A combination model of AD biomarkers revealed by machine learning precisely predicts Alzheimer's dementia: China Aging and Neurodegenerative Initiative (CANDI) study.

Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association
PMID:

Abstract

INTRODUCTION: To test the utility of the "A/T/N" system in the Chinese population, we study core Alzheimer's disease (AD) biomarkers in a newly established Chinese cohort.

Authors

  • Feng Gao
    Department of Statistics, UCLA, Los Angeles, CA 90095, USA.
  • Xinyi Lv
    Department of Neurology, Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
  • Linbin Dai
    Department of Neurology, Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
  • Qiong Wang
    Beijing Meiling Biotechnology Corporation, Beijing, 102600, PR China.
  • Peng Wang
    Neuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Zhaozhao Cheng
    Department of Neurology, Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
  • Qiang Xie
    Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230001, China.
  • Ming Ni
    Department of Orthopaedics, Chinese People's Liberation Army General Hospital (301 Hospital), 28 Fuxing Rd, 100853, Beijing, China.
  • Yan Wu
    Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China.
  • Xianliang Chai
    Department of Neurology, Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
  • Wenjing Wang
    School of Economics, Tianjin University of Commerce, Tianjin, 300134, China. Electronic address: maggiewwj@163.com.
  • Huaiyu Li
  • Feng Yu
    Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, Forensic Identification Center of Hebei Medical University, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
  • Yuqin Cao
    Department of Neurology, Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
  • Fang Tang
  • Bo Pan
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, China.
  • Guoping Wang
    School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China.
  • Kexue Deng
    Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, USTC, Hefei, 230036, Anhui, China.
  • Shicun Wang
    Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230001, China; Institute of Nuclear Medical Physics, University of Science and Technology of China, Hefei, 230026, China.
  • Qiqiang Tang
    Department of Neurology, Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
  • Jiong Shi
    China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China.
  • Yong Shen