Apolipoprotein E4, Amyloid, and Cognition in Alzheimer’s and Lewy Body Disease

Background: The role of APOE4 in the risk of Alzheimer’s disease, Lewy body disease, and their mixed diseases have not been evaluated in antemortem patients. Also, the APOE4 effect on β-amyloid deposition and cognition, with consideration of both Alzheimer’s and Lewy body diseases, remains unclear. We aimed to determine the APOE4 effects on the risk of Alzheimer’s disease, Lewy body disease, and their mixed diseases, as well as on β-amyloid deposition and cognition after adjusting for the effect of Alzheimer’s disease and Lewy body disease. Methods: Based on clinical features and 18 F-Florbetaben and dopamine transporter PET, we recruited 126 controls, 90 patients with typical Alzheimer’s disease (57 pure Alzheimer’s disease, 32 Lewy body variant of Alzheimer’s disease), 77 with typical Lewy body disease (56 pure Lewy body disease, 21 dementia with Lewy bodies with amyloid deposition), and 42 with typical Alzheimer’s disease/dementia with Lewy bodies. We used logistic regression analysis to investigate the effect of APOE4 on the risk of each disease and general linear models to investigate the independent and interaction effects of APOE4, Alzheimer’s disease, and Lewy body disease on β-amyloid deposition and cognition. Results: APOE4 was associated with increased risks of all disease subtypes except pure Lewy body disease. APOE4 was associated with increased frontal β-amyloid burden, typical Alzheimer’s disease was associated with increased β-amyloid burden in all lobar regions, and typical Lewy body disease interacted with APOE4 to increase the occipital β-amyloid burden. The interaction of APOE4 and typical Alzheimer’s disease was associated with more severe memory dysfunction, while that of APOE4 and typical Lewy body disease was associated with poorer Clinical Dementia Rating Sum of Boxes. Conclusions: Our ndings suggest that the APOE4 effect on disease risk is dependent on β-amyloid deposition and APOE4 is associated with β-amyloid deposition regardless of the clinical diagnosis; however, APOE4 further interacts with typical Lewy body disease to induce worse general cognition and higher occipital β-amyloid deposition and it interacts with typical Alzheimer’s disease This highlights the possible interaction of β-amyloid and Lewy body pathologies converging in the occipital cortex through the APOE4 effect. regression analyses evaluated independent effects of APOE4, typical AD, and typical LBD. Model 2 analyses tested the signicance of each pair of interaction terms, including APOE4 * typical AD, APOE4 * typical LBD, and typical AD * typical LBD. Model 3 analyses used APOE4, typical LBD, typical AD, and signicant interaction terms from Model 2 as predictors.

the symptomatic AD stage. Similarly, LBCI was de ned to include patients with LBVAD, AD/LBD, DLBA, and PLBD to differentiate it from typical LBD corresponding to LBD-dominant disease.

APOE genotyping
Genomic DNA was extracted from peripheral blood leukocytes using the DiaPlexQ TM ApoE Genotyping Kit following the manufacturer's instructions (SolGent co., Ltd.). Two single nucleotide polymorphisms (rs429358 for codon 112 and rs7412 for codon 158) in the APOE gene were genotyped using CFX 96 Real-time PCR system (Bio-Rad) following the manufacturer's instructions.

MRI acquisition
All MRI scans were acquired using the same 3T MRI scanner (Philips Achieva; Philips Medical System, Best, The Netherlands) with a SENSE head coil (SENSE factor = 2). A high-resolution, T1-weighted MRI volume dataset was obtained for all participants with a three-dimensional T1-turbo eld echo sequence con gured with the following acquisition parameters: axial acquisition with a 224 × 224 matrix; 256 × 256 reconstructed matrix with 182 slices; 220 mm eld of view; 0.98 × 0.98 × 1.2 mm 3 voxels; echo time of 4.6 ms; repetition time of 9.6 ms; ip angle of 8°; and slice gap of 0 mm. Moreover, axial uid-attenuated inversion recovery images were obtained to evaluate white matter hyperintensity (WMH) using the following parameters: matrix, 224 × 224; section thickness, 1 mm; echo time, 335 ms; repetition time, 8000 ms; and ip angle, 90°.

Regional WMH measurement and lacune counting
A visual rating scale of WMHs was modi ed from the Fazekas scale [30]. Periventricular WMH (PWMH) areas were classi ed as P1 (cap and band <5 mm), P2 (cap ≥5 mm or band <10 mm), and P3 (cap or band ≥10 mm); deep WMH (DWMH) areas were classi ed as D1 (maximum diameter of deep white matter lesion <10 mm), D2 (10 mm≤ lesion <25 mm), and D3 (lesion ≥25 mm). The number of lacunes was determined as previously described [31]. Manual ratings of WMHs and lacunes were performed by three MBq (8 mCi) of FBB, and 4.1 MBq per body weight (kg) of FDG were intravenously injected during the procedure. At 90 min after the injection, images were acquired during a 20 min session after a computed tomography (CT) scan for attenuation correction. The parameters for the spiral CT scan were as follows: 0.8 s per rotation at 120 kVp, 10 mA, 3.75 mm slice thickness, 0.625 mm collimation, and 9.375 mm table feed per rotation. The images were reconstructed using the ordered subset expectation maximization algorithm with four iterations and 32 subsets. A Gaussian lter with 4 mm full-width at half maximum (256 × 256 matrix with 0.98 mm pixels and 0.98 mm slice thickness) was applied to reconstructed PET images.

Assessment of 18 F-FBB-and 18 F-FP-CIT-PET images
Quantitation of 18 F-FBB-PET/CT images was based on surface-based PET analysis methods. First, we processed all T1-weighted MR images using the CIVET pipeline (http://mcin.ca/civet) to classify gray/white matter tissues and extract cortical surfaces.
Subsequently, we co-registered the FBB-PET scans to individual T1-weighted images using rigid-body transformation. We performed partial volume correction within gray and white matter regions using the idSURF method [32]. Next, the corrected FBB values were normalized to the crus-I/II gray matter reference region, which yielded an SUVR. Finally, we extracted the global FBB SUVR value as the cortical volume-weighted average of the following cortical regions of interest: frontal, anterior/posterior cingulate, lateral parietal, and lateral temporal cortices. FP-CIT-PET was interpreted using visual ratings as previously described [33]. FBB-PET was regarded as amyloid-positive if the global FBB SUVR was >1.478, as described in a previous autopsy-validation study [20].
Quality assurance for image processing All MR images and processing results were visually inspected by three researchers blinded to participant information (J.H.J., S.J., B.S.Y.) for quality assurance.

Neuropsychological evaluation
All participants were assessed using the standardized Seoul Neuropsychological Screening Battery, which assesses attention, language, visuospatial function, memory, and frontal/executive function [34,35]

Statistical analysis
An analysis of variance and the c 2 test were performed for cross-group comparisons of clinical features. Logistic regression analyses were performed to evaluate the effect of APOE4 (carrier vs. non-carrier) on disease risk after controlling for age, sex, education, hypertension, diabetes mellitus, hyperlipidemia, DWMH, PWMH, and the lacune number. Model 1 analyses evaluated the APOE4 effect on the risk of each disease (PAD, LBVAD, AD/LBD, DLBA, PLBD, ADCI, LBCI, typical AD, or typical LBD) in a combined NC and each disease group. Model 2 analyses evaluated the effect of APOE4 on the risk of ADCI and LBCI in all participants after adjusting for LBCI and ADCI, respectively. Model 3 analyses evaluated the effect of APOE4 on the risk of typical AD and typical LBD in all participants after adjusting for typical LBD and typical AD, respectively.
To determine the effect of APOE4 on β-amyloid deposition, we used general linear models to investigate the independent and interactive effects of APOE4, typical AD, and typical LBD on the global and mean FBB SUVR in the frontal, temporal, parietal, and occipital cortices with the same covariates as the logistic regression analyses. Model 1 analyses evaluated the independent effects of APOE4, typical AD, and typical LBD. Model 2 analyses tested the signi cance of each pair of interaction terms, including APOE4 * typical AD, APOE4 * typical LBD, and typical AD * typical LBD. Model 3 analyses used APOE4, typical LBD, typical AD, and signi cant interaction terms from Model 2 as predictors.
To determine the effect of APOE4 on cognitive dysfunction, the effects of APOE4, typical AD, and typical LBD on composite cognitive scores were evaluated using general linear models with similar covariates. Model 1 analyses evaluated the independent effects of APOE4, typical AD, and typical LBD. Given the signi cant interaction effects of AD and LBD on neuropsychological test scores, the interaction term of typical AD * typical LBD was further included in Model 1 analyses [22]. Model 2 analyses tested the signi cance of interaction terms, including APOE4 * typical AD and APOE4 * typical LBD. Model 3 analyses used APOE4, typical LBD, typical AD, typical AD * typical LBD, and signi cant interaction terms from Model 2 as predictors. Statistical analyses were performed using SPSS software (version 23.0; IBM Corp., Armonk, NY, USA) and signi cance was set at p<0.05.
MATLAB-based SurfStat toolbox was used for statistical analyses of vertex-wise FBB uptake [36]. To identify regional β-amyloid deposition patterns associated with APOE4, typical AD, and typical LBD, the independent and interactive effects of APOE4, typical AD, and typical LBD on the vertex-wise FBB SUVR were investigated using general linear models after adjustment for same covariates as for global and lobar FBB SUVRs. Given the signi cant interaction effects of APOE4 * typical LBD and typical AD * typical LBD on the mean lobar FBB SUVR, they were included in the models.

Results
Demographics and clinical characteristics Table 1 presents the demographic and clinical characteristics of the participants. The AD/DLB, LBVAD, and PLBD groups were older than the NC group; however, there was no signi cant among-group age difference. Male patients were more common in the LBVAD and DLBA groups than in the NC group. There were no signi cant among-group differences in education, hypertension, and hyperlipidemia; however, diabetes mellitus was more common in the PLBD group than in the NC, PAD, and AD/DLB groups. The lacune number and DWMH severity were comparable among groups. PWMH was more severe in the AD/DLB group than in the NC group and was similar across the remaining groups. The proportion of patients with dementia was higher in the AD/DLB group than in the PAD, LBVAD, and PLBD groups; moreover, it was higher in the DLBA group than in the PAD group. All disease groups had poorer K-MMSE and CDR-SOB scores than the NC group. The AD/DLB group had poorer K-MMSE scores than the PAD, LBVAD, and PLBD groups. The AD/DLB and DLBA groups had higher mean CDR-SOB scores than the PAD and LBVAD groups; moreover, the PLBD group had a higher mean CDR-SOB score than the PAD group. Compared to the NC and PLBD groups, the PAD, LBVAD, AD/DLB, and DLBA groups had higher global, frontal, parietal, temporal, and occipital FBB SUVRs. The APOE4 carrier proportion was highest in the PAD group (73.7%), followed by the AD/DLB (59.5%), LBVAD (53.1%), DLBA (47.6%), PLBD (19.6%), and NC (17.5%) groups. The PAD, AD/DLB, LBVAD, and DLBA groups had higher proportions of APOE4 carriers than the PLBD and NC groups; however, the proportion of APOE4 carriers was comparable between the PLBD and NC groups.
Effect of APOE genotype on disease risk Table 2 shows the associations between the APOE genotype and the risk of each disease compared to the NC group (Model 1). APOE4 was associated with increased risks of PAD, LBVAD, AD/DLB, and DLBA but not PLBD. The odds ratio (OR) associated with APOE4 was highest in the PAD group (OR, 95% con dence interval [CI]: 14.71, 6.54-33. and typical LBD (OR, 95% CI: 3.58, 1.80-7.10). The effect of APOE2 on the risk of PAD was not evaluated since there were no APOE2 carriers in the PAD group. Further, APOE2 was not associated with LBVAD, AD/DLB, DLBA, and PLBD risk. However, APOE2 was associated with a decreased risk of ADCI (OR, 95% CI: 0.29, 0.11-0.73) and typical AD (OR, 95% CI: 0.24, 0.09-0.70). Sensitivity analysis involving the evaluation of the association between APOE4 and LBCI after excluding patients with typical AD indicated that APOE4 was associated with an increased LBCI risk (OR, 95% CI: 2.30, 1.04-5.08). However, sensitivity analysis excluding patients with ADCI revealed that APOE4 was not associated with LBCI risk (OR, 95% CI: 1.37, 0.54-3.47).
Evaluation of the effect of APOE4 on the risk of ADCI and typical AD (Model 2 and Model 3) showed that APOE4 was associated with a higher risk of ADCI and typical AD after controlling for LBCI and typical LBD, respectively. Meanwhile, APOE4 was not associated with a risk of LBCI or typical LBD after controlling for ADCI and typical AD, respectively. APOE2 was associated with a lower risk of ADCI and typical AD after controlling for LBCI and typical LBD, respectively. However, APOE2 was not associated with LBCI or typical LBD risk after controlling for ADCI and typical AD, respectively.
Effects of APOE4, AD, and LBD on the global and regional FBB SUVR Table 3 presents the effects of APOE4, typical AD, and typical LBD on the global and regional FBB SUVR. Model 1 analyses showed that typical AD was associated with the global SUVR and mean lobar SUVR in all four lobar regions, APOE4 was associated with the mean frontal SUVR, and typical LBD was associated with the mean occipital SUVR. Model 2 analyses revealed that the interaction of typical AD and typical LBD was associated with a lower mean parietal SUVR. Further, the interaction of APOE4 and typical LBD was associated with a higher mean occipital SUVR. Model 3 analyses indicated that typical LBD and typical AD were associated with a higher mean parietal SUVR, and only typical AD was associated with the mean occipital SUVR.
There was a signi cant interaction effect between typical LBD and APOE4 on occipital β-amyloid ( Figure 1). Typical AD had a signi cant effect on whole-brain cortices, while typical LBD and APOE4 lacked independent effects on the vertex-wise FBB SUVR.
Effects of APOE4, typical AD, and typical LBD on cognition Model 1 analyses showed that typical AD and typical LBD were independently associated with poorer cognitive scores in all neuropsychological domains as well as poorer K-MMSE and CDR-SOB scores. Further, APOE4 was independently associated with poorer CDR-SOB scores (Table 4). Typical AD and typical LBD had signi cant interaction effects on all neuropsychological domains with the exception of the attention domain. However, the interaction direction implied that the degree of cognitive dysfunction was comparable across the typical AD, typical LBD, and typical AD/typical LBD groups. Model 2 analyses indicated that the interaction of APOE4 and typical AD was associated with poorer memory scores, while the interaction of APOE4 and typical LBD was associated with poorer CDR-SOB scores. Effects of typical AD, typical LBD as well as the interaction effect of typical AD and typical LBD in Model 3 were similar to those in Model 1.

Discussion
We evaluated the relationship between APOE4, AD, LBD, β-amyloid deposition, and cognition in patients with cognitive impairment and NC participants who underwent clinical assessment and FDG-PET, amyloid PET, and dopamine transporter PET. APOE4 was associated with increased risk of PAD, AD/DLB, LBVAD, and DLBA, but not PLBD. Further, typical LBD was associated with increased occipital β-amyloid burden via the interaction with APOE4. Moreover, the interactions of APOE4 with typical LBD and AD were associated with poorer CDR-SOB scores and severe memory dysfunction, respectively. This suggests that the APOE4 effect on disease risk is dependent on β-amyloid deposition; however, APOE4 interacted with typical LBD to worsen general cognition and increase occipital β-amyloid deposition.
It remains unclear whether APOE4 is associated with an increased risk of PLBD [4] [12], which could be attributed to the de nition of AD pathology. Previous autopsy studies identi ed AD pathology based on a Braak neuro brillary tangle stage of >III and a Consortium to Establish a Registry for Alzheimer's Disease plaque score of C, with both requiring signi cant tau accumulation. Since β-amyloid ligands bind to diffuse and neuritic plaques [20,37,38], our PLBD de nition implied the absence of neuritic and diffuse plaques regardless of the tau burden. Speci cally, antemortem amyloid PET scans of autopsy-con rmed PLBD were found to be amyloid-positive with a diffuse plaque being the primary contributor [37,38]. This perspective is consistent with our sensitivity analyses excluding patients with typical AD or ADCI. APOE4 was signi cantly associated with LBCI risk after excluding patients with typical AD, but not after excluding patients with ADCI. Therefore, the APOE4 effect on disease risk across AD and LBD depends on βamyloid deposition.
We found an association of LBD with increased occipital β-amyloid deposition after adjusting for typical AD. This is consistent with previous reports of relatively higher occipital amyloid deposition in patients with LBD than in patients with AD [17]. Previous studies have reported a synergistic relationship between cortical α-synuclein and β-amyloid accumulation [8,39,40] and a positive correlation between striatal dopamine depletion and occipital β-amyloid deposition in patients with LBD [41]. Therefore, the association of LBD with occipital β-amyloid deposition could re ect a possible interaction between β-amyloid and α-synucleinrelated brain changes. Patients with AD with LBD and LBD without AD have previously exhibited relatively sparse occipital β-amyloid deposition compared to patients with AD without LBD on Pittsburgh Compound B PET [38]. Given the same brain reserve, the extent of LBD pathology is negatively associated with the AD pathology required for a similar degree of cognitive dysfunction [42]. Patients with AD with LBD reportedly present with lower β-amyloid deposition than patients with AD without LBD; however, this difference was smallest in the occipital cortex [38]. Therefore, careful interpretation should be applied regarding our nding of an association between the presence of typical LBD and higher occipital β-amyloid deposition than control participants after controlling for AD.
The effect of LBD on occipital β-amyloid deposition could be attributed to the signi cant interaction between LBD and APOE4. Since APOE4 is also involved in the spread of α-synuclein or LB pathology [6,18,43,44], as well as the co-existence of α-synuclein and βamyloid pathologies [11,45], APOE4 could play a pivotal role in the interaction between α-synuclein and β-amyloid [19]. In our study, the interaction of APOE4 with LBD was associated with poorer CDR-SOB scores. Notably, no speci c cognitive domains were affected by the interaction. Since general cognition in patients with LBD is affected by several factors, including visual hallucinations, cognitive uctuation, parkinsonism severity, and various psychiatric symptoms, there is a need for further studies on the association between APOE4 and other LBD features.
The interaction of APOE4 and typical AD was associated with greater memory dysfunction. Although we could not perform tau imaging, all of the patients with typical AD presented with typical clinical AD features and signi cant β-amyloid deposition. Further, FDG-PET con rmed AD-relevant neurodegeneration. Given the close correlation between tau accumulation and clinical and neurodegenerative changes in AD [46], typical AD in our study could be considered to involve AD-speci c tau accumulation. Therefore, our ndings could constitute clinical evidence of the interaction between APOE4 and tau pathology. This is consistent with previous reports of a direct interaction of APOE4 with tau [47] and tau phosphorylation [48], as well as of a signi cant association between APOE4 and medial temporal lobe tau independent of β-amyloid burden [3].
The interaction effects of typical AD and typical LBD on cognitive dysfunction were signi cant, but they were not additive nor synergistic. The degree of cognitive de cit in the AD/DLB group was mostly comparable to that in the PAD and the PLBD groups.
This result could also be explained by the concept of brain reserve [42] and dichotomization of our participants into those with and without typical AD and those with and without typical LBD. Although we cannot measure the burden of α-synuclein or LB pathology because of the lack of feasible in vivo biomarkers, the pathologic LB burden could be reduced in the mixed AD/DLB group compared to that in the PLBD group. Conversely, it is noteworthy that the interaction effect between typical AD and typical LBD was not signi cant in the attention domain. The attention domain could be a particularly vulnerable domain that typical AD and typical LBD additively deteriorate. This study has several limitations. First, we did not perform tau PET nor measure the LB pathology burden, which impeded the establishment of the dose-dependent relationship of AD and LB pathologies with cognitive dysfunction and β-amyloid burden.
Second, we could not adjust for the effect of the β-amyloid burden on cognitive dysfunction since only 11 NC participants underwent FBB-PET. Third, LBVAD could have been under-diagnosed since we did not perform dopamine transporter PET for patients with PAD without signi cant parkinsonism (UPDRS motor scale of >16). Moreover, dopamine transporter PET has suboptimal sensitivity for LBD detection [49], particularly if LB pathology does not involve the nigrostriatal dopaminergic system [50]. Inconsistent with our nding that the highest APOE4 prevalence was in the PAD group, a previous autopsy study reported that the APOE4 prevalence was highest in the AD with LB group, followed by the AD without LB group [11]. This inconsistency could be attributed to our possible LBVAD underestimation.

Conclusion
Our ndings suggest that the APOE4 effect on disease risk is dependent on its effects on β-amyloid deposition; however, APOE4 further interacts with typical LBD to induce worse general cognition and higher occipital β-amyloid deposition. This study highlights the possible interaction of β-amyloid and LBD pathologies converging in the occipital cortex. Future studies should elucidate the underlying mechanism and clinical signi cance of occipital β-amyloid deposition.

Declarations
Ethics approval and consent to participate: This study was approved by the Institutional Review Board of the Yonsei University Medical Center. Since this was a retrospective study, the requirement for patient consent was waived.

Consent for publication: None
Availability of data and materials: For purposes of replicating procedures and results, any quali ed investigator can request anonymized data after ethics clearance and approval by all authors.
Potential Con icts of Interest: None.   Data are the results of general linear models for the global or mean lobar FBB SUVR after controlling for age, sex, education, hypertension, diabetes mellitus type 2, dyslipidemia, DWMH, PWMH, and the lacune number. Model 1 used APOE4, typical LBD, and typical AD as predictors. Model 2 tested the signi cance of the interaction terms (APOE4 * Typical AD, APOE4 * Typical LBD, or Typical AD * Typical LBD) by adding one of the three interaction terms as a predictor to Model 1. Model 3 used APOE4, typical LBD, typical AD, and the signi cant interaction terms in Model 2 as predictors. Data are the results of general linear models for neuropsychological test scores after controlling for age, sex, education, hypertension, diabetes mellitus type 2, hyperlipidemia, DWMH, PWMH, and the lacune number. Model 1 used APOE4, typical LBD, typical AD, and typical AD * typical LBD as predictors. Model 2 tested the signi cance of APOE4 * typical AD and APOE4 * typical LBD by adding one of the two interaction terms as a predictor to Model 1. Model 3 used APOE4, typical LBD, typical AD, and the signi cant interaction terms from Model 2 as predictors.