Utility of DTI as a prognostic biomarker in MCI: Beyond AD biomarkers: Neuroimaging: Neuroimaging predictors of cognitive decline. (7th December 2020)

• Record Type: Journal Article
• Authors: Pillai, Sheela Kumari Raghavan; Przybelski, Scott A.; Reid, Robert I.; Graff‐Radford, Jonathan; Lesnick, Timothy G.; Zuk, Samantha M.; Knopman, David S.; Machulda, Mary M.; Mielke, Michelle M.; Petersen, Ronald C.; Jack, Clifford R.; Vemuri, Prashanthi
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 4
• 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.039871
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Given that a proportion of mild cognitive impaired (MCI) individuals are amyloid negative and have cerebrovascular disease (CVD), there is a need for biomarkers that can complement AD biomarkers (amyloid and neurodegeneration) for the prediction of future cognitive decline in MCI. The aim of our study was to determine the utility of diffusion tensor imaging (DTI) as a CVD marker for prediction of future cognitive decline in individuals with MCI in conjunction with amyloidosis and neurodegeneration. Method: We identified 132 MCI individuals ≥60 years old (55 % were amyloid positive and 59 % were male) from the population based sample of Mayo Clinic Study of Aging (MCSA) who had structural MRI, DTI, amyloid PET, and at least one clinical follow‐up after the imaging at the time of their clinical visit as MCI. All imaging scans were acquired and processed using in house developed protocols and pipelines. We used fractional anisotropy in the genu of corpus callosum (FAGCC), as a CVD marker, education/occupation score as a resilience variable, and global cognitive z‐score as the cognitive outcome. Using mixed effect models for cognitive decline, we evaluated three models to test the prognostic ability of (i) DTI marker alone, (ii) DTI marker and amyloid PET, (iii) DTI marker, amyloid PET, and neurodegeneration (cortical thickness). The final parsimonious models included the significant interactions of potential predictors with time, main effects nested within those interactions, and other significant main effects. Since the adjustment for conventional CVD measures like WMH was important to determine the utility DTI over traditional measures, we further assessed the value of FAGCC in conjunction with white matter hyper intensity (WMH). Result: We found: i) FAGCC was associated with cognitive decline after adjusting for amyloid PET neurodegeneration (Figure 1 and Table 1) and ii) FAGCC was associated with cognitive decline even after controlling for WMH and WMH was no longer significant after accounting for FAGCC (Table 2). Conclusion: DTI has significant utility for prediction of cognitive decline in MCI from population‐based samples and will provide complementary information to AD biomarkers.