Psychoradiologic abnormalities of white matter in patients with bipolar disorder: diffusion tensor imaging studies using tract-based spatial ...
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Research Paper
Psychoradiologic abnormalities of white matter in
patients with bipolar disorder: diffusion tensor
imaging studies using tract-based spatial statistics
Cheng Yang, MM*; Lei Li, MD*; Xinyu Hu, PhD*; Qiang Luo, MM; Weihong Kuang, MD;
Su Lui, MD, PhD; Xiaoqi Huang, MD, PhD; Jing Dai, MD; Manxi He, MD;
Graham J. Kemp, DSc; John A Sweeney, PhD; Qiyong Gong, MD, PhD
Published online first on Aug. 29, 2018; subject to revision
Background: An increasing number of psychoradiology studies that use tract-based spatial statistics (TBSS) of diffusion tensor imaging
have reported abnormalities of white matter in patients with bipolar disorder; however, robust conclusions have proven elusive, especially
considering some important clinical and demographic factors. In the present study, we performed a quantitative meta-analysis of TBSS
studies to elucidate the most consistent white-matter abnormalities in patients with bipolar disorder. Methods: We conducted a system-
atic search up to May 2017 for all TBSS studies comparing fractional anisotropy (FA) between patients with bipolar disorder and healthy con-
trols. We performed anisotropic effect size–signed differential mapping meta-analysis. Results: We identified a total of 22 data sets in-
cluding 556 patients with bipolar disorder and 623 healthy controls. We found significant FA reductions in the genu and body of the
corpus callosum in patients with bipolar disorder relative to healthy controls. No regions of increased FA were reported. In subgroup
analyses, the FA reduction in the genu of the corpus callosum retained significance in patients with bipolar disorder type I, and the FA re-
duction in the body of the corpus callosum retained significance in euthymic patients with bipolar disorder. Meta-regression analysis re-
vealed that the percentage of female patients was negatively correlated with reduced FA in the body of the corpus callosum. Limitations:
Data acquisition, patient characteristics and clinical variables in the included studies were heterogeneous. The small number of diffusion
tensor imaging studies using TBSS in patients with bipolar disorder type II, as well as the lack of other clinical information, hindered the
application of subgroup meta-analyses. Conclusion: Our study consistently identified decreased FA in the genu and body of the corpus
callosum, suggesting that interhemispheric communication may be the connectivity most affected in patients with bipolar disorder.
Introduction In addition to structural and functional alterations in mul-
tiple brain regions, aberrant connectivity between regions
Bipolar disorder (BD) is a serious chronic disease character- seems to be crucial to the pathogenesis of BD.4,5 Diffusion ten-
ized by the co-occurrence of manic and depressive symptoms, sor imaging (DTI), an important psychoradiology technique
and it has a worldwide prevalence of approximately 1%.1 Two (https://radiopaedia.org/articles/psychoradiology), can
main forms are distinguished in the fifth edition of the probe the white-matter tracts that form the infrastructure of
Diagnostic and Statistical Manual of Mental Disorders (DSM-5): that connectivity. It maps the diffusion of water molecules,
BD type I (BD I) is the classic manic–depressive disorder; a and the calculated quantity of fractional anisotropy (FA) con-
diagnosis of BD type II (BD II) requires at least 1 episode of tains information about the directionality and coherence of
major depression and 1 hypomanic episode.2 Bipolar disorder neuronal fibre tracts.6,7
leads to severe impairments in work role function and a high In studies of patients with BD, however, various regions
lifetime suicide risk; thus, there is a pressing need for a better showing both FA increases and decreases have been re-
understanding of its neural basis. Magnetic resonance im ported: for example in the prefrontal white matter, temporal
aging has been a useful way to pursue this, and numerous white matter and cingulum bundle.8–10 Performing a meta-
cerebral morphological and functional abnormalities have analysis is a powerful way to integrate the results from many
been reported in patients with BD.3 studies in an unbiased way.11 Therefore, using voxel-based
Correspondence to: Q. Gong, Huaxi MR Research Center and Department of Radiology, West China Hospital of Sichuan University, Chengdu,
610041, China; qiyonggong@hmrrc.org.cn; or M. He, Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, 610031, China;
manxi_he@qq.com
*These authors contributed equally to the work.
Submitted Nov. 2, 2017; Revised Feb. 10, 2018; Accepted Feb. 26, 2018
DOI: 10.1503/jpn.170221
© 2018 Joule Inc. or its licensors
J Psychiatry Neurosci 1Yang et al.
meta-analysis to detect common abnormalities in patients with tant clinical and demographic factors of BD. The third aim
BD from multiple original studies is of particular importance. was to perform a multiple meta-regression analysis to explore
To our knowledge, there have been 3 published voxel-wise the potential effects of demographic and clinical characteristics
whole-brain meta-analyses of pertinent DTI studies on BD.12–14 on white-matter microstructural differences, taking advantage
However, these reviews had some technical limitations. First, of AES-SDM’s ability to control for moderators.
all 3 studies integrated both voxel-based analysis (VBA) and
tract-based spatial statistics (TBSS) techniques to compare Methods
white-matter abnormalities between patients with BD and
healthy controls. Although VBA and TBSS both explore whole- Inclusion of studies
brain white-matter alterations, they have inherent methodo
logical differences that make combined meta-analysis problem- We conducted our meta-analysis according to the Preferred
atic. Voxel-based analysis is relatively straightforward and Reporting Items for Systematic Reviews and Meta-Analyses
involves spatial normalization of high-resolution images from (PRISMA) guidelines. 23 We searched PubMed, Web of
all studied participants to the same stereotactic space.15 The Knowledge, MEDLINE, PsycINFO, ERIC, CINAHL,
TBSS technique was specifically developed to analyze diffusion Google Scholar and Embase using the following keywords
data, and it restricts analysis to the centre of major white-matter to identify relevant articles published up to May 2017: DTI
tracts by projecting each participant’s FA data onto the mean < OR > diffusion tensor imaging < OR > TBSS < OR > tract-
skeleton, minimizing the misalignment problems that can arise based spatial statistics < OR > fractional anisotropy; and bi-
from regular VBA16 and arguably making TBSS a more accurate polar disorder < OR > bipolar depression < OR > mania.
technique for detecting white-matter abnormalities. Second, We also manually checked the reference lists of the re-
given the limited number of reported DTI studies, these previ- trieved articles for additional relevant studies.
ous meta-analyses were unable to consider the potentially dif- The inclusion criteria for the study selections were as fol-
ferent neural alterations in patients with BD I and BD II, or the lows: studies that compared whole-brain FA alteration be-
influence of the mood state (manic, depressed or euthymic) tween patients with BD (diagnosed according to DSM-IV cri
during MRI scanning. Some of the inconsistencies in reported teria) and healthy controls; studies that used the TBSS
white-matter findings may be due to different selection of pa- approach for DTI data analysis; studies that reported Montreal
tient subtypes. For example, Versace and colleagues17 reported Neurological Institute or Talairach coordinates of the whole
FA increases in the left uncinate fasciculus, left optic radiation brain contrast of FA; studies that were published in English in
and right anterothalamic radiation, and FA decreases in the a peer-reviewed journal; and studies that used significance
right uncinate fasciculus in patients with BD I compared with thresholds for data that were either corrected for multiple
healthy controls. Including patients with both BD I and BD II, comparisons or uncorrected with spatial extent thresholds.
Haller and colleagues18 reported FA decreases in the ventral The exclusion criteria were as follows: studies that were
part of the corpus callosum compared with healthy controls. case reports or reviews; studies that provided 3-dimensional
Ambrosi and colleagues19 reported lower FA in the right infer coordinates in stereotactic space (Montreal Neurological In-
ior longitudinal fasciculus in patients with BD II compared with stitute or Talairach) were unavailable; studies that reported
patients with BD I. These different results may reflect different fewer than 10 participants in either the BD or healthy control
neural pathophysiologies in BD I and BD II, so it is important to groups; studies in which the patients were explicitly re-
identify their separate neurobiological markers. Now that more cruited to have multiple combined axis I diagnoses; and the
TBSS studies have reported results taking BD subtypes into presence of sample overlap with other included studies of
consideration, the time is ripe to conduct an updated TBSS larger sample sizes.
meta-analysis to explore how these factors influence white-
matter microstructural abnormalities in patients with BD. Quality assessment and data extraction
The first aim of this study was to conduct a meta-analysis to
identify the most prominent and replicable white-matter Two authors (C.Y. and L.L.) independently searched the liter-
microstructural abnormalities associated with BD. We used ature, assessed the quality of the retrieved articles and ex-
anisotropic effect size–signed differential mapping (AES- tracted and cross-checked the data. In cases of disagreement,
SDM), a recently developed meta-analytic technique with the another author mediated until consensus was obtained. We
potential to quantify the reproducibility of neuroimaging assessed study quality using a 12-point checklist (see Appen-
findings.20 This technique enables the results from individual dix 1, Table S1, available at jpn.ca/170221-a1) adapted from
studies to be weighted and controlled for multiple modera- previous meta-analyses24 that considered not only the demo-
tors, including demographics, clinical information and im graphic and clinical characteristics of individual study par
aging factors. It has the additional advantage that all informa- ticipants (items 1 to 4), but also the specific imaging method-
tion from contributing studies is used in the same map, ology (items 5 to 10) and the consistency of the conclusions
including positive, negative and null results. The AES-SDM and the results (items 11 and 12). Each item was given a score
technique has been successfully applied in other neuropsychi- of 1, 0.5 or 0 to indicate whether the criteria were fully met,
atric studies using TBSS, including major depressive disorder partially met or unfulfilled, respectively.
and attention-deficit/hyperactivity disorder.21,22 The second We extracted the following data from each selected study:
aim was to perform subgroup meta-analyses based on impor- the characteristics of the participants and their illness (sample
2 J Psychiatry NeurosciPsychoradiologic abnormalities of white matter in bipolar disorder
size, mean age of participants, sex, age at onset, illness dura- licated. If a brain region remained significant in all or most of
tion, symptom severity, diagnosis type, drug status, mood the combinations of studies, we considered the finding to be
states and comorbidities); magnetic resonance methodology highly replicable.26
(magnetic field strength, acquisition voxel size, number of When the sample size was sufficient, we conducted sensi-
diffusion directions and type of analysis); statistical method- tivity subgroup analyses to test the robustness of the statis-
ology (statistical threshold and correction methods for multi- tically significant findings by excluding studies with poten-
ple comparisons); and 3-dimensional coordinates (for voxel- tial confounds on a one-off basis. We performed subgroup
level quantitative meta-analyses). analyses of patients with BD I or BD II; with psychotic or
nonpsychotic symptoms; during euthymic, depressed or
Voxel-wise meta-analysis: AES-SDM mania status; and of adult or pediatric patients compared
with healthy controls separately if sufficient data sets were
For the voxel-wise meta-analysis of the selected studies to available. We also conducted a subgroup meta-analysis of
detect FA differences in white matter between patients with studies with corrected results. We conducted jackknife sensi-
BD and healthy controls, we used AES-SDM (www. tivity analysis for each subgroup result.
sdmproject.com). 20 The AES-SDM technique uses effect
sizes to combine reported peak coordinates that are ex- Meta-regression analysis
tracted from databases with statistical parametric maps, and
it recreates original maps of the effect size of FA difference We performed meta-regression analyses using age, percent-
in white matter between patients and controls. We per- age of female patients, symptom severity (Hamilton Depres-
formed the analysis as described in the AES-SDM tutorial sion Rating Scale28), age at onset and illness duration in each
and related publications. 25 We used MRIcron software study as the independent variables. We could not study non-
(www.mricro.com/mricron/) to visualize AES-SDM maps drug therapy status because of a lack of reported data. We
overlaid on 3 subgroup analyses onto a high-resolution could not explore symptom severity as rated by the Young
brain template generated by the International Consortium Mania Rating Scale29 by meta-regression because there were
for Brain M apping. only 6 data sets. The results were weighted by the square
The AES-SDM methods are briefly summarized here but root of the sample size. To minimize the reporting of spuri-
have been described in detail elsewhere.26,27 First, from each ous relationships, we selected a more conservative threshold
data set we extracted the peak coordinates of all white-matter of p = 0.0005 as used in previous studies,20 requiring abnor-
differences at the whole-brain level, and the t values or z- malities to be detected both in the slope and in one of the ex-
scores of the regions. We converted z-scores for significant tremes of the regressor, and discarding findings in regions
clusters straightforwardly to t statistics using an online con- other than those detected in the main analyses. We displayed
verter. Studies reporting no group differences were also in- the main output for each variable in a map of the regression
cluded. To avoid any potential bias toward liberally thresh- slope. Finally, we visually inspected regression plots to dis-
olded regions, we excluded the peaks that did not appear card fittings that were obviously driven by too few studies.26
statistically significant at the whole brain level.26 Second, we
recreated the peak coordinates for each study using a stan- Analysis of heterogeneity and publication bias
dard Montreal Neurological Institute map of the effect size of
the group differences in FA by means of an anisotropic Heterogeneity refers to between-study variations. We con-
Gaussian kernel. We used a relatively wide full width at half ducted a between-study heterogeneity analysis of individual
maximum (20 mm) and DTI fractional anisotropy (TBSS) clusters using a random-effects model with Q statistics, with
templates to control false-positive results. Findings from thresholds of p = 0.005, peak Z = 1.00 and a cluster extent of
studies that reported no group difference were also recreated 10 voxels. Areas showing significant heterogeneity that
with effect-size maps, the difference being that all voxels in also overlapped with the main findings were explored
the effect-size group were estimated to have a null effect using meta-regression analyses to understand the sources
size. Third, we conducted standard meta-analysis to create a of between-study variability. We also assessed publication
mean map via voxel-wise calculation of the random-effects bias by testing funnel plots using the Egger test via STATA
mean of the study maps, taking into account sample size, (www.stata.cn), in which any result showing p < 0.05 was
intrastudy variance and between-study heterogeneity. The regarded as having significant publication bias.
analytical parameters of the AES-SDM were as follows:
voxel threshold p = 0.005, peak height threshold Z = 1.00 and Fibre tracking
cluster size threshold = 100 voxels.
We used DTIquery software (http://graphics.stanford.edu/
Jackknife sensitivity analysis and subgroup analysis projects/dti/) and an atlas of human white-matter anatomy30
to help identify the most probable white-matter tracts pass-
To assess the robustness of the findings, we conducted a sys- ing through the clusters of voxels that showed significant FA
tematic whole-brain voxel-based jackknife analysis, in which group difference. We used the sample data of a healthy
we iteratively repeated the analysis, excluding 1 data set at a 35-year-old male provided by the DTIquery software. We
time to establish the extent to which the results could be rep- mapped the white-matter tracts using streamline tracking
J Psychiatry Neurosci 3Yang et al.
techniques and filtered them by tract length and a box- control group. For these 4 studies, we treated each subgroup
shaped region of interest centred on the coordinates of sig comparison as an independent data set.
nificant clusters. The demographic and clinical characteristics of the samples
are reported in Table 1. Of the 556 patients, 57 (10.3%) were
Results in a manic state at the time of scanning, 162 (29.1%) were in a
depressive state, and 232 (41.7%) were euthymic; the mood
Included studies and sample characteristics states of 105 (18.9%) were not reported. The patients included
411 with BD I, 87 with BD II and 58 whose BD subtype was
Systematic search of the databases yielded 883 English re- not mentioned. A total of 165 patients (29.7%) were reported
search papers. Of these, 18 whole-brain TBSS studies with to have comorbidities, which included substance abuse,
22 data sets met our inclusion criteria. Figure 1 shows the panic disorder, anxiety disorder, posttraumatic stress disor-
flow diagram of selection of studies. The included studies der, obsessive–compulsive disorder and attention-deficit/
compared FA differences in white matter between 556 pa- hyperactivity disorder, among others. Of the 18 DTI studies,
tients with BD (mean age 38.2 yr) and 623 healthy controls 2 studies43,44 involved 36 adolescents with BD.
(mean age 39.3 yr). Four studies reported subgroup compari-
sons: 1 study31 compared drug-free patients with BD and pa- Pooled meta-analysis of all included studies
tients treated with lithium alone with the same healthy con-
trol group; another study32 compared patients with BD (with The pooled meta-analysis of the 22 data sets with 71 clusters
and without a history of suicide attempts) with the same revealed decreased FA in the genu of the corpus callosum
healthy control group; and 2 studies19,33 compared subgroups and 2 clusters in the body of the corpus callosum in all pa-
of patients with BD (BD I and BD II) with the same healthy tients with BD compared with healthy controls (Fig. 2 and
Articles identified through Additional articles identified
the database search through other sources
n = 883 n=0
Records after duplicates removed
n = 298
Articles screened
n = 298
Articles excluded:
Not relevant diseases = 70
Reviews and letters = 51
Full text assessed for eligibility
n = 177
Articles excluded:
Not TBSS approach = 65
ROI approach = 40
Animal sample = 32
Articles included in the quantitative synthesis
Not compared with healthy
n = 18
controls = 19
No coordinates reported = 3
Fig. 1: Flow diagram for the identification and exclusion of studies. ROI = region of interest; TBSS = tract-based spatial statistics.
4 J Psychiatry NeurosciTable 1: Demographic and clinical characteristics of the participants in the 18 studies (22 data sets) included in the meta-analysis (part 1 of 2)
Participants, n
(females) Age, yr Age at
onset, Illness Severity (scale Statistical Quality
Study BD HC BD HC yr duration, yr type) Diagnosis threshold Drug states Mood states Comorbidity* scores
Ambrosi et al., 25 (12) 50 (24) 48.6 48.3 NA 20.3 9.2 (HAMD) BD I p < 0.008 10 AD, 16 AP, NA NA 11.5
BD I19 (multiple 11 AE, 16 Li,
comparison) 6 BDZ
Ambrosi et al., 25 (12) 50 (24) 48.3 48.3 NA 23.9 14.5 (HAMD) BD II p < 0.008 6 AD, 12 AP, NA NA 11.5
BD II19 (multiple 14 AE, 10 Li,
comparison) 13 BDZ
Versace et al.17 31 (20) 25 (14) 35.9 29.5 25.4 12.3 RBD 2.1, DBD BD I p < 0.05 5 Li, 12 MS, 17 euthymic, NA 11.5
15.2 (HAMD) (multiple 8 AP, 7 AD, 14 depressed
comparison) 7 BDZ
Kumar et al.34 22 (7) 41 (11) 34.7 33.2 NA 10.7 8.57 (SSPI) BD pTFCE < 0.05 55 on NA NA 11
medications,
including AP
and MS
Delaloye et al.35 15 (NA) 15 67.9 68.3 34.1 33.8 1.00 (YMRS) BD pTFCE < 0.05 10 MS, 3 AD, Euthymic NA 10.5
(NA) 6 BDZ, 4 NL
Haller et al.18 19 (14) 47 (22) 68.5 69.8 39.4 29.2 0.95 (YMRS) BD I pTFCE < 0.05 15 MS, 5 AP, Euthymic NA 11.5
BD II 7 BDZ, 5 NL,
3 UM
Benedetti et al., 26 (17) 21 (10) 45.1 39.9 31.6 13.5 20.1 (HAMD) BD I pTFCE < 0.05 26 UM Depressed NA 11
FREE31†
Benedetti et al., 14 (11) 21 (10) 47.8 39.9 31.1 17.6 19.1 (HAMD) BD I pTFCE < 0.05 14 Li Depressed NA 11
J Psychiatry Neurosci
TREAT31†
Chan et al.36 16 (4) 16 (4) 36.9 37.3 NA 0.2 3.8 (YMRS) BD I p < 0.001 6 Li, 7 MS Euthymic NA 11
(uncorrected) (sodium
valproate),
12 AP
Lagopoulos et 58 (41) 40 (24) 23.0 24.1 15.4 7.5 13.4 (HAMD) BD I, pFWE < 0.05 25 AD, 23 MS, Depressed NA 11.5
al.37 BD II, 37 AP, 8 UM
spectrum
Mahon et al., 14 (5) 15 (7) 33.3 33.7 20.8 12.5 6.8 (HAMD) BD I pFWE < 0.05 10 MS, 6 AP, NA Yes 10.5
SU32† 3 UM
Mahon et al., 15 (6) 15 (7) 36.5 33.7 24.8 11.7 5.4 (HAMD) BD I pFWE < 0.05 14 AP, 14 MS NA Yes 10.5
NSU32†
Sprooten et al.38 64 (46) 46 (31) 31.7 30.1 18.0 10.0 2.0 (HAMD) BD I pFWE < 0.05 34 MS, 28 AD, Euthymic Yes 12
23 AP, 12 Li,
11 UM
Versace et al.39 15 (14) 24 (15) 36.3 27.7 21.6 14.7 14.9 (HAMD) BD I pTFCE < 0.05 10 MS, 10 AP, Depressed NA 11.5
8 AP, 6 BDZ
Wessa et al.40 22 (11) 21 (9) 45.4 43.0 23.0 22.0 0.1 (HAMD) BD I, pFDR < 0.05 10 Li, 11 AC, Euthymic Yes 10.5
BD II 6 AD, 5 AP,
4 UM
5
Psychoradiologic abnormalities of white matter in bipolar disorder6
Yang et al.
Table 1: Demographic and clinical characteristics of the participants in the 18 studies (22 data sets) included in the meta-analysis (part 2 of 2)
Participants, n
(females) Age, yr Age at
onset, Illness Severity (scale Statistical Quality
Study BD HC BD HC yr duration, yr type) Diagnosis threshold Drug states Mood states Comorbidity* scores
Liu et al., BD I33 14 (7) 21 (13) 35.6 38.3 NA 7.3 6.7 (HAMD) BD I p < 0.001 2 Li, 12 AC, 7 manic, NA 11
(uncorrected) 12 AD, 1 AP 7 depressed
Liu et al., BD II33 13 (11) 21 (13) 35.1 38.3 NA 9.4 9.5 (HAMD) BD II p < 0.001 10 AC, 10 AD, 5 manic, NA 11
(uncorrected) 1 AP 8 depressed
Magioncalda et 61 (43) 42 (27) 44.6 44.3 25.1 19.6 6.9 manic, BD I pTFCE < 0.01 52 MS, 22 AD, 21 manic, NA 11.6
al.41 21.5 depressed, 35 AP, 21 BDZ, 20 depressed,
3.6 euthymic 2 UM 20 euthymic
(HAMD)
Oertel-Knochel 30 (14) 32 (16) 39.2 39.2 NA 10.2 NA BD I pTFCE < 0.01 24 MS, 12 AD, Euthymic NA 10.5
et al.42 13 NL, 5 AL
Gao et al.43 18 (12) 18 (12) 15.1 14.1 13.8 1.3 33.4 (YMRS) BD I, pTFCE < 0.05 2 UM, 8 VP, Manic Yes 11
BD II 7 Li, 13 AP,
3 AD
Teixeira et al.44 18 (6) 20 (6) 12.3 12.7 9.5 2.8 8.7 (YMRS) BD I, pTFCE < 0.05 All UM 6 manic, Yes 11
BD II, 8 euthymic,
BD NOS‡ 4 mixed
J Psychiatry Neurosci
Haarman et al.45 21 (12) 22 (11) 44.7 38.2 19.5 25.2 0.2 (YMRS) BD I pTFCE < 0.05 Medicated Euthymic No 11.5
AC = anticonvulsant; AD = antidepressant medication; AE = antiepileptic medication; AL = anxiolytics; AP = antipsychotic medication; BD = bipolar disorder; BDZ = benzodiazepine; DBP = depressed with bipolar disorder; FDR = false
discovery rate; FWE = family-wise error corrected; HAMD = Hamilton Depression Rating Scale; HC = healthy controls; Li = lithium; MS = mood-stabilizing medication; NA = not available; NL = neuroleptics; NOS = not otherwise specified;
RBD = remitted with bipolar disorder; SSPI = Signs and Symptoms in Psychotic Illness scale; TFCE = threshold-free cluster enhancement; UM = unmedicated; VP = valproate; YMRS = Young Mania Rating Scale.
*Comorbidity:
Mahon et al., SU: substance abuse or dependence (n = 3), anorexia nervosa (n = 1), panic disorder with (n = 1) and without (n = 1) a history of agoraphobia, anxiety disorder NOS (n = 2), posttraumatic stress disorder (n = 2),
generalized anxiety disorder (n = 1), specific phobia (n = 1) and bulimia nervosa (n = 1).
Mahon et al., NSU: substance abuse or dependence (n = 5), obsessive−compulsive disorder (n = 1) and agoraphobia without a history of panic disorder (n = 1).
Sprooten et al.: anxiety disorder (n = 30), alcohol use disorder (n = 33), substance use disorder (n = 29), nicotine dependence, current (n = 21).
Gao et al.: anxiety (n = 1), attention-deficit hyperactivity disorder (n = 1), obsessive−compulsive disorder (n = 2).
Teixeira et al.: attention-deficit/hyperactivity disorder (n = 9), oppositional defiant disorder (n = 5), generalized anxiety disorder (n = 3), conduct disorder (n = 2), simple phobia (n = 2), posttraumatic stress disorder (n = 2), panic
disorder (n = 1), separation anxiety disorder (n = 1), obsessive–compulsive disorder (n = 1) and Tourette syndrome (n = 1).
Wessa et al.: panic disorder (n = 1).
†
FREE indicates that the study includes a subgroup of drug-free patients with BD. TREAT indicates that the study includes a subgroup of lithium-treated patients with BD. SU indicates that the study includes subgroup of patients with a
previous suicide attempt. NSU indicates that the study includes subgroup of patients without a previous suicide attempt.
‡
Children and adolescents were diagnosed as BD NOS if they presented with clear manic or hypomanic episodes with elation and/or grandiosity but lacked the duration needed to be classified as BD I or BD II.Psychoradiologic abnormalities of white matter in bipolar disorder
Table 2). No regions with increased FA were found. The Subgroup meta-analysis
white-matter tracts running through these 3 regions provide
interhemispheric connections to the prefrontal, orbitofron- The subgroup meta-analysis of the studies of patients with
tal, inferior temporal and superior parietal cortices (Fig. 3). BD I included 13 data sets that compared 346 patients with
These results showed no significant between-study hetero- BD I to 350 healthy controls. The FA in patients with BD I
geneity. Extraction of funnel plots revealed no publication was decreased in the genu of the corpus callosum relative to
bias. The Egger test showed no significant publication bias that of healthy controls (Table 3). We were unable to conduct
in the genu (Egger p = 0.62) or in the anterior (Egger p = subgroup meta-analyses of the studies of patients with BD II
0.99) or posterior (Egger p = 0.23) parts of the body of the compared with either healthy controls or patients with BD I
corpus callosum. because of the limited number of data sets.
As shown in Table 3, the whole-brain jackknife sensitivity The subgroup meta-analysis of euthymic patients with BD
analysis of the pooled meta-analysis found that all 3 clusters included 7 data sets that compared 187 euthymic patients with
were highly replicable. The most robust cluster was found in BD to 199 healthy controls. Relative to controls, patients in the
the left genu of the corpus callosum, which was preserved euthymic state exhibited decreased FA in the body of the cor-
throughout all 22 combinations of the data sets. The other 2 re- pus callosum (Table 3). We were unable to conduct subgroup
sults in the body of the corpus callosum remained significant meta-analyses of manic or depressed patients compared with
in all but 2 and 7 combinations of the data sets, respectively. healthy controls because of the limited number of data sets.
A B
a1
a2
a3
Fig. 2: Results of pooled meta-analysis. Panel A shows the coronal and sagittal view showing decreased fractional anisotropy in
patients with bipolar disorder versus healthy controls in the genu of corpus callosum (a1), the posterior of the body of corpus
callosum (a2) and the anterior of the body of corpus callosum (a3). Panel B shows the most probable white-matter tracts passing
through 3 clusters of voxels (−10, 28, 16; −18, −32, 32; and 16, −6, 36) in 3-dimensional images using DTIquery.
J Psychiatry Neurosci 7Yang et al.
The subgroup meta-analysis of adult patients with BD prevented the detection of white-matter abnormalities when
(age > 18 yr) included 20 data sets that compared 520 adult comparing patients with BD with or without psychosis.
patients with BD to 585 healthy controls. The adult patients The subgroup jackknife sensitivity analyses of bipolar
had decreased FA in the genu and the body of the corpus subtypes, mood states and adult participants, as well as the
callosum, sharing 2 clusters with the results of the pooled corrected studies, found the meta-analysis results to be
meta-analysis (Table 3). We were unable to conduct sub- highly replicable when focusing only on the BD I, euthymic,
group meta-analysis of adolescent patients because of a lack adult and corrected subgroups.
of data sets.
The subgroup meta-analysis of the studies with cor- Meta-regression analysis
rected results included 19 data sets that compared 513 pa-
tients with BD and 565 healthy controls. The results were The results of the meta-regression analysis showed that the
consistent with the pooled meta-analysis (Appendix 1, percentage of female patients with BD driven by 21 data
Table S2), showing few effects of the uncorrected results on sets was negatively associated with FA reduction in the
the overall conclusions. body of the corpus callosum (Fig. 3). However, the results
Only 5 included studies34,37,38,43,44 reported white-matter should be interpreted with some caution, because they were
alterations in patients with BD and psychosis. One study in- seemingly driven by 2 outlier studies with very high site ef-
cluded only BD patients with psychosis, and the other 4 re- fects. 37,38 We detected no effect of Hamilton Depression
ported only the percentage of patients with psychosis and Rating Scale score, mean age, age at onset or illness dura-
did no subgroup analysis. The limited number of studies tion on white-matter alterations.
Table 2: Clusters of fractional anisotropy reductions in patients with bipolar disorder relative to healthy controls
Maximum Cluster
MNI coordinates SDM Number of
Region x, y, z Z value p value voxels Breakdown (number of voxels)
Genu of corpus callosum –10, 28, 16 –2.209 ~0 388 Corpus callosum (321)
Left striatum (21)
Left anterior thalamic projections (20)
Left inferior fronto-occipital fasciculus (15)
Left cingulum (11)
Body of corpus callosum –18, –32, 32 –2.470 ~0 180 Corpus callosum (125)
Left cingulum (43)
Left superior longitudinal fasciculus (12)
Body of corpus callosum 16, –6, 36 –1.303Psychoradiologic abnormalities of white matter in bipolar disorder
Table 3: Results of jackknife analysis and subgroup analysis from 18 studies (22 data sets) included in the meta-analysis*
Analysis Region of FA reduction: Region of FA reduction: Region of FA reduction:
genu of corpus callosum body of corpus callosum body of corpus callosum
Jackknife sensitivity analysis
Excluding Wessa et al.40 Yes Yes Yes
Excluding Versace et al.17 Yes Yes Yes
Excluding Chan et al.36 Yes Yes Yes
Excluding Benedetti et al., FREE31 Yes Yes No
Excluding Benedetti et al., TREAT31 Yes Yes Yes
Excluding Haller et al.18 Yes Yes Yes
Excluding Delaloye et al.35 Yes Yes No
Excluding Mahon et al., SU32 Yes Yes Yes
Excluding Mahon et al., NSU32 Yes Yes No
Excluding Gao et al.43 Yes No No
Excluding Sprooten et al.38 Yes Yes Yes
Excluding Oertel-Knochel et al.42 Yes Yes Yes
Excluding Lagopoulos et al.37 Yes Yes No
Excluding Teixeira et al.44 Yes Yes Yes
Excluding Ambrosi et al., BD I19 Yes Yes Yes
Excluding Ambrosi et al., BD II19 Yes No No
Excluding Magioncalda et al.41 Yes Yes No
Excluding Versace et al.39 Yes Yes Yes
Excluding Kumar et al.34 Yes Yes Yes
Excluding Liu et al., BD I33 Yes Yes Yes
Excluding Liu et al., BD II33 Yes Yes Yes
Excluding Haarman et al.45 Yes Yes Yes
Subgroup analysis
studies with adult BD Yes Yes No
Studies with BD I Yes No No
Studies with euthymic-state BD No Yes No
BD = bipolar disorder; FA = fractional anisotropy.
*“Yes” indicates that the specific region of FA reduction was significant in the specific jackknife analysis and subgroup analysis; “No” indicates that the specific region of FA reduction was
not significant in specific analysis.
Discussion losum in patients with BD compared with healthy controls, a
result that was consistent with those of 2 other DTI studies
The current study pooled the largest number of TBSS studies using a region-of-interest method focusing on the corpus cal-
to date in patients with BD to conduct a quantitative meta- losum.49,50 This brain region has been increasingly implicated
analysis. To the best of our knowledge, no similar work has in patients with BD: for example, a multicentre structural
been reported, especially regarding the clinical and demo- MRI study reported a decrease in the mid-sagittal area of the
graphic effects of BD subtypes, psychotic features, mood body of the corpus callosum in patients with BD compared
states, age and sex. Voxel-wise meta-analysis using AES- with healthy controls.51 It is tempting to speculate that im-
SDM revealed that patients with BD have decreased FA in paired interhemispheric communication is important in the
the genu of the corpus callosum and in 2 clusters in the body pathophysiology of BD. The recent meta-analysis by Wise
of the corpus callosum; these results were robust under jack- and colleagues14 reported that patients with BD showed de-
knife analysis. We found a significant negative association creased FA in the left cingulum, the left genu of the corpus
between the percentage of female patients and the FA in the callosum and the right anterior superior longitudinal fascicu-
body of the corpus callosum. Subgroup analyses of the BD I lus compared with healthy controls. Our findings are not
studies, euthymic studies and adult studies reproduced the completely consistent with those of previous meta-analyses,
significant findings of decreased FA in the genu and the body because we found no significant abnormalities in any tracts
of the corpus callosum. These results suggest that abnormal other than the corpus callosum. There are several possible rea-
ities in white-matter tracts may be involved in the patho sons for this. First, previous meta-analyses included both TBSS
logical mechanisms of BD. and VBA studies, whereas we only included TBSS studies,
The corpus callosum is the largest white-matter bundle because there is reason to believe that these can more accu-
that connects the bilateral cerebral hemispheres, integrating rately identify white-matter abnormalities.16 Second, we were
emotional, cognitive, motor and sensory functions.46–48 We able to include many more TBSS studies than the previous
found decreased FA in the genu and body of the corpus cal- meta-analyses, increasing the precision of effect-size estimates.
J Psychiatry Neurosci 9Yang et al.
Third, the clinical samples in our included studies differed in the corpus callosum connects several areas, including the lat-
detail from those in previous meta-analyses. eral primary motor cortex, supplementary motor areas
The white-matter fibres passing through the genu of the (SMA), the primary sensory cortex and the parietal cortex.80
corpus callosum connect the bilateral prefrontal cortices, Previous functional studies have shown that the rostral part
which are known to play a role in decision-making, attention, of the SMA (the pre-SMA) is involved in memory storage,
reward-processing and emotion regulation.52,53 Previous learning, transition, and motor and speech control, and the
structural studies found decreased volume in both the ven- pre-SMA connects to the cingulated gyrus, which is part of
tral and dorsal prefrontal cortex in patients with BD,54,55 and the limbic system related to cognitive and emotional regula-
several functional studies have observed decreased dorsal tion, while the caudal part of the SMA, the SMA proper and
and ventral prefrontal activity in patients with BD during the primary motor area are responsible for motor function.81
language tasks and executive-related tasks.56,57 Additionally, Together, the SMA may be a transitional region of the limbic
several studies have reported that the ventral prefrontal cor- and motor system, which plays an important role in the
tex is implicated in the “top–down” regulation of emotional translation of emotion into motor actions.81 Although emo-
processing in patients with BD.58,59 The FA reduction in the tional dysfunction is one of the main symptoms of BD, previ-
genu of the corpus callosum in the present study suggests ous studies have shown that patients with BD also have
impaired prefrontal interhemispheric connectivity, perhaps motor impairments such as psychomotor retardation,82 agita-
leading to neurocognitive deficits in processing speed and tion,83 attentional deficits and impairments in fine-motor
working memory,60 for example, and to emotional dysregula- skills.84–87 We therefore suggest that the FA decrease in the
tion in patients with BD. Our subgroup analysis of patients body of the corpus callosum might be related to motor and
with BD I reproduced the finding of decreased FA in the emotional dysfunction in patients with BD. Interestingly, our
genu of corpus callosum compared with healthy controls, subgroup analyses of euthymic patients with BD and adult
which was consistent with the findings of some previous DTI patients with BD replicated the FA decrease in the body of
studies.61,62 There are clinical differences between BD I and the corpus callosum. This finding was consistent with 1 pre-
BD II. In DSM-5, BD I is the classic manic–depressive disor- vious study, which found that euthymic patients with BD
der, while BD II features depressive and hypomanic epi- had decreased FA in the body of the corpus callosum com-
sodes; furthermore, the clinical manifestations and treat- pared with unaffected siblings.73 Several studies have re-
ments of BD I and BD II are different.63,64 The FA reduction in ported that brain structural and functional abnormalities are
the genu of the corpus callosum reflected a disconnection of related to current mood states in patients with BD.88,89 Our re-
the paralimbic system, which plays a central role in emo- sults may indicate a persistent callosal dysconnectivity in
tional regulation,3,65 and might lead to manic-type behaviours euthymic patients with BD, which is consistent with the ob-
such as inappropriate euphoria, excessive psychomotor be- servation that cognitive impairment and executive dysfunc-
haviour, hypersexuality and paranoia, consistent with the tion still exist in euthymic patients with BD.90,91
clinical characteristics of patients with BD I.65 Meta-regression analysis found that FA in the body of the
The pathobiological interpretation of FA reduction is com- corpus callosum (decreased overall in patients with BD com-
plex, because it can be influenced by many factors, such as re- pared with healthy controls) was negatively associated with
gional myelination levels, intra- and extracellular volume, the the percentage of female patients. This result may indicate
degree of intra-voxel fibre crossing, axonal density and aver- that female patients have lower FA values in the body of the
age axonal diameter.66 Previous studies have suggested that corpus callosum than male patients. Sex differences have been
abnormalities in the corpus callosum that are detected early in observed in the clinical characteristics of BD. Female patients
pediatric patients with BD may be due to altered myelination with BD may be more likely to have comorbidities and de-
during neurodevelopment.67 Meanwhile, several studies have pressive symptoms, which may result in high suicide risk and
reported a reduction of myelin-producing oligodendrocytes impaired occupational function.2 The sex differences of FA in
in the prefrontal cortex in patients with BD.68–70 The genu of the body of the corpus callosum may be related to differences
the corpus callosum and the prefrontal cortex are both late- in the clinical aspects of BD. A series of morphological studies
myelinating areas and are therefore more vulnerable to dam- reported a smaller corpus callosum in female patients than in
age than the early-myelinating splenium.71–73 We speculate male patients with BD.92–94 However, 1 study reported no sig-
that the FA reduction in the genu of the corpus callosum may nificant difference in the integrity of the body of the corpus
be related to a reduction of myelination and may result in a callosum when comparing male with female patients with
pathobiological process that directly slows the transfer of BD.67 These inconsistencies may have resulted from different
interhemispheric information in patients with BD.47 To help demographic characteristics, data acquisition methods and
confirm this hypothesis, further studies with more DTI indi- other confounding factors in studies of patients with BD.
ces, such as axial diffusivity and radial diffusivity, would be Medication exposure is an important potential con-
useful, because there is evidence from animal studies that founder, and understanding the effect of medications on
axial diffusivity is primarily an axonal marker and radial dif- white-matter abnormalities in patients with BD is critical for
fusivity is primarily a myelin marker.74–76 the interpretation of results. Because only 1 primary study
Our finding of decreased FA in the body of the corpus cal- enrolled unmedicated patients with BD, we could not ex-
losum in patients with BD compared with healthy controls clude the confounding influences of medication. Several im-
was consistent with several previous studies.77–79 The body of aging studies have evaluated the effect of psychotropic
10 J Psychiatry NeurosciPsychoradiologic abnormalities of white matter in bipolar disorder
edications on white-matter changes in patients with BD.
m the pathophysiology of BD. Subgroup analyses found white-
One structural MRI study reported larger bilateral temporal matter structural differences in patients with BD I, and in
lobe white-matter volumes in patients with BD who were adult and euthymic patients. Furthermore, the results of the
taking antipsychotic medications than in patients who were meta-regression analysis shed light on the structural under-
not taking them.95 Among patients with BD, longer duration pinnings of the sex differences in the clinical manifestations
of lithium treatment is associated with increased FA, sug- of patients with BD. In future studies, attention should be
gesting that this medication might enhance white-matter in- given to differences in clinical type, mood state, and demo-
tegrity.96 In another study, decreased FA was found in partic- graphics to better define neural mechanisms in patients with
ipants treated with lithium, but not in those who were BD. Differentiating mood- and type-related white-matter ab-
unmedicated; however, there was no significant difference normalities is important for elucidating the core pathophysi-
when directly comparing lithium-using and non-lithium- ology of BD and will give better insight into the nature of the
using patients.31 It has been reported that lithium and other disease. The present study also adds to the development of
mood stabilizers can improve white-matter integrity and psychoradiology, the branch of radiology that applies clinical
promote myelination by acting on neuroglial signalling path- imaging to psychiatry and psychology.100–103
ways and increasing neurotrophic factors.97,98 Further studies
designed to detect the effect of medication exposure on Acknowledgments: This study was supported by the National Natu-
white-matter changes in patients with BD are needed. ral Science Foundation of China (grant nos. 81621003, 81220108013,
81761128023, 81227002 and 81030027), the National Key Technologies
R&D Program (program no. 2012BAI01B03) and the Program for
Limitations Changjiang Scholars and Innovative Research Team (PCSIRT, grant
no. IRT16R52) at the University of China. Q. Gong acknowledges
First, the participants varied in terms of sociodemographic and support from his Changjiang Scholar Professorship Award of China
clinical characteristics. Although we performed subgroup (award no. T2014190) and American CMB Distinguished Professor-
ship Award (award no. F510000/G16916411), administered by the
analyses of patients with BD I, euthymic patients with BD, and Institute of International Education, in the United States.
adult patients with BD, the limited data sets precluded com-
Affiliations: From the Huaxi MR Research Center (HMRRC), De-
prehensive subgroup analyses (in particular of the important partment of Radiology, West China Hospital of Sichuan University,
contrast between BD I and BD II) and meta-regression analy- China (Yang, Li, Hu, Luo, Lui, Huang, Sweeney, Gong); the Depart-
ses. Further research is needed investigating the contribution ment of Psychiatry, West China Hospital of Sichuan University,
of other clinical characteristics, such as age of onset, comorbid- China (Kuang); the Department of Psychoradiology, Chengdu Men-
ities and disorder severity. Second, the heterogeneity of MRI tal Health Center, China (Kuang, Dai, He); the Liverpool Magnetic
Resonance Imaging Centre (LiMRIC) and Institute of Ageing and
image acquisition — including voxel size, field intensity of the Chronic Disease, University of Liverpool, United Kingdom (Kemp);
magnetic resonance system, diffusion direction and slice thick- the Department of Psychiatry and Behavioral Neuroscience, Univer-
ness — may influence the accuracy of the results of our meta- sity of Cincinnati, Cincinnati, Ohio, United States (Sweeney); and the
analysis. Third, the main meta-analysis included primary Department of Psychology, School of Public Administration, Sichuan
University, China (Gong).
studies, all but 1 of which enrolled medicated patients, so the
confounding influences of medication could not be excluded. Competing interests: None declared.
Fourth, the meta-regression finding that the percentage of fe- Contributors: C. Yang, L. Li, X. Hu and Q. Gong designed the study.
male patients with BD was negatively related to the FA in the C. Yang and L. Li acquired and analyzed the data, which X. Hu,
body of the corpus callosum was driven by 2 outlying studies. Q. Luo, W. Kuang, S. Lui, X. Huang, J. Dai, M. He, G.J. Kemp and
J.A. Sweeney also analyzed. C. Yang, L. Li, X. Hu, Q. Luo, W. Kuang
Fifth, it has been reported that more than 50% of patients with and J. Dai wrote the article, which all authors reviewed. All authors
BD will experience psychotic symptoms in their lifetime, and it approved the final version to be published and can certify that no
is difficult to accurately distinguish BD from other psychiatric other individuals not listed as authors have made substantial contri-
disorders in patients with psychotic symptoms.99 However, butions to the paper.
data limitations precluded a subgroup analysis comparing pa-
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