CLINICAL RESEARCH
European Heart Journal (2012) 33, 1769–1776
doi:10.1093/eurheartj/ehr467
Heart failure/cardiomyopathy
Cognitive and brain changes associated with
ischaemic heart disease and heart failure
Osvaldo P. Almeida1,2,3*, Griselda J. Garrido 1,2, Christopher Beer 2,4,5,
Nicola T. Lautenschlager1,2,6, Leonard Arnolda 7, and Leon Flicker 2,4,5
Received 19 September 2011; revised 25 October 2011; accepted 29 November 2011; online publish-ahead-of-print 31 January 2012
See page 1721 for the editorial comment on this article (doi:10.1093/eurheartj/ehs128)
Aims
It is unclear whether the cognitive dysfunction associated with heart failure (HF) is due to HF or comorbid conditions
such as ischaemic heart disease (IHD). This study aimed to determine whether, compared with controls with and
without IHD, adults with systolic HF show evidence of cognitive impairment and cerebral grey matter (GM) loss.
.....................................................................................................................................................................................
Methods
Cross-sectional study of 35 participants with HF, 56 with IHD, and 64 controls without either HF or IHD. Subjects
and results
were older than 45 years and free of overt cognitive impairment. We acquired magnetic resonance images and used
SPM8 to determine regional differences in cerebral GM volume. Participants with HF had lower scores than controls
without IHD on immediate memory, long delay recall and digit coding, whereas those with IHD had lower long delay
recall scores than controls without IHD. Compared with controls without IHD, participants with HF showed evidence of GM loss in the left cingulate, the right inferior frontal gyrus, the left middle and superior frontal gyri, the
right middle temporal lobe, the right and left anterior cingulate, the right middle frontal gyrus, the inferior and
pre-central frontal gyri, the right caudate, and occipital-parietal regions involving the left precuneus. The loss of
GM followed a similar, less extensive, pattern when we compared participants with HF and IHD.
.....................................................................................................................................................................................
Conclusion
Adults with HF have worse immediate and long-term memory and psychomotor speed than controls without IHD.
Heart failure is associated with changes in brain regions that are important for demanding cognitive and emotional
processing.
----------------------------------------------------------------------------------------------------------------------------------------------------------Keywords
Heart failure † Ischemic heart disease † Coronary disease † Memory † Cognition † Cognitive † Function †
Magnetic resonance imaging † Brain
Introduction
Heart failure (HF) is a common consequence of most diseases of
the heart, and nearly 9 in every 10 cases are associated with the
presence of ischaemic heart disease (IHD) or hypertension.1
Current estimates suggest that about 3% of adults have HF and
its prevalence in the community is expected to rise as the population ages.2 Heart failure is a leading cause of mortality worldwide,3
and survivors often experience declining physical and mental
health.4 Depression and cognitive impairment are the most frequent mental health problems among people with HF.5,6
Systematic reviews of observational studies found that people
with systolic HF perform less well than controls on measures of
general mental ability, attention, and memory,7,8 although data
on this topic remain sparse and deficits may be due to cooccurring conditions, such as IHD or cerebrovascular disease.6,9
Some investigators have suggested that cognitive deficits in HF
are a consequence of reduced systolic output,10 – 12 or, alternatively, that they reflect a generalized pattern of decline in functional
capacity.13 Others proposed that these difficulties arise because
of reduced cerebral perfusion or ischaemic damage to the
brain.14,15
* Corresponding author. Tel: +61 8 92242855, Fax: +61 8 92248009, Email: osvaldo.almeida@uwa.edu.au
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2012. For permissions please email: journals.permissions@oup.com
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1
School of Psychiatry and Clinical Neurosciences, University of Western Australia, Crawley, Perth, Australia; 2Western Australian Centre for Health and Ageing, Centre for Medical
Research, University of Western Australia, 35 Stirling Highway, Crawley, Perth WA 6009, Australia; 3Department of Psychiatry, Royal Perth Hospital, Perth, Australia; 4School
of Medicine and Pharmacology, University of Western Australia, Perth, Australia; 5Department of Geriatric Medicine, Royal Perth Hospital, Perth, Australia; 6Academic
Unit for Psychiatry of Old Age, St Vincent’s Health, Department of Psychiatry, University of Melbourne, Melbourne, Australia; and 7Academic Unit of Internal Medicine,
Australian National University Medical School, Australia
1770
Methods
Study design
We completed a cross-sectional study of adults with HF, IHD, and
controls. We collected endpoints of interest between May 2006 and
March 2009 in Perth, Western Australia.
Participants
Participants were community volunteers who responded to advertisements about the study in the local media, or were referred for assessment by their primary care physicians or hospital consultants. The
Ethics Committees of the Royal Perth, Fremantle and Sir Charles
Gairdner Hospitals approved the study protocol and participants
offered written informed consent. The Declaration of Helsinki for
Human Rights guided all activities of this study.
We excluded from participation people with past history of stroke
or cardiac arrest, hearing or visual impairment, Mini-Mental State
Examination (MMSE) score , 24,21 or who showed evidence of clinically significant depressive or anxiety symptoms [Hospital Anxiety and
Depression Scale (HADS) sub-scores . 10].22 We also excluded
volunteers younger than 45 years of age, and those who were not
fluent in written/spoken English, who reported recent myocardial infarction (≤30 days), who were unwilling/unable to undergo a MRI
scan of the head, or who showed imaging evidence of brain tumours
or cortical strokes.
Participants with established diagnosis of HF before enrolment into
the study showed evidence of left ventricular dysfunction at the time of
recruitment (ejection fraction—EF , 0.4) and clinical symptoms consistent with the diagnosis of HF for at least 6 months, such as exertion
dyspnoea, orthopnoea, fatigue and weakness, dry cough, dizzy spells or
palpitations, or physical signs of systemic oedema (CHF group).23 We
excluded adults with New York Heart Association Functional Classification (NYHA) class IV24 because of marked disability and high shortterm mortality.25 Hence, our HF participants had treated and stable
illness.
Controls with IHD had documented clinical and biochemical evidence of past myocardial infarction (i.e. elevated CK, CKMB, troponin
T, or troponin I), normal left ventricular function (EF . 0.6), and no
clinical symptoms of HF. The procedures that we used to obtain
these data have good sensitivity and specificity.26 Controls without
overt IHD denied symptoms or history suggestive of angina, myocardial infarction, and HF, and had normal left ventricular function
(EF . 0.6) (healthy controls).
The participants of this study did not overlap with those who took
part in the pilot project that we have previously reported.13,17
Outcome: cognitive function
The Cambridge Cognitive Examination of the Elderly Revised
(CAMCOG) was the primary outcome measure of this study.27 The
CAMCOG is a valid and reliable brief neuropsychological battery
that assesses various aspects of cognitive functioning, including orientation, language, memory, attention and concentration, praxis, perception, calculation, and executive functions.28 The assessment produces a
total summary score that can range from 0 to 105, with higher scores
indicating better performance.27,29 Normative data show that the
mean score for people of similar age and education is about 94
points27 with a standard deviation of 9.29 Other cognitive outcomes
included immediate, and short- and long-delayed recall (memory) as
measured by the California Verbal Learning Test (CVLT),30,31 and
the Digit Copy and Coding subtests of the Wechsler Adult Intelligence
Scale.32 The latter is a measure of psychomotor speed and attention.
Normative data for the CVLT show that the expected standard deviation for immediate, short-, and long-delayed recall is about 11.5, 3.5,
and 3.0 points, respectively.31
Outcome: cerebral grey matter volume
We used a 1.5 Tesla Siemensw Symphony MRI scanner [TR: 2830 ms,
TE: 4.48, flip angle: 15, matrix size: 256 × 256 × 172, voxel size:
(0.9 mm)3] to acquire DICOM data, which were converted to NIfTI
file format using MRIcron (http://www.mricron.com). We used Statistical Parametric Mapping version 8 (SPM8, release 4010) to process
the data on Matlabw 2010b (version 7.11.0.584) and Windows 7
64-bits. A detailed description of the methods used to analyse the
images appears in the Supplementalary Material.
Other measures
We measured symptoms of depression and anxiety with the HADS.22
Participants provided information about their age, gender, marital
status, and schooling (highest degree achieved), as well as about
their clinical history of hypertension, diabetes, and dyslipidaemia. We
assessed pre-morbid intelligence quotient (IQ) with the Cambridge
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Woo et al.16 examined magnetic resonance images (MRI) of 9
people with HF and 27 controls. They found that participants
with HF showed evidence of reduced cerebral grey matter (GM)
volume in the insula, basal ganglia, cingulate gyrus, parahippocampal
gyrus, dorsal midbrain, ventral and superior frontal cortex, and bilateral parietal and lateral parietal –occipital cortex,16 although interpretation of these results is hampered by the small sample size,
non-availability of concurrent cognitive measures, and lack of a
control group with cardiovascular disease but no HF. The latter
would have allowed the investigators to clarify if the brain
changes that they observed were specific to HF.17
The question of whether HF is causally related to structural
brain changes and cognitive decline is important because current
approaches to the management of HF require the active participation of patients, who are expected to adhere to a complex treatment regime.18 The concern is that patients may have trouble
complying with medical advice, which would lead to suboptimal
management, more frequent health complications, and greater
use of health services.19 Moreover, a better understanding of the
association between HF and cognitive impairment may enhance
our appreciation of the mechanisms that link cardiovascular diseases to cognitive decline in later life.20
We designed the present study to determine whether adults
with systolic HF show evidence of: (i) cognitive impairment compared with controls with and without established history of IHD,
and (ii) cerebral GM loss compared with controls with and
without established history of IHD. We hypothesised that participants with HF would attain lower scores than controls with and
without IHD on tests of general intellectual function, memory,
and psychomotor speed. We also expected participants with HF
to show evidence of GM loss compared with controls with and
without IHD, particularly in brain regions involved in the regulation
of psychomotor speed, attention, and memory. Finally, we
hypothesized that participants with IHD would show no evidence
of cognitive impairment or GM loss compared with cardiologically
healthy controls.
O.P. Almeida et al.
1771
Cognitive and brain changes associated with IHD and heart failure
n ¼ 31) and 99.9 (standard deviation ¼ 2.4, n ¼ 24).13 That study
did not include a group with IHD, which we expected would have a
cognitive performance that would fall between patients with HF and
controls (mean of about 97, standard deviation of about 5). Such a difference could be declared as statistically significant with 53 participants in each group (80% power). As the recruitment of 53 eligible
people with HF proved difficult within the timeframe of the project,
we inflated the number of participants with IHD and controls to
ensure that the study was sufficiently powered to declare such differences as significant (estimated power of at least 82%).
Procedures for the collection
of study measures
Results
Participants recorded demographic information at the initial assessment, which also included cardiovascular history and testing with the
MMSE. Consenting participants were then referred for an echocardiographic examination to determine their EF which we used, together
with clinical history and review of medical notes, to allocate participants to the HF, IHD, and control groups. Participants returned for
the 120 min face-to-face collection of outcomes within 2 weeks of
completion of the echocardiogram. They donated a fasting blood
sample between 8 and 9 am on the day of their cognitive assessment.
These samples were processed immediately after venepuncture to
extract plasma and serum, which were then batched and stored at
808C until assayed. Finally, we acquired the MRI scan images 2 – 8
weeks after the cognitive assessment.
Statistical methods
The data were managed and analysed with Stata version 11.2 (StataCorp, College Station, TX, USA). We used descriptive statistics to
summarize data, cross-tabulation to determine their distribution
according to group membership (Pearson’s chi-square statistic: x 2),
and analysis of variance (one-way analysis of variance or Kruskal –
Wallis test) to compare the distribution of numerical variables. Initially,
we analysed biochemical data as continuous variables, but later investigated their effect on outcomes according to quartiles (highest compared with all others) or, in the case of BNP and tHcy, according to
the clinically established cut points 100 pg/mL and 15 mmol/L.37,38
We used linear regression (regress command) to investigate the differences between IHD and HF participants and controls on the cognitive tests, taking into account the contribution of age, gender,
education, and physical activity. These variables were part of the
best fit explanatory model of cognitive function according to the cardiological group (they were all associated with P-values , 0.1). The selection of variables for the analysis of brain images followed the same
principle. Initially, we investigated the contribution of all measured
factors to total GM and selected the best parsimonious regression
model that included, along with group membership, age, gender, and
high tHcy. We also investigated the association between total GM
volume and ejection fraction and the result on the 6 min walk test
for patients with HF using Pearson correlation. Alpha was set at 5%
and all statistical tests reported are two-tailed.
We used a full 2 × 2 factorial SPM design to model regional GM
volume differences between the study groups, and included age
(lower or greater/equal 70 years), gender, and tHcy grouping as
co-variates. We declared as significant regional differences associated
with a between group difference of at least 100 voxels and
maximum P-value of 0.01.
The results of our pilot study showed that patients with HF and
healthy controls had CAMCOG scores of 93.5 (standard deviation ¼ 6.1,
One hundred and sixty-nine participants consented to complete all
study assessments, but 14 had to be excluded from the analyses
because of unusable brain images (distortions caused by
movement ¼ 9, scan artefacts ¼ 3, brain tumour ¼ 1). The
remaining 155 participants consisted of 64 controls, 56 adults
with IHD, and another 35 with HF. For 24 (68.6%) of the 35
people with HF, there was evidence that IHD was the most
likely cause of their systolic dysfunction. The remainder 11 participants with HF had systolic dysfunction of uncertain aetiology. They
were distributed as follows according to the NYHA Functional
Classification: 5 (14.3%) Class III, 19 (54.3%) Class II, and 11
(31.4%) Class I. Table 1 summarizes their demographic, lifestyle,
clinical, and laboratory characteristics. Adults with HF had lower
scores than IHD and healthy controls on measures of memory
and psychomotor speed, but not on the CAMCOG. We also
found that participants with HF showed a relative loss of total
GM compared with adults with IHD (crude analysis).
We then examined the cognitive scores of participants compared with non-cardiac controls and adjusted the analyses for
the effect of confounding by age, gender, education, smoking, physical activity, and prevalent hypertension. Figure 1 summarizes the
results of these analyses. Participants with IHD and HF had
CAMCOG score 1.8 and 2.8 points lower than non-cardiac controls (P ¼ 0.101 and P ¼ 0.029, respectively). However, people
with HF had significantly lower scores than healthy controls on
measures of immediate recall, long delay recall, and digit code.
Adults in the IHD group also had lower long delay recall scores
than controls without IHD (P ¼ 0.047). There were no other significant differences between groups. Of note, all non-cognitive
variables listed in Table 1 were included in the regression models
and we used a stepwise approach to remove one variable at a
time until all remaining variables were associated with at least a
10% change in the adjusted R-squared and had a P-value , 0.1.
In the case of the CAMCOG score, the variables retained in the
model were age, gender, education, physical activity, and use of
statins.
We investigated the association between measured factors and
total brain GM (Figure 2) and included the relevant factors in the
analysis of regional differences in the distribution of GM among
participations with HF, IHD, and controls without IHD (2 × 2 pairwise comparisons). Figure 3 illustrates the results of these analyses.
We also found that among participants with HF, total GM volume
was not associated with performance on the 6 min walk test
(Pearson r ¼ 0.11, P ¼ 0.537) or ejection fraction (Pearson
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Contextual Reading Test,33 and calculated the left ventricular EF based
on the results of an echocardiogram (Perth Echo Services). Participants
completed the 6 Min walk test.34
We used standard commercial biochemical tests to measure serum
B-type natriuretic peptide (BNP), tumour necrosis factor alpha
(TNF-a), cortisol, interleukin-6 (IL-6), and total plasma homocysteine
(tHcy). B-type natriuretic peptide concentrations ≥100 pg/mL indicate
the presence of myocardial dysfunction and HF.35 Tumour necrosis
factor alpha, IL-6, and cortisol indicate the presence of an inflammatory
process and, together with high tHcy, have been associated with neuronal loss.36
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O.P. Almeida et al.
Table 1 Demographic, lifestyle, clinical, and cognitive characteristics of adults without IHD or HF (controls), with IHD,
and with HF who completed the imaging substudy
Controls (n 5 64)
IHD (n 5 56)
HF (n 5 35)
P-value
...............................................................................................................................................................................
Demographics
Age, mean years + SD
68.7 + 11.3
66.7 + 9.5
69.2 + 9.0
0.437
Male gender, n (%)
22 (34.4)
40 (71.4)
27 (77.1)
,0.001
Australia born, n (%)
Married, n (%)
37 (57.8)
50 (78.1)
36 (64.3)
42 (75.0)
18 (52.9)
24 (70.6)
0.549
0.710
12.3 + 2.9
12.4 + 3.6
12.1 + 3.4
0.909
33 (51.6)
5 (7.8)
31 (55.4)
2 (3.6)
24 (68.6)
2 (5.7)
0.254
0.612
Education, mean years + SD
...............................................................................................................................................................................
Lifestyle
Risk alcohol use, n (%)
14 (21.9)
21 (37.0)
13 (37.1)
0.121
Physically active, n (%)
BMI ≥ 25 kg/m2, n (%)
13 (20.3)
41 (64.1)
20 (35.7)
36 (64.3)
6 (17.1)
23 (65.7)
0.070
0.986
,0.001
...............................................................................................................................................................................
Clinical measures
Use of a beta-blocker, n (%)
5 (7.8)
6 (10.7)
15 (42.9)
7 (10.9)
17 (30.4)
15 (42.9)
68.1 + 5.2
465.6 + 160.1
68.4 + 6.0
465.3 + 150.1
30.4 + 7.8
415.5 + 154.8
Hypertension, n (%)
22 (34.4)
29 (51.8)
22 (62.9)
0.017
Diabetes, n (%)
Dyslipidaemia, n (%)
8 (12.5)
25 (39.1)
12 (21.4)
42 (75.0)
8 (22.9)
19 (54.3)
0.315
,0.001
Use of a statin, n (%)
Ejection fraction, mean + SD
Six-minute walk, mean metres + SDa
0.001
,0.001
0.266
HADS-D, median score (IQR)
2 (1–3)
2 (0– 4)
1 (0–3)
0.267
HADS-A, median score (IQR)
3 (1–5)
3 (1– 6)
1 (0–2)
0.030
59.4 + 70.5
1.3 + 1.2
85.5 + 87.2
1.1 + 0.5
233.8 + 194.5
1.8 + 1.3
320.4 + 94.7
338.8 + 93.0
366.5 + 97.3
0.076
2.7 + 4.8
12.4 + 3.5
2.1 + 1.2
13.4 + 4.4
5.0 + 6.8
15.6 + 5.0
0.011
0.003
113.8 + 5.5
113.3 + 6.5
111.5 + 5.9
0.188
...............................................................................................................................................................................
Biochemistry
BNP, mean pg/mL + SDb
TNF-a, mean pg/mL + SDb
Cortisol, mean nmol/L + SDb
IL-6, mean pg/mL + SDb
tHcy, mean mmol/L + SDb
,0.001
0.014
...............................................................................................................................................................................
Cognitive measures
IQ, mean score + SD
CAMCOG, mean score + SD
CVLT immediate recall, mean + SD
CVLT short delay, mean + SD
94.7 + 5.3
48.6 + 12.2
93.8 + 5.9
44.2 + 9.1
91.8 + 7.2
40.1 + 10.5
0.084
,0.001
9.8 + 3.8
8.7 + 2.7
7.9 + 3.2
0.017
CVLT long delay, mean + SD
CVLT long cued recall, mean + SD
10.4 + 3.8
11.1 + 3.3
8.9 + 3.0
9.6 + 2.8
8.4 + 3.2
9.1 + 3.6
0.008
0.005
Digit coding, mean score + SDc
57.7 + 16.0
52.6 + 14.5
48.3 + 14.5
0.012
Digit copy, mean score + SDc
94.0 + 24.7
87.5 + 22.4
84.8 + 22.2
0.130
549.6 + 51.4
568.4 + 50.1
539.6 + 50.5
0.022
...............................................................................................................................................................................
Neuroimaging
Total grey matter, mean mm3 + SD
a
Two people with HF did not complete this task.
Data missing for four controls and one person with IHD.
One person with HF did not complete this task.
IHD, ischaemic heart disease; HF, heart failure; IQ, intelligence quotient; HADS-D, Hospital Anxiety and Depression Scale—depression subscale; HADS-A, Hospital Anxiety and
Depression Scale—anxiety subscale; IQR, interquartile range; BNP, B-type natriuretic peptide; TNF-a, tumour necrosis factor alpha; IL-6, interleukin-6; CAMCOG, Cambridge
Cognitive Examination of the Elderly; CVLT, California Verbal Learning Test.
b
c
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Ever smoker, n (%)
Current smoker, n (%)
Cognitive and brain changes associated with IHD and heart failure
1773
trols (reference zero line, n ¼ 64) on cognitive tests. The whiskers indicate the standard error of the mean difference compared with controls.
CAMCOG, Cambridge Cognitive Examination of the Elderly; CVLT, California verbal learning test; immediate, total immediate recall; short
delay, short-delayed recall; long delay, long-delayed recall. The ‘#’ indicates differences associated with P , 0.05 compared with controls.
All analyses were adjusted for measured confounding factors (best fit regression models).
Figure 2 Total brain grey matter measures of participants according to various exposures. The apex of the bars represent the mean and the
whiskers the standard error of the mean. The underscore lines indicate statistically significant difference (P , 0.05) in total cerebral grey matter
between groups after adjustment for multiple comparisons. Controls: adults without IHD or HF, IHD, ischaemic heart disease; HF, heart failure;
BMI, body mass index; BNP, B-type natriuretic peptide; TNF-a, tumour necrosis factor alpha; IL-6, interleukin 6; tHcy, total plasma
homocysteine.
r ¼ 20.25, P ¼ 0.155). The use of statins or beta-blockers was not
associated with the distribution of GM volume across the three
study groups.
Compared with healthy controls, the brain regions of participants with HF that showed the greatest loss of GM included the
left cingulate, the right inferior frontal gyrus, the left middle and
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Figure 1 Mean score of participants with ischaemic heart disease (light blue, n ¼ 56) and heart failure (salmon, n ¼ 35) compared with con-
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O.P. Almeida et al.
heart disease or heart failure (red) and participants with ischaemic heart disease but no heart failure (blue). The green colour denotes regions in
which people with ischaemic heart disease had lower density of grey matter than controls. The analyses were adjusted for age group, gender,
and high total plasma homocysteine. Detailed results of these analyses appear in Supplementary material online, Table S1A, Supplementary material online, Table S1B, and Supplementary material online, Table S1C.
superior frontal gyri, the right middle temporal lobe, the right and
left anterior cingulate, the right middle frontal gyrus, the inferior
and precentral frontal gyri, the right caudate, and occipital –parietal
regions involving the left precuneus (Figure 3A and Supplementary
material online, Table S1A). Compared with IHD controls, participants with HF showed evidence of loss of GM in the right middle
temporal lobe, the right anterior cingulate and medial frontal lobe,
the left lentiform nucleus and adjacent areas, the right precuneus,
the right thalamus and lentiform nucleus, and other regions
extending from right and left middle and superior frontal cortex
(Figure 3B and Supplementary material online, Table S1B). The relative loss of GM among participants with IHD compared with
healthy controls was much less extensive, but affected overlapping
regions such as the left medial frontal cortex, the left cingulate and
precuneus, the left and right parahippocampal gyri, and the right
and left middle temporal gyri (Figure 3C and Supplementary material online, Table S1C). There were no brain regions in which participants with HF had more GM than controls with or without IHD
(data not shown). Similarly, there were no brain regions in which
participants with IHD had more GM than healthy controls.
Detailed results of the imaging analyses appear in Supplementary
material online, Table S1.
Discussion
The results of this study show that adults with HF have worse immediate and long-term memory and psychomotor speed than
healthy controls. We also found that participants with HF display
a relative loss of cerebral GM in various cortical and subcortical
regions extending to the frontal lobes, anterior cingulate, and
temporal–parietal lobes. Contrary to expectations, our results
showed no evidence of cognitive deficits in people with HF compared with IHD. However, we found a relative loss of regional GM
among participants with HF compared with IHD that was less extensive but had a similar topographic distribution when the former
were compared with healthy controls (which suggests that these
changes may be relatively specific to HF).
Previous studies had already reported that people with HF have
worse cognitive function than healthy controls,6,10 but it was
unclear if those deficits were due to confounding.39 – 44 As far as
we are aware, this is the first study that included an additional
IHD control group that shares common risk factors with HF,
which allowed us to show that the cognitive losses may be a nonspecific consequence of increasing cardiovascular disease burden.
Moreover, our analyses revealed that these subtle deficits (only
around 0.5 SD lower than controls and thus unlikely to be associated with overt clinical impairment) cannot be explained by
impaired left ventricular ejection fraction, prevalent comorbid conditions, or biochemical markers.
The acquisition of structural brain images allowed us to examine
the impact of both HF and IHD on cerebral GM and to show that
people with HF display more widespread and extensive brain
changes than adults with IHD. Another imaging study that investigated cerebral blood flow in 17 people with HF found that the posterior cingulate and precuneus were the brain regions that showed
the greatest reduction in blood flow compared with 18 controls.15
The posterior association cortex plays an important role in the
successful retrieval of memory traces,45 and the precuneus, posterior cingulate, and retrospenial cortex have major bidirectional connections with the medial temporal lobes in primates.46 In addition,
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Figure 3 This figure illustrates the regions in which adults with heart failure had lower density of grey matter than controls without ischaemic
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Cognitive and brain changes associated with IHD and heart failure
Limitations
The study sample consisted of a group of motivated volunteers
with and without IHD or with HF. As people who volunteer to
take part in studies are commonly healthier than nonparticipants,52 healthy participant bias seems likely. This would
have resulted in a bias that minimizes the differences between participants and would have moved our findings towards the null hypothesis. Hence, the deficits and changes that we did find are
probably an underestimation of the differences that exist
between these groups. In addition, our HF sample included only
people with systolic dysfunction, and it is unclear whether these
results can be extended to patients with HF due to non-systolic
dysfunction. We also acknowledge that our study groups were
not perfectly balanced for gender, HADS scores, and clinical measures such as hypertension and dyslipidaemia, although differences
between groups were not marked and the analyses accounted for
possible confounding. Furthermore, the inclusion of relatively
young participants in the study may have contributed to attenuate
the negative consequences of cardiac disease on cognitive function
(which might be more pronounced in older people), although we
found no obvious interaction between age and cardiac illness on
cognitive scores. Another limitation is that, due to imaging artefacts, we did not examine differences in the distribution of GM
in the left temporal lobe. The cross-sectional nature of our data
preclude definitive conclusions as to whether HF, and to a lesser
extent IHD, is causally related to cognitive decline and loss of cerebral GM. Moreover, the assessment of cognitive function was not
blinded to the clinical status of participants, although imaging and
biochemical procedures were. It is possible that such a nonblinding could have biased the results of our structured cognitive
assessments. Finally, we did not record the duration of HF symptoms or of IHD because we were not confident that such information would be accurate and reliable,26 and are, consequently,
unable to comment whether longer illness duration would have
been associated with greater impairment of cognitive function or
GM loss. These questions would have been more adequately
addressed by a longitudinal study.
Conclusion
In summary, our study shows that people with HF experience loss
of GM in brain regions that are relevant to cognitive function and
that compromise performance on cognitive tasks that require
mental effort. Importantly, our results are consistent with the observation that people with HF have trouble adhering to complex
self-care advice,53 and suggest that simpler approaches to selfmanagement may be required. Future studies should aim to
clarify the physiological pathways that link HF to loss of cerebral
GM and cognitive impairment, and longitudinal surveys should determine whether the observed cerebral and cognitive changes are
progressive in nature.
Role of authors
O.P.A., N.T.L., L.A., and L.F. conceived and designed the study, and
obtained funding. O.P.A., N.T.L., L.A., L.F., and C.B. assisted with recruitment and data collection. O.P.A. and G.J.G. analysed the data
and all authors contributed to the interpretation of the results.
O.P.A. drafted the manuscript. All authors reviewed the manuscript critically and approved its submission for publication.
Supplementary material
Supplementary material is available at European Heart Journal
online.
Acknowledgements
The investigators thank participants and research staff for their
generous contribution.
Funding
This project was supported by a competitive project grant from the
National Health and Medical Research Council of Australia
(NHMRC, #403996). The sponsor had no role in the design and
running of the study, analysis of the data, drafting of the manuscript,
and decision to publish.
Conflict of interest: the authors declare that they have no conflict
of interest.
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