1. Academic Validation
  2. Effects of Homocysteine on white matter diffusion parameters in Alzheimer's disease

Effects of Homocysteine on white matter diffusion parameters in Alzheimer's disease

  • BMC Neurol. 2017 Oct 6;17(1):192. doi: 10.1186/s12883-017-0970-7.
Chen-Chang Lee 1 2 3 Shih-Wei Hsu 2 Chi-Wei Huang 4 Wen-Neng Chang 4 Sz-Fan Chen 5 Ming-Kung Wu 5 Chiung-Chih Chang 4 Lain-Chyr Hwang 3 Po-Chou Chen 6
Affiliations

Affiliations

  • 1 Department of Biomedical Engineering, I-Shou University, Kaohsiung, Taiwan.
  • 2 Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • 3 Department of Electrical Engineering, I-Shou University, Kaohsiung, Taiwan.
  • 4 Department of Neurology, Cognition and Aging Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • 5 Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • 6 Department of Biomedical Engineering, I-Shou University, Kaohsiung, Taiwan. pcchen@isu.edu.tw.
Abstract

Background: The clinical features of Alzheimer's disease (AD) are related to brain network degeneration, and hyperhomocysteinemia is related to greater white matter hyperintensities. We investigated the changes in four diffusion tensor imaging parameters in the white matter of patients with early stage AD, examined their associations with homocysteine level, and tested the clinical significance of the diffusion tensor imaging parameters and homocysteine level in correlation analysis with cognitive test scores.

Methods: We enrolled 132 patients with AD and analyzed white matter (WM) macrostructural changes using diffusion tensor neuroimaging parameters including fractional anisotropy (FA), mean diffusion (MD), axial diffusivity (axial-D) and radial diffusivity (RD). Two neuroimaging post-processing analyses were performed to provide complementary data. First, we calculated 11 major bundle microstructural integrities using a WM parcellation algorithm, and correlated them with serum homocysteine levels to explore whether the fiber bundles were affected by homocysteine. Second, we used tract-based spatial statistics to explore the anatomical regions associated with homocysteine levels. Changes in cognitive test scores caused by homocysteine served as the major outcome factor.

Results: The results suggested that homocysteine levels did not have a direct impact on cross-sectional cognitive test scores, but that they were inversely correlated with renal function, B12 and folate levels. Topographies showing independent correlations with homocysteine in FA and MD were more diffusely located compared to the posterior brain regions in axial-D and RD. In the association bundle analysis, homocysteine levels were significantly correlated with the four diffusion parameters even after correcting for confounders, however no association between homocysteine and WM to predict cognitive outcomes was established.

Conclusions: In our patients with AD, homocysteine levels were associated with renal dysfunction and decreased levels of vitamin B12 and folate, all of which require clinical attention as they may have been associated with impaired WM microstructural integrity and modulated cognitive performance in cross-sectional observations.

Keywords

Alzheimer’s disease; Default-mode network; Diffusion parameters; Homocysteine.

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