Abstract
Background
Metabolic syndrome (MetS) is highly prevalent among patients with bipolar disorder. MetS may cause complications in the brain, but studies investigating MetS-associated clinical psychiatric outcomes remain scant.
Methods
We enrolled clinically stable outpatients with bipolar disorder aged 18–65 years and performed anthropometric and fasting biochemical assessments to investigate MetS prevalence. We then performed clinical assessments by using the Young Mania Rating Scale for manic symptoms, the Montgomery–Åsberg Depression Rating Scale for depressive symptoms, the Positive and Negative Symptom Scale for psychotic symptoms, the Involuntary Movement Scale for tardive dyskinesia, the Barnes Akathisia Rating Scale for akathisia, the Udvalg for Kliniske Undersogelser for general side effects, the Schedule for Assessment of Insight for insight, the Global Assessment of Functioning scale for global functioning, and the Wisconsin Card Sorting Test (WCST) for cognitive executive function.
Results
In total, 143 patients were enrolled and had a MetS prevalence of 29.4%. The patients treated with atypical antipsychotics plus mood stabilizers (36.3%) and atypical antipsychotics alone (36.0%) had a significantly higher prevalence of MetS than did those treated with mood stabilizers alone (10.5%; p = 0.012). According to multivariate regression analyses adjusted for age, sex, smoking status, bipolar disorder subtype (I or II), pharmacological treatment duration, and psychiatric medication, compared with patients without MetS, those with MetS had significantly more previous hospitalizations (p = 0.036), severer tardive dyskinesia (p = 0.030), poorer insight (p = 0.036), poorer global function (p = 0.046), and more impaired executive function (conceptual level response on the WCST; p = 0.042).
Conclusions
Our results indicated that patients with comorbid bipolar disorder and MetS have more adverse clinical outcomes than those without, with more hospitalizations, severer tardive dyskinesia, poorer insight, poorer global function, and more impaired executive function. Monitoring MetS is crucial for assessing not only physical burden, but also psychiatric outcomes.
Keywords: Metabolic syndrome, Bipolar disorder, Clinical outcome
Background
Metabolic syndrome (MetS) is highly prevalent (16.7%–67%) among patients with bipolar disorder in many countries [1–3]. Bipolar disorder and MetS have common risk factors, including endocrine disturbances, sympathetic nervous system dysregulation, and behavior patterns such as physical inactivity and overeating [4, 5]. In addition, commonly used pharmacological bipolar disorder treatments, such as mood stabilizers and antipsychotics, may intensify the medical burden by causing weight gain and metabolic disturbances, such as alterations in lipid and glucose metabolism [6, 7]. Comorbid MetS and bipolar disorder are associated with a high risk of cardiovascular disease [3, 5, 8], a two-fold increase in mortality [9], and a 10–20-year shortening of life expectancy [10]. Studies have shown that obesity and metabolic diseases are associated with poor clinical outcome in bipolar disorder. Fagiolini et al. reported that 35.4% of 175 patients with bipolar disorder were obese and that these patients had more previous depressive and manic episodes as well as exhibited a significantly shorter time to recurrence during the maintenance phase than nonobese patients did [11]. Similarly, Calkin et al. reported that 39.1% of 276 patients with bipolar disorder were obese and that these patients had a longer illness duration, poorer global function, more disability, and poorer response to lithium than nonobese patients did [12]. In addition, obesity in bipolar disorder is associated with illness severity, particularly in relation to depression [13–15], unfavorable course of illness [15], and poor cognitive function [16–19]. Compared with euglycemic patients, those with bipolar disorder and type 2 diabetes or insulin resistance have significantly higher risk of a chronic course, rapid cycling, and bipolar disorder refractory to lithium treatment [20–22].
Nevertheless, studies investigating MetS-associated clinical psychiatric outcomes remain scant. MetS is a multidimensional entity that includes visceral obesity, dyslipidemia, hyperglycemia, and hypertension. MetS may cause complications in the brain: In an animal study, chronic hyperglycemia and insulin resistance were reported as risk factors for neuronal death through induction of a state of oxidative stress and inflammatory response, thus affecting cognitive processes [23]. Patients with MetS showed a significant reduction in mean cortical thickness and volume in both hemispheres compared with controls, suggesting an initial neurodegenerative process and cognitive deterioration with MetS, even at a preclinical stage [24]. Furthermore, four studies of topiramate as an add-on therapy in patients with bipolar disorder showed that weight reduction is associated with a significant reduction in both depressive and manic symptoms [25–28]. These interventions are potentially efficacious in ameliorating disturbed biological pathways, particularly those mediating inflammation and oxidative stress, and reducing the rate of neuroprogressive disturbances in bipolar disorders [29]. In this study, we investigated the association between MetS and clinical outcomes of patients with bipolar disorder. We hypothesized that patients with comorbid bipolar disorder and MetS have more adverse clinical outcomes than those without MetS do.
Methods
This study was conducted in a psychiatric outpatient clinic of a university medical center hospital. The patient inclusion criteria were as follows: outpatients with bipolar disorder (DSM-IV), and those aged 18–65 years with a Clinical Global Impression-Severity rating for bipolar disorder of ≤3. The exclusion criteria were any DSM-IV diagnosis of a lifetime history of schizophrenia, mental retardation, or organic mental disorder, and those currently pregnant or breastfeeding. All patients provided written informed consent before inclusion. The study was approved by the Institutional Review Board of Taipei Veterans General Hospital and conducted in accordance with the Declaration of Helsinki.
The medical and psychiatric histories of the patients were reviewed. Anthropometric and fasting biochemical assessments were performed to investigate MetS prevalence according to the 2005 International Diabetes Federation Asia criteria; a waist circumference of >90 cm in men or >80 cm in women was the essential criterion of central obesity in addition to any two of the following criteria: (a) fasting serum triglyceride levels of ≥150 mg/dL, (b) fasting high-density lipoprotein cholesterol levels of <40 mg/dL in men or <50 mg/dL in women, (c) blood pressure of ≥130/85 mmHg, or (d) a fasting glucose level of ≥100 mg/dL. Patients receiving medication for hypertension, diabetes, or hyperlipidemia were considered to fulfill the MetS components criteria. We used the following scales for clinical assessment: the Young Mania Rating Scale (YMRS) for manic symptoms, the Montgomery–Åsberg Depression Rating Scale (MADRS) for depressive symptoms, the Positive and Negative Symptom Scale (PANSS) for psychotic symptoms, the Simpson–Angus Scale (SAS) for extrapyramidal side effects [30], the Abnormal Involuntary Movement Scale (AIMS) for tardive dyskinesia [31], the Barnes Akathisia Rating Scale (BARS) for akathisia [32], the Udvalg for Kliniske Undersogelser for general side effects [33], the Schedule for Assessment of Insight (SAI) for insight [34], and the Global Assessment of Functioning (GAF) scale for functioning. Furthermore, cognitive executive function was assessed using the Wisconsin Card Sorting Test (WCST). All clinical assessments were conducted by Dr. Bai (first author).
Patient characteristics were evaluated through descriptive analyses. Patients with and without MetS were compared using a chi-square test for categorical data and the Student t test for continuous data. The Fisher exact test was used if fewer than five data points were expected to be greater than 20% of the cells in the contingency table. All tests were based on their two-tailed alternatives. The clinical outcomes of the patients with and without MetS were further compared using multivariate regression analyses adjusted for age, sex, smoking status, bipolar disorder subtype (I or II), pharmacological treatment duration, and psychiatric medication (monotherapy or combination therapy). The level of significance was set at a p value of 0.05. All statistical analyses were performed using SPSS 11.5 (SPSS Inc., Chicago, IL, USA).
Results
In total, we enrolled 143 outpatients with bipolar disorder (66.4% women) with an average age of 44.8 ± 12.0 years. The prevalence of MetS was 29.4%. Age, sex, education, pharmacological treatment duration for bipolar disorder, suicide history, bipolar subtype (I or II), as well as severity of manic (YMRS), depressive (MADRS), and psychotic (PANSS) symptoms did not differ significantly between the patients with and without MetS. The patients treated with atypical antipsychotics plus mood stabilizers (36.3%) and atypical antipsychotics alone (36.0%) had a significantly higher MetS prevalence than did those treated with mood stabilizers alone (10.5%; p = 0.012). Univariate analysis showed that compared with the patients without MetS, those with MetS had significantly more previous hospitalizations (p = 0.024), more first mood episodes with mania (p = 0.033), more extrapyramidal side effects (SAS; p = 0.003), higher incidence of akathisia (BARS; p = 0.034), higher incidence of involuntary movement disorder (AIMS; p = 0.043), poorer global functioning (GAF; p = 0.035), poorer insight (SAI; p = 0.027), and more impaired executive function (conceptual level response on the WCST; p = 0.007). The patients with MetS also had significantly more medical comorbidities than those without MetS did (71.4% vs. 32.3%, p < 0.0001), including hypertension (54.8% vs. 13.9%, p < 0.0001), hyperlipidemia (26.2% vs. 5.9%, p = 0.001), and diabetes mellitus (23.8% vs. 4%, p = 0.001).
Because smoking status [35, 36], bipolar disorder subtype [37], illness duration [38, 39], and psychiatric medications [40, 41] may influence clinical outcomes, we used multivariate regression analyses adjusted for age, sex, smoking status, bipolar disorder subtype (I or II), pharmacological treatment duration, and psychiatric medication (mood stabilizers alone, atypical antipsychotics alone, or atypical antipsychotics plus mood stabilizers). We observed that compared with the patients without MetS, those with MetS had significantly more previous hospitalizations (p = 0.036), severer tardive dyskinesia (AIMS; p = 0.030), poorer insight (SAI; p = 0.036), poorer global function (GAF; p = 0.046), and more impaired executive function (conceptual level response on the WCST; p = 0.042; Fig. 1; Tables 1 and 2).
Fig. 1.
Comparison of clinical outcomes between patients with and without metabolic syndrome using multivariate regression analyses with adjustments of age, gender, smoking, subtype of bipolar disorder, pharmacological treatment duration, and psychiatric medication group
Table 1.
Comparison of characteristics between bipolar patients with and without metabolic syndrome
| Patients with metabolic syndrome (n = 42) | Patients without metabolic syndrome (n = 101) | df, p-value | |
|---|---|---|---|
| Age (year) | 47.5 ± 11.2 | 43.7 ± 12.2 | n.s. |
| Gender (F, %) | 67.9% | 69.8% | n.s. |
| Education (more than 12 years %) | 33.3% | 33.7% | n.s. |
| Occupation (regular work %) | 28.6% | 33.7% | n.s. |
| Age at onset of bipolar disorder | 31.5 ± 12.7 | 28.4 ± 11.7 | n.s. |
| Treatment Duration of bipolar disorder | 13.9 ± 11.2 | 13.1 ± 10.7 | n.s. |
| Smoking (%) | 31% | 23.8% | n.s. |
| Times of hospitalization | 4.1 ± 4.9 | 2.5 ± 2.9 | df = 47.7,P = 0.024 |
| History of suicide attempt (%) | 42.9% | 47.5% | n.s. |
| Subtype of bipolar disorder (bipolar I %) | 69% | 59.4% | n.s. |
| Pharmacological treatment groups | 52.4% | 43.6% | n.s. |
| [mood stabilizers only] | 9.5% | 33.7% | df = 2,P = 0.012 |
| [atypical antipsychotics only] | 21.4% | 15.8% | |
| [atypical antipsychotics plus mood stabilizers] | 69% | 50.5% | |
| First mood episode with mania/hypomania (%) | 52.5% | 32.0% | df = 1,P = 0.033 |
| Young Mania Rating Scale (YMRS) | 5.3 ± 5.0 | 4.7 ± 4.9 | n.s. |
| Montgomery Åsberg Depression Rating Scale (MADRS) | 8.2 ± 7.4 | 9.2 ± 9.1 | n.s. |
| Positive and Negative Symptom Scale (PANSS) | 41.6 ± 12.6 | 39.4 ± 11.6 | n.s. |
| Simpson-Angus Scale (SAS) | 3.6 ± 4.7 | 2.1 ± 4.0 | df = 67.6,P = 0.046 |
| Abnormal Involuntary Movement Scale (AIMS) | 1.8 ± 4.4 | 0.5 ± 2.4 | df = 51.5,P = 0.021 |
| Barnes Akathesia scale (BANS) | 0.1 ± 0.6 | 0.2 ± 0.9 | n.s. |
| Udvalg for Kliniske Undersogelser (UKU) | 5.7 ± 3.3 | 4.7 ± 4.0 | n.s. |
| Schedule for Assessment of Insight (SAI) | 16.2 ± 4.9 | 18.1 ± 4.4 | df = 140,P = 0.027 |
| Global Assessment of Functioning scale (GAF) | 67.1 ± 11.7 | 71.5 ± 11.0 | df = 141,P = 0.035 |
| Level of lithium (n = 33) | 0.51 ± 0.21 | 0.74 ± 0.62 | n.s. |
| Level of valproic acid (n = 52) | 55.0 ± 35.3 | 40.8 ± 28.5 | n.s. |
| Level of carbamazapine (n = 4) | -- | 6.2 ± 1.7 | -- |
| Wisconsin Card Sorting Test (WCST) Conceptual level response % |
34.2 ± 12.5 | 41.4 ± 11.7 | df = 104,P = 0.007 |
| Body Mass Index (BMI) | 30.2 ± 4.2 | 24.8 ± 4.8 | df = 141,P < 0.0001 |
| waist circumference > 90 cm in males or > 80 cm in females | 100% | 42.6% | df = 1,P < 0.0001 |
| fasting serum triglyceride levels≧150 mg/dL | 69% | 14.9% | df = 1,P < 0.0001 |
| fasting high density lipoprotein (HDL) cholesterol < 40 mg/dL in men or <50 mg/dL in women | 73.8% | 13.9% | df = 1,P < 0.0001 |
| blood pressure≧130/85 mmHg | 78.6% | 28.7% | df = 1,P < 0.0001 |
| fasting glucose≧100 mg/dL | 47.6% | 10.9% | df = 1,P < 0.0001 |
| Waist circumference (cm) | 97.1 ± 9.7 | 81.3 ± 11.2 | df = 100,P < 0.0001 |
| Systolic blood pressure (mmHg) | 131.5 ± 17.1 | 120.6 ± 16.9 | df = 141,P = 0.001 |
| Diastolic blood pressure (mm Hg) | 82.1 ± 10.5 | 75.9 ± 11.4 | df = 141,P = 0.003 |
| Triglyceride (microg/ dL) | 198.4 ± 122.1 | 101.4 ± 69.4 | df = 52.4,P < 0.0001 |
| High density lipoprotein (HDL) (microg/ dL) | 41.6 ± 9.3 | 60.9 ± 15.6 | df = 123.6,P < 0.0001 |
| Glucose (microg/ dL) | 101.8 ± 37.7 | 87.7 ± 16.9 | df = 46.7,P = 0.026 |
| Insulin (pg/ml) | 13.7 ± 10.7 | 8.0 ± 13.6 | df = 133,P = 0.019 |
Table 2.
Multivariate regression analyses for clinical outcome and pro-inflammatory cytokines
| Previous hospitalizations (times) | Dyskinesia (AIMS) | Insight(SAI) | Global function (GAF) | Executive function(WCST) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Standardized coefficient (ß) (95% C.I.) |
P value | Standardized coefficient (ß) (95% C.I.) |
P value | Standardized coefficient (ß) (95% C.I.) |
P value | Standardized coefficient (ß) (95% C.I.) | P value | Standardized coefficient (ß) (95% C.I.) |
P value | |
| Age | −0.18 | 0.848 | 0.190 | 0.020** | −0.063 | 0.479 | −0.054 | 0.526 | −0.392 | P < 0.001** |
| (−0.062,0.051) | (0.03,0.094) | (−0.092,0.043) | (−0.208,0.107) | (−0.628,-0.205) | ||||||
| Gender | ||||||||||
| Male | -- | -- | -- | -- | -- | -- | -- | -- | ||
| Female | 0.205 | 0.021** | 0.203 | 0.020** | 0.190 | 0.026** | −0.144 | 0.079 | −0.044 | 0.653 |
| (0.238,2.918) | (0.215,2.419) | (0.224,3.464) | (−7.21,0.397) | (−5.945,3.741) | ||||||
| Smoking | 0.072 | 0.415 | 0.141 | 0.105 | 0.049 | 0.565 | −0.238 | 0.004** | −0.137 | 0.154 |
| (−0.870,2.095) | (−0.209,2.169) | (−1.240,2.262) | (−10.170,-1.962) | (−0.9007,1.445) | ||||||
| Bipolar disorder subtype | ||||||||||
| Type I | -- | -- | -- | -- | -- | -- | -- | -- | ||
| Type II | −0.197 | 0.028** | −0.408 | 0.684 | 0.294 | 0.001** | −0.009 | 0.911 | −0.041 | 0.670 |
| (−2.775,-0.162) | (−1.305,-0.858) | (1.194,4.385) | (−3.944,3.522) | (−5.739,3.704) | ||||||
| Pharmacological treatment duration (years) | 0.259 | 0.005** | 1.165 | 0.246 | 0.258 | 0.004** | 0.154 | 0.071 | 0.083 | 0.401 |
| (0.028,0.153) | (−0.021,0.080) | (0.035,0.183) | (−0.014,0.332) | (−0.127,0.315) | ||||||
| Psychiatric medication group | ||||||||||
| Mood stabilizers only | -- | -- | -- | -- | -- | -- | -- | -- | ||
| Atypical antipsychotics only | 0.185 | 0.071 | 0.094 | 0.355 | 0.054 | 0.586 | −0.321 | 0.001** | −0.219 | 0.039** |
| (−0.163,3.848) | (−0.852,2.357) | (−1.707,3.006) | (−15.003,-3.928) | (−15.303,-0.396) | ||||||
| Atypical antipsychotics plus mood stabilizers | 0.089 | 0.383 | 0.049 | 0.630 | 0.139 | 0.164 | −0.312 | 0.001** | −0.218 | 0.042** |
| (−0.829,2.143) | (−0.937,1.543) | (−0.534,3.124) | (−11.365,-2.805) | (−10.721,-0.196) | ||||||
| Metabolic syndrome (+) | 0.19 | 0.036** | 2.190 | 0.030** | −0.179 | 0.036** | −0.164 | 0.046** | −0.324 | 0.042** |
| (0.097,2.918) | (0.121,2.387) | (−3.447,-0.118) | (−7.891,-0.071) | (−9.969,-0.178) | ||||||
** p<0.05
The bold-italic data emphasized the statistical significance
Discussion
Our study showed that the prevalence of MetS was 29.4% among patients with bipolar disorder, comparable to the previously reported 33.9% in Taiwan [42] and 16.7%–67% in other countries [1]. The frequent cooccurrence of bipolar disorder and MetS may be characterized by the common genetic links, interconnected pathophysiologies, and interacting biological networks with structural and functional abnormalities in multiple cortical and subcortical brain regions subservient to cognitive and affective processing [1, 4, 5, 29]. Furthermore, many commonly used pharmacological treatments for bipolar disorder, antipsychotics, and mood stabilizers increase both weight and MetS risk [1, 3, 43, 44]. In this study, we demonstrated that patients treated with atypical antipsychotics plus mood stabilizers and atypical antipsychotics alone had a significantly higher MetS prevalence than those treated with mood stabilizers alone did. Our results were consistent with previous study results, in which cotreatment with mood stabilizers plus antipsychotics increased MetS risk [44, 45]. A comparative analysis of 32 double-blind, randomized, placebo-controlled trials showed that antipsychotics caused more weight gain than did mood stabilizers in youths [46]. Currently, many atypical antipsychotics are recommended as first-line monotherapy or in combination with mood stabilizers to improve the efficacy of bipolar disorder treatment [40, 41, 47–49]. Our results suggest that efficacious advantages of antipsychotics in bipolar disorder treatment should be balanced with their greater MetS risk.
To investigate the role of MetS in the clinical outcomes, we used multivariate regression analyses adjusted for age, sex, smoking status, bipolar disorder subtype (I or II), pharmacological treatment duration, and psychiatric medication (mood stabilizers alone, atypical antipsychotics alone, or atypical antipsychotics plus mood stabilizers) because smoking status [35, 36], bipolar disorder subtype [37], illness duration [38, 39], and psychiatric medications [40, 41] potentially influence the clinical outcomes. In addition, we observed that MetS was associated with more previous hospitalizations, severer tardive dyskinesia, poorer insight, poorer global functioning, and more impaired cognitive executive function. The current results supported our hypothesis that patients with comorbid bipolar disorder and MetS associate with the severity of neurodegenerative processes and cognitive impairment than those without [23, 50]. MetS can elicit inflammatory response (increase in the number of reactive astrocytes as well as the levels of interleukin-1-beta and tumor necrosis factor-alpha) and oxidative stress (reactive oxygen species and lipid peroxidation), causing a reduction in the number of neurons in the temporal cortex and hippocampus [23, 51]. Hyperglycemia can directly affect neuron myelin or axons and the structure and function of endoneurial microvessels, which can then induce fiber changes by altering the blood–nerve barrier and inducing hypoxia or ischemia or through unknown mechanisms [52]. The positive association between MetS and cognitive dysfunction was documented with volume losses in the hippocampus and frontal lobes [53]. Significant correlations between brain microstructural white matter alterations and cognitive impairment have also been noted in patients with MetS, particularly in the frontal lobe [54]. MetS negatively affects cognitive performance and brain structure. Potential explanatory models include impaired vascular reactivity, neuroinflammation, oxidative stress, and abnormal brain lipid metabolism [53]. Patients with MetS may also experience a substantial negative economic and health impact, considerably reducing their quality of life and social function [11, 12, 55–57].
Notably, in multivariate regression analyses, our patients with comorbid bipolar disorder and MetS had severer tardive dyskinesia than did those without. Studies have suggested that patients with affective disorder treated with antipsychotics have a greater risk of tardive dyskinesia [58]. Nevertheless, we adjusted for the pharmacological treatment duration and psychiatric medication (mood stabilizers alone, atypical antipsychotics alone, or atypical antipsychotics plus mood stabilizers) in the multivariate regression analyses. The association between MetS and tardive dyskinesia cannot be entirely explained by the pharmacological treatment. The pathophysiology of tardive dyskinesia remains to be completely understood. In addition to the leading hypothesis of dopamine receptor hypersensitivity with antipsychotic treatment, a crucial pathophysiological theory of tardive dyskinesia involves neurotoxicity [59]. MetS can elicit inflammatory response and oxidative stress, reducing the number of neurons [23, 51]; animal studies have shown that tardive dyskinesia is associated with inflammation and apoptosis [60, 61]. Furthermore, the potent antioxidants vitamins E and B6 as well as piracetam have been shown to alleviate the severity of tardive dyskinesia in randomized, double-blind, placebo-controlled studies [62, 63]. In addition, the severity of tardive dyskinesia is positively associated with that of cognitive dysfunction [64–66], significantly reduced gray matter, and widespread abnormality of white matter over corticobasal ganglion circuits, which involves emotional and behavioral regulation as well as executive function [67, 68]. Taken together, these studies further support our results that patients with MetS have severer tardive dyskinesia and are characterized by severer neurodegeneration and poorer clinical outcomes.
Strengths and limitations
Our study investigated the association between MetS and clinical outcomes in patients with bipolar disorder. The current results indicate that monitoring MetS is important for both physical and psychiatric outcomes in patients with bipolar disorder. Although the exact causes of MetS in bipolar disorder vary across patients, the etiological cascade—including biological, psychological, and sociodemographic variables— ultimately affects the clinical outcomes of the patients, whether directly or indirectly. The results also highlight the need for collaborative care among psychiatric and general medical providers to concomitantly address the psychiatric and other medical needs of patients with bipolar disorder. However, our study has some limitations, mainly because of its cross-sectional design. First, whether the association between MetS and adverse clinical outcomes of bipolar disorder is causal remains to be determined. The presence of MetS may lead to more severe neurodegeneration process and cause adverse clinical outcomes; by contrast, patients with poorer clinical outcomes may develop MetS because they receive more complex combination therapy. Nevertheless, even more, probable is the pathophysiology change of MetS and adverse clinical outcomes occur simultaneously and interact intermingle with each other. Long-term studies are needed to elucidate whether the processes of MetS and clinical outcomes are distinguishable. Second, even though the current psychiatric medication groups were controlled for in the multivariate regression analyses, the impacts of previous psychiatric medications were difficult to investigate. The average treatment duration was 13 years among our patients, and their previous medications involved varying combinations and treatment durations. Thus, clarifying the role of a specific medication in the development of MetS as well as their influence on clinical outcomes or cognitive function was difficult. Prospective studies examining patients with the newly diagnosed bipolar disorder are required. Third, our study participants were clinically stable outpatients; hence, a generalization of the results to the entire population of patients with bipolar disorder may be limited.
Conclusion
The prevalence of MetS in the 143 clinically stable outpatients with bipolar disorder was 29.4%. The patients treated with atypical antipsychotics plus mood stabilizers (36.3%) and atypical antipsychotics alone (36.0%) had a significantly higher prevalence of MetS than did those treated with mood stabilizers alone (10.5%). The efficacy advantages of antipsychotics in bipolar disorder should be balanced with its greater risk of MetS. The patients with comorbid bipolar disorder and MetS have adverse clinical outcomes than those without, with more hospitalizations, more tardive dyskinesia, poorer insight, poorer global function, and more impaired executive function. The current results supported our hypothesis that patients with comorbid bipolar disorder and MetS associated with the severity of neurodegenerative processes than those without. Monitoring of metabolic syndrome is not only important for physical burden, as considerably as for psychiatric outcomes.
Acknowledgements
None.
Funding
The study was supported by grants from the Taiwan Ministry of Science and Technology (MOST 104-2314-B-075-017), and Taipei Veterans General Hospital (V103E9-005, V103E3-006). These funding resources are independent of the study.
Availability of data and materials
Not applicable.
Authors’ contributions
Prof. Y-MB: study design, clinical rating, statistic, and paper writing; Dr. C-TL, Prof. S-JT, Dr. M-HC, Dr. P-CT: enrollment of cases, interpretation of data, critical review of the manuscript; Prof. T-PS: study design, critical review of the manuscript. All authors participated in the critical revision of the manuscript for content and read and approved the final manuscript, and agreed their accountability in ensuring that any questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable.
Ethics approval and consent to participate
All patients provided written informed consent before inclusion. The study was approved by the Institutional Review Board of Taipei Veterans General Hospital and conducted in accordance with the Declaration of Helsinki.
References
- 1.McIntyre RS, Danilewitz M, Liauw SS, Kemp DE, Nguyen HT, Kahn LS, Kucyi A, Soczynska JK, Woldeyohannes HO, Lachowski A, et al. Bipolar disorder and metabolic syndrome: an international perspective. J Affect Disord. 2010;126(3):366–87. doi: 10.1016/j.jad.2010.04.012. [DOI] [PubMed] [Google Scholar]
- 2.Grover S, Malhotra N, Chakrabarti S, Kulhara P. Metabolic syndrome in bipolar disorders. Indian J Psychol Med. 2012;34(2):110–8. doi: 10.4103/0253-7176.101767. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Vancampfort D, Vansteelandt K, Correll CU, Mitchell AJ, De Herdt A, Sienaert P, Probst M, De Hert M. Metabolic syndrome and metabolic abnormalities in bipolar disorder: a meta-analysis of prevalence rates and moderators. Am J Psychiatry. 2013;170(3):265–74. doi: 10.1176/appi.ajp.2012.12050620. [DOI] [PubMed] [Google Scholar]
- 4.McElroy SL, Keck PE., Jr Metabolic syndrome in bipolar disorder: a review with a focus on bipolar depression. J Clin Psychiatry. 2014;75(1):46–61. doi: 10.4088/JCP.13r08634. [DOI] [PubMed] [Google Scholar]
- 5.Fagiolini A, Chengappa KN, Soreca I, Chang J. Bipolar disorder and the metabolic syndrome: causal factors, psychiatric outcomes and economic burden. CNS Drugs. 2008;22(8):655–69. doi: 10.2165/00023210-200822080-00004. [DOI] [PubMed] [Google Scholar]
- 6.Loffler D, Landgraf K, Korner A, Kratzsch J, Kirkby KC, Himmerich H. Modulation of triglyceride accumulation in adipocytes by psychopharmacological agents in vitro. J Psychiatr Res. 2016;72:37–42. doi: 10.1016/j.jpsychires.2015.10.008. [DOI] [PubMed] [Google Scholar]
- 7.Zuo S, Fries BE, Szafara K, Regal R. Valproic Acid as a potentiator of metabolic syndrome in institutionalized residents on concomitant antipsychotics: fat chance, or slim to none? P & T : a peer-reviewed journal for formulary management. 2015;40(2):126–32. [PMC free article] [PubMed] [Google Scholar]
- 8.Sylvia LG, Shelton RC, Kemp DE, Bernstein EE, Friedman ES, Brody BD, McElroy SL, Singh V, Tohen M, Bowden CL, et al. Medical burden in bipolar disorder: findings from the Clinical and Health Outcomes Initiative in Comparative Effectiveness for Bipolar Disorder study (Bipolar CHOICE). Bipolar Disord. 2015;17(2):212–23. [DOI] [PubMed]
- 9.Laursen TM, Wahlbeck K, Hallgren J, Westman J, Osby U, Alinaghizadeh H, Gissler M, Nordentoft M. Life expectancy and death by diseases of the circulatory system in patients with bipolar disorder or schizophrenia in the Nordic countries. PLoS One. 2013;8(6) doi: 10.1371/journal.pone.0067133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Crump C, Sundquist K, Winkleby MA, Sundquist J. Comorbidities and mortality in bipolar disorder: a Swedish national cohort study. JAMA Psychiat. 2013;70(9):931–9. doi: 10.1001/jamapsychiatry.2013.1394. [DOI] [PubMed] [Google Scholar]
- 11.Fagiolini A, Kupfer DJ, Houck PR, Novick DM, Frank E. Obesity as a correlate of outcome in patients with bipolar I disorder. Am J Psychiatry. 2003;160(1):112–7. doi: 10.1176/appi.ajp.160.1.112. [DOI] [PubMed] [Google Scholar]
- 12.Calkin C, van de Velde C, Ruzickova M, Slaney C, Garnham J, Hajek T, O'Donovan C, Alda M. Can body mass index help predict outcome in patients with bipolar disorder? Bipolar Disord. 2009;11(6):650–6. doi: 10.1111/j.1399-5618.2009.00730.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Goldstein BI, Liu SM, Zivkovic N, Schaffer A, Chien LC, Blanco C. The burden of obesity among adults with bipolar disorder in the United States. Bipolar Disord. 2011;13(4):387–95. doi: 10.1111/j.1399-5618.2011.00932.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Goldstein BI, Liu SM, Schaffer A, Sala R, Blanco C. Obesity and the three-year longitudinal course of bipolar disorder. Bipolar Disord. 2013;15(3):284–93. doi: 10.1111/bdi.12035. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kemp DE, Gao K, Chan PK, Ganocy SJ, Findling RL, Calabrese JR. Medical comorbidity in bipolar disorder: relationship between illnesses of the endocrine/metabolic system and treatment outcome. Bipolar Disord. 2010;12(4):404–13. doi: 10.1111/j.1399-5618.2010.00823.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Galvez JF, Bauer IE, Sanches M, Wu HE, Hamilton JE, Mwangi B, Kapczinski FP, Zunta-Soares G, Soares JC. Shared clinical associations between obesity and impulsivity in rapid cycling bipolar disorder: a systematic review. J Affect Disord. 2014;168:306–13. doi: 10.1016/j.jad.2014.05.054. [DOI] [PubMed] [Google Scholar]
- 17.Yim CY, Soczynska JK, Kennedy SH, Woldeyohannes HO, Brietzke E, McIntyre RS. The effect of overweight/obesity on cognitive function in euthymic individuals with bipolar disorder. Eur Psychiatry. 2012;27(3):223–8. doi: 10.1016/j.eurpsy.2011.02.004. [DOI] [PubMed] [Google Scholar]
- 18.Depp CA, Strassnig M, Mausbach BT, Bowie CR, Wolyniec P, Thornquist MH, Luke JR, McGrath JA, Pulver AE, Patterson TL, et al. Association of obesity and treated hypertension and diabetes with cognitive ability in bipolar disorder and schizophrenia. Bipolar Disord. 2014;16(4):422–31. doi: 10.1111/bdi.12200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Lackner N, Bengesser SA, Birner A, Painold A, Fellendorf FT, Platzer M, Reininghaus B, Weiss EM, Mangge H, McIntyre RS et al. Abdominal obesity is associated with impaired cognitive function in euthymic bipolar individuals. World J Biol Psychiatry. 2016;17(7):535–46. [DOI] [PubMed]
- 20.Calkin CV, Ruzickova M, Uher R, Hajek T, Slaney CM, Garnham JS, O'Donovan MC, Alda M. Insulin resistance and outcome in bipolar disorder. Br J Psychiatry. 2015;206(1):52–7. doi: 10.1192/bjp.bp.114.152850. [DOI] [PubMed] [Google Scholar]
- 21.Ruzickova M, Slaney C, Garnham J, Alda M. Clinical features of bipolar disorder with and without comorbid diabetes mellitus. Can J Psychiatry. 2003;48(7):458–61. doi: 10.1177/070674370304800705. [DOI] [PubMed] [Google Scholar]
- 22.McIntyre RS, Muzina DJ, Kemp DE, Blank D, Woldeyohannes HO, Lofchy J, Soczynska JK, Banik S, Konarski JZ. Bipolar disorder and suicide: research synthesis and clinical translation. Curr Psychiatry Rep. 2008;10(1):66–72. doi: 10.1007/s11920-008-0012-7. [DOI] [PubMed] [Google Scholar]
- 23.Trevino S, Aguilar-Alonso P, Flores Hernandez JA, Brambila E, Guevara J, Flores G, Lopez-Lopez G, Munoz-Arenas G, Morales-Medina JC, Toxqui V, et al. A high calorie diet causes memory loss, metabolic syndrome and oxidative stress into hippocampus and temporal cortex of rats. Synapse. 2015;69(9):421–33. doi: 10.1002/syn.21832. [DOI] [PubMed] [Google Scholar]
- 24.Song SW, Chung JH, Rho JS, Lee YA, Lim HK, Kang SG, Kim HN, Kim JE, Kim SH. Regional cortical thickness and subcortical volume changes in patients with metabolic syndrome. Brain Imaging Behav. 2015;9(3):588–96. doi: 10.1007/s11682-014-9311-2. [DOI] [PubMed] [Google Scholar]
- 25.Gabriel A. Adjunctive topiramate treatment in refractory obese bipolar patients: a descriptive open label study. Eating and weight disorders : EWD. 2007;12(1):48–53. doi: 10.1007/BF03327772. [DOI] [PubMed] [Google Scholar]
- 26.McIntyre RS, Riccardelli R, Binder C, Kusumakar V. Open-label adjunctive topiramate in the treatment of unstable bipolar disorder. Can J Psychiatry. 2005;50(7):415–22. doi: 10.1177/070674370505000705. [DOI] [PubMed] [Google Scholar]
- 27.Tramontina S, Zeni CP, Pheula G, Rohde LA. Topiramate in adolescents with juvenile bipolar disorder presenting weight gain due to atypical antipsychotics or mood stabilizers: an open clinical trial. J Child Adolesc Psychopharmacol. 2007;17(1):129–34. doi: 10.1089/cap.2006.0024. [DOI] [PubMed] [Google Scholar]
- 28.Vieta E, Torrent C, Garcia-Ribas G, Gilabert A, Garcia-Pares G, Rodriguez A, Cadevall J, Garcia-Castrillon J, Lusilla P, Arrufat F. Use of topiramate in treatment-resistant bipolar spectrum disorders. J Clin Psychopharmacol. 2002;22(4):431–5. doi: 10.1097/00004714-200208000-00017. [DOI] [PubMed] [Google Scholar]
- 29.Lopresti AL, Drummond PD. Obesity and psychiatric disorders: Commonalities in dysregulated biological pathways and their implications for treatment. Prog Neuropsychopharmacol Biol Psychiatry. 2013;45:92–9. doi: 10.1016/j.pnpbp.2013.05.005. [DOI] [PubMed] [Google Scholar]
- 30.Simpson GM, Angus JW. A rating scale for extrapyramidal side effects. Acta Psychiatr Scand Suppl. 1970;212:11–9. doi: 10.1111/j.1600-0447.1970.tb02066.x. [DOI] [PubMed] [Google Scholar]
- 31.Munetz MR, Schulz SC. Screening for tardive dyskinesia. J Clin Psychiatry. 1986;47(2):75–7. [PubMed] [Google Scholar]
- 32.Barnes TR. A rating scale for drug-induced akathisia. Br J Psychiatry. 1989;154:672–6. doi: 10.1192/bjp.154.5.672. [DOI] [PubMed] [Google Scholar]
- 33.Lingjaerde O, Ahlfors UG, Bech P, Dencker SJ, Elgen K. The UKU side effect rating scale. A new comprehensive rating scale for psychotropic drugs and a cross-sectional study of side effects in neuroleptic-treated patients. Acta Psychiatr Scand Suppl. 1987;334:1–100. doi: 10.1111/j.1600-0447.1987.tb10566.x. [DOI] [PubMed] [Google Scholar]
- 34.David A, Buchanan A, Reed A, Almeida O. The assessment of insight in psychosis. Br J Psychiatry. 1992;161:599–602. doi: 10.1192/bjp.161.5.599. [DOI] [PubMed] [Google Scholar]
- 35.Szulinska M, Piorunek T, Suliburska J, Pupek-Musialik D, Kupsz J, Drzymala-Czyz S, Bogdanski P. Evaluation of insulin resistance, tumor necrosis factor alpha, and total antioxidant status in obese patients smoking cigarettes. Eur Rev Med Pharmacol Sci. 2013;17(14):1916–22. [PubMed] [Google Scholar]
- 36.Szlagatys-Sidorkiewicz A, Wos E, Aleksandrowicz E, Luczak G, Zagierski M, Martysiak-Zurowska D, Marek K, Kaminska B. Cytokine profile of mature milk from smoking and nonsmoking mothers. J Pediatr Gastroenterol Nutr. 2013;56(4):382–4. doi: 10.1097/MPG.0b013e318275f95c. [DOI] [PubMed] [Google Scholar]
- 37.Bai YM, Su TP, Tsai SJ, Wen-Fei C, Li CT, Pei-Chi T, Mu-Hong C. Comparison of inflammatory cytokine levels among type I/type II and manic/hypomanic/euthymic/depressive states of bipolar disorder. J Affect Disord. 2014;166:187–92. doi: 10.1016/j.jad.2014.05.009. [DOI] [PubMed] [Google Scholar]
- 38.Barbosa IG, Huguet RB, Mendonca VA, Sousa LP, Neves FS, Bauer ME, Teixeira AL. Increased plasma levels of soluble TNF receptor I in patients with bipolar disorder. Eur Arch Psychiatry Clin Neurosci. 2011;261(2):139–43. doi: 10.1007/s00406-010-0116-z. [DOI] [PubMed] [Google Scholar]
- 39.Guloksuz S, Cetin EA, Cetin T, Deniz G, Oral ET, Nutt DJ. Cytokine levels in euthymic bipolar patients. J Affect Disord. 2010;126(3):458–62. doi: 10.1016/j.jad.2010.04.027. [DOI] [PubMed] [Google Scholar]
- 40.Bai YM, Chang CJ, Tsai SY, Chen YC, Hsiao MC, Li CT, Tu P, Chang SW, Shen WW, Su TP. Taiwan consensus of pharmacological treatment for bipolar disorder. Journal of the Chinese Medical Association : JCMA. 2013;76(10):547–56. doi: 10.1016/j.jcma.2013.06.013. [DOI] [PubMed] [Google Scholar]
- 41.Yatham LN, Kennedy SH, Parikh SV, Schaffer A, Beaulieu S, Alda M, O'Donovan C, Macqueen G, McIntyre RS, Sharma V, et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) collaborative update of CANMAT guidelines for the management of patients with bipolar disorder: update 2013. Bipolar Disord. 2013;15(1):1–44. doi: 10.1111/bdi.12025. [DOI] [PubMed] [Google Scholar]
- 42.Chang HH, Chou CH, Chen PS, Gean PW, Huang HC, Lin CY, Yang YK, Lu RB. High prevalence of metabolic disturbances in patients with bipolar disorder in Taiwan. J Affect Disord. 2009;117(1–2):124–9. doi: 10.1016/j.jad.2008.12.018. [DOI] [PubMed] [Google Scholar]
- 43.Cerit C, Vural M, Bos Gelmez SU, Ozten E, Aker AT, Yildiz M. Metabolic syndrome with different antipsychotics: a multicentre cross-sectional study. Psychopharmacol Bull. 2010;43(4):22–36. [PubMed] [Google Scholar]
- 44.Galling B, Garcia MA, Osuchukwu U, Hagi K, Correll CU. Safety and tolerability of antipsychotic-mood stabilizer co-treatment in the management of acute bipolar disorder: results from a systematic review and exploratory meta-analysis. Expert Opin Drug Saf. 2015;14(8):1181–99. doi: 10.1517/14740338.2015.1053457. [DOI] [PubMed] [Google Scholar]
- 45.Liu YT, Chau YL, Hsu SC, Chu CL, Chen CY. Factors influencing weight gain in an Asian population of psychiatric inpatients: a retrospective study in Taiwan. Asia-Pacific psychiatry. 2014;6(2):226–34. doi: 10.1111/j.1758-5872.2012.00223.x. [DOI] [PubMed] [Google Scholar]
- 46.Correll CU, Sheridan EM, DelBello MP. Antipsychotic and mood stabilizer efficacy and tolerability in pediatric and adult patients with bipolar I mania: a comparative analysis of acute, randomized, placebo-controlled trials. Bipolar Disord. 2010;12(2):116–41. doi: 10.1111/j.1399-5618.2010.00798.x. [DOI] [PubMed] [Google Scholar]
- 47.Baker RW, Brown E, Akiskal HS, Calabrese JR, Ketter TA, Schuh LM, Trzepacz PT, Watkin JG, Tohen M. Efficacy of olanzapine combined with valproate or lithium in the treatment of dysphoric mania. Br J Psychiatry. 2004;185:472–8. doi: 10.1192/bjp.185.6.472. [DOI] [PubMed] [Google Scholar]
- 48.Carlson BX, Ketter TA, Sun W, Timko K, McQuade RD, Sanchez R, Vester-Blokland E, Marcus R. Aripiprazole in combination with lamotrigine for the long-term treatment of patients with bipolar I disorder (manic or mixed): a randomized, multicenter, double-blind study (CN138-392) Bipolar Disord. 2012;14(1):41–53. doi: 10.1111/j.1399-5618.2011.00974.x. [DOI] [PubMed] [Google Scholar]
- 49.Ketter TA, Nasrallah HA, Fagiolini A. Mood stabilizers and atypical antipsychotics: bimodal treatments for bipolar disorder. Psychopharmacol Bull. 2006;39(1):120–46. [PubMed] [Google Scholar]
- 50.Abraham KM. Animal models of obesity and metabolic syndrome: potential tools for Alzheimer's disease research. Curr Alzheimer Res. 2007;4(2):145–6. doi: 10.2174/156720507780362209. [DOI] [PubMed] [Google Scholar]
- 51.Choi J, Chandrasekaran K, Demarest TG, Kristian T, Xu S, Vijaykumar K, Dsouza KG, Qi NR, Yarowsky PJ, Gallipoli R, et al. Brain diabetic neurodegeneration segregates with low intrinsic aerobic capacity. Annals of clinical and translational neurology. 2014;1(8):589–604. doi: 10.1002/acn3.86. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Dyck PJ, Giannini C. Pathologic alterations in the diabetic neuropathies of humans: a review. J Neuropathol Exp Neurol. 1996;55(12):1181–93. doi: 10.1097/00005072-199612000-00001. [DOI] [PubMed] [Google Scholar]
- 53.Yates KF, Sweat V, Yau PL, Turchiano MM, Convit A. Impact of metabolic syndrome on cognition and brain: a selected review of the literature. Arterioscler Thromb Vasc Biol. 2012;32(9):2060–7. doi: 10.1161/ATVBAHA.112.252759. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Segura B, Jurado MA, Freixenet N, Bargallo N, Junque C, Arboix A. White matter fractional anisotropy is related to processing speed in metabolic syndrome patients: a case–control study. BMC Neurol. 2010;10:64. doi: 10.1186/1471-2377-10-64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Thompson WK, Kupfer DJ, Fagiolini A, Scott JA, Frank E. Prevalence and clinical correlates of medical comorbidities in patients with bipolar I disorder: analysis of acute-phase data from a randomized controlled trial. J Clin Psychiatry. 2006;67(5):783–8. doi: 10.4088/JCP.v67n0512. [DOI] [PubMed] [Google Scholar]
- 56.McIntyre RS, Konarski JZ, Soczynska JK, Wilkins K, Panjwani G, Bouffard B, Bottas A, Kennedy SH. Medical comorbidity in bipolar disorder: implications for functional outcomes and health service utilization. Psychiatr Serv. 2006;57(8):1140–4. doi: 10.1176/ps.2006.57.8.1140. [DOI] [PubMed] [Google Scholar]
- 57.Castanon N, Lasselin J, Capuron L. Neuropsychiatric comorbidity in obesity: role of inflammatory processes. Front Endocrinol. 2014;5:74. doi: 10.3389/fendo.2014.00074. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Kane JM. Tardive dyskinesia rates with atypical antipsychotics in adults: prevalence and incidence. J Clin Psychiatry. 2004;65(Suppl 9):16–20. [PubMed] [Google Scholar]
- 59.Zhang XY, Tan YL, Zhou DF, Cao LY, Wu GY, Haile CN, Kosten TA, Kosten TR. Disrupted antioxidant enzyme activity and elevated lipid peroxidation products in schizophrenic patients with tardive dyskinesia. J Clin Psychiatry. 2007;68(5):754–60. doi: 10.4088/JCP.v68n0513. [DOI] [PubMed] [Google Scholar]
- 60.Bishnoi M, Boparai RK. An animal model to study the molecular basis of tardive dyskinesia. Methods Mol Biol. 2012;829:193–201. doi: 10.1007/978-1-61779-458-2_12. [DOI] [PubMed] [Google Scholar]
- 61.Lane EL, Soulet D, Vercammen L, Cenci MA, Brundin P. Neuroinflammation in the generation of post-transplantation dyskinesia in Parkinson's disease. Neurobiol Dis. 2008;32(2):220–8. doi: 10.1016/j.nbd.2008.06.011. [DOI] [PubMed] [Google Scholar]
- 62.Lerner V, Miodownik C, Kaptsan A, Bersudsky Y, Libov I, Sela BA, Witztum E. Vitamin B6 treatment for tardive dyskinesia: a randomized, double-blind, placebo-controlled, crossover study. J Clin Psychiatry. 2007;68(11):1648–54. doi: 10.4088/JCP.v68n1103. [DOI] [PubMed] [Google Scholar]
- 63.Libov I, Miodownik C, Bersudsky Y, Dwolatzky T, Lerner V. Efficacy of piracetam in the treatment of tardive dyskinesia in schizophrenic patients: a randomized, double-blind, placebo-controlled crossover study. J Clin Psychiatry. 2007;68(7):1031–7. doi: 10.4088/JCP.v68n0709. [DOI] [PubMed] [Google Scholar]
- 64.Telfer S, Shivashankar S, Krishnadas R, McCreadie RG, Kirkpatrick B. Tardive dyskinesia and deficit schizophrenia. Acta Psychiatr Scand. 2011;124(5):357–62. doi: 10.1111/j.1600-0447.2011.01751.x. [DOI] [PubMed] [Google Scholar]
- 65.Ascher-Svanum H, Zhu B, Faries D, Peng X, Kinon BJ, Tohen M. Tardive dyskinesia and the 3-year course of schizophrenia: results from a large, prospective, naturalistic study. J Clin Psychiatry. 2008;69(10):1580–8. doi: 10.4088/JCP.v69n1008. [DOI] [PubMed] [Google Scholar]
- 66.Berry K, Drake R, Stewart C, Aitkin LM, Byrne J, Barrowclough C, Purandare N. Orofacial dyskinesia, frontal lobe dysfunction, and coping in older people with psychosis. Am J Geriatr Psychiatry. 2007;15(9):800–6. doi: 10.1097/JGP.0b013e31806841ae. [DOI] [PubMed] [Google Scholar]
- 67.Li CT, Chou KH, Su TP, Huang CC, Chen MH, Bai YM, Lin CP. Gray matter abnormalities in schizophrenia patients with tardive dyskinesia: a magnetic resonance imaging voxel-based morphometry study. PLoS One. 2013;8(8) doi: 10.1371/journal.pone.0071034. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Bai YM, Chou KH, Lin CP, Chen IY, Li CT, Yang KC, Chou YH, Su TP. White matter abnormalities in schizophrenia patients with tardive dyskinesia: a diffusion tensor image study. Schizophr Res. 2009;109(1–3):167–81. doi: 10.1016/j.schres.2009.02.003. [DOI] [PubMed] [Google Scholar]
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Data Availability Statement
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