Browsing by Author "Han, Baoguang"

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    Cognitive Impairment Precedes and Predicts Functional Impairment in Mild Alzheimer’s Disease
    (IOS, 2015-07) Liu-Seifert, Hong; Siemers, Eric; Price, Karen; Han, Baoguang; Selzler, Katherine J.; Henley, David; Sundell, Karen; Aisen, Paul; Cummings, Jeffrey; Raskin, Joel; Mohs, Richard; Department of Neurological Surgery, IU School of Medicine
    Abstract Background: The temporal relationship of cognitive deficit and functional impairment in Alzheimer’s disease (AD) is not well characterized. Recent analyses suggest cognitive decline predicts subsequent functional decline throughout AD progression. Objective: To better understand the relationship between cognitive and functional decline in mild AD using autoregressive cross-lagged (ARCL) panel analyses in several clinical trials. Methods: Data included placebo patients with mild AD pooled from two multicenter, double-blind, Phase 3 solanezumab (EXPEDITION/2) or semagacestat (IDENTITY/2) studies, and from AD patients participating in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cognitive and functional outcomes were assessed using AD Assessment Scale-Cognitive subscale (ADAS-Cog), AD Cooperative Study-Activities of Daily Living instrumental subscale (ADCS-iADL), or Functional Activities Questionnaire (FAQ), respectively. ARCL panel analyses evaluated relationships between cognitive and functional impairment over time. Results: In EXPEDITION, ARCL panel analyses demonstrated cognitive scores significantly predicted future functional impairment at 5 of 6 time points, while functional scores predicted subsequent cognitive scores in only 1 of 6 time points. Data from IDENTITY and ADNI programs yielded consistent results whereby cognition predicted subsequent function, but not vice-versa. Conclusions: Analyses from three databases indicated cognitive decline precedes and predicts subsequent functional decline in mild AD dementia, consistent with previously proposed hypotheses, and corroborate recent publications using similar methodologies. Cognitive impairment may be used as a predictor of future functional impairment in mild AD dementia and can be considered a critical target for prevention strategies to limit future functional decline in the dementia process.
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    Regulation of expression by promoters versus internal ribosome entry site in the 5′-untranslated sequence of the human cyclin-dependent kinase inhibitor p27
    (Oxford University Press, 2005-07-01) Liu, Zhaoqian; Dong, Zizheng; Han, Baoguang; Yang, Youyun; Liu, Yang; Zhang, Jian-Ting; Pharmacology and Toxicology, School of Medicine
    p27 kip1 regulates cell proliferation by binding to and inhibiting the activity of cyclin-dependent kinases and its expression oscillates with cell cycle. Recently, it has been suggested from studies using the traditional dicistronic DNA assay that the expression of p27 kip1 is regulated by internal ribosome entry site (IRES)-mediated translation initiation, and several RNA-binding protein factors were thought to play some role in this regulation. Considering the inevitable drawbacks of the dicistronic DNA assay, which could mislead a promoter activity or alternative splicing to IRES as previously demonstrated, we decided to reanalyze the 5′-untranslated region (5′-UTR) sequence of p27 kip1 and test whether it contains an IRES element or a promoter using more stringent methods, such as dicistronic RNA and promoterless dicistronic and monocistronic DNA assays. We found that the 5′-UTR sequence of human p27 kip1 does not have any significant IRES activity. The previously observed IRES activities are likely generated from the promoter activities present in the 5′-UTR sequences of p27 kip1 . The findings in this study indicate that transcriptional regulation likely plays an important role in p27 kip1 expression, and the mechanism of regulation of p27 expression by RNA-binding factors needs to be re-examined. The findings in this study also further enforce the importance that more stringent studies, such as promoterless dicistronic and monocistronic DNA and dicistronic RNA tests, are required to safeguard any future claims of cellular IRES.
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    Statistical analysis of clinical trial data using Monte Carlo methods
    (2014-07-11) Han, Baoguang; Gao, Sujuan; Yu, Menggang; Yu, Zhangsheng; Liu, Yunlong
    In medical research, data analysis often requires complex statistical methods where no closed-form solutions are available. Under such circumstances, Monte Carlo (MC) methods have found many applications. In this dissertation, we proposed several novel statistical models where MC methods are utilized. For the first part, we focused on semicompeting risks data in which a non-terminal event was subject to dependent censoring by a terminal event. Based on an illness-death multistate survival model, we proposed flexible random effects models. Further, we extended our model to the setting of joint modeling where both semicompeting risks data and repeated marker data are simultaneously analyzed. Since the proposed methods involve high-dimensional integrations, Bayesian Monte Carlo Markov Chain (MCMC) methods were utilized for estimation. The use of Bayesian methods also facilitates the prediction of individual patient outcomes. The proposed methods were demonstrated in both simulation and case studies. For the second part, we focused on re-randomization test, which is a nonparametric method that makes inferences solely based on the randomization procedure used in clinical trials. With this type of inference, Monte Carlo method is often used for generating null distributions on the treatment difference. However, an issue was recently discovered when subjects in a clinical trial were randomized with unbalanced treatment allocation to two treatments according to the minimization algorithm, a randomization procedure frequently used in practice. The null distribution of the re-randomization test statistics was found not to be centered at zero, which comprised power of the test. In this dissertation, we investigated the property of the re-randomization test and proposed a weighted re-randomization method to overcome this issue. The proposed method was demonstrated through extensive simulation studies.