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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.

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.

In advanced age, some individuals maintain a stable cognitive trajectory while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by traditional neurodegenerative pathologies. Hence, to identify new processes underlying variation in cognitive trajectory, we perform an unbiased proteome-wide association study of cognitive trajectory in a discovery ( n  = 104) and replication cohort ( n  = 39) of initially cognitively unimpaired, longitudinally assessed older-adult brain donors. We find 579 proteins associated with cognitive trajectory after meta-analysis. Notably, we present evidence for increased neuronal mitochondrial activities in cognitive stability regardless of the burden of traditional neuropathologies. Furthermore, we provide additional evidence for increased synaptic abundance and decreased inflammation and apoptosis in cognitive stability. Importantly, we nominate proteins associated with cognitive trajectory, particularly the 38 proteins that act independently of neuropathologies and are also hub proteins of protein co-expression networks, as promising targets for future mechanistic studies of cognitive trajectory. 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.

Depression is a common condition, but current treatments are only effective in a subset of individuals. To identify new treatment targets, we integrated depression genome-wide association study (GWAS) results ( N  = 500,199) with human brain proteomes ( N  = 376) to perform a proteome-wide association study of depression followed by Mendelian randomization. We identified 19 genes that were consistent with being causal in depression, acting via their respective cis -regulated brain protein abundance. We replicated nine of these genes using an independent depression GWAS ( N  = 307,353) and another human brain proteomic dataset ( N  = 152). Eleven of the 19 genes also had cis -regulated mRNA levels that were associated with depression, based on integration of the depression GWAS with human brain transcriptomes ( N  = 888). Meta-analysis of the discovery and replication proteome-wide association study analyses identified 25 brain proteins consistent with being causal in depression, 20 of which were not previously implicated in depression by GWAS. Together, these findings provide promising brain protein targets for further mechanistic and therapeutic studies. Wingo et al. integrate depression GWAS results with human brain proteomes to perform proteome-wide association studies followed by Mendelian randomization. They identify 25 proteins as potential causal mediators of depression, of which 20 are new.

Cerebral atherosclerosis contributes to dementia via unclear processes. We performed proteomic sequencing of dorsolateral prefrontal cortex in 438 older individuals and found associations between cerebral atherosclerosis and reduced synaptic signaling and RNA splicing and increased oligodendrocyte development and myelination. Consistently, single-cell RNA sequencing showed cerebral atherosclerosis associated with higher oligodendrocyte abundance. A subset of proteins and modules associated with cerebral atherosclerosis was also associated with Alzheimer’s disease, suggesting shared mechanisms.Proteome-wide association studies of brain samples from older adults revealed effects of cerebral atherosclerosis and Alzheimer’s disease. A subset of proteins and protein co-expression modules were associated with both, suggesting shared mechanisms.

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.

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.

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.

Stacy Steinberg, Hreinn Stefansson, Thorlakur Jonsson and colleagues found that rare variants predicted to alter the function of ABCA7 are associated with risk of Alzheimer's disease. The association was found in Iceland and replicated in northern Europe and the United States. We conducted a search for rare, functional variants altering susceptibility to Alzheimer's disease that exploited knowledge of common variants associated with the same disease. We found that loss-of-function variants in ABCA7 confer risk of Alzheimer's disease in Icelanders (odds ratio (OR) = 2.12, P = 2.2 × 10 −13 ) and discovered that the association replicated in study groups from Europe and the United States (combined OR = 2.03, P = 6.8 × 10 −15 ).

INTRODUCTION Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within non‐Hispanic White (NHW) populations. Here we provide an extensive survey of the proteomic landscape of AD across diverse racial/ethnic groups. METHODS Two cortical regions, from multiple centers, were harmonized by uniform neuropathological diagnosis. Among 998 unique donors, 273 donors self‐identified as African American, 229 as Latino American, and 434 as NHW. RESULTS While amyloid precursor protein and the microtubule‐associated protein tau demonstrated higher abundance in AD brains, no significant race‐related differences were observed. Further proteome‐wide and focused analyses (specific amyloid beta [Aβ] species and the tau domains) supported the absence of racial differences in these AD pathologies within the brain proteome. DISCUSSION Our findings indicate that the racial differences in AD risk and clinical presentation are not underpinned by dramatically divergent patterns in the brain proteome, suggesting that other determinants account for these clinical disparities. Highlights We present a large‐scale proteome (∼10,000 proteins) of DLPFC (998) and STG (244) across AD cases. About 50% of samples were from racially and ethnically diverse brain donors. Key AD proteins (amyloid and tau) correlated with CERAD and Braak stages. No significant race‐related differences in amyloid and tau protein levels were observed in AD brains. AD‐associated protein changes showed a strong correlation between the brain proteomes of African American and White individuals. This dataset advances understanding of ethnoracial‐specific AD pathways and potential therapies.