presents the demographics of the entire sample and subgroups with each modality of assessments. All 269 completed baseline clinical and psychometric assessments. 217 (81%) had a LP to obtain CSF, 206 (77%) completed PET PIB, 147 (55%) had a MRI, and 232 (86%) completed the attentional battery. One hundred and eight (40%) participants completed all baseline procedures (clinical, psychometric, attention, LP, MRI, PET PIB).
Characteristics of ACS Cohort at Baseline
As shown in , the mean level of CSF Aβ42
decreased significantly with age at a rate of −7.76 pg/mL per year (SE=2.14 pg/mL, p=0.0004) in those with a positive FH but not in those without (p=0.35). The presence of an APOE4 allele did not alter the effect of FH on the age-related decrease in CSF Aβ42
(p=0.5). Those with an ε4 allele had lower levels of age-adjusted CSF Aβ42
compared with those without (p<0.0001), and the decrease was larger if FH was positive compared with negative (F(1, 209)=5.29, p=0.02). Sensitivity analyses with multiple imputations51
on CSF Aβ42
confirmed these findings.
CSF Amyloid-beta42 as a functions of age and family history.
The variance increased among individuals age 55 or older when compared with the younger age group for CSF tau (χ2(1) = 9.71, p=0.002) and MCBP (χ2(1) = 98.35, p<.0001). presents the estimated slope (per year of age) for MCBP and CSF tau on younger (<55 y) and older individuals (>=55 y) as a function of FH and APOE4. No significant effect of FH or APOE4 was found for CSF tau on the age-related rate of change, but individuals with a positive FH had a higher level of CSF tau than those otherwise (F(1,152)=4.60, p=0.03) at age 55. For individuals younger than 55, MCBP increased by age at a significantly faster pace for individuals with APOE4 compared with those without APOE4 (F(1, 62.4)=4.72, p=0.03), eventually leading to a higher level of MCBP for those with APOE4 compared to without (p=0.01). For individuals older than 55, a trend (p=0.09) was found to suggest a faster age-related increase of MCBP for individuals with APOE4 compared with those without APOE4. Individuals with a positive FH and a positive APOE4 had the largest age-related increase of MCBP (p<0.0001).
Estimated slope (per year of age, 95% confidence interval) for MCBP and CSF tau on younger (<55 y) and older (>=55 y) individuals as a function of FH and APOE4
Brain volumes as determined by MRI decreased with age, but the difference was not statistically significant by FH (total cerebral brain volume F(1, 132)= 0.90, p=0.34; right hippocampal volume F(1, 139)=1.85, p=0.18; left hippocampal volume F(1, 139)= 0.31, p=0.58).
From a subsample of 165 participants who had DTI data, the age-adjusted mean level of fractional anisotropy was lower for individuals with a FH of AD when compared with those without in the genu (F(1,142)=3.91, p=0.05) and in the splenium (F(1,142)=4.12, p=0.04) of the corpus callosum. In the gyrus rectus, individuals with APOE4 had lower level of fractional anisotropy (F(1, 142)=4.75, p=0.03) and higher level of radial diffusivity (F(1, 142)=4.3, p=0.04) than those without APOE4. Age-related increase in radial diffusivity in the precuneus is faster if FH was positive compared with negative only among individuals with APOE4 (F(1,142)=4.67, p=0.03).
The mean performance level of auditory consonant trigrams decreased significantly with age at the rate of −0.411/year (SE=0.125, p=0.001) for these with a positive FH but not for those with a negative FH (p=0.52).
115 and 52 participants reported their mother and father’s age of onset of DAT, respectively. An earlier mother’s age of onset was correlated with larger reaction time difference between pure blocks and switched blocks of trials from the CVOE task46
(Spearman r=−0.21, p=0.04), and an earlier father’s age of onset was correlated with poorer performance in WAIS III Similarities (r=0.44, p=0.01).
Exploratory correlational analyses across the entire modalities of biomarkers confirmed those previously reported in the literature52–54
Significant correlations between MCBP and CSF biomarkers (tau r=0.22, ptau181
r=0.19, and CSF Aβ42
r=−0.41) were observed in the entire ACS cohort. Some of these are potentially modulated by age, but not by FH. In the younger cohort (age <55 y), MCBP was not significantly correlated with CSF biomarkers or brain volumes. In the older cohort (age at least 55 y), however, MCBP was significantly correlated with CSF biomarkers (Aβ42
r=−0.53, tau r=0.24, ptau181
r=0.22). Further, CSF and imaging biomarkers were correlated with Stroop performance in the younger sample only in two occasions (Aβ42
with greater interference in RTs r = −0.28, MCBP with Simon coefficient of variation (COV) r=0.31). In the older sample, however, CSF and imaging biomarkers were correlated with poorer performance across many attention measures (e.g., Aβ42
with task switching COV r = −0.22 and interference errors r = −0.20; MCBP with task switching COV r =0.19, interference RT r=0.17 and errors r =0.19, incongruent errors r=0.19, and with Simon COV r=0.17). Brain volumetric measures were also correlated with attentional and working memory measures (e.g., total cerebral brain volume with rotation span r = 0.22; left hippocampal volume with rotation span r=0.35) in the older sample. Because of a large number of correlations assessed across all modalities of markers, these findings were subject to a higher false positive rate (than 5%). Therefore they were preliminary and will only serve to generate scientific hypotheses that need to be critically tested in future studies.
Analyses were repeated on the subgroup of individuals who completed all procedures. The findings were consistent with the reported statistics, although a severe loss of statistical power resulted in losses of statistical significance.