Risk Factors Predicting Amyloid PET Positivity in Patients with Mild Cognitive Impairment and Apolipoprotein E ɛ 3/ ɛ 3 Genotypes

Abstract

Background:

The apolipoprotein E (APOE) ɛ4 allele is a well-known risk factor for AD and is associated with higher amyloid deposition and earlier dementia onset. However, the relationship between amyloid pathology and the most common APOE allele, ɛ3, has not been well studied.

Objective:

In this study, we aimed to identify the risk factors predicting amyloid PET positivity in patients with mild cognitive impairment (MCI) and APOE ɛ3/ɛ3 genotypes.

Methods:

We retrospectively reviewed the medical records of MCI patients with APOE ɛ3/ɛ3 genotypes who underwent amyloid PET scanning. Demographics, neuropsychological tests, and brain MRI were obtained. We analyzed which risk factors could affect amyloid PET positivity in MCI patients with APOE ɛ3/ɛ3 genotypes using logistic regression models.

Results:

We recruited 171 MCI patients with APOE ɛ3/ɛ3 genotypes in this study. Out of 171 patients, 49 patients (28.65%) showed positive results in the amyloid PET scans. In a multivariate logistic regression model, amyloid positivity was associated with frontal atrophy (OR = 2.63, p = 0.009), and CDR-SOB scores (OR = 2.46, p = 0.013). The odds ratio for amyloid PET positivity in patients older than and equal to 75 years with both frontal atrophy and CDR-SOB scores >1.0 was 3.63.

Conclusion:

Our study demonstrated that frontal atrophy, high CDR-SOB scores, and old age were risk factors associated with amyloid PET positivity in MCI with APOE ɛ3/ɛ3 genotypes.

Keywords

Amyloid apolipoproteins cognitive dysfunction plaque risk factors

INTRODUCTION

Alzheimer’s disease (AD) is one of the most prevalent neurodegenerative diseases, which is characterized by the deposition of cerebral amyloid-β (Aβ) [1]. Cerebral Aβ aggregation is an early pathologic event in AD, starting two to three decades before dementia onset [2, 3]. Mild cognitive impairment (MCI) is a prodromal stage of AD and amnestic MCI patients especially might progress to probable AD at a rate of 10–15% per year [4, 5]. The prevalence of amyloid positivity in patients with MCI is 47–75%, which is higher than in patients with normal cognition (1%) or subjective cognitive decline (10–44%) [3 , 7]. Presently, there are no effective therapeutic drugs that can cure AD. The current AD drugs, such as acetylcholinesterase inhibitors and N-methyl-D-aspartic acid glutamate receptor antagonists, only provide modest alleviation of AD symptoms. The aggregation and accumulation of Aβ begin two to three decades before dementia onset and recent clinical trials have focused on preventing or reducing the deposition of Aβ from the prodromal stage of AD.

Amyloid positron emission tomography (PET) has made it possible to detect cerebral Aβ pathology in vivo [8] and it has been widely applied in various clinical trials for the accurate diagnosis of AD. However, amyloid PET imaging is still limited due to the high cost, limited availability, and safety issues [9, 10]. These limitations emphasize the need for easily applicable and reliable prediction methods to identify patients at a higher probability for amyloid deposition [11].

Apolipoprotein E (APOE) is one of the most significant genetic risk factors for late-onset AD [12]. There are three common allelic forms, ɛ2, ɛ3, and ɛ4. Among these alleles, the APOE ɛ4 allele is related to medial temporal lobe hypometabolism and atrophy, increased cerebral Aβ, and altered CSF amyloid and tau levels [13 –16]. A single copy of the APOE ɛ4 allele increases the risk of developing AD by about 4-fold, whereas two copies increase the risk by about 12-fold [17]. In contrast, the APOE ɛ2 allele reduces the risk of developing AD by almost half [18]. In patients with MCI at age 70, APOE ɛ4 carriers have 56.5–86.7% amyloid PET positivity and APOE ɛ4 non-carriers have 27.0–38.7% [3]. APOE ɛ3/ɛ3 is the most common genotype in MCI patients as well as in the general population, present in 45.2 to 63.4% of the population. APOE ɛ3/ɛ3 MCI patients show 38.7% amyloid PET positivity, much lower than the 67.2% of patients with a single copy of the APOE ɛ4 allele. Furthermore, amyloid PET positivity is seen in 86.7% of the patients with two copies of the APOE ɛ4 allele [1 , 19]. The overall number of APOE ɛ3/ɛ3 MCI patients with amyloid pathology might not be small because of the high prevalence of the APOE ɛ3/ɛ3 genotype. The risk factors affecting amyloid positivity in APOE ɛ3/ɛ3 subjects have not been identified because APOE ɛ3 is usually used as a reference allele and considered to be neutral to the risk of AD [12].

When administering the amyloid targeted drugs to patients with MCI in clinical practice, it is important to find a proper subject that is an APOE ɛ3/ɛ3 carrier showing amyloid PET positivity who has a lower probability of amyloid PET positivity than an APOE ɛ4 carrier. If only high-risk patients are screened and tested for amyloid PET, the economic and social burdens may be reduced. In this study, we aimed to evaluate which risk factors affected amyloid PET positivity in APOE ɛ3/ɛ3 carriers to detect those who have higher amyloid positivity.

METHODS

Participants

We retrospectively reviewed the medical records of patients who underwent Florbetaben or Flutemetamol PET scanning at the Catholic University of Korea Seoul St. Mary’s Hospital from September 2015 to March 2019. We selected the patients who had two copies of the APOE ɛ3 allele and fulfilled the criteria of MCI. We defined MCI using Petersen’s criteria as patients with objective memory impairment for their age, but normal performance of the activities of daily living (ADL) [4]. Patients with brain lesions or neurologic disorders that affected cognitive function, such as recent or major stroke, brain tumors, Parkinson’s disease, normal pressure hydrocephalus, and epilepsy and those with abnormal laboratory findings, such as thyroid disease, vitamin B12 or folate deficiency, syphilis, and HIV, were excluded from the study. Uncontrolled psychiatric illnesses, such as schizophrenia and alcohol and drug dependent patients were also excluded.

Acquisition of PET and magnetic resonance images

A total of 673 patients underwent amyloid PET scans, either by ¹⁸F-florbetaben PET or ¹⁸F-flutemetamol PET, at the Catholic University of Korea Seoul St. Mary’s Hospital using a Discovery 710 PET/CT scanner (GE Medical Systems, Milwaukee, WI, USA) and a Biograph 40 PET/CT scanner (Siemens Healthineers, Knoxville, TN, USA). For ¹⁸F-florbetaben PET or ¹⁸F-flutemetamol PET, the PET/CT scans was acquired 90 min after the injection of an average dose of 300 MBq ¹⁸F-florbetaben or 200 MBq ¹⁸F-flutemetamol, respectively. A low-dose CT scan was performed for attenuation correction and was immediately followed by PET imaging in the three-dimensional mode for 20 min. The standard ordered subset expectation maximization (OSEM) algorithm (subset 33, integration 3) was utilized for reconstructing the PET images. All PET images were interpreted by nuclear medicine physicians who were blinded to the neuropsychological tests and classifications and dichotomized the images as amyloid-positive or negative using visual reads. The PET images were interpreted only by readers who successfully completed the electronic training program provided by the manufacturer. The patients also underwent 1.5T and 3.0T brain magnetic resonance imaging (MRI) using Signa (GE Medical Systems, Milwaukee, WI, USA), Avanto (Siemens, Knoxville, TN, USA), Verio (Siemens Healthineers, Knoxville, TN, USA), Achieva (Philips Healthcare, Best, The Netherlands), and Skyra (Siemens Healthineers, Knoxville, TN, USA) scanners consisting of T1- and T2-weighted imaging and fluid-attenuated inversion recovery sequences (FLAIR). All MRI images were reviewed by a neurology physician and radiology physicians who evaluated brain atrophy and white matter hyperintensity visually. Medial temporal atrophy was classified into grades 0 to 4 according to Scheltens’ scale [20], in which grade 2 or higher was defined as the presence of atrophy. Frontal and parietal cortical atrophy was categorized into grades 0 to 3 on a global cortical atrophy scale [21, 22] and grade 2 or higher was defined as the presence of atrophy. The presence of white matter hyperintensity was determined by a modified Fazekas scale [23] score of 2 or higher.

Assessment of cognitive functioning and clinical data

All participants underwent the Seoul Neuropsychological Screening Battery (SNSB) to evaluate their cognitive function [24]. The SNSB consists of the digit-span test (DST; forward and backward), the Korean version of the Boston Naming Test (K-BNT), the Rey-Osterrieth Complex Figure Test (RCFT; composed of copying, immediate and 20 min-delayed recall, and recognition), the Seoul Verbal Learning Test (SVLT; three learning-free recall trials involving 12 words, a 20 min-delayed recall trial of these 12 items, and a recognition test), the phonemic Controlled Oral Word Association Test (COWAT), and the Korean Color Word Stroop test (K-CWST; word and color reading of 112 items over a 2 min period). All tests were analyzed based on z-scores. The z-scores were standardized using the age and the educational criteria that are presented in the SNSB-II based on a large, nationwide Korean sample (1100 people), thereby making it possible to make comparisons with the population averages. A z-score <0 indicates a poorer performance relative to the population average, while a z-score < –1 indicates an abnormal performance. We dichotomized normal and abnormal performance based on z-score < –1. Amnestic MCI patients were defined by less than –1 either SVLT or RCFT delayed recall z-scores. Nonamnestic MCI patients were more than and equal to –1 in both of the SVLT and RCFT delayed recall z-scores, but less than –1 in at least one of the SNSB domains excluding the SVLT and RCFT recall tests. The patient’s global cognition was assessed using the Korean version of the Mini-Mental State Examination (K-MMSE). The patient’s functional performance was assessed by the Clinical Dementia Rating Sum of Boxes (CDR-SOB). Geriatric Depression Scale (GDS) scores over 10 and short-version GDS (sGDS) scores greater than 8 were defined as the presence of depression. Clinical variables, such as age, sex, education, vascular risk factors (hypertension, diabetes, and previous stroke history), and family history, were obtained by medical record review.

Statistical analysis

Our variables of interest were the following: demographics (age, sex, and education); a history of hypertension, diabetes mellitus, or stroke; family history of dementia; neuropsychological tests; brain atrophy (frontal, parietal, and medial temporal); and white matter hyperintensity.

The continuous variables were analyzed by independent t-tests or the Wilcoxon rank-sum test and the categorical variables were analyzed by the Chi-squared test or Fisher’s exact test. Logistic regression models were used to assess the predictors of amyloid positivity. Univariate regression models were used for the analysis of the variables of interest. The significant predictors identified in the univariate logistic regression models were used as independent variables in multivariate logistic regression analysis using a stepwise forward selection. All analyses were completed using SPSS version 24 (SPSS, Chicago, IL, USA) and SAS version 9.4 (SAS Institute, Cary, NC, USA). A p-value of <0.05 was considered significant.

RESULTS

From September 2015 to March 2019, 673 patients underwent Florbetaben or Flutemetamol PET scans. Of them, 265 patients who had dementia or other neurologic diseases like Parkinson’s disease or acute stroke were excluded. Of those 408, 60 had subjective cognitive decline or normal cognition. Therefore, 348 patients were identified with MCI. Twenty-two patients were excluded due to missing MRI scans and neuropsychological test data. Finally, out of 326 MCI patients, 171 (52.5%) with apolipoprotein E ɛ3/ɛ3 participated in this study. The percentage of other APOE alleles was as follows: ɛ2/ɛ2 in two patients (0.6%), ɛ2/ɛ3 in 45 (13.8%), ɛ2/ɛ4 in eight (2.5%), ɛ3/ɛ4 in 83 (25.5%), and ɛ4/ɛ4 in 17 (5.21%) patients. Of all the MCI patients with an APOE ɛ3/ɛ3 genotype, 77 (45.0%) were male. The median age of the patients was 73.0 years, ranging from 36 to 90 years and the median years of education were 12.3, ranging from 0.5 to 22 years. There were 140 patients (81.9%) with amnestic MCI and the others (18.1%) were nonamnestic MCI patients.

Out of 171 patients, 49 patients (28.65%) showed positive results in the Florbetaben or Flutemetamol PET scans, which was lower than the percentage of the MCI patients with at least one copy of APOE ɛ4 (72.2%). The mean age of the patients in the amyloid PET positive group was 76.88±8.25, which was higher than that of the amyloid PET negative group (71.46±10.05). The presence of frontal cortical atrophy was significantly higher in the amyloid PET positive group (61.2% versus 33.6%). The CDR-SOB scores were higher in the amyloid PET positive group (1.5 versus 1.0). The other baseline characteristics were not significantly different between the two groups. Other neuropsychological test results, the presence of depression, hypertension, diabetes mellitus, family history of dementia, and stroke history, showed no statistically significant differences between the two groups (Tables 1 and 2).

Table 1

Baseline characteristics of Apolipoprotein E ɛ3/ɛ3 patients (n = 171)

Characteristics	Amyloid (–)	Amyloid (+)	P
	(n = 122)	(n = 49)
Age (y)	71.46±10.05	76.88±8.25	0.001
Gender (female)	67 (54.9)	27 (55.1)	0.983
Education (y)	12.08±5.28	12.96±4.31	0.304
MMSE	26.20±2.88	25.80±2.26	0.384
MMSE (z score)	(–)0.98±1.34	(–)1.20±1.28	0.337
CDR-SOB	1.0 (0.5–1.5)	1.5 (1.0–2.0)	0.041
Depression (yes, %)	32 (26.5)	16 (32.7)	0.416
Family history	28 (23.0)	14 (28.6)	0.440
Medical history
HTN (yes, %)	46 (37.7)	23 (46.9)	0.266
DM (yes, %)	36 (29.5)	13 (26.5)	0.697
Stroke (yes, %)	15 (12.3)	7 (14.3)	0.725
Atrophy (yes, %)
Medial temporal	51 (41.8)	27 (55.1)	0.114
Parietal	64 (52.5)	30 (61.2)	0.298
Frontal	41 (33.6)	30 (61.2)	0.001
WMH (yes, %)	23 (18.9)	14 (28.6)	0.163

MMSE, Mini-Mental State Examination; CDR, Clinical Dementia Rating; SOB, Sum of Boxes; HTN, hypertension; DM, diabetes mellitus; WMH, white matter hyperintensity. Values are presented as the mean±standard deviation. Statistical analysis was performed by Independent t test or Wilcoxon rank sum test for continuous variables and Chi-square test or Exact test for categorical variables.

Table 2

Neuropsychological test in patients with amyloid positive scan and amyloid negative scan

Characteristics	Amyloid (–) (n = 122)	Amyloid (+) (n = 49)	P
DSF (z-score)	0.18 [(–)0.56–0.95]	0.02 [(–)0.56–0.86]	0.648
DSB (z-score)	(–)0.19±0.99	(–)0.26±1.26	0.687
K-BNT (z-score)	(–)0.25 [(–)1.35–1.03]	(–)0.90±2.04	0.147
RCFT-copy (z-score)	0.15 [(–)0.73–0.68]	(–)0.37 [(–)1.24–0.36]	0.056
SVLT-immediate (z-score)	(–)0.86±1.02	(–)0.91±0.95	0.764
SVLT-delayed (z-score)	(–)1.47±1.12	(–)1.38±1.15	0.614
SVLT-recognition (z-score)	(–)0.85±1.12	(–)0.84±1.25	0.930
RCFT- immediate (z-score)	(–)0.54±1.16	(–)0.88±1.04	0.071
RCFT-delayed (z-score)	(–)0.61±1.10	(–)0.93±0.99	0.078
RCFT-recognition (z-score)	(–)0.42±1.53	(–)0.88±1.38	0.073
COWAT-Phonemic (z-score)	(–)0.71±1.08	(–)0.45±1.24	0.164
K-CWST-WR (z-score)	(–)0.32±1.14	(–)0.21±0.95	0.551
K-CWST-CR (z-score)	(–)0.83±3.14	(–)0.80±2.33	0.944

DSF, digit span forward; DSB, digit span backward; KBNT, Korean Boston Naming Test; SVLT, Seoul Verbal Learning Test; RCFT, Rey Complex Figure Test; COWAT, Controlled Oral Word Association Test; KCWST-WR, Korean Color Word Stroop Test-Word reading; KCWST-CR, Korean Color Word Stroop Test-Color reading. Values are presented as the mean±standard deviation. DSF, KBNT, and RCFT were expressed as medians including interquartile ranges. Statistical analysis was performed by Independent t test or Wilcoxon rank sum test for continuous variables and Chi-square test or Exact test for categorical variables.

Table 3 provides summaries of the univariate logistic regression models. Age 75 years and older (OR = 2.45, 95% CI: 1.23–4.88), the presence of frontal atrophy (OR = 3.12, 95% CI: 1.57–6.20), and CDR-SOB scores greater than 1.0 (OR = 2.52, 95% CI: 1.28–4.98) were significantly associated with amyloid PET positivity. We further performed multivariate logistic regression analyses by a stepwise selection method to identify the risk factors associated with amyloid PET positivity.

Table 3

The association between amyloid positivity and risk factors in Apolipoprotein E ɛ3/ɛ3 patients

	Univariate analysis		Multivariate analysis
Variables	OR (95% CI)	P	OR (95% CI)	P
Age (≥75)	2.45 (1.23–4.88)	0.011	1.92 (0.92–4.00)	0.081
Frontal atrophy	3.12 (1.57–6.20)	0.001	2.63 (1.28–5.42)	0.009
CDR-SOB (>1.0)	2.52 (1.28–4.98)	0.008	2.46 (1.21–5.00)	0.013

Age and CDR-SOB were dichotomized using their median values in the sample (75 years and 1.0). Statistical analysis was performed by univariate and multivariate logistic regression models.

In a multivariate logistic regression model (Table 3), amyloid positivity was associated with two predictors, frontal atrophy (adjusted OR = 2.63, 95% CI: 1.28–5.42, p = 0.009), and CDR-SOB scores (adjusted OR = 2.46, 95% CI: 1.21–5.00, p = 0.013). In an additional analysis conducted only in amnestic MCI patients, amyloid positivity was associated with frontal atrophy (adjusted OR = 2.74, 95% CI: 1.21–6.21, p = 0.015) and age (adjusted OR = 2.71, 95% CI: 1.17–6.31, p = 0.020).

Twenty-two patients were 75 years and older, and had frontal atrophy and CDR-SOB scores greater than 1.0. Of the 22, twelve (54.6%) showed amyloid PET positivity and ten (45.5%) showed amyloid PET negativity. The odds ratio for amyloid PET positivity in patients older than and equal to 75 years, with frontal atrophy and CDR-SOB scores greater than 1.0 was 3.63 (95% CI: 1.45–9.10, p = 0.006). Compared to patients without any of the three factors, the odds ratio for amyloid PET positivity in patients with all three factors increased to 8.16 (95% CI: 2.32–28.74, p = 0.001). The odds ratio for amyloid PET positivity in patients over 75 years and older with frontal atrophy was 3.61 (95% CI: 1.76–7.40, p ≤ 0.001) and the odds ratio for amyloid PET positivity in people 75 years and older with CDR-SOB scores greater than 1.0 was 2.88 (95% CI: 1.38–6.02, p = 0.005). The odds ratio for amyloid PET positivity in patients with both frontal atrophy and CDR-SOB scores greater than 1.0 was 3.59 (95% CI: 1.65–7.78, p = 0.001).

DISCUSSION

Our study demonstrated that frontal atrophy, high CDR-SOB scores, and old age were associated with amyloid PET positivity in MCI patients with APOE ɛ3/ɛ3 genotypes. Previous studies have shown a directly proportional relationship between age and Aβ-positivity [3 , 25]. In one study, about 40% of the APOE ɛ4 noncarriers and more than 80% of the APOE ɛ4 carriers without cognitive impairment were amyloid PET-positive at age 90 [3]. We also found that age was one of the important risk factors for determining Aβ-positivity in MCI patients with the APOE ɛ3/ɛ3 genotype. The mean age of the amyloid PET positive group was higher than that of the amyloid PET negative group. In patients 75 years and older, the odds ratio for demonstrating amyloid PET positivity was 2.45.

According to a previous report, CDR-SOB scores, memory domain scores in the neuropsychological test, and the presence of the APOE ɛ4 allele were useful factors in predicting amyloid positivity in patients with amnestic MCI [26]. In patients with the APOE ɛ3/ɛ3 genotype, we also found that the CDR-SOB scores were an important factor affecting amyloid positivity. However, the overall neuropsychological tests, including the memory domain of the tests, did not show any statistical significance between the amyloid PET-positive and negative groups. These results may have been due to the small sample size and inclusion of both amnestic and nonamnestic (18.1%) MCI patients. Another hypothesis is that the memory deficits were prominent in the APOE ɛ4 carriers [27], but not likely in patients with APOE ɛ3/ɛ3. Although not statistically significant, the overall neuropsychological test scores tended to be lower in the amyloid PET positive group.

In a previous study, APOE ɛ4 was shown to be a potent risk factor for Aβ positivity [28, 29] and was related to medial temporal lobe hypometabolism and atrophy [13 –16]. However, our study found that frontal atrophy rather than medial temporal atrophy was a more sensitive predictor of amyloid PET positivity in MCI patients with the APOE ɛ3/ɛ3 genotype. APOE ɛ4 is related to medial temporal lobe atrophy, but APOE ɛ3 may be more prominent in frontal atrophy than in the medial temporal area. The relationship between memory and hippocampal volume was only observed in APOE ɛ4 homozygotes [30, 31]. In addition, Geroldi et al. reported that APOE ɛ4 non-carriers showed greater frontal lobe atrophy [32] and van der Vlies et. al. and Wolk et al. reported that APOE ɛ4 non-carriers had greater cognitive declines in the non-memory domains [33, 34]. Overall, these reports suggested that medial temporal lobe atrophy was not as prominent in the APOE ɛ3 carriers as in the APOE ɛ4 carriers.

In this study, presence of frontal atrophy, high CDR-SOB scores, and old age were related to amyloid PET positivity in MCI patients with APOE ɛ3/ɛ3 genotypes. In Palmqvist et al. paper [31], there was a model predicting amyloid PET positivity in relation to APOE genotype. When using the models described by Palmqvist et al. study, predicted amyloid PET positivity in patients older than and equal to 75 years with both frontal atrophy and CDR-SOB scores > 1.0 were 52.6% –81.7%. Using our data, the positive rates for amyloid PET in these people were 55.6%. However, when using the models described by Palmqvist et al. study, predicted amyloid PET positivity in patients less than 75 years old with no frontal atrophy and CDR-SOB scores ≦1.0 were 18.5% –55.7%. Using our data, the positive rates for amyloid PET in these people were 8.7%. Our model had a slightly lower rate of detecting people who were amyloid PET positive than the Palmqvist et al. model, but a slightly higher rate of detecting people who were amyloid PET negative. Therefore, our model could be useful to select people who were unnecessary to take amyloid PET.

This study had some limitations. Since we included both amnestic and non-amnestic MCI patients, some patients with pathology rather than AD may have been included in the study. In addition, this study was a retrospective study conducted by chart reviews, so selection bias could not be excluded. Also, brain atrophy was only analyzed by visual rating in this study, which can be less accurate than using manual or automatic volumetric methods. The reason for using a visual rating scale in this study was to access MCI people easily to predict amyloid positivity in clinical settings without using computer-assisted image analysis programs that require thin-section 3D T1 MRI images. Many recent studies suggest that neuroinflammation can co-occur with Aβ deposition in early AD [35]. However, the exact mechanism for this has not been well known. APOE genotype is one of the AD risk genes associated with neuroinflammation, and among them, APOE ɛ4 is known to have the strongest inflammatory effect [36]. It would be nice to see if inflammatory factors also could affect amyloid PET positivity in people with APOE ɛ3/ɛ3 genotypes, but we could not obtain inflammation markers. Further studies will be needed to investigate the relationship between inflammation and amyloid PET positivity in people with APOE ɛ3/ɛ3 genotypes in the future.

In conclusion, this study showed that age, CDR-SOB scores, and frontal lobe atrophy may be used as predictors of amyloid positivity in MCI patients with APOE ɛ3/ɛ3. People with APOE ɛ3/ɛ3 showed a lower positive rate of amyloid PET positivity than those with the APOE ɛ4 allele, but the number of MCI patients with cerebral amyloid pathology is not likely to be small because of the high prevalence of APOE ɛ3/ɛ3 (45.2 to 63.4% of the total population). The application of amyloid PET in MCI patients with the previously mentioned risk factors would reduce unnecessary costs and screening failure rates in disease-modifying clinical trials or help select proper patients in clinical practice with monoclonal antibodies against Aβ.

Footnotes

ACKNOWLEDGMENTS

This study was supported by a grant from Ministry of Health and Welfare (HI18C0530). Statistical consultation was supported by the Department of Biostatistics of the Catholic Research Coordinating Center.

Authors’ disclosures available online ().

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