European Neuropsychopharmacology (2008) 18, 717–722
w w w. e l s e v i e r. c o m / l o c a t e / e u r o n e u r o
Illness duration and total brain gray matter in bipolar disorder: Evidence for neurodegeneration? Benicio N. Frey a , Giovana B. Zunta-Soares b , Sheila C. Caetano c , Mark A. Nicoletti b , John P. Hatch d , Paolo Brambilla b,e,f , Alan G. Mallinger g , Jair C. Soares b,⁎ a
Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada L8P 3B6 Center of Excellence for Research and Treatment of Bipolar Disorder, Department of Psychiatry, UNC School of Medicine, Chapel Hill, NC, USA c Department of Psychiatry, University of Sao Paulo School of Medicine, Sao Paulo, SP, Brazil d Departments of Psychiatry and Orthodontics, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA e Section of Psychiatry, Department of Pathology and Experimental & Clinical Medicine, University of Udine, Udine, Italy f Scientific Institute, IRCCS "E. Medea", Italy g Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA b
Received 21 December 2007; received in revised form 23 April 2008; accepted 28 April 2008
KEYWORDS Bipolar disorder; Brain imaging; Gray matter; Major depressive disorder; Pathophysiology
Abstract Previous studies have suggested that bipolar disorder (BD) is associated with alterations in neuronal plasticity, but the effects of the progression of illness on brain anatomy have been poorly investigated. We studied the correlation between length of illness, age, age at onset, and the number of previous episodes and total brain, total gray, and total white matter volumes in BD, unipolar (UP) and healthy control (HC) subjects. Thirty-six BD, 31 UP and 55 HCs underwent a 1.5 T brain magnetic resonance imaging scan, and gray and white matter volumes were manually traced blinded to the subjects' diagnosis. Partial correlation analysis showed that length of illness was inversely correlated with total gray matter volume after adjusting for total intracranial volume in BD (rp = −0.51; p = 0.003) but not in UP subjects (rp = −0.23; p = 0.21). Age at illness onset and the number of previous episodes were not significantly correlated with gray matter volumes in BD or UP subjects. No significant correlation with total white matter volume was observed. These results suggest that the progression of illness may be associated with abnormal cellular plasticity. Prospective longitudinal studies are necessary to elucidate the long-term effects of illness progression on brain structure in major mood disorders. © 2008 Published by Elsevier B.V.
⁎ Corresponding author. UNC Center of Excellence for Research and Treatment of Bipolar Disorders (CERT-BD), Department of Psychiatry, 10616 Neuroscience Hospital CB#7160, UNC School of Medicine, Chapel Hill, NC 27599-7160, USA. Tel.: +1 919 966 8832. E-mail address:
[email protected] (J.C. Soares). 0924-977X/$ - see front matter © 2008 Published by Elsevier B.V. doi:10.1016/j.euroneuro.2008.04.015
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1. Introduction
2. Experimental procedures
Long-term studies in bipolar disorder (BD) clearly demonstrate that it has a highly recurrent natural course (Judd et al., 2003; Wittchen et al., 2003), with repeated episodes being associated with progressive psychosocial disability (Judd et al., 2005). In addition, early onset of disease (Perlis et al., 2004) and higher number of lifetime episodes (Deister and Marneros, 1993) are associated with poorer outcomes, while both followup and cross-sectional studies demonstrate persistent cognitive impairment (Balanza-Martinez et al., 2005; Robinson and Ferrier, 2006). Multiple recurrences and persistent cognitive dysfunction may be related to neuroanatomical changes (Goldberg et al., 2005; Robinson and Ferrier, 2006). Morphometric neuroimaging studies suggest that BD is associated with structural changes in brain regions that are thought to be involved with mood regulation, such as prefrontal cortex, limbic system (hippocampus and amygdala), thalamus, and basal ganglia (Soares and Mann, 1997; Strakowski et al., 2005). However, the effects of long-term BD course on structural brain volume have not been systematically studied. Brambilla et al. (2001a) found an inverse correlation between age and total gray matter volume in middle-aged individuals with BD but not in healthy controls, suggesting a faster age-related cortical neuronal loss in BD. A study that focused on specific prefrontal subregions showed that illness duration is negatively correlated with left inferior prefrontal gray matter volume in BD patients hospitalized during a manic episode (Lopez-Larson et al., 2002). Furthermore, it has been demonstrated that the duration of BD illness is correlated with smaller left putamen (Brambilla et al., 2001b), but not with caudate (Beyer et al., 2004) or thalamic volumes (Caetano et al., 2001). In this context, there is evidence that the presence of multiple affective episodes is associated with increased ventricular volumes (Strakowski et al., 2002; Brambilla et al., 2001c), but not with gray matter loss in periventricular structures (Strakowski et al., 2002). Taken together, these findings indicate that the course of BD illness is associated with several brain morphological changes. However, whether these changes are specifically related to the recurrence of acute mood episodes or are related to the progression of illness per se remains to be established. In the present study we tested the hypotheses that illness duration, age at onset, and number of previous episodes are correlated with gray and white matter volumes in BD patients, as compared with unipolar patients (UP) and healthy comparison (HC) subjects.
2.1. Subjects
Table 1
The sample consisted of 36 BD patients (mean age ± S.D. = 35.4 ± 10.8 y; age range = 18–61 y; 22 females, 14 males; 29 BD type-I, 7 BD type-II) and 31 UP subjects (mean age ± S.D. = 39.2 ± 11.8 y; age range = 18–58 y; 24 females, 7 males). BD and UP subjects met DSM-IV criteria for bipolar disorder or major depressive disorder, respectively, according to the Structured Clinical Interview for DSM-IV Axis-I (First et al., 1998). Interviews were conducted by trained psychiatrists. All participants were outpatients, and information collected during the interviews was confirmed with relatives and/or friends whenever possible. Length of illness was calculated by subtracting age at first major depressive or manic mood episode, as recorded in the clinical record or reported by the subject or family members, from the subject's current age in years. BD and UP patients had no comorbid Axis-I psychiatric disorder, current medical problems, or alcohol or substance abuse within 6 months preceding the study. None of the participants were currently psychotic. Thirteen (36%) BD and all (100%) UP subjects were off all psychiatric medications for at least 2 weeks and off lithium for at least one month prior to the study intake. The remaining 23 (64%) BD patients were using lithium therapy (mean serum lithium levels ± S.D. = 0.8 ± 0.3 mEq/L), while 2 of those were also using valproate. Demographic characteristics of the sample are detailed in Table 1. Fifty-five HCs (mean age ± S.D. = 34.2 ± 9.6 y; age range = 19–53 y; 28 females, 27 males) were evaluated with the SCID-I, non-patient version, to exclude any Axis-I psychiatric diagnosis. HCs did not have any psychiatric disorders among first-degree relatives. All subjects were free of serious medical conditions. This research was approved by the local ethics committee and all subjects provided written informed consent before entering in the study.
2.2. Brain imaging procedures Magnetic resonance imaging (MRI) scans were obtained in a 1.5 T MRI GE Signa Imaging System, version 5.4.3 software (General Electrics, Milwaukee, WI, USA) at the University of Pittsburgh. A 3D-gradient echo imaging (Spoiled Gradient Recalled Acquisition) was acquired in the coronal plane (TR = 25 ms, TE = 5 ms, nutation angle = 40°, FOV = 24 cm, NEX = 1, matrix size = 256 × 192, slice thickness = 1.5 mm, 124 slices). Total gray and white matter volumes were measured
Demographic characteristics of patients and controls Bipolar subjects (n = 36) Unipolar subjects (n = 31) Healthy subjects (n = 55) p value
Mean age ± S.D. (y) Gender, female Ethnicity, white Handedness, right Mean length of illness ± S.D. (y) Mean age at onset ± S.D. (y) Mean number of previous episodes ± S.D. a
35.4 ± 10.8 22 (61%) 35 (97%) 30 (83%) 15.0 ± 8.2 20.0 ± 6.9 17.4 ± 21.7
One-way ANOVA; bChi-Square test; cMann–Whitney test.
39.2 ± 11.8 24 (77%) 29 (93%) 28 (90%) 11.4 ± 10.6 27.9 ± 11.6 5.6 ± 6.2
34.2 ± 11.6 28 (51%) 47 (85%) 45 (82%) N/A N/A N/A
0.11a 0.054b 0.33b 0.7b 0.033c 0.012c 0.0001c
Illness duration and brain gray matter in bipolar disorder
719 statistical testing was two-sided, and null hypotheses were rejected at the 0.05 level of statistical significance.
3. Results
Figure 1 Partial residual plot showing brain gray matter volume as a function of illness duration, both adjusted for total intracranial volume, for bipolar and unipolar patients. The solid line is the regression line for BP subjects, and the broken line is the regression line for UP subjects. These plots correspond to the partial correlations reported in the text.
using a semi-automated software (Scion Image for Windows Beta 4.02; Scion Corporation Inc., Frederick, MD, USA). Gray matter, white matter, and cerebrospinal fluid (CSF) values were obtained using a histogram method (Keshavan et al., 1995), with the software NIH Image, version 1.62. Manual tracing was performed by two researchers (M.A.N., P.B.) blind to the subjects' status. Intraclass correlation coefficients were 0.98 for intracranial volume, 0.98 for total brain matter volume, 0.98 for total gray matter volume, and 0.94 for total white matter volume. Brain gray matter values (%GM) were obtained by dividing total gray matter volume by total brain matter volume.
BD and UP patients and HCs did not differ significantly in terms of age, gender, educational status, ethnicity, or handedness (all p N 0.05; Table 1). There was a trend for gender differences among the groups (p = 0.054), which was driven by a tendency of the HC subgroup to contain a relatively smaller proportion of females. Age was inversely correlated with gray matter volumes in BD patients (rp = − 0.53, p = 0.001), UP subjects (rp = − 0.56, p = 0.01), and HCs (rp = − 0.37, p = 0.006) after adjusting for ICV. In addition, the partial correlation between length of illness and gray matter volumes demonstrated a statistically significant inverse relationship between these variables in BD patients (r p = − 0.51; p = 0.003) but not in UP subjects (rp = − 0.23; p = 0.21), however these two correlations were not significantly different (Z = 1.3, p = 0.89). Fig. 1 displays this relationship as a partial residuals scatterplot of total brain gray matter volume versus length of illness after the variance due to total ICV was removed from both variables. Age at illness onset was not significantly related to gray matter volumes in either BD (rp = − 0.18, p = 0.3) or UP patients (rp = − 0.23, p = 0.22), and the number of previous episodes was not significantly correlated with gray matter volumes in BD (rS = − 0.1, p = 0.6, Spearman rank order correlation) or UP subjects (rS = 0.02, p = 0.9). None of these variables were significantly correlated with total white matter volume after adjusting for ICV (all p N 0.05). Fig. 2 shows the partial residuals scatterplot for total brain white matter
2.3. Statistical analysis The bipolar, unipolar and healthy groups were compared with respect to demographic measures with analysis of variance, Kruskal–Wallis H-test, or chi-squared test according to the measurement scale involved. The bipolar and unipolar groups were compared with respect to clinical variables with Student's t-test, Mann–Whitney U-test, or chi-squared test. Because the bipolar group included some medicated and some medication free subjects, all analyses were replicated in these two subgroups to assess potential effects of mood stabilizers. The correlations between total grey and white matter volumes and current age, length of illness (in years) and age at illness onset (in years) were assessed using partial correlation methods, adjusting for total intracranial volume. Because the distribution of number of previous affective episodes was positively skewed, we evaluated the associations between this variable and total grey and white matter volumes using Spearman's rank order correlation. All
Figure 2 Partial residual plot showing brain white matter volume as a function of illness duration both adjusted for total intracranial volume for bipolar and unipolar patients. The solid line is the regression line for BP subjects, and the broken line is the regression line for UP subjects. These plots correspond to the partial correlations reported in the text.
720 volume versus length of illness. Because two-thirds (64%) of BD patients were on mood stabilizers, all analyses were replicated in each of these subgroups. Essentially the same results were found for each of these subgroups as were found for the combined BD sample. The partial correlation between length of illness and total gray matter volume became stronger when medicated subjects were excluded (rp = − 0.67, p = 0.017).
4. Discussion We found that longer illness duration is associated with smaller total brain gray matter volume in BD but not in UP patients, while illness duration is not associated with white matter volume in either BD or UP subjects. These findings suggest that a neurodegenerative process may be involved in the pathophysiology of BD and that observable cerebral changes are primarily in gray matter. Here it is worthy noting that our sample consisted mostly of middle-aged subjects and that BD subjects had on average 15 years of progression of illness, which indicate that a substantial gray matter loss might occur early in the course of BD. Because loss of gray matter content is likely to reflect decreases in the size and number of neurons and dendritic density (Bruno et al., 2004), our finding suggests that the progression of illness is associated with abnormal cellular plasticity in BD. This assumption is consistent with postmortem studies showing decreased neuronal and glial density in individuals with BD (Rajkowska et al., 2001; Ongur et al., 1998; Harrison 2002). We cannot rule out the possibility that a neurodegenerative process is taking place in UP subjects and perhaps more time is needed to identify such changes. No differences in total brain, gray or white matter volumes between BDs, UPs, and HCs were observed in the present study. These results are in accordance with the majority of studies that found no global cerebral volume changes in individuals with BD (Hoge et al., 1999; Strakowski et al., 2005). Recent studies reported changes in gray matter in discrete regions of prefrontal, temporal, parietal, and cerebellar cortices suggesting that the cerebral changes are subtle rather than global in BD (Lyoo et al., 2004; Adler et al., 2005; Nugent et al., 2006; DelBello et al., 1999). We also found that gray matter volume did not correlate with age at onset or number of previous episodes. These results suggest that gray matter loss might be related to the progression of disease independently of the recurrence of major affective episodes. This is in line with a previous investigation showing that the presence of multiple episodes was not associated with gray matter loss in periventricular structures (Strakowski et al., 2002). However, in this latter study multiple-episode BD patients had larger ventricular volumes than first-episode patients, suggesting that recurrent episodes may progressively affect brain anatomy in BD patients. Our results are consistent with some (Martinez-Aran et al., 2004; Robinson and Ferrier, 2006) but not all (Balanza-Martinez et al., 2005) neurocognitive studies suggesting that length of illness may be associated with poor cognitive performance in individuals with BD. In addition, other factors that have been found to be associated with poorer cognitive performance and functional outcomes in BD are mood stabilizing
B.N. Frey et al. treatment (Torres et al., 2007), psychotic and manic symptoms (Tabares-Seisdedos et al., in press), and history of manic symptoms, hospitalizations and suicide attempts (Martinez-Aran et al., 2004), although others found that history of psychosis was not associated with poorer neurocognitive or functional outcomes (MacQueen et al., 1997; Selva et al., 2007). Finally, a number of studies reported that levels of neurotrophins are altered in the peripheral blood of BD and UP subjects, and that such alterations may be specifically observed during acute mood episodes (Shimizu et al., 2003; Cunha et al., 2006; Machado-Vieira et al., 2007). Whether these findings are associated or not with changes in gray matter content it is yet to be determined. The present study should be interpreted in the context of its limitations. A trend for differences in gender was observed among the three groups. However, his trend was driven mainly by a relatively low proportion of females in the HC group (the two clinical groups being more closely matched); therefore this fact does not negate the main finding of the present investigation, i.e., the inverse correlation between length of illness and gray matter volume in BD patients. The BD sample comprised medicated and unmedicated subjects, and given previous findings that lithium treatment increases gray matter content in BD subjects (Moore et al., 2000; Sassi et al., 2002), we cannot completely rule out medication effects in the present results. However, we explored the possible impact of current medications on the observed correlations by replicating the data analysis with medicated subjects excluded and found that the partial correlation between length of illness and total gray matter volume became stronger when medicated subjects were omitted from the analysis. Therefore, this finding is not likely to be an artifact of current medication status. Further, considering that previous studies have shown that lithium treatment increases gray matter content, it would be expected that current medication use would drive the present results toward the null hypothesis. Nonetheless, the possible cumulative influences of past exposure to psychiatric medications cannot be ruled out. The study of middle-aged subjects limits the investigation of cerebral changes during a longer period of time but highlights that the decline of gray matter content might occur early in the course of the illness. Importantly, due to the cross-sectional design of the present study, we cannot directly assess change in brain volumes over time or exclude the potential of biased recall in the reporting of previous episodes or date of illness onset. Finally, several key clinical variables including age at illness onset, number of previous mood episodes, and illness duration were assessed retrospectively, and their measurement may be influenced by subject recall or reporting bias. Longitudinal studies are needed to further examine these issues. In conclusion, we found that length of illness is inversely correlated with gray matter volume in BD. In UP subjects, the correlation was in the same direction but of smaller magnitude and was not statistically significant. These findings suggest that the illness progression may be associated with abnormal cellular plasticity in BD. Longitudinal studies are warranted to further investigate the long-term illness-related neuroanatomical changes in severe mood disorders.
Illness duration and brain gray matter in bipolar disorder
Role of the funding source This study was partly supported by MH 68766, MH 69774, RR 20571, NARSAD, Veterans Administration (Merit Review) and the Krus Endowed Chair in Psychiatry (UTHSCSA). The sponsors had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
Contributors Drs. Brambilla, Mallinger and Soares designed the study and wrote the protocol. Drs. Frey, Zunta-Soares, Caetano and Brambilla managed the literature searches and analyses. Mr. Nicoletti contributed to the data analyses. Dr. Hatch undertook the statistical analysis, and Dr. Frey wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.
Conflict of interest The authors declare that they have no conflicts of interest.
Acknowledgements Partly supported by MH 68766, MH 69774, RR 20571, NARSAD, Veterans Administration (Merit Review) and the Krus Endowed Chair in Psychiatry (UTHSCSA). This work was initially performed at the University of Pittsburgh, prior to Dr. Mallinger’s official duties as a Government employee. The views expressed in this paper do not necessarily represent the views of the NIMH, NIH, or the United States Government.
References Adler, C.M., Levine, A.D., DelBello, M.P., Strakowski, S.M., 2005. Changes in gray matter volume in patients with bipolar disorder. Biol. Psychiatry 58, 151–157. Balanza-Martinez, V., Tabares-Seisdedos, R., Selva-Vera, G., MartinezAran, A., Torrent, C., Salazar-Fraile, J., Leal-Cercos, C., Vieta, E., Gomez-Beneyto, M., 2005. Persistent cognitive dysfunctions in bipolar I disorder and schizophrenic patients: a 3-year follow-up study. Psychother. Psychosom. 74, 113–119. Beyer, J.L., Kuchibhatla, M., Payne, M., Moo-Young, M., Cassidy, F., MacFall, J., Krishnan, K.R., 2004. Caudate volume measurement in older adults with bipolar disorder. Int. J. Geriatr. Psychiatry 19, 109–114. Brambilla, P., Harenski, K., Nicoletti, M., Mallinger, A.G., Frank, E., Kupfer, D.J., Keshavan, M.S., Soares, J.C., 2001a. Differential effects of age on brain gray matter in bipolar patients and healthy individuals. Neuropsychobiology 43, 242–247. Brambilla, P., Harenski, K., Nicoletti, M.A., Mallinger, A.G., Frank, E., Kupfer, D.J., Keshavan, M.S., Soares, J.C., 2001b. Anatomical MRI study of basal ganglia in bipolar disorder patients. Psychiatry Res. 106, 65–80. Brambilla, P., Harenski, K., Nicoletti, M., Mallinger, A.G., Frank, E., Kupfer, D.J., Keshavan, M.S., Soares, J.C., 2001c. MRI study of posterior fossa structures and brain ventricles in bipolar patients. J. Psychiatr. Res. 35, 313–322. Bruno, S.D., Barker, G.J., Cercignani, M., Symms, M., Ron, M.A., 2004. A study of bipolar disorder using magnetization transfer imaging and voxel-based morphometry. Brain 127, 2433–2440. Caetano, S.C., Sassi, R., Brambilla, P., Harenski, K., Nicoletti, M., Mallinger, A.G., Frank, E., Kupfer, D.J., Keshavan, M.S., Soares, J.C., 2001. MRI study of thalamic volumes in bipolar and unipolar patients and healthy individuals. Psychiatry Res. 108, 161–168.
721 Cunha, A.B.M., Frey, B.N., Andreazza, A.C., Goi, J.D., Rosa, A.R., Gonçalves, C.A., Santin, A., Kapczinski, F., 2006. Serum brainderived neurotrophic factor is decreased in bipolar disorder during depressive and manic episodes. Neurosci. Lett. 398, 215–219. Deister, A., Marneros, A., 1993. Predicting the long-term outcome of affective disorders. Acta Psychiatr. Scand. 88, 174–177. DelBello, M.P., Strakowski, S.M., Zimmerman, M.E., Hawkins, J.M., Sax, K.W., 1999. MRI analysis of the cerebellum in bipolar disorder: a pilot study. Neuropsychopharmacology 21, 63–68. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B., 1998. Structured Clinical Interview for DSM-IV (SCID-I). Biomedics Research Department, New York. Goldberg, J.F., Garno, J.L., Harrow, M., 2005. Long-term remission and recovery in bipolar disorder: a review. Curr. Psychiatry Rep. 7, 456–461. Harrison, P.J., 2002. The neuropathology of primary mood disorder. Brain 125, 1428–1449. Hoge, E.A., Friedman, L., Schulz, S.C., 1999. Meta-analysis of brain size in bipolar disorder. Schizophr. Res. 37, 177–181. Judd, L.L., Schettler, P.J., Akiskal, H.S., Maser, J., Coryell, W., Solomon, D., Endicott, J., Keller, M., 2003. Long-term symptomatic status of bipolar I vs. bipolar II disorders. Int. J. Neuropsychopharmacol. 6, 127–137. Judd, L.L., Akiskal, H.S., Schettler, P.J., Endicott, J., Leon, A.C., Solomon, D.A., Coryell, W., Maser, J.D., Keller, M.B., 2005. Psychosocial disability in the course of bipolar I and II disorders: a prospective, comparative, longitudinal study. Arch. Gen. Psychiatry 62, 1322–1330. Keshavan, M.S., Anderson, S., Beckwith, C., Nash, K., Pettegrew, J.W., Krishnan, K.R., 1995. A comparison of stereology and segmentation techniques for volumetric measurements of lateral ventricles in magnetic resonance imaging. Psychiatry Res. Neuroimaging 61, 53–60. Lopez-Larson, M.P., DelBello, M.P., Zimmerman, M.E., Schwiers, M.L., Strakowski, S.M., 2002. Regional prefrontal gray and white matter abnormalities in bipolar disorder. Biol. Psychiatry 52, 93–100. Lyoo, I.K., Kim, M.J., Stoll, A.L., Demopulos, C.M., Parow, A.M., Dager, S.R., Friedman, S.D., Dunner, D.L., Renshaw, P.F., 2004. Frontal lobe gray matter density decreases in bipolar I disorder. Biol. Psychiatry 55, 648–651. Machado-Vieira, R., Dietrich, M.O., Leke, R., Cereser, V.H., Zanatto, V., Kapczinski, F., Souza, D.O., Portela, L.V., Gentil, V., 2007. Decreased plasma brain derived neurotrophic factor levels in unmedicated bipolar patients during manic episode. Biol. Psychiatry 61, 142–144. MacQueen, G.M., Young, L.T., Robb, J.C., Cooke, R.G., Joffe, R.T., 1997. Levels of functioning and well-being in recovered psychotic versus nonpsychotic mania. J. Affect. Disord. 46, 69–72. Martinez-Aran, A., Vieta, E., Reinares, M., Colon, F., Torrent, C., Sanchez-Moreno, J., et al., 2004. Cognitive function across manic or hypomanic, depressed, and euthymic states in bipolar disorder. Am. J. Psychiatry 161, 262–270. Moore, G.J., Bebchuk, J.M., Wilds, I.B., Chen, G., Manji, H.K., 2000. Lithium-induced increase in human brain grey matter. Lancet 356, 1241–1242. Nugent, A.C., Milham, M.P., Bain, E.E., Mah, L., Cannon, D.M., Marrett, S., Zarate, C.A., Pine, D.S., Price, J.L., Drevets, W.C., 2006. Cortical abnormalities in bipolar disorder investigated with MRI and voxel-based morphometry. Neuroimage 30, 485–497. Ongur, D., Drevets, W.C., Price, J.L., 1998. Glial reduction in the subgenual prefrontal cortex in mood disorders. Proc. Natl. Acad. Sci. USA 95, 13290–13295. Perlis, R.H., Miyahara, S., Marangell, L.B., Wisniewski, S.R., Ostacher, M., DelBello, M.P., Bowden, C.L., Sachs, G.S., Nierenberg, A.A., 2004. Long-term implications of early onset in bipolar disorder: data from the first 1000 participants in the
722 systematic treatment enhancement program for bipolar disorder (STEP-BD). Biol. Psychiatry 55, 875–881. Rajkowska, G., Halaris, A., Selemon, L.D., 2001. Reductions in neuronal and glial density characterize the dorsolateral prefrontal cortex in bipolar disorder. Biol. Psychiatry 49, 741–752. Robinson, L.J., Ferrier, I.N., 2006. Evolution of cognitive impairment in bipolar disorder: a systematic review of cross-sectional evidence. Bipolar Disord. 8, 103–116. Sassi, R.B., Nicoletti, M., Brambilla, P., Mallinger, A.G., Frank, E., Kupfer, D.J., Keshavan, M.S., Soares, J.C., 2002. Increased gray matter volume in lithium-treated bipolar disorder patients. Neurosci. Lett. 329, 243–245. Selva, G., Salazar, J., Balanza-Martinez, V., Martinez-Aran, A., Rubio, C., Daban, C., et al., 2007. Bipolar I patients with and without a history of psychotic symptoms: do they differ in their cognitive functioning? J. Psychiatr. Res. 41, 265–272. Shimizu, E., Hashimoto, K., Okamura, N., Koike, K., Komatsu, N., Kumakiri, C., Nakazato, M., Watanabe, H., Shinoda, N., Okada, S., Iyo, M., 2003. Alterations of serum levels of brain-derived neurotrophic factor (BDNF) in depressed patients with or without antidepressants. Biol. Psychiatry 54, 70–75.
B.N. Frey et al. Soares, J.C., Mann, J.J., 1997. The functional neuroanatomy of mood disorders. J. Psychiatr. Res. 31, 393–432. Strakowski, S.M., DelBello, M.P., Zimmerman, M.E., Getz, G.E., Mills, N.P., Ret, J., Shear, P., Adler, C.M., 2002. Ventricular and periventricular structural volumes in first- versus multipleepisode bipolar disorder. Am. J. Psychiatry 159, 1841–1847. Strakowski, S.M., Delbello, M.P., Adler, C.M., 2005. The functional neuroanatomy of bipolar disorder: a review of neuroimaging findings. Mol. Psychiatry 10, 105–116. Tabares-Seisdedos, R., Balanza-Martinez, V., Sanchez-Moreno, J., Martinez-Aran, A., Salazar-Fraile, J., Selva-Vera, G., et al. (in press) Neurocognitive and clinical predictors of functional outcome in patients with schizophrenia and bipolar I disorder at one-year follow-up. J. Affect. Disord. Torres, I.J., Boudreau, V.G., Yatham, L.N., 2007. Neuropsychological functioning in euthymic bipolar disorder: a meta-analysis. Acta Psychiatr. Scand. 116 (Suppl. 434), 17–26. Wittchen, H.U., Mhlig, S., Pezawas, L., 2003. Natural course and burden of bipolar disorders. Int. J. Neuropsychopharmacol. 6, 145–154.
