Biology subjects

Haroutunian, V.

Publications and source records attributed to Haroutunian, V..

At least 19 recordsLinked to original sources

bioRxiv2026

A Multi-Omics Study of Cognitive Resilience to Alzheimer's Disease

Alzheimers disease (AD) is the most severe form of dementia. While significant efforts have been made to identify AD risk factors and develop therapeutics, much less attention has been given to neurobiological factors and molecular signatures associated with cognitive resilience. Substantial evidence suggests that modifiable factors, such as physical and mental activity, may contribute to cognitive reserve and resilience. To this end, we developed a resilient cohort of paired genetics, transcriptomics and proteomics data from the prefrontal cortex of 282 cognitively normal older adults. We conducted extensive preprocessing and rigorous quality control (QC), including QC on sequence metrics and sample matching across multiomics. This cohort can be leveraged for identification of molecular signatures of cognitive resilience to AD and is freely shared with the research community.

genomics↗

bioRxiv2024

Large- Scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity

AbstractO_ST_ABSIntroductionC_ST_ABSAlzheimers disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups. MethodsDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS). ResultsAs a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals. DiscussionThis comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

neuroscience↗

bioRxiv2024

Bridging the Gap: Multi-Omics Profiling of Brain Tissue in Alzheimer's Disease and Older Controls in Multi-Ethnic Populations

INTRODUCTIONMulti-omics studies in Alzheimers disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked African Americans (AA) and Latin Americans (LA), who are disproportionately affected by AD. METHODSTo bridge this gap, Accelerating Medicines Partnership in AD (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors. RESULTSWe generated multi-omics data and curated and harmonized phenotypic data from AA (n=306), LA (n=326), or AA and LA (n=4) brain donors plus Non-Hispanic White (n=252) and other (n=20) ethnic groups, to establish a foundational dataset enriched for AA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSIONInclusion of traditionally underrepresented groups in multi-omics studies is essential to discover the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD.

neuroscience↗

bioRxiv2024

Human brain aging heterogeneity observed from multi-region omics data reveals a subtype closely related to Alzheimer's disease

INTRODUCTION: The interconnection between brain aging and Alzheimers disease (AD) remain to be elucidated. METHODS: We investigated multi-omics (transcriptomics and proteomics) data from multiple brain regions (i.e., the hippocampus (HIPP), prefrontal cortex (PFC), and cerebellum (CRBL)) in cognitively normal individuals. RESULTS: We found that brain samples could be divided into ADL (AD-like) and NL (normal) subtypes which were correlated across brain regions. The differentially expressed genes in the ADL samples highly overlapped with AD gene signatures and the changes were consistent across brain regions (PFC and HIPP) in the multi-omics data. Intriguingly, the ADL subtype in PFC showed more differentially expressed genes than other brain regions, which could be explained by the baseline gene expression differences in the PFC NL samples. DISCUSSION: We conclude that brain aging heterogeneity widely exists, and our findings corroborate with the hypothesis that AD-related changes occur decades before the clinical manifestation of cognitive impairment in a sub-population.

neuroscience↗

bioRxiv2023

A Scalable High Throughput Fully Automated Pipeline for the Quantification of Amyloid Pathology in Alzheimer's Disease Using Deep Learning Algorithms

The most common approach to characterize neuropathology in Alzheimers disease (AD) involves a manual survey and inspection by an expert neuropathologist of postmortem tissue that has been immunolabeled to visualize the presence of amyloid {beta} in plaques and around blood vessels and neurofibrillary tangles of the tau protein. In the case of amyloid {beta} pathology, a semiquantitative score is given that is based on areas of densest pathology. The approach has been well-validated but the process is laborious and time consuming, and inherently susceptible to intra- and inter-observer variability. Moreover, the tremendous growth in genetic, transcriptomic and proteomic data from AD patients has created new opportunities to link clinical features of AD to molecular pathogenesis through pathology, but the lack of high throughput quantitative and comprehensive approaches to assess neuropathology limits the associations that can be discovered. To address these limitations, we designed a computational pipeline to analyze postmortem tissue from AD patients in a fully automated, unbiased and high throughput manner. We used deep learning to train algorithms with a Mask Regional-Convolutional Neural Network to detect and classify different types of amyloid pathology with human level accuracy. After training on pathology slides from a Mt Sinai cohort, our algorithms identified amyloid pathology in samples made at an independent brain bank and from an unrelated cohort of patients, indicating that the algorithms were detecting reproducible and generalizable pathology features. We designed the pipeline to retain the position of the pathology it detects, making it possible to reconstruct a map of pathology across the entire whole slide image, facilitating neuropathological analyses at multiple scales. Quantitative measurements of amyloid pathology correlated positively and significantly with the severity of AD as measured by standard approaches. We conclude that we have developed a computational pipeline to analyze digitized images of neuropathology in high throughput and algorithms to detect types of amyloid pathology with human level accuracy that should enable neuropathological analysis of large tissue collections and integration of those results with orthogonal clinical and multiomic measurements.

neuroscience↗

bioRxiv2023

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

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

genomics↗

bioRxiv2023

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology. One sentence summaryCell-type specific chromatin accessibility QTL reveals regulatory mechanisms underlying brain diseases.

genomics↗

bioRxiv2022

Transcriptome and chromatin accessibility landscapes across 25 distinct human brain regions expand the susceptibility gene set for neuropsychiatric disorders

Brain region- and cell-specific transcriptomic and epigenomic molecular features are associated with heritability for neuropsychiatric traits, but a systematic view, considering cortical and subcortical regions, is lacking. Here, we provide an atlas of chromatin accessibility and gene expression in neuronal and non-neuronal nuclei across 25 distinct human cortical and subcortical brain regions from 6 neurotypical controls. We identified extensive gene expression and chromatin accessibility differences across brain regions, including variation in alternative promoter-isoform usage and enhancer-promoter interactions. Genes with distinct promoter-isoform usage across brain regions are strongly enriched for neuropsychiatric disease risk variants. Using an integrative approach, we characterized the function of the brain region-specific chromatin co-accessibility and gene-coexpression modules that are robustly associated with genetic risk for neuropsychiatric disorders. In addition, we identified a novel set of genes that is enriched for disease risk variants but is independent of cell-type specific gene expression and known susceptibility pathways. Our results provide a valuable resource for studying molecular regulation across multiple regions of the human brain and suggest a unique contribution of epigenetic modifications from subcortical areas to neuropsychiatric disorders.

neuroscience↗

bioRxiv2022

Brain Atlas for Glycoprotein Hormone Receptors at Single-Transcript Level

There is increasing evidence that anterior pituitary hormones, traditionally thought to have unitary functions in regulating single endocrine targets, act on multiple somatic tissues, such as bone, fat, and liver. There is also emerging evidence for anterior pituitary hormone action on brain receptors in mediating central neural and peripheral somatic functions. Here, we have created the most comprehensive neuroanatomical atlas on the expression of TSHRs, LHCGRs and FSHRs. We have used RNAscope, a technology that allows the detection of mRNA at single-transcript level, together with protein level validation, to document Tshr expression in 173 and Fshr expression in 353 brain regions, nuclei and sub-nuclei identified using the Atlas for the Mouse Brain in Stereotaxic Coordinates. We also identified Lhcgr transcripts in 401 brain regions, nuclei and sub-nuclei. Complementarily, we used ViewRNA, another single-transcript detection technology, to establish the expression of FSHRs in human brain samples, where transcripts were co-localized in MALAT1-positive neurons. In addition, we show high expression for all three receptors in the ventricular region--with yet unknown functions. Intriguingly, Tshr and Fshr expression in the ependymal layer of the third ventricle was similar to that of the thyroid follicular cells and testicular Sertoli cells, respectively. TSHRs were expressed specifically in tanycytes. In contrast, Fshrs were localized to NeuN-positive neurons in the granular layer of the dentate gyrus in murine and human brain--both are Alzheimers disease vulnerable regions. Our atlas thus provides a vital resource for scientists to explore the link between the stimulation or inactivation of brain glycoprotein hormone receptors on somatic function. New actionable pathways for human disease may be unmasked through further studies.

neuroscience↗

bioRxiv2021

Predictors of cognitive impairment in primary age-related tauopathy: an autopsy study

Primary age-related tauopathy (PART) is a form of Alzheimer-type neurofibrillary degeneration occurring in the absence of amyloid-beta (A{beta}) plaques. While PART shares some features with Alzheimer disease (AD), such as progressive accumulation of neurofibrillary tangle pathology in the medial temporal lobe and other brain regions, it does not progress extensively to neocortical regions. Given this restricted pathoanatomical pattern and variable symptomatology, there is a need to reexamine and improve upon how PART is neuropathologically assessed and staged. We performed a retrospective autopsy study in a collection (n=174) of post-mortem PART brains and used logistic regression to determine the extent to which a set of clinical and neuropathological features predict cognitive impairment. We compared Braak staging, which focuses on hierarchical neuroanatomical progression of AD tau and A{beta} pathology, with quantitative assessments of neurofibrillary burden using computer-derived positive pixel counts on digitized whole slide images of sections stained immunohistochemically with antibodies targeting abnormal hyperphosphorylated tau (p-tau) in the entorhinal region and hippocampus. We also assessed other factors affecting cognition, including aging-related tau astrogliopathy (ARTAG) and atrophy. We found no association between Braak stage and cognitive impairment when controlling for age (p=0.76). In contrast, p-tau burden was significantly correlated with cognitive impairment even when adjusting for age (p=0.03). The strongest correlate of cognitive impairment was cerebrovascular disease, a well-known risk factor (p<0.0001), but other features including ARTAG (p=0.03) and hippocampal atrophy (p=0.04) were also associated. In contrast, sex, APOE, psychiatric illness, education, argyrophilic grains, and incidental Lewy bodies were not. These findings support the hypothesis that comorbid pathologies contribute to cognitive impairment in subjects with PART. Quantitative approaches beyond Braak staging are critical for advancing our understanding of the extent to which age-related tauopathy changes impact cognitive function.

pathology↗

bioRxiv2021

Transcriptomic changes highly similar to Alzheimer's disease are observed in a subpopulation of individuals during normal brain aging

Aging is a major risk factor for late-onset Alzheimers disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examined multiple large-scale transcriptomic data from both normal aging and LOAD brains to understand the molecular interconnection between aging and LOAD. We found that shared gene expression changes between aging and LOAD are mostly seen in the hippocampal and several cortical regions. In the hippocampus, the expression of phosphoprotein, alternative splicing and cytoskeleton genes are commonly changed in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are more related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also found that normal aging brain transcriptomes from relatively young donors (45-70 years old) clustered into several subgroups and some subgroups showed gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptomic data from another cohort of older individuals (> 70 years), we found that samples from cognitively normal older individuals clustered with the "healthy aging" subgroup while AD samples mainly clustered with the "AD similar" subgroups. This may imply that individuals in the healthy aging subgroup will likely remain cognitively normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitively normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the "normal brain aging" to identify the very early molecular events that may lead to LOAD development.

neuroscience↗

bioRxiv2021

Acetylated Chromatin Domains Link Chromosomal Organization to Cell- and Circuit-level Dysfunction in Schizophrenia and Bipolar Disorder

To explore modular organization of chromosomes in schizophrenia (SCZ) and bipolar disorder (BD), we applied population-scale correlational structuring of 739 histone H3-lysine 27 acetylation and H3-lysine 4 trimethylation profiles, generated from the prefrontal cortex (PFC) of 568 cases and controls. Neuronal histone acetylomes and methylomes assembled as thousands of cis-regulatory domains (CRDs), revealing fine-grained, kilo-to megabase scale chromatin organization at higher resolution but firmly integrated into Hi-C chromosomal conformations. Large clusters of domains that were hyperacetylated in disease shared spatial positioning within the nucleus, predominantly regulating PFC projection neuron function and excitatory neurotransmission. Hypoacetylated domains were linked to inhibitory interneuron- and myelination-relevant genes. Chromosomal modular architecture is affected in SCZ and BD, with hyperacetylated domains showing unexpectedly strong convergences defined by cell type, nuclear topography, genetic risk, and active chromatin state across a wide developmental window.

genomics↗

bioRxiv2021

Transcribed enhancers in the human brain identify novel disease risk mechanisms

Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding the population-level variation of enhancers in the human brain. Besides regulating tissue- and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. We expanded the catalog of known human brain transcribed enhancers by an order of magnitude by generating and jointly analyzing large-scale cell-type-specific transcriptome and regulome data. Examination of the transcriptome in 1,382 brain samples in two independent cohorts identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified significant expression quantitative trait loci (eQTL) for 25,958 enhancers which mediate 6.8% of schizophrenia heritability, mostly independent from standard gene eQTL. Inclusion of enhancer eQTL in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the enhancer-gene regulome and genetic mechanisms in the human cortex in both healthy and disease states.

neuroscience↗

bioRxiv2021

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

Much is still unknown about the neurobiology of Alzheimers disease (AD). To better understand AD, we generated 636 ATAC-seq libraries from cases and controls to construct detailed genomewide chromatin accessibility maps of neurons and non-neurons from two AD-affected brain regions, the entorhinal cortex and superior temporal gyrus. By analyzing a total of 19.6 billion read pairs, we expanded the known repertoire of regulatory sequences in the human brain. Multi-omic data integration associated global patterns of chromatin accessibility with gene expression and identified cell-specific enhancer-promoter interactions. Using inter-individual variation in chromatin accessibility, we define cis-regulatory domains capturing the 3D structure of the genome. Multifaceted analyses uncovered disease associated perturbations impacting chromatin accessibility, transcription factor regulatory networks and the 3D genome, and implicated transcriptional dysregulation in AD. Overall, we applied a systematic approach to understand the role of the 3D genome in AD and to illuminate novel disease biology that can advance diagnosis and therapy.

neuroscience↗

bioRxiv2020

Meta-analysis of epigenome-wide association studies in Alzheime's disease highlights 220 differentially methylated loci across cortex

Epigenome-wide association studies of Alzheimers disease have highlighted neuropathology-associated DNA methylation differences, although existing studies have been limited in sample size and utilized different brain regions. Here, we combine data from six DNA methylomic studies of Alzheimers disease (N=1,453 unique individuals) to identify differential methylation associated with Braak stage in different brain regions and across cortex. We identify 236 CpGs in the prefrontal cortex, 95 CpGs in the temporal gyrus and ten CpGs in the entorhinal cortex at Bonferroni significance, with none in the cerebellum. Our cross-cortex meta-analysis (N=1,408 donors) identifies 220 CpGs associated with neuropathology, annotated to 121 genes, of which 84 genes have not been previously reported at this significance threshold. We have replicated our findings using two further DNA methylomic datasets consisting of a further > 600 unique donors. The meta-analysis summary statistics are available in our online data resource (www.epigenomicslab.com/ad-meta-analysis/).

genomics↗

bioRxiv2020

Transcriptional profile of pyramidal neurons in chronic schizophrenia reveals lamina-specific dysfunction of neuronal immunity

While the pathophysiology of schizophrenia has been extensively investigated using homogenized postmortem brain samples, few studies have examined changes in brain samples with techniques that may attribute perturbations to specific cell types. To fill this gap, we performed microarray assays on mRNA isolated from anterior cingulate cortex (ACC) superficial and deep pyramidal neurons from 12 schizophrenia and 12 control subjects using laser capture microdissection. Among all the annotated genes, we identified 134 significantly increased and 130 decreased genes in superficial pyramidal neurons, while 93 significantly increased and 101 decreased genes were found in deep pyramidal neurons, in schizophrenia compared to control subjects. In these differentially expressed genes, we detected lamina-specific changes of 55 and 31 genes in superficial and deep neurons in schizophrenia, respectively. Gene set enrichment analysis (GSEA) was applied to the entire pre-ranked differential expression gene lists to gain a complete pathway analysis throughout all annotated genes. Our analysis revealed over-represented groups of gene sets in schizophrenia, particularly in immunity and synapse related pathways in pyramidal neurons, suggesting the disruption of these pathways plays an important role in schizophrenia. We also detected pathways previously demonstrated in schizophrenia pathophysiology, including cytokine and chemotaxis, post-synaptic signaling, and glutamatergic synapses. In addition, we observed several novel pathways, including ubiquitin-independent protein catabolic process. By comparing our differential expression gene profiles with 51 antipsychotic treatment datasets, we demonstrated that our results were not influenced by antipsychotic treatment of our subjects. Taken together, we found pyramidal neuron-specific changes in neuronal immunity, synaptic dysfunction, and olfactory dysregulation in schizophrenia, providing new insights for the cell-subtype specific pathophysiology of chronic schizophrenia.

neuroscience↗

bioRxiv2019

Comprehensive post mortem brain samples analysis detects global reduction of multiple proteasome subunits expression in schizophrenia

OBJECTIVEA main challenge in the study of schizophrenia is its high heterogeneity. While it is generally accepted that there exist several biological mechanisms that may define distinct schizophrenia subtypes, they havent been identified yet. We applied comprehensive gene expression analysis, searching for molecular signals that differentiate patients with schizophrenia from healthy controls, and examined whether the identified signal characterizes a particular subgroup of the patients. METHODSWe performed transcriptome sequencing of 14 superior temporal gyrus (STG) samples of relatively young (mean age: 44) subjects with schizophrenia and 15 matched controls from the Stanley Medical Research Institute. Analyses of differential expression and pathway enrichment were applied and the results were compared with those obtained from an independent cohort of elderly (mean age: 74) patients. Replicability was then tested on six additional independent datasets of various brain regions. RESULTSThe two STG cohorts of relatively young and elderly subjects showed high replicability. Pathway enrichment analysis of the down-regulated genes pointed to proteasome-related pathways. Meta-analysis of differential expression identified down-regulation of 12 of 39 proteasome subunits in schizophrenia. Down-regulation of multiple proteasome subunits was replicated in six additional datasets (overall 8 cohorts, with 267 schizophrenia and 266 control samples, from 5 brain regions, were studied). This signal was concentrated in a subgroup of the patients. CONCLUSIONSWe detect global down-regulation of proteasome subunits in a subgroup of the patients with schizophrenia. The proteasome is a major intracellular protein degradation system, where ubiquitinated proteins (proteins bound by the small protein called ubiquitin) are targeted for degradation. We hypothesize that the down-regulation we detect leads to proteasome dysfunction that causes accumulation of ubiquitinated proteins. Such accumulation has recently been identified, also in a subgroup of the studied patients with schizophrenia. Thus, down-regulation of proteasome subunits might define a biological subtype of schizophrenia.

neuroscience↗

bioRxiv2019

A Consensus Proteomic Analysis of Alzheimer’s Disease Brain and Cerebrospinal Fluid Reveals Early Changes in Energy Metabolism Associated with Microglia and Astrocyte Activation

Our understanding of the biological changes in the brain associated with Alzheimers disease (AD) pathology and cognitive impairment remains incomplete. To increase our understanding of these changes, we analyzed dorsolateral prefrontal cortex of control, asymptomatic AD, and AD brains from four different centers by label-free quantitative mass spectrometry and weighted protein co-expression analysis to obtain a consensus protein co-expression network of AD brain. This network consisted of 13 protein co-expression modules. Six of these modules correlated with amyloid-{beta} plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These six modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community-based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module. This module was enriched in AD genetic risk factors, and was also highly enriched in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from the sugar metabolism module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network. In this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease.

systems biology↗