Results from our study provide several novel and important insights regarding the MoCA. First, the total score on the MoCA correlates significantly with total score on other well-known cognitive screens in a sample of older adults. Of note, the degree of shared variance was greater between the MoCA and the more comprehensive assessment provided by the RBANS compared with the more brief MMSE. Second, although the total MoCA score did not correlate significantly with the neuroimaging indices examined in this study, several MoCA subscales shared significant variance with neuroimaging indices that typically reflect brain changes associated with common aging (WBV, frontal gray matter, hippocampal volume). Finally, individuals who scored below the recommended cutoff on the MoCA performed significantly worse on the other cognitive screens compared with the individuals that performed above the cutoff, but there were no group differences on the neuroimaging measures.
The observation that the total score on the MoCA correlates significantly with performance on the MMSE and the RBANS is encouraging as it provides further convergent validity of the MoCA as a screening tool. Further, the stronger correlation between the total score on the MoCA and the more comprehensive RBANS suggests that the MoCA is capturing more behavioral data than what is obtained via the MMSE. This is particularly important as the MMSE has been criticized as lacking sensitivity to forms of cognitive dysfunction that involve executive impairment (O'Sullivan, Morris, & Markus, 2005
; Pachet, Astner, & Brown, 2010
), and the MMSE may not adequately identify neuropsychological abnormalities associated with etiologies that preferentially involve frontal or frontal-subcortical circuits (e.g., Hoops et al., 2009
; Popović, Serić, & Demarin, 2007
; Swirsky-Sacchetti et al., 1992
). The inclusion of tasks in the MoCA that tap executive function represents strength of the scale.
It is important to note, however, that the correlation between the total score on the MoCA and the total score on the RBANS was modest, with nearly 70% of the variance unaccounted for between the two scales. Given the depth of the RBANS relative to the MoCA, one interpretation of this finding is that the MoCA may lack ideal sensitivity to cognitive disorders compared with the RBANS. Alternatively, it is possible that the MoCA is capturing information not typically acquired by the RBANS. The RBANS has very good breadth of coverage though executive function is not a core feature of this battery. Nevertheless, performance on the RBANS correlated with WBV whereas performance on the MoCA did not, suggesting that overall the RBANS is more tightly associated with indices of brain integrity.
In contrast to our hypothesis, the total score on the MoCA did not correlate significantly with any of the neuriomaging variables though a modest trend was noted between total MoCA score and SH burden. The lack of significant relationships between these variables was surprising as the neuroimaging variables selected for analysis in this study are well-known biomarkers of cognitive aging (Mungas et al., 2005
; Raz et al., 2004
; for review, see Raz & Rodrigue, 2006
). The trend association between SH volume and total score on the MoCA is consistent with previous studies that have examined the impact of vascular burden on cognitive status among the elderly (Paul et al., 2005
), though the relationship in this study was modest, likely due to the relatively healthy nature of the cohort.
Individual domain scores on the MoCA did correlate significantly with several neuroimaging indices and the direction of these relationships were consistently in the predicted direction (i.e., better performances associated with higher volumes of brain regions). One surprising lack of association was between Delayed Memory and total hippocampal volume. Hippocampal volume did correlate inversely with performance on several MoCA subscales but this was not the case for the Delayed Memory trial. The absence of a significant correlation between these two variables may reflect the limited range in performance on the Delayed Memory trial. The Memory test includes only five words, presented twice to the individual. Further, the delay between presentation and delayed recall is only several minutes, and therefore, this task may not sufficiently engage hippocampal mechanisms to drive a correlation between these two variables in a relatively healthy sample. It may also be the case that inclusion of a recognition trial on the MoCA would more accurately reflect hippocampal integrity.
When the sample was subdivided according to individuals with performance above and below a score of 26 (recommended cutoff for impairment), the groups differed significantly on both the MMSE and the RBANS. These findings provide additional confidence regarding the utility of the MoCA as a brief cognitive screen as individuals with scores <26 exhibited significantly poorer performance on the other common neurocognitive measures. Like other cognitive screens, performance on the MoCA does not define the etiology of cognitive impairment and individuals with performances <26 on the MoCA will require a referral for more comprehensive neuropsychological assessment to define the potential etiology and characterize cognitive strengths and weaknesses. However, some caution is warranted regarding the utility of the cutoff score since both groups performed within normal limits on the MMSE and the RBANS, which is not surprising given that participants were enrolled in a study of “normal” aging. That is, although the group that earned a score below the recommended cutoff on the MoCA performed more poorly than individuals with scores above the cutoff, both groups performed in the average range on the other measures. This raises question as to whether the MoCA may lead to false positives in a clinical setting, particularly since on average individuals identified as impaired on the MoCA earned a total standardized score on the RBANS that was within normal limits.
In contrast to the differences in cognitive status, individuals with performances <26 on the MoCA did not reveal any significant differences in neuroimaging variables compared with those with scores above the clinical cutoff. This finding suggests that either the neuroimaging variables or the MoCA lacked the requisite sensitivity to define cerebral structural differences between these groups. Given that the neuroimaging variables were acquired using high power resolution MRI and we selected regions of interest known to relate to cognitive aging the former explanation is unlikely. Alternatively, the lack of association between these variables may reflect the cutoff criterion on the MoCA or the general health of the cohort. Further work is needed using receiver operating characteristic (ROC) curves and similar analyses to determine the stability of these findings.
A few limitations of the study should be noted. First, the sample included individuals enrolled in a longitudinal study of healthy individuals. Individuals were excluded from the parent study if they were previously diagnosed with cognitive impairment or other major health issues that increase the risk of cognitive impairment (e.g., diabetes, thyroid disease, etc.). The degree of shared variance between the total MoCA score and the individual neuriomaging variables does not reflect the associations that might be expected among a traditional clinical sample. Nevertheless, the individual MoCA scales did correlate significantly with individual neuroimaging variables. This suggests that the absence of a significant correlation between the total score on the MoCA and the neuroimaging variables reflected limited sensitivity of several select MoCA tests (i.e., delayed recall, repetition, and orientation). It is possible that the total score on the MoCA would exhibit greater sensitivity to normal aging indices if these tests were removed from the total score equation.
The present study did not incorporate ROC curves to clearly define the sensitivity and specificity of the MoCA as this was not the intent of the present investigation. Our data suggest that future studies of large cohorts are warranted to conduct these analyses and ensure that the MoCA has optimal psychometric properties for routine clinical use. It should also be noted that our sample size was sufficient to identify significant group differences on the RBANS on the MMSE when these contrasts were completed only for individuals that completed the neuroimaging protocol. Although neuroimaging differences were not observed, it is possible that significant group differences in neuroimaging indices would be obtained using more sensitive methods such as functional MRI, magnetic resonance spectroscopy, or diffusion tensor imaging.
In summary, the present study provides information regarding the utility of the MoCA by demonstrating correlations with the MMSE and the more comprehensive RBANS, as well as relationships between MoCA subscales and neuroimaging variables. However, some caution is also raised about the MoCA cutoff score since the recommended score of 26 did not discriminate groups on neuroimaging variables and performances were within normal limits on the other cognitive measures for individuals performing below the cutoff on the MoCA. Further studies are needed to determine whether more advanced imaging modalities (e.g., diffusion tensor imaging, fMRI, etc.) reveal significant differences in neuroanatomical integrity based on performance on the MoCA.