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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Manifestaciones Clínicas
Nancy X Chen1, Sarah Tomaszewski Farias2, Alexander Ivan B Posis1
1University of California, Davis, Davis, CA, USA.
Background:
Subjective cognitive decline can be an early indicator of underlying brain pathology. We investigated associations of subjective cognitive decline with imaging biomarkers of neurodegeneration, cerebrovascular injury, and amyloid burden.
Method:
Harmonized sample of ethno-racially diverse study participants from Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE), LifeAfter90 (LA90), and the Study of Healthy Aging in African Americans (STAR) aged 50-101. Subjective cognitive decline was measured via the 12-item Everyday Cognition (ECog) scale (range=1-4), where higher scores suggest more subjective cognitive decline. Regional brain volumes and white matter integrity were measured using 3T MRI. Amyloid was measured using florbetapir PET among a random subset of KHANDLE and LA90. Measures of cerebrum and gray matter volume (cerebrum gray, hippocampus, frontal, occipital, parietal, temporal), cerebrospinal fluid volume (lateral, third), and log-white matter hyperintensities were normalized with intracranial volume. We also examined free water fraction and fractional anisotropy. All MRI measures were z-standardized. Amyloid burden was quantified using standard uptake value ratios (SUVR) and amyloid positivity was defined as SUVR ≥1.1. Linear regression and logistic models estimated associations of subjective cognitive decline with global and regional brain volumes and white matter injury, SUVR, and amyloid-positivity. All models adjusted for sex, race/ethnicity, age, education, and cohort.
Result:
Participants' (N = 822) mean±SD age was 77.8±10.2, 60% were women, 50% had at most a high school education and 18% identified as Asian, 43% as Black, 16% as Hispanic/Latino (Table 1). Overall, the mean ECog was 1.36±0.36, mean amyloid SUVR was 1.09±0.17, and 33.7% were amyloid-positive). Higher (worse) ECog was associated with smaller volumes in cerebrum (β=-0.18,95%CI=-0.31,-0.05), cerebrum gray (β=-0.30,95%CI=-0.47,-0.13), hippocampus (β=-0.35,95%CI=-0.51,-0.18), and temporal cortex (β=-0.21,95%CI=-0.39,-0.03); larger volumes in lateral (β=0.27,95%=CI 0.11,0.43) and third ventricles (β=0.17,95%CI 0.01,0.33); greater log-white matter hyperintensities (β=0.29,95%CI=0.12,0.45) and free water (β=0.17,95%CI=0.004,0.33); and lower fractional anisotropy (β=-0.15,95%CI -0.22,-0.08) (Table 2). Greater ECog was also associated with higher amyloid-SUVR (β=0.05,95%CI 0.01,0.09) and higher odds of amyloid-positivity (OR=1.71,95%CI 1.05,2.80) (Table 2).
Conclusion:
In this diverse cohort of older adults, greater subjective cognitive decline was associated with worse late-life brain health. These findings highlight the importance of addressing subjective cognitive decline as potential indicators of neurodegeneration, cerebrovascular injury, and amyloid burden.
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