Depressive symptoms and regional cerebral blood ow inAlzheimer's disease

Seishi Terada a,n, Etsuko Oshima a, Shuhei Sato b, Chikako Ikeda a, Shigeto Nagao a,Satoshi Hayashi a, Chinatsu Hayashibara a, Osamu Yokota a, Yosuke Uchitomi a

a Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences,2-5-1 Shikata-cho, Kita-ku, Okayama 700-8558, Japanb Department of Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan

a r t i c l e i n f o

Article history:Received 31 December 2012Received in revised form23 October 2013Accepted 9 November 2013Available online 15 November 2013

Keywords:Alzheimer's disease (AD)DepressionDepressive symptomRegional cerebral blood ow (rCBF)

a b s t r a c t

Depressive symptoms are common in patients with Alzheimer's disease (AD) and increase the caregiverburden, although the etiology and pathologic mechanism of depressive symptoms in AD patients remainunclear. In this study, we tried to clarify the cerebral blood ow (CBF) correlates of depressive symptomsin AD, excluding the effect of apathy and anxiety. Seventy-nine consecutive patients with AD wererecruited from outpatient units of the Memory Clinic of Okayama University Hospital. The level ofdepressive symptoms was evaluated using the depression domain of the Neuropsychiatric Inventory(NPI). The patients underwent brain SPECT with 99mTc-ethylcysteinate dimer. After removing the effectsof age, anxiety and apathy scores of NPI, and ve subscales of Addenbrooke's Cognitive Examination-revised (ACE-R), correlation analysis of NPI depression scores showed a signicant cluster of voxels in theleft middle frontal gyrus (Brodmann area 9), similar to the areas in the simple correlation analysis. Thedorsolateral prefrontal area is signicantly involved in the pathogenesis of depressive symptoms in AD,and the area on the left side especially may be closely related to the depressive symptoms revealedby NPI.

& 2013 Elsevier Ireland Ltd. All rights reserved.

1. Introduction

Alzheimer's disease (AD) is the leading cause of late-onsetdementia worldwide. Depressive symptoms are common inpatients with AD and increase the caregiver burden (Akiyamaet al., 2008; Kataoka et al., 2010). Although the etiology andpathologic mechanism of depressive symptoms in AD patientsremain unclear, a biological marker that objectively evaluatesdepressive symptoms might be useful (Kataoka et al., 2010).

There have been several studies on the relationship of depressivesymptoms to regional cerebral blood ow (rCBF) or regional cerebralglucose metabolism in AD (Hirono et al., 1998; Liao et al., 2003;Holthoff et al., 2005; Lee et al., 2006; Levy-Cooperman et al., 2008;Akiyama et al., 2008). Data from previous functional imaging studieshave mainly supported the role of the dorsolateral prefrontal region(Hirono et al., 1998; Holthoff et al., 2005; Lee et al., 2006; Levy-Cooperman et al., 2008; Akiyama et al., 2008). Associations with theanterior cingulate have been described inconsistently (Hirono et al.,

1998; Liao et al., 2003). However, most of these studies did notexclude AD patients with apathy or anxiety, although depressioncommonly coexists with apathy and anxiety (Kataoka et al., 2010).The presence of apathy is particularly germane as anterior cingulateand prefrontal hypoperfusion has been associated with apathysymptoms in AD patients (Lanctt et al., 2007). Moreover, almostall studies were performed in a cross-sectional setting (Hirono et al.,1998; Holthoff et al., 2005; Lee et al., 2006; Levy-Cooperman et al.,2008; Akiyama et al., 2008).

In this study, we tried to identify the cerebral blood owcorrelates of depressive symptoms in AD without the effect of apathyand anxiety by correlation analysis. We predicted a signicantrelationship between depressive symptoms and rCBF in the dorso-lateral prefrontal regions of AD patients.

2. Methods

2.1. Subjects

Seventy-nine consecutive patients with Alzheimer's disease were recruitedfrom the outpatient units of the Memory Clinic of Okayama University Hospitalbetween September 2008 and April 2012 according to the following criteria. Theyall (i) underwent general physical and neurological examinations and extensive

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0925-4927/$ - see front matter & 2013 Elsevier Ireland Ltd. All rights reserved.http://dx.doi.org/10.1016/j.pscychresns.2013.11.002

n Correspondence to: Department of Neuropsychiatry, Okayama University GraduateSchool of Medicine, Dentistry and Pharmaceutical Sciences. Tel.: 81 86 235 7242;fax: 81 86 235 7246.

E-mail address: terada@cc.okayama-u.ac.jp (S. Terada).

Psychiatry Research: Neuroimaging 221 (2014) 8691

laboratory testing, including thyroid function tests, serum vitamin B12, and syphilisserology; (ii) took the revised Addenbrooke's Cognitive Examination (ACE-R)(Yoshida et al., 2012), the Mini Mental State Examination (MMSE) (Folstein et al.,1975), the Frontal Assessment Battery (FAB) (Kugo et al., 2007); (iii) underwentsingle photon emission computed tomography (SPECT) with 99mTc-ethylcysteinatedimer of the brain as well as magnetic resonance imaging (MRI) of the head; and(iv) were diagnosed with probable AD according to the criteria formulated bythe NINCDS-ADRDA (McKhann et al., 1984). The exclusion criteria were(i) complications from other neurological diseases or illnesses; (ii) history ofmental illness or substance abuse prior to the onset of dementia; (iii) evidence offocal brain lesions on head MRI; (iv) treatment with cholinesterase inhibitors,memantine, antipsychotics, antidepressants, or anxiolytic drugs; and (v) lefthandedness or ambidexterity.

The prole of each subject (age, sex, months of disease duration, and years ofeducation) was obtained. Scores on three subscales (depression, anxiety, andapathy) of the Neuropsychiatric Inventory (NPI), Barthel Index, and FunctionalAssessment Questionnaire (FAQ) were rated by a trained clinical psychologist,based on the information from family caregivers. The Clinical Dementia Rating(CDR) (Hughes et al., 1982) score was rated by the chief clinician.

2.2. Instruments

NPI is a valid and reliable instrument for measuring non-cognitive symptoms indementia (Cummings et al., 1994; Hirono et al., 1997). It is a caregiver-based toolthat assesses ten different domains in dementia. The NPI gives a composite scorefor each domain, which is the product of frequency multiplied by severitysubscores: scores from 1 to 4 (with 4 being the most severe) for the frequencyand from 1 to 3 (with 3 being the most severe) for the severity of each behavior(Akiyama et al., 2008). The maximum attainable score was 12. In this study, threesubscales (depression, anxiety, and apathy) were used.

ACE-R was developed to provide a brief test sensitive to early stage dementia,and is capable of differentiating between dementia subtypes including AD,frontotemporal dementia, progressive supranuclear palsy, and other parkinsoniansyndromes (Mioshi et al., 2006). ACE-R includes MMSE, but extends it toencompass important areas not covered by MMSE, such as frontal-executivefunction and visuospatial skills. For this study, we used the Japanese version ofACE-R described by Yoshida et al. (2012).

The Barthel Index consists of 10 items that measure a person's daily function-ing, specically the activities of daily living and mobility (Wade and Collin, 1988).The total Barthel Index score ranges from 0 to 100. A higher score indicates a betterperformance. The Functional Assessment Questionnaire (FAQ) measures functionalactivities of older adults using the patient's partner as an informant (Pfeffer et al.,1982). The FAQ consists of ten items, and the score on each item ranges from 0 to 3.A higher score indicates more severe impairment.

2.3. Ethics

This study was approved by the Internal Ethical Committee of OkayamaUniversity Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences.After a complete description of the study to the subjects and their relatives, writteninformed consent was obtained.

2.4. Brain perfusion SPECT imaging

All subjects were examined by brain perfusion SPECT. Patients were examinedin a comfortable supine position with their eyes closed in quiet surroundings. Tenminutes after intravenous administration of 99mTc-ethylcysteinate dimer (ECD,600MBq, Daiichi Radioisotope Laboratories Ltd., Tokyo, Japan), SPECT images wereobtained using a triple-head, rotating gamma camera interfaced to a minicomputer(GCA9300A/ DI; Toshiba, Tokyo, Japan) equipped with a fanbeam, low-energy,high-resolution collimator. Sixty projection images over a 3601 angle in a 128128matrix were acquired. All images were reconstructed using ramp-ltered back-projection and then three-dimensionally smoothed with a Butterworth lter (order8, cutoff 0.12 cycles/cm). The reconstructed images were corrected for gamma rayattenuation using the Chang method (0.09).

2.5. Data analysis

Spatial reprocessing and statistical analysis of images was performed on a voxel-by-voxel basis using Statistical Parametric Mapping 8 (SPM8, Wellcome Departmentof Imaging Neuroscience, UK) running on MATLAB (The Mathworks, Inc., Natick, MA,USA). All SPECT images of each subject were normalized to the standard brain of theMontreal Neurological Institute (MNI), and spatial normalization was performed with12-parameter afne and non-linear transformations (Friston et al., 1995). The voxelsizes of the reslice option were 2 mm2 mm2 mm. The non-linear parameterswere set at 25 mm cut-off basis functions and 16 iterations. All the normalized SPECT

images were then smoothed with an isotropic Gaussian kernel lter (12 mm full-width at half-maximum).

We applied a simple regression method using SPM8 to obtain the correlationbetween NPI-dep scores and rCBF imaging data from SPECT among 79 AD subjects. Theanalysis used a threshold of po0.001 (uncorrected) at the voxel level, and results wereconsidered signicant at 100 voxels at the cluster level (simple correlation analysis).Thereafter, to remove the effect of other factors, age, ve subscale scores of ACE-R andtwo subscale scores (anxiety, apathy) of NPI were entered into the model as nuisancecovariates, and we performed a simple regression method using SPM8 to obtain thecorrelation between NPI-dep and rCBF imaging data from SPECT. The specic effects ofdepressive symptoms were tested using [1] t-contrast with an additional zero for thescores of other factors, assuming that the presence of the symptoms would be uniquelyassociated with decreased rCBF. In the latter analysis, a threshold of po0.001(uncorrected) was used at the voxel level, and results were considered signicant at100 voxels at the cluster level. In both analyses, global normalization was performed byproportional scaling with the mean voxel value. Masking was applied using thethreshold method (0.8 times the global value). In both analyses, global normalizationwas performed by proportional scaling with the mean voxel value. Masking was appliedusing the threshold method (0.8 times the global value).

2.6. Statistical analysis

Statistical analysis was performed using the SPSS 14.0J software program (SPSSInc., Chicago, IL). The correlation analysis of NPI-dep scores to other clinicalcharacteristics was done by Pearson's correlation coefciency. A value of po0.05was accepted as signicant.

3. Results

3.1. Demographic characteristics

Demographic characteristics are shown in Table 1. Among 79AD patients, 45 were women and 34 were men. For dementiaseverity, 47 patients had CDR scores 0.5, 31 had CDR 1, and onepatient had CDR 2. On the NPI depression score, 51 patients had ascore of 0, seven patients scored 1, ten patients scored 2, tenpatients scored 3, and one patient had a score of 6.

Table 1Clinical characteristics (n79).

Mean S.D. Range

Age (years) 76.2 7.6 4989Duration 28.3 16.6 479Education 11.0 2.5 416NPI-dep 0.8 1.3 06NPI-anxiety 0.2 0.7 04NPI-apathy 2.0 2.8 012MMSE 21.4 4.2 827ACE-R 65.4 13.3 3291Attention 13.7 3.2 318Memory 10.3 5.0 123Fluency 6.4 2.9 013Language 22.0 3.3 1026Visuospatial 12.9 3.0 416

FAB 10.3 2.8 316Barthel 96.9 5.4 80100FAQ 12.0 7.2 027

Duration, disease duration (months);Education, years of education;NPI-Dep, depression scores of neuropsychiatric inventory;Duration, duration of disease;Education, years of education;MMSE, mini mental state examination;ACE-R, revised Addenbrook's cognitive examination;Attention, attention and orientation scores of ACE-R;Memory, memory scores of ACE-R;Fluency, word uency scores of ACE-R;Language, language scores of ACE-R;Visuospatial, visuospatial scores of ACE-R;FAB, frontal assessment battery;Barthel. Barthel index;FAQ, functinal assessment questionnaire.

S. Terada et al. / Psychiatry Research: Neuroimaging 221 (2014) 8691 87

Correlation analyses revealed that the NPI-dep score had nosignicant correlation to demographic characteristics, cognitivefunctions, or activities of daily living, except for NPI-anxiety, andNPI-apathy scores (Table 2).

3.2. rCBF

Fig. 1a and Table 3 show the SPM (z) map of signicantcorrelation between rCBF and NPI-dep scores among AD patients.Simple correlation analysis showed a signicant cluster of voxelsin the left middle frontal gyrus (Brodmann area 9). Table 3 showsthe probability results of the SPM analysis and the location of peakz scores in terms of MNI coordinates.

After removing the effects of age, anxiety and apathy scores onNPI, and ve subscales of ACE-R, correlation analysis showed asignicant cluster of voxels in the left middle frontal gyrus(Brodmann area 9), similar to the areas in the simple correlationanalysis (Fig. 1b).

4. Discussion

There have been seven published studies, including this one, onrCBF or regional cerebral glucose metabolism among AD patientswith depressive symptoms (Table 4) (Hirono et al., 1998; Liao et al.,2003; Holthoff et al., 2005; Lee et al., 2006; Levy-Cooperman et al.,2008; Akiyama et al., 2008).

Among the seven studies, all except one (Liao et al., 2003),showed that dorsolateral frontal regions are signicantly related todepressive symptoms in AD. In only the study of Liao et al. is rCBFin the bilateral anterior cingulate, left posterior cingulate, and

bilateral precuneus different in AD patients with and withoutdepression. Their study included more severely impaired ADpatients (mean MMSE score was 12.9) compared to those in otherstudies (Table 4). In their study, the severity of cognitive impair-ment was measured by MMSE scores. MMSE is useful, but toosimple to validate the similarity of cognitive impairment betweentwo groups. The difference between cognitive impairments in ADpatients with and without depression might indicate the differ-ence of rCBF in the bilateral anterior cingulate, left posteriorcingulate and bilateral precuneus. Based on the above, we supposethat the dorsolateral prefrontal area is signicantly related todepressive symptoms in AD and that depressive symptoms in ADare due to a specic pathogenesis rather than a reactive phenom-enon (Liao et al., 2003).

The published ndings on brain lateralization of decreasedrCBF related to depressive symptoms in AD patients are conict-ing. Lee et al. (2006) reported a signicant decrease of rCBF in theright superior frontal region, and Levy-Cooperman et al. (2008)showed a decrease of rCBF in the right dominant dorsolateral andsuperior prefrontal regions . In both studies, apathy and anxietycoexisting with depression were not considered, and the NPI-depscore was not used to divide positive and negative groups. In theother four studies, signicantly related regions related to depres-sive symptoms were the bilateral superior frontal region (Hironoet al., 1998), left dorsolateral region (Holthoff et al., 2005), leftprefrontal region (Akiyama et al., 2008), and left middle frontalgyrus (our study). In the latter four studies, the NPI-dep score wasused to evaluate depressive symptoms (Table 4). Additionally,Holthoff et al. (2005) tried to decrease the effect of coexistingapathy statistically. In the study of Akiyama et al. (2008), the twogroups (depressive and not depressive) showed similar scores onapathy and anxiety scales. In our study, correlation analyses afterremoving the effects of apathy and anxiety scores revealed asimilar result. Laterality might be caused by several factors, suchas the inuence of other lesions or the severity of the disease, or itmight reect sample size, statistical threshold, or criteria used toscore depressive symptoms (Kataoka et al., 2010). Although notconclusively, we can say that the left dorsolateral prefrontal regionis closely related to the depressive symptoms evaluated by NPI.Many studies have reported that abnormalities in cortical-limbicor cortical-subcortical circuits related to emotional regulation areimplicated in the mechanisms underlying emotional dysfunction(Peng et al., 2012). The middle frontal gyrus is located in thedorsolateral prefrontal cortex (DLPFC), and the DLPFC circuit is oneof the prefrontal-subcortical circuits, some of which are involvedin regulation of affect (Peng et al., 2012).

Several studies have found that depression is generally asso-ciated with less left frontal activity and/or more right frontalactivity (Bell et al., 1998; Minnix et al., 2004). It has beenhypothesized that relative left frontal activity is related to positiveemotion and approach motivation, whereas relative right frontalactivity is related to negative emotion and withdrawal motivation(Davidson et al., 2000; Minnix et al., 2004). In AD, the left frontalregion might induce relative right frontal activity and negativeemotion.

5. Limitations

The results in this study should be interpreted with somecaution. Firstly, domain scores lower than 4 points of NPI-depreect behavioral symptoms of mild severity referred to as asubclinical disturbance (Holthoff et al., 2005). In this study, almostall patients had scores less than 4 in the NPI-dep domain.However, the degree of hypoperfusion in the middle frontal gyruswas correlated with the severity of depressive symptoms in our

Table 2Correlation analysis of NPI-Dep.

NPI-Dep

Age 0.166Duration 0.001Education 0.015NPI-anxiety 0.487nnn

NPI-apathy 0.340nn

MMSE 0.045ACE-R 0.026Attention 0.023Memory 0.132Fluency 0.189Language 0.142Visuospatial 0.050

FAB 0.121Barthel 0.018FAQ 0.063

NPI-Dep, depression scores of neuropsychiatric inventory;Duration, duration of disease;Education, years of education;MMSE, mini mental state examination;ACE-R, revised Addenbrook's cognitive examination;Attention, attention and orientation scores of ACE-R;Memory, memory scores of ACE-R;Fluency, word uency scores of ACE-R;Language, language scores of ACE-R;Visuospatial, visuospatial scores of ACE-R;FAB, frontal assessment battery;Barthel. Barthel index;FAQ, functinal assessment questionnaire;npo0.05.nn po0.01.nnn po0.001.

S. Terada et al. / Psychiatry Research: Neuroimaging 221 (2014) 869188

Fig. 1. (a) Correlation. The SPM (z) map of signicant correlation between rCBF and NPI-dep scores among AD patients. Upper line, three-way glass view of the area ofsignicant correlation. Lower line, three-way section of the area of signicant hypoperfusion. Left, transverse, z30; central, sagittal, x30; right, coronal, y24.(b) Correlation after removing effects of other factors. The SPM (z) map of signicant correlation between rCBF and NPI-dep scores among AD patients after removing theeffects of age, ve subscale scores of ACE-R, and two subscale scores (anxiety, apathy) of NPI. Upper line, three-way glass view of the area of signicant correlation. Lowerline, three-way section of the area of signicant hypoperfusion. Left, transverse, z34; central, sagittal, x30; right, coronal, y24.

Table 3Regions signicantly related with NPI-dep scores.

Number of voxels Peak z scores p Coordinates (MNI)

x y z

Region where rCBF signicantly correlate with NPI-dep scores (Fig. 1a) 107 3.90 o0.001 30 24 303.77 o0.001 28 22 34

Region where rCBF signicantly correlate with NPI-dep scores afterremoving the effect of other factorsn (Fig. 1b)

151 4.15 o0.001 30 24 34

rCBF, regional cerebral blood ow; NPI-Dep, depression scores of neuropsychiatric inventory.Voxels, number of voxels; Z scores, peak Z scores; MNI, Montreal Neurological Institute.

n Other factors are age, ve subscales scores of ACE-R, anxiety and apathy subscale scores of NPI.

S. Terada et al. / Psychiatry Research: Neuroimaging 221 (2014) 8691 89

analysis. Therefore, we suppose that hypoperfusion in the middlefrontal gyrus was involved in the expression of clinically depres-sive symptoms in patients with AD. Secondly, although thethreshold of 0.001 (uncorrected) may be regarded as the standardthreshold currently, we did not nd any signicant area under thestrict threshold of 0.01 (corrected).

Acknowledgments

We sincerely thank Ms. Ido, Ms. Horiuchi, Ms. Imai, and Ms.Yabe for their skillful assistance. This work was supported byGrants from the Japanese Ministry of Education, Culture, Sports,Science and Technology (21591517), and the Zikei Institute ofPsychiatry.

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Table 4Studies on the cerebral regions related with depressive symptoms in Alzheimer's disease.

Hirono et al. (1998) Liao et al. (2003) Holthoff et al.(2005)

Lee et al.(2006)

Levy-Cooperman et al.(2008)

Akiyama et al.(2008)

this study(2013)

Imaging PET SPECT PET PET SPECT SPECT SPECTSoftware ROI SPM99 SPM99 SPM99 SPM2 eZIS SPM8Statistics Comparison Correlation comparison Comparison Comparison Comparison Comparison CorrelationNumber 53 43 20 24 56 44 79Two

groups1934 835 1010 1212 2729 1826

Criteria NPI-dep o or 1- SCID NPI-dep o or 4- NIMH criteria CSDD 0-7 or 8- NPI-dep o or 1- NPI-depmean

MMSE21.2 12.9 22.2 nm 23.6 (16.5)n 21.4

Regions bil superior Fr, lt anteriorCin

bil anterior Cin, ltposteriorCin, bil precuneus

lt dorsolateral(preFr)

rt superior Fr dorsolateral &superior preFr (rtZ lt)

lt preFr lt preFr

ROI, manually placed range of interest; SPM, statistical parametric mapping;eZIS, after eZIS analysis, semiquantitatively scored from 0 to 2;Number, number of patients with Alzheimer's disease;Two groups, number of two groups depression positive and negative;Criteria, criteria for grouping;Regions, areas showing signicant decrease of regional cerebral blood ow among patients with depression or areas showing signicant correlation to depressive symptoms;NPI-dep, depression score of neuropsychiatric inventory;SCID, structured clinical interview for the Diagnostic Statistical Manual of mental disorders ed 3 revised;CSDD, Cornell scale for depression in dementia; MMSE, mini-mental state examinationn, mean score of the revised Hasegawa Dementia Scale (full score 30);NIMH, NIMH criteria for depression in Alzheimer's disease;nm, Not mentioned; bil, bilateral; r, right; lt, left; Fr, frontal; Cin, cingulate; AchE inhibitors, acetylcholine.

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Depressive symptoms and regional cerebral blood flow in Alzheimer's diseaseIntroductionMethodsSubjectsInstrumentsEthicsBrain perfusion SPECT imagingData analysisStatistical analysis

ResultsDemographic characteristicsrCBF

DiscussionLimitationsAcknowledgmentsReferences