Cognitive impairment in euthymic major depressive
disorder: a meta-analysis
E. Bora
1
*, B. J. Harrison
1
,M.Yu¨ cel
1
,
2
and C. Pantelis
1
1
Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, VIC, Australia
2
Orygen Youth Health Research Centre, The University of Melbourne, VIC, Australia
Background. There is evidence to suggest that cognitive deficits might persist beyond the acute stages of illness in
major depressive disorder (MDD). However, the findings are somewhat inconsistent across the individual studies
conducted to date. Our aim was to conduct a systematic review and meta-analysis of existing studies that have
examined cognition in euthymic MDD patients.
Method. Following a systematic search across several publication databases, meta-analyses were conducted for
27 empirical studies that compared euthymic adult MDD patients (895 participants) and healthy controls
(997 participants) across a range of cognitive domains. The influence of demographic variables and confounding
factors, including age of onset and recurrent episodes, was examined.
Results. Compared with healthy controls, euthymic MDD patients were characterized by significantly poorer
cognitive functions. However, the magnitude of observed deficits, with the exception of inhibitory control, were
generally modest when late-onset cases were excuded. Late-onset cases demonstrated significantly more pronounced
deficits in verbal memory, speed of information processing and some executive functions.
Conclusions. Cognitive deficits, especially poor response inhibition, are likely to be persistent features, at least of
some forms, of adult-onset MDD. More studies are necessary to examine cognitive dysfunction in remitted psychotic,
melancholic and bipolar spectrum MDD. Cognitive deficits overall appear to be more common among patients with
late-onset depression, supporting the theories suggesting that possible vascular and neurodegenerative factors play
a role in a substantial number of these patients.
Received 3 June 2012; Revised 31 July 2012 ; Accepted 6 August 2012
Key words : Cognition, late onset, major depression, memory, neuropsychology.
Introduction
Major depressive disorder (MDD) is a heterogeneous
mental disorder with high prevalence. In addition to
affective and vegetative symptoms, cognitive func-
tions are often impaired in affected patients with dis-
turbances in concentration being among the formal
diagnostic criteria. Cognitive deficits seem to be more
severe in patients with recurrent episodes, in late-
onset elderly cases (onset after 50–65 years of age) and
among patients who have psychotic or melancholic
features (Gorwood et al. 1998; Austin et al. 1999 ;
Fleming et al. 2004 ; Herrmann et al. 2007; Bora et al.
2010b). Cognitive impairment might also be a con-
tributing factor that determines levels of social and
occupational impairment in differerent phases of
MDD (Fennig et al. 2002; Yen et al. 2011).
Despite cognitive dysfunction being conceptualized
as a state-related phenomenon of MDD, increasing
evidence suggests that at least some of these impair-
ments persist during illness remission (Hasselbalch
et al. 2011). In bipolar disorder, cognitive deficits per-
sist in euthymic patients and these are likely to be re-
lated to structural and functional brain abnormalities
(Blumberg et al. 2003 ; Zimmerman et al. 2006; Bora
et al. 2009; Hartberg et al. 2011). While MDD is a more
heterogeneous condition relative to bipolar disorder as
it includes non-melancholic/milder reactive forms,
there may be certain cognitive trait features that also
reflect underlying pathophysiological changes, pri-
marily implicating frontal brain systems. If true, such
cognitive deficits in euthymic patients might help to
characterize different subtypes of depression and can
give information about prognosis.
A number of studies that examined cognitive func-
tioning in MDD patients following recovery from
* Address for correspondence : Dr E. Bora, Melbourne
Neuropsychiatry Centre, Alan Gilbert Building NNF level 3, 161 Barry
Street, Carlton South, VIC 3053, Australia.
(Email : boremre@gmail.com)
Psychological Medicine, Page 1 of 10. f Cambridge University Press 2012
doi:10.1017/S0033291712002085
REVIEW ARTICLE
acute episodes provide inconsistent findings (Clark
et al. 2005a; Paelecke-Habermann et al. 2005; Wang
et al. 2006; Delaloye et al. 2010). Thus, not all studies
report cognitive impairments and in studies examin-
ing cognition, it is not clear what cognitive domains
are most impaired in euthymic patients. A meta-ana-
lytic review of the existing literature is required to
identify the most consistent cognitive features of eu-
thymic MDD patients and the relationship of putative
cognitive deficits with relevant clinical factors. Our
aim was to conduct a systematic review and meta-
analysis of cognitive deficits in studies of euthymic
MDD patients compared with healthy controls. We
also set out to examine the influence of relevant clini-
cal variables, such as illness relapse (i.e. number of
episodes) and age of illness onset (i.e. early versus late
onset) on cognitive performance.
Method
Our meta-analysis was conducted according to the
Preferred Reporting Items for Systematic Reviews and
Meta-Analyses (PRISMA) guidelines (Moher et al.
2009). Potential articles were identified by a compre-
hensive literature search in PubMed, Scopus and
PsycINFO during the period from January 1980 to
December 2011. The following keywords were used:
‘major depression’; ‘major depressive disorder’;
‘cognit*’; ‘ neuropsych* ’ ; ‘attention’; ‘memory’; and
‘executive ’. The reference lists of identified published
studies were also cross-checked for additional studies.
Inclusion criteria for studies were that they : (1) in-
cluded neuropsychological data pertaining to a
euthymic adult (age >17 years) MDD patient group
and a healthy control group; (2) reported sufficient
data to estimate effect sizes (Cohen’s d); and (3) used
Diagnostic and Statistical Manual of Mental Disorders
(DSM) or International Classification of Diseases (ICD)
criteria to diagnose MDD.
Studies examining MDD patients with co-morbid
physical illness were excluded. When results from the
same study population were reported in more than one
study, only the study with larger samples was included.
The flow chart (see online Supplementary Fig. S1) sum-
marizes the study inclusion process. Definitions of eu-
thymia varied between studies, with some of them
relying solely on cut-off scores on depression scales
while others required a minimum temporal duration
(e.g. 2 weeks to 6 months) for clinical remission
(Table 1). For the purposes of this study, we also define a
‘stricteuthymia’ category (7 <HAMD or 10 <MADRS,
and being remitted for at least 2 months).
Task-specific meta-analyses were conducted when
at least five independent studies reported on a given
task (e.g. Stroop task). In addition to task-specific
analyses, we grouped individual tasks into broader
cognitive domains of ‘executive function’, ‘working
memory’, ‘ attention ’, ‘processing speed’, ‘ semantic
fluency’, ‘verbal memory ’ and ‘ visual memory’. This
second step was undertaken because there were not
sufficient studies to perform meta-analyses for all in-
dividual tasks (see online Supplementary Table S1).
Cognitive domain scores were calculated by averaging
reported effect sizes for the individual tasks listed
under each domain. A separate ‘ planning’ score was
estimated within the ‘executive function ’ domain, as
planning was examined in a considerable number
of studies (Table 2). We also estimated a composite
measure of ‘ global cognition’ by averaging the effect
sizes across each of the cognitive domains.
Statistical analysis
Meta-analyses were performed using MIX software
version 1.7 on a Windows platform (Bax et al. 2006).
For each cognitive task, an effect size and standard
error were estimated. For each study, effect sizes
were calculated as the mean difference between task
performance scores for MDD patients and healthy
subjects divided by the pooled standard deviation.
Effect sizes were weighted using the inverse vari-
ance method. We used a random-effects model
(DerSimonian–Laird estimate) because the distri-
butions of effect sizes were heterogeneous for the
number of variables. The Q test was used to measure
the heterogeneity of the distribution of effect sizes.
When the Q test was significant ‘ I
2
’ – a measure of the
degree of inconsistency in the studies’ results – was
used to quantify heterogeneity (Higgins & Thompson,
2002). I
2
estimates the percentage of total variation
across studies that is due to heterogeneity rather than
chance. I
2
values between 0 and 0.25 suggest small
magnitudes of heterogeneity, while I
2
values in the
range 0.25 to 0.50 suggest medium magnitudes and
those >0.50 indicate large degrees of heterogeneity.
Publication bias was assessed by Egger’s test.
We also calculated homogeneity statistics using Q
bet
to test for differences between late-onset (LOD) and
earlier-onset adult depression (EOD). The LOD group
comprised elderly subjects whose age of illness onse
was in later life (onset after 50–65 years, depending
on the study) and the EOD group was operationalized
to include patients who had their first episode
between the ages of 18 years to somewhere between 50
and 65 years. In some studies, samples of both EOD
and LOD patients were reported. Where data were
provided for both groups, these samples were analysed
separately. For studies that reported both EOD and
LOD in elderly patients without providing separate
data for each group, the study was classified as LOD.
2 E. Bora et al.
Meta-regression analyses were used to estimate the
impact of demographic (age, gender) and clinical
(number of episodes, age at illness onset, duration
of illness, residual depressive symptoms, based on
Hamilton Depression Rating Scale) variables on
between-group differences. These meta-analyses were
conducted both in the whole sample and in EOD and
LOD samples seperately. Meta-regression analyses
(weighted generalized least squares regressions)
were conducted using SPSS version 11.0 (SPSS Inc.,
USA). Meta-regression analyses performed with a
random-effects model were conducted using the re-
stricted-information maximum likelihood method
with significance level set at p<0.05.
Results
A total of 27 studies (30 samples) comparing 895
(60.7% female) patients with MDD and 993 (60.1 %
female) healthy controls were included in the final
meta-analysis (Table 1). Of these samples, 13 included
unipolar patients, while the remaining 17 samples
included patients with a mixture of unipolar and
single-episode patients. There were no significant dif-
ferences in age between the groups [d=0.0, 95% con-
fidence interval (CI) x0.17 to 0.17, Z=0.02, p=0.98].
Global cognition
Our composite measure of global cognition was
significantly different between euthymic MDD
patients compared with healthy controls (d=0.47),
with patients having lower scores in global cognition
(Table 2).
There was no evidence for publication bias and
the distribution of effect sizes was very homogeneous
(I
2
=0). When repeating analyses on the basis of more
stringent criteria for remission (cut-off score and at
least 2 months’ duration), the magnitude of impair-
ment remained similiar (d=0.50).
Cognitive domains
Healthy controls significantly outperformed euthymic
MDD patients in all cognitive domains (d range
0.39–0.59) (Table 2). Task-specific analyses indicated
that healthy controls performed significantly better
than MDD patients in Stroop interference ( d=0.74),
Trail-Making Test part A (d=0.39), Trail-Making Test
part B (d=0.48), digit span backwards (d=0.41), list
learning (d=0.42), list recall (d=0.39), and animal
naming (d=0.57), but not in phonetic fluency,
Wisconson Card Sorting Test (WCST) perseveration,
digit span forwards and list recognition.
There was no evidence of publication bias in any of
the cognitive domains or individual tasks. The dis-
tribution of effect sizes was heterogeneous except
the attention domain and three of the individual tasks
(Stroop interference, digit backwards, WCST per-
severation). However, the magnitudes of this hetero-
geneoity were quite small (range I
2
=0 to 0.22) for all
measures.
LOD v. controls
Compared with the whole-sample analyses, specific
meta-analyses in LOD patients identified more
severe cognitive impairment for global cognition
(d=0.64) and for most cognitive domains (range of
d=0.42–1.10), with the largest effect size occuring in
the domain of verbal memory (Table 2). It was not
possible to conduct meta-analyses for the attention
and semantic fluency domains due to a lack of suf-
ficient studies in LOD patients. Unlike the whole-
sample analyses, the distribution of effect sizes was
homogeneous across all domains in LOD patients,
apart from the domain of visual memory. There was
no evidence of publication bias. In the LOD samples in
which subjects had a mean age of onset after 60 years,
cognitive deficits tended to be even more severe for
global cognition (d=0.77, 95% CI=0.36–1.19, Z =3.6,
p<0.001) and verbal memory (d=1.20, 95% CI =0.77–
1.62, Z=5.5, p<0.001).
EOD v. controls
For most cognitive domains, the magnitude of cogni-
tive deficits observed in EOD samples was notably
smaller (range d=0.21–0.54). When analyses were
limited to unipolar patients, the magnititude of ob-
served effects (d=0.30–0.49) was very similar to that of
the full EOD sample. For specific tasks, EOD patients
were most prominently impaired in Stroop inter-
ference (d=0.82). Consistent with the whole-sample
analyses, there was significant heterogeneity of
the distribution of effect sizes for most cognitive
measures, but the magnitude of such heterogeneity
was modest (range I
2
=0–0.29).
EOD v. LOD
Cognitive deficits in LOD patients were significantly
more severe than those in EOD patients in terms of
processing speed (Q
bet
=7.4, p<0.01) and verbal mem-
ory (Q
bet
=30.4, p<0.001) (see online Supplementary
Figs S2–S5). There were also trend level differences for
global cognition (Q
bet
=3.72, p=0.05) and executive
function (Q
bet
=3.42, p=0.06). The between-group
differences for executive functions were driven by
Cognition in MDD 3
Table 1. Characteristics of the studies included in the meta-analysis
n (Female)
a
Characteristics Euthymia Cognitive variables Medications
b
Baba et al. (2010) HAMD <7 BADS 20/20 on AD
EOD 10 (3)/19 (14) Age=46.3 years EOD (mean
age of onset=39 years)
LOD 10 (6)/10 (4) Age=69.2 years LOD (mean
age of onset=63 years)
Beats et al. (1996) 19 (10)/15 (9) Age=73.6 years LOD (Mix) MADRS < 10 CANTAB, letter fluency, category fluency 16/19 on medication
Behnken et al. (2010) 30 (17)/30 (17) Age=34.3 years EOD HAMD <8 Mean=3.7 RCFT 29/30 on medication Mostly on AD,
15/30 on AP
Bhalla et al. (2006) 56 (41)/41 (24) Age=71.8 years LOD (Mix) HAMD <10
3 consecutive weeks
Digit symbol, TMT-A and -B, Executive
interview, WCST, CVLT, RCFT, logical memory
Most on AD
Bhardwaj et al . (2010) 20 (2)/20 (3) Age=34.3 years EOD HAMD <8 o2 months Digit symbol, WCST, digit span On medication, no details
Biringer et al. (2007) 17/50 EOD HAMD <8 Verbal and visual memory Most on AD
Clark et al. (2005a,b) 15 (11)/47 (24) Age=45.2 years EOD HAMD <9 CPT, CVLT, IDED shift task 6/15 on AD
Delaloye et al. (2010) EOD 30 (24) LOD
11 (7) HC 30 (22)
Age EOD=65.0 years
Age LOD=75.8 years LOD
cut-off is 60 years
5 <GDS CERAD word list, Stroop interference, TMT,
reading span, LNS, reaction time
15/30 EOD on AD 8/11 LOD on AD
Gallassi et al. (2006) 33 (25)/15 (9) Age=66.7 years LOD (Mix) HAMD <7 or 11 At least
2 months
Logical memory, digit span, visual reproduction,
paired associate learning
On fluoxetine or reboxetine
Herrera-Guzma
´
n
et al. (2010)
73 (0)/37 (0) EOD HAMD <6 RAVLT, CANTAB On SNRI or SSRI
SSRI Mean=0.62
SNRI Mean=0.86
Hou et al. (2012) 14 (0)/19 (0) Age=68.2 years LOD
(onset >60 years)
Euthymic over 6 months TMT-A and -B, digit symbol, digit span, list
learning-delayed recall
>3 months medication free
Huang (2009) 13 (9)/13 (7) EOD Age=37.2 years HAMD <7 WMS-revised, WCST, CPT All on SSRI
Jaracz et al. (2002) 21 (21)/17 (17) EOD Age=40.3 years HAMD <7, o6 months WCST, letter and category fluency
Kaneda (2009) 54 (35)/54 (35) EOD Age=37.7 years HAMD <10 In 32, HAMD
<7 Over 3 months
Digit sequencing 28/32 on AD
Li et al. (2010) 19 (13)/25 (19) EOD Age=42.6 years HAMD <7 o2 weeks Tests of attentional performance, WCST,
facial memory, word list
SSRI, SNRI or bupropion
Nakano et al. (2008) HAMD <7 WCST, Stroop interference, letter fluency All on AD
Elderly 24 (18)/25 (22) Age=68.9 years LOD
Mean onset=63 years
Adult 55 (23)/60 (48) EOD Age=45.1 years
Neu et al. (2001) 27 (19)/30 (18) EOD Age=53.4 years HAMD <7 Over
6 months
RAVLT, TMT-A, category fluency,
WMS visual memory
Most on AD, not clear
O’Brien et al. (2004) 26 (0)/40 (30) LOD (Mix) MADRS <8 Letter fluency, CPT, digit span, RAVLT,
Rey design learning, CANTAB
Most on AD, not clear
Palecke-Habermann
et al. (2004)
40 (0)/20 (0) Mild
and severe groups
EOD Age=44.4 and 48.2
years
MADRS <12 Over
3 months
BADS, Stroop interference, continuous
concentration test
26/40 on medication
Pedersen et al. (2009) 20 (10)/20 (10) EOD Age=36.2 years HAMD <8 Mean=3.9 Time test of selective attention, AVLT All on AD, 12/20 on low-dose AP
4 E. Bora et al.
speed-dependent tasks (Trail-Making Test, part B:
Q
bet
=5.2, p=0.03) but not in planning.
Meta-regression analyses
In meta-regression analyses, the number of episodes,
duration of illness, current (i.e. residual) depressive
symptoms, age and gender variables had no statisti-
cally significant influence on the nature of cognitive
deficits observed in euthymic MDD patients when
conducted in separate EOD and LOD. In the whole
sample, older age of onset was associated with more
severe verbal memory deficits (B=0.32,
S.E.=0.09,
Z=3.77, p=0.0002).
Discussion
Our meta-analytical review has demonstrated overall
that cognitive deficits are evident in euthymic MDD
patients. A later age of illness onset was associated
with a more severe pattern of impairment. Cognitive
deficits were evident across all of the domains exam-
ined, albeit with small to medium effect sizes (d=0.39–
0.59). The average magnitude (Cohen’s d) of cognitive
dysfunction in euthymic MDD patients was 0.47, in-
dicating nearly 70% overlap of distributions of cogni-
tive performances of MDD patients and healthy
controls.
Cognitive dysfunction in euthymic MDD appears to
be severe and common in certain subtypes of patients.
Our findings provide strong evidence for pronounced
cognitive deficits in remitted patients who had their
first episode of illness late in life (d=0.64, 60 % overlap
with controls), with the distribution of effect sizes
being strikingly homogeneous in this population.
This finding extends previous reports of cognitive
differences between late-onset and early-onset MDD
patients (Herrmann et al. 2007). These pronounced
deficits might be related to progressive abnormalities
in cortico-striatal-pallidal-thalamic circuits that have
been identified in MDD (Rogers et al. 1998; Marchand
& Yurgelun-Todd, 2010; Bora et al. 2012b) as well as
vascular changes in white matter (Herrmann et al.
2008). Verbal memory problems might be related to a
risk of future neurodegenerative disorders in some
of these patients (Yeh et al. 2011 ; Vilalta-Franch et al.
2012). The most pronounced deficits in the LOD
patients were in verbal memory (d=1.10, 41% over-
lap), processing speed (d=0.75, 55% overlap) and
some aspects of executive functions, including the
Trail-Making Test part B (d=0.88, 49% overlap).
These deficits statistically distinguished late- from
early-onset patients. Positive correlation between
verbal memory deficits and age of onset in meta-
regression analyses also supported these findings.
Portella et al. (2003) 21 (0)/15 (9) LOD Age about 70 years
Onset >50 years
HAMD <9 Digit span, logical memory, WMS visual
memory, digit symbol, TMT-A
Patients on AD but stopped to take
10 days before test day
Preiss et al. (2009) 97 (51)/97 (51) Age=46.3 years EOD MADRS <12 Over
2 months
AVLT, TMT-A and -B 48/97 SSRI, 20/97 TCA, 17/97
mirtazapine and other AD
Trichard et al. (1995) 6/14 EOD MADRS 1 (
S.D.=1) Stroop interference, letter and category
fluency, cancellation test
On AD
Weiland-Fiedler
et al. (2004)
28 (18)/23 (11) Age=37.7 years EOD MADRS <6 o3 months CANTAB Unmedicated Past use of
medications
Xu et al. (2012) 100 (0)/202 (0) EOD HAMD <8 TMT-A and -B, digit span, WCST, Hanoi
tower, WAIS visual reproduction
100/100 on AD
Yuan et al. (2008) 18 (10)/14 (7) Age=67.3 years LOD
Onset >60 years
HAMD <8 o3 months RAVLT, TMT-A and -B, digit span Unmedicated Past use of
medications
HAMD, Hamilton Depression Rating Scale ; BADS, Behavioral Assessment of Dysexecutive Syndrome ; AD, antidepressant ; EOD, early-onset depression ; LOD, late-onset depression ; Mix, mixed ;
MADRS, Montgomery-Asberg Depression Rating Scale ; CANTAB, Cambridge Neuropsychological Test Automated Battery ; AP, antipsychotic ; TMT, Trail-Making Test ; WCST, Wisconson Card
Sorting Test ; CVLT, California Verbal Learning Test ; RCFT, Rey–Osterrieth Complex Figure Test ; CPT, Continuous Performance Test ; IDED, intra-dimensional/extra-dimensional; HC, healthy
controls ; GDS, Geriatric Depression Scale ; CERAD, Consortium to Establish a Registry for Alzheimer’s Disease ; LNS, Letter-Number Sequencing ; SNRI, Serotonin-norepinephrine reuptake
inhibitors ; SSRI, selective serotonin reuptake inhibitors ; RAVLT, Rey Auditory Verbal Learning Test ; WMS, Wechsler Memory Scale ; AVLT, Auditory Verbal Learning Test, TCA, tricyclic anti-
depressant ;
S.D., standard deviation ; WAIS, Wechsler Adult Intelligence Scale.
a
Depressed/control participants unless otherwise specified.
b
On medication/depressed participants.
Cognition in MDD 5
