Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data.

Journal: EBioMedicine
PMID: 37806288

Abstract

BACKGROUND: Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.

Authors

  • Taeho Jo
    Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.
  • Junpyo Kim
    Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA; Medical Research Institute, Sungkyunkwan University, School of Medicine, Seoul, South Korea.
  • Paula Bice
    Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.
  • Kevin Huynh
    Baker Heart and Diabetes Institute, Melbourne, 3004, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Parkville, 3010, Victoria, Australia.
  • Tingting Wang
    Department of Anesthesiology, Taizhou Hospital, Linhai, China.
  • Matthias Arnold
    Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, 27710, USA; Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany.
  • Peter J Meikle
    Baker Heart and Diabetes Institute, Melbourne, 3004, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Parkville, 3010, Victoria, Australia; Monash University, Melbourne, VIC 3800, Australia.
  • Corey Giles
    Baker Heart and Diabetes Institute, Melbourne, 3004, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Parkville, 3010, Victoria, Australia.
  • Rima Kaddurah-Daouk
    Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, 27710, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC, 27710, USA; Department of Medicine, Duke University, Durham, NC, 27710, USA.
  • Andrew J Saykin
    Indiana University, Indianapolis, IN 46202, USA.
  • Kwangsik Nho
    Radiology & Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.

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