This study presents associations with future clinical change of 2 core disease indicators in AD: MRI and CSF. We showed that both baseline MRI and CSF are independently associated with future cognitive decline. When average CDR-SB over time by biomarker quartiles was compared within each diagnostic group, MRI was more predictive of decline on the CDR-SB than CSF using likelihood ratio tests. This can also be observed in , where there is an ordered but no clear separation of cognitive decline by 25th, 50th, and 75th percentiles of t-tau and Aβ1–42. This relationship still holds after adjusting for baseline cognitive performance, supporting the idea that biomarkers provide additional information to clinical assessments. One practical implication of these findings is that either structural MRI by itself or in combination with CSF t-tau/Aβ1–42 levels could be used to identify subjects with MCI or AD at higher risk to decline more rapidly than others. This predictive power could be employed in certain clinical trial designs, such as phase II studies, where small numbers of subjects are studied to gain a preliminary sense of efficacy and could also be used in subset analyses of more rapid progressors in larger phase III studies.
In our time-to-event analysis, both STAND and log(t-tau/Aβ1–42
) were highly significant predictors of time to conversion of aMCI to AD. Our results are in concordance with most of the existing CSF and MRI literature, which has shown that MRI biomarkers such as hippocampal, entorhinal, and ventricular volumes and brain atrophy rates20–27
and CSF biomarker, t-tau/Aβ1–42
are significant predictors of future cognitive decline. Our results suggest that structural brain changes provide slightly better information than CSF to predict future clinical course of disease in subjects who meet criteria for MCI at baseline.
This is in contradiction with an earlier CSF-MRI study that found MRI biomarkers were not better predictors of future conversion compared to CSF biomarkers with a follow-up of 19 months.13
used visual grading of MRI scans for assessing medial temporal atrophy, in contrast to the automated analysis used here, which could account for the difference in results. It has been shown that the computerized scoring of MRI scans for neurodegenerative atrophy is more reliable than visual scoring of MRI scans30
and there is a better correlation between Braak stage and STAND scores (r
= 0.62) than hippocampal volume measurements (r
= 0.4) in subjects who have undergone antemortem MRI scans and then come to autopsy,11
supporting the use of STAND scores here.
, and t-tau reflect different aspects of AD pathology. Low CSF Aβ1–42
is a marker of fibrillary amyloid deposition in plaques. Near complete concordance is present between individuals with positive Pittsburgh Compound B (PIB)–PET scans and those with low CSF Aβ1–42
Although correlations with Aβ1–42
were present in our study, well accepted reasons exist to explain why Aβ1–42
might not correlate highly with clinical indices of disease intensity, where intensity is defined as rate of change. Amyloid deposition is regarded to be an early event that occurs prior to clinical symptoms, and therefore CSF Aβ1–42
is not a good leading indicator of near term cognitive decline.32
Increased CSF t-tau is a marker of neuronal injury which correlates well with NFT stage and NFT load.33,34
Atrophy on structural MRI also correlates with Braak NFT stage and NFT load35–38
but the most proximate histologic correlate of MRI volume loss is loss of neurons and synapses.8,9
It may at first be surprising to find that correlations with clinical disease progression are slightly stronger for MRI vs t-tau given that CSF t-tau is usually regarded as direct marker of neuronal injury. A possible explanation for the better correlation between MRI and cognitive/functional performance than that with t-tau is simply that MRI may be a more stable indicator of neuronal injury. Brain volume quantification with MRI has nothing analogous to daily turnover of a soluble protein with inevitable diurnal variation.39
Lower physiologic variation in brain volume may translate into stronger correlations between MRI and clinical indices of disease progression over many subjects. Another possible explanation is that MRI measures at a fixed point in time reflect cumulative damage while t-tau reflects recent or transient damage; e.g., t-tau levels become elevated immediately after acute brain injury.
There are some limitations to the study. First, the ADNI cohort is not generalizable to the general population. The recruitment mechanisms were those used for clinical trials in AD and included memory clinics, patient registries, public media campaigns, and other forms of public advertisements. Second, although numbers of subjects were relatively large, the period of clinical follow-up was relatively short, with median follow-up times of 2.0 years in CN, 1.5 years in aMCI, and 1.0 years in AD. Thus, conclusions about the relationship between baseline MRI and CSF to future clinical course pertain only to relatively short-term clinical outcomes.
Our main goal of this study was to better understand and compare the effect of CSF and global structural atrophy levels on risk of progression from aMCI to dementia. However, the findings provide some possibly useful information for a prospective clinical trial examining time from aMCI to dementia. To increase event rates, enrollment could be restricted to higher-risk subjects who have CSF or STAND scores above or below a certain value, although this may come at the risk of reducing generalizability. Alternatively, these measures could be used as stratification factors so that the study arms have not only similar demographic profiles but similar subclinical CSF and MRI profiles.