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|Year : 2018
: 60 | Issue : 4 | Page
|Biological rhythm impairment in bipolar disorder: A state or trait marker?
Pooja Patnaik Kuppili1, Vikas Menon2, Vigneshvar Chandrasekaran2, Karthick Navin2
1 Department of Psychiatry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
2 Department of Psychiatry, Jawaharlal Institute of Post Graduate Medical Education and Research, Puducherry, India
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|Date of Web Publication||28-Nov-2018|
| Abstract|| |
Context: There is limited research on biological rhythms in bipolar disorder (BD) from the Indian setting despite its intricate relationship with metabolic syndrome (MS) and functioning.
Aims: The study aimed to assess “trait marker” status of biological rhythms as well as correlates of biological rhythm impairment in euthymic BD.
Setting and Design: Cross-sectional observational study over 6 months was carried out in hospital setting.
Materials and Methods: Biological Rhythms Interview of Assessment in Neuropsychiatry Questionnaire (BRIAN) and Functioning Assessment Short Test (FAST) were used to assess biological rhythms and functioning, respectively. MS was diagnosed as per modified National Cholesterol Education Program– Adult Treatment Panel III. Depressive symptoms were assessed by the Hamilton Depression Rating Scale (HDRS). Euthymia was defined as symptomatic remission for at least 8 weeks. Ethical approval was taken.
Results: Fifty cases of euthymic BD and fifty apparently healthy controls were recruited. Total as well as certain domain-specific BRIAN and FAST scores were significantly higher in cases compared to controls. A significant positive correlation was found between the total BRIAN score with HDRS as well as FAST score. No correlation was obtained between biological rhythms and metabolic parameters.
Conclusions: Our results support the hypothesis that biological rhythm impairment is a trait marker in patients with BD. The study supports the need for management of subsyndromal depressive symptoms even in inter-episodic period.
Keywords: Biological rhythms, functioning, metabolic syndrome, subsyndromal depression, trait marker
|How to cite this article:|
Kuppili PP, Menon V, Chandrasekaran V, Navin K. Biological rhythm impairment in bipolar disorder: A state or trait marker?. Indian J Psychiatry 2018;60:404-9
| Introduction|| |
Bipolar disorder (BD) is an episodic affective illness with significant global morbidity accounting to 7% of DALYs caused by mental and substance use disorders even with conservative estimates of the prevalence of 1%. Although the patients are apparently normal, cognitive deficits have been reported even during the inter-episodic period., Thereby, it is the need of the hour to focus on hidden yet relevant and modifiable factors that could improve the course of BD. One such factor which is gaining importance in recent times is that of Biological rhythms. Biological rhythms are cyclical physical or chemical changes occurring in the body. A bidirectional relationship is found to exist between biological rhythms and BD. Impairments in biological rhythms such as decreased need for sleep and increased activity are hallmarks of BD. Further, sleep deprivation or deficits in social rhythms or interpersonal relationships precipitating an episode is well established in BD and these impairments are addressed as a part of interpersonal and social rhythm therapy.
Studies suggest that a close relationship exists between impairments in biological rhythms and metabolic syndrome., The association between the disruption of circadian rhythms and alteration of metabolic parameters could be due to the effect of several biochemical and physiological processes initiated by genetic abnormalities. The prevalence rates of Metabolic syndrome (MS) have been found to be nearly two-fold higher in patients with BD compared to the general population. The association of biological rhythm disturbance with MS has been relatively unexplored in BD despite the existing literature of the role of circadian rhythms in metabolic syndrome. There are no studies from India assessing the relationship of biological rhythms, MS and functioning in BD. Assessing the role of metabolic parameters is all the more important in the Asian setting, considering the higher burden of MS.
With this background, the current study hypothesized that impairment of biological rhythms in BD is a trait marker and is associated with impairments in metabolic parameters and functioning.
The primary objective is to compare biological rhythm disturbances between euthymic cases of BD and apparently healthy controls. The secondary objective is to assess the relationship between biological rhythms with clinical and treatment variables, functioning and metabolic parameters in patients with BD.
| Materials and Methods|| |
The study was a cross-sectional observational study carried out throughout 6 months from January to July 2017 in Jawaharlal Institute of Post Graduate Medical Education and Research (JIPMER). The hospital serves patients from Puducherry and neighboring districts of the state of Tamil Nadu. All cases presenting to the psychiatry outpatient department are first evaluated by a Senior Resident for psychiatric morbidity. Subsequent detailed evaluation of symptoms is performed by psychiatry trainees following which the case is discussed with the consultant psychiatrist and a detailed diagnosis and management plan is formulated. All psychiatric diagnoses are made as per the International Classification of Diseases-10. These patients are subsequently asked to follow-up in the bipolar clinic which is run weekly. A total of around 350–400 patients divided into three batches are under the follow-up of this clinic. Patients or their caregivers attend the follow-up clinic and receive drug refills once in 3 weeks, after assessment by the psychiatrist.
There are no studies assessing the prevalence of biological rhythm impairment in patients with euthymic BD. A study by Dopierala et al., 2016 had assessed biological rhythm impairment in euthymic BD in 54 cases and 54 controls. The population of euthymic BD was entered as 54 with 95% confidence interval and 5% alpha error which gives sample size of 47 in the euthymic BD group. This was rounded off to 50 each in euthymic BD and healthy control group each.
Study sampling and population
Sampling was hospital-based convenience sampling. The study included two groups. The patients who were currently under remission were included in the euthymic BD group. The second group comprised apparently healthy controls selected from voluntary blood donors visiting the blood bank of JIPMER. The selection criteria for the two groups are as follows:
- Euthymic BD: patients of either gender aged between 18 and 60 years diagnosed with having BD as per Diagnostic and Statistical Manual-5.0 (DSM– 5.0) with Young Mania Rating Scale (YMRS) ≤8 or Hamilton Depression Rating Scale (HDRS) ≤7 for the past 8 weeks
- Apparently healthy controls: participants of either gender aged between 18 and 60 years with no history of chronic medical/surgical illness or psychiatric illness (ascertained through medical records). The controls were age and gender matched.
Shift workers, patients with comorbid axis I psychiatric illness and those who could not read or write Tamil or English were excluded from the study.
Clearance for this study was obtained from the Institute Ethics Committee. Written Informed consent from all participants was obtained in the local language.
Sociodemographic and clinical details were collected using a semi-structured pro forma. Diagnosis of BD was made by DSM-5 criteria. The Mini-International neuropsychiatric interview 5.0 was used to assess for psychiatric comorbidity and thereby exclude participants (in both groups) with psychiatric comorbidity. The predominant polarity was defined as predominantly manic and predominantly depressive if at least two-thirds of the past episodes were fulfilling criteria for manic/hypomanic episodes and for major depressive episode as per DSM-IV TR. The Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN) was used for assessing biological rhythms. BRIAN is a 21 item questionnaire assessing domains of sleep, activity, social, diet, and chronotype over the last 2 weeks. The greater the score obtained, the higher is the impairment in biological rhythms. The BRIAN questionnaire is a self-rated questionnaire previously validated in Tamil speaking patients with BD. BRIAN questionnaire was translated into Tamil and later back-translated to English to check for equivalence. Further, pilot study of the translated Tamil version was carried out on ten patients with BD to check for feasibility.
Functioning assessment screening tool (FAST) was used for assessing functioning. It assesses domains of autonomy, work, cognitive functioning, financial issues, interpersonal relationships, and leisure. FAST has been previously used in our setting. The National Institute of Mental Health-Life Chart Methodology (NIMH-LCM™) Clinician Retrospective Chart was used for assessing details about episodes, comorbid symptoms, life events, details of hospitalization, and medication. HDRS was used to assessing symptoms of depression and YMRS was used for assessing symptoms of mania.
Only euthymic patients of BD could be assessed for MS as per modified National Cholesterol Education Program– Adult Treatment Panel III (NCEP ATP III) criteria. As per modified NCEP ATP III criteria, MS is diagnosed if three out of five criteria are met: Waist circumference of 90 cm in men and 80 cm in women; hypertriglyceridemia (triglycerides ≥150 mg/dl), low high density lipoprotein (HDL) cholesterol (HDL cholesterol ≤40 mg/dl for men and ≤50 mg/dl for women); elevated blood pressure (systolic blood pressure ≥130 mmHg and/or diastolic blood pressure ≥85 mmHg or current use of antihypertensive drugs); impaired fasting glucose (fasting plasma glucose ≥110 mg/dl). Waist circumference was measured at the approximate midpoint between lower margin of last palpable rib and top of the iliac crest.
Descriptive analysis such as percentages, frequency, central tendencies, and tests for normal distribution were performed initially. For comparison of continuous variables such as BRIAN, and FAST scores between two groups, independent sample Student's t-test and Mann–Whitney U-test were applied for data with normal distribution and non-normal distribution, respectively. For categorical variables such as gender, educational status, etc., Chi-square test and Fisher's exact test (FET) were used accordingly (FET = when the number in the cells was <5). For correlation, Pearson correlation test and Spearman correlation test were used for parametric and nonparametric samples, respectively. The two-sided P ≤ 0.05 was considered statistically significant. Data analysis was done by licensed statistical package SPSS (version 17.0; SPSS Inc., Chicago, IL, USA).
| Results|| |
A total of 124 patients were screened. Sixty-six patients were patients of euthymic BD. Of which, six patients were euthymic for <8 weeks. Five were excluded as they did not give consent and three patients could not read or write Tamil or English and two were aged >60 years. Finally, 50 cases of euthymic BD were included.
58 patients were apparently healthy controls. Out of these, three had psychiatric morbidity, two did not give consent and three patients could not read or write Tamil or English. Finally, 50 healthy controls were included.
The typical profile of a case was that of a married middle-aged male who has received about 10 years of formal education belonging to lower socioeconomic status and residing in an urban/semi-urban area. The controls were also similar to cases, except they were significantly better educated, belonged to middle socioeconomic status and lesser number of controls were married [Table 1].
Predominant polarity was mania in 96% of cases. The median number of episodes was 3.00 (interquartile range [IQR] = 2.00). The median duration since the last episode was 63.50 (IQR = 115) weeks. Mean (standard deviation [SD]) HDRS of cases and controls were 2 (1.95) and 0.22 (0.79). Mean (SD) of YMRS of cases was 0.34 (0.69). All of the controls had YMRS of 0. Hence, HDRS (U = 522.00; P < 0.001) as well as YMRS (U = 975.00; P < 0.001) was significantly higher in cases compared to controls.
The median chlorpromazine dose years was 383.00 (IQR = 703.60). The median number of psychotropic medications received over the past 1 year was 2.00 (IQR = 2.00). About 14% had ever received antidepressants. About 62% and 26% of patients were on Sodium valproate and Lithium predominantly across their lifespan until the date of recruitment. About 14% of cases received modified electroconvulsive therapy.
Profile of biological rhythms
Cases had significantly higher impairment of biological rhythms as measured by domains as well as total scores of BRIAN and PSQI [Table 2].
The cases had significantly poor functioning compared to healthy controls in total FAST (U = 215.00; P = 0.00) as well as domains of FAST, autonomy (U = 580.00; P = 0.00), occupational (U = 635.00; P = 0.00), cognitive (U = 271.00; P = 0.00), and interpersonal domain (U = 646.00; P = 0.00).
Profile of metabolic parameters
MS was diagnosed in 47.50% of cases. Decreased HDL was the most common abnormality among components of MS noted (67.50%) followed by increased waist circumference (62.50%), increased systolic blood pressure (50.00%), increased triglyceride (37.50%), increased fasting blood sugar (17.50%), and increased diastolic blood pressure (5.00%).
Correlation between biological rhythms and functioning, metabolic parameters, and other clinical variables
Significant correlation was obtained between total BRIAN score and total FAST (rs = 0.80; P < 0.001) as well as domains of FAST, autonomy (rs = 0.68; P < 0.001), occupational (rs = 0.58; P < 0.001), cognitive (rs = 0.64; P < 0.001), financial (rs = 0.28; P = 0.047), and interpersonal relationship (rs = 0.39; P = 0.01).
No significant correlation was obtained between BRIAN scores and components of MS.
The correlation between BRIAN scores and clinical variables is given in [Table 3].
|Table 3: Correlation between biological rhythms interview of assessment in neuropsychiatry scores and clinical variables|
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Significant correlation was observed between HDRS and total BRIAN score (Spearman correlation; rs = 0.67; P < 0.001; [Figure 1]) as well as sleep domain of BRIAN (Spearman correlation; rs = 0.69; P = 0.01; [Figure 2]). Significant correlation was also found between HDRS and activity domain of BRIAN (rs = 0.32; P = 0.02) as well as diet domain (rs = 0.30; P < 0.001).
|Figure 1: Correlation between total Biological Rhythms Interview of Assessment in Neuropsychiatry score and Hamilton Depressive Rating Scale|
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|Figure 2: Correlation between sleep domain of Biological Rhythms Interview of Assessment in Neuropsychiatry and Hamilton Depressive Rating Scale|
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| Discussion|| |
The chief finding of the study was that biological rhythms were significantly impaired in patients with euthymic BD. Total BRIAN as well as all domains of BRIAN except chronotype domain were significantly higher in cases with remitted BD compared to healthy controls. The current finding is in concordance with previous studies.,,,,, A study from Spain reported significant difference in only domains of sleep, activity, and social domains. An Indian study noted significant impairment only in activity, social, and diet domains. This adds to the growing evidence that impairment of biological rhythms could be a trait marker in BD. Further, this finding might also have potential utility in differentiating bipolar depression from unipolar depression as impairment in biological rhythms was found specific to remitted cases of BD but not in remitted major depressive disorder.
The finding of no correlation between the total BRIAN score and duration since the last episode further adds credence to the consideration of biological rhythm impairment being a trait marker. Although a correlation was demonstrated between sleep as well as social activity with duration since the last episode, the magnitude of correlation was small.
In our study, subsyndromal depressive symptoms in euthymic BD significantly correlated with impairment in total BRIAN as well as domains of sleep, activity, and social activity. These findings are partly supported by findings of an Indian study, which found a significant correlation between HDRS scores and total BRIAN as well as sleep and activity domains of BRIAN. Consistently, subsyndromal depressive symptoms have been found to be predictors of impairment of biological rhythms in euthymic BD in western as well as Indian studies., Further, improvement of depressive symptoms by a combination of psychoeducation of biological rhythms and medication was found to significantly improve sleep and social domains at 6 months of follow-up in a study from Brazil.
The euthymic BD reported significantly poor functioning compared to the control group, in accordance with previous studies., However, this finding needs to be interpreted carefully considering the better educational status of controls compared to cases. Impairment of biological rhythms significantly correlated with poor functioning. A significant correlation was obtained between total BRIAN score and total FAST as well as domains of FAST such as autonomy, occupational, cognitive, financial, and interpersonal relationship. Biological rhythm disturbance emerged as the most important predictor of impairment of functioning in a study reported from Brazil. In a multicentric study from Spain, Canada, and Brazil, biological function impairment and subsyndromal depressive symptoms were found to be independent predictors of functioning in BD in euthymia. Residual depressive symptoms have often been linked to poor functioning in nearly remitted BD. On the basis of this evidence, it looks like biorhythms may be the underlying mechanism through which this link can be explained. Future studies employing path analysis techniques can clarify this further.
Age of onset inversely correlated with chronotype domain of biological rhythm. This finding could be understandable in the context of complex interaction between age of onset and molecular clock genes which determine the chronotype. Certain polymorphisms of molecular clock gene, Per3 gene have been associated with early age of onset. It may also imply that early-onset and late-onset BD are two distinct populations with independent correlates and possibly endophenotypes.
The significant positive correlation was found between number of psychotropic medication and impairment of biological rhythms, especially sleep domain. This could perhaps be due to patients with sleep disturbance being prescribed more number of medication as biological rhythms, sleep and subsyndromal depression are closely interlinked as discussed earlier. Further, a bidirectional relationship has been noted between biological rhythms and action of the psychotropic medication. It is also important to consider that the patients were receiving Valproate predominantly as the valproic acid was found to alter the sleep architecture. As lithium is found to have mechanism of action through circadian pathways,, it would be worth comparing the effect of various mood stabilizers on biological rhythms in future studies.
The current study found no correlation between biological rhythms and metabolic parameters. Despite extensive search of the literature, we could not come across any studies which have assessed the association between biological rhythms and metabolic parameters in euthymic BD. The study focus on euthymic BD could be one of the reasons of not finding any association between biological rhythms and metabolic parameters as derangements in metabolic parameters are increasingly being reported as “state” changes rather than “trait” changes. There is preliminary evidence to suggest that cholesterol could be a state marker of BD. Significant interaction was reported between impairment of biological rhythms, especially sleep, social and eating domains and MS in patients with depression in a previous study. Comparison of metabolic parameters as well as assessing the association of metabolic parameters and biological rhythms in active and euthymic cases of BD might improve our understanding of the complex interaction of biological rhythms with metabolic parameters in the future.
The study is probably the first from India to comprehensively assess biological rhythms, functioning and metabolic parameters in euthymic BD. The study reflects the real world patients with BD who have comorbidities such as substance use or medical illnesses. However, few limitations exist such as the small sample size, cross-sectional study design, and lack of objective parameters to assess biological rhythms. No structured assessment of medication adherence was done. Hence, the confounding role of antipsychotics, mood stabilizers, antidepressants as well as benzodiazepines could not be addressed in the study. No structured instrument was used to screen for sleep disorders. The findings may not be generalizable due to the setting and sampling design. There is a need for future studies to assess if biorhythm disturbances are causal to or an epiphenomenon of behavioral problems in BD.
| Conclusions|| |
The findings of the study emphasize the importance of recognizing an impairment of biological rhythms as a trait marker in BD. The study also highlights the intricate relationship between biological rhythms, subsyndromal depressive symptoms, and functioning. The study findings have important treatment implications. Treating of subsyndromal depressive symptoms in the euthymic period and proper psychoeducation about biological rhythms should be emphasized during treatment of patients with BD to ensure better functioning.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Whiteford HA, Degenhardt L, Rehm J, Baxter AJ, Ferrari AJ, Erskine HE, et al.
Global burden of disease attributable to mental and substance use disorders: Findings from the Global Burden of Disease Study 2010. Lancet 2013;382:1575-86.
Kapczinski F, Vieta E, Andreazza AC, Frey BN, Gomes FA, Tramontina J, et al.
Allostatic load in bipolar disorder: Implications for pathophysiology and treatment. Neurosci Biobehav Rev 2008;32:675-92.
Huxley N, Baldessarini RJ. Disability and its treatment in bipolar disorder patients. Bipolar Disord 2007;9:183-96.
Reinberg A, Ashkenazi I. Concepts in human biological rhythms. Dialogues Clin Neurosci 2003;5:327-42.
Sheikh-Ali M, Maharaj J. Circadian clock desynchronisation and metabolic syndrome. Postgrad Med J 2014;90:461-6.
Maury E, Ramsey KM, Bass J. Circadian rhythms and metabolic syndrome: From experimental genetics to human disease. Circ Res 2010;106:447-62.
Vancampfort D, Vansteelandt K, Correll CU, Mitchell AJ, De Herdt A, Sienaert P, et al.
Metabolic syndrome and metabolic abnormalities in bipolar disorder: A meta-analysis of prevalence rates and moderators. Am J Psychiatry 2013;170:265-74.
Pandit K, Goswami S, Ghosh S, Mukhopadhyay P, Chowdhury S. Metabolic syndrome in South Asians. Indian J Endocrinol Metab 2012;16:44-55.
World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva: World Health Organization; 1992.
Dopierala E, Chrobak A, Kapczinski F, Michalak M, Tereszko A, Ferensztajn-Rochowiak E, et al.
A study of biological rhythm disturbances in polish remitted bipolar patients using the BRIAN, CSM, and SWPAQ scales. Neuropsychobiology 2016;74:125-30.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). 5th
ed. Washington, D.C: American Psychiatric Association; 2013.
Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scale for mania: Reliability, validity and sensitivity. Br J Psychiatry 1978;133:429-35.
Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56-62.
Sheehan DV, Lecrubier Y. MINI International Neuropsychiatric Interview for DSM-IV (English Version 5.0.0). Tampa: University of South Florida; 2002.
Volkert J, Zierhut KC, Schiele MA, Wenzel M, Kopf J, Kittel-Schneider S, et al.
Predominant polarity in bipolar disorder and validation of the polarity index in a German sample. BMC Psychiatry 2014;14:322.
Giglio LM, Magalhães PV, Andreazza AC, Walz JC, Jakobson L, Rucci P, et al.
Development and use of a biological rhythm interview. J Affect Disord 2009;118:161-5.
Rosa AR, Sánchez-Moreno J, Martínez-Aran A, Salamero M, Torrent C, Reinares M, et al.
Validity and reliability of the functioning assessment short test (FAST) in bipolar disorder. Clin Pract Epidemiol Ment Health 2007;3:5.
Karthick S, Kattimani S, Sarkar S, Bharadwaj B, Rajkumar RP. Quality of sleep in patients with bipolar I disorder during remission. J Psychiatr Pract 2015;21:419-26.
Leverich GS, Post RM. The NIMH life chart manual for recurrent affective illness: The NIMH-LCM. Biol Psychiatry Branch Monogr Revis. Bethesda, MD: National Institute of Mental Health; 1997.
Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al.
Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Curr Opin Cardiol 2006;21:1-6.
World Health Organization. WHO STEPwise Approach to Surveillance (STEPS). Geneva: World Health Organization; 2008b.
Rosa AR, Comes M, Torrent C, Solè B, Reinares M, Pachiarotti I, et al.
Biological rhythm disturbance in remitted bipolar patients. Int J Bipolar Disord 2013;1:6.
Iyer A, Palaniappan P. Biological dysrhythm in remitted bipolar I disorder. Asian J Psychiatr 2017;30:218-24.
Mondin TC, Cardoso TA, Souza LDM, Jansen K, da Silva Magalhães PV, Kapczinski F, et al.
Mood disorders and biological rhythms in young adults: A large population-based study. J Psychiatr Res 2017;84:98-104.
Pinho M, Sehmbi M, Cudney LE, Kauer-Sant'anna M, Magalhães PV, Reinares M, et al.
The association between biological rhythms, depression, and functioning in bipolar disorder: A large multi-center study. Acta Psychiatr Scand 2016;133:102-8.
Duarte Faria A, Cardoso Tde A, Campos Mondin T, Souza LD, Magalhaes PV, Patrick Zeni C, et al.
Biological rhythms in bipolar and depressive disorders: A community study with drug-naïve young adults. J Affect Disord 2015;186:145-8.
Giglio LM, Magalhães PV, Kapczinski NS, Walz JC, Kapczinski F. Functional impact of biological rhythm disturbance in bipolar disorder. J Psychiatr Res 2010;44:220-3.
Cardoso Tde A, Campos Mondin T, Reyes AN, Zeni CP, Souza LD, da Silva RA, et al.
Biological rhythm and bipolar disorder: Twelve-month follow-up of a randomized clinical trial. J Nerv Ment Dis 2015;203:792-7.
Benedetti F, Dallaspezia S, Colombo C, Pirovano A, Marino E, Smeraldi E, et al.
A length polymorphism in the circadian clock gene per3 influences age at onset of bipolar disorder. Neurosci Lett 2008;445:184-7.
Oral E, Özcan H, Güleç M, Selvi Y, Aydın A. Psychotropic medications affecting biological rhythm. J Mood Dis 2011;1:169-77.
DeMartinis NA, Winokur A. Effects of psychiatric medications on sleep and sleep disorders. CNS Neurol Disord Drug Targets 2007;6:17-29.
Ghaemi SN, Shields GS, Hegarty JD, Goodwin FK. Cholesterol levels in mood disorders: High or low? Bipolar Disord 2000;2:60-4.
Moreira FP, Jansen K, Mondin TC, Cardoso Tde A, Magalhães PV, Kapczinski F, et al.
Biological rhythms, metabolic syndrome and current depressive episode in a community sample. Psychoneuroendocrinology 2016;72:34-9.
Dr. Vikas Menon
Department of Psychiatry, Jawaharlal Institute of Post Graduate Medical Education and Research, Puducherry - 605 006
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]