Cerebrovascular injury markers explain the effect of systemic vascular risk on cognitive decline in older adults with lower amyloid burden. (20th December 2022)

• Record Type: Journal Article
• Authors: Shirzadi, Zahra; Yau, Wai‐Ying Wendy; Rabin, Jennifer S.; Buckley, Rachel F.; Properzi, Michael J; Fu, Jessie Fanglu; Hsieh, Stephanie; Thibault, Emma G.; Mojiri‐Forooshani, Parisa; Goubran, Maged; MacIntosh, Bradley J.; Black, Sandra E.; Price, Julie C; Johnson, Keith A.; Sperling, Reisa A.; Chhatwal, Jasmeer P.; Schultz, Aaron P.
• Is Part Of: Alzheimer's & dementia. Volume 18(2022)Supplement 6
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-20
• 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.066686
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Systemic vascular risk is a well‐established contributor to late‐life cognitive decline, yet the mechanism is not completely understood. We investigated whether neuroimaging‐based measures of vascular injury (white matter hyperintensity (WMH) volume, Peak width of Skeletonized Mean Diffusivity (PSMD), and relative cerebral blood flow (rCBF)) could explain the effect of systemic vascular risk on cognitive decline using longitudinal data from the Harvard Aging Brain Study. Method: We used the Framingham Heart Study cardiovascular disease risk score (FHS‐CVD) as an index of systemic vascular risk. We extracted WMH from structural MRI (https://hypermapp3r.readthedocs.io/ ) and PSMD from diffusion MRI (http://www.psmdmarker.com ). We performed kinetic modeling on dynamically‐acquired PiB‐PET data to extract 1) amyloid burden as the distribution volume ratio (PiB‐DVR) and 2) relative tracer delivery (PiB‐R1 via MRTM reference‐tissue analysis as a proxy of rCBF). Global cognition was assessed using Preclinical Alzheimer Cognitive Composite (PACC). We considered two linear mixed effect models to examine whether cerebrovascular injury markers could explain the FHS‐CVD effect on PACC change over time: 1) FHS‐CVD on PACC change controlling for age, sex, years of education, and PiB‐DVR; 2) the previous model including WMH, PSMD, and PIB‐R1. Analyses were stratified by high (PiB+) and low (PiB‐) baseline amyloid burden. Result: Figure 1 illustrates the relationships between demographics and neuroimaging measures at baseline. Table 1 shows the demographics and study information. We observed a significant effect of FHS‐CVD on PACC change (PiB‐: t=‐3.9, p<0.001 (Table 2); PiB+: t=‐2.6, p=0.008). When the cerebrovascular injury markers were included in the model, the effect of FHS‐CVD was reduced in the PiB‐ group while PSMD and PiB‐R1 explained PACC change (Table 3; Figure 2). The second model fit was significantly better than the first model (L.ratio= 25.9, p<0.001). The effects remained significant after controlling for gray matter volume. In contrast, cerebrovascular injury measures did not explain the effect of FHS‐CVD on PACC change in the PIB+ group. Conclusion: These results demonstrate that cerebrovascular injury largely explains the effect of systemic vascular risk on cognitive decline in older adults with lower amyloid burden suggesting mechanisms by which a higher systemic vascular risk impacts brain function.