171 research outputs found

    From model system to clinical medicine: pathophysiologic links of common proteinopathies

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    Recent clinical evidence suggests that Alzheimer disease (AD), Parkinson disease (PD), and dementia with Lewy bodies (DLB), though distinct neurological disorders, have some common pathological features that may have an impact on the clinical characteristics of these diseases. However, the question of whether these disorders have a common pathophysiology remains. Clinton and colleagues recently reported a mouse model that exhibits the combined pathologies of AD, PD, and DLB, a finding that may shed some light on this issue. Using this mouse model, the authors demonstrate that the pathogenic proteins amyloid beta, tau, and alpha-synuclein interact synergistically to enhance the accumulation of one another and accelerate cognitive decline. These data indicate shared pathogenic mechanisms and suggest the possibility that therapeutic interventions successfully targeting one of these pathogenic proteins have implications for a number of related neurodegenerative disorders

    Key inflammatory pathway activations in the MCI stage of Alzheimer's disease

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    OBJECTIVE: To determine the key inflammatory pathways that are activated in the peripheral and CNS compartments at the mild cognitive impairment (MCI) stage of Alzheimer's disease (AD). METHODS: A cross-sectional study of patients with clinical and biomarker characteristics consistent with MCI-AD in a discovery cohort, with replication in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Inflammatory analytes were measured in the CSF and plasma with the same validated multiplex analyte platform in both cohorts and correlated with AD biomarkers (CSF Aβ42, total tau (t-tau), phosphorylated tau (p-tau) to identify key inflammatory pathway activations. The pathways were additionally validated by evaluating genes related to all analytes in coexpression networks of brain tissue transcriptome from an autopsy confirmed AD cohort to interrogate if the same pathway activations were conserved in the brain tissue gene modules. RESULTS: Analytes of the tumor necrosis factor (TNF) signaling pathway (KEGG ID:4668) in the CSF and plasma best correlated with CSF t-tau and p-tau levels, and analytes of the complement and coagulation pathway (KEGG ID:4610) best correlated with CSF Aβ42 levels. The top inflammatory signaling pathways of significance were conserved in the peripheral and the CNS compartments. They were also confirmed to be enriched in AD brain transcriptome gene clusters. INTERPRETATION: A cell-protective rather than a proinflammatory analyte profile predominates in the CSF in relation to neurodegeneration markers among MCI-AD patients. Analytes from the TNF signaling and the complement and coagulation pathways are relevant in evaluating disease severity at the MCI stage of AD

    Key Inflammatory Pathway Activations in the MCI Stage of Alzheimer’s disease

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    Objective: To determine the key inflammatory pathways that are activated in the peripheral and CNS compartments at the mild cognitive impairment (MCI) stage of Alzheimer’s disease (AD). Methods: A cross-sectional study of patients with clinical and biomarker characteristics consistent with MCI-AD in a discovery cohort, with replication in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Inflammatory analytes were measured in the CSF and plasma with the same validated multiplex analyte platform in both cohorts and correlated with AD biomarkers (CSF Aβ42, total tau (t-tau), phosphorylated tau (p-tau) to identify key inflammatory pathway activations. The pathways were additionally validated by evaluating genes related to all analytes in coexpression networks of brain tissue transcriptome from an autopsy confirmed AD cohort to interrogate if the same pathway activations were conserved in the brain tissue gene modules. Results: Analytes of the tumor necrosis factor (TNF) signaling pathway (KEGG ID:4668) in the CSF and plasma best correlated with CSF t-tau and p-tau levels, and analytes of the complement and coagulation pathway (KEGG ID:4610) best correlated with CSF Aβ42 levels. The top inflammatory signaling pathways of significance were conserved in the peripheral and the CNS compartments. They were also confirmed to be enriched in AD brain transcriptome gene clusters. Interpretation: A cell-protective rather than a proinflammatory analyte profile predominates in the CSF in relation to neurodegeneration markers among MCI-AD patients. Analytes from the TNF signaling and the complement and coagulation pathways are relevant in evaluating disease severity at the MCI stage of AD

    Inflammatory Pathway Analytes Predicting Rapid Cognitive Decline in MCI stage of Alzheimer’s disease

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    Objective: To determine the inflammatory analytes that predict clinical progression and evaluate their performance against biomarkers of neurodegeneration. Methods: A longitudinal study of MCI-AD patients in a Discovery cohort over 15 months, with replication in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) MCI cohort over 36 months. Fifty-three inflammatory analytes were measured in the CSF and plasma with a RBM multiplex analyte platform. Inflammatory analytes that predict clinical progression on Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) and Mini Mental State Exam scores were assessed in multivariate regression models. To provide context, key analyte results in ADNI were compared against biomarkers of neurodegeneration, hippocampal volume, and CSF neurofilament light (NfL), in receiver operating characteristic (ROC) analyses evaluating highest quartile of CDR-SB change over two years (≥3 points). Results: Cerebrospinal fluid inflammatory analytes in relation to cognitive decline were best described by gene ontology terms, natural killer cell chemotaxis, and endothelial cell apoptotic process and in plasma, extracellular matrix organization, blood coagulation, and fibrin clot formation described the analytes. CSF CCL2 was most robust in predicting rate of cognitive change and analytes that correlated to CCL2 suggest IL-10 pathway dysregulation. The ROC curves for ≥3 points change in CDR-SB over 2 years when comparing baseline hippocampal volume, CSF NfL, and CCL2 were not significantly different. Interpretation: Baseline levels of immune cell chemotactic cytokine CCL2 in the CSF and IL-10 pathway dysregulation impact longitudinal cognitive and functional decline in MCI-AD. CCL2’s utility appears comparable to biomarkers of neurodegeneration in predicting rapid decline

    The tau tubulin kinases TTBK1/2 promote accumulation of pathological TDP-43

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    Pathological aggregates of phosphorylated TDP-43 characterize amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD-TDP), two devastating groups of neurodegenerative disease. Kinase hyperactivity may be a consistent feature of ALS and FTLD-TDP, as phosphorylated TDP-43 is not observed in the absence of neurodegeneration. By examining changes in TDP-43 phosphorylation state, we have identified kinases controlling TDP-43 phosphorylation in a C. elegans model of ALS. In this kinome-wide survey, we identified homologs of the tau tubulin kinases 1 and 2 (TTBK1 and TTBK2), which were also identified in a prior screen for kinase modifiers of TDP-43 behavioral phenotypes. Using refined methodology, we demonstrate TTBK1 and TTBK2 directly phosphorylate TDP-43 in vitro and promote TDP-43 phosphorylation in mammalian cultured cells. TTBK1/2 overexpression drives phosphorylation and relocalization of TDP-43 from the nucleus to cytoplasmic inclusions reminiscent of neuropathologic changes in disease states. Furthermore, protein levels of TTBK1 and TTBK2 are increased in frontal cortex of FTLD-TDP patients, and TTBK1 and TTBK2 co-localize with TDP-43 inclusions in ALS spinal cord. These kinases may represent attractive targets for therapeutic intervention for TDP-43 proteinopathies such as ALS and FTLD-TDP

    Association of cerebrospinal fluid Aβ42 with A2M gene in cognitively normal subjects

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    Low cerebrospinal fluid (CSF) Aβ42 levels correlate with increased brain Aβ deposition in Alzheimer’s disease (AD), which suggests a disruption in the degradation and clearance of Aβ from the brain. In addition, APOE ε4 carriers have lower CSF Aβ42 levels than non-carriers. The hypothesis of this investigation was that CSF Aβ42 levels correlate with regulatory region variation in genes that are biologically associated with degradation or clearance of Aβ from the brain. CSF Aβ42 levels were tested for associations with Aβ degradation and clearance genes and APOE ε4. Twenty-four SNPs located within the 5′ and 3′ regions of 12 genes were analyzed. The study sample consisted of 99 AD patients and 168 cognitively normal control subjects. CSF Aβ42 levels were associated with APOE ε4 status in controls but not in AD patientsA2M regulatory region SNPs were also associated with CSF Aβ42 levels in controls, but not in AD patients, even after adjusting for APOE ε4. These results suggest that genetic variation within the A2M gene influences CSF Aβ42 levels

    Rasagiline Effects on Glucose Metabolism, Cognition, and Tau in Alzheimer’s Dementia

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    Background: A Phase II proof of concept (POC) randomized clinical trial was conducted to evaluate the effects of rasagiline, a monoamine oxidase B (MAO-B) inhibitor approved for Parkinson disease, in mild to moderate Alzheimer\u27s disease (AD). The primary objective was to determine if 1 mg of rasagiline daily for 24 weeks is associated with improved regional brain metabolism (fluorodeoxyglucose–positron emission tomography [FDG-PET]) compared to placebo. Secondary objectives included measurement of effects on tau PET and evaluation of directional consistency of clinical end points. Methods: This was a double-blind, parallel group, placebo-controlled, community-based, three-site trial of 50 participants randomized 1:1 to receive oral rasagiline or placebo (NCT02359552). FDG-PET was analyzed for the presence of an AD-like pattern as an inclusion criterion and as a longitudinal outcome using prespecified regions of interest and voxel-based analyses. Tau PET was evaluated at baseline and longitudinally. Clinical outcomes were analyzed using an intention-to-treat (ITT) model. Results: Fifty patients were randomized and 43 completed treatment. The study met its primary end point, demonstrating favorable change in FDG-PET differences in rasagiline versus placebo in middle frontal (P \u3c 0.025), anterior cingulate (P \u3c 0.041), and striatal (P \u3c 0.023) regions. Clinical measures showed benefit in quality of life (P \u3c 0.04). Digit Span, verbal fluency, and Neuropsychiatric Inventory (NPI) showed non-significant directional favoring of rasagiline; no effects were observed in Alzheimer\u27s Disease Assessment Scale-Cognitive Subscale (ADAS-cog) or activities of daily living. Rasagiline was generally well tolerated with low rates of adverse events and notably fewer neuropsychiatric symptoms in the active treatment group. Discussion: These outcomes illustrate the potential benefits of rasagiline on clinical and neuroimaging measures in patients with mild to moderate AD. Rasagiline appears to affect neuronal activity in frontostriatal pathways, with associated clinical benefit potential warranting a more fully powered trial. This study illustrated the potential benefit of therapeutic repurposing and an experimental medicine proof-of-concept design with biomarkers to characterize patient and detect treatment response

    Artificial Intelligence Framework Identifies Candidate Targets for Drug Repurposing in Alzheimer’s Disease

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    Background: Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer’s disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. Methods: To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein–protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein–protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells. Results: Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861–0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862–0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD. Conclusions: In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD

    DJ-1 isoforms in whole blood as potential biomarkers of Parkinson disease

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    DJ-1 is a multifunctional protein that plays an important role in oxidative stress, cell death, and synucleinopathies, including Parkinson disease. Previous studies have demonstrated that total DJ-1 levels decrease in the cerebrospinal fluid, but do not change significantly in human plasma from patients with Parkinson disease when compared with controls. In this study, we measured total DJ-1 and its isoforms in whole blood of patients with Parkinson disease at various stages, Alzheimer disease, and healthy controls to identify potential peripheral biomarkers of PD. In an initial discovery study of 119 subjects, 7 DJ-1 isoforms were reliably detected, and blood levels of those with 4-hydroxy-2-nonenal modifications were discovered to be altered in late-stage Parkinson disease. This result was further confirmed in a validation study of another 114 participants, suggesting that, unlike total DJ-1 levels, post-translationally modified isoforms of DJ-1 from whole blood are candidate biomarkers of late-stage Parkinson disease

    Biomarker-driven phenotyping in Parkinson's disease: A translational missing link in disease-modifying clinical trials

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    Past clinical trials of putative neuroprotective therapies have targeted PD as a single pathogenic disease entity. From an Oslerian clinicopathological perspective, the wide complexity of PD converges into Lewy bodies and justifies a reductionist approach to PD: A single-mechanism therapy can affect most of those sharing the classic pathological hallmark. From a systems-biology perspective, PD is a group of disorders that, while related by sharing the feature of nigral dopamine-neuron degeneration, exhibit unique genetic, biological, and molecular abnormalities, which probably respond differentially to a given therapeutic approach, particularly for strategies aimed at neuroprotection. Under this model, only biomarker-defined, homogenous subtypes of PD are likely to respond optimally to therapies proven to affect the biological processes within each subtype. Therefore, we suggest that precision medicine applied to PD requires a reevaluation of the biomarker-discovery effort. This effort is currently centered on correlating biological measures to clinical features of PD and on identifying factors that predict whether various prodromal states will convert into the classical movement disorder. We suggest, instead, that subtyping of PD requires the reverse view, where abnormal biological signals (i.e., biomarkers), rather than clinical definitions, are used to define disease phenotypes. Successful development of disease-modifying strategies will depend on how relevant the specific biological processes addressed by an intervention are to the pathogenetic mechanisms in the subgroup of targeted patients. This precision-medicine approach will likely yield smaller, but well-defined, subsets of PD amenable to successful neuroprotection.Fil: Espay, Alberto J.. University of Cincinnati; Estados UnidosFil: Schwarzschild, Michael A.. Massachusetts General Hospital; Estados UnidosFil: Tanner, Caroline M.. University of California; Estados UnidosFil: Fernandez, Hubert H.. Cleveland Clinic; Estados UnidosFil: Simon, David K.. Harvard Medical School; Estados UnidosFil: Leverenz, James B.. Cleveland Clinic; Estados UnidosFil: Merola, Aristide. University of Cincinnati; Estados UnidosFil: Chen Plotkin, Alice. University of Pennsylvania; Estados UnidosFil: Brundin, Patrik. Van Andel Research Institute. Center for Neurodegenerative Science; Estados UnidosFil: Kauffman, Marcelo Andres. Universidad Austral; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; ArgentinaFil: Erro, Roberto. Universita di Verona; Italia. University College London; Reino UnidoFil: Kieburtz, Karl. University of Rochester Medical Center; Estados UnidosFil: Woo, Daniel. University of Cincinnati; Estados UnidosFil: Macklin, Eric A.. Massachusetts General Hospital; Estados UnidosFil: Standaert, David G.. University of Alabama at Birmingahm; Estados UnidosFil: Lang, Anthony E.. University of Toronto; Canad
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