Browsing by Author "Liu, Lei"

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    A semiparametric recurrent events model with time-varying coefficients
    (Wiley Blackwell (John Wiley & Sons), 2013-03-15) Yu, Zhangsheng; Liu, Lei; Bravata, Dawn M.; Williams, Linda S.; Tepper, Robert S.; Department of Biostatistics, Richard M. Fairbanks School of Public Health
    We consider a recurrent events model with time-varying coefficients motivated by two clinical applications. We use a random effects (Gaussian frailty) model to describe the intensity of recurrent events. The model can accommodate both time-varying and time-constant coefficients. We use the penalized spline method to estimate the time-varying coefficients. We use Laplace approximation to evaluate the penalized likelihood without a closed form. We estimate the smoothing parameters in a similar way to variance components. We conduct simulations to evaluate the performance of the estimates for both time-varying and time-independent coefficients. We apply this method to analyze two data sets: a stroke study and a child wheeze study.
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    System modeling reveals the molecular mechanisms of HSC cell cycle alteration mediated by Maff and Egr3 under leukemia
    (BMC, 2017-10-03) Li, Rudong; Wang, Yin; Cheng, Hui; Liu, Gang; Cheng, Tao; Liu, Yunlong; Liu, Lei; Medical and Molecular Genetics, School of Medicine
    Background Molecular mechanisms of the functional alteration of hematopoietic stem cells (HSCs) in leukemic environment attract intensive research interests. As known in previous researches, Maff and Egr3 are two important genes having opposite functions on cell cycle; however, they are both highly expressed in HSCs under leukemia. Hence, exploring the molecular mechanisms of how the genes act on cell cycle will help revealing the functional alteration of HSCs. Results We herein utilize the bioinformatic resources to computationally model the acting mechanisms of Maff and Egr3 on cell cycle. Using the data of functional experiments as reference, molecular acting mechanisms are optimally enumerated through model selection. The results are consolidated by evidences from gene sequence analysis, thus having enhanced the confidence of our pilot findings, which suggest that HSCs possibly undergo a “adaptation - suppression” process in response to the malignant environment of leukemia. Conclusion As a pilot research, our results may provide valuable insights for further experimental studies. Meanwhile, our research method combining computational modeling and data from functional experiments can be worthwhile for knowledge discovery; and it can be generalized and extended to other biological/biomedical studies. Electronic supplementary material The online version of this article (doi:10.1186/s12918-017-0467-4) contains supplementary material, which is available to authorized users.
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    The Association between Postload Plasma Glucose Levels and 38-Year Mortality Risk of Coronary Heart Disease: The Prospective NHLBI Twin Study
    (Public Library of Science, 2013-07-19) Dai, Jun; Krasnow, Ruth E.; Liu, Lei; Sawada, Stephen G.; Reed, Terry; Medicine, School of Medicine
    Background: Due to the paucity of direct evidence, we aimed to evaluate whether the association between postload plasma glucose levels (ppGlucose) and long-term risk of mortality from coronary heart disease was independent of or attributable to genes and common environment. Methods and findings: From the prospective National Heart, Lung, and Blood Institute (NHLBI) Twin Study, we included 903 middle-aged male twins, who were nondiabetic, free of coronary heart disease at baseline (1969-1973), and followed for up to 38 years for coronary heart, cardiovascular, and all-cause mortality. Frailty survival models were used to estimate hazard ratio (HR) for various associations: overall (equivalent to singleton population association), within-pair (controlling for genes and environment common to co-twins), and between-pair association (reflecting influences of common factors). Overall associations were statistically significant for coronary heart and cardiovascular but not all-cause deaths after controlling for known risk factors. The associations were not statistically significant in within-pair analyses. The within-pair association was not statistically different by zygosity for specific and all-cause death risk. After the full adjustment for known risk factors, HR (95% confidence interval) for within-pair association was 1.07 (0.90, 1.28), 1.06 (0.94, 1.19), and 0.99 (0.94, 1.05) for coronary heart, cardiovascular, and all-cause mortality, respectively. The fully adjusted between-pair associations were statistically significant for specific and all-cause death risk: a 50 mg/dL increase in the mean value of ppGlucose for a twin pair was associated with a raised death risk [HR (95% confidence interval) 1.15 (1.02, 1.30), 1.10 (1.02, 1.20), and 1.05 (1.01, 1.09) for coronary heart, cardiovascular, and all-cause mortality, respectively]. Between-pair association was significant in dizygotic but not in monozygotic twins. Conclusion: The positive association between ppGlucose and long-term coronary heart mortality risk is largely explained by factors shared between co-twins, including familial factors; however, within-pair effects cannot be absolutely excluded.