Canadian
Psychiatric Association
Association des psychiatres
du Canada
Original Research
Physical Activity as a Predictor of Clinical
Trial Outcomes in Bipolar Depression:
A Subanalysis of a Mitochondrial-Enhancing
Nutraceutical Randomized Controlled Trial
The Canadian Journal of Psychiatry /
La Revue Canadienne de Psychiatrie
1-13
ª The Author(s) 2019
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/0706743719889547
TheCJP.ca | LaRCP.ca
L’activité physique comme prédicteur des résultats d’un essai
clinique en dépression bipolaire : une sous-analyse d’un essai
randomisé contrôlé d’un nutriceutique améliorant les mitochondries
Melanie M. Ashton, BSc, GDip1,2,3, Mohammadreza Mohebbi, PhD4,
Alyna Turner, PhD1,5, Wolfgang Marx, PhD1,6,
Michael Berk, MD, PhD1,3,5,7,8 , Gin S. Malhi, MD9,10,11,
Chee H. Ng, MBBS, MD2, Sue M. Cotton, PhD7,8, Seetal Dodd, PhD1,5,7,
Jerome Sarris, PhD2,12, Malcolm Hopwood, MD13,
Brendon Stubbs, PhD14,15, and Olivia M. Dean, PhD1,3
Abstract
Objectives: Individuals with bipolar disorder (BD) generally engage in low levels of physical activity (PA), and yet few studies
have investigated the relationship between PA and change in BD symptom severity. The aim of this subanalysis of an adjunctive
nutraceutical randomized controlled trial for the treatment of bipolar depression was to explore the relationship between PA,
the active adjunctive treatments (a nutraceutical “mitochondrial cocktail”), and clinical outcomes.
Methods: Participants with bipolar depression were randomized to receive N-acetylcysteine alone, N-acetylcysteine with a
combination of nutraceuticals (chosen for the potential to increase mitochondrial activity), or placebo for 16 weeks. Participants (n ¼ 145) who completed the International Physical Activity Questionnaire–Short Form (IPAQ-SF; measured at
Week 4) were included in this exploratory subanalysis. Assessments of BD symptoms, functioning, and quality of life were
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
IMPACT Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, Victoria, Australia
Professorial Unit, The Melbourne Clinic, Department of Psychiatry, University of Melbourne, Richmond, Victoria, Australia
The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
Biostatistics Unit, Faculty of Health, Deakin University, Geelong, Victoria, Australia
School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia
Department of Rehabilitation, Nutrition and Sport, School of Allied Health, College of Science, Health and Engineering, La Trobe University,
Bundoora, Victoria, Australia
Centre of Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia
Orygen, Parkville, Victoria, Australia
Academic Department of Psychiatry, Northern Sydney Local Health District, St Leonards, New South Wales, Australia
Faculty of Medicine and Health, Department of Psychiatry, Northern Clinical School, University of Sydney, New South Wales, Australia
CADE Clinic, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, New South Wales, Australia
NICM Health Research Institute, Western Sydney University, Westmead, New South Wales, Australia
Professorial Psychiatry Unit, Albert Road Clinic, Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia
Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, United Kingdom
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
Corresponding Author:
Melanie M. Ashton, BSc, GDip, IMPACT Strategic Research Centre, Deakin University, P.O. Box 281, Geelong, Victoria 3220, Australia.
Email: m.ashton@deakin.edu.au
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The Canadian Journal of Psychiatry
completed at monthly visits up until Week 20. Generalised Estimating Equations were used to explore whether IPAQ-SF
scores were a moderator of treatment received on outcomes of the study.
Results: Week-4 PA was not related to changes in Montgomery Åsberg Depression Rating Scale scores across the study until
Week 20. However, participants who engaged in more PA and who received the combination treatment were more likely to
have a reduction in scores on the Bipolar Depression Rating Scale (P ¼ 0.03). However, this was not consistent in all domains
explored using the IPAQ-SF. Participants who engaged in higher levels of PA also experienced greater improvement in social
and occupational functioning and less impairment in functioning due to their psychopathology and improvement in quality of
life at Week 20, irrespective of treatment.
Conclusions: This study provides novel evidence of the association between PA and reduction in BD symptoms in a
nutraceutical clinical trial. However, further research assessing the potential synergistic effects of PA in BD is required.
Abrégé
Objectifs : Les personnes souffrant d’un trouble bipolaire (TB) ne s’adonnent généralement qu’à de faibles taux d’activité
physique (AP), et pourtant, peu d’études ont recherché la relation entre l’AP et le changement de la gravité des symptômes du
TB. L’objet de cette sous-analyse d’un essai randomisé contrôlé d’un adjuvant nutriceutique pour le traitement de la
dépression bipolaire était d’explorer la relation entre l’AP, les traitements adjuvants actifs (un « cocktail mitochondrial » dans
un nutriceutique), et les résultats cliniques.
Méthodes : Les participants souffrant de dépression bipolaire ont reçu de façon aléatoire soit la N-acétylcystéine seulement,
soit la N-acétylcystéine avec une combinaison de nutriceutiques (choisis pour leur potentiel d’accroı̂tre l’activité mitochondriale), soit un placebo pendant 16 semaines. Les participants (n ¼ 145) qui ont rempli la version abrégée du questionnaire d’activité physique international (IPAQ-SF; mesuré à la 4e semaine) ont été inclus dans cette sous-analyse
exploratoire. Les évaluations des symptômes de TB, du fonctionnement et de la qualité de vie ont été effectuées lors de
visites mensuelles, jusqu’à la 20e semaine. Des modèles linéaires mixtes ont servi à explorer si les scores à l’IPAQ-SF étaient un
modérateur du traitement reçu dans les résultats de l’étude.
Résultats : À la 4e semaine, l’AP n’était pas liée aux changements des scores à l’échelle de la dépression de Montgomery
Åsberg dans toute l’étude jusqu’à la 20e semaine. Toutefois, les participants qui faisaient plus d’AP et qui recevaient un
traitement combiné étaient plus susceptibles d’avoir une réduction de leurs scores à l’échelle de dépression bipolaire
(P ¼ 0.03). Cependant, cela n’était pas constant dans tous les domaines explorés à l’aide de l’IPAQ-SF. Les participants qui se
sont adonnés à des taux d’AP plus élevés ont aussi connu une plus grande amélioration du fonctionnement social et
professionnel, et moins de déficience du fonctionnement en raison de leur psychopathologie et de la qualité de vie à la
20e semaine, sans égard au traitement.
Conclusions : Cette étude apporte de nouvelles données probantes de l’association entre l’AP et la réduction des
symptômes de TB dans un essai clinique nutriceutique. Il faut cependant plus de recherche pour évaluer les effets synergiques
de l’AP dans le TB.
Keywords
physical activity, exercise, bipolar disorder, bipolar depression, mitochondrial agents, nutraceuticals, N-acetylcysteine
Introduction
Bipolar depression is often difficult to treat. One approach to
optimize the effects of current therapeutics may be through
lifestyle interventions such as engagement in physical activity (PA). Despite many known benefits of PA in the general
population1 and increasing evidence that individuals with
other serious mental disorders such as schizophrenia2 and
major depression3,4 can also benefit, limited research has
investigated PA and symptom severity in bipolar disorder
(BD; for reviews5,6).
To date, the literature is largely based on cross-sectional,
prospective cohort, or small pilot studies, all of which suggest
that engagement in PA improves mood and quality of life, but
the evidence base is limited.5,7-9 Individuals with BD engage
in lower levels of PA, are less likely to meet recommended
international guidelines for exercise (World Health Organization [WHO]10), and are more likely to be sedentary versus
age- and sex-matched controls.11 Therefore, not surprisingly,
people with BD demonstrate lower levels of cardiorespiratory
fitness compared to healthy controls.12,13 Previous research
has suggested that increased PA is associated with better cognition in euthymic females with a diagnosis of BD.14 Achieving an adequate level of PA has been included in the current
National Institute of Health guidelines for treating BD, but
only in the broad sense of improving general health.15 In the
general population, it is recommended that individuals
achieve 150 min of moderate or 75 min of vigorous PA per
week.10 The literature to date in the general population has
found that both continuous and interval aerobic PA at a moderate to high intensity can improve mitochondrial function.16-
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19
An emerging evidence base also advocates that resistance
training, specifically targeting the loading and strengthening
of skeletal muscles, can also improve mitochondrial function.19,20 While people with BD may have mitochondrial dysfunction,21 it is unclear whether PA at moderate to high
intensity at recommended guidelines such as those recommended by WHO10 can influence mitochondrial function.
PA is low-cost, safe, and tolerable and therefore could be an
effective adjunct to improve response to treatment in BD;
however, this has been largely unexplored. Therefore, we
aimed to investigate whether PA was associated with changes
in symptoms, functioning, and quality of life in BD. This
study was embedded in a double-blind randomized controlled
trial (RCT) evaluating the efficacy of adjunctive nutraceuticals for the treatment of bipolar depression. The adjunctive
nutraceuticals were specifically selected due to their potential
mitochondrial-enhancing properties,22 and there may be a
relationship between PA and the nutraceuticals via mitochondrial biogenesis.23 There were three arms of the RCT: Nacetylcysteine (NAC) alone, a combination treatment (CT)
of nutraceuticals including NAC and placebo.
We hypothesized that reported PA would be an effect
modifier for the relationship between those receiving NAC
alone or the CT, and an improvement on depression, functioning, and quality of life outcomes. We also hypothesized that
PA in categorical terms, according to the scoring guide of the
PA scale (low, moderate, and high), would be an effect modifier for the relationship between those receiving NAC alone or
CT, and outcomes (detailed above). Finally, when utilizing
data categorized by WHO recommendations, we hypothesized that PA (according to WHO recommendations) would
be an effect modifier for the relationship between treatment
with NAC alone or CT, and outcomes (detailed above).
Methods
Ethics
The study was run in accordance with International Council
for Harmonisation Good Clinical Practices Guidelines.24
Ethical approval was granted from Barwon Health Human
Research and Ethics Committee (HREC), Northern Sydney
Local Health District HREC, The Melbourne Clinic
Research Ethics Committee and Deakin University HREC.
The study is registered on the Australian and New Zealand
Clinical Trial Registry (ACTRN12612000830897).
Trial Study Design
Participants (n ¼ 181) who were randomized received the
study medication for 16 weeks and visited study sites (Melbourne, Geelong, and Sydney) every 4 weeks for clinical
interviews with a research assistant up until Week 20. Inclusion criteria were a diagnosis of BD, determined by the
Mini-International Neuropsychiatric Interview 5.025 and a
current moderate to severe depressive episode measured by
a score 20 on the Montgomery Åsberg Depression Rating
Scale (MADRS). 26 Full study protocol 16 and primary
results20 have been published previously.
The primary aim of the trial was to assess the efficacy of
the two active arms of the study (NAC alone and CT) compared to placebo for treating depressive symptoms (measured by the MADRS) at Week 16. Primary results of the
study at the primary endpoint were not significant at
Week 16.27 However, at Week 20 (4 weeks post–study medication discontinuation), CT was superior to placebo at
improving the following outcome measures; changes in
depression symptoms measured by the MADRS which was
the primary outcome measure in the study; bipolar depression symptom severity measured by the Bipolar Depression
Rating Scale (BDRS)28; Social and Occupational Functioning Assessment Scale (SOFAS), 29 a clinician-rated
measure of functioning; The Longitudinal Interval
Follow-Up Evaluation–Range of Impaired Functioning
(LIFE-RIFT),30 a clinician-rated measure of impairment
in functioning from psychopathology and the Clinical Global Impressions Scales Bipolar Version–Improvement
(CGI-I), 31 a 1-item clinician-rated scale measuring
improvement. Participants also completed The Quality of
life Enjoyment and Satisfaction Questionnaire–Short Form
(Q-LES-Q-SF),32 a self-report measure of quality of life.
There was no significant relationship between CT versus placebo in regard to Q-LES-Q-SF scores, but this outcome was
included in the subanalysis because of the association
between PA and quality of life in BD.13 Total possible scores
for each outcome measure and indication of direction for
improvement can be found in Supplemental Table 1.
PA
The International Physical Activity Questionnaire–Short
Form (IPAQ-SF)33 was administered at Week 4 to measure
each participant’s general level of PA. The IPAQ-SF is a
10-item self-report questionnaire where participants recall
the number of days and minutes of vigorous activity, moderate activity, walking and sitting time, over the past 7 days.
The IPAQ-SF has been used extensively in other mental
health disorder populations and has acceptable validity and
reliability.34 The IPAQ-SF was administered at Week 4 to
reduce participant burden at the baseline visit and to coincide
with collection of dietary intake data. The IPAQ-SF was
administered as secondary outcomes’ data and has been
included in the protocol16; however, this measure was inadvertently omitted from the trial registry.
Data were cleaned using IPAQ-SF recommendations33
that include removing cases with missing values and removing cases with values too low (less than 10 min of activity per
day). There was no missing data for vigorous, moderate
activity, or walking. Two participants had missing values for
the “time spent sitting” item. Both these participants
remained in the analysis as this item is not used to calculate
total scores or categorical scores. Minimum and maximum
values were implemented to remove outliers. As a result, one
4
participant was removed for too few minutes (6 min) of
activity. To normalize the data, the protocol suggests truncating each daily activity time to no more than 180 min. This
rule was employed for five participants reporting vigorous
activity, seven for moderate activity, and six for walking. Of
note, one participant filled in the IPAQ-SF questionnaire at
Week 8, not Week 4 but remained in the analysis.
Weekly metabolic equivalent of task (MET)-minute
scores for each activity type were first calculated as follows:
Note. Abbreviations: BMI ¼ body mass index; CT ¼ combination treatment; IPAQ ¼ International Physical Activity Questionnaire; NAC: N-acetylcysteine.
*P < 0.05. **P < 0.01.
360.0
990.0
Male gender, n (%)
17 (34.7)
18 (36.0)
16 (34.8)
51 (35.2)
Age, M (SD)
45.88 (11.9)
45.0 (12.1)
47.7 (13.3)
46.1 (12.4)
21.3 to 72.0
BMI, M (SD)
30.3 (7.9), n ¼ 47
27.9 (6.3)
28.2 (6.8)
28.8 (7.0), n ¼ 143
16.82 to 52.8
Total weekly physical activity (MET-min), M (SD) 2,024.4 (2,477.8)
1,766.3 (2,433.2) 1,603.1 (1,718.9)
1,801.8 (2,239.3)
0 to 11,118.0
IPAQ categorical
Low, n (%)
22 (44.9)
27 (54.0)
23 (50.0)
72 (49.7)
Moderate, n (%)
13 (26.5)
11 (22.0)
14 (30.4)
38 (26.2)
High, n (%)
14 (28.6)
12 (24.0)
9 (19.6)
35 (24.1)
WHO recommendations
No physical activity, n (%)
7 (14.3)
4 (8.0)
5 (10.9)
16 (11.0)
Below WHO recommendations, n (%)
9 (18.4)
17 (34.0)
14 (30.4)
40 (27.6)
Within WHO recommendations, n (%)
9 (18.4)
10 (20.0)
4 (8.7)
23 (15.9)
Above WHO recommendations, M (SD)
24 (49.0)
19 (38.0)
23 (50.0)
66 (45.5)
Minutes spent sitting per weekday, M (SD)
421.9 (236.6)
427.6 (251.6)
441.8 (239.9), n ¼ 44
430.0 (241.4), n ¼ 143
21 to 1,260
Characteristics
Table 1. Study Participants’ Characteristics.
Placebo (n ¼ 49)
NAC (n ¼ 50)
CT (n ¼ 46)
Total (n ¼ 145)
Range
Median Cutpoint
The Canadian Journal of Psychiatry
Vigorous activity, minutes/week ¼ total minutes per week of
vigorous activity 8.0 METs
Moderate activity, minutes/week ¼ total minutes per week
of moderate activity 4.0 METs
Walking, minutes/week ¼ total minutes per week of walking
3.3 METs
Each total activity-MET score was then summed to create
a continuous total PA score.
In addition to total PA scores, a categorical value was
produced for each participant. The categories were low,
moderate, or high PA and were calculated for each participant in accordance with IPAQ-SF scoring protocol.33 Within
this protocol, participants’ activity levels were deemed high
if they engaged in at least 3 days of vigorous activity and
achieving a total activity of at least 1,500 MET min/week, or
a combination of all intensity levels for 7 days or more and
achieving a total activity of at least 3,000 MET min/week.
Moderate activity category was achieved if participants
engaged in at least 20 min of vigorous activity for 3 days,
or at least 30 min of walking and/or moderate activity for
5 days, or a combination of any activity level for 5 or
more days and achieving a total activity of at least
600 MET-min/week. Lastly, participants’ activities were
categorized as low if they did not fit into either of the
above categories. A summary of categorical scores for
the sample can be found in Table 1.
The last item of the IPAQ-SF is “time spent sitting” and is
used to assess participants’ rates of sedentary behaviors.
Sitting has been presented as a separate variable, measured
in average minutes per typical weekday.
In addition to the validated exploration of the IPAQ scale,
further analysis was conducted using WHO recommendations. This was completed to provide preliminary data for
guidelines and clinical practice and to provide real-world
advice to patients. To explore these data in relation to WHO
recommendations, total PA data in MET-min/week were
categorically scored. These additional categories were utilized to aid direct interpretation of the results to participant
adherence to WHO recommendations as outlined below.
This quick interpretation allows results from this study to
be easily translated into policy and clinical care.
1.
No PA—All activity < 10 min duration (equivalent of 0
MET-min/week).
2. Below WHO recommendations—Less than 150 min of
moderate activity or 75 min of vigorous activity per week.
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La Revue Canadienne de Psychiatrie
Equivalent of energy expenditure between 0 and 600 METmin/week (not inclusive).
3. Within WHO recommendations—At least 150 min of moderate activity or 75 min of vigorous activity per week.
Equivalent of energy expenditure between 600 and 1,200
MET-min/week (inclusive).
4. Exceeding WHO recommendations—WHO recommends
for greater health benefits, at least 300 min of moderate
activity and 150 min of vigorous activity. Equivalent of
energy expenditure greater than 1,200 MET-min/week.
Statistical Analysis
Generalized estimating equations (GEE) were used to assess
whether PA (as a total score, categorical value, and according to WHO recommendations) were predictors of outcomes
from the nutraceutical RCT (MADRS, BDRS, SOFAS,
LIFE-RIFT, Q-LES-Q-SF, and CGI-I scores). Each predictor
was assessed individually including an exploration of each
of the treatment arms (NAC alone or CT) compared to placebo across the study up until Week 20. By using GEE, the
analyses are able to take into account the longitudinal nature
of data (i.e., measurement autocorrelation in follow-ups).
The primary outcome of the study followed a modified
intention-to-treat analysis whereby participants with post–
baseline data were included in the analysis.27 First, the original RCT analyses were replicated by including treatment
arms as a nominal factor, log of follow-up time as a covariate, and the two-way interaction between log(time) and
treatment arms was replicated, followed by including each
predictor (each PA score) in a separate model to evaluate
whether it is a predictor of outcomes. The latter model
contained treatment arms as a nominal factor, log of
follow-up time as a covariate, predictor of interest, all possible two-way interactions and the three-way interactions
between treatment arms, log of follow-up time, and the
predictor of interest. Three-way models evaluated the
effect of each predictor on the outcome measure, across
time in the study, for each treatment arm. Treatment by
PA two-way interactions explored the role of the predictor
for each of the study, independent of time. Each model
utilized Baron and Kenny 35 criteria guidelines as first
described by Kraemer et al.36 Each model for each of the
predictors is described below.
Categorical PA
We took into account the ordinal nature of PA categories
when modeling the IPAQ-SF as low, moderate, and high.
The model included a fixed-effect treatment group and
categorical (ordinal) PA, and logarithm of time as covariates, all two-way interactions and the three-way interactions. As above, three-way interactions were then
removed to explore two-way interactions. Total PA was
also assessed as a continuous score, details of which are
outlaid in Supplemental Material.
PA According to WHO Recommendations
PA according to WHO recommendations was assessed as
nominal data and included in the model as a factor. The
initial model included a fixed-effect treatment group and
PA according to WHO recommendations, and logarithm of
time as covariate, all two-way interactions and all three-way
interactions. After this model was run for each outcome,
three-way interactions were then removed to explore all
two-way interactions for each outcome.
The P value for all overall three-way interactions were
reported alongside Wald w2 statistic (used to measure parameter effects). In addition, for each treatment group (NAC
alone or CT), three-way interactions were reported with P
value and Wald w2 statistic, alongside their corresponding b
coefficients and 95% confidence intervals (CIs) to measure
association.
After examining three-way and two-way interactions of
interest for each predictor, the data were then further
explored for nonspecified predictors. Nonspecified predictors demonstrated a relationship with change in the outcome
measure independent of what treatment was received and
time. Each model for nonspecified predictors included the
main effects of treatment group, the predictor, and logarithm
of time. This model assesses for nonspecified predictors as it
explores the predictors’ response in the sample as a whole
(combining all treatment groups).
The GEE technique was implemented for model estimation using an unstructured working correlation matrix and
a robust variance estimator.37 Statistical analyses were
completed using IBM SPSS Statistics for Windows,
Version 25.38
Results
Participants
Of the 181 participants in the clinical trial, 33 participants
were excluded from the analysis for not having any post–
baseline data, 2 participants excluded for missing IPAQ-SF
data, and 1 participant excluded due to insufficient activity
(less than 10 min activity). Therefore, 145 participants were
included in the current analysis. The average age of the
sample was 46.14 years (SD ¼ 12.38), ranging from 21 to
72 years of age, and 51% were male. Participants were randomized to receive NAC (n ¼ 50), CT (n ¼ 46), and placebo
(n ¼ 49). A full list of study sample characteristics can be
found in Table 1.
Analysis of Predictors
Change scores were calculated for each outcome measure
(except CGI-I that self-evidently had no baseline data available). Mean change (Week 20 minus baseline scores) for
each outcome variable per treatment group is shown in Supplemental Table 2. On average, participants in all treatment
arms improved across all outcome measures. As CGI-I
6
Table 2. IPAQ Scores Categorized into Low, Moderate, and High According to IPAQ-SF Guidelines as a Predictor of Mean Change Scores for Each Treatment Arm.
Placebo
METCategorical
Low
Placebo
CT
NAC
MADRS change
Mean (SD)
12 (10.1)
14.1 (9.5) 15.1 (10.8)
n
20
18
19
BDRS change
Mean (SD)
9.5 (9.8) 10.2 (10.3) 13.4 (9.7)
n
19
16
19
SOFAS change
Mean (SD)
12.7 (12.9)
17.3 (12.7)
13.3 (10.6)
n
19
18
18
LIFE-RIFT change
Mean (SD)
2.3 (4.4)
3.7 (5.0)
3.7 (3.7)
n
19
16
19
Q-LES-Q change
Mean (SD)
12.7 (23.4)
16.7 (18.0)
18.1 (18.1)
n
19
18
19
CGI-I Week 20b
n
20
18
19
NAC
CT Interactiona
b Coefficient (95%
CI)
Moderate
CT
4.9 (11.2)
10
18.7 (7.6)
11
15.4 (10.8) 14.8 (12.2) 22.5 (3.5)
7
10
2
2.1 (12.4)
8
17.1 (7.9)
11
13.8 (9.3)
6
NAC
High
11.7 (9.3)
10
CT
10.6 (8.1)
9
21.0 (2.8)
2
Interaction
Test
Interaction
Test
P Value
NAC Interactiona
b Coefficient (95%
CI)
0.02
(2.9 to 2.8)
w2(1) < 0.01
P ¼ 0.987
2.8
(0.01 to 5.6)
w2 (1) ¼ 3.8
P ¼ 0.051
9.2 (7.2)
9
0.2
(2.7 to 3.0)
w2(1) ¼ 0.01
P ¼ 0.917
2.9
(0.03 to 5.7)
w2(1) ¼ 3.9
P ¼ 0.047
Placebo
P Value
17.5 (14.5)
11
14.5 (14.5)
6
14.7 (12.0)
10
12.5 (7.8)
2
13.0 (11.2)
9
0.7
(4.8 to 3.4)
w2(1) ¼ 0.1
P ¼ 0.736
0.2
(3.8 to 3.5)
w2(1) ¼ 0.01
P ¼ 0.932
0.8 (3.6)
8
5.6 (3.8)
11
4.7 (2.5)
6
3.7 (4.2)
10
4.0 (1.4)
2
3.6 (2.0)
9
0.1
(1.5 to 1.3)
w2(1) ¼ 0.01
P ¼ 0.909
0.5
(0.7 to 1.8)
w2(1) ¼ 0.7
P ¼ 0.417
<0.01 (15.0)
9
23.1 (19.8)
11
17.1 (10.0)
7
21.8 (18.0)
9
26.8 (12.6)
2
15.9 (23.7)
9
1.8
(6.7 to 3.2)
0.2
(0.4 to 0.8)
w2(1)
P
w2(1)
P
2.6 (12.7)
9
9
11
7
10
2
9
¼ 0.5
¼ 0.486
¼ 0.4
¼ 0.546
5.2
(11.0 to 0.6)
0.05
(0.5 to 0.6)
w2(1)
P
w2(1)
P
¼ 3.1
¼ 0.077
¼ 0.03
¼ 0.864
Note. Abbreviations: BDRS ¼ Bipolar Depression Rating Scale; CGI-I ¼ Clinical Global Impression Improvement; CT ¼ combination treatment; LIFE-RIFT ¼ Longitudinal Interval Follow-Up Evaluation–Range of Impaired
Functioning Tool; MADRS ¼ Montgomery Åsberg Depression Rating Scale; NAC ¼ N-acetylcysteine; SOFAS: Social and Occupational Functioning Scale.
a
Three-way interaction between potential predictor, time and treatment group, reference group was placebo.
b
As CGI-I is not administered at baseline, mean score change has not been measured. High and low levels of each predictor were determined by median split.
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represents a single score of change from baseline, mean
Week-20 CGI-I scores per treatment group are summarized
in Supplemental Table 3. On average, research clinicians
rated participants as improving across the study. For all
models with a significant interaction, age, sex and body mass
index were explored as potential confounders, and no factors
had a statistically significant impact on the relationships.
PA as a Categorical Variable
PA scores on the IPAQ-SF were categorized as low, moderate, or high using scale recommendations. From the whole
sample, 49.7% of participants were categorized as engaging
in low weekly PA, 26.2% engaging in moderate weekly PA,
and 24.1% engaging in high weekly PA. A visual representation of data has been included in Supplemental Figure 1b.
Categorical PA was not significantly associated with
scores for MADRS, SOFAS, LIFE-RIFT, Q-LES-Q-SF, or
CGI-I (see Table 2). There was a three-way interaction
between taking NAC and engaging in high exercise and
participant’s BDRS outcomes. Compared to placebo, participants receiving NAC and engaging in a high amount of
exercise showed an increase in BDRS scores, indicating a
worsening of symptoms across the trial. For every one-level
increase in level of PA (i.e., level of PA according to IPAQSF categorical scores), mean BDRS on NAC further
increased by 2.85 (95% CI, 0.03 to 5.7) units when compared
with placebo group with similar PA level. There were no
significant two-way interactions between treatment received
and categorical PA.
WHO Recommendations
PA scores were represented in terms of WHO recommendations. From the whole sample, 11% engaged in no weekly
PA, 27.6% engaged in weekly PA under the WHO recommendations, 15.9% engaged in weekly PA within the WHO
recommendations, and 45.5% engaged in weekly PA greater
than, or, exceeding the WHO recommendations. A visual
representation of data has been included in Supplemental
Figure 1c.
Results of the effect modification analysis are shown in
Table 3. PA according to WHO recommendations was not
significantly associated with scores for MADRS, SOFAS,
LIFE-RIFT, Q-LES-Q-SF, or CGI-I. There was a significant
three-way interaction between treatment received, PA
according to WHO recommendations, and time. Participants
who were randomized to receive CT and engaged in more
PA had a greater reduction in BDRS scores, indicating an
improvement in symptoms. For every one-level increase in
PA (i.e., level of PA categorized according to WHO recommendations), mean BDRS in the combination therapy group
further decreased by 2.15 (95% CI, 4.07 to 0.23) units
when compared with the placebo group with similar PA
levels. There were no significant two-way interactions
between treatment received and PA in terms of WHO
recommendations.
Total PA Scores
Total PA, as a continuous score, was not significantly associated with MADRS, SOFAS, LIFE-RIFT, Q-LES-Q-SF, or
CGI-I scores (see Supplemental Table 4). There was, however, a significant three-way interaction between participants taking CT and engaging in more PA and
participant’s BDRS outcomes. Compared to placebo, participants receiving CT and engaging in a high amount of exercise showed a decrease in BDRS scores at Week 20
indicating an improvement in symptoms across the trial. For
every 10% increase in participants’ total MET score, BDRS
scores decreased by 0.09 (95% CI, 1.8 to 0.1) units.
There were no significant two-way interactions between
treatment received and log-transformed total PA.
Nonspecified Predictors’ Analysis
Results of the nonspecified predictors of outcomes analysis
can be found in Table 4. Total PA was not significantly
related to MADRS or CGI-I outcomes. Total PA was a significant nonspecified predictor of SOFAS, LIFE-RIFT, and
Q-LES-Q-SF scores at Week 20, irrespective of treatment
received. For every 10% increase in participants’ total MET
score, SOFAS scores increased by 0.06 (CI, 0.01 to 1.31)
units, LIFE-RIFT scores decreased by 0.02 (95% CI, 0.41
to 0.08) units, and Q-LES-Q-SF scores would increase by
0.09 (95% CI, 0.13 to 1.80) units.
Categorical PA did not significantly predict Week-20
MADRS scores. Higher PA categories, according to the
IPAQ-SF scoring protocol, was a nonspecified predictor of
SOFAS, LIFE-RIFT, CGI-I, and Q-LES-Q-SF. Higher activity levels were more likely to be associated with slightly
improved scores for these measures, regardless of treatment
received. For every one-level increase in level of PA according to IPAQ-SF categorical scores (i.e., moderate to high),
mean SOFAS scores at Week 20 increased by 2.27 (95% CI,
0.24 to 4.30) units, mean LIFE-RIFT scores decreased by
0.67 (95% CI, 1.23 to 0.11) units, mean Q-LES-Q-SF
scores increased by 2.39 (95% CI, 0.03 to 4.75) units, and
mean CGI-I scores decreased by 0.16 (95% CI, 0.31 to
0.01) units.
PA according to WHO recommendations was not associated with Week-20 MADRS or CGI-I scores. Higher PA
categories, according to WHO recommendations, was a nonspecified predictor of SOFAS, LIFE-RIFT, and Q-LESQ-SF. Higher activity levels were more likely to be associated with slightly improved scores for these measures,
regardless of treatment received. For every one-level
increase in level of PA according to WHO recommendations
(i.e., from below to within recommendations), mean SOFAS
scores at Week 20 increased by 1.80 (95% CI, 0.35 to 3.25)
units, mean LIFE-RIFT scores decreased by 0.71 (95% CI,
8
Table 3. Physical Activity According to WHO Recommendations as a Predictor of Mean Change Scores for Each Treatment Arm.
Placebo
MET–WHO
CT
No Physical Activity
NAC
Placebo
CT
NAC
Placebo
Below WHO Recommendations
MADRS change
Mean (SD)
11.3 (14.5) 9.0 (13.9) 15.0 (7.2) 14.1 (5.0) 14.8 (9.1) 14.9 (10.1)
n
7
3
4
8
12
12
BDRS change
Mean (SD)
14.1 (11.0) <0.01 (14.1) 14.5 (11.1) 12.1 (7.5)
9.9 (9.8) 12.9 (9.3)
n
7
2
4
7
11
12
SOFAS change
Mean (SD)
15.3 (16.0)
7.0 (15.9)
19.8 (10.1)
13.9 (11.3)
18.0 (11.3)
12.9 (8.9)
n
7
3
4
7
12
11
LIFE-RIFT change
Mean (SD)
3.0 (4.5) <0.01 (7.1)
3.5 (5.1)
3.7 (3.5)
3.7 (4.2)
3.4 (4.0)
n
7
2
4
7
11
12
Q-LES-Q change
Mean (SD)
13.8 (22.2) 10.1 (14.5)
24.6 (11.4)
19.4 (23.7)
18.8 (16.2)
16.4 (18.9)
n
7
3
4
7
12
12
b
CGI-I Week 20
n
7
3
4
8
12
12
CT
NAC
Within WHO Recommendations
Placebo
CT
Exceeding WHO Recommendations
3.0 (11.2) 15.3 (7.1)
8
4
18.0 (13.7) 13.0 (11.1) 19.9 (7.0)
7
17
12
0.6 (11.1) 16.8 (5.1)
7
4
15.0 (11.1)
6
1.6 (11.3)
8
16.0 (15.4)
4
9.7 (16.8)
6
NAC
10.4 (8.5)
12
Overall Three-Way
Interaction Test
P Value
Interactiona
b Coefficient
(95% CI)
w2(2) ¼ 3.3
P ¼ 0.19
0.8
(2.8 to 1.2)
Interaction
Test
P Value
w2(1) ¼ 0.6
P ¼ 0.440
Interactiona
b Coefficient
(95% CI)
Interaction
Test
P value
1.1
w2(1) ¼ 1.0
(1.1 to 3.2)
P ¼ 0.319
8.5 (10.2) 18.1 (7.5)
16
12
9.8 (10.5)
12
w2(2) ¼ 6.2
P ¼ 0.046
2.2
w2(1) ¼ 4.8
0.1
(4.1 to 0.2)
P ¼ 0.028 (2.2 to 2.0)
w2(1) <0.01
P ¼ 0.951
12.1 (12.4)
16
18.9 (13.4)
12
13.7 (10.5)
12
w2(2) ¼ 1.4
P ¼ 0.504
1.7
(1.1 to 4.5)
w2(1) ¼ 1.4
P ¼ 0.243
0.8
w2(1) ¼ 0.4
(1.8 to 3.4)
P ¼ 0.546
0.4 (4.7)
7
5.0 (4.1)
4
4.7 (2.0)
6
2.3 (4.2)
16
5.7 (4.2)
12
3.9 (4.0)
12
w2(2) ¼ 0.8
P ¼ 0.666
0.4
(1.3 to 0.5)
w2(1) ¼ 0.8
P ¼ 0.382
0.1
w2(1) ¼ 0.03
(1.0 to 0.8)
P ¼ 0.866
3.1 (16.0)
7
17.0 (11.9)
4
13.8 (15.8)
7
14.2 (20.9)
16
23.7 (22.8)
12
17.9 (21.1)
12
16
12
12
w2(2) ¼ 1.3
P ¼ 0.512
w2(2) ¼ 0.8
P ¼ 0.67
1.3
(2.5 to 5.1)
0.2
(0.6 to 0.2)
w2(1) ¼ 0.5
P ¼ 0.496
w2(1) ¼ 0.7
P ¼ 0.402
1.0
w2(1) ¼ 0.2
(5.1 to 3.1)
P ¼ 0.640
<0.01
w2(1) <0.01
(0.4 to 0.4)
P ¼ 0.999
8
4
7
Note. Abbreviations: BDRS ¼ Bipolar Depression Rating Scale; CGI-I ¼ Clinical Global Impression Improvement; CT ¼ combination treatment; LIFE-RIFT ¼ Longitudinal Interval Follow-Up Evaluation–Range of Impaired
Functioning Tool; MADRS ¼ Montgomery Åsberg Depression Rating Scale; NAC: N-acetylcysteine; SOFAS ¼ Social and Occupational Functioning Scale.
a
Three-way interaction between potential predictor, time and treatment group, reference group was placebo.
b
As CGI-I is not administered at baseline, mean score change has not been measured. High and low levels of each predictor were determined by median split.
9
La Revue Canadienne de Psychiatrie
Table 4. Total Weekly Physical Activity, IPAQ Categorical Scores,
and Physical Activity Categorized by WHO Recommendations as
Nonspecified Predictors of Outcomes.
Predictor
b Coefficient (95% CI)
Main Effect
Total weekly physical activity
MADRS
0.2 (0.6 to 0.3)
w2(1) ¼ 0.6, P ¼ 0.458
BDRS
0.1 (0.5 to 0.2)
w2(1) ¼ 0.5, P ¼ 0.498
SOFAS
0.7 (0.01 to 1.3)
w2(1) ¼ 4.0, P ¼ 0.046
LIFE-RIFT
0.2 (0.4 to 0.1)
w2(1) ¼ 8.5, P ¼ 0.004
Q-LES-Q
1.0 (0.1 to 1.8)
w2(1) ¼ 5.2, P ¼ 0.023
CGI-I
0.01 (0.1 to 0.04)
w2(1) ¼ 0.1, P ¼ 0.709
IPAQ scores in categorical
MADRS
1.1 (2.2 to 0.03)
w2(1) ¼ 3.7, P ¼ 0.056
BDRS
0.7 (1.9 to 0.4)
w2(1) ¼ 1.5, P ¼ 0.218
SOFAS
2.3 (0.2 to 4.3)
w2(1) ¼ 4.8, P ¼ 0.028
LIFE-RIFT
0.7 (1.2 to 0.1)
w2(1) ¼ 5.6, P ¼ 0.018
Q-LES-Q
2.4 (0.03 to 4.8)
w2(1) ¼ 3.9, P ¼ 0.047
CGI-I
0.2 (0.3 to 0.01) w2(1) ¼ 4.4, P ¼ 0.036
Physical activity categorized by WHO recommendations
MADRS
0.6 (1.5 to 0.3)
w2(1) ¼ 1.5, P ¼ 0.219
BDRS
0.4 (1.3 to 0.4)
w2(1) ¼ 1.0, P ¼ 0.311
SOFAS
1.8 (0.3 to 3.3)
w2(1) ¼ 5.9, P ¼ 0.015
LIFE-RIFT
0.7 (1.1 to 0.3)
w2(1) ¼ 13.7, P < 0.001
Q-LES-Q
2.2 (0.5 to 4.0)
w2(1) ¼ 6.0, P ¼ 0.014
CGI-I
0.1 (0.2 to 0.1)
w2(1) ¼ 1.1, P ¼ 0.286
Note. Abbreviations: BDRS ¼ Bipolar Depression Rating Scale; CGI-I ¼
Clinical Global Impression Improvement; CT ¼ Combination Treatment;
LIFE-RIFT ¼ Longitudinal Interval Follow-Up Evaluation–Range of Impaired
Functioning Tool; MADRS ¼ Montgomery Åsberg Depression Rating Scale;
NAC ¼ N-acetylcysteine; SOFAS: Social and Occupational Functioning
Assessment Scale.
Bolded p-values highlight significant values.
1.09 to 0.34) units, and mean Q-LES-Q-SF scores
increased by 2.25 (95% CI, 0.45 to 4.04) units.
Discussion
The aim of this subanalysis of a nutraceutical RCT was to
assess the relationships between PA, treatment received, and
changes from baseline to Week 20 in outcomes measures for
individuals with BD. Results suggest that there may be an
association between PA and some of the depression and
functioning outcomes of the study, but this was not consistent for all outcome measures.
In regard to depression symptoms, PA was unrelated to
change across the study from baseline to Week 20 on the
primary outcome measure, the MADRS. However, for participants receiving CT, total PA significantly predicted
changes in bipolar depression symptoms (measured by the
BDRS). There was a robust relationship between participants receiving CT who exceeded WHO recommendations
for PA. These participants showed a greater reduction in the
BDRS depression symptoms, compared to participants
receiving placebo at a similar level of PA, in a dosedependent manner; however, the differences between the
groups were minimal. In contrast, participants who received
NAC and engaged in higher levels of PA demonstrated a
worsening of their BD symptoms, but this was not consistent
across all measures. After some types of strenuous, high
intensity, or endurance PA, there is evidence of a shortterm acute inflammatory response in some people39-42 that
adapts over time. Inflammation is a necessary part of
muscular recovery from exercise, and anti-inflammatory
medication such as NAC may be inhibiting this process.43,44
There may be a delicate balance between anti-inflammatory
use and benefits of exercise, potentially leading to the need
for targeted and timed anti-inflammatory medication.44 As
use of NAC appears to demonstrate a worsening of BD
symptoms for those in a high category of the IPAQ compared to placebo, this may be a demonstration of a disruption
to this delicate balance and warrants further investigation.
As the CT group demonstrates improvement on this same
depression scale, there is potentially an element within the
CT, which is protective and counteracting the negative
effects of NAC. However, due to the exploratory nature of
this subanalysis and the low number of participants, cautious
interpretation is required.
It is possible that the combination of mitochondrialenhancing PA and the mitochondrial-enhancing CT may
be an important interaction for improving bipolar depression
symptoms. This is in keeping with the hypothesis that BD is
at its heart a mitochondrial disorder manifested by decreased
biogenesis in depression and excess energy generation in
mania.21 Previous research has also found a reduction of
depression (unipolar and bipolar) with PA at higher levels.45
The potential for PA in BD is profound, given its positive
effects on neuroplasticity,46 hippocampal volume,47 increasing brain-derived neurotrophic factor,48 mitochondrial activity, and neurogenesis23 potentially mediated by peroxisome
proliferator-activated receptor-gamma coactivator (PGC)1a.49 These are all processes that are disturbed in BD, giving
rise to the possibility that PA may improve symptoms of BD
via improving mitochondrial dysfunction and neuroplasticity. The additional benefits of receiving CT and engaging
in higher levels of PA may be achieved via synergistic
effects on the pathway regulating mitochondrial energy generation, such as PGC-1a.49,50
There were no significant relationships between participants’ PA, the treatment they received on the study and
functional outcomes (LIFE-RIFT and SOFAS), quality
of life (Q-LES-Q-SF), or clinician-rated improvement
(CGI-I). However, there were relationships between the
PA predictors and outcome measures, irrespective of what
treatment they received. PA (including all variations on the
scale) was a nonspecified predictor of improvement in social
and occupational functioning (SOFAS), psychopathologyinduced impairment of functioning (LIFE-RIFT), and quality of life (Q-LES-Q-SF) at Week 20. These results are in
keeping with previous research suggesting improved outcomes for those who engage in more PA.51 One interpretation could be a bidirectional relationship between
functioning and PA. For instance, if a participant has adequate physical functioning levels, then they may have a
10
greater motivation or ability to engage in PA. However, as
PA is only measured once, we cannot determine causality.
Strengths of this study include the design of the doubleblind adjunctive RCT adjunctive, allowing for robust clinical
trial data. PA has been measured according to a validated
scale with two possible outcome measures for interpretation
(continuous weekly score and categorical weekly score).33
This scale takes a conservative approach in truncating and
removing data for less skew. In addition, PA has been categorized according to WHO recommendations allowing for
real-world, practical interpretations and has implications for
public health messages.
Results of this study should be cautiously interpreted due
to its limitations. In particular, the phasic nature of BD may
interact with PA levels of participants. Given the scale was
administered at Week 4, we cannot guarantee the phase of
BD that participants were in is consistent across the sample.
In addition, there is no measure of activity later in the study
to assess change in participants’ level of PA. The disparity of
energy expended in different states in BD highlights the
potential for a bipolar-specific PA scale with populationspecific standards. In terms of the PA Scale used (IPAQ-SF),
limitations exist due to the nature of self-report and can be
prone to error and recall bias.52 In addition, the IPAQ considers the intensity of PA but does not record the types of
exercise participants have engaged in. To reduce recall bias
and to be able to review types of exercise, actigraphy could
be used in addition to PA questionnaires.52
The nature of exploratory subanalyses in general poses
further limitations. The RCT was powered for the primary
outcome, that is, change in depression for the active treatment groups, which means the subanalysis is likely underpowered. Due to the small sample size of the data, there was
insufficient power for a robust response to assess the categorical data measured from the IPAQ-SF scoring guide as
nominal and as a factor within the model. PA is measured
only once and as a covariate that is not directly being intervened, which limits interpretability of results. Lastly, the
results presented in this subanalysis are statistically significant, but they represent small changes in outcome and thus
small clinical significance. Future studies directly assessing
the impact of PA programs should be powered to see
greater changes in outcomes. Post hoc analyses always
need to be interpreted with caution, as is the case for multiple comparisons.
Conclusion and Future Directions
Engaging participants to increase their activity may be a
cost-effective way of improving treatment outcomes with
additional health benefits for comorbid physical disorders
This subanalysis of an adjunctive nutraceutical RCT adds
some further support to the association between PA and
mental health, and in particular, BD. PA measured at the
beginning of this study was associated with functioning and
quality of life at the end of the study. This subanalysis
The Canadian Journal of Psychiatry
suggests that measures of PA may be useful when analyzing
outcomes of a new treatment. Future research may clarify the
potential adjunctive effects of higher PA and mitochondrialenhancing therapies in treating bipolar depression symptoms, possibly through mitochondrial biogenesis.
Authors’ Note
The sponsors and funding bodies have played no role in collection,
analysis, interpretation of results, or writing of the manuscript.
Acknowledgments
The authors would like to thank all participants of the study. The
authors would also like to acknowledge the following health services involved in this study: Barwon Health, The Geelong Clinic,
The Melbourne Clinic, and the University of Sydney CADE Clinic
based at Royal North Shore Hospital. The authors are grateful to the
Stanley Medical Research Institute, The CRC for Mental Health
and the National Health and Medical Research Council for funding
the study. M.M.A would like to thank Australasian Sociesty for
Bipolar Depressive Disorders, Lundbeck, Australian Rotary
Health, Ian Parker Bipolar Research Fund and Deakin University
for scholarship support.
Declaration of Conflicting Interests
M.M.A. has received grant/research support from Deakin University, Australasian Society for Bipolar Depressive Disorders,
Lundbeck, Australian Rotary Health, Ian Parker Bipolar Research
Fund, and Cooperative Research Centre for Mental Health. A.T.
has received travel or grant support from the NHMRC, Deakin
University, AMP Foundation, National Stroke Foundation, Hunter
Medical Research Institute, Helen Macpherson Smith Trust, Schizophrenia Fellowship NSW, SMHR, ISAD, and the University of
Newcastle. M.B. has received grant support from NIH, Simons
Autism Foundation, Cancer Council of Victoria, CRC for Mental
Health, Stanley Medical Research Foundation, MBF, NHMRC,
Beyond Blue, Geelong Medical Research Foundation, Bristol
Myers Squibb, Eli Lilly, GlaxoSmithKline, Organon, Novartis,
Mayne Pharma, and Servier. M.B. has been a speaker for Astra
Zeneca, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline,
Janssen Cilag, Lundbeck, Merck, Pfizer, Sanofi Synthelabo,
Servier, Solvay and Wyeth, and served as a consultant to Astra
Zeneca, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline,
Janssen Cilag, Lundbeck, and Servier. C.H.N. had served as a
consultant for Lundbeck, Grunbiotics, Servier, Janssen-Cilag,
Wyeth and Eli Lilly, received research grant support from Wyeth
and Lundbeck, and speaker honoraria from Servier, Lundbeck,
Bristol-Myers Squibb, Organon, Eli Lilly, GlaxoSmithKline,
Janssen-Cilag, Astra-Zenaca, Wyeth, and Pfizer. M.H. has
received grant support from ISSCR, Servier, US DOD, and Bionomics, has been a speaker for Janssen-Cilag, Lundbeck, and
Servier, and has been a consultant for AstraZeneca, Eli Lilly,
Janssen-Cilag, Lundbeck, and Servier. J.S. has received either
presentation honoraria, travel support, clinical trial grants, book
royalties or independent consultancy payments from Integria
Healthcare & MediHerb, Pfizer, Scius Health, Key Pharmaceuticals, Taki Mai, Bioceuticals & Blackmores, Soho-Flordis, Healthworld, HealthEd, HealthMasters, Elsevier, Chaminade University,
International Society for Affective Disorders, Complementary
Medicines Australia, Terry White Chemists, ANS, Society for
Medicinal Plant and Natural Product Research, UBiome,
11
La Revue Canadienne de Psychiatrie
Omega-3 Centre, the National Health and Medical Research
Council, CR Roper Fellowship. S.D. has received grant support
from Stanley Medical Research Institute, NHMRC, Beyond Blue,
ARHRF, Simons Foundation, Geelong Medical Research Foundation, Fondation FondaMental, Eli Lilly, Glaxo SmithKline, Organon, Mayne Pharma, and Servier. He has received speaker’s fees
from Eli Lilly, advisory board fees from Eli Lilly and Novartis,
and conference travel support from Servier. J.S. has received
either presentation honoraria, travel support, clinical trial grants,
book royalties or independent consultancy payments from Integria
Healthcare & MediHerb, Pfizer, Scius Health, Key Pharmaceuticals, Taki Mai, Bioceuticals & Blackmores, Soho-Flordis, Healthworld, HealthEd, HealthMasters, Elsevier, Chaminade University,
International Society for Affective Disorders, Complementary
Medicines Australia, Terry White Chemists, ANS, Society for
Medicinal Plant and Natural Product Research, UBiome,
Omega-3 Centre, the National Health and Medical Research
Council, CR Roper Fellowship. G.S.M. has received grant or
research support from National Health and Medical Research
Council, Australian Rotary Health, NSW Health, Ramsay Health,
American Foundation for Suicide Prevention, Ramsay Research
and Teaching Fund, Elsevier, AstraZeneca, and Servier; has been
a speaker for AstraZeneca, Janssen-Cilag, Lundbeck, and Servier;
and has been a consultant for AstraZeneca, Janssen Cilag, Lundbeck, and Servier. S.M.C. has received grant support from the
NHMRC, the Stanley Medical Research Institute, BeyondBlue,
Movember, The University of Melbourne, Australian Catholic
University, ARHRF, and Mental Illness Research Fund (Victoria
Department of Human Services). O.M.D. is a R.D. Wright Biomedical Research Fellow and has received grant support from the
Brain and Behavior Foundation, Simons Autism Foundation,
Stanley Medical Research Institute, Deakin University, Lilly,
NHMRC and Australasian Society for Bipolar and Depressive
Disorders (ASBDD)/Servier.
Funding
The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article: The
study has been funded by CRC for Mental Health, the Stanley
Medical Research Institute, and an NHMRC Project Grant
(APP1026307). M.M.A. is supported by Deakin University, Australasian Society for Bipolar and Depressive Disorders (ASBDD)/
Lundbeck, and Australian Rotary Health/Ian Parker Bipolar
Research Fund. M.B. is supported by a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellowship (APP1059660 and APP1156072). S.C. is supported by a
NHMRC Senior Research Fellowship (APP1136344). J.S. is
funded by an NHMRC Clinical Research Fellowship
(APP1125000). W.M. is supported by Deakin postdoctoral fellowship. B.S. is supported by a Clinical Lectureship (ICA-CL-201703-001) jointly funded by Health Education England (HEE) and the
National Institute for Health Research (NIHR). B.S. is part funded
by the NIHR Biomedical Research Centre at South London and
Maudsley NHS Foundation Trust. This paper presents independent
research supported by the National Institute for Health Research
(NIHR) and the views expressed are those of the author(s) and not
necessarily those of the (partner organisation), the NHS, the NIHR
or the Department of Health and Social Care. O.M.D. is supported
by a NHMRC R.D. Wright Biomedical Research Fellowship
(APP1145634).
ORCID iD
Michael Berk, MD, PhD
https://orcid.org/0000-0002-5554-6946
Supplemental Material
Supplemental material for this article is available online.
References
1. Piercy KL, Troiano RP, Ballard RM, et al. The physical activity guidelines for Americans. JAMA. 2018;320(19):
2020-2028.
2. Firth J, Cotter J, Elliott R, French P, Yung AR. A systematic
review and meta-analysis of exercise interventions in schizophrenia patients. Psychol Med. 2015;45(7):1343-1361.
3. Schuch FB, Vancampfort D, Richards J, Rosenbaum S, Ward
PB, Stubbs B. Exercise as a treatment for depression: a metaanalysis adjusting for publication bias. J Psychiatr Res. 2016;
77:42-51.
4. Stubbs B, Vancampfort D, Hallgren M, et al. EPA guidance on
physical activity as a treatment for severe mental illness: a
meta-review of the evidence and Position Statement from the
European Psychiatric Association (EPA), supported by the
International Organization of Physical Therapists in Mental
Health (IOPTMH). Eur Psychiatry. 2018;54:124-144.
5. Bauer IE, Galvez JF, Hamilton JE, et al. Lifestyle interventions
targeting dietary habits and exercise in bipolar disorder: a systematic review. J Psychiatr Res. 2016;74:1-7.
6. Thomson D, Turner A, Lauder S, et al. A brief review of
exercise, bipolar disorder, and mechanistic pathways. Front
Psychol. 2015;6:147.
7. Ng F, Dodd S, Berk M. The effects of physical activity in the
acute treatment of bipolar disorder: a pilot study. J Affect
Disord. 2007;101(1-3):259-262.
8. Sylvia LG, Nierenberg AA, Stange JP, Peckham AD, Deckersbach T. Development of an integrated psychosocial treatment to address the medical burden associated with bipolar
disorder. J Psychiatr Pract. 2011;17(3):224-232.
9. Sylvia LG, Salcedo S, Bernstein EE, Baek JH, Nierenberg AA,
Deckersbach T. Nutrition, exercise, and wellness treatment in
bipolar disorder: proof of concept for a consolidated intervention. Int J Bipolar Disord. 2013;1(1):24.
10. World Health Organization. Global recommendations on physical activity for health. Geneva, Switzerland: World Health
Organization; 2010.
11. Vancampfort D, Firth J, Schuch FB, et al. Sedentary behavior
and physical activity levels in people with schizophrenia, bipolar disorder and major depressive disorder: a global systematic
review and meta-analysis. World Psychiatry. 2017;16(3):
308-315.
12. Vancampfort D, Stubbs B, Sienaert P, et al. A comparison of
physical fitness in patients with bipolar disorder, schizophrenia and healthy controls. Disabil Rehabil. 2016;38(20):
2047-2051.
13. Vancampfort D, Hagemann N, Wyckaert S, et al. Higher
cardio-respiratory fitness is associated with increased mental
12
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
The Canadian Journal of Psychiatry
and physical quality of life in people with bipolar disorder: a
controlled pilot study. Psychiatry Res. 2017;256:219-224.
Fellendorf F, Kainzbauer N, Platzer M, et al. Gender differences in the association between physical activity and cognitive function in individuals with bipolar disorder. J Affec
Disord. 2017;221:232-237.
National Collaborating Centre for Mental Health. Bipolar disorder: The NICE guideline on the assessment and management
of bipolar disorder in adults, children and young people in
primary and secondary care. London, United Kingdom: British
Psychological Society; 2018.
Daussin FN, Zoll J, Dufour SP, et al. Effect of interval versus
continuous training on cardiorespiratory and mitochondrial
functions: relationship to aerobic performance improvements
in sedentary subjects. Am J Physiol Regul Integr Comp Physiol. 2008;295(1):R264-R272.
Fritzen AM, Thøgersen FB, Thybo K, et al. Adaptations in
mitochondrial enzymatic activity occurs independent of genomic dosage in response to aerobic exercise training and deconditioning in human skeletal muscle. Cells. 2019;8(3):237.
Taivassalo T, Shoubridge EA, Chen J, et al. Aerobic conditioning in patients with mitochondrial myopathies: physiological,
biochemical, and genetic effects. Ann Neurol. 2001;50(2):
133-141.
Pesta D, Hoppel F, Macek C, et al. Similar qualitative and
quantitative changes of mitochondrial respiration following
strength and endurance training in normoxia and hypoxia in
sedentary humans. Am J Physiol Regul Integr Comp Physiol.
2011;301(4):R1078-R1087.
Porter C, Reidy PT, Bhattarai N, Sidossis LS, Rasmussen BB.
Resistance exercise training alters mitochondrial function in
human skeletal muscle. Med Sci Sports Exerc. 2015;47(9):
1922.
Morris G, Walder K, McGee SL, et al. A model of the mitochondrial basis of bipolar disorder. Neurosci Biobehav Rev.
2017;74(Pt A):1-20.
Dean OM, Turner A, Malhi GS, et al. Design and rationale of a
16-week adjunctive randomized placebo-controlled trial of
mitochondrial agents for the treatment of bipolar depression.
Braz J Psychiatry. 2015;37(1):3-12.
Sylvia LG, Ametrano RM, Nierenberg AA. Exercise treatment
for bipolar disorder: potential mechanisms of action mediated
through increased neurogenesis and decreased allostatic load.
Psychother Psychosom. 2010;79(2):87-96.
Food Drug Administration. International conference on harmonisation: guidance on statistical principles for clinical trials
(ich-e9). Fed Regist. 1997;62:25692-25709.
Sheehan DV, Lecrubier Y, Sheehan KH, et al. The miniinternational neuropsychiatric interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric
interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;
59(Suppl 20):22-33;quiz 34–57.
Montgomery S, Asberg M. A new depression scale designed
to be sensitive to change. Br J Psychiatry. 1979;134:
382-389.
27. Berk M, Turner A, Malhi GS, et al. A randomised controlled
trial of a mitochondrial therapeutic target for bipolar depression: mitochondrial agents, N-acetylcysteine, and placebo.
BMC Med. 2019;17(1):18.
28. Berk M, Dodd S, Dean OM, Kohlmann K, Berk L, Malhi GS.
The validity and internal structure of the Bipolar Depression
Rating Scale: data from a clinical trial of N-acetylcysteine as
adjunctive therapy in bipolar disorder. Acta Neuropsychiatr.
2010;22(5):237-242.
29. Morosini PL, Magliano L, Brambilla L, Ugolini S, Pioli R.
Development, reliability and acceptability of a new version
of the DSM-IV Social and Occupational Functioning Assessment Scale (SOFAS) to assess routine social functioning. Acta
Psychiatr Scand. 2010;101(4):323-329.
30. Leon AC, Solomon DA, Mueller TI, Turvey CL, Endicott J,
Keller MB. The range of impaired functioning tool (LIFERIFT): a brief measure of functional impairment. Psychol Med.
1999;29(4):869-878.
31. Spearing MK PR, Leverich GS, Brandt D, Nolen W. Modification of the clinical global impressions (CGI) scale for use in
bipolar illness (BP): the CGI-BP. Psychiatry Res. 1997;73:
159-171.
32. Endicott J, Nee J, Harrison W, Blumenthal R. Quality of Life
Enjoyment and Satisfaction Questionnaire: a new measure.
Psychopharmacol Bull. 1993;29(2):321-326.
33. Craig CL, Marshall AL, Sjostrom M, et al. International physical activity questionnaire: 12-country reliability and validity.
Med Sci Sport Exerc. 2003;35(8):1381-1395.
34. Soundy A, Roskell C, Stubbs B, Vancampfort D. Selection,
use and psychometric properties of physical activity measures to assess individuals with severe mental illness: a
narrative synthesis. Arch Psychiatr Nurs. 2014;28(2):
135-151.
35. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic,
and statistical considerations. J Personal Social Psychol. 1986;
51(6):1173-1182.
36. Kraemer HC, Stice E, Kazdin A, Offord D, Kupfer D. How do
risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. Am J Psychiatry.
2001;158(6):848-856.
37. White H. A heteroskedasticity-consistent covariance matrix
estimator and a direct test for heteroskedasticity. Econometrica. 1980;48(4):817-838.
38. IBM Corp. IBM SPSS Statistics for Windows, Version 25.0.
Armonk, NY: Author; 2017.
39. Lira FS, Dos Santos T, Caldeira RS, et al. Short-term high- and
moderate-intensity training modifies inflammatory and metabolic factors in response to acute exercise. Front Physiol. 2017;
8:856-856.
40. Monteiro PA, Campos EZ, De Oliveira FP, et al. Modulation of
inflammatory response arising from high-intensity intermittent
and concurrent strength training in physically active males.
Cytokine. 2017;91:104-109.
41. Kaspar F, Jelinek HF, Perkins S, Al-Aubaidy HA, De Jong B,
Butkowski E. Acute-phase inflammatory response to single-
La Revue Canadienne de Psychiatrie
42.
43.
44.
45.
46.
47.
bout HIIT and endurance training: a comparative study. Mediators Inflamm. 2016;2016:5474837-5474837.
Zwetsloot KA, John CS, Lawrence MM, Battista RA, Shanely
RA. High-intensity interval training induces a modest systemic
inflammatory response in active, young men. J Inflamm Res.
2014;7:9-17.
Peake JM, Neubauer O, Della Gatta PA, Nosaka K. Muscle
damage and inflammation during recovery from exercise. J
Appl Physiol (Bethesda, MD: 1985). 2017;122(3):559-570.
Chazaud B. 2016. Inflammation during skeletal muscle regeneration and tissue remodeling: application to exercise-induced muscle damage management. Immunol Cell Biol. 94(2):140-145.
Schuch FB, Vancampfort D, Firth J, et al. Physical activity and
incident depression: a meta-analysis of prospective cohort
studies. Am J Psych. 2018;175(7):631-648.
Phillips C. Physical activity modulates common neuroplasticity substrates in major depressive and bipolar disorder. Neural
Plasticity. 2017;2017:7014146-7014146.
Firth J, Stubbs B, Vancampfort D, Schuch F, Lagopoulos J,
Rosenbaum S, Ward PB. Effect of aerobic exercise on hippocampal volume in humans: a systematic review and meta-analysis. Neuroimage. 2018;166:230-238.
13
48. Kerling A, Kuck M, Tegtbur U, et al. Exercise increases
serum brain-derived neurotrophic factor in patients with
major depressive disorder. J Affect Disord. 2017;215:
152-155.
49. Granata C, Jamnick NA, Bishop DJ. Principles of exercise
prescription, and how they influence exercise-induced changes
of transcription factors and other regulators of mitochondrial
biogenesis. Sport Med. 2018;48(7):1541-1559.
50. Nierenberg AA, Ghaznavi SA, Sande Mathias I, Ellard KK,
Janos JA, Sylvia LG. Peroxisome proliferator-activated receptor gamma coactivator-1 alpha as a novel target for bipolar
disorder and other neuropsychiatric disorders. Biol Psychiatry.
2018;83(9):761-769.
51. Sylvia LG, Friedman ES, Kocsis JH, et al. Association of exercise with quality of life and mood symptoms in a comparative
effectiveness study of bipolar disorder. J Affect Disord. 2013;
151(2):722-727.
52. Paul DR, McGrath R, Vella CA, Kramer M, Baer DJ,
Moshfegh AJ. Understanding the nature of measurement
error when estimating energy expenditure and physical
activity via physical activity recall. J Phys Activ Health.
2018;15(7):543-549.