Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

Journal: Scientific reports
PMID: 32433583

Abstract

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjusted for intracranial volume (ICV). 93 potential determinants of GMV from the categories sociodemographics, anthropometric measurements, cardio-metabolic variables, lifestyle factors, medication, sleep, and nutrition were obtained from 293 participants from a population-based cohort from Southern Germany. Elastic net regression was used to identify the most important determinants of ICV-adjusted GMV. The four variables age (selected in each of the 1000 splits), glomerular filtration rate (794 splits), diabetes (323 splits) and diabetes duration (122 splits) were identified to be most relevant predictors of GMV adjusted for intracranial volume. The elastic net model showed better performance compared to a constant linear regression (mean squared error = 1.10 vs. 1.59, p < 0.001). These findings are relevant for preventive and therapeutic considerations and for neuroimaging studies, as they suggest to take information on metabolic status and renal function into account as potential confounders.

Authors

  • Franziska Galiè
    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.
  • Daniel Keeser
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Ebba Beller
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Ben Illigens
    Dresden International University, Division of Health Care Sciences, Center for Clinical Research and Management Education, Dresden, Germany.
  • Roberto Lorbeer
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Sergio Grosu
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Sonja Selder
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Sigrid Auweter
    Department of Radiology, University Hospital, LMU Munich, Munich, 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.).
  • Wolfgang Rathmann
    German Center for Diabetes Research (DZD), München, Neuherberg, Germany.
  • Lars Schwettmann
    Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Karl-Heinz Ladwig
    Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Jakob Linseisen
    Chair of Epidemiology, Ludwig-Maximilians-University München, UNIKA-T Augsburg, Augsburg, Germany.
  • Annette Peters
    Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
  • Fabian Bamberg
    Department of Diagnostic and Interventional Radiology, University Medical Center Tübingen, Tübingen, Germany.
  • Birgit Ertl-Wagner
    Department of Radiology, Ludwig-Maximilians-University Munich, Munich, Germany.
  • Sophia Stoecklein
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany. Sophia.Stoecklein@med.uni-muenchen.de.

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