Abstract
Background and purpose
The aim was to investigate the effect of APOE ε4 allele on cognitive decline in adAD. Presence of the APOE ε4 allele reduces age of symptom onset, increases disease progression, and lowers cognitive performance in sporadic Alzheimer's disease (AD), while the impact of the APOE ε4 allele in autosomal‐dominant AD (adAD) is incompletely known.
Methods
Mutation carriers (MCs; n = 39) and non‐carriers (NCs; n = 40) from six adAD families harbouring a mutation in the APP (28 MCs and 25 NCs) or the PSEN1 genes (11 MCs and 15 NCs) underwent repeated cognitive assessments. A timeline of disease course was defined as years to expected age of clinical onset (YECO) based on history of disease onset in each family. The MC and NC groups were comparable with regard to demographics and prevalence of the APOE ε4 allele. The relationship between cognitive decline and YECO, YECO2, education, APOE, and APOE‐by‐YECO interaction was analysed using linear mixed‐effects models.
Results
The trajectory of cognitive decline was significantly predicted by linear and quadratic YECO and education in MCs and was determined by age and education in NCs. Adding APOE ε4 allele (presence/absence) as a predictor did not change the results in the MC and NC groups. The outcome also remained the same for MCs and NCs after adding the APOE‐by‐YECO interaction as a predictor. Analyses of APP and PSEN1 MCs separately showed favourable APOE‐by‐YECO interaction in APP (less steep decline) and unfavourable interaction in PSEN1 (steeper decline), linked to the APOE ε4 allele.
Conclusion
The APOE ε4 allele influences cognitive decline positively in APP and negatively in PSEN1 mutation carriers with adAD, indicating a possible antagonistic pleiotropy.
Keywords: APOE, APP/PSEN1 , autosomal‐dominant Alzheimer's disease, cognition, longitudinal
Presence of the APOE ε4 allele influences cognitive decline positively in APP mutation carriers (MCs) and negatively in PSEN1 MCs. In contrast, the opposite pattern was obtained when APOE ε4 was absent. These findings indicate a possible antagonistic pleiotropy.
INTRODUCTION
Presence of the APOE ε4 allele (ε4+) is associated with a younger age of symptom onset in a dose‐related manner in sporadic Alzheimer's disease (sAD) compared to absence of an APOE ε4 allele (ε4−), as shown by the earliest onset in APOE ε4 homozygotes, followed by heterozygotes, with the latest onset in non‐carriers of the APOE ε4 allele [1]. In sAD, APOE ε4+ has been related to higher regional density of plaque and tangle brain pathology [2], an increased amount of white matter hyperintensities [3], dose‐dependent hippocampal thinning [4], increased cerebrospinal fluid biomarker abnormality [5], elevated positron emission tomography‐measured beta‐amyloid binding [6], and decreased glucose metabolism [7]. Furthermore, it has been shown that APOE ε4+ has a negative impact on cognition in sAD, as well as in cerebrovascular disease and type 2 diabetes [8, 9]. In addition, it has been shown that APOE ε4+ is associated with impaired episodic memory in non‐demented older adults compared to APOE ε4− [10, 11]. Some studies have also documented negative influences in cognitive domains other than memory [12]. Together, the effects of APOE ε4 on sAD indicate a multifactorial disorder related to allelic variation in APOE, aging, cerebrovascular disease, traumatic brain injury, the immune system, mitochondrial functioning, and infection. All these risk factors may act collectively to cause Alzheimer's disease (AD) pathology in sAD [13].
Studies of the Colombian family (the PSEN1 E280A mutation) have reported a reduced age of onset due to presence of the ε4 allele [14], while other studies have reported a lack of significant negative influence on age of onset depending on APOE ε4+ [15, 16] and no effect on cognitive decline [17, 18]. In children with a family history of AD, significant negative effects of APOE ε4+ on cognition have been reported when comparing children with and without the ε4 allele [19].
Presence of the APOE ε4 allele has been shown to have differential effects on memory performance depending on age. Studies in young adults and children have found better cognitive performance in cognitive tasks in APOE ε4 carriers compared to ε4 non‐carriers, which could be indicative of antagonistic pleiotropy [20, 21]. In a study of embryonic development, the ε4 allele was present less frequently in spontaneously aborted embryos versus controls, suggesting that the presence of ε4 has protective effects during embryogenesis [22]. In addition, there are reports of favourable effects of APOE ε4+ on tasks of attention in young healthy individuals [23] and there was a favourable effect of APOE ε4+ across ages in a short‐term memory task with brief retention intervals [24]. Similarly, adults with a high parasite burden living in the Amazon carrying APOE ε4 performance across cognitive domains was positively affected in adults with a high versus low parasite burden of living [25]. A recent study using transgenic mice (APP/PSEN1) suggested that the APOE gene has two opposing roles, one favourable in aging and another related to beta‐amyloid toxicity and impairment [26], corresponding to the originally proposed antagonistic pleiotropy in aging [27].
In summary, previous reports regarding the effects of APOE ε4 on cognition in various populations are mixed. Age, various diseases, type of AD, and challenging environments may be involved. The objective of the present longitudinal study was to investigate the effect of the APOE ε4 allele on cognitive decline in mutation carriers (MCs) and non‐carriers (NCs) from autosomal‐dominant AD (adAD) families, departing from four hypotheses. First, the presence of APOE ε4 has a negative effect on cognition in adAD MCs. Second, APOE ε4 effect interacts with time of disease development in adAD MCs. Third, the APOE effect on cognitive decline is different in APP and PSEN1 owing to a differential cognitive trajectory [28]. Fourth, there is no APOE and APOE‐by‐time interaction in NCs.
METHODS
Participants
Adult members from six families carrying a mutation of early‐onset adAD were invited to a comprehensive clinical examination at the Memory Clinic, Karolinska University Hospital Huddinge, Sweden. Three families carried an APP mutation (Swedish, Arctic and London), and three families carried a PSEN1 mutation (I143T, M146V and H163Y; see details in Appendix S1). No family carried a PSEN2 mutation. All individuals who accepted a clinical examination were enrolled in the study (39 mutation carriers [MCs] and 40 non‐carriers [NCs]). All participants were invited to follow‐up examinations: 59 individuals had two examinations, 33 individuals had three examinations, and 22 had four or more examinations, with a total of 229 examinations.
The demographic characteristics of the participants are presented in Table 1. The participant groups (MCs and NCs from APP and PSEN1 families) were comparable in demographic and basic clinical characteristics (Appendix S1).
TABLE 1.
Baseline demographic and clinical characteristics in APP and PSEN1 mutation carriers and non‐carriers in autosomal‐dominant Alzheimer's disease
| Characteristic | Carriers | Non‐carriers | ||
|---|---|---|---|---|
| APP | PSEN1 | APP | PSEN1 | |
| N (female/male) | 28 (10/18) | 11 (4/7) | 25 (11/14) | 15 (7/8) |
| Age, mean ± SD years | 47.9 ± 11.2 | 35.6 ± 9.6 | 47.4 ± 9.9 | 33.8 ± 11.1 |
| YECO, mean ± SD | −7.1 ± 11.0 | −11.3 ± 11.4 | −7.5 ± 9.7 | −8.2 ± 11.8 |
| Education, mean ± SD years | 10.9 ± 2.5 | 12.0 ± 3.0 | 10.8 ± 2.9 | 10.6 ± 1.5 |
| APOE ε4 (presence/absence) | 13/15 | 6/5 | 7/18 | 6/9 |
| MMSE score, mean ± SD | 25.3 ± 4.6 | 26.7 ± 5.2 | 28.7 ± 1.7 | 29.5 ± 0.8 |
Abbreviation: MMSE, Mini Mental State Examination; YECO, years to expected clinical onset.
Diagnosis
The clinical diagnosis was decided by a consensus meeting of medical professionals based on all available reports, excluding information on the mutation status as described above [28] (details are presented in Appendix S1).
At baseline, eight MCs were diagnosed with dementia [29] and as having AD [30], and nine MCs were diagnosed with mild cognitive impairment (MCI) [31]. All the remaining 22 MCs were asymptomatic. At the last examination, 26 MCs were diagnosed with AD dementia and 13 were still asymptomatic. No NC was diagnosed with AD, MCI, or any other disease affecting the brain, either at baseline or at any follow‐up examination.
Advancement of disease
The advancement of disease was calculated as present age minus the family‐specific age of clinical onset of disease (years to expected age of clinical onset [YECO]) in line with previous research [16, 28]. This measure is invariant within families and is significantly associated with the observed age of onset and parental age of onset [16, 28].
Assessment of cognition
Cognitive assessment focused on tests within five domains: verbal (Similarities test), visuospatial (Block Design test), episodic memory (Rey Auditory Verbal Learning Test [RAVLT]), executive function (Digit Symbol test), and attention (Trailmaking Test A [TMTA]) as described above [28] (details are presented in Appendix S1).
APOE genotyping
The APOE genotyping method is described in Appendix S1.
Statistical analysis
Details of statistical analyses are presented in Appendix S1.
RESULTS
Baseline
Most participants were below 50 years of age (5–10 years ahead of clinical onset). Test results were poorer in MCs versus NCs for four out of the five tests (Block Design, RAVLT, Digit Symbol, and TMTA; p values < 0.01). Participants in APP and PSEN1 families did not differ in any of the cognitive tests (p values > 0.1). Furthermore, there was no significant gene (APP/PSEN1)‐by‐mutation (MC/NC) interaction on any of the five tests (p values > 0.1). These results, which were obtained after taking demographic characteristics (age, sex and education) into account, indicate that MCs and NCs from APP and PSEN1 families were comparable at baseline.
Longitudinal cognitive change
Firstly, longitudinal cognitive change was analysed using linear mixed models in relation to linear and curvilinear measures of disease advancement (YECO and YECO2) and years of education separately in MCs and NCs (results are presented in Table S1). In MCs, the model of cognitive decline was significant in all five tests (Similarities, Block Design, RAVLT, Digit Symbol and TMTA; p values < 0.001 or p values < 0.01) covering five cognitive domains (verbal, visuospatial, episodic memory, executive function, and attention, respectively). The decline was highly significant for linear and curvilinear predictors (Table S1). Education was a strong positive predictor in four tests in MCs (p values < 0.001 or p values < 0.01; Table S1).
In NCs, there was a significant cognitive decline in two tests – linear in the Digit Symbol test and curvilinear in the Similarities test (p values < 0.05), while there was no significant change in the other cognitive tests (p values > 0.1). Education was a strong positive predictor in all five tests (p values < 0.05).
These results indicate that MCs had extensive and disease‐related changes across time in all domains according to relatively large beta weights, while NCs had minor time‐related cognitive changes in two tests (Similarities and Digit Symbol) as indicated by the relatively small beta weights (Table S1).
Next, the effect of APOE on cognition was analysed by adding APOE to the previous analyses (presence vs. absence of the ε4 allele) as a fourth predictor (Table 2). The outcome showed that APOE was not a significant predictor in any of the five cognitive tests in MCs (p values > 0.1). This finding contradicts the first hypothesis that APOE is a main factor in MCs. In NCs, APOE ε4+ was a significant negative predictor for performance in the TMTA measuring information processing speed (p < 0.05), while APOE was not a significant factor in the other four tests (p values > 0.1). The results indicate that the negative effect of APOE ε4+ in NCs may have implications for normal aging as APOE ε4 may be a possible covariate of the typical decline of processing speed in aging. In addition, the effects of the linear and curvilinear time (YECO and YECO2) were significant and negative on all cognitive tests in MCs, in agreement with the previous results.
TABLE 2.
Outcome of linear mixed‐effect models on cognitive tests (dependent variable) and predictors (years to expected clinical onset [YECO], YECO2, education, and APOE ε4 presence/absence) showing estimates, standard errors and p values of significant predictors in mutation carriers and non‐carriers
| Domain/Test | Carriers (n = 39) | Non‐carriers (n = 40) | ||||||
|---|---|---|---|---|---|---|---|---|
| YECO | YECO2 | Educ | APOE | YECO | YECO2 | Educ | APOE | |
| est | est | est | est | est | est | est | est | |
| [SE] | [SE] | [SE] | [SE] | [SE] | [SE] | [SE] | [SE] | |
| p | p | p | p | p | p | p | p | |
| Verbal/Sim |
−0.140 [0.021] <0.001 |
−0.006 [0.001] <0.001 |
+0.244 [0.084] <0.01 |
ns |
ns |
−0.001 [0.001] <0.05 |
+0.250 [0.049] <0.001 |
ns |
| Visuospatial/BD |
−0.172 [0.021] <0.001 |
−0.005 [0.001] <0.001 |
+0.272 [0.090] <0.01 |
ns |
ns |
ns |
+0.236 [0.076] <0.01 |
ns |
| Episodic memory/RAVLT |
−0.162 [0.020] <0.001 |
−0.005 [0.001] <0.001 |
+0.137 [0.064] <0.05 |
ns |
ns |
ns |
+0.146 [0.062] <0.05 |
ns |
| Executive function/DiSy |
−0.182 [0.020] <0.001 |
−0.005 [0.001] <0.001 |
+0.239 [0.081] <0.01 |
ns |
−0.017 [0.008] <0.05 |
ns |
+0.170 [0.059] <0.01 |
ns |
| Attention/TMTA |
−0.019 [0.004] <0.001 |
−0.001 [0.001] <0.01 |
ns |
ns |
ns |
ns |
+0.020 [0.006] <0.01 |
−0.068 [0.032] <0.05 |
Abbreviations: BD, Block Design test; est, estimate; DiSy, Digit Symbol test; RAVLT, Rey Auditory Verbal Learning Test; ns, not significant; Sim, Similarities test; TMTA, Trailmaking Test A; YECO, years to expected clinical onset.
In NCs, the time effect was significant and negative in two tests (Digit Symbol and Similarities test) in agreement (Table 2). Years of education was a significant and strong positive predictor for performance in four tests in MCs and in all five tests in NCs (Table 2).
In the third analysis, the APOE ε4‐by‐YECO interaction was added as a fifth predictor to the previous analysis with three predictors. An overview of the outcome is presented separately for MCs and NCs (Table 3). The outcome showed that the APOE‐by‐YECO interaction was not significant in any of the five cognitive tests in MCs (p values > 0.1). Furthermore, the main effect of APOE was not significant in any cognitive test (p values > 0.1) in MCs. The effect of education was significant and strong in four tests (p values < 0.05) as in the second analysis. This pattern of results for MCs was identical to the pattern of results in the previous step.
TABLE 3.
Outcome of linear mixed‐effect models on cognitive test results (dependent variables) and predictors (years to expected clinical onset [YECO], YECO2, education, APOE ε4 presence/absence, and YECO‐by‐APOE interaction) showing estimates, standard errors and p values of significant predictors in mutation carriers and non‐carriers
| Domain/Test | YECO | YECO2 | Educ | APOE | APOE × YECO |
|---|---|---|---|---|---|
| est | est | est | est | est | |
| [SE] | [SE] | [SE] | [SE] | [SE] | |
| p | p | p | p | p | |
| Carriers, n = 39 | |||||
| Verbal/Sim |
−0.156 [0.024] <0.001 |
−0.005 [0.001] <0.001 |
+0.237 [0.083] <0.001 |
ns |
ns |
| Visuospatial/BD |
−0.176 [0.023] <0.001 |
−0.005 [0.001] <0.001 |
+0.248 [0.081] <0.01 |
ns |
ns |
| Episodic memory/RAVLT |
−0.159 [0.023] <0.001 |
−0.005 [0.001] 0.001 |
+0.137 [0.064] <0.05 |
ns |
ns |
| Executive function/DiSy |
−0.169 [0.023] <0.001 |
−0.005 [0.001] <0.001 |
+0.235 [0.081] <0.01 |
ns |
ns |
| Attention/TMTA |
−0.036 [0.005] <0.001 |
−0.001 [0.001] <0.001 |
ns |
ns |
ns |
| Non‐carriers n = 40 | |||||
| Verbal/Sim |
ns |
−0.002 [0.001] <0.05 |
+0.245 [0.050] <0.001 |
ns |
ns |
| Visuospatial/BD |
ns |
ns |
+0.239 [0.077] <0.01 |
ns |
ns |
| Episodic memory/RAVLT |
ns |
ns |
+0.152 [0.064] <0.05 |
ns |
ns |
| Executive function/DiSy |
ns |
ns |
+0.164 [0.060] <0.01 |
ns |
ns |
| Attention/TMTA |
ns |
ns |
+0.020 [0.006] <0.01 |
−0.071 [0.034] <0.05 |
ns |
Abbreviations: BD, Block Design test; est, estimate; DiSy, Digit Symbol test; RAVLT, Rey Auditory Verbal Learning Test; ns, not significant; Sim, Similarities test; TMTA, Trailmaking Test A; YECO, years to expected clinical onset.
In NCs, there was no significant interaction effect in any test (p values > 0.1), and the main effect of APOE was significant in one test (TMTA), in agreement with the result in the previous analysis (Table 3). The lack of significant time‐related effect in NCs was consistent with the previous analyses, and the significant positive effects of education in almost every cognitive test in NCs were also consistent with the previous analyses (Table 3).
In the fourth and final analysis, the effect on cognition using the five previous predictors (YECO, YECO2, education, APOE, and APOE‐by‐YECO interaction) was analysed separately in APP and PSEN1 MCs (Table 4). In APP MCs, there were two significant and positive APOE‐by‐YECO interaction effects in the Similarities test (verbal domain; p < 0.05) and the TMTA (attention domain; p < 0.05). The significant positive beta weights for APOE‐by‐YECO interaction were unexpected. The positive APOE‐by‐YECO interactions in all five tests in APP MCs imply that the marked time‐related (YECO and YECO2) cognitive decline is counteracted to some extent by the APOE‐by‐YECO interaction due to presence of the ε4 allele. APOE as a main factor was not significant as found in the previous steps. Compared to the results in the previous analysis, the significant negative time‐related effect on YECO and the positive effect of education on cognitive decline remained significant with marked estimates, while the effect on YECO2 remained significant with less strong estimates.
TABLE 4.
Outcome of linear mixed‐effect models on cognitive test results (dependent variables) and predictors (years to expected clinical onset [YECO], YECO2, education, APOE ε4 presence/absence, and YECO‐by‐APOE interaction) showing estimates, standard errors and p values of significant predictors in APP and PSEN1 mutation carriers
| Domain/Test | YECO | YECO2 | Educ | APOE | APOE × YECO |
|---|---|---|---|---|---|
| est | est | est | est | est | |
| [SE] | [SE] | [SE] | [SE] | [SE] | |
| p | p | p | p | p | |
| APP mutation carriers, n = 28 | |||||
| Verbal/Sim |
−0.136 [0.032] <0.001 |
ns |
ns |
ns |
+0.099 [0.047] <0.05 |
| Visuospatial/BD |
−0.201 [0.041] <0.001 |
−0.006 [0.001] <0.001 |
ns |
ns |
+0.079 [0.046] p = 0.09 |
| Episodic memory/RAVLT |
−0.126 [0.029] <0.001 |
ns |
+0.168 [0.077] <0.05 |
ns |
+0.058 [0.045] p > 0.10 |
| Executive function/DiSy |
−0.150 [0.029] <0.001 |
ns |
+0.219 [0.095] <0.05 |
ns |
+0.067 [0.043] p > 0.10 |
| Attention/TMTA |
−0.031 [0.006] <0.001 |
ns |
ns |
ns |
+0.024 [0.009] <0.05 |
| PSEN1 mutation carriers, n = 11 | |||||
| Verbal/Sim |
−0.186 [0.039] <0.001 |
−0.007 [0.001] <0.001 |
ns |
ns |
+0.006 [0.028] p > 0.10 |
| Visuospatial/BD |
−0.044 [0.020] <0.05 |
ns |
ns |
ns |
−0.084 [0.026] p < 0.01 |
| Episodic memory/RAVLT |
−0.184 [0.036] <0.001 |
−0.078 [0.001] <0.001 |
ns |
−1.367 [0.398] <0.01 |
−0.052 [0.026] p = 0.053 |
| Executive function/DiSy |
−0.206 [0.040] <0.001 |
−0.008 [0.001] <0.001 |
+0.329 [0.142] <0.05 |
ns |
−0.056 [0.029] p = 0.058 |
| Attention/TMTA |
−0.031 [0.010] <0.01 |
−0.001 [0.001] <0.001 |
ns |
ns |
−0.002 [.007] p > 0.10 |
Abbreviations: BD, Block Design test; est, estimate; DiSy, Digit Symbol test; RAVLT, Rey Auditory Verbal Learning Test; ns, not significant; Sim, Similarities test; TMTA, Trailmaking Test A; YECO, years to expected clinical onset.
In PSEN1 MCs, there was one significant and negative APOE‐by‐YECO interaction in the Block Design test (visuospatial domain; p < 0.01 [Table 4]). The beta weights were negative in this test as well as in three other cognitive tests (RAVLT, Digit Symbol and TMTA), although not significant. The implication of negative APOE‐by‐YECO interaction is that the marked time‐related (YECO and YECO2) cognitive decline in PSEN1 MCs is reinforced by the APOE‐by‐YECO interaction, that is, presence of the ε4 allele. The effect of APOE as a main factor was significant and negative in one cognitive test (RAVLT; p < 0.01).
Comparison of the significant APOE‐by‐YECO interaction effects, positive in APP and negative in PSEN1 MCs, implies that the APOE ε4 allele influences cognitive decline differently by showing a favourable influence in APP MCs and a harmful influence in PSEN1 MCs for unknown reasons.
To examine these results more closely, the APOE‐by‐YECO interaction effects on cognitive decline due to APOE ε4+/ε4− across the five tests were visualized separately in APP and PSEN1 MCs (Figure 1). In APP MCs (left column), the cognitive decline across all five tests was less pronounced when the APOE ε4 was present compared to absent. In PSEN1 MCs (right column), the cognitive decline was more pronounced across all tests when the APOE ε4 allele was present compared to absent.
FIGURE 1.
Longitudinal cognitive decline across time of disease advancement (years to expected clinical onset [YECO]) on five tests in APP and PSEN1 mutation carriers (MCs) divided into APOE subgroups, showing APP MCs with and without the ε4 allele in the left column and PSEN1 MCs with and without the ε4 allele in the right column. RAVLT, Rey Auditory Verbal Learning Test; Sim, Similarities test; TMTA, Trailmaking Test A
DISCUSSION
The aim of this study was to explore how cognitive decline in adAD is affected by the presence or absence of the APOE ε4 allele and the APOE‐by‐YECO interaction term in addition to disease advancement (YECO, YECO2) and years of education in APP or a PSEN1 MCs and NCs from six adAD families.
The results showed that linear and curvilinear disease advancement (YECO) were powerful predictors of cognitive decline in MCs, in agreement with previous research on cognition in adAD [16, 28, 32]. In addition, years of education was a powerful positive predictor that mitigates cognitive decline [33]. In contrast, there was no or only minimal change in cognition across time in NCs in most tests, a typical finding in middle‐aged normal individuals [34]. The results of the three‐predictor model of cognitive decline in adAD was considered as a point of departure for investigating the possible additive contribution of APOE ε4 for prediction of cognitive decline in adAD.
The outcome after adding APOE (presence/absence of ε4) as a predictor to the three previously used predictors showed that APOE did not contribute significantly to cognitive decline in any test in MCs. Similar findings of nonsignificant APOE ε4 effects on cognition in adAD have been obtained previously [17, 18, 35]. A few studies, for instance, one study in children with a family history of AD, have reported contrasting results [19]. Compared to previous research in sAD showing a negative effect of APOE ε4, the lack of a clear negative effect in adAD in the present study and other studies suggests that different mechanisms exist, one in sAD and another in adAD. It could be that presence of the APOE ε4 allele is a negative factor for sAD because it influences the cerebrovascular system, while this is not the case or is less so in adAD. It is well documented that APOE ε4 is related to the vascular system, and it could be speculated that manifest and incident disease(s) in the vascular system may be partly responsible for the APOE effect in sAD and MCI [8, 9, 13, 20, 21]. An alternative interpretation could be that APOE is age‐related. In support of the age‐related APOE hypothesis, a longitudinal study on memory in normal aging and preclinical AD [11] showed that the APOE ε4 effect shifted from positive to negative when participants were aged 50–60 years [11]. In addition, APOE is involved in many biological systems, not only the cerebrovascular system, which implies that other mechanisms could explain the lack of significant APOE ε4 effects on cognition in adAD MCs in the present study [20, 21].
In NCs, presence of the APOE ε4 allele was a significant negative factor for cognitive function in the attention domain (TMTA test), which is indicated by a decline in cognitive processing speed in normal aging [34, 36], but not in other cognitive domains. The time‐related predictors (YECO and YECO2) were nonsignificant, except for one test (Digit Symbol) that indexed the executive domain and another test (Similarities) that indexed the verbal domain; the statistical power of these associations was small compared to the corresponding power of these predictors in MCs. The detrimental effect of APOE ε4 on attention (TMTA) in NCs could be compared to similar findings in normal aging [36]. Similar negative effects have been reported in numerous studies of normal aging [37, 38, 39].
The addition of APOE‐by‐YECO interaction as a fifth predictor did not contribute significantly to the model in any cognitive tests, either in MCs or in NCs. These results run counter to the hypothesis that the APOE effect increases across time as presented in the Introduction. However, it has been demonstrated that the cognitive trajectories are different in APP and PSEN1 MCs [28], which motivated the corollary hypothesis that the effect of APOE and APOE‐by‐YECO interaction may depend on the mutated adAD gene (APP and PSEN1).
The main result was the differential effect of the APOE‐by‐YECO interaction on cognitive decline in MCs when APP and PSEN1 MCs were compared. The beta weights of the APOE‐by‐YECO interaction were positive in all five cognitive tests and significant in two tests (Similarities and TMTA) in APP MCs (i.e., favourable). In contrast, the APOE‐by‐YECO interaction was negative in four cognitive tests (the exception was the verbal Similarities test) and significant in one test (Block Design) in PSEN1 MCs, that is, it was unfavourable. This pattern of results, observed as contrasting mean level of trajectories across YECO in most tests for APOE ε4 in APP versus PSEN1, was an unexpected and novel finding (Figure 1). Specifically, the cognitive decline started relatively early and continued slowly in the preclinical disease course in the cognitive tests in APP MCs when APOE ε4 was present. In contrast, the trajectory of cognitive decline was biphasic, slow in the early preclinical part of the disease course, and steep around the estimated clinical onset in PSEN1 MCs when APOE ε4 was present. These findings indicate that APOE ε4+ was a favourable factor with regard to cognition in APP MCs and an unfavourable factor for cognitive decline in PSEN1 MCs. When APOE ε4 was absent, the cognitive decline was pronounced across the disease course in APP MCs, while cognitive decline was markedly smaller in PSEN1 MCs, and possibly not significantly different from normal aging. Together, these findings could be conceived of as a double dissociation and a gene–gene interaction (APP/PSEN1 vs. ε4+/ε4−).
A possible interpretation of the different cognitive trajectories in APP and PSEN1 linked to APOE ε4 presence versus absence indicates opposing roles of APOE ε4 in APP and PSEN1 genes. The pattern was similar across cognitive domains, indicating cognitive independence. The pattern was also unrelated to demographic features, as the groups were comparable. Furthermore, there was no difference in mean years to estimated clinical onset. So far there is no explanation of the finding other than a gene–gene interaction with unknown players. However, the APOE‐by‐YECO interaction on cognitive decline in APP and PSEN1 MCs must be regarded as uncertain because the group sample sizes are small. A reliable conclusion awaits information from larger future studies on this topic. Meanwhile, it is an intriguing pattern of observations that can be related to the antagonistic pleiotropy phenomenon [40].
The antagonistic pleiotropy phenomenon has been observed in different contexts (high‐parasite environments), aging (cognitively normal middle‐aged and adults), populations (fetal development, children and adults), and specific cognitive tasks (short vs. long exposure in short‐term memory/attention and episodic memory vs. non‐memory) [11, 16, 20, 21, 22, 23, 24, 25] in agreement with a recent suggestion that APOE has opposing roles in aging and neurodegeneration based on mice studies [26]. A possible explanation for antagonistic pleiotropy is that the APOE ε4 allele may lead to increased resistance to toxic agents, or may contribute to brain repair [20, 21, 41].
The findings of the present study can be summarized in relation to the hypotheses. The first hypothesis, that the presence of APOE ε4 has a negative effect on cognition in MCs, was not confirmed. The second hypothesis, that there is a possible time‐related interaction (APOE‐by‐YECO) in cognition in MCs, was not confirmed. The third hypothesis, that APOE and the APOE‐by‐YECO interaction term have differential effects on cognition in APP and PSEN1 MCs, was partly confirmed. The fourth hypothesis, that APOE and the APOE‐by‐YECO interaction term have no effect on cognition in NCs, was confirmed with one exception: the TMTA attention domain showed a decrease in performance.
It is advantageous that the present study included MCs and NCs from six adAD families, followed with repeated examinations of cognition and covering more than 40 years of natural disease course. The main drawback is the small sample size, laying the study open to random influences on results.
To conclude, the results indicate that presence of the APOE ε4 allele influences cognitive decline positively in APP MCs (relatively slow progression) and negatively in PSEN1 MCs (pronounced progression). When APOE ε4 was absent, the opposite pattern was obtained, pronounced progression in APP MCs and slow or minimal progression in PSEN1 MCs. These results indicate opposing roles of the APOE ε4 allele on cognition in APP and PSEN1 that may reflect an antagonistic pleiotropic phenomenon.
AUTHOR CONTRIBUTIONS
Ove Almkvist: study conception, data acquisition, statistical analysis, data interpretation, drafting and revision of the manuscript, final approval, accountable for the study. Charlotte Johansson: data acquisition, data interpretation, revision of the manuscript, final approval, accountable for the study. Jose Laffita‐Mesa: data acquisition, data interpretation, revision of the manuscript, final approval, accountable for the study. Steinunn Thordardottir: data acquisition, data interpretation, revision of the manuscript, final approval, accountable for the study. Caroline Graff: data interpretation, revision of the manuscript, final approval, accountable for the study, responsible for the cohort, principal investigator.
FUNDING INFORMATION
The study was supported by grants from the Swedish Research Council (VR 2018‐02754), the Swedish Dementia foundation, the Swedish Brain Foundation, the Regional Agreement on Medical Training and Clinical Research (ALF) between Stockholm Region and Karolinska Institutet, the Swedish Alzheimer foundation, the Stohnes Foundation, and the Gamla Tjänarinnor Foundation.
CONFLICT OF INTEREST
None.
ETHICAL APPROVAL
All participants provided written informed consent to participate in the study, which was conducted according to the declaration of Helsinki and subsequent revisions. Ethical approval was obtained from the regional Human Ethics Committee of Stockholm, Sweden.
Supporting information
Appendix S1
ACKNOWLEDGEMENTS
We are grateful to all participants for their interest and efforts in all examinations. We are also grateful to the genetic guardian, Håkan Thonberg, and the research coordinators, Anne Kinhult‐Ståhlbom, Nathalie Asperén and Catharina Roman for their professional work.
Almkvist O, Johansson C, Laffita‐Mesa J, Thordardottir S, Graff C. APOE ε4 influences cognitive decline positively in APP and negatively in PSEN1 mutation carriers with autosomal‐dominant Alzheimer's disease. Eur J Neurol. 2022;29:3580‐3589. doi: 10.1111/ene.15536
DATA AVAILABILITY STATEMENT
Data are available upon reasonable request to the corresponding author or the principal investigator (Caroline Graff).
REFERENCES
- 1. Corder EH, Saunders AM, Strittmatter WJ, et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science. 1993;261:921‐923. [DOI] [PubMed] [Google Scholar]
- 2. Sabbagh MN, Malek‐Ahmadi M, Dugger BN, et al. The influence of apolipoprotein E genotype on regional pathology in Alzheimer's disease. BMC Neurol. 2013;13:44. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Sudre CH, Cardoso MJ, Frost C, et al. APOE e4 status is associated with white matter hyperintensities volume accumulation rate independent of AD diagnosis. Neurobiol Aging. 2017;53:67‐75. [DOI] [PubMed] [Google Scholar]
- 4. Kerchner GA, Berdnik D, Shen JC, et al. APOE ε4 worsens hippocampal CA1 apical neuropil atrophy and episodic memory. Neurology. 2014;82:691‐697. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Kester MI, Blankenstein MA, Bouwman FH, van Elk EJ, Scheltens P, van der Flier WM. CSF biomarkers in Alzheimer's disease and controls: associations with APOE genotype are modified by age. J Alzheimers Dis. 2009;16:601‐607. [DOI] [PubMed] [Google Scholar]
- 6. Grimmer T, Tholen S, Yousefi BH, et al. Progression of cerebral amyloid load is associated with the apolipoprotein E ε4 genotype in Alzheimer's disease. Biol Psychiatry. 2010;68:879‐884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Shinohara M, Sato N. The roles of apolipoprotein E, lipids and glucose metabolism in the pathogenesis of Alzheimer's disease. Adv Exp Med Biol. 2019;1128:85‐101. [DOI] [PubMed] [Google Scholar]
- 8. McGuinness B, Carson R, Barrett SL, Craig D, Passmore AP. Apolipoprotein epsilon4 and neuropsychological performance in Alzheimer's disease and vascular dementia. Neurosci Lett. 2010;483:62‐66. [DOI] [PubMed] [Google Scholar]
- 9. Zhen J, Lin T, Huang X, et al. Association of ApoE genetic polymorphism and type 2 diabetes with cognition in non‐demented aging Chinese adults: a community based cross‐sectional study. Aging Dis. 2018;9:346‐357. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Bondi MW, Salmon DP, Galasko RG, et al. Neuropsychological function and apolipoprotein E genotype in the preclinical detection of Alzheimer's disease. Psychol Aging. 1999;14:295‐303. [DOI] [PubMed] [Google Scholar]
- 11. Caselli RJ, Locke DE, Dueck AC, et al. The neuropsychology of normal aging and preclinical Alzheimer's disease. Alzheimers Dement. 2014;10:84‐92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Goltermann J, Redlich R, Dohm K, et al. Apolipoprotein E homozygous ε4 allele status: a deteriorating effect on visuospatial working memory and global brain structure. Front Neurol. 2019;10:552. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Armstrong RA. Risk factors for Alzheimer's disease. Folia Neuropathol. 2019;57:87‐105. [DOI] [PubMed] [Google Scholar]
- 14. Pastor P, Roe CM, Villegas A, et al. Apolipoprotein E e4 modifies Alzheimer's disease onset in an E280A PS1 kindred. Ann Neurol. 2003;54:163‐169. [DOI] [PubMed] [Google Scholar]
- 15. Ryan NS, Nicholas JM, Weston PSJ, et al. Clinical phenotype and genetic associations in autosomal dominant familial Alzheimer's disease: a case series. Lancet Neurol. 2016;15:1326‐1335. [DOI] [PubMed] [Google Scholar]
- 16. Ryman DC, Acosta‐Baena N, Aisen PS, et al. Symptom onset in autosomal dominant Alzheimer disease: a systematic review and meta‐analysis. Neurology. 2014;83:253‐260. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Aguirre‐Acevedo DC, Lopera F, Henao E, et al. Cognitive decline in a Colombian kindred with autosomal dominant Alzheimer disease: a retrospective cohort study. JAMA Neurol. 2016;73:431‐438. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Talboom JS, Håberg A, De Both MD, et al. Family history of Alzheimer's disease alters cognition and is modified by medical and genetic factors. Elife. 2019;8:e46179. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Bloss CS, Delis DC, Salmon DP, Bondi MW. Decreased cognition in children with risk factors for Alzheimer's disease. Biol Psychiatry. 2008;64:904‐906. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Liu CC, Kanekiyo T, Xu H, et al. Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol. 2013;9:106‐118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Tuminello ER, Han SD. The apolipoprotein e antagonistic pleiotropy hypothesis: review and recommendations. Int J Alzheimers Dis. 2011;2011:726197. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Zetterberg H, Palmér M, Ricksten A, et al. Influence of the apolipoprotein E epsilon4 allele on human embryonic development. Neurosci Lett. 2002;324:189‐192. [DOI] [PubMed] [Google Scholar]
- 23. Evans S, Dowell NG, Tabet N, Tofts PS, King SL, Rusted JM. Cognitive and neural signatures of the APOE E4 allele in mid‐aged adults. Neurobiol Aging. 2014;35:1615‐1623. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Zokaei N, Grogan J, Fallon SJ, et al. Short‐term memory advantage for brief durations in human APOE ε4 carriers. Sci Rep. 2020;10:9503. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Trumble BC, Stieglitz J, Blackwell AD, et al. Apolipoprotein E4 is associated with improved cognitive function in Amazonian forager‐horticulturalists with a high parasite burden. FASEBJ. 2017;31:1508‐1515. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Hudry E, Klickstein J, Cannavo C, et al. Opposing roles of apolipoprotein E in aging and neurodegeneration. Life Sci Alliance. 2019;2:e201900325. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Williams GC. Pleiotropy, natural selection, and the evolution of senescence. Evolution. 1957;195(11):398‐411. [Google Scholar]
- 28. Almkvist O, Rodriguez‐Vieitez E, Thordardottir S, et al. Longitudinal cognitive decline in autosomal‐dominant Alzheimer's disease varies with mutations in APP and PSEN1 genes. Neurobiol Aging. 2019;82:40‐47. [DOI] [PubMed] [Google Scholar]
- 29. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders (DSM‐IV‐TR). 4th ed. Text revision, Author 2000. American Psychiatric Association; 2013. [Google Scholar]
- 30. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS‐ADRDA work group under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease. Neurology. 1984;3:939‐944. [DOI] [PubMed] [Google Scholar]
- 31. Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment–beyond controversies, towards a consensus: report of the international working group on mild cognitive impairment. J Intern Med. 2004;256:240‐246. [DOI] [PubMed] [Google Scholar]
- 32. Bateman RJ, Xiong C, Benzinger TL, et al. Clinical and biomarker changes in dominantly inherited Alzheimer's disease. N Engl J Med. 2012;367:780. [Published correction appears]. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Stern Y. Cognitive reserve. Neuropsychologia. 2009;47:2015‐2028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Bosnes I, Bosnes O, Stordal E, Nordahl HM, Myklebust TÅ, Almkvist O. Processing speed and working memory are predicted by components of successful aging: a HUNT study. BMC Psychol. 2022;10:16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Bussy A, Snider BJ, Coble D, et al. Dominantly inherited Alzheimer network. Effect of apolipoprotein E4 on clinical, neuroimaging, and biomarker measures in noncarrier participants in the dominantly inherited Alzheimer network. Neurobiol Aging. 2019;75:42‐50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Salthouse TA. Trajectories of normal cognitive aging. Psychol Aging. 2019;34:17‐24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Reas ET, Laughlin GA, Bergstrom J, Kritz‐Silverstein D, Barrett‐Connor E, McEvoy LK. Effects of APOE on cognitive aging in community‐dwelling older adults. Neuropsychology. 2019;33:406‐416. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Small BJ, Rosnick CB, Fratiglioni L, Bäckman L. Apolipoprotein E and cognitive performance: a meta‐analysis. Psychol Aging. 2004;19:592‐600. [DOI] [PubMed] [Google Scholar]
- 39. Wisdom NM, Callahan JL, Hawkins KA. The effects of apolipoprotein E on non‐impaired cognitive functioning: a meta‐analysis. Neurobiol Aging. 2011;32:63‐74. [DOI] [PubMed] [Google Scholar]
- 40. Smith CJ, Ashford JW, Perfetti TA. Putative survival advantages in young apolipoprotein ɛ4 carriers are associated with increased neural stress. J Alzheimers Dis. 2019;68:885‐923. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Lanfranco MF, Ng CA, Rebeck GW. ApoE lipidation as a therapeutic target in Alzheimer's disease. Int J Mol Sci. 2020;21:6336. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Appendix S1
Data Availability Statement
Data are available upon reasonable request to the corresponding author or the principal investigator (Caroline Graff).