The Pathology of Rapid Cognitive Decline in Clinically Diagnosed Alzheimer’s Disease

Participants

Data were requested from the NACC Database (visits conducted between September 2005 and March 2017). The NACC data sets used for this study were the Uniform Data Set (UDS), the NP Data Set, and the Genetic Data Set (RDD-Gen). Participants from NACC who had a total MMSE score between 12–30 at the initial visit, a presumptive etiological diagnosis of AD at the initial visit, and at least three visits with the UDS neuropsychology test battery were included. Participants unable to meet these criteria were excluded. The NACC dataset is fully de-identified, and all participants had provided written informed consent at their ADC, as approved by local institutional review boards [15].

Demographic information and clinical data

Clinical data from the NACC database were obtained from all participants meeting our above extraction criteria. This information included demographic information (age at initial visit, sex, race, level of education, age at cognitive onset, and age at death), baseline MMSE score, and clinical health history (variables of cardiovascular disease, autoimmune disease, psychiatric measures, and medications).

Neuropathological and genetic data

Pathologically determined AD was ascertained by creating a variable combining two NACC variables of amyloid plaques and tau proteins, ranked in severity by CERAD (C score) and Braak Stage (B score), respectively [16]. C Score ranks the density of neuritic plaques (neuron fragments surrounding amyloid-β protein) while B Score measures the cortical distribution of neurofibrillary tangles (aggregates of hyperphosphorylated tau proteins). Plaque and tangle scores in the NP database were derived according to the NIA–Reagan Institute criteria [17]. Pathologically verified AD was defined as a C score of C2 or higher combined with a B score of B2 (stage III) or higher [18]. Defining pathologically verified AD also allowed for the retrospective comparison of the pathological profile of a clinically diagnosed AD sample with a pathologically confirmed subset.

Variables of cerebral amyloid angiopathy, Lewy body distribution, atrophy (cerebral cortical atrophy measured 0–3 in severity and lobar atrophy measured as present/absent), multiple pathology and vascular pathology count variables, TDP-43, and APOE ɛ4 status were also compared between groups. It should be noted that some of these data points were not collected until Version10 of the NP database, leading to only a subset of individuals having this data.

Pathologically verified AD was defined by creating a binary variable (1 = C Score of C2 and B Score of B2 (or stage III) or higher; 0 = not meeting this criteria). Count variables of cerebrovascular disease and “other” pathologies were created to assess for burden of cerebrovascular disease and multiple pathologies.

Neuropsychological tests

Tests selected from the UDS neuropsychology test battery are as follows: MMSE, Wechsler Memory Scale-Revised Logical Memory Ia Story Units Recalled and Logical Memory IIa-Delayed Story Units Recalled, the Boston Naming Test (total raw), Animal Naming Test and Vegetable Naming (total raw), Digit Span forwards and backwards (trials correct), Trail Making Test Part A and B (seconds to complete), and the Wechsler Adult Intelligence Scale-Revised Digit Symbol test (total raw). The test selection identified tests across cognitive domains.

Classification of groups

Participants were classified into two different groups based on a progressive loss of points on the MMSE. Consistent with prior research, individuals were categorized as experiencing RCD if they had an average decline of ≥3 points on the MMSE per year over their first three ADC clinic visits; individuals who did not experience such loss were categorized as experiencing NCD [12].

Statistical analyses

We compared participant demographic, clinical history, and pathological data between groups using Chi-square tests for categorical variables, and independent-samples t-tests for continuous variables.

Subsequently, in order to identify potential independent baseline predictors of RCD, we constructed a multivariable logistic regression model using group membership as the outcome of interest. Independent predictors included in the model were determined in accordance with individual variable significance coupled with previous research on traits predictive of rapid decline in AD. Demographic factors, neuropsychology testing, and disease characteristics were added to the model in congruence with our stated hypothesis as described below:

Demographic factors of education, sex, and age were added to the model despite individual insignificance due to their correlation with neuropsychology testing.

We inspected statistically significant neuropsychological tests for multicollinearity as this could be problematic in the predictive model. Raw scores on the Wechsler Memory Scale-Revised Logical Memory Ia Story Units Recalled, the Animal Naming Test, and Trail Making Test Part B were included due to their significant baseline differences between groups and their relatively low collinearity.

Thyroid disease was included as a significant autoimmune disease measure that has also been cited in previous research as an indicator of worse cognitive trajectory [19, 20] along with neuropsychiatric measures of depression and nighttime behaviors (defined as presence versus absence from the Neuropsychiatric Inventory Questionnaire, NPI-Q [22]) added due to the frequent occurrence of these symptoms in Lewy body disease (LBD) and AD, respectively [21].

Statistical significance was established throughout at p < 0.05 All statistical analyses were performed with the use of SPSS (version 23.0).

Participant demographics and clinical data

This study included 290 participants clinically diagnosed with AD at their initial visit, 230 of which were classified as NCD, and 60 of which were classified as RCD. Those classified as NCD had a mean MMSE decline of 0.94 (SD:0.94) points per year, ranging from a loss of 2.67 points per year to a gain of 1.67 points per year, with mode loss of 0.66 points per year. Those classified as RCD had a mean MMSE decline of 4.28 (SD:1.23) points per year, ranging from a loss of 8 points per year to a loss of 3 points per year, with mode loss of 3.33 points per year. MMSE at initial ADC visit did not differ significantly between groups.

Time from initial diagnosis to death was significantly different between RCD and NCD, but other demographic variables did not differ significantly (Table 1.1).

Thyroid disease and AD medication use was more prevalent in the RCD group than the NCD group (30.0 versus 16.1%, p = 0.01; 79.7 versus 62.0%, p = 0.01, respectively). Anxiolytic medication use was significantly higher in the NCD group (9.2 versus 0%, p = 0.02). Other baseline clinical history measures (vascular risk factors, cardiovascular disease, psychiatric measures, and medications) did not vary between groups (see Table 1.2).

Neuropathological and genetic differences

There were differences in pathology between the RCD and NCD groups (see Table 2.1). However, differences in the Braak stage and plaque severity did not meet significance. Contrastingly, non-AD pathology did differ. Cerebral amyloid angiopathy was found to be significantly greater in patients with RCD than NCD (mean [SD]: 1.62[1.03] versus 1.13[1.02], p = 0.002). Additionally, individuals with RCD had significantly more diffuse neocortical Lewy bodies than NCD (20.0% versus 10.0%, p = 0.04), but showed no differences in limbic/amygdala-predominant, brainstem-predominant, or overall presence of Lewy body pathology.

In a subset of patients, atrophy at autopsy suggested that overall cerebral cortical atrophy (28 RCD/117 NCD: mean [SD] 1.54[0.92] versus 1.17[0.83], p = 0.04) as well as gross lobar atrophy (30 RCD/119 NCD: 33.3 versus 16.0%, p = 0.03), was markedly higher in RCD, while medial temporal lobe/hippocampal sclerosis did not differ between groups.

No significant differences were observed in vascular disease count or multiple pathology disease count, TDP-43, or the presence/predominance of the APOE ɛ4 allele.

Among the original total study sample (n = 290:230 NCD; 60 RCD), 218 patients (75%) had pathologically verified AD upon autopsy (Table 2.2). The NCD group contained 165 (72%) participants with pathologically verified AD while the RCD group contained 53 (88%). Identical analyses on the neuropathology of this subset with pathologically confirmed AD were conducted to determine if similar pathological findings were consistent in this subset. It was observed that Braak NFT and neuritic plaque severity were also not significantly different between groups in this subset, and neither was the severity of cortical atrophy, the only variable that differed in significance in this subgroup with respect to the full sample. However, the severity of cerebral amyloid angiopathy, prevalence of neocortical diffuse LBD, and gross lobar atrophy remained significantly different between groups.

Neuropsychological testing differences

Though baseline scores on the MMSE did not differ significantly, individuals with RCD had lower performance at baseline on the following neuropsychological measures: Wechsler Memory Scale-Revised Logical Memory Ia Story Units Recalled, the Boston Naming Test, the Animal Naming Test, and Trail Making Test part B (see Table 3 and Chart 1). Other neuropsychological measures did not vary at baseline.

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Chart 1

Neuropsychological Testing Differences

A model of clinical and neuropsychological predictors of RCD at baseline

A multivariable logistic regression model was fit to determine predictors of group membership, simultaneously entering related variables of disease characteristics, neuropsychological testing, and demographic information. Table 4 summarizes the results from the model, which was found overall to be statistically significant (χ² = 25.8, p = 0.002), though only slightly above chance level with an AUC of 0.70 (95% CI).

Presence of thyroid disease (odds ratio (OR): 2.87; 95% CI: 1.36–6.05; p = 0.005) was a significant baseline predictor of RCD as well as receiving a lower raw score on the Wechsler Memory Scale-Revised Logical Memory Ia Story Units Recalled (OR: 0.88; 95% CI: 0.80–0.97; p = 0.009).

Demographics of age, sex, and education were not associated with increased likelihood of an individual’s categorization as RCD within the model, nor were variables of nighttime behavior and depression from the NPI-Q, the Animal Naming Test, or Trail Making Test part B.

Central findings

This study looked at demographic, neuropsychological, and pathological correlates of RCD in AD in a large, well characterized sample with autopsy confirmation. The primary finding from our study is that patients with RCD had a more severe pathological signature than their NCD counterparts, specifically with more extensive comorbidity. This is evidenced in the autopsy data which demonstrated that RCD patients, despite having shorter time from diagnosis to death, had more cerebral amyloid angiopathy, greater atrophy, and more diffuse neocortical Lewy bodies. None of the observed demographic factors differed between the groups, which may indicate that RCD is driven primarily by biological factors (i.e., a more aggressive form of AD, with comorbidities) and less influenced by demographics (age, education, etc.) as previous research has suggested.

Secondary findings

Though RCD and NCD had similar baseline MMSE scores, individual neuropsychology test results suggest significant underlying baseline differences in language and memory (WMS Logical Memory Immediate Recall, Animal naming, BNT) and executive functioning (Trails B and WAIS-R Digit Symbol). Lower performance on these tests implies cortical dysfunction, which is consistent with the finding of more extensive extra-limbic atrophy, suggesting that disease has already progressed more extensively throughout the brain in the RCD group before their initial ADC visit. This demonstrates the importance of adequate neuropsychological characterization early on in the disease course, as well as the usefulness of and potential for the development of a predictive model of cognitive trajectory including similar measures.

Baseline cardiovascular risk factors and psychiatric symptoms also did not differentiate between groups, although a significantly higher portion of the RCD population was taking an AD medication at baseline visit. Observing that more RCD individuals are taking cognitive enhancing agents is indicative of other clinically distinguishing factors at baseline that were perceptible by a clinician, yet not captured in the database. This has been suggested in previous studies, which observe that cognitive symptoms may be indicated at baseline presentation without an obvious profile or causative effect [23].

Though a count of multiple pathologies did not appear significant, there was evidence of more comorbidity in the RCD group, with RCD presenting with more neocortical Lewy bodies and evidence of greater occurrence of autoimmune disease (thyroid disease). Other publications have also linked thyroid disease to cognitive decline [19, 20], though this is not consistent across studies [12].

While there is evidence of differences in clinically-identifiable factors at baseline, the regression model with a combination of factors of disease characteristics, neuropsychology testing, and demographic information was inadequately predictive of RCD. However, WMS logical memory immediate recall and thyroid disease were significant within the model, suggesting that further research is warranted, perhaps in different datasets.

Implications for current research

To our knowledge, the present sample is the largest with autopsy confirmation that has been examined for defining factors of RCD. Because of this, we sought to also examine many previous correlations with RCD found in previous publications. Our sample consists of 20% with RCD versus NCD, consistent with the proportions of previous research, varying between 11–40% [24]. We found that many of the distinguishing factors purported by past research did not significantly differentiate groups in our sample. Factors such as age, higher level of education, lower baseline cognition, neuropsychiatric status, and APOE ɛ4 status, were associated with RCD in prior research [12, 24], but did not reach statistical significance in the current sample, further emphasizing that RCD is still lacking consensus in disease profile and definition.

Limitations

One limitation of the present study is the limited specificity of certain data points in NACC, namely variables of vascular pathology, multiple pathology, and thyroid disease. For example, it was difficult from the current dataset to accurately assess severity of vascular burden because the data available suggested that all participants were greatly, and similarly, burdened. More recent data being collected in NACC NP V10 allows for a more nuanced severity quantification of vascular pathology, but it will take time to accumulate an adequate number of participants. The same is true of the multiple pathologies count, though with the opposite limitation, with our sample having a mode of zero additional pathologies. Thyroid disease is also not parsed out into hypo/hyperthyroidism in NACC; prospective data collection would be required to obtain this data. It should also be taken into consideration that the NACC database subject education is likely above the population average, thus potentially limiting the generalizability of results [25].

In regards to the neuropsychology test data, it has been suggested in previous research that the MMSE may be too blunt of an instrument, thus being a questionable choice by which to define RCD. The MMSE has been criticized for its limited ability to assess global cognitive function, namely its lack of sensitivity to language and executive functioning [26]. This could attest to executive and language differences between RCD and NCD at baseline despite nearly identical MMSE scores, and begs the question of whether it should be the measure of choice in defining RCD. However, it can be observed that the neuropsychology database in NACC is also relatively limited in expansiveness, thus restricting the ability to probe deeply into cognition between groups [27].

It is also worth acknowledging the increased possibility of false-positives (Type I error) within our results due to multiple comparisons. The results of this study are hypothesis-generating so we did not adjust for multiplicity.

Implications for future research

Future research should look to biomarkers that might help predict the likelihood of one’s categorization as RCD in vivo, relating to neuropsychology test data over time. Looking at cerebral amyloid angiopathy, the presence of neocortical Lewy bodies, and patterns of atrophy could provide valuable insight into the differences between NCD and RCD in life. It would also be useful to look at datasets that parse out hypo- and hyperthyroidism in individuals with clinically diagnosed AD to see if there are distinguishing clinical presentations between these diseases. In clinical trials, it would be useful to segregate the RCD group to study the differences in their reactions to experimental interventions, and to be aware of the possible comorbidity with Lewy body in this cohort, which might impact trial results.

Overall, we demonstrated that individuals with RCD show more severe pathology, are more likely to have pathological comorbidity, and have lower baseline scores on neuropsychology tests of language and executive function. Despite evidence of baseline differences, a predictive model including these variables was not optimally sensitive to RCD categorization, suggesting that future research is needed to better capture the early profile of patients most likely to decline rapidly.