Associated factors of white matter hyperintensity volume: a machine-learning approach.

Journal: Scientific reports
Published Date: Jan 27, 2021

Abstract

To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we used a data-driven machine-learning approach. We analysed two independent cohorts (KORA and SHIP). WMH volumes were derived from cMRI-images (FLAIR). 90 (KORA) and 34 (SHIP) potential determinants of WMH including measures of diabetes, blood-pressure, medication-intake, sociodemographics, life-style factors, somatic/depressive-symptoms and sleep were collected. Elastic net regression was used to identify relevant predictor covariates associated with WMH volume. The ten most frequently selected variables in KORA were subsequently examined for robustness in SHIP. The final KORA sample consisted of 370 participants (58% male; age 55.7 ± 9.1 years), the SHIP sample comprised 854 participants (38% male; age 53.9 ± 9.3 years). The most often selected and highly replicable parameters associated with WMH volume were in descending order age, hypertension, components of the social environment (i.e. widowed, living alone) and prediabetes. A systematic machine-learning based analysis of two independent, population-based cohorts showed, that besides age and hypertension, prediabetes and components of the social environment might play important roles in the development of WMH. Our results enable personal risk assessment for the development of WMH and inform prevention strategies tailored to the individual patient.

Authors

  • Sergio Grosu
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Susanne Rospleszcz
    Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Felix Hartmann
    Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany.
  • Mohamad Habes
    Biggs Alzheimer's Institute, University of Texas San Antonio Health Science Center, USA.
  • Fabian Bamberg
    Department of Diagnostic and Interventional Radiology, University Medical Center Tübingen, Tübingen, Germany.
  • Christopher L Schlett
    From the MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, 68 Varosmajor St, 1122 Budapest, Hungary (M.K., J.K., B.M., P.M.H.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (J.K., Y.K., A.I., M.T.L., B.F., H.J.A., U.H.); Center for Cause of Death Investigation, Faculty of Medicine, Hokkaido University, Hokkaido, Japan (Y.K.); Department for Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Freiburg, Germany (C.L.S.); and Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (H.J.A.).
  • Franziska Galiè
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Roberto Lorbeer
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Sigrid Auweter
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Sonja Selder
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Robin Buelow
    Institute of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany.
  • Margit Heier
    Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany.
  • Wolfgang Rathmann
    German Center for Diabetes Research (DZD), München, Neuherberg, Germany.
  • Katharina Mueller-Peltzer
    Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Freiburg, Germany.
  • Karl-Heinz Ladwig
    Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Hans J Grabe
    Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany.
  • Annette Peters
    Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
  • Birgit B Ertl-Wagner
    From the Department of Radiology, University of Wisconsin Madison School of Medicine and Public Health, 600 Highland Dr, Madison, WI 53792 (D.A.B., M.L.S.); Department of Radiology, New York University, New York, NY (L.M.); Department of Musculoskeletal Radiology (M.A.B.) and Institute for Technology Assessment (E.F.H.), Massachusetts General Hospital, Boston, Mass; Department of Medical Imaging, Hospital for Sick Children, University of Toronto, Toronto, Canada (B.B.E.W.); Department of Radiology, University of California-San Diego, San Diego, Calif (K.J.F.); Department of Cancer Imaging, Division of Imaging Sciences & Biomedical Engineering, Kings College London, London, England (V.J.G.); Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, Calif (C.P.H.); and Department of Radiology and Radiologic Science, The Johns Hopkins University School of Medicine, Baltimore, Md (C.R.W.).
  • Sophia Stoecklein
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany. Sophia.Stoecklein@med.uni-muenchen.de.

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