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A Genetic Variant (COMT) Coding Dopaminergic Activity Predicts Personality Traits in Healthy Elderly.

Personality and individual differences

Kotyuk E, Duchek J, Head D, Szekely A, Goate AM, Balota DA.
PMID: 25960587
Pers Individ Dif. 2015 Aug 01;82:61-66. doi: 10.1016/j.paid.2015.03.012.

Association studies between the NEO five factor personality inventory and COMT rs4680 have focused on young adults and the results have been inconsistent. However, personality and cortical changes with age may put older adults in a more sensitive range...

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Kotyuk E, Duchek J, Head D, et al. A Genetic Variant (COMT) Coding Dopaminergic Activity Predicts Personality Traits in Healthy Elderly. Pers Individ Dif. 2015;82:61-66doi: 10.1016/j.paid.2015.03.012.
Kotyuk, E., Duchek, J., Head, D., Szekely, A., Goate, A. M., & Balota, D. A. (2015). A Genetic Variant (COMT) Coding Dopaminergic Activity Predicts Personality Traits in Healthy Elderly. Personality and individual differences, 8261-66. https://doi.org/10.1016/j.paid.2015.03.012
Kotyuk, Eszter, et al. "A Genetic Variant (COMT) Coding Dopaminergic Activity Predicts Personality Traits in Healthy Elderly." Personality and individual differences vol. 82 (2015): 61-66. doi: https://doi.org/10.1016/j.paid.2015.03.012
Kotyuk E, Duchek J, Head D, Szekely A, Goate AM, Balota DA. A Genetic Variant (COMT) Coding Dopaminergic Activity Predicts Personality Traits in Healthy Elderly. Pers Individ Dif. 2015 Aug 01;82:61-66. doi: 10.1016/j.paid.2015.03.012. PMID: 25960587; PMCID: PMC4422069.
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A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium.

Alzheimer's & dementia (Amsterdam, Netherlands)

Gross AL, Hassenstab JJ, Johnson SC, Clark LR, Resnick SM, Kitner-Triolo M, Masters CL, Maruff P, Morris JC, Soldan A, Pettigrew C, Albert MS.
PMID: 28653035
Alzheimers Dement (Amst). 2017 May 30;8:147-155. doi: 10.1016/j.dadm.2017.05.003. eCollection 2017.

INTRODUCTION: We established a method for diagnostic harmonization across multiple studies of preclinical Alzheimer's disease and validated the method by examining its relationship with clinical status and cognition.METHODS: Cognitive and clinical data were used from five studies (RESULTS: In...

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Gross AL, Hassenstab JJ, Johnson SC, et al. A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. Alzheimers Dement (Amst). 2017;8:147-155doi: 10.1016/j.dadm.2017.05.003.
Gross, A. L., Hassenstab, J. J., Johnson, S. C., Clark, L. R., Resnick, S. M., Kitner-Triolo, M., Masters, C. L., Maruff, P., Morris, J. C., Soldan, A., Pettigrew, C., & Albert, M. S. (2017). A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. Alzheimer's & dementia (Amsterdam, Netherlands), 8147-155. https://doi.org/10.1016/j.dadm.2017.05.003
Gross, Alden L, et al. "A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium." Alzheimer's & dementia (Amsterdam, Netherlands) vol. 8 (2017): 147-155. doi: https://doi.org/10.1016/j.dadm.2017.05.003
Gross AL, Hassenstab JJ, Johnson SC, Clark LR, Resnick SM, Kitner-Triolo M, Masters CL, Maruff P, Morris JC, Soldan A, Pettigrew C, Albert MS. A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. Alzheimers Dement (Amst). 2017 May 30;8:147-155. doi: 10.1016/j.dadm.2017.05.003. eCollection 2017. PMID: 28653035; PMCID: PMC5476965.
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Autosomal Dominant Alzheimer Disease: A Unique Resource to Study CSF Biomarker Changes in Preclinical AD.

Frontiers in neurology

Schindler SE, Fagan AM.
PMID: 26175713
Front Neurol. 2015 Jun 29;6:142. doi: 10.3389/fneur.2015.00142. eCollection 2015.

Our understanding of the pathogenesis of Alzheimer disease (AD) has been greatly influenced by investigation of rare families with autosomal dominant mutations that cause early onset AD. Mutations in the genes coding for amyloid precursor protein (APP), presenilin 1...

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Schindler SE, Fagan AM. Autosomal Dominant Alzheimer Disease: A Unique Resource to Study CSF Biomarker Changes in Preclinical AD. Front Neurol. 2015;6:142doi: 10.3389/fneur.2015.00142.
Schindler, S. E., & Fagan, A. M. (2015). Autosomal Dominant Alzheimer Disease: A Unique Resource to Study CSF Biomarker Changes in Preclinical AD. Frontiers in neurology, 6142. https://doi.org/10.3389/fneur.2015.00142
Schindler, Suzanne Elizabeth, and Fagan, Anne M. "Autosomal Dominant Alzheimer Disease: A Unique Resource to Study CSF Biomarker Changes in Preclinical AD." Frontiers in neurology vol. 6 (2015): 142. doi: https://doi.org/10.3389/fneur.2015.00142
Schindler SE, Fagan AM. Autosomal Dominant Alzheimer Disease: A Unique Resource to Study CSF Biomarker Changes in Preclinical AD. Front Neurol. 2015 Jun 29;6:142. doi: 10.3389/fneur.2015.00142. eCollection 2015. PMID: 26175713; PMCID: PMC4483518.
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Diffusion tensor MRI as a biomarker in axonal and myelin damage.

Imaging in medicine

Aung WY, Mar S, Benzinger TL.
PMID: 24795779
Imaging Med. 2013 Oct 01;5(5):427-440. doi: 10.2217/iim.13.49.

Diffusion tensor imaging has been used extensively as a research tool to understand the structural changes associated with white matter pathology. Using water diffusion as the basis to construct anatomic details, diffusion tensor imaging offers the potential to identify...

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Aung WY, Mar S, Benzinger TL. Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging Med. 2013;5(5):427-440doi: 10.2217/iim.13.49.
Aung, W. Y., Mar, S., & Benzinger, T. L. (2013). Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging in medicine, 5(5), 427-440. https://doi.org/10.2217/iim.13.49
Aung, Wint Yan, et al. "Diffusion tensor MRI as a biomarker in axonal and myelin damage." Imaging in medicine vol. 5,5 (2013): 427-440. doi: https://doi.org/10.2217/iim.13.49
Aung WY, Mar S, Benzinger TL. Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging Med. 2013 Oct 01;5(5):427-440. doi: 10.2217/iim.13.49. PMID: 24795779; PMCID: PMC4004089.
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Youden index and Associated Cut-points for Three Ordinal Diagnostic Groups.

Communications in statistics: Simulation and computation

Luo J, Xiong C.
PMID: 23794784
Commun Stat Simul Comput. 2013 Jan;42(6):1213-1234. doi: 10.1080/03610918.2012.661906.

Directly relating to sensitivity and specificity and providing an optimal cut-point which maximizes overall classification effectiveness for diagnosis purpose, the Youden index has been frequently utilized in biomedical diagnosis practice. Current application of the Youden index is limited to...

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Luo J, Xiong C. Youden index and Associated Cut-points for Three Ordinal Diagnostic Groups. Commun Stat Simul Comput. 2013;42(6):1213-1234doi: 10.1080/03610918.2012.661906.
Luo, J., & Xiong, C. (2013). Youden index and Associated Cut-points for Three Ordinal Diagnostic Groups. Communications in statistics: Simulation and computation, 42(6), 1213-1234. https://doi.org/10.1080/03610918.2012.661906
Luo, Jingqin, and Xiong, Chengjie. "Youden index and Associated Cut-points for Three Ordinal Diagnostic Groups." Communications in statistics: Simulation and computation vol. 42,6 (2013): 1213-1234. doi: https://doi.org/10.1080/03610918.2012.661906
Luo J, Xiong C. Youden index and Associated Cut-points for Three Ordinal Diagnostic Groups. Commun Stat Simul Comput. 2013 Jan;42(6):1213-1234. doi: 10.1080/03610918.2012.661906. PMID: 23794784; PMCID: PMC3685301.
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Optimizing parameters in clinical trials with a randomized start or withdrawal design.

Computational statistics & data analysis

Xiong C, Luo J, Gao F, Morris JC.
PMID: 24159249
Comput Stat Data Anal. 2014 Jan 01;69:101-113. doi: 10.1016/j.csda.2013.07.013.

Disease-modifying (DM) trials on chronic diseases such as Alzheimer's disease (AD) require a randomized start or withdrawal design. The analysis and optimization of such trials remain poorly understood, even for the simplest scenario in which only three repeated efficacy...

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Xiong C, Luo J, Gao F, et al. Optimizing parameters in clinical trials with a randomized start or withdrawal design. Comput Stat Data Anal. 2014;69:101-113doi: 10.1016/j.csda.2013.07.013.
Xiong, C., Luo, J., Gao, F., & Morris, J. C. (2014). Optimizing parameters in clinical trials with a randomized start or withdrawal design. Computational statistics & data analysis, 69101-113. https://doi.org/10.1016/j.csda.2013.07.013
Xiong, Chengjie, et al. "Optimizing parameters in clinical trials with a randomized start or withdrawal design." Computational statistics & data analysis vol. 69 (2014): 101-113. doi: https://doi.org/10.1016/j.csda.2013.07.013
Xiong C, Luo J, Gao F, Morris JC. Optimizing parameters in clinical trials with a randomized start or withdrawal design. Comput Stat Data Anal. 2014 Jan 01;69:101-113. doi: 10.1016/j.csda.2013.07.013. PMID: 24159249; PMCID: PMC3804275.
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Apolipoprotein E levels in cerebrospinal fluid and the effects of ABCA1 polymorphisms.

Molecular neurodegeneration

Wahrle SE, Shah AR, Fagan AM, Smemo S, Kauwe JS, Grupe A, Hinrichs A, Mayo K, Jiang H, Thal LJ, Goate AM, Holtzman DM.
PMID: 17430597
Mol Neurodegener. 2007 Apr 12;2:7. doi: 10.1186/1750-1326-2-7.

BACKGROUND: Animal studies suggest that brain apolipoprotein E (apoE) levels influence amyloid-beta (Abeta) deposition and thus risk for Alzheimer's disease (AD). We have previously demonstrated that deletion of the ATP-binding cassette A1 transporter (ABCA1) in mice causes dramatic reductions...

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Wahrle SE, Shah AR, Fagan AM, et al. Apolipoprotein E levels in cerebrospinal fluid and the effects of ABCA1 polymorphisms. Mol Neurodegener. 2007;2:7doi: 10.1186/1750-1326-2-7.
Wahrle, S. E., Shah, A. R., Fagan, A. M., Smemo, S., Kauwe, J. S., Grupe, A., Hinrichs, A., Mayo, K., Jiang, H., Thal, L. J., Goate, A. M., & Holtzman, D. M. (2007). Apolipoprotein E levels in cerebrospinal fluid and the effects of ABCA1 polymorphisms. Molecular neurodegeneration, 27. https://doi.org/10.1186/1750-1326-2-7
Wahrle, Suzanne E, et al. "Apolipoprotein E levels in cerebrospinal fluid and the effects of ABCA1 polymorphisms." Molecular neurodegeneration vol. 2 (2007): 7. doi: https://doi.org/10.1186/1750-1326-2-7
Wahrle SE, Shah AR, Fagan AM, Smemo S, Kauwe JS, Grupe A, Hinrichs A, Mayo K, Jiang H, Thal LJ, Goate AM, Holtzman DM. Apolipoprotein E levels in cerebrospinal fluid and the effects of ABCA1 polymorphisms. Mol Neurodegener. 2007 Apr 12;2:7. doi: 10.1186/1750-1326-2-7. PMID: 17430597; PMCID: PMC1857699.
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DIFFEOMORPHIC SURFACE FLOWS: A NOVEL METHOD OF SURFACE EVOLUTION.

SIAM journal on applied mathematics

Zhang S, Younes L, Zweck J, Ratnanather JT.
PMID: 20016768
SIAM J Appl Math. 2008 Jan 01;68(3):806-824. doi: 10.1137/060664707.

We describe a new class of surface flows, diffeomorphic surface flows, induced by restricting diffeomorphic flows of the ambient Euclidean space to a surface. Different from classical surface PDE flows such as mean curvature flow, diffeomorphic surface flows are...

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Zhang S, Younes L, Zweck J, et al. DIFFEOMORPHIC SURFACE FLOWS: A NOVEL METHOD OF SURFACE EVOLUTION. SIAM J Appl Math. 2008;68(3):806-824doi: 10.1137/060664707.
Zhang, S., Younes, L., Zweck, J., & Ratnanather, J. T. (2008). DIFFEOMORPHIC SURFACE FLOWS: A NOVEL METHOD OF SURFACE EVOLUTION. SIAM journal on applied mathematics, 68(3), 806-824. https://doi.org/10.1137/060664707
Zhang, Sirong, et al. "DIFFEOMORPHIC SURFACE FLOWS: A NOVEL METHOD OF SURFACE EVOLUTION." SIAM journal on applied mathematics vol. 68,3 (2008): 806-824. doi: https://doi.org/10.1137/060664707
Zhang S, Younes L, Zweck J, Ratnanather JT. DIFFEOMORPHIC SURFACE FLOWS: A NOVEL METHOD OF SURFACE EVOLUTION. SIAM J Appl Math. 2008 Jan 01;68(3):806-824. doi: 10.1137/060664707. PMID: 20016768; PMCID: PMC2794150.
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A Unified Approach of Meta-Analysis: Application to an Antecedent Biomarker Study in Alzheimer's Disease.

Journal of applied statistics

Xiong C, van Belle G, Zhu K, Miller JP, Morris JC.
PMID: 21221414
J Appl Stat. 2011 Jan 01;38(1):15-27. doi: 10.1080/02664760903008987.

This article provides a unified methodology of meta-analysis that synthesizes medical evidence by using both available individual patient data (IPD) and published summary statistics within the framework of likelihood principle. Most up-to-date scientific evidence on medicine is crucial information...

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Xiong C, van Belle G, Zhu K, et al. A Unified Approach of Meta-Analysis: Application to an Antecedent Biomarker Study in Alzheimer's Disease. J Appl Stat. 2011;38(1):15-27doi: 10.1080/02664760903008987.
Xiong, C., van Belle, G., Zhu, K., Miller, J. P., & Morris, J. C. (2011). A Unified Approach of Meta-Analysis: Application to an Antecedent Biomarker Study in Alzheimer's Disease. Journal of applied statistics, 38(1), 15-27. https://doi.org/10.1080/02664760903008987
Xiong, Chengjie, et al. "A Unified Approach of Meta-Analysis: Application to an Antecedent Biomarker Study in Alzheimer's Disease." Journal of applied statistics vol. 38,1 (2011): 15-27. doi: https://doi.org/10.1080/02664760903008987
Xiong C, van Belle G, Zhu K, Miller JP, Morris JC. A Unified Approach of Meta-Analysis: Application to an Antecedent Biomarker Study in Alzheimer's Disease. J Appl Stat. 2011 Jan 01;38(1):15-27. doi: 10.1080/02664760903008987. PMID: 21221414; PMCID: PMC3017356.
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Combining Multiple Markers to Improve the Longitudinal Rate of Progression-Application to Clinical Trials on the Early Stage of Alzheimer's Disease.

Statistics in biopharmaceutical research

Xiong C, van Belle G, Chen K, Tian L, Luo J, Gao F, Yan Y, Chen L, Morris JC, Crane P.
PMID: 24363827
Stat Biopharm Res. 2013 Jan 01;5(1). doi: 10.1080/19466315.2012.756662.

Clinical trials on early stage Alzheimer's disease (AD) are reaching a bottleneck because none of the current disease markers changes appreciably early in the disease process and therefore a huge sample is required to adequately power such trials. We...

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Xiong C, van Belle G, Chen K, et al. Combining Multiple Markers to Improve the Longitudinal Rate of Progression-Application to Clinical Trials on the Early Stage of Alzheimer's Disease. Stat Biopharm Res. 2013;5(1)doi: 10.1080/19466315.2012.756662.
Xiong, C., van Belle, G., Chen, K., Tian, L., Luo, J., Gao, F., Yan, Y., Chen, L., Morris, J. C., & Crane, P. (2013). Combining Multiple Markers to Improve the Longitudinal Rate of Progression-Application to Clinical Trials on the Early Stage of Alzheimer's Disease. Statistics in biopharmaceutical research, 5(1), . https://doi.org/10.1080/19466315.2012.756662
Xiong, Chengjie, et al. "Combining Multiple Markers to Improve the Longitudinal Rate of Progression-Application to Clinical Trials on the Early Stage of Alzheimer's Disease." Statistics in biopharmaceutical research vol. 5,1 (2013). doi: https://doi.org/10.1080/19466315.2012.756662
Xiong C, van Belle G, Chen K, Tian L, Luo J, Gao F, Yan Y, Chen L, Morris JC, Crane P. Combining Multiple Markers to Improve the Longitudinal Rate of Progression-Application to Clinical Trials on the Early Stage of Alzheimer's Disease. Stat Biopharm Res. 2013 Jan 01;5(1). doi: 10.1080/19466315.2012.756662. PMID: 24363827; PMCID: PMC3868484.
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DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups.

Journal of statistical software

Luo J, Xiong C.
PMID: 23504300
J Stat Softw. 2012 Oct;51(3):1-24. doi: 10.18637/jss.v051.i03. Epub 2012 Sep 22.

Medical researchers endeavor to identify potentially useful biomarkers to develop marker-based screening assays for disease diagnosis and prevention. Useful summary measures which properly evaluate the discriminative ability of diagnostic markers are critical for this purpose. Literature and existing software,...

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Luo J, Xiong C. DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups. J Stat Softw. 2012;51(3):1-24doi: 10.18637/jss.v051.i03.
Luo, J., & Xiong, C. (2012). DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups. Journal of statistical software, 51(3), 1-24. https://doi.org/10.18637/jss.v051.i03
Luo, Jingqin, and Xiong, Chengjie. "DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups." Journal of statistical software vol. 51,3 (2012): 1-24. doi: https://doi.org/10.18637/jss.v051.i03
Luo J, Xiong C. DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups. J Stat Softw. 2012 Oct;51(3):1-24. doi: 10.18637/jss.v051.i03. Epub 2012 Sep 22. PMID: 23504300; PMCID: PMC3595562.
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Validity and power of minimization algorithm in longitudinal analysis of clinical trials.

Biostatistics & epidemiology

Weng H, Bateman R, Morris JC, Xiong C.
PMID: 29250611
Biostat Epidemiol. 2017;1(1):59-77. doi: 10.1080/24709360.2017.1331822. Epub 2017 Jun 13.

We studied the validity of longitudinal statistical inferences of clinical trials using minimization, a dynamic randomization algorithm designed to minimize treatment imbalance for prognostic factors. Repeated measures analysis of covariance and the random intercept and slope models, were used...

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Weng H, Bateman R, Morris JC, et al. Validity and power of minimization algorithm in longitudinal analysis of clinical trials. Biostat Epidemiol. 2017;1(1):59-77doi: 10.1080/24709360.2017.1331822.
Weng, H., Bateman, R., Morris, J. C., & Xiong, C. (2017). Validity and power of minimization algorithm in longitudinal analysis of clinical trials. Biostatistics & epidemiology, 1(1), 59-77. https://doi.org/10.1080/24709360.2017.1331822
Weng, Hua, et al. "Validity and power of minimization algorithm in longitudinal analysis of clinical trials." Biostatistics & epidemiology vol. 1,1 (2017): 59-77. doi: https://doi.org/10.1080/24709360.2017.1331822
Weng H, Bateman R, Morris JC, Xiong C. Validity and power of minimization algorithm in longitudinal analysis of clinical trials. Biostat Epidemiol. 2017;1(1):59-77. doi: 10.1080/24709360.2017.1331822. Epub 2017 Jun 13. PMID: 29250611; PMCID: PMC5730087.
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Showing 1 to 12 of 100 entries