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Using classification and regression tree modeling to investigate appetite hormones and proinflammatory cytokines as biomarkers to differentiate bipolar I depression from major depressive disorder

Published online by Cambridge University Press:  10 February 2021

Kai-Lin Huang ,
Mu-Hong Chen Open the ORCID record for Mu-Hong Chen [Opens in a new window] ,
Ju-Wei Hsu ,
Shih-Jen Tsai  and
Ya-Mei Bai
Kai-Lin Huang
Affiliation:
Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
Mu-Hong Chen*
Affiliation:
Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
Ju-Wei Hsu
Affiliation:
Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
Shih-Jen Tsai
Affiliation:
Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
Ya-Mei Bai*
Affiliation:
Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
*
*Author for correspondence: Mu-Hong Chen, MD, PhD Email: kremer7119@gmail.com
*Ya-Mei Bai, MD, PhD Email: ymbi@mail2000.com.tw
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Abstract

Background

Altered immunity and metabolic profiles have been compared between bipolar depression (BD) and major depressive disorder (MDD). This study aimed at developing a composite predictor of appetite hormones and proinflammatory cytokines to differentiate BD from MDD.

Methods

This cross-sectional study enrolled patients with BD and those with MDD aged 20 to 59 years and displaying depressive episodes. Clinical characteristics (age, sex, body mass index, and depression severity), cytokines (C-reactive protein, interleukin [IL]-2, IL-6, tumor necrosis factor [TNF]-α, P-selectin, and monocyte chemoattractant protein), and appetite hormones (leptin, adiponectin, ghrelin, and insulin) were assessed as potential predictors using a classification and regression tree (CRT) model for differentiating BD from MDD.

Results

The predicted probability of a composite predictor of ghrelin and TNF-α was significantly greater (for BD: area under curve = 0.877; for MDD: area under curve = 0.914) than that of any one marker (all P > .05) to distinguish BD from MDD. The most powerful predictors for diagnosing BD were high ghrelin and TNF-α levels, whereas those for MDD were low ghrelin and TNF-α levels.

Conclusion

A composite predictor of ghrelin and TNF-α driven by CRT could assist in the differential diagnosis of BD from MDD with high specificity. Further clinical studies are warranted to validate our results and to explore underlying mechanisms.

Keywords

Bipolar disordermajor depressive disordercytokinesghrelinclassification and regression tree
Type
Original Research
Information
CNS Spectrums , Volume 27 , Issue 4 , August 2022 , pp. 450 - 456
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Vöhringer, PA, Perlis, RH. Discriminating between bipolar disorder and major depressive disorder. Psychiatric Clin North Am. 2016;39(1):1–10.CrossRefGoogle ScholarPubMed
Angst, J, Gamma, A, Benazzi, F, et al. Toward a re-definition of subthreshold bipolarity: epidemiology and proposed criteria for bipolar-II, minor bipolar disorders and hypomania. J Affect Disord. 2003;73(1–2):133–146.CrossRefGoogle Scholar
Baldessarini, RJ, Tondo, L, Pinna, M, et al. Suicidal risk factors in major affective disorders. Br J Psychiatry. 2019;215(4):621–626.CrossRefGoogle Scholar
Ren, J, Zhao, G, Sun, X, et al. Identification of plasma biomarkers for distinguishing bipolar depression from major depressive disorder by iTRAQ-coupled LC-MS/MS and bioinformatics analysis. Psychoneuroendocrinology. 2017;86:17–24.CrossRefGoogle ScholarPubMed
Fernandes, BS, Gama, CS, Kauer-Sant'Anna, M, et al. Serum brain-derived neurotrophic factor in bipolar and unipolar depression: a potential adjunctive tool for differential diagnosis. J Psychiatr Res. 2009;43(15):1200–1204.CrossRefGoogle ScholarPubMed
Bai, YM, Chen, MH, Hsu, JW, et al. A comparison study of metabolic profiles, immunity, and brain gray matter volumes between patients with bipolar disorder and depressive disorder. J Neuroinflammation. 2020;17(1):42. CrossRefGoogle ScholarPubMed
Bai, YM, Su, TP, Li, CT, et al. Comparison of pro-inflammatory cytokines among patients with bipolar disorder and unipolar depression and normal controls. Bipolar Disord. 2015;17(3):269–277.CrossRefGoogle ScholarPubMed
Brunoni, AR, Supasitthumrong, T, Teixeira, AL, et al. Differences in the immune-inflammatory profiles of unipolar and bipolar depression. J Affect Disord. 2020;262:8–15.CrossRefGoogle ScholarPubMed
Rosso, G, Cattaneo, A, Zanardini, R, et al. Glucose metabolism alterations in patients with bipolar disorder. J Affect Disord. 2015;184:293–298.CrossRefGoogle ScholarPubMed
Bai, YM, Chiou, WF, Su, TP, et al. Pro-inflammatory cytokine associated with somatic and pain symptoms in depression. J Affect Disord. 2014;155:28–34.CrossRefGoogle ScholarPubMed
Morin, V, Hozer, F, Costemale-Lacoste, JF. The effects of ghrelin on sleep, appetite, and memory, and its possible role in depression: a review of the literature. L’Encephale. 2018;44(3):256–263.CrossRefGoogle ScholarPubMed
Wittekind, DA, Kluge, M. Ghrelin in psychiatric disorders—a review. Psychoneuroendocrinology. 2015;52:176–194.CrossRefGoogle ScholarPubMed
Stieg, MR, Sievers, C, Farr, O, et al. Leptin: a hormone linking activation of neuroendocrine axes with neuropathology. Psychoneuroendocrinology. 2015;51:47–57.CrossRefGoogle ScholarPubMed
Cordas, G, Gazal, M, Schuch, EM, et al. Leptin in depressive episodes: is there a difference between unipolar and bipolar depression? Neuroendocrinology. 2015;101(1):82–86.CrossRefGoogle Scholar
Syk, M, Ellstrom, S, Mwinyi, J, et al. Plasma levels of leptin and adiponectin and depressive symptoms in young adults. Psychiatry Res. 2019;272:1–7.CrossRefGoogle ScholarPubMed
Mansur, RB, Rizzo, LB, Santos, CM, et al. Adipokines, metabolic dysfunction and illness course in bipolar disorder. J Psychiatric Res. 2016;74:63–69.CrossRefGoogle ScholarPubMed
Chen, JJ, Zhou, CJ, Liu, Z, et al. Divergent urinary metabolic phenotypes between major depressive disorder and bipolar disorder identified by a combined GC-MS and NMR spectroscopic metabonomic approach. J Proteome Res. 2015;14(8):3382–3389.CrossRefGoogle ScholarPubMed
Wollenhaupt-Aguiar, B, Librenza-Garcia, D, Bristot, G, et al. Differential biomarker signatures in unipolar and bipolar depression: a machine learning approach. Aust N Z J Psychiatry. 2020;54(4):393–401.CrossRefGoogle ScholarPubMed
van der Ploeg, T, Austin, PC, Steyerberg, EW. Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints. BMC Med Res Methodol. 2014;14:137.CrossRefGoogle ScholarPubMed
Boerstler, H, de Figueiredo, JM. Prediction of use of psychiatric services: application of the CART (classification and regression trees) algorithm. J Ment Health Adm. 1991;18(1):27–34.CrossRefGoogle ScholarPubMed
Blockeel, H, Struyf, J. Efficient algorithms for decision tree cross-validation. J Mach Learn Res. 2003;3(null):621–650.Google Scholar
Himmerich, H, Sheldrick, AJ. TNF-alpha and ghrelin: opposite effects on immune system, metabolism and mental health. Protein Pept Lett. 2010;17(2):186–196.CrossRefGoogle ScholarPubMed
Soczynska, JK, Kennedy, SH, Woldeyohannes, HO, et al. Mood disorders and obesity: understanding inflammation as a pathophysiological nexus. Neuromol Med. 2011;13(2):93–116.CrossRefGoogle ScholarPubMed
Kurt, E, Guler, O, Serteser, M, et al. The effects of electroconvulsive therapy on ghrelin, leptin and cholesterol levels in patients with mood disorders. Neurosci Lett. 2007;426(1):49–53.CrossRefGoogle ScholarPubMed
Ozsoy, S, Besirli, A, Abdulrezzak, U, et al. Serum ghrelin and leptin levels in patients with depression and the effects of treatment. Psychiatry Investig. 2014;11(2):167–172.CrossRefGoogle ScholarPubMed
Barim, AO, Aydin, S, Colak, R, et al. Ghrelin, paraoxonase and arylesterase levels in depressive patients before and after citalopram treatment. Clin Biochem. 2009;42(10–11):1076–1081.CrossRefGoogle ScholarPubMed
Matsuo, K, Nakano, M, Nakashima, M, et al. Neural correlates of plasma acylated ghrelin level in individuals with major depressive disorder. Brain Res. 2012;1473:185–192.CrossRefGoogle ScholarPubMed
Schanze, A, Reulbach, U, Scheuchenzuber, M, et al. Ghrelin and eating disturbances in psychiatric disorders. Neuropsychobiology. 2008;57(3):126–130.CrossRefGoogle ScholarPubMed
Pinar, M, Gulsun, M, Tasci, I, et al. Maprotiline induced weight gain in depressive disorder: changes in circulating ghrelin and adiponectin levels and insulin sensitivity. Prog Neuropsychopharmacol Biol Psychiatry. 2008;32(1):135–139.CrossRefGoogle ScholarPubMed
Mao, R, Zhang, C, Chen, J, et al. Different levels of pro- and anti-inflammatory cytokines in patients with unipolar and bipolar depression. J Affect Disord. 2018;237:65–72.CrossRefGoogle ScholarPubMed
Hung, YJ, Hsieh, CH, Chen, YJ, et al. Insulin sensitivity, proinflammatory markers and adiponectin in young males with different subtypes of depressive disorder. Clin Endocrinol (Oxf). 2007;67(5):784–789.CrossRefGoogle ScholarPubMed
Iacob, E, Light, KC, Tadler, SC, et al. Dysregulation of leukocyte gene expression in women with medication-refractory depression versus healthy non-depressed controls. BMC Psychiatry. 2013;13:273. CrossRefGoogle ScholarPubMed
Sowa-Kucma, M, Styczen, K, Siwek, M, et al. Are there differences in lipid peroxidation and immune biomarkers between major depression and bipolar disorder: effects of melancholia, atypical depression, severity of illness, episode number, suicidal ideation and prior suicide attempts. Prog Neuropsychopharmacol Biol Psychiatry. 2018;81:372–383.CrossRefGoogle ScholarPubMed
Fernandes, BS, Williams, LM, Steiner, J, et al. The new field of “precision psychiatry”. BMC Med. 2017;15(1):80. CrossRefGoogle Scholar
Fernandes, BS, Berk, M. Staging in bipolar disorder: one step closer to precision psychiatry. Braz J Psychiatry. 2017;39(2):88–89.CrossRefGoogle ScholarPubMed
Fernandes, BS, Borgwardt, S, Carvalho, AF, et al. Editorial: back to the future: on the road towards precision psychiatry. Front Psychiatry. 2020;11:112 CrossRefGoogle Scholar
Galecki, P, Mossakowska-Wojcik, J, Talarowska, M. The anti-inflammatory mechanism of antidepressants—SSRIs, SNRIs. Prog Neuro-Psychopharmacol Biol Psychiatry. 2018;80(Pt C):291–294.CrossRefGoogle ScholarPubMed
Hashioka, S, McGeer, PL, Monji, A, et al. Anti-inflammatory effects of antidepressants: possibilities for preventives against Alzheimer’s disease. Cent Nerv Syst Agents Med Chem. 2009;9(1):12–19.CrossRefGoogle ScholarPubMed
Himmerich, H, Bartsch, S, Hamer, H, et al. Modulation of cytokine production by drugs with antiepileptic or mood stabilizer properties in anti-CD3- and anti-Cd40-stimulated blood in vitro. Oxid Med Cell Longevity. 2014;2014:806162. CrossRefGoogle ScholarPubMed
Himmerich, H, Bartsch, S, Hamer, H, et al. Impact of mood stabilizers and antiepileptic drugs on cytokine production in-vitro. J Psychiatric Res. 2013;47(11):1751–1759.CrossRefGoogle ScholarPubMed
Correll, CU, Detraux, J, De Lepeleire, J, et al. Effects of antipsychotics, antidepressants and mood stabilizers on risk for physical diseases in people with schizophrenia, depression and bipolar disorder. World Psychiatry. 2015;14(2):119–136.CrossRefGoogle ScholarPubMed
Wolfers, T, Buitelaar, JK, Beckmann, CF, et al. From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics. Neurosci Biobehav Rev. 2015;57:328–349.CrossRefGoogle ScholarPubMed