Molecular properties underlying regional vulnerability to Alzheimer's disease pathology

Convergent Neuroimaging and Molecular Signatures in Mild Cognitive Impairment and Alzheimer's Disease: A Data-Driven Meta-Analysis with N = 3,118

The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer's disease (AD). We conducted data-driven meta-analyses to combine 3,118 structural magnetic resonance images from three datasets to obtain robust atrophy patterns. Then we introduced a set of radiogenomic analyses to investigate the biological basis of the atrophy patterns in AD. Our results showed that the hippocampus and amygdala exhibit the most severe atrophy, followed by the temporal, frontal, and occipital lobes in mild cognitive impairment (MCI) and AD. The extent of atrophy in MCI was less severe than that in AD. A series of biological processes related to the glutamate signaling pathway, cellular stress response, and synapse structure and function were investigated through gene set enrichment analysis. Our study contributes to understanding the manifestations of atrophy and a deeper understanding of the pathophysiological processes that contribute to atrophy, providing new insight for further clinical research on AD.

Proteomic features of gray matter layers and superficial white matter of the rhesus monkey neocortex: comparison of prefrontal area 46 and occipital area 17

In this novel large-scale multiplexed immunofluorescence study we comprehensively characterized and compared layer-specific proteomic features within regions of interest of the widely divergent dorsolateral prefrontal cortex (A46) and primary visual cortex (A17) of adult rhesus monkeys. Twenty-eight markers were imaged in rounds of sequential staining, and their spatial distribution precisely quantified within gray matter layers and superficial white matter. Cells were classified as neurons, astrocytes, oligodendrocytes, microglia, or endothelial cells. The distribution of fibers and blood vessels were assessed by quantification of staining intensity across regions of interest. This method revealed multivariate similarities and differences between layers and areas. Protein expression in neurons was the strongest determinant of both laminar and regional differences, whereas protein expression in glia was more important for intra-areal laminar distinctions. Among specific results, we observed a lower glia-to-neuron ratio in A17 than in A46 and the pan-neuronal markers HuD and NeuN were differentially distributed in both brain areas with a lower intensity of NeuN in layers 4 and 5 of A17 compared to A46 and other A17 layers. Astrocytes and oligodendrocytes exhibited distinct marker-specific laminar distributions that differed between regions; notably, there was a high proportion of ALDH1L1-expressing astrocytes and of oligodendrocyte markers in layer 4 of A17. The many nuanced differences in protein expression between layers and regions observed here highlight the need for direct assessment of proteins, in addition to RNA expression, and set the stage for future protein-focused studies of these and other brain regions in normal and pathological conditions.

Tau follows principal axes of functional and structural brain organization in Alzheimer's disease

Alzheimer's disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns ("gradient contraction") are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.

Characterization of tau propagation pattern and cascading hypometabolism from functional connectivity in Alzheimer's disease

Tau pathology and its spatial propagation in Alzheimer's disease (AD) play crucial roles in the neurodegenerative cascade leading to dementia. However, the underlying mechanisms linking tau spreading to glucose metabolism remain elusive. To address this, we aimed to examine the association between pathologic tau aggregation, functional connectivity, and cascading glucose metabolism and further explore the underlying interplay mechanisms. In this prospective cohort study, we enrolled 79 participants with 18F-Florzolotau positron emission tomography (PET), 18F-fluorodeoxyglucose PET, resting-state functional, and anatomical magnetic resonance imaging (MRI) images in the hospital-based Shanghai Memory Study. We employed generalized linear regression and correlation analyses to assess the associations between Florzolotau accumulation, functional connectivity, and glucose metabolism in whole-brain and network-specific manners. Causal mediation analysis was used to evaluate whether functional connectivity mediates the association between pathologic tau and cascading glucose metabolism. We examined 22 normal controls and 57 patients with AD. In the AD group, functional connectivity was associated with Florzolotau covariance (β = .837, r = 0.472, p < .001) and glucose covariance (β = 1.01, r = 0.499, p < .001). Brain regions with higher tau accumulation tend to be connected to other regions with high tau accumulation through functional connectivity or metabolic connectivity. Mediation analyses further suggest that functional connectivity partially modulates the influence of tau accumulation on downstream glucose metabolism (mediation proportion: 49.9%). Pathologic tau may affect functionally connected neurons directly, triggering downstream glucose metabolism changes. This study sheds light on the intricate relationship between tau pathology, functional connectivity, and downstream glucose metabolism, providing critical insights into AD pathophysiology and potential therapeutic targets.

Genetic-based patient stratification in Alzheimer's disease

Alzheimer's disease (AD) shows a high pathological and symptomatological heterogeneity. To study this heterogeneity, we have developed a patient stratification technique based on one of the most significant risk factors for the development of AD: genetics. We addressed this challenge by including network biology concepts, mapping genetic variants data into a brain-specific protein-protein interaction (PPI) network, and obtaining individualized PPI scores that we then used as input for a clustering technique. We then phenotyped each obtained cluster regarding genetics, sociodemographics, biomarkers, fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging, and neurocognitive assessments. We found three clusters defined mainly by genetic variants found in MAPT, APP, and APOE, considering known variants associated with AD and other neurodegenerative disease genetic architectures. Profiling of these clusters revealed minimal variation in AD symptoms and pathology, suggesting different biological mechanisms may activate the neurodegeneration and pathobiological patterns behind AD and result in similar clinical and pathological presentations, even a shared disease diagnosis. Lastly, our research highlighted MAPT, APP, and APOE as key genes where these genetic distinctions manifest, suggesting them as potential targets for personalized drug development strategies to address each AD subgroup individually.

Exploring Heparan Sulfate Proteoglycans as Mediators of Human Mesenchymal Stem Cell Neurogenesis

Alzheimer's disease (AD) and traumatic brain injury (TBI) are major public health issues worldwide, with over 38 million people living with AD and approximately 48 million people (27-69 million) experiencing TBI annually. Neurodegenerative conditions are characterised by the accumulation of neurotoxic amyloid beta (Aβ) and microtubule-associated protein Tau (Tau) with current treatments focused on managing symptoms rather than addressing the underlying cause. Heparan sulfate proteoglycans (HSPGs) are a diverse family of macromolecules that interact with various proteins and ligands and promote neurogenesis, a process where new neural cells are formed from stem cells. The syndecan (SDC) and glypican (GPC) HSPGs have been implicated in AD pathogenesis, acting as drivers of disease, as well as potential therapeutic targets. Human mesenchymal stem cells (hMSCs) provide an attractive therapeutic option for studying and potentially treating neurodegenerative diseases due to their relative ease of isolation and subsequent extensive in vitro expansive potential. Understanding how HSPGs regulate protein aggregation, a key feature of neurodegenerative disorders, is essential to unravelling the underlying disease processes of AD and TBI, as well as any link between these two neurological disorders. Further research may validate HSPG, specifically SDCs or GPCs, use as neurodegenerative disease targets, either via driving hMSC stem cell therapy or direct targeting.

Selective vulnerability and resilience to Alzheimer's disease tauopathy as a function of genes and the connectome

Brain regions in Alzheimer's (AD) exhibit distinct vulnerability to the disease's hallmark pathology, with the entorhinal cortex and hippocampus succumbing early to tau tangles while others like primary sensory cortices remain resilient. The quest to understand how local/regional genetic factors, pathogenesis, and network-mediated spread of pathology together govern this selective vulnerability (SV) or resilience (SR) is ongoing. Although many risk genes in AD are known from gene association and transgenic studies, it is still not known whether and how their baseline expression signatures confer SV or SR to brain structures. Prior analyses have yielded conflicting results, pointing to a disconnect between the location of genetic risk factors and downstream tau pathology. We hypothesize that a full accounting of genes' role in mediating SV/SR would require the modeling of network-based vulnerability, whereby tau misfolds, aggregates, and propagates along fiber projections. We therefore employed an extended network diffusion model (eNDM) and tested it on tau pathology PET data from 196 AD patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Thus the fitted eNDM model becomes a reference process from which to assess the role of innate genetic factors. Using the residual (observed - model-predicted) tau as a novel target outcome, we obtained its association with 100 top AD risk-genes, whose baseline spatial transcriptional profiles were obtained from the Allen Human Brain Atlas (AHBA). We found that while many risk genes at baseline showed a strong association with regional tau, many more showed a stronger association with residual tau. This suggests that both direct vulnerability, related to the network, as well as network-independent vulnerability, are conferred by risk genes. We then classified risk genes into four classes: network-related SV (SV-NR), network-independent SV (SV-NI), network-related SR (SR-NR), and network-independent SR (SR-NI). Each class has a distinct spatial signature and associated vulnerability to tau. Remarkably, we found from gene-ontology analyses, that genes in these classes were enriched in distinct functional processes and encompassed different functional networks. These findings offer new insights into the factors governing innate vulnerability or resilience in AD pathophysiology and may prove helpful in identifying potential intervention targets.

Multivariate investigation of aging in mouse models expressing the Alzheimer's protective APOE2 allele: integrating cognitive metrics, brain imaging, and blood transcriptomics

APOE allelic variation is critical in brain aging and Alzheimer's disease (AD). The APOE2 allele associated with cognitive resilience and neuroprotection against AD remains understudied. We employed a multipronged approach to characterize the transition from middle to old age in mice with APOE2 allele, using behavioral assessments, image-derived morphometry and diffusion metrics, structural connectomics, and blood transcriptomics. We used sparse multiple canonical correlation analyses (SMCCA) for integrative modeling, and graph neural network predictions. Our results revealed brain sub-networks associated with biological traits, cognitive markers, and gene expression. The cingulate cortex emerged as a critical region, demonstrating age-associated atrophy and diffusion changes, with higher fractional anisotropy in males and middle-aged subjects. Somatosensory and olfactory regions were consistently highlighted, indicating age-related atrophy and sex differences. The hippocampus exhibited significant volumetric changes with age, with differences between males and females in CA3 and CA1 regions. SMCCA underscored changes in the cingulate cortex, somatosensory cortex, olfactory regions, and hippocampus in relation to cognition and blood-based gene expression. Our integrative modeling in aging APOE2 carriers revealed a central role for changes in gene pathways involved in localization and the negative regulation of cellular processes. Our results support an important role of the immune system and response to stress. This integrative approach offers novel insights into the complex interplay among brain connectivity, aging, and sex. Our study provides a foundation for understanding the impact of APOE2 allele on brain aging, the potential for detecting associated changes in blood markers, and revealing novel therapeutic intervention targets.

Morphological connectivity differences in Alzheimer's disease correlate with gene transcription and cell-type

Alzheimer's disease (AD) is one of the most prevalent forms of dementia in older individuals. Convergent evidence suggests structural connectome abnormalities in specific brain regions are linked to AD progression. The biological basis underpinnings of these connectome changes, however, have remained elusive. We utilized an individual regional mean connectivity strength (RMCS) derived from a regional radiomics similarity network to capture altered morphological connectivity in 1654 participants (605 normal controls, 766 mild cognitive impairment [MCI], and 283 AD). Then, we also explored the biological basis behind these morphological changes through gene enrichment analysis and cell-specific analysis. We found that RMCS probes of the hippocampus and medial temporal lobe were significantly altered in AD and MCI, with these differences being spatially related to the expression of AD-risk genes. In addition, gene enrichment analysis revealed that the modulation of chemical synaptic transmission is the most relevant biological process associated with the altered RMCS in AD. Notably, neuronal cells were found to be the most pertinent cells in the altered RMCS. Our findings shed light on understanding the biological basis of structural connectome changes in AD, which may ultimately lead to more effective diagnostic and therapeutic strategies for this devastating disease.

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

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

Spatial transcriptomic patterns underlying regional vulnerability to amyloid-β and tau pathologies and their relationships to cognitive dysfunction in Alzheimer's disease

Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We studied the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies leveraging two large independent cohorts (n = 715) of participants along the AD continuum. We identified several AD susceptibility genes and gene modules in a gene co-expression network with expression profiles related to regional vulnerability to Aβ and tau pathologies in AD. In particular, we found that the positive APOE -to-tau association was only seen in the AD cohort, whereas patients with AD and frontotemporal dementia shared similar positive MAPT -to-tau association. Some AD candidate genes showed sex-dependent negative gene-to-Aβ and gene-to-tau associations. In addition, we identified distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. Finally, we proposed a novel analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations. Taken together, our study identified distinct gene expression profiles and biochemical pathways that may explain the discordance between regional Aβ and tau pathologies, and filled the gap between gene-to-pathology associations and cognitive dysfunction in individual AD patients that may ultimately help identify novel personalized pathogenetic biomarkers and therapeutic targets.

One Sentence Summary

We identified replicable cognition-related associations between regional gene expression profiles and selectively regional vulnerability to amyloid-β and tau pathologies in AD.

Genome-wide methylomic regulation of multiscale gene networks in Alzheimer's disease

INTRODUCTION

Recent studies revealed the association of abnormal methylomic changes with Alzheimer's disease (AD) but there is a lack of systematic study of the impact of methylomic alterations over the molecular networks underlying AD.

METHODS

We profiled genome-wide methylomic variations in the parahippocampal gyrus from 201 post mortem control, mild cognitive impaired, and AD brains.

RESULTS

We identified 270 distinct differentially methylated regions (DMRs) associated with AD. We quantified the impact of these DMRs on each gene and each protein as well as gene and protein co-expression networks. DNA methylation had a profound impact on both AD-associated gene/protein modules and their key regulators. We further integrated the matched multi-omics data to show the impact of DNA methylation on chromatin accessibility, which further modulates gene and protein expression.

DISCUSSION

The quantified impact of DNA methylation on gene and protein networks underlying AD identified potential upstream epigenetic regulators of AD.

HIGHLIGHTS

A cohort of DNA methylation data in the parahippocampal gyrus was developed from 201 post mortem control, mild cognitive impaired, and Alzheimer's disease (AD) brains. Two hundred seventy distinct differentially methylated regions (DMRs) were found to be associated with AD compared to normal control. A metric was developed to quantify methylation impact on each gene and each protein. DNA methylation was found to have a profound impact on not only the AD-associated gene modules but also key regulators of the gene and protein networks. Key findings were validated in an independent multi-omics cohort in AD. The impact of DNA methylation on chromatin accessibility was also investigated by integrating the matched methylomic, epigenomic, transcriptomic, and proteomic data.

Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease

From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.

Toward Best Practices for Imaging Transcriptomics of the Human Brain

Modern brainwide transcriptional atlases provide unprecedented opportunities for investigating the molecular correlates of brain organization, as quantified using noninvasive neuroimaging. However, integrating neuroimaging data with transcriptomic measures is not straightforward, and careful consideration is required to make valid inferences. In this article, we review recent work exploring how various methodological choices affect 3 main phases of imaging transcriptomic analyses, including 1) processing of transcriptional atlas data; 2) relating transcriptional measures to independently derived neuroimaging phenotypes; and 3) evaluating the functional implications of identified associations through gene enrichment analyses. Our aim is to facilitate the development of standardized and reproducible approaches for this rapidly growing field. We identify sources of methodological variability, key choices that can affect findings, and considerations for mitigating false positive and/or spurious results. Finally, we provide an overview of freely available open-source toolboxes implementing current best-practice procedures across all 3 analysis phases.

Differential Effects of Tau Stage, Lewy Body Pathology, and Substantia Nigra Degeneration on 18F-FDG PET Patterns in Clinical Alzheimer Disease

Comorbid Lewy body (LB) pathology is common in Alzheimer disease (AD). The effect of LB copathology on ¹⁸F-FDG PET patterns in AD is yet to be studied. We analyzed associations of neuropathologically assessed tau pathology, LB pathology, and substantia nigra neuronal loss (SNnl) with antemortem ¹⁸F-FDG PET hypometabolism in patients with a clinical AD presentation. Methods: Twenty-one patients with autopsy-confirmed AD without LB neuropathologic changes (LBNC) (pure-AD), 24 with AD and LBNC copathology (AD-LB), and 7 with LBNC without fulfilling neuropathologic criteria for AD (pure-LB) were studied. Pathologic groups were compared regarding regional and voxelwise ¹⁸F-FDG PET patterns, the cingulate island sign ratio (CISr), and neuropathologic ratings of SNnl. Additional analyses assessed continuous associations of Braak tangle stage and SNnl with ¹⁸F-FDG PET patterns. Results: Pure-AD and AD-LB showed highly similar patterns of AD-typical temporoparietal hypometabolism and did not differ in CISr, regional ¹⁸F-FDG SUVR, or SNnl. By contrast, pure-LB showed the expected pattern of pronounced posterior-occipital hypometabolism typical for dementia with LB (DLB), and both CISr and SNnl were significantly higher compared with the AD groups. In continuous analyses, Braak tangle stage correlated significantly with more AD-like, and SNnl with more DLB-like, ¹⁸F-FDG PET patterns. Conclusion: In autopsy-confirmed AD dementia patients, comorbid LB pathology did not have a notable effect on the regional ¹⁸F-FDG PET pattern. A more DLB-like ¹⁸F-FDG PET pattern was observed in relation to SNnl, but advanced SNnl was mostly limited to relatively pure LB cases. AD pathology may have a dominant effect over LB pathology in determining the regional neurodegeneration phenotype.

The Mitochondrial Enzyme 17βHSD10 Modulates Ischemic and Amyloid-β-Induced Stress in Primary Mouse Astrocytes

Severe brain metabolic dysfunction and amyloid-β accumulation are key hallmarks of Alzheimer's disease (AD). While astrocytes contribute to both pathologic mechanisms, the role of their mitochondria, which is essential for signaling and maintenance of these processes, has been largely understudied. The current work provides the first direct evidence that the mitochondrial metabolic switch 17β-hydroxysteroid dehydrogenase type 10 (17βHSD10) is expressed and active in murine astrocytes from different brain regions. While it is known that this protein is overexpressed in the brains of AD patients, we found that 17βHSD10 is also upregulated in astrocytes exposed to amyloidogenic and ischemic stress. Importantly, such catalytic overexpression of 17βHSD10 inhibits mitochondrial respiration during increased energy demand. This observation contrasts with what has been found in neuronal and cancer model systems, which suggests astrocyte-specific mechanisms mediated by the protein. Furthermore, the catalytic upregulation of the enzyme exacerbates astrocytic damage, reactive oxygen species (ROS) generation and mitochondrial network alterations during amyloidogenic stress. On the other hand, 17βHSD10 inhibition through AG18051 counters most of these effects. In conclusion, our data represents novel insights into the role of astrocytic mitochondria in metabolic and amyloidogenic stress with implications of 17βHSD10 in multiple neurodegenerative mechanisms.

Circular RNAs in Alzheimer's Disease: A New Perspective of Diagnostic and Therapeutic Targets

BACKGROUND

Circular RNAs (circRNAs), as covalently closed single-stranded noncoding RNA molecules, have been recently identified to involve in several biological processes, principally through targeting microRNAs. Among various neurodegenerative diseases (NDs), accumulating evidence has proposed key roles for circRNAs in the pathogenesis of Alzheimer's disease (AD); although the exact relationship between these RNA molecules and AD progression is not clear, they have been believed to mostly act as miRNA sponges or gene transcription modulators through correlating with multiple proteins, involved in the accumulation of Amyloid β (Aβ) peptides, as well as tau protein, as AD's pathological hallmark. More interestingly, circRNAs have also been reported to play diagnostic and therapeutic roles during AD progression.

OBJECTIVE

Literature review indicated that circRNAs could essentially contribute to the onset and development of AD. Thus, in the current review, the circRNAs' biogenesis and functions are addressed at first, and then the interplay between particular circRNAs and AD is comprehensively discussed. Eventually, the diagnostic and therapeutic significance of these noncoding RNAs is highlighted in brief.

RESULTS

A large number of circRNAs are expressed in the brain. Thereby, these RNA molecules are noticed as potential regulators of neural functions in healthy circumstances, as well as neurological disorders. Moreover, circRNAs have also been reported to have potential diagnostic and therapeutic capacities in relation to AD, the most prevalent ND.

CONCLUSION

CircRNAs have been shown to act as sponges for miRNAs, thereby regulating the function of related miRNAs, including oxidative stress, reduction of neuroinflammation, and the formation and metabolism of Aβ, all of which developed in AD. CircRNAs have also been proposed as biomarkers that have potential diagnostic capacities in AD. Despite these characteristics, the use of circRNAs as therapeutic targets and promising diagnostic biomarkers will require further investigation and characterization of the function of these RNA molecules in AD.

The "Loss" of Perineuronal Nets in Alzheimer's Disease: Missing or Hiding in Plain Sight?

Perineuronal nets (PNNs) are chondroitin-sulfate glycosaminoglycan (CS-GAG) containing extracellular matrix structures that assemble around neurons involved in learning, memory, and cognition. Owing to the unique patterning of negative charges stemming from sulfate modifications to the attached CS-GAGs, these matrices play key roles in mediating glycan-protein binding, signaling interactions, and charged ion buffering of the underlying circuitry. Histochemical loss of PNN matrices has been reported for a range of neurocognitive and neurodegenerative diseases, implying that PNNs might be a key player in the pathogenesis of neurological disorders. In this hypothesis and theory article, we begin by highlighting PNN changes observed in human postmortem brain tissue associated with Alzheimer's disease (AD) and corresponding changes reported in rodent models of AD neuropathology. We then discuss the technical limitations surrounding traditional methods for PNN analyses and propose alternative explanations to these historical findings. Lastly, we embark on a global re-evaluation of the interpretations for PNN changes across brain regions, across species, and in relation to other neurocognitive disorders.

Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer's disease

Background

Increased total tau (t-tau) in cerebrospinal fluid (CSF) is a key characteristic of Alzheimer’s disease (AD) and is considered to result from neurodegeneration. T-tau levels, however, can be increased in very early disease stages, when neurodegeneration is limited, and can be normal in advanced disease stages. This suggests that t-tau levels may be driven by other mechanisms as well. Because tau pathophysiology is emerging as treatment target for AD, we aimed to clarify molecular processes associated with CSF t-tau levels.

Methods

We performed a proteomic, genomic, and imaging study in 1380 individuals with AD, in the preclinical, prodromal, and mild dementia stage, and 380 controls from the Alzheimer’s Disease Neuroimaging Initiative and EMIF-AD Multimodality Biomarker Discovery study.

Results

We found that, relative to controls, AD individuals with increased t-tau had increased CSF concentrations of over 400 proteins enriched for neuronal plasticity processes. In contrast, AD individuals with normal t-tau had decreased levels of these plasticity proteins and showed increased concentrations of proteins indicative of blood–brain barrier and blood-CSF barrier dysfunction, relative to controls. The distinct proteomic profiles were already present in the preclinical AD stage and persisted in prodromal and dementia stages implying that they reflect disease traits rather than disease states. Dysregulated plasticity proteins were associated with SUZ12 and REST signaling, suggesting aberrant gene repression. GWAS analyses contrasting AD individuals with and without increased t-tau highlighted several genes involved in the regulation of gene expression. Targeted analyses of SNP rs9877502 in GMNC, associated with t-tau levels previously, correlated in individuals with AD with CSF concentrations of 591 plasticity associated proteins. The number of APOE-e4 alleles, however, was not associated with the concentration of plasticity related proteins.

Conclusions

CSF t-tau levels in AD are associated with altered levels of proteins involved in neuronal plasticity and blood–brain and blood-CSF barrier dysfunction. Future trials may need to stratify on CSF t-tau status, as AD individuals with increased t-tau and normal t-tau are likely to respond differently to treatment, given their opposite CSF proteomic profiles.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13024-022-00521-3.

Syndecan-3 as a Novel Biomarker in Alzheimer's Disease

Early diagnosis of Alzheimer’s disease (AD) is of paramount importance in preserving the patient’s mental and physical health in a fairly manageable condition for a longer period. Reliable AD detection requires novel biomarkers indicating central nervous system (CNS) degeneration in the periphery. Members of the syndecan family of transmembrane proteoglycans are emerging new targets in inflammatory and neurodegenerative disorders. Reviewing the growing scientific evidence on the involvement of syndecans in the pathomechanism of AD, we analyzed the expression of the neuronal syndecan, syndecan-3 (SDC3), in experimental models of neurodegeneration. Initial in vitro studies showed that prolonged treatment of tumor necrosis factor-alpha (TNF-α) increases SDC3 expression in model neuronal and brain microvascular endothelial cell lines. In vivo studies revealed elevated concentrations of TNF-α in the blood and brain of APPSWE-Tau transgenic mice, along with increased SDC3 concentration in the brain and the liver. Primary brain endothelial cells and peripheral blood monocytes isolated from APPSWE-Tau mice exhibited increased SDC3 expression than wild-type controls. SDC3 expression of blood-derived monocytes showed a positive correlation with amyloid plaque load in the brain, demonstrating that SDC3 on monocytes is a good indicator of amyloid pathology in the brain. Given the well-established role of blood tests, the SDC3 expression of monocytes could serve as a novel biomarker for early AD detection.

Relating Global and Local Connectome Changes to Dementia and Targeted Gene Expression in Alzheimer's Disease

Networks are present in many aspects of our lives, and networks in neuroscience have recently gained much attention leading to novel representations of brain connectivity. The integration of neuroimaging characteristics and genetics data allows a better understanding of the effects of the gene expression on brain structural and functional connections. The current work uses whole-brain tractography in a longitudinal setting, and by measuring the brain structural connectivity changes studies the neurodegeneration of Alzheimer's disease. This is accomplished by examining the effect of targeted genetic risk factors on the most common local and global brain connectivity measures. Furthermore, we examined the extent to which Clinical Dementia Rating relates to brain connections longitudinally, as well as to gene expression. For instance, here we show that the expression of PLAU gene increases the change over time in betweenness centrality related to the fusiform gyrus. We also show that the betweenness centrality metric impact dementia-related changes in distinct brain regions. Our findings provide insights into the complex longitudinal interplay between genetics and brain characteristics and highlight the role of Alzheimer's genetic risk factors in the estimation of regional brain connectivity alterations.

Air pollution interacts with genetic risk to influence cortical networks implicated in depression

Air pollution is a reversible cause of significant global mortality and morbidity. Epidemiological evidence suggests associations between air pollution exposure and impaired cognition and increased risk for major depressive disorders. However, the neural bases of these associations have been unclear. Here, in healthy human subjects exposed to relatively high air pollution and controlling for socioeconomic, genomic, and other confounders, we examine across multiple levels of brain network function the extent to which particulate matter (PM_2.5) exposure influences putative genetic risk mechanisms associated with depression. Increased ambient PM_2.5 exposure was associated with poorer reasoning and problem solving and higher-trait anxiety/depression. Working memory and stress-related information transfer (effective connectivity) across cortical and subcortical brain networks were influenced by PM_2.5 exposure to differing extents depending on the polygenic risk for depression in gene-by-environment interactions. Effective connectivity patterns from individuals with higher polygenic risk for depression and higher exposures with PM_2.5, but not from those with lower genetic risk or lower exposures, correlated spatially with the coexpression of depression-associated genes across corresponding brain regions in the Allen Brain Atlas. These converging data suggest that PM_2.5 exposure affects brain network functions implicated in the genetic mechanisms of depression.

Neuroanatomical anomalies associated with rare AP4E1 mutations in people who stutter

Developmental stuttering is a common speech disorder with strong genetic underpinnings. Recently, stuttering has been associated with mutations in genes involved in lysosomal enzyme trafficking. However, how these mutations affect the brains of people who stutter remains largely unknown. In this study, we compared grey matter volume and white matter fractional anisotropy between a unique group of seven subjects who stutter and carry the same rare heterozygous AP4E1 coding mutations and seven unrelated controls without such variants. The carriers of the AP4E1 mutations are members of a large Cameroonian family in which the association between AP4E1 and persistent stuttering was previously identified. Compared to controls, mutation carriers showed reduced grey matter volume in the thalamus, visual areas and the posterior cingulate cortex. Moreover, reduced fractional anisotropy was observed in the corpus callosum, consistent with the results of previous neuroimaging studies of people who stutter with unknown genetic backgrounds. Analysis of gene expression data showed that these structural differences appeared at the locations in which expression of AP4E1 is relatively high. Moreover, the pattern of grey matter volume differences was significantly associated with AP4E1 expression across the left supratentorial regions. This spatial congruency further supports the connection between AP4E1 mutations and the observed structural differences.

Brain region-specific disruption of mitochondrial bioenergetics in cynomolgus macaques fed a Western versus a Mediterranean diet

Mitochondrial dysfunction is evident in diseases affecting cognition and metabolism such as Alzheimer's disease and type 2 diabetes. Human studies of brain mitochondrial function are limited to postmortem tissue, preventing the assessment of bioenergetics by respirometry. Here, we investigated the effect of two diets on mitochondrial bioenergetics in three brain regions: the prefrontal cortex (PFC), the entorhinal cortex (ERC), and the cerebellum (CB), using middle-aged nonhuman primates. Eighteen female cynomolgus macaques aged 12.3 ± 0.7 yr were fed either a Mediterranean diet that is associated with healthy outcomes or a Western diet that is associated with poor cognitive and metabolic outcomes. Average bioenergetic capacity within each brain region did not differ between diets. Distinct brain regions have different metabolic requirements related to their function and disease susceptibility. Therefore, we also examined differences in bioenergetic capacity between brain regions. Mitochondria isolated from animals fed a Mediterranean diet maintained distinct differences in mitochondrial bioenergetics between brain regions, whereas animals fed the Western diet had diminished distinction in bioenergetics between brain regions. Notably, fatty acid β-oxidation was not affected between regions in animals fed a Western diet. In addition, bioenergetics in animals fed a Western diet had positive associations with fasting blood glucose and insulin levels in PFC and ERC mitochondria but not in CB mitochondria. Altogether, these data indicate that a Western diet disrupts bioenergetic patterns across brain regions and that circulating blood glucose and insulin levels in Western-diet fed animals influence bioenergetics in brain regions susceptible to Alzheimer's disease and type 2 diabetes.NEW & NOTEWORTHY We show that compared with cynomolgus macaques fed a Mediterranean diet, a Western diet resulted in diminished bioenergetic pattern between brain regions related to blood glucose and insulin levels, specifically in brain regions susceptible to neurodegeneration and diabetes. In addition, fatty acid metabolism not directly linked to the TCA cycle and glucose metabolism did not show differences in bioenergetics due to diet.

The Spatiotemporal Coupling: Regional Energy Failure and Aberrant Proteins in Neurodegenerative Diseases

The spatial and temporal coordination of each element is a pivotal characteristic of systems, and the central nervous system (CNS) is not an exception. Glial elements and the vascular interface have been considered more recently, together with the extracellular matrix and the immune system. However, the knowledge of the single-element configuration is not sufficient to predict physiological or pathological long-lasting changes. Ionic currents, complex molecular cascades, genomic rearrangement, and the regional energy demand can be different even in neighboring cells of the same phenotype, and their differential expression could explain the region-specific progression of the most studied neurodegenerative diseases. We here reviewed the main nodes and edges of the system, which could be studied to develop a comprehensive knowledge of CNS plasticity from the neurovascular unit to the synaptic cleft. The future goal is to redefine the modeling of synaptic plasticity and achieve a better understanding of neurological diseases, pointing out cellular, subcellular, and molecular components that couple in specific neuroanatomical and functional regions.

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

The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.

Bayesian Physics-Based Modeling of Tau Propagation in Alzheimer's Disease

Amyloid-β and hyperphosphorylated tau protein are known drivers of neuropathology in Alzheimer's disease. Tau in particular spreads in the brains of patients following a spatiotemporal pattern that is highly sterotypical and correlated with subsequent neurodegeneration. Novel medical imaging techniques can now visualize the distribution of tau in the brain in vivo, allowing for new insights to the dynamics of this biomarker. Here we personalize a network diffusion model with global spreading and local production terms to longitudinal tau positron emission tomography data of 76 subjects from the Alzheimer's Disease Neuroimaging Initiative. We use Bayesian inference with a hierarchical prior structure to infer means and credible intervals for our model parameters on group and subject levels. Our results show that the group average protein production rate for amyloid positive subjects is significantly higher with 0.019±0.27/yr, than that for amyloid negative subjects with -0.143±0.21/yr (p = 0.0075). These results support the hypothesis that amyloid pathology drives tau pathology. The calibrated model could serve as a valuable clinical tool to identify optimal time points for follow-up scans and predict the timeline of disease progression.

Basal Forebrain Cholinergic Neurons: Linking Down Syndrome and Alzheimer's Disease

Down syndrome (DS, trisomy 21) is characterized by intellectual impairment at birth and Alzheimer's disease (AD) pathology in middle age. As individuals with DS age, their cognitive functions decline as they develop AD pathology. The susceptibility to degeneration of a subset of neurons, known as basal forebrain cholinergic neurons (BFCNs), in DS and AD is a critical link between cognitive impairment and neurodegeneration in both disorders. BFCNs are the primary source of cholinergic innervation to the cerebral cortex and hippocampus, as well as the amygdala. They play a critical role in the processing of information related to cognitive function and are directly engaged in regulating circuits of attention and memory throughout the lifespan. Given the importance of BFCNs in attention and memory, it is not surprising that these neurons contribute to dysfunctional neuronal circuitry in DS and are vulnerable in adults with DS and AD, where their degeneration leads to memory loss and disturbance in language. BFCNs are thus a relevant cell target for therapeutics for both DS and AD but, despite some success, efforts in this area have waned. There are gaps in our knowledge of BFCN vulnerability that preclude our ability to effectively design interventions. Here, we review the role of BFCN function and degeneration in AD and DS and identify under-studied aspects of BFCN biology. The current gaps in BFCN relevant imaging studies, therapeutics, and human models limit our insight into the mechanistic vulnerability of BFCNs in individuals with DS and AD.

The Interplay of Apoes with Syndecans in Influencing Key Cellular Events of Amyloid Pathology

Apolipoprotein E (ApoE) isoforms exert intricate effects on cellular physiology beyond lipid transport and metabolism. ApoEs influence the onset of Alzheimer’s disease (AD) in an isoform-dependent manner: ApoE4 increases AD risk, while ApoE2 decreases it. Previously we demonstrated that syndecans, a transmembrane proteoglycan family with increased expression in AD, trigger the aggregation and modulate the cellular uptake of amyloid beta (Aβ). Utilizing our previously established syndecan-overexpressing cellular assays, we now explore how the interplay of ApoEs with syndecans contributes to key events, namely uptake and aggregation, in Aβ pathology. The interaction of ApoEs with syndecans indicates isoform-specific characteristics arising beyond the frequently studied ApoE–heparan sulfate interactions. Syndecans, and among them the neuronal syndecan-3, increased the cellular uptake of ApoEs, especially ApoE2 and ApoE3, while ApoEs exerted opposing effects on syndecan-3-mediated Aβ uptake and aggregation. ApoE2 increased the cellular internalization of monomeric Aβ, hence preventing its extracellular aggregation, while ApoE4 decreased it, thus helping the buildup of extracellular plaques. The contrary effects of ApoE2 and ApoE4 remained once Aβ aggregated: while ApoE2 reduced the uptake of Aβ aggregates, ApoE4 facilitated it. Fibrillation studies also revealed ApoE4′s tendency to form fibrillar aggregates. Our results uncover yet unknown details of ApoE cellular biology and deepen our molecular understanding of the ApoE-dependent mechanism of Aβ pathology.

Common neural and transcriptional correlates of inhibitory control underlie emotion regulation and memory control

Inhibitory control is crucial for regulating emotions and may also enable memory control. However, evidence for their shared neurobiological correlates is limited. Here, we report meta-analyses of neuroimaging studies on emotion regulation, or memory control and link neural commonalities to transcriptional commonalities using the Allen Human Brain Atlas (AHBA). Based on 95 functional magnetic resonance imaging studies, we reveal a role of the right inferior parietal lobule embedded in a frontal–parietal–insular network during emotion regulation and memory control, which is similarly recruited during response inhibition. These co-activation patterns also overlap with the networks associated with ‘inhibition’, ‘cognitive control’ and ‘working memory’ when consulting the Neurosynth. Using the AHBA, we demonstrate that emotion regulation- and memory control-related brain activity patterns are associated with transcriptional profiles of a specific set of ‘inhibition-related’ genes. Gene ontology enrichment analysis of these ‘inhibition-related’ genes reveal associations with the neuronal transmission and risk for major psychiatric disorders as well as seizures and alcoholic dependence. In summary, this study identified a neural network and a set of genes associated with inhibitory control across emotion regulation and memory control. These findings facilitate our understanding of the neurobiological correlates of inhibitory control and may contribute to the development of brain stimulation and pharmacological interventions.

KL-VS heterozygosity is associated with lower amyloid-dependent tau accumulation and memory impairment in Alzheimer's disease

Klotho-VS heterozygosity (KL-VS^het) is associated with reduced risk of Alzheimer’s disease (AD). However, whether KL-VS^het is associated with lower levels of pathologic tau, i.e., the key AD pathology driving neurodegeneration and cognitive decline, is unknown. Here, we assessed the interaction between KL-VS^het and levels of beta-amyloid, a key driver of tau pathology, on the levels of PET-assessed neurofibrillary tau in 551 controls and patients across the AD continuum. KL-VS^het showed lower cross-sectional and longitudinal increase in tau-PET per unit increase in amyloid-PET when compared to that of non-carriers. This association of KL-VS^het on tau-PET was stronger in Klotho mRNA-expressing brain regions mapped onto a gene expression atlas. KL-VS^het was related to better memory functions in amyloid-positive participants and this association was mediated by lower tau-PET. Amyloid-PET levels did not differ between KL-VS^het carriers versus non-carriers. Together, our findings provide evidence to suggest a protective role of KL-VS^het against amyloid-related tau pathology and tau-related memory impairments in elderly humans at risk of AD dementia.

The KL-VS haplotype of the Klotho gene has been associated with reduced risk of Alzheimer’s disease and dementia. Here the authors show an association between the KL-VS haplotype and amyloid-dependent tau accumulation using PET data.

Association Between Gray Matter Volume Variations and Energy Utilization in the Brain: Implications for Developmental Stuttering

Purpose The biological mechanisms underlying developmental stuttering remain unclear. In a previous investigation, we showed that there is significant spatial correspondence between regional gray matter structural anomalies and the expression of genes linked to energy metabolism. In the current study, we sought to further examine the relationship between structural anomalies in the brain in children with persistent stuttering and brain regional energy metabolism. Method High-resolution structural MRI scans were acquired from 26 persistent stuttering and 44 typically developing children. Voxel-based morphometry was used to quantify the between-group gray matter volume (GMV) differences across the whole brain. Group differences in GMV were then compared with published values for the pattern of glucose metabolism measured via F18 fluorodeoxyglucose uptake in the brains of 29 healthy volunteers using positron emission tomography. Results A significant positive correlation between GMV differences and F18 fluorodeoxyglucose uptake was found in the left hemisphere (ρ = .36, p < .01), where speech-motor and language processing are typically localized. No such correlation was observed in the right hemisphere (ρ = .05, p = .70). Conclusions Corroborating our previous gene expression studies, the results of the current study suggest a potential connection between energy metabolism and stuttering. Brain regions with high energy utilization may be particularly vulnerable to anatomical changes associated with stuttering. Such changes may be further exacerbated when there are sharp increases in brain energy utilization, which coincides with the developmental period of rapid speech/language acquisition and the onset of stuttering during childhood. Supplemental Material https://doi.org/10.23641/asha.14110454.

Prioritizing Genetic Contributors to Cortical Alterations in 22q11.2 Deletion Syndrome Using Imaging Transcriptomics

22q11.2 deletion syndrome (22q11DS) results from a hemizygous deletion that typically spans 46 protein-coding genes and is associated with widespread alterations in brain morphology. The specific genetic mechanisms underlying these alterations remain unclear. In the 22q11.2 ENIGMA Working Group, we characterized cortical alterations in individuals with 22q11DS (n = 232) versus healthy individuals (n = 290) and conducted spatial convergence analyses using gene expression data from the Allen Human Brain Atlas to prioritize individual genes that may contribute to altered surface area (SA) and cortical thickness (CT) in 22q11DS. Total SA was reduced in 22q11DS (Z-score deviance = -1.04), with prominent reductions in midline posterior and lateral association regions. Mean CT was thicker in 22q11DS (Z-score deviance = +0.64), with focal thinning in a subset of regions. Regional expression of DGCR8 was robustly associated with regional severity of SA deviance in 22q11DS; AIFM3 was also associated with SA deviance. Conversely, P2RX6 was associated with CT deviance. Exploratory analysis of gene targets of microRNAs previously identified as down-regulated due to DGCR8 deficiency suggested that DGCR8 haploinsufficiency may contribute to altered corticogenesis in 22q11DS by disrupting cell cycle modulation. These findings demonstrate the utility of combining neuroanatomic and transcriptomic datasets to derive molecular insights into complex, multigene copy number variants.

Metabolic and amyloid PET network reorganization in Alzheimer's disease: differential patterns and partial volume effects

Alzheimer’s disease (AD) is a neurodegenerative disorder, considered a disconnection syndrome with regional molecular pattern abnormalities quantifiable by the aid of PET imaging. Solutions for accurate quantification of network dysfunction are scarce. We evaluate the extent to which PET molecular markers reflect quantifiable network metrics derived through the graph theory framework and how partial volume effects (PVE)-correction (PVEc) affects these PET-derived metrics 75 AD patients and 126 cognitively normal older subjects (CN). Therefore our goal is twofold: 1) to evaluate the differential patterns of [¹⁸F]FDG- and [¹⁸F]AV45-PET data to depict AD pathology; and ii) to analyse the effects of PVEc on global uptake measures of [¹⁸F]FDG- and [¹⁸F]AV45-PET data and their derived covariance network reconstructions for differentiating between patients and normal older subjects. Network organization patterns were assessed using graph theory in terms of “degree”, “modularity”, and “efficiency”. PVEc evidenced effects on global uptake measures that are specific to either [¹⁸F]FDG- or [¹⁸F]AV45-PET, leading to increased statistical differences between the groups. PVEc was further shown to influence the topological characterization of PET-derived covariance brain networks, leading to an optimised characterization of network efficiency and modularisation. Partial-volume effects correction improves the interpretability of PET data in AD and leads to optimised characterization of network properties for organisation or disconnection.

Differential patterns of gray matter volumes and associated gene expression profiles in cognitively-defined Alzheimer's disease subgroups

The clinical presentation of Alzheimer's disease (AD) varies widely across individuals but the neurobiological mechanisms underlying this heterogeneity are largely unknown. Here, we compared regional gray matter (GM) volumes and associated gene expression profiles between cognitively-defined subgroups of amyloid-β positive individuals clinically diagnosed with AD dementia (age: 66 ± 7, 47% male, MMSE: 21 ± 5). All participants underwent neuropsychological assessment with tests covering memory, executive-functioning, language and visuospatial-functioning domains. Subgroup classification was achieved using a psychometric framework that assesses which cognitive domain shows substantial relative impairment compared to the intra-individual average across domains, which yielded the following subgroups in our sample; AD-Memory (n = 41), AD-Executive (n = 117), AD-Language (n = 33), AD-Visuospatial (n = 171). We performed voxel-wise contrasts of GM volumes derived from 3Tesla structural MRI between subgroups and controls (n = 127, age 58 ± 9, 42% male, MMSE 29 ± 1), and observed that differences in regional GM volumes compared to controls closely matched the respective cognitive profiles. Specifically, we detected lower medial temporal lobe GM volumes in AD-Memory, lower fronto-parietal GM volumes in AD-Executive, asymmetric GM volumes in the temporal lobe (left < right) in AD-Language, and lower GM volumes in posterior areas in AD-Visuospatial. In order to examine possible biological drivers of these differences in regional GM volumes, we correlated subgroup-specific regional GM volumes to brain-wide gene expression profiles based on a stereotactic characterization of the transcriptional architecture of the human brain as provided by the Allen human brain atlas. Gene-set enrichment analyses revealed that variations in regional expression of genes involved in processes like mitochondrial respiration and metabolism of proteins were associated with patterns of regional GM volume across multiple subgroups. Other gene expression vs GM volume-associations were only detected in particular subgroups, e.g., genes involved in the cell cycle for AD-Memory, specific sets of genes related to protein metabolism in AD-Language, and genes associated with modification of gene expression in AD-Visuospatial. We conclude that cognitively-defined AD subgroups show neurobiological differences, and distinct biological pathways may be involved in the emergence of these differences.

Alternative splicing in Alzheimer's disease

Alzheimer's disease (AD) is the most frequent neurodegenerative disorder in the elderly, occurring in approximately 20% of people older than 80. The molecular causes of AD are still poorly understood. However, recent studies have shown that Alternative Splicing (AS) is involved in the gene expression reprogramming associated with the functional changes observed in AD patients. In particular, mutations in cis-acting regulatory sequences as well as alterations in the activity and sub-cellular localization of trans-acting splicing factors and components of the spliceosome machinery are associated with splicing abnormalities in AD tissues, which may influence the onset and progression of the disease. In this review, we discuss the current molecular understanding of how alterations in the AS process contribute to AD pathogenesis. Finally, recent therapeutic approaches targeting aberrant AS regulation in AD are also reviewed.

Spatial Relationships between Molecular Pathology and Neurodegeneration in the Alzheimer's Disease Continuum

A deeper understanding of the spatial relationships of β-amyloid (Aβ), tau, and neurodegeneration in Alzheimer's disease (AD) could provide insight into pathogenesis and clinical trial design. We included 81 amyloid-positive patients (age 64.4 ± 9.5) diagnosed with AD dementia or mild cognitive impairment due to AD and available 11C-PiB (PIB), 18F-Flortaucipir (FTP),18F-FDG-PET, and 3T-MRI, and 31 amyloid-positive, cognitively normal participants (age 77.3 ± 6.5, no FDG-PET). W-score voxel-wise deviation maps were created and binarized for each imaging-modality (W > 1.64, P < 0.05) adjusting for age, sex, and total intracranial volume (sMRI-only) using amyloid-negative cognitively normal adults. For symptomatic patients, FDG-PET and atrophy W-maps were combined into neurodegeneration maps (ND). Aβ-pathology showed the greatest proportion of cortical gray matter suprathreshold voxels (spatial extent) for both symptomatic and asymptomatic participants (median 94-55%, respectively), followed by tau (79-11%) and neurodegeneration (41-3%). Amyloid > tau > neurodegeneration was the most frequent hierarchy for both groups (79-77%, respectively), followed by tau > amyloid > neurodegeneration (13-10%) and amyloid > neurodegeneration > tau (6-13%). For symptomatic participants, most abnormal voxels were PIB+/FTP+/ND- (median 35%), and the great majority of ND+ voxels (91%) colocalized with molecular pathology. Amyloid spatially exceeded tau and neurodegeneration, with individual heterogeneities. Molecular pathology and neurodegeneration showed a progressive overlap along AD course, indicating shared vulnerabilities or synergistic toxic mechanisms.

Alzheimer's Disease: An Overview of Major Hypotheses and Therapeutic Options in Nanotechnology

Alzheimer's disease (AD), a progressively fatal neurodegenerative disorder, is the most prominent form of dementia found today. Patients suffering from Alzheimer's begin to show the signs and symptoms, like decline in memory and cognition, long after the cellular damage has been initiated in their brain. There are several hypothesis for the neurodegeneration process; however, the lack of availability of in vivo models makes the recapitulation of AD in humans impossible. Moreover, the drugs currently available in the market serve to alleviate the symptoms and there is no cure for the disease. There have been two major hurdles in the process of finding the same-the inefficiency in cracking the complexity of the disease pathogenesis and the inefficiency in delivery of drugs targeted for AD. This review discusses the different drugs that have been designed over the recent years and the drug delivery options in the field of nanotechnology that have been found most feasible in surpassing the blood-brain barrier (BBB) and reaching the brain.

Network Diffusion Modeling Explains Longitudinal Tau PET Data

Alzheimer's disease is associated with the cerebral accumulation of neurofibrillary tangles of hyperphosphorylated tau protein. The progressive occurrence of tau aggregates in different brain regions is closely related to neurodegeneration and cognitive impairment. However, our current understanding of tau propagation relies almost exclusively on postmortem histopathology, and the precise propagation dynamics of misfolded tau in the living brain remain poorly understood. Here we combine longitudinal positron emission tomography and dynamic network modeling to test the hypothesis that misfolded tau propagates preferably along neuronal connections. We follow 46 subjects for three or four annual positron emission tomography scans and compare their pathological tau profiles against brain network models of intracellular and extracellular spreading. For each subject, we identify a personalized set of model parameters that characterizes the individual progression of pathological tau. Across all subjects, the mean protein production rate was 0.21 ± 0.15 and the intracellular diffusion coefficient was 0.34 ± 0.43. Our network diffusion model can serve as a tool to detect non-clinical symptoms at an earlier stage and make informed predictions about the timeline of neurodegeneration on an individual personalized basis.

Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer's disease

In Alzheimer's disease (AD), the Braak staging scheme suggests a stereotypical tau spreading pattern that does, however, not capture interindividual variability in tau deposition. This complicates the prediction of tau spreading, which may become critical for defining individualized tau-PET readouts in clinical trials. Since tau is assumed to spread throughout connected regions, we used functional connectivity to improve tau spreading predictions over Braak staging methods. We included two samples with longitudinal tau-PET from controls and AD patients. Cross-sectionally, we found connectivity of tau epicenters (i.e., regions with earliest tau) to predict estimated tau spreading sequences. Longitudinally, we found tau accumulation rates to correlate with connectivity strength to patient-specific tau epicenters. A connectivity-based, patient-centered tau spreading model improved the assessment of tau accumulation rates compared to Braak stage-specific readouts and reduced sample sizes by ~40% in simulated tau-targeting interventions. Thus, connectivity-based tau spreading models may show utility in clinical trials.

Donor-Specific Transcriptomic Analysis of Alzheimer's Disease-Associated Hypometabolism Highlights a Unique Donor, Ribosomal Proteins and Microglia

Alzheimer's disease (AD) starts decades before clinical symptoms appear. Low-glucose utilization in regions of the cerebral cortex marks early AD. To identify these regions, we conducted a voxel-wise meta-analysis of previous studies conducted with positron emission tomography that compared AD patients with healthy controls. The resulting map marks hypometabolism in the posterior cingulate, middle frontal, angular gyrus, and middle and inferior temporal regions. Using the Allen Human Brain Atlas, we identified genes that show spatial correlation across the cerebral cortex between their expression and this hypometabolism. Of the six brains in the Atlas, one demonstrated a strong spatial correlation between gene expression and hypometabolism. Previous neuropathological assessment of this brain from a 39-year-old male noted a neurofibrillary tangle in the entorhinal cortex. Using the transcriptomic data, we estimate lower proportions of neurons and more microglia in the hypometabolic regions when comparing this donor's brain with the other five donors. Within this single brain, signal recognition particle (SRP)-dependent cotranslational protein targeting genes, which encode primarily cytosolic ribosome proteins, are highly expressed in the hypometabolic regions. Analyses of human and mouse data show that expression of these genes increases progressively across AD-associated states of microglial activation. In addition, genes involved in cell killing, chronic inflammation, ubiquitination, tRNA aminoacylation, and vacuole sorting are associated with the hypometabolism map. These genes suggest disruption of the protein life cycle and neuroimmune activation. Taken together, our molecular characterization reveals a link to AD-associated hypometabolism that may be relevant to preclinical stages of AD.

Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder

Major depressive disorder is a debilitating condition with diverse neuroimaging correlates, including cortical thinning in medial prefrontal cortex and altered functional connectivity of cortical association networks. However, the molecular bases of these imaging markers remain ambiguous, despite a need for treatment targets and mechanisms. Here, we advance cross-modal approaches to identify cell types and gene transcripts associated with depression-implicated cortex. Across multiple population-imaging datasets (combined N ≥ 23,723) and ex vivo patient cortical tissue, somatostatin interneurons and astrocytes emerge as replicable cell-level correlates of depression and negative affect. These data identify transcripts, cell types, and molecular processes associated with neuroimaging markers of depression and offer a roadmap for integrating in vivo clinical imaging with genetic and postmortem patient transcriptional data.

Major depressive disorder emerges from the complex interactions of biological systems that span genes and molecules through cells, networks, and behavior. Establishing how neurobiological processes coalesce to contribute to depression requires a multiscale approach, encompassing measures of brain structure and function as well as genetic and cell-specific transcriptional data. Here, we examine anatomical (cortical thickness) and functional (functional variability, global brain connectivity) correlates of depression and negative affect across three population-imaging datasets: UK Biobank, Brain Genomics Superstruct Project, and Enhancing NeuroImaging through Meta Analysis (ENIGMA; combined n ≥ 23,723). Integrative analyses incorporate measures of cortical gene expression, postmortem patient transcriptional data, depression genome-wide association study (GWAS), and single-cell gene transcription. Neuroimaging correlates of depression and negative affect were consistent across three independent datasets. Linking ex vivo gene down-regulation with in vivo neuroimaging, we find that transcriptional correlates of depression imaging phenotypes track gene down-regulation in postmortem cortical samples of patients with depression. Integrated analysis of single-cell and Allen Human Brain Atlas expression data reveal somatostatin interneurons and astrocytes to be consistent cell associates of depression, through both in vivo imaging and ex vivo cortical gene dysregulation. Providing converging evidence for these observations, GWAS-derived polygenic risk for depression was enriched for genes expressed in interneurons, but not glia. Underscoring the translational potential of multiscale approaches, the transcriptional correlates of depression-linked brain function and structure were enriched for disorder-relevant molecular pathways. These findings bridge levels to connect specific genes, cell classes, and biological pathways to in vivo imaging correlates of depression.

Analysis of brain atrophy and local gene expression in genetic frontotemporal dementia

Frontotemporal dementia is a heterogeneous neurodegenerative disorder characterized by neuronal loss in the frontal and temporal lobes. Despite progress in understanding which genes are associated with the aetiology of frontotemporal dementia, the biological basis of how mutations in these genes lead to cell loss in specific cortical regions remains unclear. In this work we combined gene expression data for 16,772 genes from the Allen Institute for Brain Science atlas with brain maps of gray matter atrophy in symptomatic C9orf72, GRN and MAPT mutation carriers obtained from the Genetic Frontotemporal dementia Initiative study. No significant association was seen between C9orf72, GRN and MAPT expression and the atrophy patterns in the respective genetic groups. After adjusting for spatial autocorrelation, between 1,000 and 5,000 genes showed a negative or positive association with the atrophy pattern within each individual genetic group, with the most significantly associated genes being TREM2, SSBP3 and GPR158 (negative association in C9orf72, GRN and MAPT respectively) and RELN, MXRA8 and LPA (positive association in C9orf72, GRN and MAPT respectively). An overrepresentation analysis identified a negative association with genes involved in mitochondrial function, and a positive association with genes involved in vascular and glial cell function in each of the genetic groups. A set of 423 and 700 genes showed significant positive and negative association, respectively, with atrophy patterns in all three maps. The gene set with increased expression in spared cortical regions was enriched for neuronal and microglial genes, while the gene set with increased expression in atrophied regions was enriched for astrocyte and endothelial cell genes. Our analysis suggests that these cell types may play a more active role in the onset of neurodegeneration in frontotemporal dementia than previously assumed, and in the case of the positively-associated cell marker genes, potentially through emergence of neurotoxic astrocytes and alteration in the blood-brain barrier respectively.

Linking Lysosomal Enzyme Targeting Genes and Energy Metabolism with Altered Gray Matter Volume in Children with Persistent Stuttering

Developmental stuttering is a childhood onset neurodevelopmental disorder with an unclear etiology. Subtle changes in brain structure and function are present in both children and adults who stutter. It is a highly heritable disorder, and 12-20% of stuttering cases may carry a mutation in one of four genes involved in intracellular trafficking. To better understand the relationship between genetics and neuroanatomical changes, we used gene expression data from the Allen Institute for Brain Science and voxel-based morphometry to investigate the spatial correspondence between gene expression patterns and differences in gray matter volume between children with persistent stuttering (n = 26, and 87 scans) and their fluent peers (n = 44, and 139 scans). We found that the expression patterns of two stuttering-related genes (GNPTG and NAGPA) from the Allen Institute data exhibited a strong positive spatial correlation with the magnitude of between-group gray matter volume differences. Additional gene set enrichment analyses revealed that genes whose expression was highly correlated with the gray matter volume differences were enriched for glycolysis and oxidative metabolism in mitochondria. Because our current study did not examine the participants' genomes, these results cannot establish the direct association between genetic mutations and gray matter volume differences in stuttering. However, our results support further study of the involvement of lysosomal enzyme targeting genes, as well as energy metabolism in stuttering. Future studies assessing variations of these genes in the participants' genomes may lead to increased understanding of the biological mechanisms of the observed spatial relationship between gene expression and gray matter volume.

Quantitative patterns of motor cortex proteinopathy across ALS genotypes

Degeneration of the primary motor cortex is a defining feature of amyotrophic lateral sclerosis (ALS), which is associated with the accumulation of microscopic protein aggregates in neurons and glia. However, little is known about the quantitative burden and pattern of motor cortex proteinopathies across ALS genotypes. We combined quantitative digital image analysis with multi-level generalized linear modelling in an independent cohort of 82 ALS cases to explore the relationship between genotype, total proteinopathy load and cellular vulnerability to aggregate formation. Primary motor cortex phosphorylated (p)TDP-43 burden and microglial activation were more severe in sporadic ALS-TDP disease than C9-ALS. Oligodendroglial pTDP-43 pathology was a defining feature of ALS-TDP in sporadic ALS, C9-ALS and ALS with OPTN, HNRNPA1 or TARDBP mutations. ALS-FUS and ALS-SOD1 showed less cortical proteinopathy in relation to spinal cord pathology than ALS-TDP, where pathology was more evenly spread across the motor cortex-spinal cord axis. Neuronal pTDP-43 aggregates were rare in GAD67+ and Parvalbumin+ inhibitory interneurons, consistent with predominant accumulation in excitatory neurons. Finally, we show that cortical microglia, but not astrocytes, contain pTDP-43. Our findings suggest divergent quantitative, genotype-specific vulnerability of the ALS primary motor cortex to proteinopathies, which may have implications for our understanding of disease pathogenesis and the development of genotype-specific therapies.

Disentangling Heterogeneity in Alzheimer's Disease and Related Dementias Using Data-Driven Methods

Brain aging is a complex process that includes atrophy, vascular injury, and a variety of age-associated neurodegenerative pathologies, together determining an individual's course of cognitive decline. While Alzheimer's disease and related dementias contribute to the heterogeneity of brain aging, these conditions themselves are also heterogeneous in their clinical presentation, progression, and pattern of neural injury. We reviewed studies that leveraged data-driven approaches to examining heterogeneity in Alzheimer's disease and related dementias, with a principal focus on neuroimaging studies exploring subtypes of regional neurodegeneration patterns. Over the past decade, the steadily increasing wealth of clinical, neuroimaging, and molecular biomarker information collected within large-scale observational cohort studies has allowed for a richer understanding of the variability of disease expression within the aging and Alzheimer's disease and related dementias continuum. Moreover, the availability of these large-scale datasets has supported the development and increasing application of clustering techniques for studying disease heterogeneity in a data-driven manner. In particular, data-driven studies have led to new discoveries of previously unappreciated disease subtypes characterized by distinct neuroimaging patterns of regional neurodegeneration, which are paralleled by heterogeneous profiles of pathological, clinical, and molecular biomarker characteristics. Incorporating these findings into novel frameworks for more differentiated disease stratification holds great promise for improving individualized diagnosis and prognosis of expected clinical progression, and provides opportunities for development of precision medicine approaches for therapeutic intervention. We conclude with an account of the principal challenges associated with data-driven heterogeneity analyses and outline avenues for future developments in the field.

Spread of pathological tau proteins through communicating neurons in human Alzheimer's disease

Tau is a hallmark pathology of Alzheimer's disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β-amyloid (Aβ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer's disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our model. Surprisingly, the ESM predicts the spatial patterns of tau irrespective of whether brain Aβ is present, but regions with greater Aβ burden show greater tau than predicted by connectivity patterns, suggesting a role of Aβ in accelerating tau spread. Altogether, our results provide evidence in humans that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain Aβ.

Basal forebrain volume reliably predicts the cortical spread of Alzheimer's degeneration

Alzheimer's disease neurodegeneration is thought to spread across anatomically and functionally connected brain regions. However, the precise sequence of spread remains ambiguous. The prevailing model used to guide in vivo human neuroimaging and non-human animal research assumes that Alzheimer's degeneration starts in the entorhinal cortices, before spreading to the temporoparietal cortex. Challenging this model, we previously provided evidence that in vivo markers of neurodegeneration within the nucleus basalis of Meynert (NbM), a subregion of the basal forebrain heavily populated by cortically projecting cholinergic neurons, precedes and predicts entorhinal degeneration. There have been few systematic attempts at directly comparing staging models using in vivo longitudinal biomarker data, and none to our knowledge testing if comparative evidence generalizes across independent samples. Here we addressed the sequence of pathological staging in Alzheimer's disease using two independent samples of the Alzheimer's Disease Neuroimaging Initiative (n1 = 284; n2 = 553) with harmonized CSF assays of amyloid-β and hyperphosphorylated tau (pTau), and longitudinal structural MRI data over 2 years. We derived measures of grey matter degeneration in a priori NbM and the entorhinal cortical regions of interest. To examine the spreading of degeneration, we used a predictive modelling strategy that tests whether baseline grey matter volume in a seed region accounts for longitudinal change in a target region. We demonstrated that predictive spread favoured the NbM→entorhinal over the entorhinal→NbM model. This evidence generalized across the independent samples. We also showed that CSF concentrations of pTau/amyloid-β moderated the observed predictive relationship, consistent with evidence in rodent models of an underlying trans-synaptic mechanism of pathophysiological spread. The moderating effect of CSF was robust to additional factors, including clinical diagnosis. We then applied our predictive modelling strategy to an exploratory whole-brain voxel-wise analysis to examine the spatial specificity of the NbM→entorhinal model. We found that smaller baseline NbM volumes predicted greater degeneration in localized regions of the entorhinal and perirhinal cortices. By contrast, smaller baseline entorhinal volumes predicted degeneration in the medial temporal cortex, recapitulating a prior influential staging model. Our findings suggest that degeneration of the basal forebrain cholinergic projection system is a robust and reliable upstream event of entorhinal and neocortical degeneration, calling into question a prevailing view of Alzheimer's disease pathogenesis.

Functional brain architecture is associated with the rate of tau accumulation in Alzheimer's disease

In Alzheimer's diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independent samples including 53 (ADNI) and 41 (BioFINDER) amyloid-biomarker defined AD subjects and 28 (ADNI) vs. 16 (BioFINDER) amyloid-negative healthy controls. In both samples, AD subjects show faster tau accumulation than controls. Second, in AD, higher fMRI-assessed connectivity between 400 regions of interest (ROIs) is associated with correlated tau-PET accumulation in corresponding ROIs. Third, we show that a model including baseline connectivity and tau-PET is associated with future tau-PET accumulation. Together, connectivity is associated with tau spread in AD, supporting the view of transneuronal tau propagation.

Brain Imaging Genomics: Integrated Analysis and Machine Learning

Brain imaging genomics is an emerging data science field, where integrated analysis of brain imaging and genomics data, often combined with other biomarker, clinical and environmental data, is performed to gain new insights into the phenotypic, genetic and molecular characteristics of the brain as well as their impact on normal and disordered brain function and behavior. It has enormous potential to contribute significantly to biomedical discoveries in brain science. Given the increasingly important role of statistical and machine learning in biomedicine and rapidly growing literature in brain imaging genomics, we provide an up-to-date and comprehensive review of statistical and machine learning methods for brain imaging genomics, as well as a practical discussion on method selection for various biomedical applications.