriptome profiling in AD patient-derived neuron models of autosomal-dominant EOAD and sporadic LOAD to identify disease endotypes (Caldwell et al. Sci Adv Am Assoc Adv Sci. 2020;6:eaba5933, Mertens et al. Cell Stem Cell. 2021;28:1533-1548.e6, Caldwell et al. Alzheimers Demen. 2022). Further, analyses of large postmortem brain cohorts demonstrate that only one-third of AD patients show hallmark disease endotypes like increased inflammation and decreased synaptic signaling (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). Areas of the brain less affected by AD pathology at early disease stages-such as the primary visual cortex-exhibit similar transcriptomic dysregulation as those regions traditionally affected and, therefore, may offer a view into the molecular mechanisms of AD without the associated inflammatory changes and gliosis induced by pathology (Haroutunian et al. Neurobiol Aging. 2009;30:561-73). To this end, we analyzed AD patient samples from the primary visual cortex (19 EOAD, 20 LOAD) using transcriptomic signatures to identify patient clusters and disease endotypes. Interestingly, although the clusters showed distinct combinations and severity of endotypes, each patient cluster contained both EOAD and LOAD cases, suggesting that AAO may not directly correlate with the identity and severity of AD endotypes.

Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis

The assessment of Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) associated with brain changes remains a challenging task. Recent studies have demonstrated that combination of multi-modality imaging techniques can better reflect pathological characteristics and contribute to more accurate diagnosis of AD and MCI. In this paper, we propose a novel tensor-based multi-modality feature selection and regression method for diagnosis and biomarker identification of AD and MCI from normal controls. Specifically, we leverage the tensor structure to exploit high-level correlation information inherent in the multi-modality data, and investigate tensor-level sparsity in the multilinear regression model. We present the practical advantages of our method for the analysis of ADNI data using three imaging modalities (VBM-MRI, FDG-PET and AV45-PET) with clinical parameters of disease severity and cognitive scores. The experimental results demonstrate the superior performance of our proposed method against the state-of-the-art for the disease diagnosis and the identification of disease-specific regions and modality-related differences. The code for this work is publicly available at https://github.com/junfish/BIOS22.

The three-dimensional landscape of cortical chromatin accessibility in Alzheimer's disease

To characterize the dysregulation of chromatin accessibility in Alzheimer's disease (AD), we generated 636 ATAC-seq libraries from neuronal and nonneuronal nuclei isolated from the superior temporal gyrus and entorhinal cortex of 153 AD cases and 56 controls. By analyzing a total of ~20 billion read pairs, we expanded the repertoire of known open chromatin regions (OCRs) in the human brain and identified cell-type-specific enhancer-promoter interactions. We show that interindividual variability in OCRs can be leveraged to identify cis-regulatory domains (CRDs) that capture the three-dimensional structure of the genome (3D genome). We identified AD-associated effects on chromatin accessibility, the 3D genome and transcription factor (TF) regulatory networks. For one of the most AD-perturbed TFs, USF2, we validated its regulatory effect on lysosomal genes. Overall, we applied a systematic approach to understanding the role of the 3D genome in AD. We provide all data as an online resource for widespread community-based analysis.

Engagement of vascular early response genes typifies mild cognitive impairment

INTRODUCTION

Molecular responses in the brains of persons with mild cognitive impairment (MCI), the earliest transitional state between normal aging and early Alzheimer's disease (AD), are poorly understood.

METHODS

We examined AD-related neuropathology and transcriptome changes in the neocortex of individuals with MCI relative to controls and temporal responses to the mild hypoxia in mouse brains.

RESULTS

Subsets of vascular early response to hypoxia genes were upregulated in MCI prior to the buildup of AD neuropathology. Early activation of pro-angiogenic hypoxia-inducible factor signaling in response to mild hypoxia was detected in mouse brains similar to those that were altered in MCI. Protracted responses to hypoxia were characterized by activation of phosphoinositide 3-kinase (PI3K)-protein kinase B (Akt)-the mammalian target of rapamycin (mTOR) pathways in brain microvessel isolates.

DISCUSSION

These findings suggest that cerebrovascular remodeling is an important antecedent to the development of dementia and a component of the homeostatic response to reduced oxygen tension in aging prior to the onset of AD.

Preservation Analysis on Spatiotemporal Specific Co-expression Networks Suggests the Immunopathogenesis of Alzheimer's Disease

The occurrence and development of Alzheimer’s disease (AD) is a continuous clinical and pathophysiological process, molecular biological, and brain functional change often appear before clinical symptoms, but the detailed underlying mechanism is still unclear. The expression profiling of postmortem brain tissue from AD patients and controls provides evidence about AD etiopathogenesis. In the current study, we used published AD expression profiling data to construct spatiotemporal specific coexpression networks in AD and analyzed the network preservation features of each brain region in different disease stages to identify the most dramatically changed coexpression modules and obtained AD-related biological pathways, brain regions and circuits, cell types and key genes based on these modules. As result, we constructed 57 spatiotemporal specific networks (19 brain regions by three disease stages) in AD and observed universal expression changes in all 19 brain regions. The eight most dramatically changed coexpression modules were identified in seven brain regions. Genes in these modules are mostly involved in immune response-related pathways and non-neuron cells, and this supports the immune pathology of AD and suggests the role of blood brain barrier (BBB) injuries. Differentially expressed genes (DEGs) meta-analysis and protein–protein interaction (PPI) network analysis suggested potential key genes involved in AD development that might be therapeutic targets. In conclusion, our systematical network analysis on published AD expression profiling data suggests the immunopathogenesis of AD and identifies key brain regions and genes.

A Bayesian group lasso classification for ADNI volumetrics data

The primary objective of this paper is to develop a statistically valid classification procedure for analyzing brain image volumetrics data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in elderly subjects with cognitive impairments. The Bayesian group lasso method thereby proposed for logistic regression efficiently selects an optimal model with the use of a spike and slab type prior. This method selects groups of attributes of a brain subregion encouraged by the group lasso penalty. We conduct simulation studies for high- and low-dimensional scenarios where our method is always able to select the true parameters that are truly predictive among a large number of parameters. The method is then applied on dichotomous response ADNI data which selects predictive atrophied brain regions and classifies Alzheimer's disease patients from healthy controls. Our analysis is able to give an accuracy rate of 80% for classifying Alzheimer's disease. The suggested method selects 29 brain subregions. The medical literature indicates that all these regions are associated with Alzheimer's patients. The Bayesian method of model selection further helps selecting only the subregions that are statistically significant, thus obtaining an optimal model.

Relationship between Brain Tissue Changes and Blood Biomarkers of Cyclophilin A, Heme Oxygenase-1, and Inositol-Requiring Enzyme 1 in Patients with Alzheimer's Disease

Cyclophilin A (CypA), heme oxygenase-1 (HO-1), and inositol-requiring enzyme 1 (IRE1) are believed to be associated with Alzheimer's disease (AD). In this study, we investigated the association between gray matter volume (GMV) changes and blood levels of CypA, HO-1, and IRE1 in cognitively normal (CN) subjects and those with amnestic mild cognitive impairment (aMCI) and AD. Forty-five elderly CN, 34 aMCI, and 39 AD subjects were enrolled in this study. The results of voxel-based multiple regression analysis showed that blood levels of CypA, HO-1, and IRE1 were correlated with GMV on brain magnetic resonance imaging (MRI) in the entire population (p = 0.0005). The three serum protein levels were correlated with GMV of signature AD regions in the population as a whole. CypA values increased with increasing GMV in the occipital gyrus (r = 0.387, p < 0.0001) and posterior cingulate (r = 0.196, p = 0.034). HO-1 values increased with increasing GMV at the uncus (r = 0.307, p = 0.0008), lateral globus pallidus and putamen (r = 0.287, p = 0.002), and hippocampus (r = 0.197, p = 0.034). IRE1 values decreased with increasing GMV at the uncus (r = -0.239, p = 0.010) and lateral globus pallidus and putamen (r = -0.335, p = 0.0002). Associations between the three serum protein levels and regional GMV indicate that the blood levels of these biomarkers may reflect the pathological mechanism of AD in the brain.

NREM delta power and AD-relevant tauopathy are associated with shared cortical gene networks

Reduced NREM sleep in humans is associated with AD neuropathology. Recent work has demonstrated a reduction in NREM sleep in preclinical AD, pointing to its potential utility as an early marker of dementia. We test the hypothesis that reduced NREM delta power and increased tauopathy are associated with shared underlying cortical molecular networks in preclinical AD. We integrate multi-omics data from two extensive public resources, a human Alzheimer's disease cohort from the Mount Sinai Brain Bank (N = 125) reflecting AD progression and a (C57BL/6J × 129S1/SvImJ) F2 mouse population in which NREM delta power was measured (N = 98). Two cortical gene networks, including a CLOCK-dependent circadian network, are associated with NREM delta power and AD tauopathy progression. These networks were validated in independent mouse and human cohorts. Identifying gene networks related to preclinical AD elucidate possible mechanisms associated with the early disease phase and potential targets to alter the disease course.

Integrated miRNA-Seq and mRNA-Seq Study to Identify miRNAs Associated With Alzheimer's Disease Using Post-mortem Brain Tissue Samples

Alzheimer's disease (AD), the leading form of dementia, is associated with abnormal tau and β-amyloid accumulation in the brain. We conducted a miRNA-seq study to identify miRNAs associated with AD in the post-mortem brain from the inferior frontal gyrus (IFG, n = 69) and superior temporal gyrus (STG, n = 81). Four and 64 miRNAs were differentially expressed (adjusted p-value < 0.05) in AD compared to cognitively normal controls in the IFG and STG, respectively. We observed down-regulation of several miRNAs that have previously been implicated in AD, including hsa-miR-212-5p and hsa-miR-132-5p, in AD samples across both brain regions, and up-regulation of hsa-miR-146a-5p, hsa-miR-501-3p, hsa-miR-34a-5p, and hsa-miR-454-3p in the STG. The differentially expressed miRNAs were previously implicated in the formation of amyloid-β plaques, the dysregulation of tau, and inflammation. We have also observed differential expressions for dozens of other miRNAs in the STG, including hsa-miR-4446-3p, that have not been described previously. Putative targets of these miRNAs (adjusted p-value < 0.1) were found to be involved in Wnt signaling pathway, MAPK family signaling cascades, sphingosine 1-phosphate (S1P) pathway, adaptive immune system, innate immune system, and neurogenesis. Our results support the finding of dysregulated miRNAs previously implicated in AD and propose additional miRNAs that appear to be dysregulated in AD for experimental follow-up.

Transformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential Therapeutics for Alzheimer's Disease

To identify the molecular mechanisms and novel therapeutic targets of late-onset Alzheimer's Disease (LOAD), we performed an integrative network analysis of multi-omics profiling of four cortical areas across 364 donors with varying cognitive and neuropathological phenotypes. Our analyses revealed thousands of molecular changes and uncovered neuronal gene subnetworks as the most dysregulated in LOAD. ATP6V1A was identified as a key regulator of a top-ranked neuronal subnetwork, and its role in disease-related processes was evaluated through CRISPR-based manipulation in human induced pluripotent stem cell-derived neurons and RNAi-based knockdown in Drosophila models. Neuronal impairment and neurodegeneration caused by ATP6V1A deficit were improved by a repositioned compound, NCH-51. This study provides not only a global landscape but also detailed signaling circuits of complex molecular interactions in key brain regions affected by LOAD, and the resulting network models will serve as a blueprint for developing next-generation therapeutic agents against LOAD.

Differential transcript usage unravels gene expression alterations in Alzheimer's disease human brains

Alzheimer's disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain could contribute for a better understanding of the AD pathology. In this work, we probed the differential expression of genes in different brain regions of healthy and AD adult subjects using data from three large transcriptomic studies: Mayo Clinic, Mount Sinai Brain Bank (MSBB), and ROSMAP. Using a combination of differential expression of gene and isoform switch analyses, we provide a detailed landscape of gene expression alterations in the temporal and frontal lobes, harboring brain areas affected at early and late stages of the AD pathology, respectively. Next, we took advantage of an indirect approach to assign the complex gene expression changes revealed in bulk RNAseq to individual cell types/subtypes of the adult brain. This strategy allowed us to identify previously overlooked gene expression changes in the brain of AD patients. Among these alterations, we show isoform switches in the AD causal gene amyloid-beta precursor protein (APP) and the risk gene bridging integrator 1 (BIN1), which could have important functional consequences in neuronal cells. Altogether, our work proposes a novel integrative strategy to analyze RNAseq data in AD and other neurodegenerative diseases based on both gene/transcript expression and regional/cell-type specificities.

Transcriptomic and Network Analysis Identifies Shared and Unique Pathways across Dementia Spectrum Disorders

Background: Dementia is a growing public health concern with an estimated prevalence of 50 million people worldwide. Alzheimer’s disease (AD) and vascular and frontotemporal dementias (VaD, FTD), share many clinical, genetical, and pathological features making the diagnosis difficult. Methods: In this study, we compared the transcriptome from the frontal cortex of patients with AD, VaD, and FTD to identify dysregulated pathways. Results: Upregulated genes in AD were enriched in adherens and tight junctions, mitogen-activated protein kinase, and phosphatidylinositol 3-kinase and protein kinase B/Akt signaling pathways, whereas downregulated genes associated with calcium signaling. Upregulated genes in VaD were centered on infectious diseases and nuclear factor kappa beta signaling, whereas downregulated genes are involved in biosynthesis of amino acids and the pentose phosphate pathway. Upregulated genes in FTD were associated with ECM receptor interactions and the lysosome, whereas downregulated genes were involved in glutamatergic synapse and MAPK signaling. The transcription factor KFL4 was shared among the 3 types of dementia. Conclusions: Collectively, we identified similarities and differences in dysregulated pathways and transcription factors among the dementias. The shared pathways and transcription factors may indicate a potential common etiology, whereas the differences may be useful for distinguishing dementias.

Comparison of brain connectomes by MRI and genomics and its implication in Alzheimer's disease

BACKGROUND

The human brain is complex and interconnected structurally. Brain connectome change is associated with Alzheimer's disease (AD) and other neurodegenerative diseases. Genetics and genomics studies have identified molecular changes in AD; however, the results are often limited to isolated brain regions and are difficult to interpret its findings in respect to brain connectome. The mechanisms of how one brain region impacts the molecular pathways in other regions have not been systematically studied. And how the brain regions susceptible to AD pathology interact with each other at the transcriptome level and how these interactions relate to brain connectome change are unclear.

METHODS

Here, we compared structural brain connectomes defined by probabilistic tracts using diffusion magnetic resonance imaging data in Alzheimer's Disease Neuroimaging Initiative database and a brain transcriptome dataset covering 17 brain regions.

RESULTS

We observed that the changes in diffusion measures associated with AD diagnosis status and the associations were replicated in an independent cohort. The result suggests that disease associated white matter changes are focal. Analysis of the brain connectome by genomic data, tissue-tissue transcriptional synchronization between 17 brain regions, indicates that the regions connected by AD-associated tracts were likely connected at the transcriptome level with high number of tissue-to-tissue correlated (TTC) gene pairs (P = 0.03). And genes involved in TTC gene pairs between white matter tract connected brain regions were enriched in signaling pathways (P = 6.08 × 10-9). Further pathway interaction analysis identified ionotropic glutamate receptor pathway and Toll receptor signaling pathways to be important for tissue-tissue synchronization at the transcriptome level. Transcript profile entailing Toll receptor signaling in the blood was significantly associated with diffusion properties of white matter tracts, notable association between fractional anisotropy and bilateral cingulum angular bundles (Ppermutation = 1.0 × 10-2 and 4.9 × 10-4 for left and right respectively).

CONCLUSIONS

In summary, our study suggests that brain connectomes defined by MRI and transcriptome data overlap with each other.

Systems modeling of white matter microstructural abnormalities in Alzheimer's disease

INTRODUCTION

Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression.

METHODS

We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD.

RESULTS

We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions.

DISCUSSION

Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD.

Synergy between the alteration in the N-terminal region of butyrylcholinesterase K variant and apolipoprotein E4 in late-onset Alzheimer's disease

While the life expectancy of the population has increased, Alzheimer’s disease (AD) has emerged as one of the greatest health problems of old age. AD is characterized by neuronal loss and cognitive decline. In the AD brain, there is a decrease in levels of acetylcholinesterase (AChE) and an increase in the levels of the related enzyme butyrylcholinesterase (BChE), that accumulate in plaques and tangles. Apolipoprotein E (ApoE) is a major cholesterol carrier and plays an important role in maintaining lipid homeostasis. APOE-ε4 constitutes the most important known genetic risk factor for late-onset AD. It has been proposed that the BCHE-K allele (Ala539Thr) acts in synergy with the APOE-ε4 allele to promote risk for AD. However, there is insufficient evidence to support a correlation. Most studies focused only on the coding regions of the genes. In this study, we analyzed sequence regions beyond the BCHE coding sequence. We found synergy between APOE-ε4 and SNPs localized in 5′UTR (rs1126680) and in intron 2 (rs55781031) of the BCHE-K allele (rs1803274) in 18% of patients with late-onset AD (n = 55). The results show that the coexistence of the APOE-ε4 allele and 3 SNPs in the BCHE gene is associated with a highly elevated risk of late-onset AD. SNP (rs1126680) in 5′UTR of the BCHE gene is located 32 nucleotides upstream of the 28 amino acid signal peptide. Mass spectrometry analysis of the BChE protein produced by SNP (rs1126680) showed that the mutation caused an in frame N-terminal extension of 41 amino acids of the BChE signal peptide. The resultant variant with a 69 amino acid signal peptide, designated N-BChE, may play a role in development of AD.

CDT2-controlled cell cycle reentry regulates the pathogenesis of Alzheimer's disease

INTRODUCTION

Altered cell cycle reentry has been observed in Alzheimer's disease (AD). Denticleless (DTL) was predicted as the top driver of a cell cycle subnetwork associated with AD.

METHODS

We systematically investigated DTL expression in AD and studied the molecular, cellular, and behavioral endophenotypes triggered by DTL overexpression.

RESULTS

We experimentally validated that CDT2, the protein encoded by DTL, activated cyclin-dependent kinases through downregulating P21, which induced tau hyperphosphorylation and Aβ toxicity, two hallmarks of AD. We demonstrated that cyclin-dependent kinases inhibition by roscovitine not only rescued CDT2-induced cognitive defects but also reversed expression changes induced by DTL overexpression. RNA-seq data from the DTL overexpression experiments revealed the molecular mechanisms underlying CDT2 controlled cell cycle reentry in AD.

DISCUSSION

These findings provide new insights into the molecular mechanisms of AD pathogenesis and thus pave a way for developing novel therapeutics for AD by targeting AD specific cell cycle networks and drivers.

Integrative approach to sporadic Alzheimer's disease: deficiency of TYROBP in cerebral Aβ amyloidosis mouse normalizes clinical phenotype and complement subnetwork molecular pathology without reducing Aβ burden

Integrative gene network approaches enable new avenues of exploration that implicate causal genes in sporadic late-onset Alzheimer's disease (LOAD) pathogenesis, thereby offering novel insights for drug-discovery programs. We previously constructed a probabilistic causal network model of sporadic LOAD and identified TYROBP/DAP12, encoding a microglial transmembrane signaling polypeptide and direct adapter of TREM2, as the most robust key driver gene in the network. Here, we show that absence of TYROBP/DAP12 in a mouse model of AD-type cerebral Aβ amyloidosis (APP^KM670/671NL/PSEN1^Δexon9) recapitulates the expected network characteristics by normalizing the transcriptome of APP/PSEN1 mice and repressing the induction of genes involved in the switch from homeostatic microglia to disease-associated microglia (DAM), including Trem2, complement (C1qa, C1qb, C1qc, and Itgax), Clec7a and Cst7. Importantly, we show that constitutive absence of TYROBP/DAP12 in the amyloidosis mouse model prevented appearance of the electrophysiological and learning behavior alterations associated with the phenotype of APP^KM670/671NL/PSEN1^Δexon9 mice. Our results suggest that TYROBP/DAP12 could represent a novel therapeutic target to slow, arrest, or prevent the development of sporadic LOAD. These data establish that the network pathology observed in postmortem human LOAD brain can be faithfully recapitulated in the brain of a genetically manipulated mouse. These data also validate our multiscale gene networks by demonstrating how the networks intersect with the standard neuropathological features of LOAD.

GJA1 (connexin43) is a key regulator of Alzheimer's disease pathogenesis

GJA1 (connexin43) has been predicted as the top key driver of an astrocyte enriched subnetwork associated with Alzheimer's disease (AD). In this study, we comprehensively examined GJA1 expression across 29 transcriptomic and proteomic datasets from post-mortem AD and normal control brains. We demonstrated that GJA1 was strongly associated with AD amyloid and tau pathologies and cognitive functions. RNA sequencing analysis of Gja1-/- astrocytes validated that Gja1 regulated the subnetwork identified in AD, and many genes involved in Aβ metabolism. Astrocytes lacking Gja1 showed reduced Apoe protein levels as well as impaired Aβ phagocytosis. Consistent with this, wildtype neurons co-cultured with Gja1-/- astrocytes contained higher levels of Aβ species than those with wildtype astrocytes. Moreover, Gja1-/- astrocytes was more neuroprotective under Aβ stress. Our results underscore the importance of GJA1 in AD pathogenesis and its potential for further investigation as a promising pharmacological target in AD.

Parahippocampal gyrus expression of endothelial and insulin receptor signaling pathway genes is modulated by Alzheimer's disease and normalized by treatment with anti-diabetic agents

A large body of literature links risk of cognitive decline, mild cognitive impairment (MCI) and dementia with Type 2 Diabetes (T2D) or pre-diabetes. Accumulating evidence implicates a close relationship between the brain insulin receptor signaling pathway (IRSP) and the accumulation of amyloid beta and hyperphosphorylated and conformationally abnormal tau. We showed previously that the neuropathological features of Alzheimer's disease (AD were reduced in patients with diabetes who were treated with insulin and oral antidiabetic medications. To understand better the neurobiological substrates of T2D and T2D medications in AD, we examined IRSP and endothelial cell markers in the parahippocampal gyrus of controls (N = 30), of persons with AD (N = 19), and of persons with AD and T2D, who, in turn, had been treated with anti-diabetic drugs (insulin and or oral agents; N = 34). We studied the gene expression of selected members of the IRSP and selective endothelial cell markers in bulk postmortem tissue from the parahippocampal gyrus and in endothelial cell enriched isolates from the same brain region. The results indicated that there are considerable abnormalities and reductions in gene expression (bulk tissue homogenates and endothelial cell isolates) in the parahippocampal gyri of persons with AD that map directly to genes associated with the microvasculature and the IRSP. Our results also showed that the numbers of abnormally expressed microvasculature and IRSP associated genes in diabetic AD donors who had been treated with anti-diabetic agents were reduced significantly. These findings suggest that anti-diabetic treatments may reduce or normalize compromised microvascular and IRSP functions in AD.

The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease

Alzheimer's disease (AD) affects half the US population over the age of 85 and is universally fatal following an average course of 10 years of progressive cognitive disability. Genetic and genome-wide association studies (GWAS) have identified about 33 risk factor genes for common, late-onset AD (LOAD), but these risk loci fail to account for the majority of affected cases and can neither provide clinically meaningful prediction of development of AD nor offer actionable mechanisms. This cohort study generated large-scale matched multi-Omics data in AD and control brains for exploring novel molecular underpinnings of AD. Specifically, we generated whole genome sequencing, whole exome sequencing, transcriptome sequencing and proteome profiling data from multiple regions of 364 postmortem control, mild cognitive impaired (MCI) and AD brains with rich clinical and pathophysiological data. All the data went through rigorous quality control. Both the raw and processed data are publicly available through the Synapse software platform.

Brain donation at autopsy: clinical characterization and toxicologic analyses

The study of postmortem human brain tissue is central to the advancement of neurobiologic studies of psychiatric and neurologic illnesses, particularly the study of brain-specific isoforms and molecules. Due to tissue demands, especially pertaining to brain regions strongly implicated in the pathophysiology of neuropsychiatric disorders, the success and future of this research depend on the availability of high-quality brain specimens from large numbers of subjects, including nonpsychiatric controls, both of which may be obtained from brain banks. In this chapter, we elaborate on the need for and acquisition of well-curated and properly diagnosed postmortem human brains, relying upon our experience with the Human Brain and Tissue Repository located at the Lieber Institute for Brain Development in Baltimore, MD. We explain the advantages of sourcing postmortem human tissue from medical examiner offices, which provide access to cases of all ages, both with and without central nervous system disorders. Neuropathology analyses and toxicologic screenings, along with autopsy reports and extensive interviews with family members and treating physicians, are invaluable to the diagnoses of postmortem cases. Ultimately, the study of psychiatric and neurologic disorders is the study of brain disease, and accordingly, there is no substitution for human brain tissue.

Aberrant DNA methylation associated with Alzheimer's disease in the superior temporal gyrus

Abnormal DNA methylation patterns have been demonstrated to be associated with the pathogenesis of Alzheimer's disease (AD). The present study aimed to identify differential methylation in the superior temporal gyrus (STG) of patients with late-onset AD based on epigenome-wide DNA methylation data by bioinformatics analysis. The genome-wide DNA methylation data in the STG region of 34 patients with late-onset AD and 34 controls without dementia were recruited from the Gene Expression Omnibus database. Through systemic quality control, differentially methylated CpG sites were determined by the Student's t-test and mean methylation value differences between the two conditions. Hierarchical clustering analysis was applied to assess the classification performance of differentially methylated CpGs. Functional analysis was performed to investigate the biological functions of the genes associated with differentially methylated CpGs. A total of 17,895 differentially methylated CpG sites were initially identified, including 11,822 hypermethylated CpGs and 6,073 hypomethylated CpGs. Further analysis examined 2,211 differentially methylated CpGs (covering 1,991 genes). AD subjects demonstrated distinctive DNA methylation patterns when compared with the controls, with a classification accuracy value of 1. Hypermethylation was mainly detected for genes regulating the cell cycle progression, whereas hypomethylation was observed in genes involved in transcription factor binding. The present study demonstrated widespread and distinctive DNA methylation alterations in late-onset AD. Identification of AD-associated epigenetic biomarkers may allow for the development of novel diagnostic and therapeutic targets.

Alzheimer's brains show inter-related changes in RNA and lipid metabolism

Alzheimer's disease (AD) involves changes in both lipid and RNA metabolism, but it remained unknown if these differences associate with AD's cognition and/or post-mortem neuropathology indices. Here, we report RNA-sequencing evidence of inter-related associations between lipid processing, cognition level, and AD neuropathology. In two unrelated cohorts, we identified pathway-enriched facilitation of lipid processing and alternative splicing genes, including the neuronal-enriched NOVA1 and hnRNPA1. Specifically, this association emerged in temporal lobe tissue samples from donors where postmortem evidence demonstrated AD neuropathology, but who presented normal cognition proximate to death. The observed changes further associated with modified ATP synthesis and mitochondrial transcripts, indicating metabolic relevance; accordingly, mass-spectrometry-derived lipidomic profiles distinguished between individuals with and without cognitive impairment prior to death. In spite of the limited group sizes, tissues from persons with both cognitive impairment and AD pathology showed elevation in several drug-targeted genes of other brain, vascular and autoimmune disorders, accompanied by pathology-related increases in distinct lipid processing transcripts, and in the RNA metabolism genes hnRNPH2, TARDBP, CLP1 and EWSR1. To further detect 3'-polyadenylation variants, we employed multiple cDNA primer pairs. This identified variants that showed limited differences in scope and length between the tested cohorts, yet enabled superior clustering of demented and non-demented AD brains versus controls compared to total mRNA expression values. Our findings indicate inter-related cognition-associated differences in AD's lipid processing, alternative splicing and 3'-polyadenylation, calling for pursuing the underlying psychological and therapeutics implications.

Connectivity, not region-intrinsic properties, predicts regional vulnerability to progressive tau pathology in mouse models of disease

Spatiotemporal tau pathology progression is regarded as highly stereotyped within each type of degenerative condition. For instance, AD has a progression of tau pathology consistently beginning in the entorhinal cortex, the locus coeruleus, and other nearby noradrenergic brainstem nuclei, before spreading to the rest of the limbic system as well as the cingulate and retrosplenial cortices. Proposed explanations for the consistent spatial patterns of tau pathology progression, as well as for why certain regions are selectively vulnerable to exhibiting pathology over the course of disease generally focus on transsynaptic spread proceeding via the brain's anatomic connectivity network in a cell-independent manner or on cell-intrinsic properties that might render some cell populations or regions uniquely vulnerable. We test connectivity based explanations of spatiotemporal tau pathology progression and regional vulnerability against cell-intrinsic explanation, using regional gene expression profiles as a proxy. We find that across both exogenously seeded and non-seeded tauopathic mouse models, the connectivity network provides a better explanation than regional gene expression profiles, even when such profiles are limited to specific sets of tau risk-related genes only. Our results suggest that, regardless of the location of pathology initiation, tau pathology progression is well characterized by a model positing entirely cell-type and molecular environment independent transsynaptic spread via the mouse brain's connectivity network. These results further suggest that regional vulnerability to tau pathology is mainly governed by connectivity with regions already exhibiting pathology, rather than by cell-intrinsic factors.

Genome-Wide Analysis of Periodontal and Peri-Implant Cells and Tissues

Omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ or tissue sample, are powerful means of generating comprehensive genome-level data sets on complex diseases. We have systematically assessed the transcriptome, miRNome and methylome of gingival tissues from subjects with different diagnostic entities of periodontal disease, and studied the transcriptome of primary cells ex vivo, or in vitro after infection with periodontal pathogens. Our data further our understanding of the pathobiology of periodontal diseases and indicate that the gingival -omes translate into discernible phenotypic characteristics and possibly support an alternative, "molecular" classification of periodontitis.Here, we outline the laboratory steps required for the processing of periodontal cells and tissues for -omics analyses using current microarrays or next-generation sequencing technology.

Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer's disease

Background

Alzheimer’s disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. However, despite extensive clinical and genomic studies, the molecular basis of AD development and progression remains elusive.

Methods

To elucidate molecular systems associated with AD, we developed a large scale gene expression dataset from 1053 postmortem brain samples across 19 cortical regions of 125 individuals with a severity spectrum of dementia and neuropathology of AD. We excluded brain specimens that evidenced neuropathology other than that characteristic of AD. For the first time, we performed a pan-cortical brain region genomic analysis, characterizing the gene expression changes associated with a measure of dementia severity and multiple measures of the severity of neuropathological lesions associated with AD (neuritic plaques and neurofibrillary tangles) and constructing region-specific co-expression networks. We rank-ordered 44,692 gene probesets, 1558 co-expressed gene modules and 19 brain regions based upon their association with the disease traits.

Results

The neurobiological pathways identified through these analyses included actin cytoskeleton, axon guidance, and nervous system development. Using public human brain single-cell RNA-sequencing data, we computed brain cell type-specific marker genes for human and determined that many of the abnormally expressed gene signatures and network modules were specific to oligodendrocytes, astrocytes, and neurons. Analysis based on disease severity suggested that: many of the gene expression changes, including those of oligodendrocytes, occurred early in the progression of disease, making them potential translational/treatment development targets and unlikely to be mere bystander result of degeneration; several modules were closely linked to cognitive compromise with lesser association with traditional measures of neuropathology. The brain regional analyses identified temporal lobe gyri as sites associated with the greatest and earliest gene expression abnormalities.

Conclusions

This transcriptomic network analysis of 19 brain regions provides a comprehensive assessment of the critical molecular pathways associated with AD pathology and offers new insights into molecular mechanisms underlying selective regional vulnerability to AD at different stages of the progression of cognitive compromise and development of the canonical neuropathological lesions of AD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0355-3) contains supplementary material, which is available to authorized users.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Genome-wide DNA methylation profiling in the superior temporal gyrus reveals epigenetic signatures associated with Alzheimer's disease

BACKGROUND

Alzheimer's disease affects ~13% of people in the United States 65 years and older, making it the most common neurodegenerative disorder. Recent work has identified roles for environmental, genetic, and epigenetic factors in Alzheimer's disease risk.

METHODS

We performed a genome-wide screen of DNA methylation using the Illumina Infinium HumanMethylation450 platform on bulk tissue samples from the superior temporal gyrus of patients with Alzheimer's disease and non-demented controls. We paired a sliding window approach with multivariate linear regression to characterize Alzheimer's disease-associated differentially methylated regions (DMRs).

RESULTS

We identified 479 DMRs exhibiting a strong bias for hypermethylated changes, a subset of which were independently associated with aging. DMR intervals overlapped 475 RefSeq genes enriched for gene ontology categories with relevant roles in neuron function and development, as well as cellular metabolism, and included genes reported in Alzheimer's disease genome-wide and epigenome-wide association studies. DMRs were enriched for brain-specific histone signatures and for binding motifs of transcription factors with roles in the brain and Alzheimer's disease pathology. Notably, hypermethylated DMRs preferentially overlapped poised promoter regions, marked by H3K27me3 and H3K4me3, previously shown to co-localize with aging-associated hypermethylation. Finally, the integration of DMR-associated single nucleotide polymorphisms with Alzheimer's disease genome-wide association study risk loci and brain expression quantitative trait loci highlights multiple potential DMRs of interest for further functional analysis.

CONCLUSION

We have characterized changes in DNA methylation in the superior temporal gyrus of patients with Alzheimer's disease, highlighting novel loci that facilitate better characterization of pathways and mechanisms underlying Alzheimer's disease pathogenesis, and improve our understanding of epigenetic signatures that may contribute to the development of disease.

The triggering receptor expressed on myeloid cells 2 (TREM2) is associated with enhanced inflammation, neuropathological lesions and increased risk for Alzheimer's dementia

INTRODUCTION

The objective of this study was to elucidate the relationship between the triggering receptor expressed on myeloid cells 2 (TREM2) risk variant, neuropathological lesions, alterations in gene and protein expression, and the severity of neuroinflammation.

METHODS

The genetic association study of the R47 H TREM2 variant with Alzheimer's disease (AD), neuropathology, and changes in TREM2 and TYRO protein tyrosine kinase-binding protein (TYROBP) gene and protein expression, and neuroinflammatory markers.

RESULTS

The TREM2 variant is associated with: (i) AD (odds ratio: 4.76; P = .014); (ii) increased density of amyloid plaques and neurofibrillary tangles in multiple brain regions; (iii) increased TREM2 (P = .041) and TYROBP (P = .006) gene expression; (iv) decreased TREM2 protein levels (P = .016); and (v) upregulation of proinflammatory cytokines (regulated on activation, normal T cell expressed and secreted [RANTES] and interferon [IFN] gamma) (P = .003) and nominal downregulation of protective markers (α2-macroglobulin, interleukin 4 or IL-4, and ApoA1) (P = .018).

DISCUSSION

These findings link the TREM2 missense mutation with specific molecular abnormalities and increases in neuropathological lesions in the human brain.

The relationship between dopamine receptor D1 and cognitive performance

BACKGROUND

Cognitive impairment cuts across traditional diagnostic boundaries and is one of the most typical symptoms in various psychiatric and neurobiological disorders.

AIMS

The objective of this study was to examine the genetic association between 94 candidate genes, including receptors and enzymes that participate in neurotransmission, with measures of cognition.

METHODS

The Clinical Dementia Rating (CDR), a global measure of cognition, and genotypes derived from a custom array of 1,536 single-nucleotide polymorphisms (SNPs) in 94 genes were available for a large postmortem cohort of Caucasian cases with Alzheimer's disease (AD), schizophrenia and controls (n=727). A cohort of healthy young males (n=1,493) originating from the LOGOS project (Learning On Genetics Of Schizophrenia Spectrum) profiled across multiple cognitive domains was available for targeted SNP genotyping. Gene expression was quantified in the superior temporal gyrus of control samples (n=109). The regulatory effect on transcriptional activity was assessed using the luciferase reporter system.

RESULTS

The rs5326-A allele at the promoter region of dopamine receptor D1 (DRD1) locus was associated with: (i) poorer cognition (higher CDR) in the postmortem cohort (P=9.325×10(-4)); (ii) worse cognitive performance relevant to strategic planning in the LOGOS cohort (P=0.008); (iii) lower DRD1 gene expression in the superior temporal gyrus of controls (P=0.038); and (iv) decreased transcriptional activity in human neuroblastoma (SH-SY5Y) cells (P=0.026).

CONCLUSIONS

An interdisciplinary approach combining genetics with cognitive and molecular neuroscience provided a possible mechanistic link among DRD1 and alterations in cognitive performance.

Impaired mitochondrial energy metabolism as a novel risk factor for selective onset and progression of dementia in oldest-old subjects

Recent evidence shows that Alzheimer disease (AD) dementia in the oldest-old subjects was associated with significantly less amyloid plaque and fibrillary tangle neuropathology than in the young-old population. In this study, using quantitative (q) PCR studies, we validated genome-wide microarray RNA studies previously conducted by our research group. We found selective downregulation of mitochondrial energy metabolism genes in the brains of oldest-old, but not young-old, AD dementia cases, despite a significant lack of classic AD neuropathology features. We report a significant decrease of genes associated with mitochondrial pyruvate metabolism, the tricarboxylic acid cycle (TCA), and glycolytic pathways. Moreover, significantly higher levels of nitrotyrosylated (3-NT)-proteins and 4-hydroxy-2-nonenal (HNE) adducts, which are indexes of cellular protein oxidation and lipid peroxidation, respectively, were detected in the brains of oldest-old subjects at high risk of developing AD, possibly suggesting compensatory mechanisms. These findings support the hypothesis that although oldest-old AD subjects, characterized by significantly lower AD neuropathology than young-old AD subjects, have brain mitochondrial metabolism impairment, which we hypothesize may selectively contribute to the development of dementia. Outcomes from this study provide novel insights into the molecular mechanisms underlying clinical dementia in young-old and oldest-old AD subjects and provide novel strategies for AD prevention and treatment in oldest-old dementia cases.