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There are minimal data directly comparing plasma neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) in aging and neurodegenerative disease research. We evaluated associations of plasma NfL and plasma GFAP with brain volume and cognition in two independent cohorts of older adults diagnosed as clinically normal (CN), mild cognitive impairment (MCI), or Alzheimer’s dementia.
We studied 121 total participants (Cohort 1: n = 50, age 71.6 ± 6.9 years, 78% CN, 22% MCI; Cohort 2: n = 71, age 72.2 ± 9.2 years, 45% CN, 25% MCI, 30% dementia). Gray and white matter volumes were obtained for total brain and broad subregions of interest (ROIs). Neuropsychological testing evaluated memory, executive functioning, language, and visuospatial abilities. Plasma samples were analyzed in duplicate for NfL and GFAP using single molecule array assays (Quanterix Simoa). Linear regression models with structural MRI and cognitive outcomes included plasma NfL and GFAP simultaneously along with relevant covariates.
Higher plasma GFAP was associated with lower white matter volume in both cohorts for temporal (Cohort 1: β = −0.33, p = .002; Cohort 2: β = −0.36, p = .03) and parietal ROIs (Cohort 1: β = −0.31, p = .01; Cohort 2: β = −0.35, p = .04). No consistent findings emerged for gray matter volumes. Higher plasma GFAP was associated with lower executive function scores (Cohort 1: β = −0.38, p = .01; Cohort 2: β = −0.36, p = .007). Plasma NfL was not associated with gray or white matter volumes, or cognition after adjusting for plasma GFAP.
Plasma GFAP may be more sensitive to white matter and cognitive changes than plasma NfL. Biomarkers reflecting astroglial pathophysiology may capture complex dynamics of aging and neurodegenerative disease.
Objective: We evaluated whether memory recall following an extended (1 week) delay predicts cognitive and brain structural trajectories in older adults
Clinically normal older adults (52–92 years old) were followed longitudinally for up to 8 years after completing a memory paradigm at baseline [Story Recall Test (SRT)] that assessed delayed recall at 30 min and 1 week. Subsets of the cohort underwent neuroimaging (N = 134, mean age = 75) and neuropsychological testing (N = 178–207, mean ages = 74–76) at annual study visits occurring approximately 15–18 months apart. Mixed-effects regression models evaluated if baseline SRT performance predicted longitudinal changes in gray matter volumes and cognitive composite scores, controlling for demographics.
Worse SRT 1-week recall was associated with more precipitous rates of longitudinal decline in medial temporal lobe volumes (p = .037), episodic memory (p = .003), and executive functioning (p = .011), but not occipital lobe or total gray matter volumes (demonstrating neuroanatomical specificity; p > .58). By contrast, SRT 30-min recall was only associated with longitudinal decline in executive functioning (p = .044).
Memory paradigms that capture longer-term recall may be particularly sensitive to age-related medial temporal lobe changes and neurodegenerative disease trajectories. (JINS, 2020, xx, xx-xx)
To develop and validate the Discrepancy-based Evidence for Loss of Thinking Abilities (DELTA) score. The DELTA score characterizes the strength of evidence for cognitive decline on a continuous spectrum using well-established psychometric principles for improving detection of cognitive changes.
DELTA score development used neuropsychological test scores from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (two tests each from Memory, Executive Function, and Language domains). We derived regression-based normative reference scores using age, gender, years of education, and word-reading ability from robust cognitively normal ADNI participants. Discrepancies between predicted and observed scores were used for calculating the DELTA score (range 0–15). We validated DELTA scores primarily against longitudinal Clinical Dementia Rating-Sum of Boxes (CDR-SOB) and Functional Activities Questionnaire (FAQ) scores (baseline assessment through Year 3) using linear mixed models and secondarily against cross-sectional Alzheimer’s biomarkers.
There were 1359 ADNI participants with calculable baseline DELTA scores (age 73.7 ± 7.1 years, 55.4% female, 100% white/Caucasian). Higher baseline DELTA scores (stronger evidence of cognitive decline) predicted higher baseline CDR-SOB (ΔR2 = .318) and faster rates of CDR-SOB increase over time (ΔR2 = .209). Longitudinal changes in DELTA scores tracked closely and in the same direction as CDR-SOB scores (fixed and random effects of mean + mean-centered DELTA, ΔR2 > .7). Results were similar for FAQ scores. High DELTA scores predicted higher PET-Aβ SUVr (ρ = 324), higher CSF-pTau/CSF-Aβ ratio (ρ = .460), and demonstrated PPV > .9 for positive Alzheimer’s disease biomarker classification.
Data support initial development and validation of the DELTA score through its associations with longitudinal functional changes and Alzheimer’s biomarkers. We provide several considerations for future research and include an automated scoring program for clinical use.
Objectives: To describe multivariate base rates (MBRs) of low scores and reliable change (decline) scores on Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) in college athletes at baseline, as well as to assess MBR differences among demographic and medical history subpopulations. Methods: Data were reported on 15,909 participants (46.5% female) from the NCAA/DoD CARE Consortium. MBRs of ImPACT composite scores were derived using published CARE normative data and reliability metrics. MBRs of sex-corrected low scores were reported at <25th percentile (Low Average), <10th percentile (Borderline), and ≤2nd percentile (Impaired). MBRs of reliable decline scores were reported at the 75%, 90%, 95%, and 99% confidence intervals. We analyzed subgroups by sex, race, attention-deficit/hyperactivity disorder and/or learning disability (ADHD/LD), anxiety/depression, and concussion history using chi-square analyses. Results: Base rates of low scores and reliable decline scores on individual composites approximated the normative distribution. Athletes obtained ≥1 low score with frequencies of 63.4% (Low Average), 32.0% (Borderline), and 9.1% (Impaired). Athletes obtained ≥1 reliable decline score with frequencies of 66.8%, 32.2%, 18%, and 3.8%, respectively. Comparatively few athletes had low scores or reliable decline on ≥2 composite scores. Black/African American athletes and athletes with ADHD/LD had higher rates of low scores, while greater concussion history was associated with lower MBRs (p < .01). MBRs of reliable decline were not associated with demographic or medical factors. Conclusions: Clinical interpretation of low scores and reliable decline on ImPACT depends on the strictness of the low score cutoff, the reliable change criterion, and the number of scores exceeding these cutoffs. Race and ADHD influence the frequency of low scores at all cutoffs cross-sectionally.
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