| Title | Alzheimer's disease progression model based on integrated biomarkers and clinical measures |
| Authors | Qiu, Yue Li, Liang Zhou, Tian-yan Lu, Wei |
| Affiliation | Peking Univ, State Key Lab Nat & Biomimet Drugs, Beijing 100191, Peoples R China. Peking Univ, Hlth Sci Ctr, Dept Pharmaceut, Sch Pharmaceut Sci, Beijing 100191, Peoples R China. |
| Keywords | Alzheimer's disease mild cognitive impairment A beta(42) p-tau hippocampus ADAS-cog disease progression model NONMEM COGNITIVE IMPAIRMENT IN-VIVO NEURODEGENERATION THERAPEUTICS AUTOPHAGY MELATONIN DEMENTIA ATROPHY PLAQUES TAU |
| Issue Date | 2014 |
| Publisher | 中国药理学报 |
| Citation | ACTA PHARMACOLOGICA SINICA.2014,35,(9),1111-1120. |
| Abstract | Aim: Biomarkers and image markers of Alzheimer's disease (AD), such as cerebrospinal fluid A beta(42) and p-tau, are effective predictors of cognitive decline or dementia. The aim of this study was to integrate these markers with a disease progression model and to identify their abnormal ranges. Methods: The data of 395 participants, including 86 normal subjects, 108 early mild cognitive impairment (EMCI) subjects, 120 late mild cognitive impairment (LMCI) subjects, and 81 AD subjects were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. For the participants, baseline and long-term data on cerebrospinal fluid A beta(42) and p-tau, hippocampal volume, and ADAS-cog were available. Various linear and nonlinear models were tested to determine the associations among the ratio of A beta(42) to p-tau (the Ratio), hippocampal volume and ADAS-cog. Results: The most likely models for the Ratio, hippocampal volume, and ADAS-cog (logistic, E-max, and linear models, respectively) were used to construct the final model. Baseline disease state had an impact on all the 3 endpoints (the Ratio, hippocampal volume, and ADAS-cog), while APOE epsilon 4 genotype and age only influence the Ratio and hippocampal volume. Conclusion: The Ratio can be used to identify the disease stage for an individual, and clinical measures integrated with the Ratio improve the accuracy of mild cognitive impairment (MCI) to AD conversion forecasting. |
| URI | http://hdl.handle.net/20.500.11897/323000 |
| ISSN | 1671-4083 |
| DOI | 10.1038/aps.2014.57 |
| Indexed | SCI(E) PubMed 中国科技核心期刊(ISTIC) 中国科学引文数据库(CSCD) |
| Appears in Collections: | 天然药物与仿生药物国家重点实验室 |
