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Pre-treatment allostatic load and metabolic dysregulation predict SSRI response in major depressive disorder: a preliminary report

Published online by Cambridge University Press:  22 May 2020

Christina M. Hough Open the ORCID record for Christina M. Hough [Opens in a new window] ,
F. Saverio Bersani ,
Synthia H. Mellon ,
Alexandra E. Morford ,
Daniel Lindqvist ,
Victor I. Reus ,
Elissa S. Epel  and
Owen M. Wolkowitz
Christina M. Hough*
Affiliation:
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USA Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
F. Saverio Bersani
Affiliation:
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USA Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
Synthia H. Mellon
Affiliation:
Department of OB/GYN and Reproductive Sciences, UCSF School of Medicine, San Francisco, CA, USA
Alexandra E. Morford
Affiliation:
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USA Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
Daniel Lindqvist
Affiliation:
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USA Department of Clinical Sciences, Section for Psychiatry, Lund University, Lund, Sweden
Victor I. Reus
Affiliation:
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USA
Elissa S. Epel
Affiliation:
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USA
Owen M. Wolkowitz
Affiliation:
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (UCSF) School of Medicine, San Francisco, CA, USA
*
Author for correspondence: Christina M. Hough, E-mail: cmhough@ucla.edu
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Abstract

Background

Major depressive disorder (MDD) is associated with increased allostatic load (AL; a measure of physiological costs of repeated/chronic stress-responding) and metabolic dysregulation (MetD; a measure of metabolic health and precursor to many medical illnesses). Though AL and MetD are associated with poor somatic health outcomes, little is known regarding their relationship with antidepressant-treatment outcomes.

Methods

We determined pre-treatment AL and MetD in 67 healthy controls and 34 unmedicated, medically healthy MDD subjects. Following this, MDD subjects completed 8-weeks of open-label selective serotonin reuptake inhibitor (SSRI) antidepressant treatment and were categorized as ‘Responders’ (⩾50% improvement in depression severity ratings) or ‘Non-responders’ (<50% improvement). Logistic and linear regressions were performed to determine if pre-treatment AL or MetD scores predicted SSRI-response. Secondary analyses examined cross-sectional differences between MDD and control groups.

Results

Pre-treatment AL and MetD scores significantly predicted continuous antidepressant response (i.e. absolute decreases in depression severity ratings) (p = 0.012 and 0.014, respectively), as well as post-treatment status as a Responder or Non-responder (p = 0.022 and 0.040, respectively), such that higher pre-treatment AL and MetD were associated with poorer SSRI-treatment outcomes. Pre-treatment AL and MetD of Responders were similar to Controls, while those of Non-responders were significantly higher than both Responders (p = 0.025 and 0.033, respectively) and Controls (p = 0.039 and 0.001, respectively).

Conclusions

These preliminary findings suggest that indices of metabolic and hypothalamic-pituitary-adrenal-axis dysregulation are associated with poorer SSRI-treatment response. To our knowledge, this is the first study to demonstrate that these markers of medical disease risk also predict poorer antidepressant outcomes.

Keywords

Allostatic loadantidepressant responsemajor depressive disordermetabolic dysregulationmetabolic syndrometreatment predictiontreatment response
Type
Original Article
Information
Psychological Medicine , Volume 51 , Issue 12 , September 2021 , pp. 2117 - 2125
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press.

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References

Belleau, E. L., Treadway, M. T., & Pizzagalli, D. A. (2019). The impact of stress and major depressive disorder on hippocampal and medial prefrontal cortex morphology. Biological Psychiatry, 85(6), 443–453.CrossRefGoogle ScholarPubMed
Biessels, G. J., & Reagan, L. P. (2015). Hippocampal insulin resistance and cognitive dysfunction. Nature Reviews. Neuroscience, 16(11), 660–671. doi: 10.1038/nrn4019.CrossRefGoogle ScholarPubMed
Bloch, M., Schmidt, P. J., Danaceau, M. A., Adams, L. F., & Rubinow, D. R. (1999). Dehydroepiandrosterone treatment of midlife dysthymia. Biological Psychiatry, 45(12), 1533–1541. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10376113.CrossRefGoogle ScholarPubMed
Bose, M., Oliván, B., & Laferrère, B. (2009). Stress and obesity: The role of the hypothalamic-pituitary-adrenal axis in metabolic disease. Current Opinion in Endocrinology, Diabetes, and Obesity, 16(5), 340–346. doi: 10.1097/MED.0b013e32832fa137.CrossRefGoogle ScholarPubMed
Colle, R., De Larminat, D., Rotenberg, S., Hozer, F., Hardy, P., Verstuyft, C., … Corruble, E. (2017). Pioglitazone could induce remission in major depression: A meta-analysis. Neuropsychiatric Disease and Treatment, 13, 9.CrossRefGoogle ScholarPubMed
Dranovsky, A., & Hen, R. (2006). Hippocampal neurogenesis: Regulation by stress and antidepressants. Biological Psychiatry, 59(12), 1136–1143.CrossRefGoogle Scholar
First, M. B. (1997). Structured clinical interview for DSM-IV axis I disorders. Washington, DC: American Psychiatric Press.Google Scholar
Fischer, S., Macare, C., Cleare, A. J. J. N., & Reviews, B. (2017). Hypothalamic-pituitary-adrenal (HPA) axis functioning as predictor of antidepressant response–meta-analysis. Neuroscience and Biobehavioral Reviews, 83, 200–211.CrossRefGoogle ScholarPubMed
Fitzsimons, C. P., van Hooijdonk, L. W., Morrow, J. A., Peeters, B. W., Hamilton, N., Craighead, M., & Vreugdenhil, E. (2009). Antiglucocorticoids, neurogenesis and depression. Mini Reviews in Medicinal Chemistry, 9(2), 249–264.CrossRefGoogle ScholarPubMed
Furtado, M., & Katzman, M. A. (2015). Examining the role of neuroinflammation in major depression. Psychiatry Research, 229(1), 27–36.CrossRefGoogle ScholarPubMed
Green, E., Goldstein-Piekarski, A. N., Schatzberg, A. F., Rush, A. J., Ma, J., & Williams, L. (2017). Personalizing antidepressant choice by sex, body mass index, and symptom profile: An iSPOT-D report. Personalized Medicine in Psychiatry, 1–2, 65–73. https://doi.org/10.1016/j.pmip.2016.12.001.CrossRefGoogle Scholar
Grundy, S. M., Brewer, H. B., Cleeman, J. I., Smith, S. C., & Lenfant, C. (2004). Definition of metabolic syndrome report of the National Heart, Lung, and Blood Institute/American Heart Association Conference on scientific issues related to definition. Circulation, 109(3), 433–438.CrossRefGoogle ScholarPubMed
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology Neurosurgery & Psychiatry, 23, 56–62. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/14399272.CrossRefGoogle ScholarPubMed
Hough, C. M., Lindqvist, D., Epel, E. S., Denis, M. S., Reus, V. I., Bersani, F. S., … Wolkowitz, O. M. (2017). Higher serum DHEA concentrations before and after SSRI treatment are associated with remission of major depression. Psychoneuroendocrinology, 77, 122–130.CrossRefGoogle ScholarPubMed
Jha, M. K., Wakhlu, S., Dronamraju, N., Minhajuddin, A., Greer, T. L., & Trivedi, M. H. (2018). Validating pre-treatment body mass index as moderator of antidepressant treatment outcomes: Findings from CO-MED trial. Journal of Affective Disorders, 234, 34–37. doi: 10.1016/j.jad.2018.02.089.CrossRefGoogle ScholarPubMed
Lecrubier, Y. (2002). How do you define remission? Acta Psychiatrica Scandinavica, 106(s415), 7–11. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12492767.CrossRefGoogle Scholar
Liu, C. S., Carvalho, A. F., & McIntyre, R. S. (2014). Towards a “metabolic” subtype of major depressive disorder: Shared pathophysiological mechanisms may contribute to cognitive dysfunction. CNS & Neurological Disorders Drug Targets, 13(10), 1693–1707. doi:CNSNDDT-EPUB-63696 [pii].CrossRefGoogle ScholarPubMed
Luppino, F. S., de Wit, L. M., Bouvy, P. F., Stijnen, T., Cuijpers, P., Penninx, B. W., & Zitman, F. G. (2010). Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies. Archives of General Psychiatry, 67(3), 220–229.CrossRefGoogle ScholarPubMed
Makki, K., Froguel, P., & Wolowczuk, I. (2013). Adipose tissue in obesity-related inflammation and insulin resistance: Cells, cytokines, and chemokines. ISRN inflammation, 2013, 1–12.CrossRefGoogle ScholarPubMed
Maninger, N., Wolkowitz, O. M., Reus, V. I., Epel, E. S., & Mellon, S. H. (2009). Neurobiological and neuropsychiatric effects of dehydroepiandrosterone (DHEA) and DHEA sulfate (DHEAS). Frontiers in Neuroendocrinology, 30(1), 65–91. doi: 10.1016/j.yfrne.2008.11.002.CrossRefGoogle Scholar
Marijnissen, R., Vogelzangs, N., Mulder, M., Van Den Brink, R., Comijs, H. C., & Voshaar, R. O. J. P. m. (2017). Metabolic dysregulation and late-life depression: A prospective study. Psychological Medicine, 47(6), 1041–1052.CrossRefGoogle ScholarPubMed
McEwen, B. S. (2000). The neurobiology of stress: From serendipity to clinical relevance. Brain Research, 886(1), 172–189.CrossRefGoogle Scholar
McEwen, B. S. (2001). Plasticity of the hippocampus: Adaptation to chronic stress and allostatic load. Annals of the New York Academy of Sciences, 933(1), 265–277.CrossRefGoogle ScholarPubMed
McEwen, B. S. (2003). Mood disorders and allostatic load. Biological Psychiatry, 54(3), 200–207. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/12893096.CrossRefGoogle ScholarPubMed
McGregor, G., Malekizadeh, Y., & Harvey, J. (2015). Minireview: Food for thought: Regulation of synaptic function by metabolic hormones. Molecular Endocrinology, 29(1), 3–13.CrossRefGoogle ScholarPubMed
McMahon, F. J. (2014). Prediction of treatment outcomes in psychiatry – where do we stand? Dialogues in Clinical Neuroscience, 16(4), 455.Google ScholarPubMed
Mojtabai, R. (2017). Nonremission and time to remission among remitters in major depressive disorder: Revisiting STAR* D. Depression and Anxiety, 34(12), 1123–1133.CrossRefGoogle ScholarPubMed
Mulvahill, J. S., Nicol, G. E., Dixon, D., Lenze, E. J., Karp, J. F., Reynolds, C. F. III, … Mulsant, B. H. (2017). Effect of metabolic syndrome on late-life depression: Associations with disease severity and treatment resistance. Journal of the American Geriatrics Society, 65(12), 2651–2658.CrossRefGoogle ScholarPubMed
Pan, A., Keum, N., Okereke, O. I., Sun, Q., Kivimaki, M., Rubin, R. R., & Hu, F. B. (2012). Bidirectional association between depression and metabolic syndrome: A systematic review and meta-analysis of epidemiological studies. Diabetes Care, 35(5), 1171–1180. doi: 10.2337/dc11-2055.CrossRefGoogle ScholarPubMed
Panel, N. C. E. P. N. E. (2002). Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) final report. Circulation, 106(25), 3143.Google Scholar
Papakostas, G. I., Petersen, T., Sonawalla, S. B., Merens, W., Iosifescu, D. V., Alpert, J. E., … Nierenberg, A. A. (2003). Serum cholesterol in treatment-resistant depression. Neuropsychobiology, 47(3), 146–151. doi:10.1159/000070584.70584 [pii].CrossRefGoogle ScholarPubMed
Peixoto, C., Devicari Cheda, J. N., Nardi, A. E., Veras, A. B., & Cardoso, A. (2014). The effects of dehydroepiandrosterone (DHEA) in the treatment of depression and depressive symptoms in other psychiatric and medical illnesses: A systematic review. Current Drug Targets, 15(9), 901–914. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25039497.CrossRefGoogle ScholarPubMed
Preskorn, S. (2009). Outpatient management of depression (3rd ed.). West Islip, NY: Professional Communications.Google Scholar
Rabkin, J. G., McElhiney, M. C., Rabkin, R., McGrath, P. J., & Ferrando, S. J. (2006). Placebo-controlled trial of dehydroepiandrosterone (DHEA) for treatment of nonmajor depression in patients with HIV/AIDS. American Journal of Psychiatry, 163(1), 59–66. doi: 10.1176/appi.ajp.163.1.59.CrossRefGoogle ScholarPubMed
Raison, C. L., Capuron, L., & Miller, A. H. (2006). Cytokines sing the blues: Inflammation and the pathogenesis of depression. Trends in Immunology, 27(1), 24–31.CrossRefGoogle ScholarPubMed
Rush, A. J., Kraemer, H. C., Sackeim, H. A., Fava, M., Trivedi, M. H., Frank, E., … Kupfer, D. J. (2006). Report by the ACNP Task Force on response and remission in major depressive disorder. Neuropsychopharmacology, 31(9), 1841.CrossRefGoogle ScholarPubMed
Schmidt, P. J., Daly, R. C., Bloch, M., Smith, M. J., Danaceau, M. A., St Clair, L. S., … Rubinow, D. R. (2005). Dehydroepiandrosterone monotherapy in midlife-onset major and minor depression. Archives of General Psychiatry, 62(2), 154–162. doi: 10.1001/archpsyc.62.2.154.CrossRefGoogle ScholarPubMed
Schmidt, H. D., & Duman, R. S. (2007). The role of neurotrophic factors in adult hippocampal neurogenesis, antidepressant treatments and animal models of depressive-like behavior. Behavioural Pharmacology, 18(5–6), 391–418.CrossRefGoogle ScholarPubMed
Seeman, T. E., McEwen, B. S., Rowe, J. W., & Singer, B. H. (2001). Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proceedings of the National Academy of Sciences, 98(8), 4770–4775.CrossRefGoogle ScholarPubMed
Sheline, Y. I., Liston, C., & McEwen, B. S. (2019). Parsing the hippocampus in depression: Chronic stress, hippocampal volume, and major depressive disorder. Biological Psychiatry, 85(6), 436–438.CrossRefGoogle ScholarPubMed
Soczynska, J. K., Kennedy, S. H., Woldeyohannes, H. O., Liauw, S. S., Alsuwaidan, M., Yim, C. Y., & McIntyre, R. S. (2011). Mood disorders and obesity: Understanding inflammation as a pathophysiological nexus. Neuromolecular Medicine, 13(2), 93–116. doi: 10.1007/s12017-010-8140-8.CrossRefGoogle ScholarPubMed
Sonawalla, S. B., Papakostas, G. I., Petersen, T. J., Yeung, A. S., Smith, M. M., Sickinger, A. H., … Fava, M. (2002). Elevated cholesterol levels associated with nonresponse to fluoxetine treatment in major depressive disorder. Psychosomatics, 43(4), 310–316. doi: S0033-3182(02)70385-X [pii] doi: 10.1176/appi.psy.43.4.310.CrossRefGoogle ScholarPubMed
Trivedi, M. H., Rush, A. J., Wisniewski, S. R., Nierenberg, A. A., Warden, D., Ritz, L., … Team, S. D. S. (2006). Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: Implications for clinical practice. American Journal of Psychiatry, 163(1), 28–40. doi: 10.1176/appi.ajp.163.1.28.CrossRefGoogle ScholarPubMed
Vancampfort, D., Correll, C. U., Wampers, M., Sienaert, P., Mitchell, A., De Herdt, A., … De Hert, M. (2014). Metabolic syndrome and metabolic abnormalities in patients with major depressive disorder: A meta-analysis of prevalences and moderating variables. Psychological Medicine, 44(10), 2017–2028.CrossRefGoogle ScholarPubMed
Van Doorn, C., Macht, V. A., Grillo, C. A., & Reagan, L. P. (2017). Leptin resistance and hippocampal behavioral deficits. Physiology & Behavior, 176, 207–213. doi: 10.1016/j.physbeh.2017.03.002.CrossRefGoogle ScholarPubMed
Virtanen, M., Ferrie, J. E., Akbaraly, T., Tabak, A., Jokela, M., Ebmeier, K. P., … Kivimäki, M. (2017). Metabolic syndrome and symptom resolution in depression: A 5-year follow-up of older adults. Journal of Clinical Psychiatry, 78(1), e1–e7.CrossRefGoogle ScholarPubMed
Vogelzangs, N., Beekman, A., Boelhouwer, I. G., Bandinelli, S., Milaneschi, Y., Ferrucci, L., & Penninx, B. (2011). Metabolic depression: A chronic depressive subtype? Findings from the InCHIANTI study of older persons. The Journal of Clinical Psychiatry, 72(5), 598–604.CrossRefGoogle ScholarPubMed
Vogelzangs, N., Beekman, A. T., van Reedt Dortland, A. K., Schoevers, R. A., Giltay, E. J., De Jonge, P., & Penninx, B. W. (2014). Inflammatory and metabolic dysregulation and the 2-year course of depressive disorders in antidepressant users. Neuropsychopharmacology, 39(7), 1624–1634.CrossRefGoogle ScholarPubMed
Walker, E. R., McGee, R. E., & Druss, B. G. (2015). Mortality in mental disorders and global disease burden implications: A systematic review and meta-analysis. JAMA Psychiatry, 72(4), 334–341.CrossRefGoogle Scholar
Wolkowitz, O. M., Reus, V. I., Keebler, A., Nelson, N., Friedland, M., Brizendine, L., & Roberts, E. (1999). Double-blind treatment of major depression with dehydroepiandrosterone. American Journal of Psychiatry, 156(4), 646–649. doi: 10.1176/ajp.156.4.646.Google Scholar
Wolkowitz, O. M., Reus, V. I., & Mellon, S. H. (2011). Of sound mind and body: Depression, disease, and accelerated aging. Dialogues in Clinical Neuroscience, 13(1), 25–39. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21485744.Google Scholar
Wolkowitz, O. M., Reus, V. I., Roberts, E., Manfredi, F., Chan, T., Raum, W. J., … Weingartner, H. (1997). Dehydroepiandrosterone (DHEA) treatment of depression. Biological Psychiatry, 41(3), 311–318. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9024954.CrossRefGoogle ScholarPubMed
Woo, Y. S., McIntyre, R. S., Kim, J.-B., Lee, M.-S., Kim, J.-M., Yim, H. W., & Jun, T.-Y. (2016). Association of treatment response with obesity and other metabolic risk factors in adults with depressive disorders: Results from a National Depression Cohort study in Korea (the CRESCEND study). Journal of Affective Disorders, 203, 190–198.CrossRefGoogle Scholar
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