21 research outputs found

    Integrated transcriptomics establish macrophage polarization signatures and have potential applications for clinical health and disease

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    Growing evidence defines macrophages (Mφ) as plastic cells with wide-ranging states of activation and expression of different markers that are time and location dependent. Distinct from the simple M1/M2 dichotomy initially proposed, extensive diversity of macrophage phenotypes have been extensively demonstrated as characteristic features of monocyte-macrophage differentiation, highlighting the difficulty of defining complex profiles by a limited number of genes. Since the description of macrophage activation is currently contentious and confusing, the generation of a simple and reliable framework to categorize major Mφ phenotypes in the context of complex clinical conditions would be extremely relevant to unravel different roles played by these cells in pathophysiological scenarios. In the current study, we integrated transcriptome data using bioinformatics tools to generate two macrophage molecular signatures. We validated our signatures in in vitro experiments and in clinical samples. More importantly, we were able to attribute prognostic and predictive values to components of our signatures. Our study provides a framework to guide the interrogation of macrophage phenotypes in the context of health and disease. The approach described here could be used to propose new biomarkers for diagnosis in diverse clinical settings including dengue infections, asthma and sepsis resolution

    Astrocyte biomarker signatures of amyloid-β and tau pathologies in Alzheimer’s disease

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    Astrocytes can adopt multiple molecular phenotypes in the brain of Alzheimer's disease (AD) patients. Here, we studied the associations of cerebrospinal fluid (CSF) glial fibrillary acidic protein (GFAP) and chitinase-3-like protein 1 (YKL-40) levels with brain amyloid-β (Aβ) and tau pathologies. We assessed 121 individuals across the aging and AD clinical spectrum with positron emission tomography (PET) brain imaging for Aβ ([18F]AZD4694) and tau ([18F]MK-6240), as well as CSF GFAP and YKL-40 measures. We observed that higher CSF GFAP levels were associated with elevated Aβ-PET but not tau-PET load. By contrast, higher CSF YKL-40 levels were associated with elevated tau-PET but not Aβ-PET burden. Structural equation modeling revealed that CSF GFAP and YKL-40 mediate the effects of Aβ and tau, respectively, on hippocampal atrophy, which was further associated with cognitive impairment. Our results suggest the existence of distinct astrocyte biomarker signatures in response to brain Aβ and tau accumulation, which may contribute to our understanding of the complex link between reactive astrogliosis heterogeneity and AD progression

    Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

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    Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues

    Image_1_Master Regulators Connectivity Map: A Transcription Factors-Centered Approach to Drug Repositioning.TIF

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    <p>Drug discovery is a very expensive and time-consuming endeavor. Fortunately, recent omics technologies and Systems Biology approaches introduced interesting new tools to achieve this task, facilitating the repurposing of already known drugs to new therapeutic assignments using gene expression data and bioinformatics. The inherent role of transcription factors in gene expression modulation makes them strong candidates for master regulators of phenotypic transitions. However, transcription factors expression itself usually does not reflect its activity changes due to post-transcriptional modifications and other complications. In this aspect, the use of high-throughput transcriptomic data may be employed to infer transcription factors-targets interactions and assess their activity through co-expression networks, which can be further used to search for drugs capable of reverting the gene expression profile of pathological phenotypes employing the connectivity maps paradigm. Following this idea, we argue that a module-oriented connectivity map approach using transcription factors-centered networks would aid the query for new repositioning candidates. Through a brief case study, we explored this idea in bipolar disorder, retrieving known drugs used in the usual clinical scenario as well as new candidates with potential therapeutic application in this disease. Indeed, the results of the case study indicate just how promising our approach may be to drug repositioning.</p

    Table_2_Master Regulators Connectivity Map: A Transcription Factors-Centered Approach to Drug Repositioning.XLSX

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    <p>Drug discovery is a very expensive and time-consuming endeavor. Fortunately, recent omics technologies and Systems Biology approaches introduced interesting new tools to achieve this task, facilitating the repurposing of already known drugs to new therapeutic assignments using gene expression data and bioinformatics. The inherent role of transcription factors in gene expression modulation makes them strong candidates for master regulators of phenotypic transitions. However, transcription factors expression itself usually does not reflect its activity changes due to post-transcriptional modifications and other complications. In this aspect, the use of high-throughput transcriptomic data may be employed to infer transcription factors-targets interactions and assess their activity through co-expression networks, which can be further used to search for drugs capable of reverting the gene expression profile of pathological phenotypes employing the connectivity maps paradigm. Following this idea, we argue that a module-oriented connectivity map approach using transcription factors-centered networks would aid the query for new repositioning candidates. Through a brief case study, we explored this idea in bipolar disorder, retrieving known drugs used in the usual clinical scenario as well as new candidates with potential therapeutic application in this disease. Indeed, the results of the case study indicate just how promising our approach may be to drug repositioning.</p

    Cannabidiol Exposure During Neuronal Differentiation Sensitizes Cells Against Redox-Active Neurotoxins

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    Cannabidiol (CBD), one of the most abundant Cannabis sativa-derived compounds, has been implicated with neuroprotective effect in several human pathologies. Until now, no undesired side effects have been associated with CBD. In this study, we evaluated CBD’s neuroprotective effect in terminal differentiation (mature) and during neuronal differentiation (neuronal developmental toxicity model) of the human neuroblastoma SH-SY5Y cell line. A dose-response curve was performed to establish a sublethal dose of CBD with antioxidant activity (2.5 μM). In terminally differentiated SH-SY5Y cells, incubation with 2.5 μM CBD was unable to protect cells against the neurotoxic effect of glycolaldehyde, methylglyoxal, 6-hydroxydopamine, and hydrogen peroxide (H2O2). Moreover, no difference in antioxidant potential and neurite density was observed. When SH-SY5Y cells undergoing neuronal differentiation were exposed to CBD, no differences in antioxidant potential and neurite density were observed. However, CBD potentiated the neurotoxicity induced by all redox-active drugs tested. Our data indicate that 2.5 μM of CBD, the higher dose tolerated by differentiated SH-SY5Y neuronal cells, does not provide neuroprotection for terminally differentiated cells and shows, for the first time, that exposure of CBD during neuronal differentiation could sensitize immature cells to future challenges with neurotoxins

    Influence of Different Diagnostic Criteria on Alzheimer Disease Clinical Research

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    BACKGROUND AND OBJECTIVES: Updates in Alzheimer disease (AD) diagnostic guidelines by the National Institute on Aging-Alzheimer's Association (NIA-AA) and the International Working Group (IWG) over the past 11 years may affect clinical diagnoses. We assessed how these guidelines affect clinical AD diagnosis in a cohort of cognitively unimpaired (CU) and cognitively impaired (CI) individuals. METHODS: We applied clinical and biomarker data in algorithms to classify individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort according to the following diagnostic guidelines for AD: 2011 NIA-AA, 2016 IWG-2, 2018 NIA-AA, and 2021 IWG-3, assigning the following generic diagnostic labels: (1) not AD (nAD), (2) increased risk of developing AD (irAD), and (3) AD. Diagnostic labels were compared according to their frequency, convergence across guidelines, biomarker profiles, and prognostic value. We also evaluated the diagnostic discordance among the criteria. RESULTS: A total of 1,195 individuals (mean age 73.2 ± 7.2 years, mean education 16.1 ± 2.7, 44.0% female) presented different repartitions of diagnostic labels according to the 2011 NIA-AA (nAD = 37.8%, irAD = 23.0%, AD = 39.2%), 2016 IWG-2 (nAD = 37.7%, irAD = 28.7%, AD = 33.6%), 2018 NIA-AA (nAD = 40.7%, irAD = 9.3%, AD = 50.0%), and 2021 IWG-3 (nAD = 51.2%, irAD = 8.4%, AD = 48.3%) frameworks. Discordant diagnoses across all guidelines were found in 512 participants (42.8%) (138 [91.4%] occurring in only β-amyloid [CU 65.4%, CI 34.6%] and 191 [78.6%] in only tau-positive [CU 71.7%, CI 28.3%] individuals). Differences in predicting cognitive impairment between nAD and irAD groups were observed with the 2011 NIA-AA (hazard ratio [HR] 2.21, 95% CI 1.34-3.65, p = 0.002), 2016 IWG-2 (HR 2.81, 95% CI 1.59-4.96, p < 0.000), and 2021 IWG-3 (HR 3.61, 95% CI 2.09-6.23, p < 0.000), but not with 2018 NIA-AA (HR 1.69, 95% CI 0.87-3.28, p = 0.115). DISCUSSION: Over 42% of the studied population presented discordant diagnoses when using the different examined AD criteria, mostly in individuals with a single positive biomarker. Except for 2018 NIA-AA, all guidelines identified asymptomatic individuals at risk of cognitive impairment. Our findings highlight important differences between the guidelines, emphasizing the necessity for updated criteria with enhanced staging metrics, considering clinical, research, therapeutic, and trial design aspects
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