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Effect of myelin integrity on rapid speed gait in normal aging

Mustapha Bouhrara¹, Nikkita Khattar¹, Luis E. Cortina¹, Abinand C. Rejimon¹, Elango Palchamy¹, and Richard G. Spencer¹
¹NIA, NIH, Baltimore, MD, United States

Synopsis

Microstructural white matter (WM) degeneration has been shown to have a direct impact on mobility performance. However, the association between speed gait and myelin changes is less clear. This study examines the effect of myelin degeneration measured using myelin water fraction (MWF), a specific proxy of myelin content, and relaxation rates, sensitive but non-specific measures of myelin, on rapid gait speed (RGS), which represents an integrated metric of physiologic function. Our study is conducted on a large age-range cohort of cognitively unimpaired participants. We show statistically significant correlations between MWF loss and RGS decline in several WM structures.

PURPOSE

To investigate the potential correlation between demyelination and rapid gait speed (RGS) decline in a cohort of cognitively unimpaired subjects across a wide age range. We further evaluated correlations of different MRI metrics of myelin integrity (myelin water fraction, MWF, and longitudinal, R₁, and transverse, R₂, relaxation rates) to RGS differences in order to develop further insights into the effect of normal aging and myelin integrity on rapid walk performance, a well-known metric of integrated physical capability.

METHODS

Subjects and MRI
The study cohort consisted of 72 participants (56.2±22.8years) of 35 women (51.3±20.7years) and 37 men (60.8±24.1years) spanning the age range between 22 and 94 years. Participants underwent a mini-mental state exam (MMSE score for women=28.8±1.6; MMSE men=28.1±1.7). Age and MMSE were not statistically different between men and women.

For each participant, ten 3D spoiled-gradient-recalled-echo (SPGR) images were acquired with flip angles (FAs) of [2 4 6 8 10 12 14 16 18 20]°, echo time of (TE) 1.37ms and repetition time (TR) of 5ms, and ten 3D balanced steady-state free-precession images were acquired with FAs of [2 7 11 16 24 32 40 60]°, TE of 2.8ms, TR of 5.8ms, and radiofrequency excitation pulse phase increments of 0^oor 180^o to account for off-resonance effects (1). All images were acquired with a voxel size of 1.6mm×1.6mm×1.6mm. Further, we used the DAM to correct for B₁ inhomogeneity (2). The DAM protocol consists of two fast spin-echo images acquired with FAs of 45° and 90°, TE of 102ms, TR of 3s, and acquisition voxel size of 2.6mm×2.6mm×4mm. All images were obtained with a field-of-view of 240mm×208mm×150mm and reconstructed on the scanner to a voxel size of 1mm×1mm×1mm. The protocol for gait analysis used in our laboratory has been described elsewhere (3). Briefly, RGS was measured within three days of the MRI measurements; for this standardized test, participants are instructed to walk as quickly as possible over a 6m course in an uncarpeted straight corridor (3).

Image processing and statistical analysis
For each participant, a whole-brain MWF map was generated using the BMC-mcDESPOT analysis from the SPGR, bSSFP, an DAM images (4-6), an R₁map was generated from the SPGR and DAM images (7), and an R₂ map was generated from the bSSFP and DAM images (7). Further, the averaged SPGR image over FAs was nonlinearly registered to the MNI space and the computed transformation matrix was then applied to the corresponding maps using FSL software (8). Nine WM regions of interest (ROIs) were defined from the MNI structural atlas (Fig. 1) (8). Finally, for each ROI, the effect of MWF, R₁, or R₂, on RGS was investigated using multiple linear regression with the mean RGS within the ROI as the dependent variable and the mean of MWF (R₁ or R₂) within the ROI as the independent variables, with sex, age, body mass index (BMI), and MMSE accounted for as covariates.

RESULTS & DISCUSSION

Figure 2 indicates the statistically significant positive correlation between RGS and MWF in most WM regions evaluated, indicating that decreases in MWF correspond to decreases in RGS. The results are in agreement with, and complementary to, previous DTI-based investigations showing that disrupted regional WM microstructural integrity affects stability and speed of walking in cognitively normal subjects (9-12). However, DTI-outcomes, including fractional anisotropy, while sensitive to microstructural changes, are not specific, so that potential microstructural correlates of the decline in RGS in these studies include not only myelin loss, but also axonal damage or other forms of neurodegeneration. Furthermore, most previous investigations focused on the association between WM microstructural changes and walking in patients with specific pathologies such as Parkinson’s disease, small vessel disease, and leukoaraiosis, with much more limited work conducted on persons free of overt neurological diseases. Therefore, our work adds new insights highlighting the specific implications of myelin loss for RGS decline.

Overall, similar trends were observed between RGS and MWF, R₁ and R₂ (Figs. 2, 3 and 4). Unlike R₁, R₂ exhibited less significant correlations and moderate slopes in certain brain regions as compared to MWF-derived results (Fig. 2). This reflect the known sensitivity of R₁ to lipids (13), the main constituent of myelin. This relationship between R₁ and RGS serves as further evidence of the correlation between walking speed and myelination.

Our MWF and relaxation rates analyses indicate that brain structures other than the motor cortex can potentially affect walking speed; this is in agreement with previous studies (9-12). Indeed, the frontal, temporal, and occipital lobes, as well as the cerebellum and the internal capsules, are involved in processing and coordinating motor and sensory information, while the corpus callosum plays an essential role in integrating functions between hemispheres, including gait planning, and processing visuospatial information.

CONCLUSIONS

In this first study examining the association between myelin integrity and walking speed, we showed that decreases in myelination are associated with declining performance of RGS, a standardized integrative functional task, in a population subjects free of overt neurological diseases. MWF analysis of regional white matter integrity therefore provides significant insight into the pathophysiology of gait impairment in normative aging.

Acknowledgements

This work was supported by the Intramural Research Program of the National Institute on Aging of the National Institutes of Health.

References

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Figures

Figure 1. Visualization of the white matter ROIs used in our analysis. 1) Frontal lobes, 2) Parietal lobes, 3) Occipital lobes, 4) Cerebellum, 5) Splenium of corpus callosum, 6) Body of corpus callosum, 7) Genu of corpus callosum, 8) Internal capsule, 9) Temporal lobes.

Figure 2. Regressions of RGS with MWF. Results are shown for 9 WM brain structures/ROIs displayed in Fig. 1. For each ROI, the coefficient of determination, R², of the multiple linear regression model, as well as the slope, βMWF, and the significance, pMWF, of the relationship are reported. All analyses were adjusted for covariates as described. All ROIs exhibited significant (p < 0.01) positive correlations between RGS and MWF, besides the genu of corpus callosum (CC), which was close to significance (p < 0.1).

Figure 3. Regressions of RGS with R₁. Results are shown for 9 WM brain structures/ROIs displayed in Fig. 1. For each ROI, the coefficient of determination, R², of the multiple linear regression model, as well as the slope, β_R1, and the significance, p_R1, of the R₁ dependent parameter are reported. All ROIs exhibited significant (p < 0.01) positive correlations between RGS and R₁.

Figure 4. Regressions of RGS with R₂. Results are shown for 9 WM brain structures/ROIs displayed in Fig. 1. For each ROI, the coefficient of determination, R², of the multiple linear regression model, as well as the slope, β_R2, and the significance, p_R2, of the R₂ dependent parameter are reported. All ROIs exhibited significant (p < 0.01) positive correlations between RGS and R₂, besides the cerebellum, the body of corpus callosum (CC), and the genu of CC.

Proc. Intl. Soc. Mag. Reson. Med. 28 (2020)

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