Determinants of white matter hyperintensity burden in patients with Fabry disease

Natalia S Rost1, Lisa Cloonan2, Allison S Kanakis2

  • 1From the J. Philip Kistler Stroke Research Center, Department of Neurology (N.S.R., L.C., A.S.K., K.M.F.), and the Center for Human Genetic Research, Department of Neurology (N.S.R., D.R.A., V.C., K.B.S.), Massachusetts General Hospital, Boston; Neurogenetics Unit (C.M.L.), School of Medicine of Riberirao Preto, University of São Paulo, Brazil; Division of Medical Genetics (D.P.G.), University of Versailles-St Quentin en Yvelines Paris-Saclay University, France; Fundación para el Estudio de las Enfermedades Neurometabólicas (FESEN) (J.M.P.), Buenos Aires, Argentina; and Departments of Neuroradiology (G.A.H.) and Neurology (C.S., N.Ü.), Fabry Center for Interdisciplinary Therapy (FAZIT) (C.S., N.Ü.), University of Würzburg, Germany. nrost@partners.org.

Neurology
|May 11, 2016
PubMed
Abstract

Insights

Age and prior stroke independently predict white matter hyperintensity (WMH) burden in Fabry disease (FD). The fourth decade is critical for WMH progression, with new predictors emerging in patients aged 31-40.

Area of Science:

  • Neurology
  • Radiology
  • Genetics

Background:

  • Fabry disease (FD) is a rare genetic disorder affecting multiple organs.
  • White matter hyperintensities (WMH) are common in FD and may indicate disease progression.
  • Volumetric MRI assessment offers a quantitative method to evaluate WMH burden.

Purpose of the Study:

  • To identify determinants of white matter hyperintensity (WMH) burden in patients with Fabry disease (FD).
  • To utilize a semiautomated volumetric MRI assessment method for WMH quantification.

Main Methods:

  • Retrospective analysis of brain MRI from 223 patients with confirmed FD.
  • Volumetric assessment of WMH using a validated, computer-assisted method (T2-FLAIR MRI).
  • Statistical analysis including univariate and multivariate linear regression (lnWMHV).

Main Results:

  • Age and history of stroke were independently associated with WMH burden (lnWMHV).
  • WMH burden and its predictors varied significantly by decade of life (p < 0.0001).
  • The cohort included 132 females (59%), with a mean age of 39.2 years.

Conclusions:

  • Age and prior stroke are key independent predictors of WMH burden in FD.
  • The fourth decade of life (ages 31-40) is a critical period for WMH progression in FD.
  • Further research is needed to understand WMH biology and its role as an MRI marker in FD progression.