Osteoarthritis and APOE4 Interact to Influence Memory Decline in Non-Demented Older People

Abstract

Background:

The question that whether the presence of osteoarthritis (OA) can modify the effects of apolipoprotein E4 (APOE4) genotype on longitudinal change in cognitive performance among non-demented older people remains unclear.

Objective:

To examine whether the association of APOE4 genotype with change in verbal episodic memory over time is modified by the presence of OA among non-demented older people.

Methods:

Longitudinal data from 1,400 non-demented older people were obtained from the Alzheimer’s Disease Neuroimaging Initiative database. The sample included 466 healthy individuals and 934 mild cognitive impairment. The effects of the OA×APOE4 genotype interaction term on longitudinal change in cognitive performance were examined using linear mixed-effects regression models. Global cognition was assessed by the Mini-Mental State Examination score and Clinical Dementia Rating–Sum of Boxes. Verbal episodic memory was evaluated by the Rey Auditory Verbal Learning Test (RAVLT) immediate recall and delayed recall score.

Results:

We found that OA interacted with APOE4 genotype to influence longitudinal change in verbal episodic memory (as assessed by RAVLT immediate recall score) but not global cognition. Specifically, the OA–/APOE4+ group had a steeper decline in RAVLT immediate recall score compared with the OA+/APOE4+ group. However, there was no difference in RAVLT immediate recall score between OA–/APOE4–and OA+/APOE4–individuals.

Conclusion:

Our study suggested that the association of APOE4 genotype with change in RAVLT immediate recall score over time is modified by the presence of OA at earliest stages of the disease.

Keywords

Alzheimer’ disease cognitive decline mild cognitive impairment osteoarthritis

INTRODUCTION

Osteoarthritis (OA) is a common, multi-factorial and devastating joint disorder, which leads to poor functional outcomes and disability [1]. A previous case-control study suggested a link between the presence of OA and an increased risk of dementia [2]. In addition, a meta-analysis examining the association of OA with the risk of dementia strengthened this link [3]. OA, as one of chronic peripheral inflammatory conditions, may contribute to neuroinflammation and exacerbation of Alzheimer’s disease (AD) pathology [4]. More recently, the presence of OA was found to be associated with longitudinal change in volumes of the gray matter of the whole brain among non-demented older people [5].

Polymorphism in the apolipoprotein E (APOE) gene is one of the strongest genetic risk factors of late-onset AD dementia, with the APOE4 allele conferring an increased risk and decreasing age at onset of the disease [6]. Emerging evidence indicates that the APOE4 genotype increases the accumulation of amyloid pathology and facilitates the process of neurodegeneration, thereby impairing cognitive performance and increasing the risk of developing AD dementia [7]. More importantly, systemic inflammation that contributes to the development of OA [8] has been found to be associated with cognitive decline in APOE4 positive individuals [9]. Although both OA and APOE4 genotype were reported to be associated with an increased risk of AD, it is also possible that APOE4 interacts with OA to affect cognitivedecline.

In the present study, we examined whether the presence of OA can modify the effects of APOE4 genotype on longitudinal change in cognitive performance among non-demented older people and we hypothesized that OA may interact with APOE4 genotype to influence cognitive decline such that OA+/APOE4+ individuals show a steeper decline in cognitive performance compared with other three groups (OA–/APOE4–, OA+/APOE4–, and OA–/APOE4+).

METHODS

Data source

Longitudinal data were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database https://adni.loni.usc.edu. The major goals of the ADNI study have been to investigate whether a variety of markers, including demographics, cognitive assessments, neuroimaging measures and other biological markers, can be integrated to assess the progression of Mild cognitive impairment (MCI) and early AD and to facilitate the recruitment of participants for clinical trials. Since 2003, ADNI has recruited over 2000 older adults over four phases (ADNI-1, ADNI-GO, ADNI-2, ADNI-3) across the US and Canada. Study visits involve clinical, neuropsychological, and neuroimaging assessments. Recruitment procedures have been reported [10]. Further detailed information and updates can be found at the website: https://adni.loni.usc.edu/.

Participants

In our study, we included 1,400 non-demented older people at baseline, including 466 cognitively normal older people and 934 individuals with MCI. Diagnostic criteria for a cognitively normal individual included a Mini-Mental State Examination (MMSE) [11] score between 24 and 30 (a higher score indicates better cognitive performance) and a Clinical Dementia Rating (CDR) [12] score of 0. The criteria for an individual with MCI included an MMSE score between 24 and 30, a CDR score of 0.5, the presence of a subjective memory complaint, the presence of an objective memory impairment as measured by Logical Memory II subscale (Delayed Paragraph Recall, Paragraph A only) from the Wechsler Memory Scale–Revised, essentially preserved activities of daily living, and the absence of a dementia diagnosis. In ADNI, participants with MCI are categorized as amnestic MCI.

In ADNI study, participants were assessed at baseline, then returned for follow-up assessments at 6 months, 1 year, and every year thereafter. In the present study, we selected participants with at least two assessments. Participants with only one visit at baseline were excluded from the current analyses.

All participants provided written informed consent, and local institutional review boards of all ADNI institutions approved the ADNI study.

Cognitive assessments

Participants underwent a battery of neuropsychological assessments at each ADNI visit. In the current study, we selected four cognitive tests, including MMSE, CDR sum of boxes (CDR-SB) and Rey Auditory Verbal Learning Test (RALVT) [13] immediate recall score and delayed recall score. Specifically, MMSE and CDR-SB were used to assess global cognition and RAVLT immediate recall score and delayed recall score were used to assess verbal episodic memory. RAVLT immediate recall score and delayed recall score were used as our primary cognitive outcomes because these measures are associated with other AD-related markers, such as hippocampal volume [14], temporal lobe glucose metabolic rates [15], and cortical amyloid-β (Aβ) deposition [16].

Determination of OA status

Medical history was recorded based on self-report by participants or their relatives at ADNI visits. We extracted the information of OA status from the dataset “RECMHIST.csv”, which were downloaded from the ADNI database. We searched the database with the search term “osteoarthritis” to identify participants with OA. In the present study, out of 1,400 participants, 212 subjects had a diagnosis of OA.

APOE allele genotyping

APOE genotypes of the study participants were extracted from the dataset “ADNIMERGE.csv”. In the present study, the presence of at least one APOE4 allele was considered as APOE4 positive. There were 800 participants who were APOE4 negative and 600 participants who were APOE4 positive.

Statistical analysis

Our study participants were classified into four groups: OA–/APOE4–(n = 687), OA+/APOE4–(n = 113), OA–/APOE4+ (n = 501), and OA+/APOE4+ (n = 99). Group differences were evaluated with Chi-squared tests for categorical variables (gender, clinical diagnosis, hypertension, and diabetes) and Kruskal-Wallis rank sum tests for continuous variables (age, educational levels, body mass index (BMI), MMSE, CDR-SB, and RAVLT immediate recall score and delayed recall score). For multiple comparisons, statistically significant variables were followed by post hoc pairwise comparisons (Chi-squared tests for categorical variables and Wilcoxon rank sum tests for continuous variables) with the Bonferroni adjustment [17]. To investigate the effects of OA status and APOE4 genotype on longitudinal change in MMSE, CDR-SB, and RAVLT immediate recall and delayed recall scores, we performed four linear mixed-effects regression models for each cognitive measure. In each model, we included main effects of OA and APOE4 genotype, their interactions with time, interaction between OA and APOE4 genotype, as well as their joint interaction with time. In addition, each model was adjusted for main effects of age, educational level, gender, clinical diagnosis, BMI, hypertension, diabetes, and their interactions with time, as well as a random intercept for each subject. The following linear mixed models were run: $\begin{matrix} Cognitive measure s_{change} \sim O A^{*} APOE 4^{*} time \\ + Ag e^{*} time + Gende r^{*} time + Educatio n^{*} time \\ + Hypertensio n^{*} time + Diabete s^{*} time + BM I^{*} time \end{matrix}$ Where cognitive measures _change is the change in our four cognitive tests (MMSE, CDR-SB, RAVLT immediate recall and delayed recall scores) from baseline.

To examine interactions between OA and APOE4 genotype, memory decline across all pairwise group contrasts was assessed (OA–/APOE4–, OA+/APOE4–, OA–/APOE4+, and OA+/APOE4+). The False Discovery Rate (FDR) [18] was used to obtain adjusted p values when conducting multiple comparisons between these four groups. All p values were 2-sided, and all statistical work was performed using R version 4.1.1 [19].

RESULTS

Baseline characteristics of the study sample

Our study participants were categorized into four groups based on joint OA and APOE4 genotype (Table 1). OA–/APOE4+ individuals were younger than OA–/APOE4–and OA+/APOE4–individuals (all p < 0.01). Expectedly, OA–/APOE4+ individuals had lower MMSE score and higher CDR-SB score than OA–/APOE4–and OA+/APOE4–individuals (all p < 0.01). OA+/APOE4+ individuals also had lower MMSE score than OA–/APOE4–individuals (p < 0.01). OA–/APOE4+ individuals had lower RAVLT immediate recall score than OA–/APOE4–and OA+/APOE4–individuals (all p < 0.01). OA+/APOE4+ individuals also had lower RAVLT immediate recall score than OA–/APOE4–individuals (p = 0.02). OA–/APOE4+ individuals had lower RAVLT delayed recall score than OA–/APOE4–and OA+/APOE4–individuals (all p < 0.01). OA+/APOE4+ individuals also had lower RAVLT delayed recall score than OA–/APOE4–and OA+/APOE4–individuals (p < 0.05). OA–/APOE4+ individuals had lower BMI than OA–/APOE4–individuals (p < 0.001). OA–/APOE4+ individuals had higher percentage of MCI diagnosis than OA–/APOE- and OA+/APOE4–individuals (p < 0.001). OA+/APOE4+ individuals had higher percentage of history of hypertension than OA–/APOE4+ individuals (p = 0.01). There were no group differences in educational levels, sex or diabetes.

Table 1

Non-demented individuals by OA and APOE4 status

Variables	OA–/APOE4–	OA+/APOE4–	OA–/APOE4+	OA+/APOE4+
n (%)	687 (49.1)	113 (8.1)	501 (36.0)	99 (7.1)
Age, y	73.8 (9.5)	75.6 (10.1)	72.4 (9.5)	73.5 (10.8)
Follow-up duration, y	4 (4)	4 (3)	3 (3)	4 (3)
Education, y	16 (4)	16 (4)	16 (4)	16 (4)
Female gender, n (%)	296 (43.1)	57 (50.4)	218 (43.5)	48 (48.5)
MCI diagnosis, n (%)	402 (58.5)	62 (54.9)	402 (80.2)	68 (68.7)
Hypertension, n (%)	266 (38.7)	53 (46.9)	204 (40.7)	55 (55.6)
Diabetes, n (%)	57 (8.3)	12 (10.6)	30 (6)	10 (10.1)
BMI	26.8 (5.39)	26.7 (6.14)	25.9 (4.92)	26.2 (6.1)
MMSE	29 (2)	29 (3)	28 (3)	28 (2.5)
CDR-SB	0.5 (1.5)	0.5 (1.5)	1 (1.5)	1 (1.75)
RAVLT immediate recall score	39 (17)	42 (19)	34 (15)	35 (15)
RAVLT delayed recall score	5 (4)	5 (3)	4 (4)	4 (4)

OA, osteoarthritis; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; CDR-SB, Clinical Dementia Rating–Sum of Boxes; BMI, body mass index; RAVLT, Rey auditory verbal learning test. Values indicate medians and interquartile range for continuous variables.

Summary of longitudinal change models

To examine whether OA can interact with APOE4 genotype to influence longitudinal change in cognitive measures, several linear mixed-effects regression models were performed.

As shown in Table 2 and Figs. 1and 2, the 3-way interaction term between OA, APOE4 genotype, and time was not significant for MMSE (Coefficient = –0.0128, SE = 0.0587, p = 0.8278) or CDR-SB (Coefficient = 0.0093, SE = 0.0373, p = 0.8026), indicating that OA did not interact with APOE4 genotype to affect longitudinal change in MMSE or CDR-SB among non-demented older people.

Table 2

Summary of linear mixed-effect models with MMSE and CDR-SB as dependent variables

	MMSE			CDR-SB
Model predictors	Coefficients	SE	p	Coefficients	SE	p
OA×Time	0.0694	0.0391	0.0757	–0.1133	0.0249	<0.0001
APOE4+×Time	–0.3955	0.0242	<0.0001	0.3139	0.0154	<0.0001
Age×Time	–0.0105	0.0017	<0.0001	0.0112	0.0011	<0.0001
Female gender×Time	–0.0948	0.0217	<0.0001	0.0709	0.0138	<0.0001
Education×Time	0.0049	0.0038	0.2000	–0.0039	0.0024	0.1029
MCI diagnosis×Time	–0.3195	0.0217	<0.0001	0.2223	0.0138	<0.0001
Hypertension×Time	0.0188	0.0213	0.3770	–0.0086	0.0135	0.5260
Diabetes×Time	–0.0868	0.0405	0.0319	0.1412	0.0256	<0.0001
BMI×Time	0.0135	0.0022	<0.0001	–0.0107	0.0014	<0.0001
OA×APOE4×Time	–0.0128	0.0587	0.8278	0.0093	0.0373	0.8026

OA, osteoarthritis; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; CDR-SB, Clinical Dementia Rating–Sum of Boxes; BMI, body mass index. Main effects of age, education, gender and diagnosis were included in the linear mixed-effects models, but not shown in Table 2 because longitudinal effects were the main research interests of the present study. Coefficients represent the amount of change in each cognitive measure (MMSE or CDR-SB) annually.

Fig. 1

Decline in MMSE score by joint OA and APOE4 status. OA did not interact with APOE4 genotype to affect longitudinal change in MMSE among non-demented older people. OA, osteoarthritis; MMSE, Mini-Mental State Examination. The regression lines were obtained from the adjusted model.

Fig. 2

Decline in CDR-SB score by joint OA and APOE4 status. OA did not interact with APOE4 genotype to affect longitudinal change in CDR-SB among non-demented older people. OA, osteoarthritis; CDR-SB, Clinical Dementia Rating–Sum of Boxes. The regression lines were obtained from the adjusted model.

In contrast, as shown in Table 3 and Fig. 3, we found that the 3-way interaction term between OA, APOE4 genotype, and time was significant (Coefficient = 0.3468, SE = 0.1735, p = 0.0457) for RAVLT immediate recall score, suggesting that OA interacted with APOE4 genotype to influence longitudinal change in RAVLT immediate recall score among non-demented older people. To better understand this interaction, we further contrasted groups based on OA and APOE4 status (OA–/APOE4–, OA+/APOE4–, OA–/APOE4+, and OA+/APOE4+). The FDR method was used to obtain adjusted p values when conducting multiple comparisons between these four groups. As shown in Table 4 and Fig. 3, post hoc contrasts suggested that the OA–/APOE4+ group had steeper decline in RAVLT immediate recall score compared with the OA+/APOE4+ group (coefficient = –0.3474, SE = 0.1316, p = 0.01). However, there was no difference in RAVLT immediate recall score between OA–/APOE- and OA+/APOE4–individuals (coefficient = –0.0006, SE = 0.1143, p = 0.9957).

Table 3

Summary of linear mixed-effect models with RAVLT immediate recall and delayed scores as dependent variables

	RAVLT immediate recall score			RAVLT delayed recall score
Model predictors	Coefficients	SE	p	Coefficients	SE	p
OA×Time	0.0006	0.1142	0.9957	–0.0235	0.0355	0.5087
APOE4+×Time	–0.7730	0.0717	<0.0001	–0.0712	0.0220	0.0012
Age×Time	–0.0392	0.0051	<0.0001	–0.0067	0.0015	<0.0001
Female gender×Time	–0.2255	0.0640	0.0004	–0.0660	0.0196	0.0007
Education×Time	0.0473	0.0112	<0.0001	0.0000	0.0034	0.9992
MCI diagnosis×Time	–0.2933	0.0638	<0.0001	0.0129	0.0196	0.5085
Hypertension×Time	0.2344	0.0626	0.0002	0.0608	0.0191	0.0015
Diabetes×Time	–0.1752	0.1189	0.1408	0.0160	0.0362	0.6586
BMI×Time	0.0373	0.0065	<0.0001	0.0013	0.0020	0.5191
OA×APOE4×Time	0.3468	0.1735	0.0457	0.1039	0.0536	0.0525

OA, osteoarthritis; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; RAVLT, Rey auditory verbal learning test; BMI, body mass index. Main effects of age, education, gender and diagnosis were included in the linear mixed-effects models, but not shown in Table 3 because longitudinal effects were the main research interests of the present study. Coefficients represent the amount of change in each cognitive measure (RAVLT immediate recall score or delayed recall score) annually.

Fig. 3

Decline in RAVLT immediate recall score by joint OA and APOE4 status. The OA–/APOE4+ group had steeper decline in RAVLT immediate recall score compared with the OA+/APOE4+ group. However, there was no difference in memory decline between OA–/APOE- and OA+/APOE4–individuals. OA, osteoarthritis; RAVLT, Rey auditory verbal learning test. Notes: The regression lines were obtained from the adjusted model.

Table 4

Comparisons of change in RAVLT immediate recall score across OA/APOE groups

	RAVLT immediate recall score
Contrast	Coefficients	SE	p
OA–/APOE4–×Time versus OA+/APOE4–×Time	–0.0006	0.1143	0.9957
OA–/APOE4–×Time versus OA–/APOE4+×Time	0.7730	0.0718	<0.0001
OA–/APOE4–×Time versus OA+/APOE4+×Time	0.4256	0.1249	0.0013
OA+/APOE4–×Time versus OA–/APOE4+×Time	0.7736	0.1222	<0.0001
OA+/APOE4–×Time versus OA+/APOE4+×Time	0.4262	0.1586	0.0100
OA–/APOE4+×Time versus OA+/APOE4+×Time	–0.3474	0.1316	0.0100

OA, osteoarthritis; RAVLT, Rey auditory verbal learning test. Multiple comparisons were adjusted using the FDR method. Coefficients represent the amount of change in RAVLT immediate recall score annually.

Additionally, as shown in Table 3 and Fig. 4, we found that the 3-way interaction term between OA, APOE4 genotype and time was marginally significant (Coefficient = 0.1039, SE = 0.0536, p = 0.0525) for RAVLT delayed recall score. To explore this interaction, we further contrasted groups based on OA and APOE4 status (OA–/APOE4–, OA+/APOE4–, OA–/APOE4+, and OA+/APOE4+). The FDR method was used to obtain adjusted p values when conducting multiple comparisons between these four groups. As shown in Table 5 and Fig. 4, post hoc contrasts suggested that the OA–/APOE4+ group had a tendency to decline faster in RAVLT delayed recall score compared with the OA+/APOE4+ group, while this was not statistically significant (coefficient = –0.0804, SE = 0.0404, p = 0.1398). There was no difference in RAVLT delayed recall score between OA–/APOE- and OA+/APOE4–individuals (coefficient = 0.0235, SE = 0.0356, p = 0.6111).

Table 5

Comparisons of change in RAVLT delayed recall score across OA/APOE groups

	RAVLT delayed recall score
Contrast	Coefficients	SE	p
OA–/APOE4–×Time versus OA+/APOE4–×Time	0.0235	0.0356	0.6111
OA–/APOE4–×Time versus OA–/APOE4+×Time	0.0712	0.0221	0.0075
OA–/APOE4–×Time versus OA+/APOE4+×Time	–0.0092	0.0383	0.8111
OA+/APOE4–×Time versus OA–/APOE4+×Time	0.0478	0.0380	0.4181
OA+/APOE4–×Time versus OA+/APOE4+×Time	–0.0326	0.0490	0.6111
OA–/APOE4+×Time versus OA+/APOE4+×Time	–0.0804	0.0404	0.1398

OA, osteoarthritis; RAVLT, Rey auditory verbal learning test. Multiple comparisons were adjusted using the FDR method. Coefficients represent the amount of change in RAVLT delayed recall score annually.

Fig. 4

Decline in RAVLT delayed recall score by joint OA and APOE4 status. The OA–/APOE4+ group had a tendency to decline faster in RAVLT delayed recall score compared with the OA+/APOE4+ group, while this was not statistically significant. There was no difference in RAVLT delayed recall score between OA–/APOE- and OA+/APOE4–individuals (coefficient = 0.0235, SE = 0.0356, p = 0.6111). OA, osteoarthritis; RAVLT, Rey auditory verbal learning test. The regression lines were obtained from the adjusted model.

DISCUSSION

This is the first study to examine the effects of the OA×APOE4 interaction on longitudinal change in cognitive performance among non-demented older people. We found that OA interacted with APOE4 genotype to influence longitudinal change in memory decline (as assessed by RAVLT immediate recall score) but not global cognition (as assessed by MMSE or CDR-SB). Specifically, the OA–/APOE4+ group had steeper decline in RAVLT immediate recall score compared with the OA+/APOE4+ group. However, there was no difference in RAVLT immediate recall score between OA–/APOE4–and OA+/APOE4–individuals. As expected, APOE4+ groups (OA–/APOE4+ and OA+/APOE4+) declined faster in memory performance than APOE4–groups (OA–/APOE4–and OA+/APOE4–).

The novel finding of our study was that OA status interacted with APOE4 genotype to affect memory decline among non-demented older people such that the OA–/APOE4+ group showed steeper memory decline compared with the OA+/APOE4+ group. However, this finding was not consistent with our hypothesis. Given the well-stablished relationship between APOE4 genotype and a risk of AD dementia [6, 7] as well as the potential association of OA with cognitive decline from previous studies [2, 3], we hypothesized that OA status may exacerbate the effects of APOE4 genotype on memory decline over time. There are several potential explanations for this inconsistency. For instance, it is possible that the presence of OA, as one of chronic peripheral inflammatory conditions, can mitigate the APOE4–associated memory decline at early stages of the disease. It is known that peripheral inflammation can have an impact on inflammatory response in the central nervous system through several routes and that neuroinflammation plays an important role in the pathogenesis of AD [20]. However, the question that whether it is protective or detrimental remains unclear. It has been proposed that microglial activation, a key player in neuroinflammation in AD, takes place in the earliest phases of the disease to clear amyloid (the M2 phenotype) and protect neurons, then switches to the M1 phenotype and leads to neuron damage [20]. Therefore, it is possible that the presence of OA, as a chronic peripheral inflammatory condition, may alleviate the detrimental effects of APOE4 genotype on memory decline at the early stages of the disease.

Additionally, tissue degradation and inflammation are two hallmarks of OA. In the early phase of OA, the immune system is activated to remove senescent cells and repair joint tissues. During disease progression, the senescent chondrocyte senescence-associated secretory phenotype can contribute to an imbalance between cartilage synthesis and removal, leading to structural dysfunction [21]. Similarly, the immune system that rejects the senescent cells in cartilage and other joint tissues can also attack the senescent cells in brain and delay cognitive decline [22], particularly at the early stages of AD.

Finally, increased longitudinal exposure to anti-inflammatory medications among individuals with OA may also explain our results. For example, several epidemiological studies reported that anti-inflammatory medications showed some protective effects against developing AD dementia [23, 24]. However, human clinical trials did not support this notion [25].

Our study should be interpreted with considering several potential limitations. First, the study sample in the OA+ groups was smaller than that of OA–groups. Further studies should increase the study sample to increase statistical power. Second, the information of OA status was obtained by self-report of our study participants. This approach may increase the possibility of recall bias. Further studies should utilize structured diagnostic framework to obtain the status of OA and other related parameters, such as onset and severity of OA, should also be included in the study. Third, the ADNI cohort represents a convenience sample, which may increase the possibility of selection bias. Fourth, individuals with OA engage in less physical activity, which may influence cognitive function. Further studies should include this variable to adjust this effect. Fifth, in the current study, we did not utilize other independent datasets to validate the current findings. Further study is needed to test the robustness of our findings. Finally, the fact that the sample size of the OA+/APOE4–group among the AD group was relatively small and AD participants had much higher dropout rate during the follow-up prohibited us from including the AD group into our analyses. Further studies with larger sample size of the AD group would be helpful to provide insights into the relationship between OA, APOE4 genotype, and memory decline at the later stages of the disease.

In conclusion, our study suggested that the association of APOE4 genotype with change in RAVLT immediate recall score over time is modified by the presence of OA at earliest stages of the disease.

Footnotes

ACKNOWLEDGMENTS

Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health . The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

This study was funded by the Project of Wenzhou Science and Technology Bureau (No. Y20190275).

Authors’ disclosures available online ().

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