Susceptibility networks reveal independent patterns of brain iron abnormalities in multiple sclerosis
Jack A. Reeves,
Niels Bergsland,
Michael G. Dwyer,
Gregory E. Wilding,
Dejan Jakimovski,
Fahad Salman,
Balint Sule,
Nicklas Meineke,
Bianca Weinstock-Guttman,
Robert Zivadinov,
Ferdinand Schweser
Affiliations
Jack A. Reeves
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
Niels Bergsland
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA; MR Research Laboratory, IRCCS, Don Gnocchi Foundation ONLUS, Milan, Italy
Michael G. Dwyer
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Center for Biomedical Imaging, Clinical and Translational Science Institute, Clinical and Translational Research Center, State University of New York at Buffalo, 6045C, 875 Ellicott Street, Buffalo, NY 14203, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
Gregory E. Wilding
Department of Biostatistics, School of Public Health and Health Professions, State University of New York at Buffalo, Buffalo, NY, USA
Dejan Jakimovski
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
Fahad Salman
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
Balint Sule
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
Nicklas Meineke
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
Bianca Weinstock-Guttman
Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA; Jacobs Neurological Institute, Buffalo, NY, USA
Robert Zivadinov
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Center for Biomedical Imaging, Clinical and Translational Science Institute, Clinical and Translational Research Center, State University of New York at Buffalo, 6045C, 875 Ellicott Street, Buffalo, NY 14203, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
Ferdinand Schweser
Buffalo Neuroimaging Analysis Center, Buffalo, NY, USA; Center for Biomedical Imaging, Clinical and Translational Science Institute, Clinical and Translational Research Center, State University of New York at Buffalo, 6045C, 875 Ellicott Street, Buffalo, NY 14203, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA; Corresponding author at: Center for Biomedical Imaging, Clinical and Translational Science Institute, Clinical and Translational Research Center, State University of New York at Buffalo, 6045C, 875 Ellicott Street, Buffalo, NY 14203, USA.
Brain iron homeostasis is necessary for healthy brain function. MRI and histological studies have shown altered brain iron levels in the brains of patients with multiple sclerosis (MS), particularly in the deep gray matter (DGM). Previous studies were able to only partially separate iron-modifying effects because of incomplete knowledge of iron-modifying processes and influencing factors. It is therefore unclear to what extent and at which stages of the disease different processes contribute to brain iron changes. We postulate that spatially covarying magnetic susceptibility networks determined with Independent Component Analysis (ICA) reflect, and allow for the study of, independent processes regulating iron levels.We applied ICA to quantitative susceptibility maps for 170 individuals aged 9–81 years without neurological disease (“Healthy Aging” (HA) cohort), and for a cohort of 120 patients with MS and 120 age- and sex-matched healthy controls (HC; together the “MS/HC” cohort).Two DGM-associated “susceptibility networks” identified in the HA cohort (the Dorsal Striatum and Globus Pallidus Interna Networks) were highly internally reproducible (i.e. “robust”) across multiple ICA repetitions on cohort subsets. DGM areas overlapping both robust networks had higher susceptibility levels than DGM areas overlapping only a single robust network, suggesting that these networks were caused by independent processes of increasing iron concentration. Because MS is thought to accelerate brain aging, we hypothesized that associations between age and the two robust DGM-associated networks would be enhanced in patients with MS. However, only one of these networks was altered in patients with MS, and it had a null age association in patients with MS rather than a stronger association. Further analysis of the MS/HC cohort revealed three additional disease-related networks (the Pulvinar, Mesencephalon, and Caudate Networks) that were differentially altered between patients with MS and HCs and between MS subtypes. Exploratory regression analyses of the disease-related networks revealed differential associations with disease duration and T2 lesion volume. Finally, analysis of ROI-based disease effects in the MS/HC cohort revealed an effect of disease status only in the putamen ROI and exploratory regression analysis did not show associations between the caudate and pulvinar ROIs and disease duration or T2 lesion volume, showing the ICA-based approach was more sensitive to disease effects.These results suggest that the ICA network framework increases sensitivity for studying patterns of brain iron change, opening a new avenue for understanding brain iron physiology under normal and disease conditions.
