Amyloid angiopathy may contribute to white‐matter hyperintensities in Alzheimer's disease: Development of new models and analysis methods: Novel imaging analysis. (7th December 2020)

• Record Type: Journal Article
• Authors: Xia, Ying; Fazlollahi, Amir; Yates, Paul A.; Yassi, Nawaf; Desmond, Patricia M.; Salvado, Olivier; Villemagne, Victor L.L.; Rowe, Christopher C.; Fripp, Jurgen; Masters, Colin L.; Raniga, Parnesh
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 2
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.038899
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Cerebral amyloid angiopathy (CAA) is characterised by the accumulation of amyloid‐b (Aβ) in cerebral vessels and is often coexistent with Alzheimer's disease (AD). However, the overlap between CAA and AD and the contribution of CAA pathology to cerebrovascular lesions are not well understood. We hypothesize that in subjects with high Aβ load, the presence of imaging markers of CAA would be associated with greater white matter hyperintensities (WMH) burden. Method: Data used in the preparation of this article was obtained from the Australian Imaging Biomarkers and Lifestyle flagship study of ageing (AIBL). See www.aibl.csiro.au . We analysed MRI (SWI and FLAIR) and 11C‐PiB‐PET data from 98 cognitively normal (CN), 34 mild‐cognitive impairment (MCI) and 38 AD participants. Subjects were classified as being Aβ+ if their Aβ load was above 20 centiloid. SWI images were manually read for lobar microbleeds (LMB) and superficial siderosis. Subjects were classified as probable‐CAA (PCAA, 2 or more LMB or siderosis), possible‐CAA (SCAA, single LMB or siderosis) or non‐CAA (NCAA) based on the modified Boston criteria. Subjects classified as SCAA (n = 24) were excluded from further analysis since literature shows this group to be heterogenous and having low incidence of CAA pathology. WMH were automatically quantified on FLAIR. Group comparisons of WMH load were made using Kruskal Wallis rank test. A GLM was performed comparing WMH (log10 transformed) and CAA/ Aβ+ classification with age, intracranial volume, gender, APOE‐ ε 4 genotype and use of anti‐platelet or anticoagulant medication modelled as covariates. Result: Significantly higher WMH volume was observed in PCAA (n = 17) than NCAA (n = 129) (p‐value = 0.021, d = 0.36). When amyloid status was considered, PCAA/Aβ+ (n = 15) subjects had a significantly higher WMH load than NCAA/Aβ+ (n = 57) subjects (p‐value = 0.012, d = 0.57) and NCAA/Aβ‐ (n = 72) subjects (p‐value = 0.0006, d = 0.76) (Figure 1). PCAA/Aβ‐ (n = 2) were removed from further analysis. GLM results showed a significant association of WMH with PCAA/Aβ+ as compared to NCAA/Aβ+ (p‐value = 0.02, beta = 0.322 [0.056, 0.588]). Conclusion: Our findings suggest that CAA may contribute to WMH burden in subjects with high Aβ load. Further studies are required to validate our observations and characterise the contributions of CAA compared to small vessel disease associated with traditional risk factors towards the phenotype of AD.