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A Blood Test for Depression?

Anthony J. Rothschild, MD

Published: February 25, 2015

See Article by Bilello et al and Rejoinder by Papakostas.

This work may not be copied, distributed, displayed, published, reproduced, transmitted, modified, posted, sold, licensed, or used for commercial purposes. By downloading this file, you are agreeing to the publisher’s Terms & Conditions.

A Blood Test for Depression?

In the early 1980s after publication of Dr Bernard Carroll’s seminal paper standardizing the dexamethasone suppression test (DST) for melancholia (endogenous depression),1 the popular media ran headlines proclaiming that a blood test had been discovered for depression. Approximately 6 years later, the clinical utility of the DST in everyday practice was determined to be limited.2 The excitement over a simple blood test to diagnose depression launched the research careers of many young psychiatrists, including this author. In this issue of the Journal, Bilello and colleagues3 report on a panel consisting of 9 biomarkers associated with the neurotrophic, metabolic, inflammatory, and hypothalamic-pituitary-adrenal axis pathways that, along with gender and body mass index (BMI) data, was able to identify people with major depressive disorder (MDD) with an accuracy of over 90%. The theoretical basis for this commercial test is that the 9 biomarkers in the panel are associated with alterations in key pathways associated with unipolar depression.4-10

Having been down this path before, as a clinician and researcher, I would urge caution about embracing the utility of a blood test for depression for several reasons.

Bilello and colleagues3 report excellent sensitivity and specificity of their test for MDD and have replicated a previous study4 that used the same panel without including gender and BMI as variables. In the earlier study, the panel and associated algorithm produced good clinical sensitivity and specificity (92% and 81%, respectively) in differentiating MDD patients from normal healthy individuals. However, a notable limitation in both studies is that the sample size is not large. As a means of comparison, the 2013 study by Papakostas et al4 had a sample size of 36 MDD patients and 43 nondepressed controls, and the Bilello et al study3 had 68 MDD patients and 86 nondepressed controls, while the 1981 Carroll et al study2 had 215 patients with a diagnosis of melancholia, 100 patients with nonendogenous depression, and 70 nondepressed controls.

Apart from the methodological questions, it is important that the clinical application be thoughtfully weighed by both practitioners and researchers. What does this blood test for MDD add to the diagnosis and treatment of patients? In the study, the patients already met criteria for MDD, so what does the test add? The authors state that it is not a screening test, so what is it? Is the test better than the diagnostic acumen of a board-certified psychiatrist or other mental health professional using well-studied DSM-511 criteria for MDD? According to the website of Ridge Diagnostics, Inc, which provides the test, the test costs $800.12 Is this cost-effective? What information, if any, does this $800 add that has not been already obtained from the trained mental health professional?

A testimonial on the company website13 from a psychiatrist states that the test might be used by family practice physicians who are not as well-trained as psychiatrists to diagnose MDD. While the basis for this statement is not clear (family practice residencies do include training in diagnosing MDD), there are better, less costly models for diagnosing MDD in the general practice setting, such as integrated collaborative care.13

Back in the 1980s, the argument was made by Carroll and others that MDD was too heterogeneous a category to be useful for the study of biomarkers.14 Having a biomarker for MDD is like having a biomarker for all cancers, regardless of tissue source. Carroll originally focused on the use of the DST in the more narrow subtype of melancholia (endogenous depression), while others focused on other narrow subtypes of depression, such as psychotic depression.15 Given the broad nature of MDD, which most likely includes patients with many diverse etiologies, it would be of interest to apply this biomarker panel to more narrow subtypes such as melancholia or psychotic depression, or even other criteria such as the Research Domain Criteria,16 with a focus on constructs under the “negative valence systems” domain (acute threat, potential threat, sustained threat, loss, and frustrative nonreward).17

What would be helpful for clinicians is a biomarker test with results that would convert to those seen in a normal control as the patient improves or, even better, convert before the changes are clinically noticeable in the depressed patient, as had been reported with the DST.18 Could this test measure the risk for developing MDD in never-depressed individuals or in the family members of people who have suffered from MDD? Could the test differentiate patients with MDD from patients in the depressed phase of bipolar disorder? Could the test point toward the use of particular somatic treatments, as has been reported with inflammatory biomarkers19 or pharmacogenomics?20

In summary, the study by Bilello and colleagues3 presents a potential serum-based biologic diagnostic test for MDD. What remains unclear is whether the test provides added value for the diagnosis of MDD above and beyond what a trained clinician can do without the test. If the test could provide answers to questions about the patient that are not already known by the trained clinician (eg, predict whether the patient is responding to the treatment before it is clinically noticeable or predict risk in nondepressed patients), then there would be added value for the care and treatment of MDD. Although we are not there yet, hopefully that day is coming soon.

Author affiliations: University of Massachusetts Medical School and UMass Memorial Health Care, Worcester.

Potential conflicts of interest: Dr Rothschild has been a consultant for Allergan, Eli Lilly, GlaxoSmithKline, Noven, Omnicare, and Pfizer; has received grant/research support from Alkermes, AssureRx, Cyberonics, National Institute of Mental Health, and St Jude Medical; and has received royalties for the Rothschild Scale for Antidepressant Tachyphylaxis (RSAT)™ and from American Psychiatric Press.

Funding/support: None reported.


1. Carroll BJ, Feinberg M, Greden JF, et al. A specific laboratory test for the diagnosis of melancholia: standardization, validation, and clinical utility. Arch Gen Psychiatry. 1981;38(1):15-22. PubMed doi:10.1001/archpsyc.1981.01780260017001

2. The APA Task Force on Laboratory Tests in Psychiatry. The dexamethasone suppression test: an overview of its current status in psychiatry. Am J Psychiatry. 1987;144(10):1253-1262. PubMed

3. Bilello JA, Thurmond LM, Smith KM, et al. MDDScore: confirmation of a blood test to aid in the diagnosis of major depressive disorder. J Clin Psychiatry. 2015;76(2):e199-e206.

4. Papakostas GI, Shelton RC, Kinrys G, et al. Assessment of a multi-assay, serum-based biological diagnostic test for major depressive disorder: a pilot and replication study. Mol Psychiatry. 2013;18(3):332-339. PubMed doi:10.1038/mp.2011.166

5. Smith KM, Renshaw PF, Bilello JA. The diagnosis of depression: current and emerging methods. Compr Psychiatry. 2013;54(1):1-6. PubMed doi:10.1016/j.comppsych.2012.06.006

6. Shelton RC. The molecular neurobiology of depression. Psychiatr Clin North Am. 2007;30(1):1-11. PubMed doi:10.1016/j.psc.2006.12.005

7. Kenis G, Maes M. Effects of antidepressants on the production of cytokines. Int J Neuropsychopharmacol. 2002;5(4):401-412. PubMed doi:10.1017/S1461145702003164

8. Maes M. Major depression and activation of the inflammatory response system. In: Dantzer R, Wollman EE, Yirmiya R, eds. Cytokines, Stress and Depression. New York, NY: Kluwer Academic/Plenum Publishers; 1999:25-46. doi:10.1007/978-0-585-37970-8_2

9. Zhu CB, Blakely RD, Hewlett WA. The proinflammatory cytokines interleukin-1beta and tumor necrosis factor-alpha activate serotonin transporters. Neuropsychopharmacology. 2006;31(10):2121-2131. PubMed

10. Tichomirowa MA, Keck ME, Schneider HJ, et al. Endocrine disturbances in depression. J Endocrinol Invest. 2005;28(3):89-99. PubMed doi:10.1007/BF03345535

11. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Washington, DC: American Psychiatric Press, Inc; 2013.

12. Ridge Diagnostics. Accessed September 10, 2014.

13. Cerimele JM, Katon WJ, Sharma V, et al. Delivering psychiatric services in primary-care setting. Mt Sinai J Med. 2012;79(4):481-489. PubMed doi:10.1002/msj.21324

14. Carroll BJ, Feinberg M, Greden JF, et al. Diagnosis of endogenous depression: comparison of clinical, research and neuroendocrine criteria. J Affect Disord. 1980;2(3):177-194. PubMed doi:10.1016/0165-0327(80)90004-X

15. Rothschild AJ, Schatzberg AF, Rosenbaum AH, et al. The dexamethasone suppression test as a discriminator among subtypes of psychotic patients. Br J Psychiatry. 1982;141(5):471-474. PubMed doi:10.1192/bjp.141.5.471

16. Insel T, Cuthbert B, Garvey M, et al. Research Domain Criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry. 2010;167(7):748-751. PubMed doi:10.1176/appi.ajp.2010.09091379

17. Ostergaard SD, Fava M, Rothschild AJ, et al. The implications of the National Institute of Mental Health Research Domain Criteria for researchers and clinicians. Acta Psychiatr Scand. 2014;130(6):409-414. PubMed doi:10.1111/acps.12331

18. Rothschild AJ, Schatzberg AF. Fluctuating postdexamethasone cortisol levels in a patient with melancholia. Am J Psychiatry. 1982;139(1):129-130. PubMed

19. Uher R, Tansey KE, Dew T, et al. An inflammatory biomarker as a differential predictor of outcome of depression treatment with escitalopram and nortriptyline [published online ahead of print July 14, 2014]. Am J Psychiatry. PubMed doi:10.1176/appi.ajp.2014.14010094

20. Winner J, Allen JD, Altar CA, et al. Psychiatric pharmacogenomics predicts health resource utilization of outpatients with anxiety and depression. Transl Psychiatry. 2013;3(3):e242. PubMed doi:10.1038/tp.2013.2

Submitted: September 15, 2014; accepted September 15, 2014.

Corresponding author: Anthony J. Rothschild, MD, Department of Psychiatry, University of Massachusetts Medical School and UMass Memorial Health Care, 55 Lake Ave N, Worcester, MA 01655 (

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