Browsing by Author "Yu, Peng"

Now showing 1 - 8 of 8
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    APX3330 Promotes Neurorestorative Effects after Stroke in Type One Diabetic Rats
    (Buck Institute for Age Research, 2018-06-01) Yan, Tao; Venkat, Poornima; Chopp, Michael; Zacharek, Alex; Yu, Peng; Ning, Ruizhuo; Qiao, Xiaoxi; Kelley, Mark R.; Chen, Jieli; Medicine, School of Medicine
    APX3330 is a selective inhibitor of APE1/Ref-1 redox activity. In this study, we investigate the therapeutic effects and underlying mechanisms of APX3330 treatment in type one diabetes mellitus (T1DM) stroke rats. Adult male Wistar rats were induced with T1DM and subjected to transient middle cerebral artery occlusion (MCAo) and treated with either PBS or APX3330 (10mg/kg, oral gavage) starting at 24h after MCAo, and daily for 14 days. Rats were sacrificed at 14 days after MCAo and, blood brain barrier (BBB) permeability, ischemic lesion volume, immunohistochemistry, cell death assay, Western blot, real time PCR, and angiogenic ELISA array were performed. Compared to PBS treatment, APX3330 treatment of stroke in T1DM rats significantly improves neurological functional outcome, decreases lesion volume, and improves BBB integrity as well as decreases total vessel density and VEGF expression, while significantly increases arterial density in the ischemic border zone (IBZ). APX3330 significantly increases myelin density, oligodendrocyte number, oligodendrocyte progenitor cell number, synaptic protein expression, and induces M2 macrophage polarization in the IBZ of T1DM stroke rats. Compared to PBS treatment, APX3330 treatment significantly decreases plasminogen activator inhibitor type-1 (PAI-1), monocyte chemotactic protein-1 and matrix metalloproteinase 9 (MMP9) and receptor for advanced glycation endproducts expression in the ischemic brain of T1DM stroke rats. APX3330 treatment significantly decreases cell death and MMP9 and PAI-1 gene expression in cultured primary cortical neurons subjected to high glucose and oxygen glucose deprivation, compared to untreated control cells. APX3330 treatment increases M2 macrophage polarization and decreases inflammatory factor expression in the ischemic brain as well as promotes neuroprotective and neurorestorative effects after stroke in T1DM rats.
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    ASXL1 interacts with the cohesin complex to maintain chromatid separation and gene expression for normal hematopoiesis
    (American Association for the Advancement of Science, 2017-01-20) Li, Zhaomin; Zhang, Peng; Yan, Aimin; Guo, Zhengyu; Ban, Yuguang; Li, Jin; Chen, Shi; Yang, Hui; He, Yongzheng; Li, Jianping; Guo, Ying; Zhang, Wen; Hajiramezanali, Ehsan; An, Huangda; Fajardo, Darlene; Harbour, J. William; Ruan, Yijun; Nimer, Stephen D.; Yu, Peng; Chen, Xi; Xu, Mingjiang; Yang, Feng-Chun; Department of Pediatrics, IU School of Medicine
    ASXL1 is frequently mutated in a spectrum of myeloid malignancies with poor prognosis. Loss of Asxl1 leads to myelodysplastic syndrome-like disease in mice; however, the underlying molecular mechanisms remain unclear. We report that ASXL1 interacts with the cohesin complex, which has been shown to guide sister chromatid segregation and regulate gene expression. Loss of Asxl1 impairs the cohesin function, as reflected by an impaired telophase chromatid disjunction in hematopoietic cells. Chromatin immunoprecipitation followed by DNA sequencing data revealed that ASXL1, RAD21, and SMC1A share 93% of genomic binding sites at promoter regions in Lin-cKit+ (LK) cells. We have shown that loss of Asxl1 reduces the genome binding of RAD21 and SMC1A and alters the expression of ASXL1/cohesin target genes in LK cells. Our study underscores the ASXL1-cohesin interaction as a novel means to maintain normal sister chromatid separation and regulate gene expression in hematopoietic cells.
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    Empirically Defining Trajectories of Late-Life Cognitive and Functional Decline
    (IOS, 2015-11) Hochstetler, Helen; Trzepacz, Paula T.; Wang, Shufang; Yu, Peng; Case, Michael; Henley, David B.; Degenhardt, Elisabeth; Leoutsakos, Jeannie-Marie; Lyketsos, Constantine G.; Department of Psychiatry, IU School of Medicine
    Background: Alzheimer’s disease (AD) is associated with variable cognitive and functional decline, and it is difficult to predict who will develop the disease and how they will progress. Objective: This exploratory study aimed to define latent classes from participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database who had similar growth patterns of both cognitive and functional change using Growth Mixture Modeling (GMM), identify characteristics associated with those trajectories, and develop a decision tree using clinical predictors to determine which trajectory, as determined by GMM, individuals will most likely follow. Methods: We used ADNI early mild cognitive impairment (EMCI), late MCI (LMCI), AD dementia, and healthy control (HC) participants with known amyloid-β status and follow-up assessments on the Alzheimer’s Disease Assessment Scale - Cognitive Subscale or the Functional Activities Questionnaire (FAQ) up to 24 months postbaseline. GMM defined trajectories. Classification and Regression Tree (CART) used certain baseline variables to predict likely trajectory path. Results: GMM identified three trajectory classes (C): C1 (n = 162, 13.6%) highest baseline impairment and steepest pattern of cognitive/functional decline; C3 (n = 819, 68.7%) lowest baseline impairment and minimal change on both; C2 (n = 211, 17.7%) intermediate pattern, worsening on both, but less steep than C1. C3 had fewer amyloid- or apolipoprotein-E ɛ4 (APOE4) positive and more healthy controls (HC) or EMCI cases. CART analysis identified two decision nodes using the FAQ to predict likely class with 82.3% estimated accuracy. Conclusions: Cognitive/functional change followed three trajectories with greater baseline impairment and amyloid and APOE4 positivity associated with greater progression. FAQ may predict trajectory class.
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    Enrichment of clinical trials in MCI due to AD using markers of amyloid and neurodegeneration
    (American Academy of Neurology (AAN), 2016-09-20) Wolz, Robin; Schwarz, Adam J.; Gray, Katherine R.; Yu, Peng; Hill, Derek L.G.; Radiology and Imaging Sciences, School of Medicine
    Objective: To investigate the effect of enriching mild cognitive impairment (MCI) clinical trials using combined markers of amyloid pathology and neurodegeneration. Methods: We evaluate an implementation of the recent National Institute for Aging–Alzheimer's Association (NIA-AA) diagnostic criteria for MCI due to Alzheimer disease (AD) as inclusion criteria in clinical trials and assess the effect of enrichment with amyloid (A+), neurodegeneration (N+), and their combination (A+N+) on the rate of clinical progression, required sample sizes, and estimates of trial time and cost. Results: Enrichment based on an individual marker (A+ or N+) substantially improves all assessed trial characteristics. Combined enrichment (A+N+) further improves these results with a reduction in required sample sizes by 45% to 60%, depending on the endpoint. Conclusions: Operationalizing the NIA-AA diagnostic criteria for clinical trial screening has the potential to substantially improve the statistical power of trials in MCI due to AD by identifying a more rapidly progressing patient population.
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    Florbetapir F18 PET Amyloid Neuroimaging and Characteristics in Patients With Mild and Moderate Alzheimer Dementia
    (Elsevier, 2016-03) Degenhardt, Elisabeth K.; Witte, Michael M.; Case, Michael G.; Yu, Peng; Henley, David B.; Hochstetler, Helen M.; D'Souza, Deborah N.; Trzepacz, Paula T.; Department of Psychiatry, IU School of Medicine
    Background Clinical diagnosis of Alzheimer disease (AD) is challenging, with a 70.9%–87.3% sensitivity and 44.3%–70.8% specificity, compared with autopsy diagnosis. Florbetapir F18 positron emission tomography (FBP-PET) estimates beta-amyloid plaque density antemortem. Methods Of 2052 patients (≥55 years old) clinically diagnosed with mild or moderate AD dementia from 2 solanezumab clinical trials, 390 opted to participate in a FBP-PET study addendum. We analyzed baseline prerandomization characteristics. Results A total of 22.4% had negative FBP-PET scans, whereas 72.5% of mild and 86.9% of moderate AD patients had positive results. No baseline clinical variable reliably differentiated negative from positive FBP-PET scan groups. Conclusions These data confirm the challenges of correctly diagnosing AD without using biomarkers. FBP-PET can aid AD dementia differential diagnosis by detecting amyloid pathology antemortem, even when the diagnosis of AD is made by expert clinicians.
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    Florbetapir positron emission tomography and cerebrospinal fluid biomarkers
    (Elsevier, 2015-08) Hake, Ann Marie; Trzepacz, Paula T.; Wang, Shufang; Yu, Peng; Case, Michael; Hochstetler, Helen; Witte, Michael M.; Degenhardt, Elisabeth K.; Dean, Robert A.; Department of Neurology, IU School of Medicine
    BACKGROUND: We evaluated the relationship between florbetapir-F18 positron emission tomography (FBP PET) and cerebrospinal fluid (CSF) biomarkers. METHODS: Alzheimer's Disease Neuroimaging Initiative-Grand Opportunity and Alzheimer's Disease Neuroimaging Initiative 2 (GO/2) healthy control (HC), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia subjects with clinical measures and CSF collected ±90 days of FBP PET data were analyzed using correlation and logistic regression. RESULTS: In HC and MCI subjects, FBP PET anterior and posterior cingulate and composite standard uptake value ratios correlated with CSF amyloid beta (Aβ1-42) and tau/Aβ1-42 ratios. Using logistic regression, Aβ1-42, total tau (t-tau), phosphorylated tau181P (p-tau), and FBP PET composite each differentiated HC versus AD. Aβ1-42 and t-tau distinguished MCI versus AD, without additional contribution by FBP PET. Total tau and p-tau added discriminative power to FBP PET when classifying HC versus AD. CONCLUSION: Based on cross-sectional diagnostic groups, both amyloid and tau measures distinguish healthy from demented subjects. Longitudinal analyses are needed.
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    Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer’s Disease
    (Karger, 2016-03) Trzepacz, Paula T.; Hochstetler, Helen; Yu, Peng; Castelluccio, Peter; Witte, Michael M.; Dell'Agnello, Grazia; Degenhardt, Elisabeth; Department of Psychiatry, IU School of Medicine
    Aims: To assess how hippocampal volume (HV) from volumetric magnetic resonance imaging (vMRI) is related to the amyloid status at different stages of Alzheimer's disease (AD) and its relevance to patient care. Methods: We evaluated the ability of HV to predict the florbetapir positron emission tomography (PET) amyloid positive/negative status by group in healthy controls (HC, n = 170) and early/late mild cognitive impairment (EMCI, n = 252; LMCI, n = 136), and AD dementia (n = 75) subjects from the Alzheimer's Disease Neuroimaging Initiative Grand Opportunity (ADNI-GO) and ADNI2. Logistic regression analyses, including elastic net classification modeling with 10-fold cross-validation, were used with age and education as covariates. Results: HV predicted amyloid status only in LMCI using either logistic regression [area under the curve (AUC) = 0.71, p < 0.001] or elastic net classification modeling [positive predictive value (PPV) = 72.7%]. In EMCI, age (AUC = 0.70, p < 0.0001) and age and/or education (PPV = 63.1%), but not HV, predicted amyloid status. Conclusion: Using clinical neuroimaging, HV predicted amyloid status only in LMCI, suggesting that HV is not a biomarker surrogate for amyloid PET in clinical applications across the full diagnostic spectrum.
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    Subscale Validation of the Neuropsychiatric Inventory Questionnaire (NPI-Q): Comparison of ADNI and NACC Cohorts
    (Elsevier, 2013) Trzepacz, Paula T.; Saykin, Andrew; Yu, Peng; Bhamditipati, Phani; Sun, Jia; Dennehy, Ellen B.; Willis, Brian; Cummings, Jeffrey L.; Alzheimer's Disease Neuroimaging Intiative; Radiology and Imaging Sciences, School of Medicine
    Objective: Neuropsychiatric symptoms are prevalent in mild cognitive impairment (MCI) and Alzheimer disease (AD) and commonly measured using the Neuropsychiatric Inventory (NPI). Based on existing exploratory literature, we report preliminary validation of three NPI Questionnaire (NPI-Q-10) subscales that measure clinically meaningful symptom clusters. Methods: Cross-sectional results for three subscales (NPI-Q-4-Frontal, NPI-Q-4-Agitation/Aggression, NPI-Q-3-Mood) in amnestic MCI and AD dementia cases from the National Alzheimer's Coordinating Center (NACC) and Alzheimer's Disease Neuroimaging Initiative (ADNI) databases were analyzed using confirmatory unrotated principal component analysis. Results: ADNI contributed 103 MCI, 90 MCI converters, and 112 AD dementia cases, whereas NACC contributed 1,042 MCI, 763 MCI converters, and 3,048 AD dementia cases. NACC had higher baseline mean age (75.7 versus 74.6), and more impaired mean scores (at month 24) on Mini-Mental State Exam (19.5 versus 22.4) and NPI-Q-10 (5.0 versus 4.3), and all NPI-Q subscales than ADNI. Medians were not different between cohorts for NPI-Q-4-Agitation/Aggression, and NPI-Q-3-Mood, however. Each item on all scales/subscales contributed variance in principal component analysis Pareto plots. All items in Factor (F) 1 for each scale/subscale projected in a positive direction on biplots (revealing coherence), whereas F2 and F3 items showed more spatial separation (revealing independence). There were remarkable similarities between cohorts for factor loadings and spatial patterns of item projections, although factor item identities varied somewhat, especially beyond F1. Conclusion: The similar pattern of results across two cohorts support validity of these subscales, which are worthy of further psychometric evaluation in MCI and AD patients and preliminary application in clinical settings.