Search

Abstract Background Recent research has postulated that the activation of cGAS-STING-interferon signalling pathways could be implicated in the pathogenesis of Alzheimer’s disease (AD). However, the precise types of interferons and related cytokines, both from the brain and periphery, responsible for cognitive impairment in patients with AD remain unclear. Methods A total of 131 participants (78 [59.5%] female and 53 [40.5%] male; mean [SD] age, 61.5 [7.6] years) with normal cognition and cognitive impairment from the China Aging and Neurodegenerative Initiative cohort were included. CSF and serum IFNα-2a, IFN-β, IFN-γ, TNF-α, IL-6, IL-10, MCP-1and CXCL-10 were tested. The correlation between these interferons and related cytokines with AD core biomarkers in the CSF and plasma, cognition performance, and brain MRI measures were analysed. Results We found that only CSF IFN-β levels were significantly elevated in Alzheimer’s disease compared to normal cognition. Furthermore, CSF IFN-β levels were significantly associated with AD core biomarkers (CSF P-tau and Aβ42/Aβ40 ratio) and cognitive performance (MMSE and CDR score). Additionally, the CSF IFN-β levels were significantly correlated with the typical pattern of brain atrophy in AD (such as hippocampus, amygdala, and precuneus). In contrast, CSF IL-6 levels were significantly elevated in non-AD cognitively impaired patients compared to other groups. Moreover, CSF IL-6 levels were significantly associated with cognitive performance in non-AD individuals and correlated with the vascular cognitive impairment-related MRI markers (such as white matter hyperintensity). Conclusion Our findings demonstrate that distinct inflammatory molecules are associated with different cognitive disorders. Notably, CSF IFN-β levels are significantly linked to the pathology and cognitive performance of AD, identifying this interferon as a potential target for AD therapy.

Abstract Introduction Heparin binding proteins (HBPs) with roles in extracellular matrix assembly are strongly correlated to β-amyloid (Aβ) and tau pathology in Alzheimer’s disease (AD) brain and cerebrospinal fluid (CSF). However, it remains challenging to detect these proteins in plasma using standard mass spectrometry-based proteomic approaches. Methods We employed heparin-affinity chromatography, followed by off-line fractionation and tandem mass tag mass spectrometry (TMT-MS), to enrich HBPs from plasma obtained from AD (n = 62) and control (n = 47) samples. These profiles were then correlated to Aβ, tau and phosphorylated tau (pTau) CSF biomarkers and plasma pTau181 from the same individuals, as well as a consensus brain proteome network to assess the overlap with AD brain pathophysiology. Results Heparin enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundant proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude in abundance, were measured across 109 samples. Compared to the consensus AD brain protein co-expression network, we observed that specific plasma proteins exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes, highlighting the complex interplay between the two compartments. Elevated proteins in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate with Aβ deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and the APOE4 proteoform. Additionally, heparin-enriched proteins in plasma demonstrated significant correlations with conventional AD CSF biomarkers, including Aβ, total tau, pTau, and plasma pTau181. A panel of five plasma proteins classified AD from control individuals with an area under the curve (AUC) of 0.85. When combined with plasma pTau181, the panel significantly improved the classification performance of pTau181 alone, increasing the AUC from 0.93 to 0.98. This suggests that the heparin-enriched plasma proteome captures additional variance in cognitive dementia beyond what is explained by pTau181. Conclusion These findings support the utility of a heparin-affinity approach coupled with TMT-MS for enriching amyloid-associated proteins, as well as a wide spectrum of plasma biomarkers that reflect pathological changes in the AD brain.

Summary: Background: Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. However, it is unknown whether PVS can predict dementia risk and brain atrophy trajectories in participants without dementia, as longitudinal studies on PVS are scarce and current methods for PVS assessment lack robustness and inter-scanner reproducibility. Methods: We developed a robust algorithm to automatically assess PVS count and size on clinical MRI, and investigated 1) their relationship with dementia risk and brain atrophy in participants without dementia, 2) their longitudinal evolution, and 3) their potential use as a screening tool in simulated clinical trials. We analysed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1 ± 9.7 years-old, 56.6% women) from three publicly available observational studies on ageing and dementia (the Alzheimer’s Disease Neuroimaging Initiative, the National Alzheimer’s Coordinating Centre database, and the Open Access Series of Imaging Studies). Clinical and MRI data collected between 2004 and 2022 were analysed with consistent methods, controlling for confounding factors, and combined using mixed-effects models. Findings: Our fully-automated method for PVS assessment showed excellent inter-scanner reproducibility (intraclass correlation coefficients >0.8). Fewer PVS and larger PVS diameter at baseline predicted higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers differed significantly in participants without dementia who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants at low risk of dementia based on our PVS markers enhanced the power of the trial independently of Alzheimer’s disease biomarkers. Interpretation: These robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia. Funding: US National Institutes of Health.

Abstract Lewy body dementia (LBD), a class of disorders comprising Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer’s disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson’s disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or “modules” of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

The spleen tyrosine kinase (SYK) and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) interaction has a major role in the normal innate and adaptive immune responses, but dysregulation of this interaction is implicated in several human diseases, including autoimmune disorders, hematological malignancies, and Alzheimer's Disease. Development of small molecule chemical probes could aid in studying this pathway both in normal and aberrant contexts. Herein, we describe the miniaturization of a time-resolved fluorescence resonance energy transfer (TR-FRET) assay to measure the interaction between SYK and FCER1G in a 1536-well ultrahigh throughput screening (uHTS) format. The assay utilizes the His-SH2 domains of SYK, which are indirectly labeled with anti-His-terbium to serve as a TR-FRET donor and a FITC-conjugated phosphorylated ITAM domain peptide of FCER1G to serve as an acceptor. We have optimized the assay into a 384-well HTS format and further miniaturized the assay into a 1536-well uHTS format. Robust assay performance has been achieved with a Z’ factor > 0.8 and signal-to-background (S/B) ratio > 15. The utilization of this uHTS TR-FRET assay for compound screening has been validated by a pilot screening of 2,036 FDA-approved and bioactive compounds library. Several primary hits have been identified from the pilot uHTS. One compound, hematoxylin, was confirmed to disrupt the SYK/FECR1G interaction in an orthogonal protein–protein interaction assay. Thus, our optimized and miniaturized uHTS assay could be applied to future scaling up of a screening campaign to identify small molecule inhibitors targeting the SYK and FCER1G interaction.

Antibodies are used in many areas of biomedical and clinical research, but many of these antibodies have not been adequately characterized, which casts doubt on the results reported in many scientific papers. This problem is compounded by a lack of suitable control experiments in many studies. In this article we review the history of the ‘antibody characterization crisis’, and we document efforts and initiatives to address the problem, notably for antibodies that target human proteins. We also present recommendations for a range of stakeholders – researchers, universities, journals, antibody vendors and repositories, scientific societies and funders – to increase the reproducibility of studies that rely on antibodies.

Abstract Background Seizure detection is challenging outside the clinical environment due to the lack of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We developed a novel, discreet, unobstructive in-ear sensing system that enables long-term electroencephalography (EEG) recording. This is the first study we are aware of that systematically compares the seizure detection utility of in-ear EEG with that of simultaneously recorded intracranial EEG. In addition, we present a similar comparison between simultaneously recorded in-ear EEG and scalp EEG. Methods In this foundational research, we conducted a clinical feasibility study and validated the ability of the ear-EEG system to capture focal-onset seizures against 1255 hrs of simultaneous ear-EEG data along with scalp or intracranial EEG in 20 patients with refractory focal epilepsy (11 with scalp EEG, 8 with intracranial EEG, and 1 with both). Results In a blinded, independent review of the ear-EEG signals, two epileptologists were able to detect 86.4% of the seizures that were subsequently identified using the clinical gold standard EEG modalities, with a false detection rate of 0.1 per day, well below what has been reported for ambulatory monitoring. The few seizures not detected on the ear-EEG signals emanated from deep within the mesial temporal lobe or extra-temporally and remained very focal, without significant propagation. Following multiple sessions of recording for a median continuous wear time of 13 hrs, patients reported a high degree of tolerance for the device, with only minor adverse events reported by the scalp EEG cohort. Conclusions These preliminary results demonstrate the potential of using ear-EEG to enable routine collection of complementary, prolonged, and remote neurophysiological evidence, which may permit real-time detection of paroxysmal events such as seizures and epileptiform discharges. This study suggests that the ear-EEG device may assist clinicians in making an epilepsy diagnosis, assessing treatment efficacy, and optimizing medication titration.

Background A major goal of the Target Enablement to Accelerate Therapy Development for Alzheimer’s disease (TREAT-AD) program is to develop and identify high-quality tools to test target or mechanistic hypotheses. As part of this initiative, it is important that commercial reagents including research antibodies being used to interrogate drug targets have confirmed validation data in knock-out cell lines. Ideally, these antibodies should also have utility for both in vitro and in vivo studies such that the levels of target proteins in target tissues can be quantified. Methods We evaluated commercial antibodies against TREAT-AD protein targets Moesin (Uniprot ID: P26038), CD44 (Uniprot ID: P16070), Midkine (Uniprot ID: P21741) and Secreted frizzled-related protein 1, referred to as “sFRP-1” (sFRP-1; Uniprot ID: Q8N474). Moesin, Midkine and sFRP-1, that were confirmed as selective based on data in knock-out cell lines. Western blot analysis was used to compare protein levels in brain homogenates from a mouse model with AD-relevant pathology (5XFAD) versus age-matched C57BL/6J control mice. Results Anti-Moesin ab52490 reacted in mouse brain homogenate with a predicted molecular weight of 68 kDa. Moesin protein expression was 2.8 times higher in 5xFAD compared to WT. Anti-CD44 ab189524 reacted with a band at the predicted size of 82 kDa. CD44 protein expression was 1.9 times higher in 5xFAD compared to WT. Anti-Midkine AF7769 reacted with a band ~16 kDa and a 17.8 times greater expression in 5xFAD compared to WT. Anti-sFRP-1 ab267466 reacted with a band at 35 kDa as predicted. sFRP-1 protein expression was 11.9 times greater in 5xFAD compared to WT. Conclusions These data confirm the utility of these selective commercially available antibodies against Moesin, CD44, Midkine, and sFRP-1 for in vivo studies in mice and provide insight into the use of 5XFAD mice for in vivo target engagement studies for these target proteins.

Summary: Background: Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD. Methods: 445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants. Findings: We found both tau metrics significantly elevated across increasing disease stages (p

Background A major goal of the Target Enablement to Accelerate Therapy Development for Alzheimer’s disease (TREAT-AD) program is to develop and identify high-quality tools to test target or mechanistic hypotheses. As part of this initiative, it is important that commercial reagents including research antibodies being used to interrogate drug targets have confirmed validation data in knock-out cell lines. Ideally, these antibodies should also have utility for both in vitro and in vivo studies such that the levels of target proteins in target tissues can be quantified. Methods We evaluated commercial antibodies against TREAT-AD protein targets Moesin (Uniprot ID: P26038), CD44 (Uniprot ID: P16070), Midkine (Uniprot ID: P21741) and Secreted frizzled-related protein 1, referred to as “sFRP-1” (sFRP-1; Uniprot ID: Q8N474). Moesin, Midkine and sFRP-1, that were confirmed as selective based on data in knock-out cell lines. Western blot analysis was used to compare protein levels in brain homogenates from a mouse model with AD-relevant pathology (5XFAD) versus age-matched C57BL/6J control mice. Results Anti-Moesin ab52490 reacted in mouse brain homogenate with a predicted molecular weight of 68 kDa. Moesin protein expression was 2.8 times higher in 5xFAD compared to WT. Anti-CD44 ab189524 reacted with a band at the predicted size of 82 kDa. CD44 protein expression was 1.9 times higher in 5xFAD compared to WT. Anti-Midkine AF7769 reacted with a band ~16 kDa and a 17.8 times greater expression in 5xFAD compared to WT. Anti-sFRP-1 ab267466 reacted with a band at 35 kDa as predicted. sFRP-1 protein expression was 11.9 times greater in 5xFAD compared to WT. Conclusions These data confirm the utility of these selective commercially available antibodies against Moesin, CD44, Midkine, and sFRP-1 for in vivo studies in mice and provide insight into the use of 5XFAD mice for in vivo target engagement studies for these target proteins.

Abstract Integration of the omics data, including metabolomics and proteomics, provides a unique opportunity to search for new associations within metabolic disorders, including Alzheimer’s disease. Using metabolomics, we have previously profiled oxylipins, endocannabinoids, bile acids, and steroids in 293 CSF and 202 matched plasma samples from AD cases and healthy controls and identified both central and peripheral markers of AD pathology within inflammation-regulating cytochrome p450/soluble epoxide hydrolase pathway. Additionally, using proteomics, we have identified five cerebrospinal fluid protein panels, involved in the regulation of energy metabolism, vasculature, myelin/oligodendrocyte, glia/inflammation, and synapses/neurons, affected in AD, and reflective of AD-related changes in the brain. In the current manuscript, using metabolomics-proteomics data integration, we describe new associations between peripheral and central lipid mediators, with the above-described CSF protein panels. Particularly strong associations were observed between cytochrome p450/soluble epoxide hydrolase metabolites, bile acids, and proteins involved in glycolysis, blood coagulation, and vascular inflammation and the regulators of extracellular matrix. Those metabolic associations were not observed at the gene-co-expression level in the central nervous system. In summary, this manuscript provides new information regarding Alzheimer’s disease, linking both central and peripheral metabolism, and illustrates the necessity for the “omics” data integration to uncover associations beyond gene co-expression.

Abstract Background Despite being twice as likely to get Alzheimer’s disease (AD), African Americans have been grossly underrepresented in AD research. While emerging evidence indicates that African Americans with AD have lower cerebrospinal fluid (CSF) levels of Tau compared to Caucasians, other differences in AD CSF biomarkers have not been fully elucidated. Here, we performed unbiased proteomic profiling of CSF from African Americans and Caucasians with and without AD to identify both common and divergent AD CSF biomarkers. Methods Multiplex tandem mass tag-based mass spectrometry (TMT-MS) quantified 1,840 proteins from 105 control and 98 AD patients of which 100 identified as Caucasian while 103 identified as African American. We used differential protein expression and co-expression approaches to assess how changes in the CSF proteome are related to race and AD. Co-expression network analysis organized the CSF proteome into 14 modules associated with brain cell-types and biological pathways. A targeted mass spectrometry method, selected reaction monitoring (SRM), with heavy labeled internal standards was used to measure a panel of CSF module proteins across a subset of African Americans and Caucasians with or without AD. A receiver operating characteristic (ROC) curve analysis assessed the performance of each protein biomarker in differentiating controls and AD by race. Results Consistent with previous findings, the increase of Tau levels in AD was greater in Caucasians than in African Americans by both immunoassay and TMT-MS measurements. CSF modules which included 14–3-3 proteins (YWHAZ and YWHAG) demonstrated equivalent disease-related elevations in both African Americans and Caucasians with AD, whereas other modules demonstrated more profound disease changes within race. Modules enriched with proteins involved with glycolysis and neuronal/cytoskeletal proteins, including Tau, were more increased in Caucasians than in African Americans with AD. In contrast, a module enriched with synaptic proteins including VGF, SCG2, and NPTX2 was significantly lower in African Americans than Caucasians with AD. Following SRM and ROC analysis, VGF, SCG2, and NPTX2 were significantly better at classifying African Americans than Caucasians with AD. Conclusions Our findings provide insight into additional protein biomarkers and pathways reflecting underlying brain pathology that are shared or differ by race.

Abstract Alzheimer’s disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT−) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT−), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT− individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD.

Cognitive impairment in the elderly features complex molecular pathophysiology extending beyond the hallmark pathologies of traditional disease classification. Molecular subtyping using large-scale -omic strategies can help resolve this biological heterogeneity. Using quantitative mass spectrometry, we measured ∼8000 proteins across >600 dorsolateral prefrontal cortex tissues with clinical diagnoses of no cognitive impairment (NCI), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia. Unbiased classification of MCI and AD cases based on individual proteomic profiles resolved three classes with expression differences across numerous cell types and biological ontologies. Two classes displayed molecular signatures atypical of AD neurodegeneration, such as elevated synaptic and decreased inflammatory markers. In one class, these atypical proteomic features were associated with clinical and pathological hallmarks of cognitive resilience. We were able to replicate these classes and their clinicopathological phenotypes across two additional tissue cohorts. These results promise to better define the molecular heterogeneity of cognitive impairment and meaningfully impact its diagnostic and therapeutic precision.

Background: A major goal of the Target Enablement to Accelerate Therapy Development for Alzheimer’s disease (TREAT-AD) program is to develop and identify high-quality tools to test target or mechanistic hypotheses. As part of this initiative, it is important that commercial reagents including research antibodies being used to interrogate drug targets have confirmed validation data in knock-out cell lines. Ideally, these antibodies should also have utility for both in vitro and in vivo studies such that the levels of target proteins in target tissues can be quantified. Methods: We evaluated commercial antibodies against TREAT-AD protein targets Moesin (Uniprot ID: P26038), CD44 (Uniprot ID: P16070), Midkine (Uniprot ID: P21741) and Secreted frizzled-related protein 1, referred to as “sFRP-1” (sFRP-1; Uniprot ID: Q8N474). Moesin, Midkine and sFRP-1, that were confirmed as selective based on data in knock-out cell lines. Western blot analysis was used to compare protein levels in brain homogenates from a mouse model with AD-relevant pathology (5XFAD) versus age-matched C57BL/6J control mice. Results: Anti-Moesin ab52490 reacted in mouse brain homogenate with a predicted molecular weight of 68 kDa. Moesin protein expression was 2.8 times higher in 5xFAD compared to WT. Anti-CD44 ab189524 reacted with a band at the predicted size of 82 kDa. CD44 protein expression was 1.9 times higher in 5xFAD compared to WT. Anti-Midkine AF7769 reacted with a band ~16 kDa and a 17.8 times greater expression in 5xFAD compared to WT. Anti-sFRP-1 ab267466 reacted with a band at 35 kDa as predicted. sFRP-1 protein expression was 11.9 times greater in 5xFAD compared to WT. Conclusions: These data confirm the utility of these selective commercially available antibodies against Moesin, CD44, Midkine, and sFRP-1 for in vivo studies in mice and provide insight into the use of 5XFAD mice for in vivo target engagement studies for these target proteins.

Abstract Robust and accessible biomarkers that can capture the heterogeneity of Alzheimer’s disease and its diverse pathological processes are urgently needed. Here, we undertook an investigation of Alzheimer’s disease cerebrospinal fluid (CSF) and plasma from the same subjects (n=18 control, n=18 AD) using three different proteomic platforms—SomaLogic SomaScan, Olink proximity extension assay, and tandem mass tag-based mass spectrometry—to assess which protein markers in these two biofluids may serve as reliable biomarkers of AD pathophysiology observed from unbiased brain proteomics studies. Median correlation of overlapping protein measurements across platforms in CSF (r~0.7) and plasma (r~0.6) was good, with more variability in plasma. The SomaScan technology provided the most measurements in plasma. Surprisingly, many proteins altered in AD CSF were found to be altered in the opposite direction in plasma, including important members of AD brain co-expression modules. An exception was SMOC1, a key member of the brain matrisome module associated with amyloid-β deposition in AD, which was found to be elevated in both CSF and plasma. Protein co-expression analysis on greater than 7000 protein measurements in CSF and 9500 protein measurements in plasma across all proteomic platforms revealed strong changes in modules related to autophagy, ubiquitination, and sugar metabolism in CSF, and endocytosis and the matrisome in plasma. Cross-platform and cross-biofluid proteomics represents a promising approach for AD biomarker development.

Studying the shared genetic etiology of disease can help improve diagnosis and treatment. Here, the authors find evidence for shared genetic and molecular pathophysiology between several common psychiatric and neurodegenerative diseases using results of 25 GWAS and large-scale human brain transcriptomic and proteomic sequencing.

Current isolation-based approaches for cell type-specific proteomics pose several challenges. Here, the authors present an approach for in vivo cell type-specific protein labeling to characterize proteomic differences between neurons and astrocytes in their native state in adult mouse brain.

Mitochondria influence cellular function through both cell-autonomous and non-cell autonomous mechanisms, such as production of paracrine and endocrine factors. Here, we demonstrate that mitochondrial regulation of the secretome is more extensive than previously appreciated, as both genetic and pharmacological disruption of the electron transport chain caused upregulation of the Alzheimer’s disease risk factor apolipoprotein E (APOE) and other secretome components. Indirect disruption of the electron transport chain by gene editing of SLC25A mitochondrial membrane transporters as well as direct genetic and pharmacological disruption of either complexes I, III, or the copper-containing complex IV of the electron transport chain elicited upregulation of APOE transcript, protein, and secretion, up to 49-fold. These APOE phenotypes were robustly expressed in diverse cell types and iPSC-derived human astrocytes as part of an inflammatory gene expression program. Moreover, age- and genotype-dependent decline in brain levels of respiratory complex I preceded an increase in APOE in the 5xFAD mouse model. We propose that mitochondria act as novel upstream regulators of APOE-dependent cellular processes in health and disease.

Abstract Alzheimer's disease (AD) drug discovery has focused on a set of highly studied therapeutic hypotheses, with limited success. The heterogeneous nature of AD processes suggests that a more diverse, systems‐integrated strategy may identify new therapeutic hypotheses. Although many target hypotheses have arisen from systems‐level modeling of human disease, in practice and for many reasons, it has proven challenging to translate them into drug discovery pipelines. First, many hypotheses implicate protein targets and/or biological mechanisms that are under‐studied, meaning there is a paucity of evidence to inform experimental strategies as well as high‐quality reagents to perform them. Second, systems‐level targets are predicted to act in concert, requiring adaptations in how we characterize new drug targets. Here we posit that the development and open distribution of high‐quality experimental reagents and informatic outputs—termed target enabling packages (TEPs)—will catalyze rapid evaluation of emerging systems‐integrated targets in AD by enabling parallel, independent, and unencumbered research.

Abstract In advancing age, some individuals maintain a stable cognitive performance over time, while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by common neurodegenerative pathologies. Hence, we aimed to identify new molecular processes underlying variation in cognitive trajectory using brain microRNA profile followed by an integrative analysis with brain transcriptome and proteome. Individual cognitive trajectories were derived from longitudinally assessed cognitive-test scores of older-adult brain donors from four longitudinal cohorts. Postmortem brain microRNA profiles, transcriptomes, and proteomes were derived from the dorsolateral prefrontal cortex. The global microRNA association study of cognitive trajectory was performed in a discovery (n = 454) and replication cohort (n = 134), followed by a meta-analysis that identified 6 microRNAs. Among these, miR-132-3p and miR-29a-3p were most significantly associated with cognitive trajectory. They explain 18.2% and 2.0% of the variance of cognitive trajectory, respectively, and act independently of the eight measured neurodegenerative pathologies. Furthermore, integrative transcriptomic and proteomic analyses revealed that miR-132-3p was significantly associated with 24 of the 47 modules of co-expressed genes of the transcriptome, miR-29a-3p with 3 modules, and identified 84 and 214 downstream targets of miR-132-3p and miR-29a-3p, respectively, in cognitive trajectory. This is the first global microRNA study of cognitive trajectory to our knowledge. We identified miR-29a-3p and miR-132-3p as novel and robust contributors to cognitive trajectory independently of the eight known cerebral pathologies. Our findings lay a foundation for future studies investigating mechanisms and developing interventions to enhance cognitive stability in advanced age.

Resources reporting RNA editing sites from brain tissue have been published. Here, the authors provide an atlas of RNA editing events found in the aged and Alzheimer’s disease human brain tissue resulting in changes at protein level.

Spatial navigation patterns in indoor space usage can reveal important cues about the cognitive health of participants. In this work, we present a low-cost, scalable, open-source edge computing system using Bluetooth low energy (BLE) beacons for tracking indoor movements in a large, 1700 m2 facility used to carry out therapeutic activities for participants with mild cognitive impairment (MCI). The facility is instrumented with 39 edge computing systems, along with an on-premise fog server. The participants carry a BLE beacon, in which BLE signals are received and analyzed by the edge computing systems. Edge computing systems are sparsely distributed in the wide, complex indoor space, challenging the standard trilateration technique for localizing subjects, which assumes a dense installation of BLE beacons. We propose a graph trilateration approach that considers the temporal density of hits from the BLE beacon to surrounding edge devices to handle the inconsistent coverage of edge devices. This proposed method helps us tackle the varying signal strength, which leads to intermittent detection of beacons. The proposed method can pinpoint the positions of multiple participants with an average error of 4.4 m and over 85% accuracy in region-level localization across the entire study area. Our experimental results, evaluated in a clinical environment, suggest that an ordinary medical facility can be transformed into a smart space that enables automatic assessment of individuals’ movements, which may reflect health status or response to treatment.

Abstract Background Alzheimer’s disease, cardiovascular disease, and other cardiometabolic disorders may share inflammatory origins. Lipid mediators, including oxylipins, endocannabinoids, bile acids, and steroids, regulate inflammation, energy metabolism, and cell proliferation with well-established involvement in cardiometabolic diseases. However, their role in Alzheimer’s disease is poorly understood. Here, we describe the analysis of plasma and cerebrospinal fluid lipid mediators in a case–control comparison of ~150 individuals with Alzheimer’s disease and ~135 healthy controls, to investigate this knowledge gap. Methods Lipid mediators were measured using targeted quantitative mass spectrometry. Data were analyzed using the analysis of covariates, adjusting for sex, age, and ethnicity. Partial least square discriminant analysis identified plasma and cerebrospinal fluid lipid mediator discriminates of Alzheimer’s disease. Alzheimer’s disease predictive models were constructed using machine learning combined with stepwise logistic regression. Results In both plasma and cerebrospinal fluid, individuals with Alzheimer’s disease had elevated cytochrome P450/soluble epoxide hydrolase pathway components and decreased fatty acid ethanolamides compared to healthy controls. Circulating metabolites of soluble epoxide hydrolase and ethanolamides provide Alzheimer’s disease predictors with areas under receiver operator characteristic curves ranging from 0.82 to 0.92 for cerebrospinal fluid and plasma metabolites, respectively. Conclusions Previous studies report Alzheimer’s disease-associated soluble epoxide hydrolase upregulation in the brain and that endocannabinoid metabolism provides an adaptive response to neuroinflammation. This study supports the involvement of P450-dependent and endocannabinoid metabolism in Alzheimer’s disease. The results further suggest that combined pharmacological intervention targeting both metabolic pathways may have therapeutic benefits for Alzheimer’s disease.

While hippocampal atrophy and its regional susceptibility to Alzheimer’s disease (AD) are well reported at late stages of AD, studies of the asymptomatic stage of AD are limited but could elucidate early stage pathophysiology as well as provide predictive biomarkers. In this study, we performed multi-modal magnetic resonance imaging (MRI) to estimate morphometry, functional connectivity, and tissue microstructure of hippocampal subfields in cognitively normal adults including those with asymptomatic AD. High-resolution resting-state functional, diffusion and structural MRI, cerebral spinal fluid (CSF), and neuropsychological evaluations were performed in healthy young adults (HY: n = 40) and healthy older adults with negative (HO−: n = 47) and positive (HO+ : n = 25) CSF biomarkers of AD. Morphometry, functional connectivity, and tissue microstructure were estimated from the structural, functional, and diffusion MRI images, respectively. Our results indicated that normal aging affected morphometry, connectivity, and microstructure in all hippocampal subfields, while the subiculum and CA1-3 demonstrated the greatest sensitivity to asymptomatic AD pathology. Tau, rather than amyloid-β, was closely associated with imaging-derived synaptic and microstructural measures. Microstructural metrics were significantly associated with neuropsychological assessments. These findings suggest that the subiculum and CA1-3 are the most vulnerable in asymptomatic AD and tau level is driving these early changes.

Haque et al. demonstrate that the episodic memory of a single visual scene is sufficient for humans to recognize if a visual scene has subsequently changed. A prediction error signal first arises in the visual association cortex when individuals recognize these changes.

To investigate the molecular foundation of sporadic Alzheimer’s disease (AD), Beckmann et al. constructed multiscale causal networks on a large human AD multi-omics dataset, detecting AD-associated networks and their top predicted regulator, VGF, with extensive validation in the 5xFAD mouse model.

Abstract Background Proteomic characterization of microglia provides the most proximate assessment of functionally relevant molecular mechanisms of neuroinflammation. However, microglial proteomics studies have been limited by low cellular yield and contamination by non-microglial proteins using existing enrichment strategies. Methods We coupled magnetic-activated cell sorting (MACS) and fluorescence activated cell sorting (FACS) of microglia with tandem mass tag-mass spectrometry (TMT-MS) to obtain a highly-pure microglial proteome and identified a core set of highly-abundant microglial proteins in adult mouse brain. We interrogated existing human proteomic data for Alzheimer’s disease (AD) relevance of highly-abundant microglial proteins and performed immuno-histochemical and in-vitro validation studies. Results Quantitative multiplexed proteomics by TMT-MS of CD11b + MACS-enriched (N = 5 mice) and FACS-isolated (N = 5 mice), from adult wild-type mice, identified 1791 proteins. A total of 203 proteins were highly abundant in both datasets, representing a core-set of highly abundant microglial proteins. In addition, we found 953 differentially enriched proteins comparing MACS and FACS-based approaches, indicating significant differences between both strategies. The FACS-isolated microglia proteome was enriched with cytosolic, endoplasmic reticulum, and ribosomal proteins involved in protein metabolism and immune system functions, as well as an abundance of canonical microglial proteins. Conversely, the MACS-enriched microglia proteome was enriched with mitochondrial and synaptic proteins and higher abundance of neuronal, oligodendrocytic and astrocytic proteins. From the 203 consensus microglial proteins with high abundance in both datasets, we confirmed microglial expression of moesin (Msn) in wild-type and 5xFAD mouse brains as well as in human AD brains. Msn expression is nearly exclusively found in microglia that surround Aβ plaques in 5xFAD brains. In in-vitro primary microglial studies, Msn silencing by siRNA decreased Aβ phagocytosis and increased lipopolysaccharide-induced production of the pro-inflammatory cytokine, tumor necrosis factor (TNF). In network analysis of human brain proteomic data, Msn was a hub protein of an inflammatory co-expression module positively associated with AD neuropathological features and cognitive dysfunction. Conclusions Using FACS coupled with TMT-MS as the method of choice for microglial proteomics, we define a core set of highly-abundant adult microglial proteins. Among these, we validate Msn as highly-abundant in plaque-associated microglia with relevance to human AD.

PurposeTo assess the pathological aging effect on caudate functional connectivity among mild cognitive impairment (MCI) participants and examine whether and how sex and amyloid contribute to this process.Materials and MethodsTwo hundred and seventy-seven functional magnetic resonance imaging (fMRI) sessions from 163 cognitive normal (CN) older adults and 309 sessions from 139 participants with MCI were included as the main sample in our analysis. Pearson's correlation was used to characterize the functional connectivity (FC) between caudate nuclei and each brain region, then caudate nodal strength was computed to quantify the overall caudate FC strength. Association analysis between caudate nodal strength and age was carried out in MCI and CN separately using linear mixed effect (LME) model with covariates (education, handedness, sex, Apolipoprotein E4, and intra-subject effect). Analysis of covariance was conducted to investigate sex, amyloid status, and their interaction effects on aging with the fMRI data subset having amyloid status available. LME model was applied to women and men separately within MCI group to evaluate aging effects on caudate nodal strength and each region's connectivity with caudate nuclei. We then evaluated the roles of sex and amyloid status in the associations of neuropsychological scores with age or caudate nodal strength. An independent cohort was used to validate the sex-dependent aging effects in MCI.ResultsThe MCI group had significantly stronger age-related increase of caudate nodal strength compared to the CN group. Analyzing women and men separately revealed that the aging effect on caudate nodal strength among MCI participants was significant only for women (left: P = 6.23 × 10−7, right: P = 3.37 × 10−8), but not for men (P > 0.3 for bilateral caudate nuclei). The aging effects on caudate nodal strength were not significantly mediated by brain amyloid burden. Caudate connectivity with ventral prefrontal cortex substantially contributed to the aging effect on caudate nodal strength in women with MCI. Higher caudate nodal strength is significantly related to worse cognitive performance in women but not in men with MCI.ConclusionSex modulates the pathological aging effects on caudate nodal strength in MCI regardless of amyloid status. Caudate nodal strength may be a sensitive biomarker of pathological aging in women with MCI.

Differences in expressing facial emotions are broadly observed in people with cognitive impairment. However, these differences have been difficult to objectively quantify and systematically evaluate among people with cognitive impairment across disease etiologies and severity. Therefore, a computer vision-based deep learning model for facial emotion recognition trained on 400.000 faces was utilized to analyze facial emotions expressed during a passive viewing memory test. In addition, this study was conducted on a large number of individuals (n = 493), including healthy controls and individuals with cognitive impairment due to diverse underlying etiologies and across different disease stages. Diagnoses included subjective cognitive impairment, Mild Cognitive Impairment (MCI) due to AD, MCI due to other etiologies, dementia due to Alzheimer’s diseases (AD), and dementia due to other etiologies (e.g., Vascular Dementia, Frontotemporal Dementia, Lewy Body Dementia, etc.). The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance across all participants. A participant with a score of less than or equal to 24 was considered cognitively impaired (CI). Compared to cognitively unimpaired (CU) participants, CI participants expressed significantly less positive emotions, more negative emotions, and higher facial expressiveness during the test. In addition, classification analysis revealed that facial emotions expressed during the test allowed effective differentiation of CI from CU participants, largely independent of sex, race, age, education level, mood, and eye movements (derived from an eye-tracking-based digital biomarker for cognitive impairment). No screening methods reliably differentiated the underlying etiology of the cognitive impairment. The findings provide quantitative and comprehensive evidence that the expression of facial emotions is significantly different in people with cognitive impairment, and suggests this may be a useful tool for passive screening of cognitive impairment.

Vast numbers of differentially expressed genes and perturbed networks have been identified in Alzheimer’s disease (AD), however, neither disease nor brain region specificity of these transcriptome alterations has been explored. Using RNA-Seq data from 231 temporal cortex and 224 cerebellum samples from patients with AD and progressive supranuclear palsy (PSP), a tauopathy, we identified a striking correlation in the directionality and magnitude of gene expression changes between these 2 neurodegenerative proteinopathies. Further, the transcriptomic changes in AD and PSP brains ware highly conserved between the temporal and cerebellar cortices, indicating that highly similar transcriptional changes occur in pathologically affected and grossly less affected, albeit functionally connected, areas of the brain. Shared up- or downregulated genes in AD and PSP are enriched in biological pathways. Many of these genes also have concordant protein changes and evidence of epigenetic control. These conserved transcriptomic alterations of 2 distinct proteinopathies in brain regions with and without significant gross neuropathology have broad implications. AD and other neurodegenerative diseases are likely characterized by common disease or compensatory pathways with widespread perturbations in the whole brain. These findings can be leveraged to develop multifaceted therapies and biomarkers that address these common, complex, and ubiquitous molecular alterations in neurodegenerative diseases.

With the ultimate goal of developing a more representative animal model of Alzheimer's disease (AD), two female amyloid-β-(Aβ) precursor protein-transgenic (APPtg) rhesus monkeys were generated by lentiviral transduction of the APP gene into rhesus oocytes, followed by in vitro fertilization and embryo transfer. The APP-transgene included the AD-associated Swedish K670N/M671L and Indiana V717F mutations (APPSWE/IND) regulated by the human polyubiquitin-C promoter. Overexpression of APP was confirmed in lymphocytes and brain tissue. Upon sacrifice at 10 years of age, one of the monkeys had developed Aβ plaques and cerebral Aβ-amyloid angiopathy in the occipital, parietal, and caudal temporal neocortices. The induction of Aβ deposition more than a decade prior to its usual emergence in the rhesus monkey supports the feasibility of creating a transgenic nonhuman primate model for mechanistic analyses and preclinical testing of treatments for Alzheimer's disease and cerebrovascular amyloidosis.

Developing an in vitro blood-brain-barrier (BBB) model that reproduces the organ’s complex structure and function is an open challenge. Here the authors present a BBB-on-a-chip that includes endothelial cells, pericytes and a 3D astrocytic network which resembles the morphology and function of astrocytes in the BBB in vivo.

Cognitive abilities tend to decline over time in advanced age, yet some individuals experience stable abilities or rapid decline. Here the authors present a proteome-wide association study of cognitive trajectory, and identify 38 proteins associated with cognitive resilience.

Core spliceosome and related RNA-binding proteins aggregate in Alzheimer’s disease (AD) brain even in early asymptomatic stages (AsymAD) of disease. To assess the specificity of RNA-binding protein aggregation in AD, we developed a targeted mass spectrometry approach to quantify broad classes of RNA-binding proteins with other pathological proteins including tau and amyloid beta (Aβ) in detergent insoluble fractions from control, AsymAD, AD and Parkinson’s disease (PD) brain. Relative levels of specific insoluble RNA-binding proteins across different disease groups correlated with accumulation of Aβ and tau aggregates. RNA-binding proteins, including splicing factors with homology to the basic-acidic dipeptide repeats of U1-70K, preferentially aggregated in AsymAD and AD. In contrast, PD brain aggregates were relatively depleted of many RNA-binding proteins compared to AsymAD and AD groups. Correlation network analyses resolved 29 distinct modules of co-aggregating proteins including modules linked to spliceosome assembly, nuclear speckles and RNA splicing. Modules related to spliceosome assembly and nuclear speckles showed stage-specific enrichment of insoluble RBPs from AsymAD and AD brains, whereas the RNA splicing module was reduced specifically in PD. Collectively, this work identifies classes of RNA-binding proteins that distinctly co-aggregate in detergent-insoluble fractions across the specific neurodegenerative diseases we examined.

Abstract Introduction We and collaborators discovered that flickering lights and sound at gamma frequency (40 Hz) reduce Alzheimer's disease (AD) pathology and alter immune cells and signaling in mice. To determine the feasibility of this intervention in humans we tested the safety, tolerability, and daily adherence to extended audiovisual gamma flicker stimulation. Methods Ten patients with mild cognitive impairment due to underlying AD received 1‐hour daily gamma flicker using audiovisual stimulation for 4 or 8 weeks at home with a delayed start design. Results Gamma flicker was safe, tolerable, and adherable. Participants’ neural activity entrained to stimulation. Magnetic resonance imaging and cerebral spinal fluid proteomics show preliminary evidence that prolonged flicker affects neural networks and immune factors in the nervous system. Discussion These findings show that prolonged gamma sensory flicker is safe, tolerable, and feasible with preliminary indications of immune and network effects, supporting further study of gamma stimulation in AD.

Summary: We present a consensus atlas of the human brain transcriptome in Alzheimer’s disease (AD), based on meta-analysis of differential gene expression in 2,114 postmortem samples. We discover 30 brain coexpression modules from seven regions as the major source of AD transcriptional perturbations. We next examine overlap with 251 brain differentially expressed gene sets from mouse models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus tau pathology and reveal age- and sex-dependent expression signatures for disease progression. Human coexpression modules enriched for neuronal and/or microglial genes broadly overlap with mouse models of AD, Huntington’s disease, amyotrophic lateral sclerosis, and aging. Other human coexpression modules, including those implicated in proteostasis, are not activated in AD models but rather following other, unexpected genetic manipulations. Our results comprise a cross-species resource, highlighting transcriptional networks altered by human brain pathophysiology and identifying correspondences with mouse models for AD preclinical studies.

Abstract Background The complicated cellular and biochemical changes that occur in brain during Alzheimer’s disease are poorly understood. In a previous study we used an unbiased label-free quantitative mass spectrometry-based proteomic approach to analyze these changes at a systems level in post-mortem cortical tissue from patients with Alzheimer’s disease (AD), asymptomatic Alzheimer’s disease (AsymAD), and controls. We found modules of co-expressed proteins that correlated with AD phenotypes, some of which were enriched in proteins identified as risk factors for AD by genetic studies. Methods The amount of information that can be obtained from such systems-level proteomic analyses is critically dependent upon the number of proteins that can be quantified across a cohort. We report here a new proteomic systems-level analysis of AD brain based on 6,533 proteins measured across AD, AsymAD, and controls using an analysis pipeline consisting of isobaric tandem mass tag (TMT) mass spectrometry and offline prefractionation. Results Our new TMT pipeline allowed us to more than double the depth of brain proteome coverage. This increased depth of coverage greatly expanded the brain protein network to reveal new protein modules that correlated with disease and were unrelated to those identified in our previous network. Differential protein abundance analysis identified 350 proteins that had altered levels between AsymAD and AD not caused by changes in specific cell type abundance, potentially reflecting biochemical changes that are associated with cognitive decline in AD. RNA binding proteins emerged as a class of proteins altered between AsymAD and AD, and were enriched in network modules that correlated with AD pathology. We developed a proteogenomic approach to investigate RNA splicing events that may be altered by RNA binding protein changes in AD. The increased proteome depth afforded by our TMT pipeline allowed us to identify and quantify a large number of alternatively spliced protein isoforms in brain, including AD risk factors such as BIN1, PICALM, PTK2B, and FERMT2. Many of the new AD protein network modules were enriched in alternatively spliced proteins and correlated with molecular markers of AD pathology and cognition. Conclusions Further analysis of the AD brain proteome will continue to yield new insights into the biological basis of AD.

Abstract Background Microglia are innate immune cells of the brain that perform phagocytic and inflammatory functions in disease conditions. Transcriptomic studies of acutely-isolated microglia have provided novel insights into their molecular and functional diversity in homeostatic and neurodegenerative disease states. State-of-the-art mass spectrometry methods can comprehensively characterize proteomic alterations in microglia in neurodegenerative disorders, potentially providing novel functionally relevant molecular insights that are not provided by transcriptomics. However, comprehensive proteomic profiling of adult primary microglia in neurodegenerative disease conditions has not been performed. Methods We performed quantitative mass spectrometry based proteomic analyses of purified CD11b+ acutely-isolated microglia from adult (6 mo) mice in normal, acute neuroinflammatory (LPS-treatment) and chronic neurodegenerative states (5xFAD model of Alzheimer’s disease [AD]). Differential expression analyses were performed to characterize specific microglial proteomic changes in 5xFAD mice and identify overlap with LPS-induced pro-inflammatory changes. Our results were also contrasted with existing proteomic data from wild-type mouse microglia and from existing microglial transcriptomic data from wild-type and 5xFAD mice. Neuropathological validation studies of select proteins were performed in human AD and 5xFAD brains. Results Of 4133 proteins identified, 187 microglial proteins were differentially expressed in the 5xFAD mouse model of AD pathology, including proteins with previously known (Apoe, Clu and Htra1) as well as previously unreported relevance to AD biology (Cotl1 and Hexb). Proteins upregulated in 5xFAD microglia shared significant overlap with pro-inflammatory changes observed in LPS-treated mice. Several proteins increased in human AD brain were also upregulated by 5xFAD microglia (Aβ peptide, Apoe, Htra1, Cotl1 and Clu). Cotl1 was identified as a novel microglia-specific marker with increased expression and strong association with AD neuropathology. Apoe protein was also detected within plaque-associated microglia in which Apoe and Aβ were highly co-localized, suggesting a role for Apoe in phagocytic clearance of Aβ. Conclusions We report a comprehensive proteomic study of adult mouse microglia derived from acute neuroinflammation and AD models, representing a valuable resource to the neuroscience research community. We highlight shared and unique microglial proteomic changes in acute neuroinflammation aging and AD mouse models and identify novel roles for microglial proteins in human neurodegeneration.

Abstract Background Disease-associated-microglia (DAM) represent transcriptionally-distinct and neurodegeneration-specific microglial profiles with unclear significance in Alzheimer’s disease (AD). An understanding of heterogeneity within DAM and their key regulators may guide pre-clinical experimentation and drug discovery. Methods Weighted co-expression network analysis (WGCNA) was applied to existing microglial transcriptomic datasets from neuroinflammatory and neurodegenerative disease mouse models to identify modules of highly co-expressed genes. These modules were contrasted with known signatures of homeostatic microglia and DAM to reveal novel molecular heterogeneity within DAM. Flow cytometric validation studies were performed to confirm existence of distinct DAM sub-populations in AD mouse models predicted by WGCNA. Gene ontology analyses coupled with bioinformatics approaches revealed drug targets and transcriptional regulators of microglial modules predicted to favorably modulate neuroinflammation in AD. These guided in-vivo and in-vitro studies in mouse models of neuroinflammation and neurodegeneration (5xFAD) to determine whether inhibition of pro-inflammatory gene expression and promotion of amyloid clearance was feasible. We determined the human relevance of these findings by integrating our results with AD genome-wide association studies and human AD and non-disease post-mortem brain proteomes. Results WGCNA applied to microglial gene expression data revealed a transcriptomic framework of microglial activation that predicted distinct pro-inflammatory and anti-inflammatory phenotypes within DAM, which we confirmed in AD and aging models by flow cytometry. Pro-inflammatory DAM emerged earlier in mouse models of AD and were characterized by pro-inflammatory genes (Tlr2, Ptgs2, Il12b, Il1b), surface marker CD44, potassium channel Kv1.3 and regulators (NFkb, Stat1, RelA) while anti-inflammatory DAM expressed phagocytic genes (Igf1, Apoe, Myo1e), surface marker CXCR4 with distinct regulators (LXRα/β, Atf1). As neuro-immunomodulatory strategies, we validated LXRα/β agonism and Kv1.3 blockade by ShK-223 peptide that promoted anti-inflammatory DAM, inhibited pro-inflammatory DAM and augmented Aβ clearance in AD models. Human AD-risk genes were highly represented within homeostatic microglia suggesting causal roles for early microglial dysregulation in AD. Pro-inflammatory DAM proteins were positively associated with neuropathology and preceded cognitive decline confirming the therapeutic relevance of inhibiting pro-inflammatory DAM in AD. Conclusions We provide a predictive transcriptomic framework of microglial activation in neurodegeneration that can guide pre-clinical studies to characterize and therapeutically modulate neuroinflammation in AD.