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Effect of Myelin Content on Cognitive Outcomes in Cerebral Small Vessel Disease
Elizabeth Dao1, Roger Tam1, Ging-Yuek R Hsiung1, Lisanne ten Brinke1, Rachel Crockett1, Cindy K Barha1, Youngjin Yoo1, Walid al Keridy2, Stephanie H Doherty1, Alex L MacKay1, Cornelia Laule1, and Teresa Liu-Ambrose1
1University of British Columbia, Vancouver, BC, Canada, 2King Saud University, Riyadh, Saudi Arabia

Synopsis

Pathology studies report myelin damage as a salient feature in cerebral small vessel disease (cSVD). Currently, the role of myelin content in-vivo on cognition is poorly understood. Thus, the main purpose of this study was to investigate the association between myelin content and cognitive function in cSVD. Normal appearing white matter (NAWM) myelin water fraction (MWF) was quantified in 55 people with cSVD with spin-echo myelin water imaging. After accounting for age, education, and white matter hyperintensity volume, lower NAWM MWF was significantly associated with slower processing speed and poorer working memory, but not with set shifting or inhibitory control.

Background and Purpose

Cerebral small vessel disease (cSVD) is the second most common cause of cognitive impairment and dementia1. At a macrostructural level, cSVD predominantly manifests as white matter hyperintensities (WMHs)2. At a microstructural level, pathology studies report myelin damage as a salient feature2,3. Diffusion tensor imaging studies suggest microstructural white matter (WM) damage extends beyond WMHs into the normal appearing WM (NAWM)4,5, but diffusion tensor imaging metrics are influenced by a variety of tissue features beyond myelin6. Myelin water fraction (MWF) derived from quantitative T2 relaxation measurement may provide more myelin-specific tissue characterization about cSVD but has yet to be applied in this population. Consequently, the specific role of myelin content in cSVD cognition is poorly understood. Thus, the purpose of this study was twofold:
1) investigate the association between cSVD (i.e. WMHs) and myelin integrity in the NAWM and;
2) assess the association between NAWM myelin integrity and cognitive function in older adults with cSVD.

Methods

Participants
This study included 55 participants who: 1) had cSVD, defined as the presence of WMHs on MRI7 with a Fazekas score of ≥ 18, 2) were cognitively impaired, defined as a Montreal Cognitive Assessment score < 26/30 at baseline9 and; 3) were ≥ 50 years-old.

MRI Experiments
Each participant completed a 3T (Philips Achieva) whole-brain 48-echo 3D gradient and spin echo (GRASE) for T2 measurement (TR/ΔTE=1073/8ms, FOV = 230×190×100mm3, acquired resolution=1×2×5mm3, reconstructed resolution=1×1×2.5mm3)10. 3DT1-MPRAGE (TR/TE=3000/8ms, TI=1072ms, 1x1x1mm3), PD (TR/TE=3000/30ms, 1x1x1mm3) and T2 (TR/TE=2500/363ms, 1x1x1.6mm3) were collected for tissue segmentation.

Image Processing
Voxel-wise T2 distributions were calculated using a modified Extended Phase Graph algorithm combined with regularized non-negative least squares and flip angle optimization10,11. MWF was quantified as the amplitude of the short T2 component (15-40ms representing myelin water) divided by the amplitude across the entire distribution (total water, the sum of all T2 components)10,12.
WM masks were generated from 3DT1 images using the automated brain segmentation algorithm in FSL-FAST13. These WM masks were then registered to the GRASE images using FLIRT. To remove WMHs from the WM mask, WMH masks created using PD/T2 segmentation14 were resampled to the GRASE image using FLIRT and applywarp in FSL. The resampled WMH mask was then subtracted from the WM mask to generate a NAWM mask. Each participant’s NAWM mask was multiplied by their MWF map to generate a NAWM MWF map in native space (Figure 1). Average NAWM MWF was calculated for each participant. WMH masks were used to quantify WMH volume in mm3.

Cognitive Assessments
Assessment of cognitive function included processing speed and executive functions: 1) Trail Making Test Part A (processing speed); 2) Trail Making Test Part B minus A (set shifting); 3) Verbal Digit Span Backwards Test (working memory) and; 4) Stroop Test (inhibitory control).

Statistical Analysis
A bivariate correlation analysis assessed the relationship between NAWM MWF and total WMH volume. Multiple linear regression analyses assessed the contribution of NAWM MWF on cognitive outcomes controlling for age, education, and total WMH volume. The overall alpha was set at ≤ 0.05.

Results

Participant demographics and descriptive statistics are summarized in Table 1. The mean age was 75.7 ± 5.8 years and Montreal Cognitive Assessment score was 21.4 ± 3.5.
NAWM MWF was significantly correlated with total WMH volume (r = -0.29, p = 0.031, Figure 2). After accounting for age, education, and total WMH volume, lower NAWM MWF was significantly associated with slower processing speed (β = -0.29, p = 0.037) and poorer working memory (β = 0.30, p = 0.048). NAWM MWF was not significantly associated with set shifting or inhibitory control (p > 0.132). Table 2 summarizes regression results.

Discussion

We report that greater WMH volume is associated with reduced NAWM myelin content. This further affirms reports from histological and MRI studies indicating deterioration in the NAWM in cSVD3-5. In addition, our results provide preliminary evidence that myelin damage in what appears to be healthy cerebral WM may have negative cognitive consequences for processing speed and working memory. These findings are consistent with MWF studies in other clinical populations (i.e., multiple sclerosis and mild cognitive impairment)15-17. Here we provide the first evidence suggesting that myelin deterioration is also detrimental for cognitive function in people with cSVD, independent of WMHs.
We did not find a significant association between myelin content and set shifting or inhibitory control. These results are in contrast to diffusion tensor and magnetization transfer imaging studies18-21; however, it is important to note that these studies do not specifically assess myelin. While diffusion tensor and magnetization transfer imaging studies suggest that damage to WM microstructure may contribute to reduced set shifting and inhibitory control, our data suggests that this relationship might not be associated with myelin specific changes and may instead be associated with other WM microstructural damage (e.g., axonal loss or alterations in membrane permeability).

Conclusion

Myelin integrity in NAWM may play a role in the evolution of impaired processing speed and working memory in people with cSVD. Future studies with a longitudinal design and larger sample sizes are needed to fully elucidate the role of myelin as a potential biomarker for cognitive function.

Acknowledgements

We would like to thank the study participants and the MRI technologists at the UBC MRI Research Centre. We also thank Kevin Lam for his assistance with the WMH segmentations. Funding for this research was provided by the Heart and Stroke Foundation of Canada (G-15-0009019) and the Alzheimer Society Research Program (15-18). T.L.A. is a Canada Research Chair (Tier 2) in Physical Activity, Mobility, and Cognitive Neuroscience. E.D. is the recipient of the Canadian Institutes of Health Research Doctoral Award and the Michael Smith Foundation for Health Research Research Trainee Award.

References

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Figures

Figure 1 A) PD-weighted scan for WMH segmentation; B) T2-weighted scan for white matter hyperintensity segmentation; C) white matter hyperintensity mask; D) myelin water fraction map; E) normal appearing white matter myelin water fraction mask; F) normal appearing white matter myelin water fraction map

Table 1 Descriptive Characteristics

MoCA = Montreal Cognitive Assessment; MMSE = Mini-Mental State Examination; NAWM = normal appearing white matter; MWF = myelin water fraction; WMH = white matter hyperintensity


Figure 2 Bivariate Correlation Analysis of Normal Appearing White Matter (NAWM) Myelin Water Fraction (MWF) Versus White Matter Hyperintensity (WMH) Volume

Table 2 Multiple Linear Regression Results

Independent Variables in Step 1 = age and education; Independent Variables in Step 2 = age, education, and white matter hyperintensity volume; Independent Variables in Step 3 = age, education, white matter hyperintensity volume, and normal appearing white matter (NAWM) myelin water fraction (MWF)

*Significant at p ≤ 0.05


Proc. Intl. Soc. Mag. Reson. Med. 29 (2021)
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