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.
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.
Background
We recently identified U1 small nuclear ribonucleoprotein (snRNP) tangle-like aggregates and RNA splicing abnormalities in sporadic Alzheimer’s disease (AD). However little is known about snRNP biology in early onset AD due to autosomal dominant genetic mutations or trisomy 21 in Down syndrome. Therefore we investigated snRNP biochemical and pathologic features in these disorders.
Findings
We performed quantitative proteomics and immunohistochemistry in postmortem brain from genetic AD cases. Electron microscopy was used to characterize ultrastructural features of pathologic aggregates. U1-70k and other snRNPs were biochemically enriched in the insoluble fraction of human brain from subjects with presenilin 1 (PS1) mutations. Aggregates of U1 snRNP-immunoreactivity formed cytoplasmic tangle-like structures in cortex of AD subjects with PS1 and amyloid precursor protein (APP) mutations as well as trisomy 21. Ultrastructural analysis with electron microscopy in an APP mutation case demonstrated snRNP immunogold labeling of paired helical filaments (PHF).
Conclusions
These studies identify U1 snRNP pathologic changes in brain of early onset genetic forms of AD. Since dominant genetic mutations and trisomy 21 result in dysfunctional amyloid processing, the findings suggest that aberrant β-amyloid processing may influence U1 snRNP aggregate formation.
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.
Despite a key role of amyloid-beta (Aβ) in Alzheimer's disease (AD), mechanisms that link Aβ plaques to tau neurofibrillary tangles and cognitive decline still remain poorly understood. The purpose of this study was to quantify proteins in the sarkosyl-insoluble brain proteome correlated with Aβ and tau insolubility in the asymptomatic phase of AD (AsymAD) and through mild cognitive impairment (MCI) and symptomatic AD. Employing label-free mass spectrometry-based proteomics, we quantified 2711 sarkosyl-insoluble proteins across the prefrontal cortex from 35 individual cases representing control, AsymAD, MCI and AD. Significant enrichment of Aβ and tau in AD was observed, which correlated with neuropathological measurements of plaque and tau tangle density, respectively. Pairwise correlation coefficients were also determined for all quantified proteins to Aβ and tau, across the 35 cases. Notably, six of the ten most correlated proteins to Aβ were U1 small nuclear ribonucleoproteins (U1 snRNPs). Three of these U1 snRNPs (U1A, SmD and U1-70K) also correlated with tau consistent with their association with tangle pathology in AD. Thus, proteins that cross-correlate with both Aβ and tau, including specific U1 snRNPs, may have potential mechanistic roles in linking Aβ plaques to tau tangle pathology during AD progression.
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.
Frontotemporal lobar degeneration (FTLD) is the most common cause of dementia with pre-senile onset, accounting for as many as 20% of cases. A common subset of FTLD cases is characterized by the presence of ubiquitinated inclusions in vulnerable neurons (FTLD-U). While the pathophysiological mechanisms underlying neurodegeneration in FTLD-U have not yet been elucidated, the presence of inclusions in this disease indicates enhanced aggregation of one or several proteins. Moreover, these inclusions suggest altered expression, processing, or degradation of proteins during FTLD-U pathogenesis. Thus, one approach to understanding disease mechanisms is to delineate the molecular changes in protein composition in FTLD-U brain. Using a combined approach consisting of laser capture microdissection (LCM) and high-resolution liquid chromatography-tandem mass spectrometry (LC–MS/MS), we identified 1252 proteins in hippocampal dentate granule cells excised from three post-mortem FTLD-U and three unaffected control cases processed in parallel. Additionally, we employed a labeling-free quantification technique to compare the abundance of the identified proteins between FTLD-U and control cases. Quantification revealed 54 proteins with selective enrichment in FTLD-U, including TAR–DNA binding protein 43 (TDP-43), a recently identified component of ubiquitinated inclusions. Moreover, 19 proteins were selectively decreased in FTLD-U. Subsequent immunohistochemical analysis of TDP-43 and three additional protein candidates suggests that our proteomic profiling of FTLD-U dentate granule cells reveals both inclusion-associated proteins and non-aggregated disease-specific proteins. Application of LCM is a valuable tool in the molecular analysis of complex tissues, and its application in the proteomic characterization of neurodegenerative disorders such as FTLD-U may be used to identify proteins altered in disease.
by
Andrew T. McKenzie;
Sarah Moyon;
Minghui Wang;
Igor Katsyv;
Won-Min Song;
Xianxiao Zhou;
Eric B Dammer;
Duc M. Duong;
Joshua Aaker;
Yongzhong Zhao;
Noam Beckmann;
Pei Wang;
Jun Zhu;
James J Lah;
Nicholas Seyfried;
Allan I Levey;
Pavel Katsel;
Vahram Haroutunian;
Eric E. Schadt;
Brian Popko;
Patrizia Casaccia;
Bin Zhang
Background: Oligodendrocytes (OLs) and myelin are critical for normal brain function and have been implicated in neurodegeneration. Several lines of evidence including neuroimaging and neuropathological data suggest that Alzheimer's disease (AD) may be associated with dysmyelination and a breakdown of OL-axon communication.
Methods: In order to understand this phenomenon on a molecular level, we systematically interrogated OL-enriched gene networks constructed from large-scale genomic, transcriptomic and proteomic data obtained from human AD postmortem brain samples. We then validated these networks using gene expression datasets generated from mice with ablation of major gene expression nodes identified in our AD-dysregulated networks.
Results: The robust OL gene coexpression networks that we identified were highly enriched for genes associated with AD risk variants, such as BIN1 and demonstrated strong dysregulation in AD. We further corroborated the structure of the corresponding gene causal networks using datasets generated from the brain of mice with ablation of key network drivers, such as UGT8, CNP and PLP1, which were identified from human AD brain data. Further, we found that mice with genetic ablations of Cnp mimicked aspects of myelin and mitochondrial gene expression dysregulation seen in brain samples from patients with AD, including decreased protein expression of BIN1 and GOT2.
Conclusions: This study provides a molecular blueprint of the dysregulation of gene expression networks of OL in AD and identifies key OL- and myelination-related genes and networks that are highly associated with AD.
Here we report proteomic analyses of 129 human cortical tissues to define changes associated with the asymptomatic and symptomatic stages of Alzheimer's disease (AD). Network analysis revealed 16 modules of co-expressed proteins, 10 of which correlated with AD phenotypes. A subset of modules overlapped with RNA co-expression networks, including those associated with neurons and astroglial cell types, showing altered expression in AD, even in the asymptomatic stages. Overlap of RNA and protein networks was otherwise modest, with many modules specific to the proteome, including those linked to microtubule function and inflammation. Proteomic modules were validated in an independent cohort, demonstrating some module expression changes unique to AD and several observed in other neurodegenerative diseases. AD genetic risk loci were concentrated in glial-related modules in the proteome and transcriptome, consistent with their causal role in AD. This multi-network analysis reveals protein- and disease-specific pathways involved in the etiology, initiation, and progression of AD.
by
Bing Bai;
Chad Hales;
Ping-Chung Chen;
Yair Gozal;
Eric B Dammer;
Jason Jon Fritz;
Xusheng Wang;
Qiangwei Xia;
Duc Duong;
Craig Street;
Gloria Cantero;
Dongmei Cheng;
Drew R. Jones;
Zhiping Wu;
Yuxin Li;
Ian Diner;
Craig Heilman;
Howard D Rees III;
Hao Wu;
Li Lin;
Keith E. Szulwach;
Marla Gearing;
Elliott J. Mufson;
David A. Bennett;
Thomas J. Montine;
Nicholas Seyfried;
Thomas Wingo;
Yi E. Sun;
Peng Jin;
John Hanfelt;
Donna M. Willcock;
Allan I Levey;
James J Lah;
Junmin Peng
Deposition of insoluble protein aggregates is a hallmark of neurodegenerative diseases. The universal presence of β-amyloid and tau in Alzheimer’s disease (AD) has facilitated advancement of the amyloid cascade and tau hypotheses that have dominated AD pathogenesis research and therapeutic development. However, the underlying etiology of the disease remains to be fully elucidated. Here we report a comprehensive study of the human brain-insoluble proteome in AD by mass spectrometry. We identify 4,216 proteins, among which 36 proteins accumulate in the disease, including U1-70K and other U1 small nuclear ribonucleoprotein (U1 snRNP) spliceosome components. Similar accumulations in mild cognitive impairment cases indicate that spliceosome changes occur in early stages of AD. Multiple U1 snRNP subunits form cytoplasmic tangle-like structures in AD but not in other examined neurodegenerative disorders, including Parkinson disease and frontotemporal lobar degeneration. Comparison of RNA from AD and control brains reveals dysregulated RNA processing with accumulation of unspliced RNA species in AD, including myc box-dependent-interacting protein 1, clusterin, and presenilin-1. U1-70K knockdown or antisense oligonucleotide inhibition of U1 snRNP increases the protein level of amyloid precursor protein. Thus, our results demonstrate unique U1 snRNP pathology and implicate abnormal RNA splicing in AD pathogenesis.