Depressive Symptoms are Associated with Progression to Dementia in Patients with Amyloid-Positive Mild Cognitive Impairment

Abstract

Background: Depressive symptoms are prevalent in patients with mild cognitive impairment (MCI) and are considered to be a risk factor for progression to dementia.

Objective: The purpose of this study was to evaluate whether depressive symptoms in MCI promote disease progression in a manner related to amyloid status, and to determine the relationship between depressive symptoms and longitudinal cerebral structural changes.

Methods: Baseline data for 336 patients with MCI (75 with depression and 261 without) from the Alzheimer’s Disease Neuroimaging Initiative study were analyzed. All participants underwent comprehensive cognitive testing, volumetric magnetic resonance imaging (MRI), and [¹⁸F]AV45 positron emission tomography amyloid imaging. Depressive symptoms were measured using the Neuropsychiatric Inventory Questionnaire. A voxel-based morphometric analysis using volumetric brain MRI data was used to compare longitudinal structural changes related to depressive symptoms.

Results: The conversion rate to dementia was different between patients with and without depression in amyloid-positive MCI (40.8% versus 19.7%, respectively; p = 0.006). Patients who were amyloid-positive at baseline also exhibited a greater degree of 2-year cognitive decline. Depression in amyloid-positive MCI was associated with longitudinal cortical atrophy in the left cingulate gyrus.

Conclusion: Our study indicates that the presence of depressive symptoms in patients with amyloid-positive MCI is associated with higher progression to dementia and longitudinal cortical atrophy.

Keywords

Alzheimer’s disease depression mild cognitive impairment

INTRODUCTION

Alzheimer’s disease (AD) is the most common cause of dementia. AD significantly impairs the quality of life of both patients and their caregivers [1]. The identification of risk factors for conversion to dementia in patients with mild cognitive impairment (MCI) can facilitate the timely implementation of interventions to slow or modify disease progression. Among a variety of proposed biomarkers, amyloid-related markers have received significant attention as early detectable markers of conversion potential, as these markers have a known association with cognitive decline in MCI[2 –4].

Neuropsychiatric symptoms such as depression, apathy, anxiety, and irritability have been examined in the context of cognitive decline [5 –8]. A recent study suggested that the prevalence of depression in MCI was as high as 25–40% [9]. Depression has been implicated as a risk factor for the conversion of MCI to dementia. Yet, evidence for this association is inconsistent; whereas several studies have concluded that depression accelerates the progression of MCI to dementia [10 –12], other longitudinal studies have failed to determine whether depression predicts the conversion of MCI to dementia, despite a synergistic effect of MCI and depression on the reduction of hippocampal volume[13, 14].

The objective of our study was to reexamine the hypothesis that depression accompanying MCI is associated with later progression to dementia. We excluded patients with apathy in order to avoid clinical overlap with depression and to focus on the effects of depression itself. Furthermore, to inform the pathophysiology underlying the relationship between MCI and depression, we examined amyloid deposition as well as longitudinal changes in brain volume over a 2-year follow-up period.

MATERIALS AND METHODS

Ethics statement

The institutional review board of Kangwon National University approved this study, which was performed in accordance with the tenets of the declaration of Helsinki. Detailed protocols for informed consent can be found in the ADNI information pages (http://www.adni-info.org).

Alzheimer’s Disease Neuroimaging Initiative

The data used in the preparation of this article were obtained from the ADNI database (http://adni.loni.usc.edu). The ADNI was launched in 2003 by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, the Food and Drug Administration, private pharmaceutical companies and nonprofit organizations, as a 5-year public–private partnership with a US$60 million budget. The primary goal of ADNI is to identify the optimal combinations of serial MRI, PET and other biological markers, in conjunction with clinical and neuropsychological assessments to predict and measure the progression of MCI and early AD. The objective is to determine sensitive and specific markers of very early AD progression that will aid researchers and clinicians in developing new treatments and monitoring their effectiveness, while lessening the expense and duration of clinicaltrials.

The Principal Investigator of this initiative is Michael W. Weiner, MD, VA Medical Center and University of California–San Francisco, but ADNI is the fruit of the efforts of many coinvestigators from diverse academic institutions and private corporations; subjects have been recruited from over 50 sites across the US and Canada. ADNI studies are conducted in accordance with the Good Clinical Practice guidelines, the principles of the Declaration of Helsinki, and US 21 CFR Part 50 (Protection of Human Subjects), and Part 56 (Institutional Review Boards). This study was approved by the Institutional Review Boards of all of the participating institutions. Written informed consent was obtained from all participants at each site. The initial goal of ADNI was to recruit 800 subjects, but with the project extensions ADNI-GO and ADNI-2 has recruited over 1500 subjects aged 55 to 90 years. The research population consists of cognitively normal older individuals, individuals with early or late MCI, or patients with early AD. The follow-up duration of each group is specified in the protocols for ADNI-1, ADNI-2 and ADNI-GO. Subjects originally recruited for ADNI-1 and ADNI-GO had the option to be followed in ADNI-2. For up-to-date information, see http://www.adni-info.org. Data from ADNI-GO/ADNI2 are included in the present work. Preprocessed T1-weighted MPRAGE MR images (T1-W MRI) were downloaded from the ADNI database as on 15 September 2016.

Patient selection and study design

The patients with amnestic MCI who had completed baseline [¹⁸F]AV45 PET as well as T1-weighted MRI at baseline and 2-year follow-up were included in this study. Diagnoses of amnestic MCI were made according to the criteria of Petersen et al. [15]; accordingly, subjects showed objective memory impairment but did not meet the criteria for dementia. Additionally, all subjects had a Mini-Mental State Examination (MMSE) [16] score of 24 or higher, a global Clinical Dementia Rating (CDR) [17] score of 0.5, a CDR memory score of 0.5 or higher, and a score indicating impairment on the delayed recall of Story A of the Wechsler Memory Scale-Revised [18]. Basic demographic data and apolipoprotein E ɛ4 (APOEɛ4) status were also documented.

Neuropsychological and neuropsychiatric data

Longitudinal neuropsychological markers such as MMSE score, Alzheimer’s Disease Scale Cognitive Subscale (ADAS-cog) [19] score, and Clinical Dementia Rating-Sum of Boxes (CDR-SOB) score were evaluated at baseline and at 2-year follow-up. Neuropsychiatric Inventory Questionnaire (NPI-Q) scores were also obtained at baseline (at the time of PET scanning) for the diagnosis of subsyndromal depressive symptoms using the 4th item (positive: depression; negative: no depression) [20].

[¹⁸F]AV45 PET

The [¹⁸F]AV45 PET mean standard uptake value ratio (SUVR) was determined for each subject. Aβ-positive (Aβ+) and Aβ-negative (Aβ–) status were defined according to a SUVR threshold of≥1.10. This threshold was taken from the ADNI database as the composite volume of interest (VOI) standardized uptake value ratio (SUVR) with the highest accuracy for discriminating between cognitively normal subjects and patients with AD [21].

Imaging parameters

All subjects were imaged using a 3-T MRI scanner (GE, Siemens, or Philips). Data were collected at multiple ADNI sites in accordance with a standardized MRI protocol (http://adni.loni.usc.edu/methods/documents/mri-protocols/) that was developed by comparing and evaluating 3D T1-weighted sequences for morphometric analyses. MRI acquisition and processing were performed as per standard protocol [22].

Image processing and statistical parametric mapping

We performed volumetric analyses using Statistical Parametric Mapping 8 (SPM8, Welcome Department of Cognitive Neurology, London, UK) in a MATLAB 7.5.0 environment (Mathworks, Natick, MA, USA). For quantitative analysis of the whole brain, a standard voxel-based morphometry protocol was used and included spatial normalization, segmentation, and smoothing [23, 24]. All images were smoothed using an 8-mm Gaussian filter to minimize between-subjects variability in local anatomy. Smoothed gray matter segments were compared using a voxel-based paired t-test in order to identify cortical atrophy occurring between baseline and the 2-year follow-up. We also examined the effect of depression on longitudinal cortical atrophy using a flexible factorial design. The absolute threshold for masking was 0.1. Results were considered to be statistically significant when p < 0.05 (family-wise error rate [FWE]-corrected for paired t tests and uncorrected for the flexible factorial design). The x, y, and z coordinates of areas with significant correlations in the analysis were converted into Montreal Neurological Institute (MNI) coordinates and identified using MRIcron (http://www.mccauslandcenter.sc.edu/mricro/mricron/). We also performed volumetric calculations and anatomical segmentation using the Individual Brain Atlases tool in the Statistical Parametric Mapping Toolbox (IBASPM; http://www.thomaskoenig.ch/Lester/ibaspm.htm) [25]. MRI data were normalized to the MNI template and spatial transformation matrices were obtained. Additionally, individual MRI data were segmented and each individual gray matter voxel was labeled in accordance with the MNI anatomical atlas and transformation matrices. The volumes of hippocampus was computed based on previously obtained individual atlases. The total intracranial volume was computed as the sum of all gray matter, white matter, and CSF volume, and used to normalize the volume of each brain region.

Statistical analysis

Independent t-tests and chi-square tests were used to examine between-group differences in continuous variables and categorical variables, respectively. The number of patients converted to dementia in amyloid-negative MCI was small that the relationship between depressive symptoms and progression to dementia in amyloid-positive MCI was assessed using a multiple logistic regression. The pool of predictors included age, sex, educational level, MMSE score, CDR-SOB score, and ApoEɛ4 status. The level of statistical significance was set at p < 0.05. Statistical analyses were performed with R (Version 3.3.2, The R Foundation for Statistical Computing, 64-bit platform).

RESULTS

In amyloid-positive MCI, the conversion rate to dementia was higher in depressed group and depression was associated with longitudinal cortical atrophy. The details are as follows.

Subject characteristics

At the time of review, data was available for 337 patients with amnestic MCI (156 women and 181 men; mean age, 71.8±1.3) with the average length of time between baseline and follow-up was 1.94±0.4 years. All patients with MCI were classified according to brain amyloid status and the presence of depressive symptoms (Table 1). There were no significant between-group differences in age (except within amyloid negative subjects, p < 0.008), sex ratio, education level, length of time between baseline and follow-up, baseline neuropsychological test results, or initial cortical volume of the hippocampus for the amyloid-positive and amyloid-negative groups. APOE ɛ4 status was significantly more common in amyloid-positive MCI compared to amyloid-negative MCI (p < 0.05). For amyloid-positive MCI, there were significant differences in CDR-SOB scores (p < 0.008) and ADAS-cog scores (p < 0.03) between baseline and follow-up.

Table 1

Demographic and clinical data for the subjects

	Amyloid negative subjects			Amyloid positive subjects
Depressive symptom	Dep–(n = 124)	Dep+(n = 26)	p	Dep–(n = 137)	Dep+(n = 49)	p
Age, years (SD)	70.9 (7.6)	66.6 (6.6)	0.008	73.5 (6.8)	72.6 (6.4)	0.437
Sex, F/M %	46.8/53.2	42.3/57.7	0.842	45.3/54.7	49.0/51.0	0.778
Education, years (SD)	16.3 (2.5)	16.4 (2.4)	0.896	16.1 (3.0)	16.4 (2.5)	0.516
APOE ɛ4 gene dose			0.983			0.044
- No copies	95 (76.6%)	20 (76.9%)		47 (34.3%)	19 (38.8%)
- One copy	25 (20.2%)	5 (19.2%)		60 (43.8%)	27 (55.1%)
- Two copies	4 (3.2%)	1 (3.8%)		30 (21.9%)	3 (6.1%)
F/U duration, year (SD)	1.9 (0.3)	1.9 (0.3)	0.858	1.8 (0.5)	1.9 (0.5)	0.223
CDR-SOB (SD)	1.2 (0.7)	1.4 (0.8)	0.225	1.4 (0.9)	1.6 (0.8)	0.228
ADAS-Cog score (SD)	12.1 (5.0)	11.3 (4.3)	0.424	16.1 (6.6)	18.3 (7.8)	0.066
MMSE (SD)	28.6 (1.3)	28.4 (1.9)	0.618	27.8 (1.8)	27.3 (1.9)	0.111
ΔCDR-SOB (SD)	0.1 (0.5)	0.1 (0.3)	0.789	0.4 (1.0)	0.8 (0.9)	0.008
ΔADAS-Cog score (SD)	0.1 (2.1)	0.5 (2.1)	0.361	0.4 (3.3)	1.9 (4.3)	0.036
ΔMMSE (SD)	0.1 (1.0)	1.1 (3.8)	0.236	0.8 (1.8)	1.0 (1.8)	0.516
Progression to dementia	4 (3.2%)	1 (3.8%)	1.000	27 (19.7%)	20 (40.8%)	0.006
Hippocampus, left, mm³ (SD)	4.0 (0.7)	4.0 (0.5)	0.898	3.8 (0.7)	3.6 (0.6)	0.082
Hippocampus, right, mm³ (SD)	3.4 (0.5)	3.6 (0.4)	0.208	3.3 (0.5)	3.1 (0.5)	0.073

Dep-, subgroup without depressive symptom; Dep+, subgroup with depressive symptom; CDR-SOB, The Clinical Dementia Rating Scale Sum of Boxes, ADAS-cog, Alzheimer’s Disease Assessment Scale Cognitive subscale; MMSE, Mini-Mental State Examination; Δ, difference between baseline and 2-year follow-up.

Conversion rate

The rate of progression to dementia was higher in patients with depression compared to patients without depression (40.8% versus 19.7%, respectively; p < 0.006) in amyloid-positive MCI (Table 1). Baseline depression, CDR-SOB score, and MMSE score were significantly associated with progression to dementia (Table 2). The odds ratio for depression was 2.77 (95% confidence interval, 1.23–6.32; p = 0.01).

Table 2

Risk factors for conversion to dementia in amyloid-positive MCI subjects in multivariate logistic regression analyses

	Estimate	SE	z value	p	OR (95% CI)
(Intercept)	0.7880	3.9889	0.20	0.8434	2.20 (0.00–5405.39)
Depression	1.0193	0.4155	2.45	0.0142	2.77 (1.23–6.32)
Age	0.0340	0.0321	1.06	0.2891	1.03 (0.97–1.10)
Sex	–0.2665	0.4046	–0.66	0.5102	0.77 (0.34–1.69)
Education	0.0737	0.0723	1.02	0.3076	1.08 (0.94–1.24)
APOE4 status	0.2884	0.2956	0.98	0.3293	1.33 (0.75–2.41)
MMSE	–0.2733	0.1085	–2.52	0.0118	0.76 (0.61–0.94)
CDR-SOB	0.9227	0.2220	4.16	<0.0001	2.52 (1.65–3.96)

MCI, mild cognitive impairment; SE, standard error; OR, odds ratio; CI, confidence interval; CDR-SOB, The Clinical Dementia Rating Scale Sum of Boxes; MMSE, Mini-Mental State Examination.

Longitudinal cortical atrophy

Between the baseline and 2-year follow-up, a significant volumetric decrease was observed in the amyloid-positive MCI without depression group in the left parahippocampus, bilateral hippocampus, left middle temporal gyrus, left middle cingulum, right fusiform gyrus, right precuneus, and right middle occipital cortex (p < 0.05, FWE-corrected) (Fig. 1, Table 3). For the amyloid-positive MCI with depression group, longitudinal cortical atrophy was identified in the left hippocampus, left superior temporal pole, left insula, right superior temporal gyrus, right precentral gyrus, and right postcentral gyrus (p < 0.05, FWE-corrected). No cortical atrophy was observed between baseline and 2-year follow-up in amyloid-negative MCI, regardless of depression symptoms. A comparison of longitudinal cortical atrophy between amyloid-positive MCI with and without depressive symptoms revealed that depression was significantly associated with volumetric changes in the left anterior cingulum (p < 0.001, uncorrected) (Fig. 2).

Fig.1

Statistical parametric mapping for longitudinal cortical atrophy over 2 years in each group (p < 0.05, FWE-corrected). (a) Amyloid negative subjects without depression (n = 124), (b) Amyloid negative subjects with depression (n = 26), (c) Amyloid positive subjects without depression (n = 137), (d) Amyloid positive subjects with depression (n = 49).

Table 3

Location and peaks of significant decreases in regional cortical volume from the baseline to follow-up scans of amyloid-positive MCI (p < 0.05, FWE-corrected)

Structure	Talairach coordinates			FWE p value	Z-score
	x	y	z
MCI without depression
Left parahippocampus	–24	2	–26	<0.001	7.57
Left hippocampus	–26	–12	18	<0.001	7.30
Left middle temporal	–54	–16	–10	<0.001	7.22
Right amygdala	24	2	–24	<0.001	7.20
Right hippocampus	28	–10	–18	<0.001	7.19
Right fusiform	40	–12	–38	<0.001	7.71
Left cuneus	–16	–68	24	<0.001	7.73
Left middle cingulum	–4	–32	46	<0.001	7.70
Right precuneus	4	–66	30	<0.001	7.70
Right middle occipital gyrus	36	–82	26	0.001	5.20
MCI with depression
Right superior temporal gyrus	48	–22	12	<0.001	6.80
Right postcentral gyrus	64	–14	14	<0.001	6.20
Right precentral gyrus	56	–8	42	<0.001	6.12
Left hippocampus	–30	–12	–14	<0.001	5.59
Left superior temporal pole	–34	20	–24	<0.001	5.55
Left insula	–38	16	–8	0.001	5.53
Left superior temporal gyrus	–42	–4	–10	0.001	5.45

MCI, mild cognitive impairment; FWE, family-wise error.

Fig.2

Cortical atrophy associated with depressive symptom in amyloid positive subjects over 2 years (Uncorrected p < 0.001).

DISCUSSION

Although many epidemiological and clinical studies have suggested that depressive symptoms are associated with an increased risk of dementia, this is the first study to show longitudinal changes in brain structure related to depression and amyloid status in MCI. Patients with amyloid-positive MCI who also had depression had a higher risk of progression to dementia and exhibited a greater degree of cognitive decline over a 2-year follow-up period compared to non-depressed subjects with amyloid-positive MCI. Additionally, we identified significant cortical atrophy in amyloid-positive but not amyloid-negative MCI over a 2-year follow-up period, regardless of the presence of depressive symptoms. Within the amyloid-positive MCI group, depression was associated with specific longitudinal changes on volumetric MRI, specifically affecting the cingulate gyrus. These findings are consistent with pre-existing literature; depression has been previously associated with a 2-fold risk of MCI conversion to dementia [26], and moreover the presence of depressive symptoms has been associated with greater atrophy of regions related to AD pathology [27]. Our data therefore add to these findings regarding depression in MCI and dementia by incorporating amyloid positivity as an additional factor.

MCI describes a subset of heterogeneous disease entities of degenerative, vascular, metabolic, traumatic, and psychiatric etiology that can involve depression [28]. The present data regarding amyloid positivity in MCI are consistent with MCI due to AD with intermediate likelihood, as per the revised diagnostic criteria of the National Institute for Aging-Alzheimer’s Association [29].

In the present study, longitudinal changes in the hippocampus, parahippocampus, temporal gyrus, precuneus, and cingulate gyrus in amyloid-positive MCI were consistent with previous reports of a so-called “AD signature on brain MRI,” and support the hypothesis that these changes were related to AD vulnerability [30]. Subtle cortical thinning in these regions is detectable even in symptom-free amyloid-positive individuals [31]. Additionally, our result regarding the medial temporal lobe is consistent with the findings of a previous meta-analysis on volumetric changes during longitudinal follow-up in AD [32]. There were more areas with diffuse cortical atrophic change in non-depressed group than depressed group in amyloid-positive MCI and this might be due to the difference of the numbers included for SPM analysis (137 versus 49, respectively). Depression-related changes in the left anterior cingulum of patients with amyloid-positive MCI highlight the involvement of the frontal-limbic circuit in depression pathogenesis [33 –35]. Indeed, previous MRI studies have shown that depression in elderly individuals free of cognitive decline was associated with a decrease in the volume of the prefrontal area [36 –38]. Moreover, studies in patients with late life depression and cognitive impairment have identified reduced cortical thickness in the cingulate cortex, orbitofrontal cortex, dorsolateral prefrontal cortex, temporal area, and parietal area [39, 40]. Accordingly, our findings may be related to altered mood control in patients with MCI that eventually progresses to dementia.

The issue of depression in MCI patients is clinically important for a number of reasons, not limited to the hypothesis that even mild depression is a risk factor for the conversion of amyloid-positive MCI to dementia. Recent studies have indicated that subjects with lifetime occurrences of major depression have increased amyloid uptake in the precuneus and parietal region [41]; additionally, patients with amyloid positive-MCI were shown to have greater frontotemporal amyloid burden [42]. Considering the effect of depression on cortical atrophy in amyloid-positive MCI in the present study, we speculate that the pathological features of late-onset depression interact with those of amyloid deposition to produce structural changes in the brain. This hypothesis is supported by a previous study that observed depression-associated decreases in cortical volume in patients with AD [39]. Thus, the careful assessment of psychological status over time in MCI is necessary not only to improve the quality of life of patients and caregivers, but also to reduce the risk of progression to dementia.

The present study had several limitations. First, a less stringent threshold for significance was adopted to determine effects of depression on cortical atrophy in our statistical mapping analysis (p < 0.001, uncorrected). Second, we did not consider antidepressant medication use in our study, such that we did not account for possible effects of antidepressants on cortical atrophy. Finally, because subjects with a geriatric depression score <6 were included in the ADNI cohort, patients with significant depressive symptoms were excluded. Additionally, we diagnosed depression and apathy using a single item of the NPI-Q rather than a structured clinical interview. A clinical trial known as “The ADNI Depression Project” is currently recruiting elderly participants who meet the criteria for major depression or late-life depression. This 30-month prospective study will evaluate blood markers, clinical data, cognitive assessments, brain MRI, and [¹⁸F]AV45 PET amyloid imaging in order to further shed light on the pathological mechanisms contributing to cognitive impairment in older adults with depression.

In summary, we identified depressive symptom as an independent risk factor for conversion to dementia in amyloid-positive MCI. Longitudinal structural changes related to depression at cingulate gyrus in our study might enhance our understanding of the neurobiological interaction between AD and depression.

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 sectorcontributions 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 research was also supported by the Original Technology Research Program for Brain Science through the National Research Foundation of Korea (NRF) funded by the Korean government (MSIP) (No. 2014M3C7A1064752).

Authors’ disclosures available online ().

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Depressive Symptoms are Associated with Progression to Dementia in Patients with Amyloid-Positive Mild Cognitive Impairment

Abstract

Keywords

INTRODUCTION

MATERIALS AND METHODS

Ethics statement

Alzheimer’s Disease Neuroimaging Initiative

Patient selection and study design

Neuropsychological and neuropsychiatric data

[18F]AV45 PET

Imaging parameters

Image processing and statistical parametric mapping

Statistical analysis

RESULTS

Subject characteristics

Conversion rate

Longitudinal cortical atrophy

DISCUSSION

Footnotes

ACKNOWLEDGMENTS

References

[¹⁸F]AV45 PET