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Effect of age on white matter microstructure in nondemented ApoE4 carriers and non-carriers
Patcharaporn Srisaikaew1,2, Jordan A. Chad3,4, Pasuk Mahakkanukrauh1,5, Nicole D. Anderson3,6, and J. Jean Chen3,4
1Department of Anatomy, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand, 2PhD Program in Anatomy, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand, 3Rotman Research Institute, Baycrest Health Centre, Toronto, ON, Canada, 4Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 5Excellence in Osteology Research and Training Center (ORTC), Chiang Mai University, Chiang Mai, Thailand, 6Department of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada

Synopsis

With advancing age, ApoE4 increases the risk of developing AD compared to non-carriers. TBSS analysis and FSL’s randomise permutation tool were used to test diffusivity (FA, MD, RD, AxD, MO, and NA) differences in the effect of age in nondemented ApoE4+ compared to ApoE4- older adults. The difference between groups in the association of DTI metrics and age was most present in posterior WM regions. MO and NA were more sensitive to age-related effects than conventional DTI metrics in crossing fibres. We support the changes in DTI metrics due to the manifestation of the ApoE4 across whole-brain age-related WM microstructures.

Abstract

Introduction: The apolipoprotein E4 allele (ApoE4) is a major genetic risk factor for late-onset Alzheimer’s disease (AD). Having one or two copies of ApoE4 increases the risk of developing AD in aging1. Several studies have found age-related changes in diffusion-tensor imaging (DTI) parameters in cognitively normal older adults carrying ApoE4 in regions of AD pathology in frontal and temporal white matter (WM) tracts2,3,4. Recent work by Chad et al.5 suggests that orthogonal tensor decomposition, consisting of mean diffusivity (MD), mode of anisotropy (MO) and norm of anisotropy (NA), are more sensitive to neurodegeneration in regions of complex fibre architecture than traditional metrics, such as fractional anisotropy (FA)6. In this work, we aim to investigate the impact of ApoeE4 on age-related effects in WM microstructure, comparing orthogonal tensor decomposition against conventional DTI metrics.
Methods: Data from 122 nondemented (CDR=0) participants aged over 55 were taken from the open-access series of imaging studies (OASIS-3)7. DTI data were acquired on Siemens 3T system with b of 0 (1 volume per acquisition) and 1,000 s/mm2, 65 directions from age- and education-matched ApoE4+ and ApoE4- individuals. ApoE4+: n=61, 8 ε4/ε4, 7 ε2/ε4, and 46 ε3/ε4 genotypes, 70.90±7.09 years old, education level=16.33±2.52 years, M:F = 29:32; ApoE4-: n = 61, 48 ε3/ε3, 12 ε2/ε3, and 1 ε2/ε2, 70.09±7.05 years old, education level=16.26±2.32 years, M:F=25:36. Data were analyzed using FMRIB’s diffusion toolbox (FSL 5.0.10) to derive FA; MD; radial diffusivity, RD; axial diffusivity, AxD; MO; and NA. Tract based spatial statistics (TBSS) was used to assess age effects and group differences thereof, corrected for multiple comparisons using FSL randomise threshold-free cluster enhancement (5,000 permutations, p < 0.05).
Results: The results showed widespread significant associations of DTI metrics and age across the whole-brain WM tracts including fornix (Fx), cingulum (Cg), corpus callosum (CC), superior and inferior longitudinal fasciculus (SLF and ILF), inferior fronto-occipital fasciculus (IFOF), internal and external capsule (IC and EC), corona radiata (CR), and posterior thalamic radiation (PTR). Table 1 shows age effects across different DTI metrics and groups. Negative age-associations in FA along with positive age-associations in AxD, MD, RD were found in most of the tracts. The overlap map of the significant age effects across both groups is shown in Figure 1. MO and NA were both more sensitive to degenerative changes in crossing fibres (e.g. IC, EC) than FA. In ApoE4-, negative associations of MO and NA with age coincide with those in FA, while positive age-association with MO and NA in the IC and EC are not observed for FA. There was no positive correlation between age and MO and NA in the ApoE4+ group (Figure 2 and Figure 3). Finally, the difference between groups in the age associations were mostly in posterior WM regions including sCC and PTR.
Discussion: The effect of ApoE4 on neurodegeneration is still not fully understood. Our results replicated the significant decrease in FA along with increased diffusivity (AxD, MD, and RD) with advancing age in a number of WM tracts across the carrier and non-carrier groups. MO and NA enable the observation of selective degeneration in aging by measuring the shape of the tensor. Decreased MO and NA in gCC and part of the PTR was found in both groups, likely caused by reduced myelin integrity which is representedby a change in the shape of tensor. In regions without prominent fibre crossings, the ApoE4+ group exhibited weaker age effects than ApoE4-. In regions of fibre crossings such as IC and CR (crossings between spinal cord and longitudinal association fibres), increase in MO and NA with age was only found in ApoE4-, suggesting that these regions may be associated with high inter-subject heterogeneity in the ApoE4+ group.
Conclusion: Our findings emphasize the influence of ApoE4 status on the age-related effects on WM microstructure in cognitively normal older adults. Tensor-shape metrics (MO and NA) may be more sensitive to group differences in age-related effects than conventional DTI metrics, especially in crossing WM fibres, and may be useful in further investigation of WM microstructure across the life span.

Acknowledgements

This research was funded by the Thailand Research Fund (TRF) through the Royal Golden Jubilee Ph.D. Programme (Grant No. PHD/0069/2559) to PS and PM, Faculty of Medicine Research Fund (Grant No. 087/2562), and the Excellence in Osteology Research and Training Center (ORTC) with partially support by Chiang Mai University. We gratefully thank the Rotman Research Institute at Baycrest, Toronto, Canada, for hosting PS as a visiting graduate student. We would like to especially thank Jacob JL. Matthew for his advice and kind support throughout the OASIS-3 data set-up in this study.

References

1. Fernandez CG, Hamby ME, McReynolds ML, & Ray WJ. The role of APOE4 in disrupting the homeostatic functions of astrocytes and microglia in aging and Alzheimer’s disease. Front. Aging Neurosci. 2019;11:14.

2. Corder EH, Saunders AM, Strittmatter WJ, et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science. 1993;261(5123): 921-923.

3. Operto G, Cacciaglia R, Grau-Rivera O, et al. White matter microstructure is altered in cognitively normal middle-aged APOE-ε4 homozygotes. Alzheimers Res Ther. 2018;10(1): 48.

4. Ryan L, Walther K, Bendlin BB, et al. Age-related differences in white matter integrity and cognitive function are related to APOE status. Neuroimage. 2011;54(2):1565-1577.

5. Chad JA, Pasternak O, Chen JJ. Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fibre architecture. Neurobiol Aging 2021 (in press).

6. Ennis DB, & Kindlmann G. Orthogonal tensor invariants and the analysis of diffusion tensor magnetic resonance images. Magn Reson Med. 2006;55(1):136-146.

7. OASIS-3: Principal Investigators: T. Benzinger, D. Marcus, J. Morris; NIH P50 AG00561, P30 NS09857781, P01 AG026276, P01 AG003991, R01 AG043434, UL1 TR000448, R01 EB009352. AV-45 doses were provided by Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly.

Figures

Figure 1. The overlap map of the significant associations between DTI metrics with increasing age across the whole-brain WM in nondemented ApoE carrier (ApoE4+, green), ApoE4 non-carrier (ApoE4-, orange), and both groups (Overlap, pink) at p < 0.05. Note: MO is increasing with age, MO(↑); MO is decreasing with age, MO(↓); NA is increasing with age, NA(↑); NA is decreasing with age, NA(↓).

Figure 2. Significant associations between DTI metrics with increasing age across the whole-brain WM in nondemented ApoE non-carrier (ApoE4-) group at p < 0.05. The colour bar shows the negative (blue) and positive (yellow) correlation between DTI metrics with age. Note: MO is increasing with age, MO(↑); MO is decreasing with age, MO(↓); NA is increasing with age, NA(↑); NA is decreasing with age, NA(↓).

Figure 3. Significant associations between DTI metrics with increasing age across the whole-brain WM in nondemented ApoE4 carrier (ApoE4+) group at p < 0.05. The colour bar shows the negative (blue) and positive (yellow) correlation between DTI metrics with age. Note: fractional anisotropy, FA; mean diffusivity, MD; radial diffusivity, RD; axial diffusivity, AxD; mode of anisotropy, MO; and norm of anisotropy, NA.

Table 1. Summary of age effects across different DTI metrics and groups. Tracts involved: fornix (Fx), cingulum (Cg), genu, body, splenium of the corpus callosum (bCC, gCC, and sCC), superior and inferior longitudinal fasciculus (SLF and ILF), inferior fronto-occipital fasciculus (IFOF), internal and external capsule (IC and EC), corona radiata (CR), and posterior thalamic radiation (PTR). Note: ↑ = Positive association with advancing age; ↓ = Negative association with advancing age.

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