hdWGCNA and Cellular Communication Identify Active NK Cell Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers through Machine Learning.

Journal: Current Alzheimer research
PMID: 38808722

Abstract

BACKGROUND: Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of β-amyloid plaques and the formation of neurofibrillary tangles. Given this context, it becomes imperative to develop an early and accurate biomarker model for AD diagnosis, employing machine learning and bioinformatics analysis.

Authors

  • Guobin Song
    School of Stomatology, Southwest Medical University, Luzhou, China.
  • Haoyang Wu
    Department of Chemical Engineering, Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA whgreen@mit.edu kfjensen@mit.edu.
  • Haiqing Chen
    Clinical Medical College, Southwest Medical University, Luzhou, China.
  • Shengke Zhang
    Clinical Medical College, Southwest Medical University, Luzhou, China.
  • Qingwen Hu
    Clinical Medical College, Southwest Medical University, Luzhou, China.
  • Haotian Lai
    Clinical Medical College, Southwest Medical University, Luzhou, China.
  • Claire Fuller
    Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, MD, USA.
  • Guanhu Yang
    Department of Specialty Medicine, Ohio University, Athens, OH, United States.
  • Hao Chi
    University of Chinese Academy of Sciences , Beijing, China.

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