RESUMO
The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease.
Assuntos
Doença de Alzheimer , Doença de Alzheimer/genética , Humanos , Genômica , Biomarcadores , Demência/genética , Proteômica , MultiômicaRESUMO
Alzheimer's Disease (AD) biomarker measurement is key to aid in the diagnosis and prognosis of the disease. In the research setting, participant recruitment and retention and optimization of sample use, is one of the main challenges that observational studies face. Thus, obtaining accurate established biomarker measurements for stratification and maximizing use of the precious samples is key. Accurate technologies are currently available for established biomarkers, mainly immunoassays and immunoprecipitation liquid chromatography-mass spectrometry (IP-MS), and some of them are already being used in clinical settings. Although some immunoassays- and IP-MS based platforms provide multiplexing for several different coding proteins there is not a current platform that can measure all the stablished and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA™) is a mid-throughput platform with antibody-based measurements with a sequencing output that requires 15µL of sample volume to measure more than 100 analytes, including those typically assayed for AD. Here we benchmarked and compared the AD-relevant biomarkers including in the NULISA against validated assays, in both CSF and plasma. Overall, we have found that CSF measures of Aß42/40, NfL, GFAP, and p-tau217 are highly correlated and have similar predictive performance when measured by immunoassay, mass-spectrometry or NULISA. In plasma, p-tau217 shows a performance similar to that reported with other technologies when predicting amyloidosis. Other established and exploratory biomarkers (total tau, p-tau181, NRGN, YKL40, sTREM2, VILIP1 among other) show a wide range of correlation values depending on the fluid and the platform. Our results indicate that the multiplexed immunoassay platform produces reliable results for established biomarkers in CSF that are useful in research settings, with the advantage of measuring additional novel biomarkers using minimal sample volume.
RESUMO
Alzheimer Disease (AD) is a highly polygenic disease that presents with relatively earlier onset (≤70yo; EOAD) in about 5% of cases. Around 90% of these EOAD cases remain unexplained by pathogenic mutations. Using data from EOAD cases and controls, we performed a genome-wide association study (GWAS) and trans-ancestry meta-analysis on non-Hispanic Whites (NHW, NCase=6,282, NControl=13,386), African Americans (AA NCase=782, NControl=3,663) and East Asians (NCase=375, NControl=838 CO). We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL and functional annotations, we nominate four novel genes that are involved in microglia activation, glutamate production, and signaling pathways. These results indicate that EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD.
RESUMO
OBJECTIVES: The adult-onset focal dystonias are characterized by over-active muscles leading to abnormal movements. For most cases, the etiology and pathogenesis remain unknown. In the current study, unbiased proteomics methods were used to identify potential changes in blood plasma proteins. METHODS: A large-scale unbiased proteomics screen was used to compare proteins (N = 6,345) in blood plasma of normal healthy controls (N = 49) with adult-onset focal dystonia (N = 143) consisting of specific subpopulations of cervical dystonia (N = 45), laryngeal dystonia (N = 49), and blepharospasm (N = 49). Pathway analyses were conducted to identify relevant biological pathways. Finally, protein changes were used to build a prediction model for dystonia. RESULTS: After correction for multiple comparisons, 15 proteins were associated with adult-onset focal dystonia. Subgroup analyses revealed some proteins were shared across the dystonia subgroups while others were unique to 1 subgroup. The top biological pathways involved changes in the immune system, metal ion transport, and reactive oxygen species. A 4-protein model showed high accuracy in discriminating control individuals from dystonia cases [average area under the curve (AUC) = 0.89]. INTERPRETATION: These studies provide novel insights into the etiopathogenesis of dystonia, as well as novel potential biomarkers. ANN NEUROL 2024;96:110-120.
Assuntos
Distúrbios Distônicos , Proteômica , Humanos , Proteômica/métodos , Feminino , Masculino , Distúrbios Distônicos/sangue , Distúrbios Distônicos/diagnóstico , Pessoa de Meia-Idade , Adulto , Idoso , Biomarcadores/sangue , Proteínas Sanguíneas/metabolismoRESUMO
Comprehensive expression quantitative trait loci studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein quantitative trait loci in brain, cerebrospinal fluid, and plasma. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in cerebrospinal fluid, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 loci in brain, 30 loci in cerebrospinal fluid, and 22 loci in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These resources are accessible through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer for use by the scientific community.
Assuntos
Regulação da Expressão Gênica , Proteoma , Locos de Características Quantitativas , Humanos , Encéfalo , Estudo de Associação Genômica Ampla , Genômica , Fenótipo , Proteoma/genética , Plasma , Líquido CefalorraquidianoRESUMO
Changes in Amyloid-ß (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages).
RESUMO
Background: To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies. Methods: We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models. Findings: We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aß42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89). Interpretation: Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs. Funding: Proteomic data generation was supported by NIH: RF1AG044546.
RESUMO
There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.
RESUMO
Animal studies show aging varies between individuals as well as between organs within an individual1-4, but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20-50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer's disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.
Assuntos
Envelhecimento , Biomarcadores , Doença , Saúde , Especificidade de Órgãos , Proteoma , Proteômica , Adulto , Humanos , Envelhecimento/sangue , Doença de Alzheimer/sangue , Biomarcadores/sangue , Encéfalo/metabolismo , Disfunção Cognitiva/sangue , Proteoma/análise , Aprendizado de Máquina , Estudos de Coortes , Progressão da Doença , Insuficiência Cardíaca/sangue , Matriz Extracelular/metabolismo , Sinapses/metabolismo , Calcificação Vascular/sangue , CoraçãoRESUMO
The integration of quantitative trait loci (QTL) with disease genome-wide association studies (GWAS) has proven successful at prioritizing candidate genes at disease-associated loci. QTL mapping has mainly been focused on multi-tissue expression QTL or plasma protein QTL (pQTL). Here we generated the largest-to-date cerebrospinal fluid (CSF) pQTL atlas by analyzing 7,028 proteins in 3,107 samples. We identified 3,373 independent study-wide associations for 1,961 proteins, including 2,448 novel pQTLs of which 1,585 are unique to CSF, demonstrating unique genetic regulation of the CSF proteome. In addition to the established chr6p22.2-21.32 HLA region, we identified pleiotropic regions on chr3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron-specificity and neurological development. We also integrated this pQTL atlas with the latest Alzheimer's disease (AD) GWAS through PWAS, colocalization and Mendelian Randomization and identified 42 putative causal proteins for AD, 15 of which have drugs available. Finally, we developed a proteomics-based risk score for AD that outperforms genetics-based polygenic risk scores. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits.
RESUMO
Genetic studies of Alzheimer disease (AD) have prioritized variants in genes related to the amyloid cascade, lipid metabolism, and neuroimmune modulation. However, the cell-specific effect of variants in these genes is not fully understood. Here, we perform single-nucleus RNA-sequencing (snRNA-seq) on nearly 300,000 nuclei from the parietal cortex of AD autosomal dominant (APP and PSEN1) and risk-modifying variant (APOE, TREM2 and MS4A) carriers. Within individual cell types, we capture genes commonly dysregulated across variant groups. However, specific transcriptional states are more prevalent within variant carriers. TREM2 oligodendrocytes show a dysregulated autophagy-lysosomal pathway, MS4A microglia have dysregulated complement cascade genes, and APOEε4 inhibitory neurons display signs of ferroptosis. All cell types have enriched states in autosomal dominant carriers. We leverage differential expression and single-nucleus ATAC-seq to map GWAS signals to effector cell types including the NCK2 signal to neurons in addition to the initially proposed microglia. Overall, our results provide insights into the transcriptional diversity resulting from AD genetic architecture and cellular heterogeneity. The data can be explored on the online browser ( http://web.hararilab.org/SNARE/ ).
Assuntos
Doença de Alzheimer , Humanos , Doença de Alzheimer/genética , Doença de Alzheimer/metabolismo , Heterozigoto , Microglia/metabolismo , Lobo Parietal/metabolismo , RNA/metabolismoRESUMO
Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
RESUMO
Genome-wide association studies (GWAS) have identified many modifiers of Alzheimer disease (AD) risk enriched in microglia. Two of these modifiers are common variants in the MS4A locus (rs1582763: protective and rs6591561: risk) and serve as major regulators of CSF sTREM2 levels. To understand their functional impact on AD, we used single nucleus transcriptomics to profile brains from carriers of these variants. We discovered a "chemokine" microglial subpopulation that is altered in MS4A variant carriers and for which MS4A4A is the major regulator. The protective variant increases MS4A4A expression and shifts the chemokine microglia subpopulation to an interferon state, while the risk variant suppresses MS4A4A expression and reduces this subpopulation of microglia. Our findings provide a mechanistic explanation for the AD variants in the MS4A locus. Further, they pave the way for future mechanistic studies of AD variants and potential therapeutic strategies for enhancing microglia resilience in AD pathogenesis.
RESUMO
Introduction: More than 50 mutations in the MAPT gene result in heterogeneous forms of frontotemporal lobar dementia with tau inclusions (FTLD-Tau). However, early pathogenic events that lead to disease and the degree to which they are common across MAPT mutations remain poorly understood. The goal of this study is to determine whether there is a common molecular signature of FTLD-Tau. Methods: We analyzed genes differentially expressed in induced pluripotent stem cell-derived neurons (iPSC-neurons) that represent the three major categories of MAPT mutations: splicing (IVS10 + 16), exon 10 (p.P301L), and C-terminal (p.R406W) compared with isogenic controls. The genes that were commonly differentially expressed in MAPT IVS10 + 16, p.P301L, and p.R406W neurons were enriched in trans-synaptic signaling, neuronal processes, and lysosomal function. Many of these pathways are sensitive to disruptions in calcium homeostasis. One gene, CALB1, was significantly reduced across the three MAPT mutant iPSC-neurons and in a mouse model of tau accumulation. We observed a significant reduction in calcium levels in MAPT mutant neurons compared with isogenic controls, pointing to a functional consequence of this disrupted gene expression. Finally, a subset of genes commonly differentially expressed across MAPT mutations were also dysregulated in brains from MAPT mutation carriers and to a lesser extent in brains from sporadic Alzheimer disease and progressive supranuclear palsy, suggesting that molecular signatures relevant to genetic and sporadic forms of tauopathy are captured in a dish. The results from this study demonstrate that iPSC-neurons capture molecular processes that occur in human brains and can be used to pinpoint common molecular pathways involving synaptic and lysosomal function and neuronal development, which may be regulated by disruptions in calcium homeostasis.
RESUMO
INTRODUCTION: The identification of multiple genetic risk factors for Alzheimer's disease (AD) suggests that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain. METHODS: We interrogated metabolomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE É4, and TREM2 risk variant carriers, and sporadic AD (sAD). RESULTS: We identified 133 unique and shared metabolites associated with ADAD, TREM2, and sAD. We identified a signature of 16 metabolites significantly altered between groups and associated with AD duration. DISCUSSION: AD genetic variants show distinct metabolic perturbations. Investigation of these metabolites may provide greater insight into the etiology of AD and its impact on clinical presentation. HIGHLIGHTS: APP/PSEN1/PSEN2 and TREM2 variant carriers show distinct metabolic changes. A total of 133 metabolites were differentially abundant in AD genetic groups. ß-citrylglutamate is differentially abundant in autosomal dominant, TREM2, and sporadic AD. A 16-metabolite profile shows differences between Alzheimer's disease (AD) genetic groups. The identified metabolic profile is associated with duration of disease.
Assuntos
Doença de Alzheimer , Humanos , Doença de Alzheimer/genética , Doença de Alzheimer/patologia , Precursor de Proteína beta-Amiloide/genética , Encéfalo/patologia , Heterozigoto , Lipidômica , Mutação , Presenilina-1/genéticaRESUMO
Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.proteomics.wustl.edu/ ). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10 -14 ), Alzheimer's disease (FDR ≤ 5.46×10 -10 ) and coronary artery disease (FDR ≤ 4.64×10 -2 ). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
RESUMO
BACKGROUND: Autosomal-dominant Alzheimer's disease (ADAD) is caused by pathogenic mutations in APP, PSEN1, and PSEN2, which usually lead to an early age at onset (< 65). Circular RNAs are a family of non-coding RNAs highly expressed in the nervous system and especially in synapses. We aimed to investigate differences in brain gene expression of linear and circular transcripts from the three ADAD genes in controls, sporadic AD, and ADAD. METHODS: We obtained and sequenced RNA from brain cortex using standard protocols. Linear counts were obtained using the TOPMed pipeline; circular counts, using python package DCC. After stringent quality control (QC), we obtained the counts for PSEN1, PSEN2 and APP genes. Only circPSEN1 passed QC. We used DESeq2 to compare the counts across groups, correcting for biological and technical variables. Finally, we performed in-silico functional analyses using the Circular RNA interactome website and DIANA mirPath software. RESULTS: Our results show significant differences in gene counts of circPSEN1 in ADAD individuals, when compared to sporadic AD and controls (ADAD = 21, AD = 253, Controls = 23-ADADvsCO: log2FC = 0.794, p = 1.63 × 10-04, ADADvsAD: log2FC = 0.602, p = 8.22 × 10-04). The high gene counts are contributed by two circPSEN1 species (hsa_circ_0008521 and hsa_circ_0003848). No significant differences were observed in linear PSEN1 gene expression between cases and controls, indicating that this finding is specific to the circular forms. In addition, the high circPSEN1 levels do not seem to be specific to PSEN1 mutation carriers; the counts are also elevated in APP and PSEN2 mutation carriers. In-silico functional analyses suggest that circPSEN1 is involved in several pathways such as axon guidance (p = 3.39 × 10-07), hippo signaling pathway (p = 7.38 × 10-07), lysine degradation (p = 2.48 × 10-05) or Wnt signaling pathway (p = 5.58 × 10-04) among other KEGG pathways. Additionally, circPSEN1 counts were able to discriminate ADAD from sporadic AD and controls with an AUC above 0.70. CONCLUSIONS: Our findings show the differential expression of circPSEN1 is increased in ADAD. Given the biological function previously ascribed to circular RNAs and the results of our in-silico analyses, we hypothesize that this finding might be related to neuroinflammatory events that lead or that are caused by the accumulation of amyloid-beta.
Assuntos
Doença de Alzheimer , Humanos , Doença de Alzheimer/metabolismo , Precursor de Proteína beta-Amiloide/genética , Precursor de Proteína beta-Amiloide/metabolismo , Encéfalo/metabolismo , Mutação , Presenilina-1/genética , Presenilina-1/metabolismo , RNA Circular/genéticaRESUMO
During the first hours after stroke onset, neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between the National Institutes of Health Stroke Scale (NIHSS) within 6â h of stroke onset and NIHSS at 24â h. A total of 5876 individuals from seven countries (Spain, Finland, Poland, USA, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of NIHSS at 24â h of variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture from that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2 and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each locus. Expression quantitative trait loci mapping and summary data-based Mendelian randomization indicate that ADAM23 (log Bayes factor = 5.41) was driving the association for 2q33.3. Gene-based analyses suggested that GRIA1 (log Bayes factor = 5.19), which is predominantly expressed in the brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (log Bayes factor = 7.64) ABCB5 (log Bayes factor = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single-nuclei RNA-sequencing indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a presynaptic protein and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provide the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischaemic stroke.
Assuntos
Isquemia Encefálica , AVC Isquêmico , Acidente Vascular Cerebral , Teorema de Bayes , Isquemia Encefálica/complicações , Isquemia Encefálica/genética , Estudo de Associação Genômica Ampla , Humanos , Acidente Vascular Cerebral/complicações , Acidente Vascular Cerebral/genética , Estados UnidosRESUMO
Understanding the tissue-specific genetic controls of protein levels is essential to uncover mechanisms of post-transcriptional gene regulation. In this study, we generated a genomic atlas of protein levels in three tissues relevant to neurological disorders (brain, cerebrospinal fluid and plasma) by profiling thousands of proteins from participants with and without Alzheimer's disease. We identified 274, 127 and 32 protein quantitative trait loci (pQTLs) for cerebrospinal fluid, plasma and brain, respectively. cis-pQTLs were more likely to be tissue shared, but trans-pQTLs tended to be tissue specific. Between 48.0% and 76.6% of pQTLs did not co-localize with expression, splicing, DNA methylation or histone acetylation QTLs. Using Mendelian randomization, we nominated proteins implicated in neurological diseases, including Alzheimer's disease, Parkinson's disease and stroke. This first multi-tissue study will be instrumental to map signals from genome-wide association studies onto functional genes, to discover pathways and to identify drug targets for neurological diseases.